Innate Immune Pathways in the Draining Lymph Node

James Arrich

University College London (UCL)

Division of Medicine Centre for Clinical Pharmacology Rayne Institute London

This thesis is submitted for the degree of Doctor of Philosophy

2020

Declaration

I, James Arrich confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis.

Chester, July 2020

Abstract

The draining lymph node (dLN) is the anatomical site in which adaptive immune responses are initiated following vaccination. It is increasingly recognised that the dLN also serves an important innate barrier function and that inflammatory stimuli (including vaccine adjuvants) drive cardinal aspects of the innate immune response within the dLN. The characterisation of these intranodal innate immune processes and their impact upon the concurrently developing adaptive immune response is therefore central to the design of novel vaccines and adjuvants.

Neutrophil and monocyte infiltration is a cardinal feature of the innate immune response. This phenomenon is studied within the dLN in the context of two key innate immune pathways; cyclooxygenase-dependent prostanoids and type I interferons. These processes were studied using a murine skin immunisation model following challenge with killed E. coli (KEC), which induced the rapid and sequential infiltration of neutrophils and monocytes into the dLN. These infiltrating myeloid cells were major expressers of cardinal prostanoid synthases (cyclooxygenase-2, microsomal PGE synthase-1 and thromboxane synthase), as well as important interferon-stimulated genes such as CXCL9 and CXCL10. Notably, cyclooxygenase inhibition during their infiltration did not modulate the developing humoral immune response. In contrast, type 1 interferons drove the differential upregulation of CD69 by different lymphocyte subsets and the acute production of interferon-γ by dLN NK cells; processes that play important roles in the retention and activation of T cells. In vitro evidence suggests that these processes are driven by interferon-stimulated monocytes, a hypothesis supported by the markedly increased expression of type I interferon stimulated genes by dLN monocytes in vivo.

In conclusion, this thesis highlights the role of infiltrating myeloid cells as unappreciated orchestrators of type I interferon-driven innate immune pathways in the dLN. This finding informs hypotheses that assert that inflammatory monocytes drive Th1 T cell responses in the dLN.

Impact Statement

The field of vaccine research has rarely seemed more pertinent than in the light of the COVID- 19 pandemic. This thesis contributes to this crucial field as it presents data that informs vaccine adjuvant design. Adjuvants serve to increase the immunogenicity of the antigen(s) within a vaccine formulation. However, until recently, adjuvant design was a relatively neglected field of research, with only two adjuvants currently listed in the UK immunisation regimen. It is increasingly recognised that adjuvants work in part by engaging the innate immune system directly within the draining lymph node (dLN). It is by characterising and delineating these intranodal innate immune pathways that this thesis contributes to this expanding field.

This thesis demonstrates that neutrophils and monocytes (both key effector cells of the innate immune system) infiltrate the dLN in large numbers following a murine skin challenge with killed E. coli bacteria (KEC). Moreover, these infiltrating myeloid cells demonstrated markedly elevated expression of genes that drive the innate immune response, including synthases that manufacture inflammatory prostanoids and a range of type 1 interferon-stimulated genes (ISGs). Type 1 interferons were shown to play important roles in driving the differential upregulation of CD69 by different lymphocyte subsets as well as inducing the production of IFNγ by NK cells. These processes are important for the retention and activation of T cells within the dLN. The fact that monocytes in particular are major expressers of ISGs suggests that monocytes orchestrate these processes within the dLN. This thesis therefore highlights interferon-activated monocytes as key cells that potentially orchestrate the induction of T cell responses and are thus an important target for future adjuvant research. Indeed, this thesis poses several hypotheses that address how monocytes may mediate such a function and sets out the methods by which these hypotheses could be tested. Moreover, efforts have been made to disseminate the findings of this thesis to the wider scientific community. In this regard, data from this thesis has been presented at both university and national conferences in poster format (the British Society of Immunology Congress 2017 and the UCL Division of Medicine Conference 2018) and is planned to be submitted for publication in peer-reviewed academic journals.

Finally, the fact that the aforementioned processes are studied in the context of a challenge with KEC is also of wider significance. Laboratories within the UCL Division of Medicine have pioneered the use of KEC to study acute inflammation in the skin of healthy human volunteers. The intradermal murine immunisation model established in this thesis therefore provides a platform that can be readily adopted to undertake parallel studies of this inflammatory

stimulus in humans and mice. Furthermore, this thesis demonstrates that aspects of the innate immune response to KEC mirror that of novel TLR4-agonist adjuvants such as AS01 and GLA-SE. The direct comparison of KEC with these adjuvants in mice and/or humans may therefore reveal important differences in the immune response that could inform future adjuvant design.

Acknowledgements

I would like to express sincere thanks and gratitude to my supervisor Professor Derek Gilroy for providing me with continuous guidance and feedback throughout the project. I would also like to thank my secondary supervisor Professor Arne Akbar and my tutors in the MBPhD programme (Professor Raymond MacAllister, Professor Robert Unwin and Dr Daniel Marks) for their advice and support at times of concern.

I would like to thank Dr Andreas Wack for the provision of IFNAR-deficient mice and guidance with regard to the study of type I interferons, and Dr Mark Coles for sharing data that informed experiments conducted in this thesis.

To all members of the Gilroy lab (past and present), it has been a joy to work with you over the past 6 years and I would like to thank you all for your guidance, support and friendship. I would like to thank Dr Justine Newson for her patience when teaching me the practical side of biomedical research and Dr Roel De Maeyer for continually challenging my assumptions with a kind but critical ear. Finally, I would like to especially thank Dr Rachel Van de Merwe, you went the extra mile when you saw I was struggling.

Specific thanks must also be extended to Dr Pascal Durrenberger and David Pearce for teaching me how to perform immunohistochemistry as well as Dr Helina-Elaine Marshall, Dr Meera Mehta and Dr Gabriel Pollara for microbiological guidance. Similarly, I would like to thank all staff at the KLB biological services unit for always doing their best to facilitate my animal work and safeguard the welfare of the mice I was privileged to use for my research.

Thanks to all my beloved family and friends for their support. Thanks to my aunt Ellen McVey, uncle Kevin Murphy and my friends Dr Louise China, Jonathan Johnson and Emma McFadden for letting me stay with them when I needed to undertake my final experiments.

Special thanks to my graduate tutor Dr David Sattelle and my friend Dr Benjamin Bennett for their feedback, advice and guidance with regard to the resubmitted version of this thesis.

Finally, I would like to thank the MBPhD programme for giving me the opportunity and funding to study for a PhD, it has been an incredible privilege.

Explanation of Acronyms and Abbreviations

2-ME 2-Mercaptoethanol

AIM2 Absent in Melanoma 2

AP-1 Activator Protein 1

APRIL A Proliferation Inducing Ligand

BAFF B cell Activating Factor

BCA Bicinchoninic Acid

BCG Bacillus Calmette-Guerin

BCR B Cell Receptor

BSA Bovine Serum Albumin

CD11b-ve CD11b-Negative Cells cDC Conventional Dendritic Cell. Type 1 = cDC1, type 2 = cDC2 cDNA Complementary DNA

CFA Complete Freund’s Adjuvant

CFU Colony Forming Unit

CLEC2 C-type Lectin-like receptor 2

CNS Conserved Non-coding Sequence

Con Contralateral

Contra Contralateral

COX Cyclooxygenase

CpG C-phosphate-G Nucleotides

CREB cAMP Response Element Binding Protein

Ct Cycle Threshold

CTRL Control – refers to either (1) the ipsilateral superficial parotid lymph nodes of mice injected with appropriate control diluent, (2) the collective term to refer to contralateral, inguinal and control lymph nodes or (3) cell suspensions not exposed to inflammatory stimuli in vitro. Please see figure legends.

DAB Diaminobenzidine

DC Dendritic Cell dLN Draining Lymph Node

DMSO Dimethyl Sulphoxide

DNA Deoxyribonucleic Acid dNTP Deoxyribonucleotide Triphosphates

EDTA Ethylenediaminetetraacetic acid

EGR Early Growth Response Transcription Factors

ELISA Enzyme-Linked Immunosorbent Assay

ELISPOT Enzyme-Linked Immunospot

FACS Fluorescence-Activated Cell Sorting

FBS Fetal Bovine Serum

FDC Follicular Dendritic Cell

FLICA Fluorochrome-Labelled Inhibitor of Caspase 1

FMO Fluorescence Minus One Control

FRC Fibroblastic Reticular Cell

FSC-A Forward Scatter Area

GC Germinal Centre

GFP Green Fluorescent Protein

GLA-SE Glucopyranosyl Lipid Adjuvant Formulated in a Stable Emulsion

HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid

HEV High Endothelial Venule

HKEC Heat-killed E. coli hr Hour

HSV Herpes Simplex Virus i.p. Intraperitoneal

IFNAR Interferon α/β Receptor

IFNα Interferon-alpha

IFNβ Interferon-beta 8

IFNγ Interferon-gamma

IFZ Interfollicular Zone

IHC Immunohistochemistry

ILC Innate Lymphoid Cell

Imm Immunised

IMS Industrial Methylated Sprits

Indo Indomethacin

Ipsi Ipsilateral

IRF Interferon Regulatory Factor

ISG Interferon-Stimulated Gene

JAK Janus Kinase

KEC Killed E. coli (either heat or UV-killed)

KEC-Draining Lymph Node The ipsilateral superficial parotid lymph node that drains the murine earflap following intradermal injection of KEC. HKEC- draining lymph node is synonymous.

KO Knockout (refers to IFNAR-deficient mice)

LAT1 Large Neutral Amino Acid Transporter 1

LCMV Lymphocytic Choriomeningitis Virus

LFA-1 Lymphocyte Function-Associated Antigen 1

LIGHT Lymphotoxin-like, exhibits inducible expression and competes with HSV glycoprotein D for binding to herpesvirus entry mediator, a receptor expressed on T lymphocytes

LN Lymph Node

LPA Lysophosphatidic Acid

LPS Lipopolysaccharide

LYVE-1 Lymphatic Vessel Endothelial Hyaluronan Receptor 1

MALT Mucosa-Associated Lymphoid Tissue

MHC II Major Histocompatibility Complex 2

Mig DC Migratory Dendritic Cell

MMLV Moloney Murine Leukaemia Virus

Mono Monocyte mPGES-1 Microsomal Prostaglandin E Synthase 1

MRC Marginal Reticular Cell

MRI Magnetic Resonance Imaging mRNA Messenger RNA

MSMD Mendelian Susceptibility to Mycobacterial Disease mTOR Molecular Target of Rapamycin

MVA Modified Vaccinia Virus Ankara

MyD88 Myeloid Differentiation Primary Response 88 ndLN Non-Draining Lymph Node

Neut Neutrophil

NFκB Nuclear Factor Kappa B

NK Cell Natural Killer cell

NKT cell Natural Killer T cell

NLR NOD-Like Receptor

NLRP3 NLR family pyrin domain containing 3

NO RT No Reverse Transcriptase Control

NSAIDS Non-Steroidal Anti-Inflammatory Drugs

OCT (Immunohistochemistry) Optimum Cutting Temperature Compound

OCT (Transcription Factor) Octamer Transcription Factor

OD Optical Density

Other CD11b-positive cells that are neither neutrophils or monocytes

OVA-A647 Ovalbumin Alexa Fluor 647 p.o. Per Os (administered by oral gavage)

PAMP Pathogen Associated Molecular Pattern

PBS Phosphate-Buffered Saline

PCR Polymerase Chain Reaction

PFA Paraformaldehyde

PGE2 Prostaglandin E2

PMA Phorbol Myristate Acetate

PNAd Peripheral Node Addressin

PPD Purified Protein Derivative

PRR Pattern Recognition Receptor

PVC Perivascular Channel qRT-PCR Quantitative Reverse Transcription Polymerase Chain Reaction

RCT Randomised Controlled Trial

RNA Ribonucleic Acid

RT Reverse Transcriptase

S1P Sphingosine-1-Phospate

S1PR1 Sphingosine-1-Phosphate Receptor 1

SCS Subcapsular Sinus

SLO Secondary Lymphoid Organ

SPL Spleen or splenic

SSI Statens Serum Institut (manufacturer of vaccine-grade BCG)

STAT Signal Transducer and Activator of Transcription

TBXA2 Thromboxane A2

TBXAS Thromboxane A Synthase

TCR T Cell Receptor

TLR Toll-Like Receptor

TNFα Tumour Necrosis Factor-Alpha

TRM T cell Tissue Resident Memory T cell

UV Ultraviolet Light

UVKEC UV-Killed E. coli

VSV Vesicular Stomatitis Virus

WT Wild-Type

γδ T cell Gamma-Delta T cell

Table of Contents

Declaration ...... 2

Abstract ...... 3

Impact Statement ...... 4

Acknowledgements ...... 6

Explanation of Acronyms and Abbreviations ...... 7

Table of Contents ...... 12

Table of Figures ...... 22

Table of Tables ...... 26

1 Introduction ...... 27

1.1 Vaccines ...... 27 1.1.1 History of vaccines...... 27 1.1.2 Vaccine challenges ...... 29 1.2 Initiation of adaptive immune responses ...... 30 1.2.1 Lymph node anatomy ...... 31 1.2.1.1 Parenchyma ...... 32 1.2.1.1.1 Cortex ...... 32 1.2.1.1.2 Medulla ...... 33 1.2.1.1.3 Lymphatic sinuses...... 34 1.2.1.1.3.1 Lymphatic endothelial cells ...... 34 1.2.1.1.4 Vasculature ...... 35 1.2.1.2 Lymph node stromal cells ...... 35 1.2.1.2.1 Fibroblastic reticular cells ...... 35 1.2.1.2.2 Follicular dendritic cells ...... 36 1.2.1.2.3 Marginal reticular cells ...... 36 1.2.1.2.4 The lymph node conduit system ...... 37 1.2.2 Lymphocyte recirculation ...... 39 1.2.2.1 Lymphocyte entry ...... 39 1.2.2.1.1 High endothelial venules ...... 39 1.2.2.1.2 Afferent lymphatics ...... 40 1.2.2.2 Intranodal lymphocyte migration and motility ...... 41 1.2.2.2.1 Intranodal migration ...... 41 1.2.2.2.2 Intranodal motility ...... 41 12

1.2.2.2.2.1 T cells ...... 41 1.2.2.2.2.2 B cells...... 41 1.2.2.3 Lymphocyte egress ...... 42 1.2.2.4 Regulation of lymphocyte recirculation ...... 43 1.2.3 Trafficking and distribution of antigen in the draining lymph node ...... 44 1.2.3.1 Lymph-borne antigen ...... 44 1.2.3.1.1 Determinants of lymphatic antigen drainage ...... 44 1.2.3.1.2 Distribution of lymph-borne antigen within the draining lymph node ..... 44 1.2.3.2 Cellular trafficking of antigen ...... 46 1.2.3.2.1 Dendritic cells ...... 46 1.2.3.2.2 Dendritic cell classification ...... 46 1.2.3.2.3 Dendritic cell trafficking ...... 46 1.2.3.2.4 Neutrophils and monocytes ...... 47 1.2.4 Activation of lymphocytes in the draining lymph node ...... 47 1.2.4.1 B cells...... 47 1.2.4.2 T cells ...... 48 1.2.4.2.1 Dynamics of T cell activation ...... 48 1.2.4.2.2 Anatomy of T cell activation ...... 49 1.2.4.2.3 T cell differentiation ...... 49 1.3 Adjuvants and innate immune pathways in the draining lymph node ...... 51 1.3.1 Adjuvants...... 51 1.3.1.1 Adjuvant mechanisms ...... 52 1.3.1.1.1 Common features ...... 52 1.3.1.1.2 Differentiating features ...... 53 1.3.1.2 Outstanding questions for adjuvant research ...... 54 1.3.2 Innate immune pathways in the draining lymph node ...... 59 1.3.2.1 Innate immune pathways within afferent lymph ...... 59 1.3.2.2 Lymph node hypertrophy ...... 60 1.3.2.3 Lymph node resident macrophages ...... 62 1.3.2.4 Natural killer cells ...... 63 1.3.2.5 Innate lymphoid cells...... 63 1.3.2.6 Natural killer T cells ...... 64 1.3.2.7 Memory CD8 T cells ...... 64 1.3.2.8 Cytokines and chemokines in the draining lymph node ...... 65 1.3.2.8.1 Sources of cytokines and chemokines in the draining lymph node ...... 65

1.3.2.8.2 Distribution of cytokines and chemokines in the draining lymph node .... 66 1.3.2.8.3 Functions of cytokines and chemokines in the draining lymph node ...... 66 1.3.3 Neutrophils and monocytes in the draining lymph node ...... 67 1.3.3.1 Neutrophils in the draining lymph node ...... 67 1.3.3.1.1 Determinants of neutrophil infiltration into the draining lymph node ..... 67 1.3.3.1.2 Mechanisms of neutrophil infiltration into the draining lymph node ...... 68 1.3.3.1.3 Functions of neutrophils in the draining lymph node ...... 69 1.3.3.1.3.1 Innate immunity ...... 69 1.3.3.1.3.2 Adaptive immunity ...... 69 1.3.3.2 Inflammatory monocytes in the draining lymph node ...... 70 1.3.3.2.1 Definition and differentiation of monocytes in the draining lymph node 70 1.3.3.2.2 Mechanisms of inflammatory monocyte infiltration into the draining lymph node ...... 71 1.3.3.2.3 Functions of inflammatory monocytes in the draining lymph node ...... 72 1.4 Summary and aims ...... 75 1.4.1 Aims ...... 76 2 Materials and Methods ...... 77

2.1 Materials ...... 77 2.1.1 General reagents ...... 77 2.1.2 Formulations ...... 78 2.1.3 Antibodies ...... 79 2.1.4 Primer sequences ...... 81 2.2 Methods ...... 83 2.2.1 Animal procedures ...... 83 2.2.1.1 Mice ...... 83 2.2.1.2 Murine earflap injection ...... 88 2.2.1.2.1 BCG Statens Serum Institut (SSI)...... 88 2.2.1.2.2 BCG Pasteur ...... 88 2.2.1.2.3 Fluorescent E. coli bioparticles ...... 89 2.2.1.2.4 Ovalbumin A647: alum ...... 89 2.2.1.2.5 UV-killed E. coli (UVKEC) ...... 89 2.2.1.2.6 Heat-killed E. coli (HKEC) ...... 89 2.2.1.3 Indomethacin: rationale, preparation and oral gavage ...... 89 2.2.2 Tissue collection and processing ...... 90 2.2.2.1 Identification of the cervical lymph node draining the murine earflap ...... 90

2.2.2.2 Peritoneal washout ...... 90 2.2.2.3 Plasma ...... 91 2.2.2.4 Generation of single-cell suspensions ...... 91 2.2.2.4.1 Lymph nodes ...... 91 2.2.2.4.1.1 Mechanical disaggregation ...... 92 2.2.2.4.1.2 Digestion...... 93 2.2.2.4.2 Spleens ...... 93 2.2.2.5 Cell enumeration ...... 98 2.2.3 Bacteria ...... 98 2.2.3.1 E. coli culture ...... 98 2.2.3.2 E. coli killing ...... 99 2.2.3.3 Whole-Cell E. coli antibody ELISA ...... 100 2.2.4 Cell culture and stimulation...... 101 2.2.4.1 BCG recall assays ...... 101 2.2.4.2 IFNγ ELISPOT ...... 101 2.2.4.3 Intracellular cytokine staining ...... 102 2.2.4.4 In vitro stimulation of lymph node and spleen cells ...... 102 2.2.4.5 Chemotaxis assays ...... 103 2.2.4.6 RAW 264.7 cell culture and stimulation ...... 104 2.2.5 Flow Cytometry and fluorescence-activated cell sorting (FACS) ...... 106 2.2.5.1 Flow cytometry ...... 106 2.2.5.1.1 Extracellular staining ...... 106 2.2.5.1.2 Intracellular staining ...... 106 2.2.5.1.3 Analysis ...... 107 2.2.5.1.4 Measurement of CD69 expression by flow cytometry ...... 111 2.2.5.2 Fluorescence-activated cell sorting (FACS) ...... 111 2.2.6 RNA extraction and analysis ...... 112 2.2.6.1 RNA extraction ...... 112 2.2.6.2 Reverse transcription ...... 114 2.2.6.3 End-point polymerase chain reaction ...... 114 2.2.6.4 Real-time polymerase chain reaction ...... 115 2.2.6.5 Analysis of real-time PCR data ...... 116 2.2.6.6 Primer design and validation ...... 116 2.2.7 Immunohistochemistry ...... 117 2.2.7.1 Paraffin infiltration of tissue ...... 117

2.2.7.2 Sectioning of paraffin-embedded tissue ...... 118 2.2.7.3 Immunohistochemical staining ...... 118 2.2.8 Statistical analysis and sample size determination ...... 120 3 Investigations of Neutrophil and Monocyte Infiltration into the Draining Lymph Node 121

3.1 Abstract ...... 121 3.2 Introduction ...... 122 3.2.1 Bacillus Calmette-Guerin (BCG) ...... 122 3.2.2 BCG vaccine efficacy ...... 122 3.2.3 Mechanisms of BCG-mediated protection against tuberculosis ...... 123 3.2.4 Killed E. coli (KEC) ...... 124 3.2.5 The murine earflap immunisation model ...... 125 3.2.6 Summary ...... 125 3.2.7 Aims ...... 126 3.3 Results ...... 127 3.3.1 The ipsilateral superficial parotid lymph node drains the murine earflap ...... 127 3.3.2 Labelled E. coli bioparticles elicit neutrophil infiltration into the draining lymph node 129 3.3.3 Skin injection of BCG does not elicit a marked neutrophil influx into the draining lymph node ...... 129 3.3.4 Skin injection of BCG reliably induces a T cell response but also occasionally induces lymphadenopathy ...... 133 3.3.5 Skin injection of killed E. coli induces acute neutrophil infiltration into the draining lymph node ...... 135 3.3.6 Neutrophils are predominantly localised in peripheral regions of the draining lymph node ...... 137 3.3.7 Skin injection of killed E. coli induces acute CD69 upregulation by lymphocytes in the draining lymph node ...... 137 3.3.8 Ly6Chi monocytes infiltrate the draining lymph node following skin injection of killed E. coli (KEC) ...... 139 3.3.9 Neutrophil infiltration precedes monocyte infiltration in the draining lymph node 142 3.4 Discussion...... 146 3.4.1 The murine earflap immunisation model ...... 146 3.4.2 Bacillus Calmette-Guerin (BCG) ...... 147 3.4.3 Killed E. coli...... 148 3.4.4 Neutrophil and monocyte infiltration into the draining lymph node ...... 149

3.4.4.1 Kinetics of neutrophil and monocyte infiltration ...... 149 3.4.4.2 Determinants of neutrophil and monocyte infiltration ...... 149 3.4.5 Summary and conclusions ...... 151 4 Investigations of Prostanoid Synthases in the Draining Lymph Node ...... 152

4.1 Abstract ...... 152 4.2 Introduction ...... 153 4.2.1 Prostanoids ...... 153 4.2.2 Cyclooxygenases ...... 155 4.2.3 Cyclooxygenase inhibitors ...... 156

4.2.4 Prostaglandin E2 ...... 156

4.2.5 Thromboxane A2 ...... 157 4.2.6 Prostanoid production in the draining lymph node ...... 158 4.2.7 Prostanoids and developing adaptive immune responses ...... 159 4.2.8 Prostanoid functions within the draining lymph node ...... 161 4.2.9 Summary ...... 161 4.2.10 Aims ...... 163 4.3 Results ...... 164 4.3.1 Skin injection of killed E. coli induces the acute expression of cyclooxygenase-2 in the draining lymph node ...... 164 4.3.2 Expression of cyclooxygenase-2, microsomal prostaglandin E synthase-1 and thromboxane synthase are increased in the KEC-draining lymph node ...... 166 4.3.3 Infiltrating neutrophils and monocytes express COX-2, mPGES-1 and TBXAS in the KEC-draining lymph node ...... 168 4.3.4 Cyclooxygenase inhibition reduces neutrophil infiltration into the draining lymph node following challenge with killed E. coli ...... 170 4.3.5 Cyclooxygenase inhibition at the time of challenge does not potentiate the humoral immune response to killed E. coli ...... 171 4.4 Discussion...... 174 4.4.1 Technical limitation ...... 174 4.4.2 The expression of cyclooxygenase-2, microsomal prostaglandin E synthase-1 and thromboxane synthase in the draining lymph node ...... 175 4.4.3 Drivers of prostanoid synthase expression in the draining lymph node ...... 176 4.4.4 Functions of prostanoid synthase expression in the draining lymph node ...... 177 4.4.5 Summary ...... 179 5 Investigations of Type I Interferons in the Draining Lymph Node ...... 180

5.1 Abstract ...... 180

5.2 Introduction ...... 181 5.2.1 Overview of type I interferons ...... 181 5.2.2 Type I interferons and lymph node barrier function ...... 181 5.2.3 Type I interferons and the developing adaptive immune response ...... 182 5.2.4 Mechanisms of type I interferon-driven inflammation in the draining lymph node 183 5.2.4.1 Chemokine production in the draining lymph node ...... 183 5.2.4.2 Inflammasome activation within the draining lymph node ...... 184 5.2.4.3 IFNγ in the draining lymph node...... 185 5.2.5 Summary ...... 186 5.2.6 Aims ...... 187 5.3 Results ...... 188 5.3.1 The expression of type I interferon-stimulated genes (ISGs) is increased in the KEC-draining lymph node ...... 188 5.3.2 IFNAR-deficient mice exhibit no defect in monocyte infiltration into the KEC- draining lymph node ...... 188 5.3.3 Neutrophils and monocytes infiltrating the KEC-draining lymph node exhibit increased expression of interferon-stimulated genes (ISGs) ...... 191 5.3.4 The genes encoding type I interferons are not significantly expressed in the KEC- draining lymph node ...... 191 5.3.5 Neutrophils and monocytes infiltrating the KEC-draining lymph node exhibit increased expression of the interferon-induced chemokines CXCL9 and CXCL10 ...... 194 5.3.6 Neutrophils and monocytes infiltrating the KEC-draining lymph node exhibit increased expression of the interferon-induced chemokine CCL2 ...... 196 5.3.7 Neutrophils and monocytes infiltrating the KEC-draining lymph node exhibit increased expression of the inflammasome components NLRP3, pro-IL-1β and pro-IL-18 198 5.3.8 NK cells are the major expresser of IFNγ in the KEC-draining lymph node ...... 200 5.3.9 IFNγ production is impaired in the KEC-draining lymph nodes of IFNAR-deficient mice 203 5.3.10 In vitro stimulation of lymphoid cell suspensions with KEC reveals increased IFNγ expression by NK cells within spleen cell suspensions relative to non-draining lymph node cell suspensions...... 204 5.3.11 In vitro stimulation of lymphoid cell suspensions with IFNβ and/or IFNγ induces a small increase in IFNγ expression by NK cells ...... 205 5.3.12 NK cells can produce IFNγ independent of the interferon αβ receptor (IFNAR) signalling 206 5.3.13 Monocyte frequency positively correlates with NK cell IFNγ expression following in vitro stimulation with KEC ...... 207 18

5.4 Discussion...... 209 5.4.1 Summary of findings: ...... 209 5.4.2 Technical limitations ...... 209 5.4.3 Type I interferon independent monocyte infiltration into the draining lymph node 210 5.4.4 Infiltrating neutrophils and monocytes as effectors of type I IFN stimulation in the draining lymph node ...... 210 5.4.5 Regulation of IFNγ expression by type I interferons in the KEC-draining lymph node 213 5.4.6 Summary ...... 215 6 Regulation of CD69 Expression in the Draining Lymph Node ...... 217

6.1 Abstract ...... 217 6.2 Introduction ...... 218 6.2.1 Regulation of CD69 expression ...... 218 6.2.1.1 CD69 expression in the steady state ...... 218 6.2.1.2 CD69 expression in the context of inflammation ...... 219 6.2.1.2.1 Cytokine-driven CD69 expression ...... 219 6.2.1.2.2 Antigen-driven expression of CD69 ...... 220 6.2.1.3 Transcriptional regulation of CD69 expression ...... 220 6.2.1.4 Post-transcriptional regulation of CD69 expression ...... 221 6.2.2 Functions of CD69 ...... 221 6.2.2.1 CD69 and immunoregulation...... 221 6.2.2.2 CD69 and memory T cells ...... 222 6.2.2.3 CD69 and S1P-dependent cell migration ...... 223 6.2.3 Summary ...... 224 6.2.4 Aims ...... 224 6.3 Results ...... 225 6.3.1 CD69 is upregulated by both lymphocytes and myeloid cells in the draining lymph node following skin injection of killed E. coli (KEC) ...... 225 6.3.2 Lymphocyte subsets differentially express CD69 in the KEC-draining lymph node 226 6.3.3 The upregulation of CD69 in the KEC-draining lymph node is largely dependent upon the interferon α/β receptor (IFNAR)...... 228 6.3.4 In vitro stimulation with interferon-β is sufficient to induce differential upregulation of CD69 by lymphocyte subsets ...... 229 6.3.5 Both T and B cells exhibit increased expression of type I interferon-stimulated genes in the KEC-draining lymph node ...... 232

6.3.6 In vitro stimulation with KEC induces IFNAR-independent CD69 expression among B cells but not T cells ...... 233 6.3.7 In vitro stimulation with IFNγ induces IFNAR-independent CD69 expression among B cells but not T cells ...... 235 6.3.8 In vitro re-stimulation of cell suspensions generated from KEC-draining lymph nodes with KEC induces IFNAR-independent CD69 expression by T cells ...... 237 6.3.9 The extent to which in vitro stimulation with KEC induces CD69 on T cells is positively correlated with the percentage of monocytes in the cell suspension ...... 238 6.3.10 Type I interferons impair the chemotaxis of T cells to sphingosine-1-phosphate (S1P) but B cells do not respond to this chemokine ...... 240 6.3.11 CD69+ve T cells exhibit impaired S1P chemotaxis relative to CD69-ve T cells...... 242 6.3.12 B cells accumulate in the KEC-draining lymph node to a greater extent than T cells 244 6.4 Discussion...... 251 6.4.1 IFNAR-dependent mechanisms of CD69 expression ...... 251 6.4.2 IFNAR-independent mechanisms of CD69 expression ...... 252 6.4.3 Differential regulation of CD69 expression by lymphocyte subsets ...... 253 6.4.4 Regulation of lymphocyte sphingosine-1-phosphate (S1P) chemotaxis by CD69 255 6.4.5 Analysis of the impaired S1P chemotaxis exhibited by B cells ...... 255 6.4.6 Implications of differential CD69 expression on lymphocyte egress from the draining lymph node ...... 256 6.4.7 Conclusion ...... 257 7 Discussion ...... 260

7.1 Summary of findings ...... 260 7.2 The relationship between type I interferons and Ly6Chi monocytes within the draining lymph node ...... 262 7.2.1 Ly6Chi monocytes as effectors of type I interferon responses in the draining lymph node ...... 262 7.2.2 Inflammasome activation as the link between Ly6Chi monocytes and type I interferons ...... 264 7.2.3 Re-evaluation of the importance of infiltrating Ly6Chi monocytes relative to lymph node resident macrophages ...... 268 7.2.4 Functions of interferon-activated monocytes in the draining lymph node ...... 269 7.2.4.1 Interferon-driven CXCR3 ligand production may be central to monocyte functions in the draining lymph node ...... 269 7.2.4.2 Ly6Chi monocytes, NK cells and CXCR3+ve T cells may exhibit CXCR3-dependent clustering in interfollicular and medullary regions of the draining lymph node ...... 271

7.2.4.3 Potential innate immune functions of Ly6Chi monocyte, NK cell, CD8+ve T cell clusters in the draining lymph node ...... 273 7.2.4.4 Potential adaptive immune functions of Ly6Chi monocyte, NK cell, CD8+ve T cell clusters in the draining lymph node ...... 276 7.3 The KEC-draining lymph node as a model that informs the design of TLR-4 based adjuvants ...... 280 Bibliography...... 282

Appendix 1: Vaccines Included in the UK Immunisation Regimen (1) ...... 335

Table of Figures

Figure 1.1: Gross lymph node anatomy...... 32 Figure 1.2: Lymph node microanatomy ...... 38 Figure 1.3: Range of Ly6Chi monocyte-derived cells that have been described in the draining lymph node ...... 71 Figure 1.4: The draining lymph node during acute inflammation ...... 74 Figure 2.1: Murine earflap injection ...... 88 Figure 2.2: Sample sizes required to compare the neutrophil and monocyte yield of a mechanical and a digestive method of lymph node disaggregation ...... 92 Figure 2.3: Lymph node isolation from surrounding tissue ...... 93 Figure 2.4: Yield of neutrophils in the absence of digestion ...... 93 Figure 2.5: Growth and enumeration of E. coli bacteria ...... 99 Figure 2.6: Killing of E. coli bacteria...... 100 Figure 2.7: IFNγ ELISPOT controls...... 102 Figure 2.8: AccucheckTM counting beads ...... 104 Figure 2.9: Lipopolysaccharide stimulation of RAW 264.7 cells ...... 105 Figure 2.10: Gating strategies, fluorescence-minus one (FMO) and isotype controls ...... 110 Figure 2.11: Cell sort strategies and purities ...... 113 Figure 2.12: Calculation of primer amplification efficiencies ...... 117 Figure 2.13: Isotype controls for immunohistochemical staining ...... 119 Figure 3.1: The superficial parotid lymph node drains the murine earflap ...... 128 Figure 3.2: E. coli bioparticles predominantly associate with neutrophils in the draining lymph node ...... 131 Figure 3.3: Skin injection of BCG bacilli does not induce a significant neutrophil influx into the draining lymph node ...... 132 Figure 3.4: Skin injection of BCG reliably elicits a T cell response but variably induces lymphadenopathy ...... 134 Figure 3.5: Skin injection of killed E. coli induces acute neutrophil infiltration into the draining lymph node ...... 136 Figure 3.6: Infiltrating neutrophils are localised in peripheral regions of the KEC-draining lymph node ...... 138 Figure 3.7: Acute CD69 upregulation in the superficial parotid lymph node following injection of killed E. coli into the murine earflap ...... 139 Figure 3.8: Ly6Chi monocytes infiltrate the draining lymph node ...... 141

Figure 3.9: Neutrophil infiltration precedes monocyte infiltration in the draining lymph node ...... 142 Supplementary Figure 3.10: Skin injection of killed E. coli elicits the acute infiltration of neutrophils and unidentified CD11b+ve Ly6Glo cells ...... 143 Supplementary Figure 3.11: Kinetics of neutrophil and monocyte infiltration into the KEC- draining lymph node ...... 144 Supplementary Figure 3.12: Lymphocytes in the draining superficial parotid lymph node do not significantly upregulate CD69 following BCG challenge ...... 145 Figure 4.1: The synthesis of prostanoids from arachidonic acid by the action of cyclooxygenases and terminal prostanoid synthases...... 154 Figure 4.2: Acute expression of cyclooxygenase-2 in the draining lymph node following skin injection of killed E. coli ...... 165 Figure 4.3: Increased expression of COX-2, mPGES- 1 and TBXAS in the KEC-draining lymph node ...... 167 Figure 4.4: Infiltrating neutrophils and monocytes express COX-2, mPGES-1 and TBXAS in the KEC-draining lymph node ...... 169 Figure 4.5: Cyclooxygenase inhibition reduces but does not ablate neutrophil infiltration into the draining lymph node...... 171 Figure 4.6: Acute cyclooxygenase inhibition does not influence the developing humoral immune response following skin challenge with killed E. coli ...... 173 Figure 5.1: Increased expression of type I interferon-stimulated genes (ISGs) in the KEC- draining lymph node ...... 189 Figure 5.2: The infiltration of neutrophils and monocytes is unimpaired in the KEC-draining lymph nodes of IFNAR-deficient mice ...... 190 Figure 5.3: Neutrophils and monocytes infiltrating the KEC-draining lymph node exhibit increased expression of interferon-stimulated genes (ISGs) ...... 192 Figure 5.4: The expression of type I interferons is not marked in the KEC-draining lymph node ...... 193 Figure 5.5: Increased expression of CXCL9 and CXCL10 in the KEC-draining lymph node ...... 196 Figure 5.6: CCL2 expression is increased in the KEC-draining lymph node ...... 197 Figure 5.7: Increased expression of inflammasome components by neutrophils and monocytes infiltrating the KEC-draining lymph node ...... 200 Figure 5.8: IFNγ expression is increased in the KEC-draining lymph node ...... 201 Figure 5.9: CD11b+ve NK cells, neutrophils and monocytes express IFNγ protein in the KEC- draining lymph node ...... 202

Figure 5.10: IFNγ production is impaired in the KEC-draining lymph nodes of IFNAR-deficient mice ...... 203 Figure 5.11: In vitro stimulation of lymphoid cell suspensions with KEC elicits IFNγ expression by NK cells ...... 204 Figure 5.12: In vitro stimulation of lymphoid cell suspensions with IFNβ and/or IFNγ induces a small increase in IFNγ expression by NK cells...... 205 Figure 5.13: NK cells can produce IFNγ independent of the interferon αβ receptor (IFNAR)... 207 Figure 5.14: Monocyte frequency positively correlates with NK cell IFNγ expression following in vitro stimulation with KEC ...... 208 Figure 5.15: Proposed mechanism for the induction of IFNγ production by type I IFN-activated monocytes in the draining lymph node...... 215 Figure 6.1: CD69-dependent regulation of S1P1 expression and lymphocyte egress from lymph nodes ...... 223 Figure 6.2: CD69 is upregulated by both lymphocytes and myeloid cells in the KEC-draining lymph node ...... 226 Figure 6.3: B and T cells differentially express CD69 in the KEC-draining lymph node ...... 227 Figure 6.4: CD4 and CD8 T cells differentially express CD69 in the KEC-draining lymph node . 228 Figure 6.5: The upregulation of CD69 in the KEC-draining lymph node is largely dependent on the interferon α/β receptor (IFNAR) ...... 229 Figure 6.6: In vitro stimulation with interferon β is sufficient to induce differential upregulation of CD69 by lymphocyte subsets ...... 231 Figure 6.7: T and B cells in the KEC-draining lymph node exhibit increased expression of interferon-stimulated genes ...... 232 Figure 6.8: In vitro stimulation with KEC induces interferon α/β Receptor (IFNAR) dependent and independent CD69 expression ...... 234 Figure 6.9: In vitro stimulation with IFNγ induces interferon α/β receptor (IFNAR) dependent and independent CD69 expression ...... 236 Figure 6.10: Re-stimulation of KEC-draining lymph node cells with KEC in vitro induces IFNAR- independent CD69 expression by T cells ...... 237 Figure 6.11: In vitro stimulation reveals a positive correlation between monocyte frequency and the percentage of CD69+ve T cells in a lymph node or spleen cell suspension ...... 239 Figure 6.12: Type I interferons impair the chemotaxis of T cells to sphingosine-1-phosphate (S1P) ...... 241 Figure 6.13: CD69+ve T cells exhibit impaired S1P chemotaxis ...... 243 Figure 6.14: Lymphocytes exhibit differential accumulation in the draining lymph node ...... 245

Supplementary Figure 6.15: Measurement of CD69 expression on B and T cells by median fluorescence intensity (MFI)...... 246 Supplementary Figure 6.16: The infiltration of monocytes is temporally associated with the upregulation of CD69 by T cells within the KEC-draining lymph node ...... 247 Supplementary Figure 6.17: The effects of sphingosine-1-phosphate concentration and in vitro pre-incubation on lymphocyte chemotaxis ...... 248 Supplementary Figure 6.18: The expression of interferon-stimulated genes (ISGs) by B and T cells relative to four different reference genes ...... 249 Figure 6.19: Flow cytometry of permeabilised lymphocytes does not reveal an intracellular store of CD69 ...... 250 Figure 7.1: Diagrammatic representation of main thesis findings...... 261 Figure 7.2: Ly6Chi monocytes infiltrating the draining lymph node are activated by type I interferons to induce the production of IFNγ by NK cells and CD8 T cells as well as the expression of CD69 by lymphocytes via activation of the inflammasome. Created with biorender.com...... 266 Figure 7.3: Experiment design to determine the impact of monocyte depletion on IFNγ production and CD69 upregulation in the draining lymph node...... 267 Figure 7.4: Proposed positive feedback loop between Ly6Chi monocytes, NK cells and CD8+ve memory T cells triggered by type I interferons and maintained by CXCR3 ligands and IFNγ ... 271 Figure 7.5: Putative intranodal localisation of CXCR3-dependent clusters of Ly6Chi monocytes, NK cells and CD8+ve T cells...... 273 Figure 7.6: Putative innate immune functions of NK cell, CD8+ve memory T cell, Ly6Chi monocyte clusters ...... 275 Figure 7.7: Putative adaptive immune functions of NK cell, CD8 Memory T cell, Ly6Chi monocyte clusters ...... 279

Table of Tables

Table 1.1 Notable adjuvants and their inflammatory properties ...... 57 Table 2.1: General reagents ...... 77 Table 2.2: Cell culture media ...... 78 Table 2.3: Flow cytometry buffers ...... 78 Table 2.4: Immunohistochemistry buffers ...... 78 Table 2.5: Flow cytometry antibodies ...... 79 Table 2.6: Flow cytometry isotype controls ...... 80 Table 2.7: Immunohistochemistry primary antibodies ...... 80 Table 2.8: Immunohistochemistry isotype controls ...... 80 Table 2.9: Immunohistochemistry secondary antibodies ...... 80 Table 2.10: Primer sequences ...... 81 Table 2.11: Positive control (+ve CTRL) cDNA ...... 82 Table 2.12: Overview of the use of animals in this thesis ...... 85 Table 2.13: Mechanical methods - Lymphocytes ...... 94 Table 2.14: Digestive methods - Lymphocytes ...... 94 Table 2.15: Mechanical methods – Neutrophils and Monocytes ...... 95 Table 2.16: Digestive methods - Neutrophils and Monocytes...... 95 Table 2.17: Mechanical methods - Dendritic Cells ...... 96 Table 2.18: Digestive methods - Dendritic Cells ...... 96 Table 2.19: Digestive methods - Macrophages ...... 97 Table 2.20: Digestive methods - Stromal Cells ...... 97 Table 2.21: Reverse Transcription Reaction Mixture ...... 114 Table 2.22: End-Point PCR Reaction Mixture ...... 115 Table 2.23: Real-Time PCR Reaction Mixture ...... 115 Table 2.24: Paraffin embedding program ...... 118 Table 2.25: Dewax protocol ...... 119 Table 5.1: Expression of pro-inflammatory genes by neutrophils, monocytes and other CD11b+ve cells in the KEC-draining lymph node ...... 212 Table 6.1: Comparison of S1P Chemotaxis Methods ...... 259

1 Introduction

1.1 Vaccines

Vaccination is considered to be amongst the most effective health interventions in history (1). The incidence of various infectious diseases that used to plague populations has declined precipitously since the advent of vaccination programs, notably culminating in the successful eradication of smallpox (2,3).

Vaccines work through the safe exposure of the adaptive immune system to antigens from an infectious agent. This facilitates the development of immunological memory, which bestows protection against the pathogen if subsequently encountered. Currently available vaccines can be divided into 3 main types; live attenuated vaccines, inactivated vaccines and subunit vaccines. These, respectively, utilise weakened strains of a chosen pathogen , killed preparations of a chosen pathogen and purified antigens to generate immunological memory (4). The majority of the vaccines included in the United Kingdom’s routine immunisation schedule are intramuscularly administered subunit vaccines, although a notable minority are either of the live attenuated and inactivated subtypes and/or are administered by other routes (e.g. intradermal, intranasal and oral) (Appendix 1).

The advent of vaccinology pre-dates both germ theory and any detailed understanding of the immune system. As such the development of the first vaccines was largely empiric and thus the history of vaccination is a useful lens through which to discuss the state of modern vaccinology.

1.1.1 History of vaccines

The principle of immunity (protection bestowed by prior disease exposure) has been recognised for millennia (5). Prior to vaccination, this was most famously exploited through the practice of variolation, in which individuals were inoculated with small amounts of smallpox lesion material to protect against future smallpox outbreaks (although this practice did incur a 2% risk of developing smallpox) (6). The advent of vaccination is largely credited to the work of Edward Jenner in the late 18th century (5,7), who used both experimental and observational data to demonstrate that exposure to the relatively harmless disease cowpox bestowed protection against subsequent exposure to the much more dangerous disease smallpox (7). This is due to the fact that that the cowpox and smallpox viruses belong to the same genus and are sufficiently similar to induce cross-protective immune responses (8). Further vaccines were

not developed until the late 19th century, in tandem with the increasing acceptance of the germ theory of disease (4). This time period was marked by the discovery of methods to attenuate pathogens through exposure to hostile conditions such as heat and oxidative stress (4). Louis Pasteur was a pioneer in this field, formulating a rabies vaccine in 1885 in which attenuation was achieved through the exposure of infected rabbit spinal cord to dry air (9). In addition to attenuated vaccines, the end of the 19th century bore witness to the development of the first inactivated vaccines, targeting typhoid, cholera and bubonic plague (4,10).

The 20th century heralded huge strides in vaccine development, including the attenuation of pathogens via serial culture that underpins the majority of modern live attenuated vaccines (4). This was first adopted by Albert Calmette and Camille Guerin at the Pasteur institute, who in 1905, isolated a culture of Mycobacterium bovis from the udder of an infected cow and proceeded to attenuate it through hundreds of repeated passages over a period of 16 years in order to develop a live attenuated vaccine against tuberculosis; Bacillus Calmette-Guerin (BCG) (11). The serial passage of viral pathogens was made possible by the discovery that viruses could be propagated in in vitro cell cultures in the mid-20th century (12). A series of live attenuated viral vaccines were therefore developed in the latter half of the 20th century, with notable examples including the measles, mumps and rubella vaccines (4,13,14).

The other major vaccine development of the 20th century was the introduction of subunit vaccines. The first step to the development of a subunit vaccine was the discovery that formalin-inactivated diphtheria toxin (toxoid) exhibited immunogenicity (15). Another important step was the serendipitous discovery that aluminium salts used in toxoid preparation enhanced their immunogenicity (16), underlining the importance of adjuvants (discussed extensively in Section 1.3.1). Since then, a diverse range of subunit vaccines have been developed utilising antigens such as cell-surface proteins and capsular polysaccharides (Appendix 1). The conjugation of capsular polysaccharides to carrier proteins was a further advance, as this increases the immunogenicity of non-protein antigens by enabling T cell help (17,18). As a result, several such conjugate vaccines are included in the UK routine immunisation schedule (Appendix 1).

With regard to vaccine mechanisms, seminal work conducted in the late 19th and early 20th centuries led to the discovery and description of antibodies and their capacity to neutralise, agglutinate and opsonise pathogens and/or their toxins (19–21). This was a significant advance as the vast majority of modern-day vaccines bestow antibody-dependent protection (22,23). Such protection may be mediated by various antibody functions, including neutralisation and complement activation (22,23). As a result, measures of antibody titre or function are used as

immune correlates of protection following vaccination (22,23). Exceptions are the varicella zoster and BCG vaccines, which are believed to bestow T cell dependent protection (although antibody titres remain a useful correlate of vaccine efficacy in the case of the varicella zoster vaccine) (22,23).

Since the turn of the twenty first century, important vaccines have been developed against human papilloma virus (a major driver of cervical cancer), meningitis B and rotavirus (4). The live attenuated rotavirus vaccine was developed through the genetic reassortment of bovine and human rotaviruses and bestows a high level protection against severe childhood gastroenteritis (24,25). Furthermore, the subunit meningitis B vaccine represents the first vaccine developed using reverse vaccinology, in which novel antigens were identified through sequencing of the pathogen’s genome (26). In summary, these examples exemplify the history of vaccinology, which has been characterised by a steady progression from the empiric methods employed by Jenner to more informed approaches to vaccine design that are underpinned by advances in our understanding of immunology (27).

1.1.2 Vaccine challenges

Whilst vaccines have been developed against a broad array of pathogens, two challenges persist; namely novel pathogens and pathogens that have proved refractory to vaccines. With regards to the former, early characterisation of the novel pathogen is important for candidate vaccines to be rapidly developed and clinically evaluated (28). In a pandemic scenario where time is of the essence, an approach that encourages the parallel development of multiple candidate vaccines of varying types is advantageous (29,30). This is facilitated through the use of a range of different technology platforms and adjuvants (29,30). Similarly, time necessitates the clearance of different regulatory steps and the establishment of manufacturing and logistics processes in parallel so that once a candidate vaccine is validated it can rapidly be administered at scale to large populations (29).

In addition to novel pathogens, there remain a number of important pathogens that have proved refractory to the development of an effective vaccine. Notable examples include tuberculosis, malaria, and human immunodeficiency virus (HIV). A multitude of factors contribute to this problem. Firstly, with some pathogens, it has proved difficult to identify immunogenic antigens that are not subject to the escape mechanisms of antigen drift and shift. This may be overcome by novel methods to identify such antigens, such as the genome sequencing and reverse vaccinology approach used to develop the meningitis B vaccine (21). Another problem is that the precise mechanisms of protective immunity are not fully 29

understood for certain pathogens. Tuberculosis is a prime example as there is evidence that T cells bestow protection but vaccine development is hindered by the lack of reliable correlates of protection akin to antibody titres (31–34). This problem has been compounded by the fact that (until recently) there has been a relative dearth of adjuvants capable of potentiating T cell responses (Section 1.3.1). Fundamental to this problem is the fact that the adjuvant mechanisms and the factors that modulate the developing adaptive immune response are only partially understood.

Secondary lymphoid organs such as draining lymph nodes (dLNs) are the anatomical location in which adaptive immune responses are initiated. This thesis concerns itself with the characterisation of innate immune pathways within the draining lymph node (dLN) in order to better our understanding of how these processes may impact the developing adaptive immune response and thereby inform adjuvant design. This introduction therefore first covers the anatomy and physiology that underpins the initiation of adaptive immune responses within the dLN before exploring our current understanding of adjuvant mechanisms and innate immune pathways in the dLN.

1.2 Initiation of adaptive immune responses

Adaptive immune responses are initiated by a process of clonal selection whereby antigens induce the activation and proliferation of lymphocytes expressing cognate antigen receptors. Lymphocyte antigen receptors are generated by the somatic recombination of numerous different gene segments during lymphocyte development. This process facilitates the generation of a huge variety of lymphocyte antigen receptors; theoretically ≥1011 different B cell receptors (BCRs) and ≥1015 T cell receptors (TCRs) (35). The diversity of the lymphocyte antigen receptor repertoire maximizes the number of antigens that can be targeted by lymphocytes. However, as each lymphocyte can only express a single lymphocyte antigen receptor, the diversity of this repertoire necessarily limits the number of cognate lymphocytes available to respond to a given antigen. Indeed, studies demonstrate that only 1 in 1-3 x 105 T cells (36–38) and 1 in 105-106 B cells (39–41) are cognate for a given antigen in a naïve mouse. Facilitating the presentation of an antigen to the small numbers of cognate lymphocytes available therefore represents a ‘needle in a haystack’ problem for the immune system. Nevertheless, the activation of naïve T cells is remarkably efficient, Van Heijst et al having demonstrated that >95% of cognate T cells are activated during the first 8 days of a viral infection (42). Such efficiency is promoted by the fact that vertebrate immune systems have

evolved secondary lymphoid organs that serve as specialised sites of lymphocyte activation by facilitating the presentation of antigen to large numbers of naïve lymphocytes (43).

The secondary lymphoid organs (SLOs) consist of the mucosa-associated lymphoid tissue (MALT), spleen and lymph nodes. SLOs accumulate antigen from distinct anatomical compartments (the mucosa, blood and extracellular fluid/lymph respectively) and present it to large numbers of lymphocytes that continually recirculate between SLOs and the bloodstream (43). Their importance with regard to lymphocyte activation is demonstrated by the impaired adaptive immune responses exhibited by mice harbouring defects in SLO development and structure (44–47). In evolutionary terms, lymph nodes are the most recent of the SLOs (48) and initiate adaptive immune responses to antigens transported from tissues via afferent lymphatic vessels (43). The dLN is therefore central to the generation of adaptive immune responses to vaccines and pathogens that enter the intradermal, subcutaneous and intramuscular spaces. In such circumstances, cognate lymphocytes are predominantly activated in the primary dLN (49–52) and ablation of afferent lymphatic vessels results in delayed lymphocyte activation in the spleen as opposed to the dLN (53).

Lymph nodes are highly organised structures in which antigen and lymphocytes are concurrently channelled so as to efficiently promote the rapid activation of the small number of lymphocytes with receptors cognate for a given antigen. Thus, the following sections describe lymph node anatomy and the physiological processes fundamental to lymph node function; lymphocyte recirculation, antigen trafficking and lymphocyte activation.

1.2.1 Lymph node anatomy

The cumulative action of Starling forces acting across the capillary wall that force the extravasation of fluid out of capillaries and into the extracellular space of the tissue interstitium. This extracellular fluid is redefined as lymph as it enters the lymphatic system via blunt-ended lymphatic capillaries located within tissues. These lymphatic capillaries progressively converge to form larger lymphatic vessels that ultimately drain lymph back into the cardiovascular system via the thoracic duct (54). Lymph nodes are encapsulated bean- shaped lymphoid structures interspersed along the lymphatic tree, particularly at sites where lymphatic vessels converge (55). Lymph flows through lymph nodes; entering by one or more afferent lymphatic vessels that penetrate the lymph node capsule and exiting through an efferent lymphatic vessel that projects from the lymph node hilum (55,56). Lymph nodes also receive a vascular supply via a feed arteriole and a draining vein that enter and exit from the hilum respectively (55,57). Lymph nodes possess a highly organised internal structure that can 31

be divided into three compartments, the parenchyma, the lymphatic sinuses and the vasculature. The parenchyma can be further divide into an outer cortex and an inner medulla. Figure 1.1 depicts the major features of lymph node anatomy.

Figure 1.1: Gross lymph node anatomy. Created with biorender.com

1.2.1.1 Parenchyma

1.2.1.1.1 Cortex The cortex forms the main body of the lymph node parenchyma and can be broadly divided into the B cell-rich follicles in the outer cortex that lie directly underneath the subscapular sinus and the T cell rich paracortex that lies deep to the follicles. The follicles exhibit marked expression of the CXCR5 ligand CXCL13, whereas the paracortex exhibits marked expression of the CCR7 ligands CCL19 and CCL21 (58–62). These chemokines are central to the organisation of the lymph node cortex as both T cells and dendritic cells use CCR7 to localise within the paracortex and B cells use CXCR5 to localise within the follicles (61,63–65). Indeed, deletion of CXCL13 and CCL21 leads to gross distortions in the anatomy of the lymph node cortex (61,62,66). These regions also exhibit differences in their underlying stromal architecture, with follicular dendritic cells (FDCs) and fibroblastic reticular cells (FRCs) forming distinct stromal networks in the follicles and paracortex respectively (67). Moreover, the paracortex also harbours networks of resident dendritic cells (68) and macrophages (69). T cells migrate along the FRC network in the paracortex and scan both lymph node resident and migratory dendritic cells for cognate antigen, whilst B cells move along the FDC network in the follicle in search of soluble or membrane bound antigen (Section 1.2.2.2).

The paracortex is not a uniform structure and can be further subdivided. The cortical ridge refers to the region of the paracortex adjacent to the follicles. It exhibits a particularly dense stromal network, an increased number of high endothelial venules (HEVs) and is a prominent site for the interaction of dendritic cells with lymphocytes entering the lymph node (59,70). Similarly, the peripheral region of the paracortex adjacent to the medulla also serves as a site of T cell activation and has been termed the medullary ridge (70). These regions are superficially contiguous with the interfollicular zones (IFZs) that lie between follicles. The IFZs are rich in HEVs and host strategically positioned dendritic cells, NK cells, γδ T cells, NKT cells and innate-like CD8 T cells that rapidly respond to pathogens that drain into the overlying lymphatic sinuses via afferent lymphatics (71,72). In terms of dendritic cells, it is recognised that these peripheral regions of the paracortex are enriched with cDC2s that are specialised to present to CD4 T cells via MHC Class II (71,73–76). In contrast, deeper regions of the paracortex are enriched with cDC1s specialised to present to CD8 T cells via MHC class I(71,73– 76). Moreover, CD4 and CD8 T cells are similarly distributed such that CD4 T cells and cDC2s are concentrated in peripheral regions of the paracortex, whilst CD8 T cells and cDC1s are concentrated within deeper regions of the paracortex (76).

The lymph node cortex is therefore characterised by the spatial segregation of lymphocytes into the superficial follicles and underlying paracortex, which express different chemokines and harbour distinct networks of stromal cells and antigen presenting cells. Moreover, the border zones between these regions are prominent sites for the activation of both innate immune cells and lymphocytes. The main features of the LN cortex are depicted in Figure 1.2.

1.2.1.1.2 Medulla The medulla lies deep to the paracortex and is adjacent to the lymph node hilum. It consists of a network of interconnected lymphatic sinuses interspersed with sections of parenchyma called medullary cords (55,77). The medullary cords are predominantly populated by medullary cord macrophages, B cells and plasma cells residing on a network of medullary fibroblastic reticular cells (77–81). CXCL12 is strongly expressed in the medullary cords and is thought to promote the localisation of CXCR4+ve plasma cells in this region (78,79). Indeed, the medullary cords are regarded as a specific niche for the survival of plasma cells (77,79,80). Moreover, the medullary cord macrophages, along with medullary sinus macrophages, play an important role in the trapping of foreign material that drains into the medullary lymphatic sinuses (77). Finally, the medulla also been reported as a site of lymphocyte egress into efferent lymph (82) , although the cortical lymphatic sinuses are thought to be the primary site

of lymphocytes egress from the lymph node parenchyma (Section 1.2.2.3). The main features of the LN medulla are depicted in Figure 1.2.

1.2.1.1.3 Lymphatic sinuses

Lymph flows through lymph nodes via a series of lymphatic sinuses lined by LYVE-1+ve lymphatic endothelial cells. Afferent lymph first enters the subcapsular sinus, a space that lies between the overlying capsule and the underlying cortex, before distributing throughout the medullary and cortical lymphatic sinuses (57). The cortical lymphatic sinuses are blunt-ended structures that begin in interfollicular and perifollicular regions of the paracortex and connect to the medullary lymphatic sinuses (83,84). The medullary lymphatic sinuses coalesce to form an efferent lymphatic vessel that protrudes from the hilum.

These lymphatic sinuses play important roles with regard to the trapping of antigen borne in afferent lymph as strategically positioned macrophages and dendritic cells capture antigen that drains into the subcapsular and medullary sinuses (Sections 1.2.3.1 and 1.3.2.3). In addition, these lymphatic sinuses serve as sites of cellular entry and egress from the dLN. T cells and dendritic cells arriving via afferent lymphatics have been shown to enter the lymph node parenchyma via the subcapsular and medullary sinuses (85), whilst lymphocytes egress the lymph node parenchyma by transmigrating into the cortical and medullary lymphatic sinuses (82,83,83).

1.2.1.1.3.1 Lymphatic endothelial cells

The lymphatic endothelial cells (LECs) that line the lymphatic sinuses are not homogenous and exhibit more than just structural functions. Single cell transcriptional analysis has revealed clear differences in gene expression between LECs depending on their location within the dLN (86,87). Indeed, the LECs that line the floor and ceiling of subcapsular sinus are distinct populations, as are the LECs lining the medullary (86,87) and cortical lymphatic sinuses (86). In terms of function, LECs help establish concentration gradients for the cardinal chemokines CCL21 (88) and sphingosine-1-phosphate (S1P) (89,90). Moreover, the S1P produced by LECs provides an important survival signal to recirculating T cells (91). Finally, LECs do more than just passively channel lymph. Indeed, the LECs that line the floor of the subcapsular sinus synthesise protein filters that regulate access of lymph borne material to the lymph node conduit system (92) (Section 1.2.1.2.4). Furthermore, LECs have been shown to process and

present antigen and are thereby able to induce peripheral tolerance within T cells under steady state conditions (93–95). Thus, the lymphatic sinuses and their resident cell populations actively modulate the entry, egress and function of cells within the dLN as well as contributing to the capture and distribution of lymph-borne antigen.

1.2.1.1.4 Vasculature The vascular system of a lymph node consists of a feed arteriole and draining vein that enter and exit the lymph node at the hilum and are connected by capillary networks that perfuse the lymph node parenchyma (55,57,96,97). The unique feature of the lymph node vasculature is the high endothelial venule (HEV). HEVs are specialised post-capillary venules that facilitate the trafficking of lymphocytes from the bloodstream into the lymph node parenchyma. HEVs are found in orders III to V of the lymph node venular tree and predominantly course through the paracortex (57,97,98). The thick cuboidal endothelium, basal lamina and perivascular sheath of HEVs distinguishes them from post-capillary venules in other tissues (99). Indeed, the term ‘high’ endothelial venule stems from the height of their cuboidal endothelium relative to the flat endothelium of other venules (57). The HEV endothelium expresses the CD62L ligands collectively known as peripheral node addressin (PNAd) (100,101), membrane bound forms of the chemokines CCL19, CCL21 and CXCL12 (102–109), and the integrin ligands ICAM-1, ICAM-2 and VCAM (110) to facilitate the rolling, firm arrest and transmigration of lymphocytes (Section 1.2.2.1.1). The specialised phenotype of HEV endothelial cell is maintained by dendritic cells as their depletion incurs a loss of HEV phenotype and a consequent reduction in lymphocyte trafficking and lymph node cellularity (98).

1.2.1.2 Lymph node stromal cells Non-haematopoietic stromal cells are crucial to the structure and function of lymph nodes. They can be divided into the endothelial cells that line the lymphatic sinuses and blood vessels of the lymph node (Sections 1.2.1.1.3.1 and 1.2.1.1.4) and the non-endothelial structural cell subsets that populate the lymph node parenchyma (111). The latter include fibroblastic reticular cells (FRCs), follicular dendritic cells (FDCs) and marginal reticular cells (MRCs).

1.2.1.2.1 Fibroblastic reticular cells Distinct subsets of fibroblastic reticular cells (FRCs) form dense fibrous networks in the paracortex (T zone FRCs) and medulla (medullary FRCs) (59,67,79). A third subset of FRCs that 35

sparsely populate the outer regions of follicles have also been described (B zone FRCs) (58). Each of these FRC subsets serves to promote the structure and function of its corresponding lymph node compartment. The network formed by T zone FRCs is a lattice-like structure that provides a physical framework which B cells and T cells use to migrate through the paracortex after exiting HEVs (67). These T zone FRCs also promote the survival and localisation of T cells by producing the survival factor IL-7 and the CCR7 ligands CCL19 and CCL21 respectively (62). The B zone FRCs are an important source of the B cell survival factor BAFF (58) and there is also evidence to suggest they produce the B cell chemokine CXCL13 (79). Similarly, medullary FRCs support plasma cell localisation and survival within the medulla through the production of CXCL12, BAFF, APRIL and IL-6 (79). It is thus unsurprising that the conditional ablation of FRCs has profound effects upon lymph nodes; resulting in significant reductions in their cellularity, the loss of distinct B cell and T cell regions and a reduced capacity to initiate T cell and B cell responses (58,112). Thus, distinct FRC subsets organise and maintain the compartmentalised structure of the lymph node parenchyma through the production of distinct combinations of survival factors and chemokines.

1.2.1.2.2 Follicular dendritic cells Follicular dendritic cells (FDCs) form the stromal network that B cells use to migrate within the follicle (67) and can be identified by their high expression of the complement receptors CD21 and CD35. FDCs store opsonised antigens on their surface that can be recognised by migrating B cells (113,114) and are important for the maintenance of the germinal centres that develop during a humoral immune response (60). The conditional ablation of FDCs changes the organisation of B cells in the outer cortex from a set of discrete follicles to a peripheral band of B cells (60). However, FDC ablation does not reduce either B cell numbers or the expression of BAFF and CXCL131 in the lymph node (60). These findings suggest that FDCs are important for the organisation of B cells in the outer cortex but are redundant for their survival and localisation in the lymph node.

1.2.1.2.3 Marginal reticular cells Marginal reticular cells (MRCs) are a subset of lymph node stromal cells that form a fibrous network in the outer regions of the follicle directly underneath the floor of the subcapsular

1 B zone FRCs (Section 1.2.1.2.1) and marginal reticular cells (Section 1.2.1.2.3) are considered more important sources of BAFF and CXCL13 in the lymph node. 36

sinus (115,116). It is thought that MRCs are the direct descendants of the lymphoid tissue organizer cells that participate in the formation of lymph nodes during embryological development (115,116). Their precise role is not yet clear but they are known to express CXCL13 (79,115) and serve as progenitor cells for follicular dendritic cells (117).

1.2.1.2.4 The lymph node conduit system The interconnecting fibres that form reticular stromal network of the paracortex (Section 1.2.1.1.1) consist of an inner collagen core and an outer sheath formed by the basement membranes of the basement membranes of T zone FRCs (118). The network of these tube-like structures is the lymph node conduit system (Figure 1.2). These conduits begin as transendothelial channels in the subcapsular sinus and allow lymphatic fluid and low molecular weight substances (<70kDa) to flow throughout the paracortex and rapidly accumulate in FRC layer that sheathes HEVs (92,118,119). The 70kDa size-limit is imposed by sieve-like protein structures that span the entrance to conduits in the lymphatic sinus endothelium (92). These sieves exclude the majority of lymph-borne virions but a small number are able to gain rapid access to the conduit system, demonstrating that this size exclusion is not perfect (120). These conduits serve as an antigen distribution network as dendritic cells can sample conduit-borne antigen via extend processes they extend into the conduit lumen (118). A similar but less dense conduit system lined by MRCs and FDCs has been described in the follicles and similarly it facilitates the rapid capture of low molecular weight antigens by B cells and FDCs (121,122). In addition to such antigen distribution, the paracortical conduit network is utilised by B cells to rapidly export IgM into efferent lymph (123). It therefore serves the dual function of facilitating the rapid access and export of antigens and IgM antibodies respectively.

Figure 1.2: Lymph node microanatomy Representative diagram detailing the structural and cellular microanatomy of a lymph node in cross section. cDC: conventional dendritic cell, FDC: follicular dendritic cell, HEV: high endothelial venule, LEC: lymphatic endothelial cell, MRC: marginal reticular cell. Created with biorender.com

SCS: subcapsular sinus, S1P: sphingosine-1-phosphate. Created with biorender.com

1.2.2 Lymphocyte recirculation

Lymphocytes continually recirculate between the bloodstream and secondary lymphoid organs in search of cognate antigen (97). This is necessary in light of the low frequency of lymphocytes cognate to any given antigen (Section 1.2). Lymphocytes enter lymph nodes via both HEVs and afferent lymphatics and egress via efferent lymph. It is estimated that T cells and B cells spend an average of 30 minutes in the bloodstream before entering an SLO (124) and take 12-20 hours and 18-36 hours respectively to transit through lymph nodes in the steady state (125,126). The following sections will describe the process of lymphocyte entry into, transit through and egress from lymph nodes as well as the mechanisms that regulate these complex processes.

1.2.2.1 Lymphocyte entry

1.2.2.1.1 High endothelial venules Lymphocytes continually transmigrate across the HEV endothelium to enter lymph nodes directly from the bloodstream (57). Lymphocytes initially roll along the HEV endothelium due to the interactions of CD62L on lymphocytes with peripheral node addressins on the HEV endothelium (102). LFA-1 on rolling lymphocytes binds endothelial ICAM-1/2 to mediate the firm arrest of lymphocytes on the HEV endothelium (110). This adhesion is also dependent upon chemokines2 such as CCL19, CCL21, CXCL12 and CXCL13 anchored to the surface of the HEV endothelium (102–109,128), which are thought to induce the conformational changes in LFA-1 required for it to bind ICAM-1 and 2 (129). In addition, the adhesion of rolling lymphocytes to the HEV endothelium requires their desensitisation to the chemokine sphingosine-1 phosphate (S1P), which is present in high concentrations in blood (130). Once firmly adherent, lymphocytes cross from the luminal to the abluminal surface of the HEV endothelium and accumulate in pockets formed between the underside of HEV endothelial cells and their basement membrane (107,131,132). This process requires lymphocytes to modulate the affinity of LFA-1 on their surface; presumably to facilitate the morphological changes required for diapedesis (133). Lymphocytes within these HEV pockets cross the endothelial basement membrane to enter a narrow perivascular channel (PVC) created by the fibroblastic reticular cells that ensheath the HEV (67,107,131). This process of transmigration is dependent upon the production of lysophosphatidic acid (LPA) by HEV endothelial cells as it drives an autocrine increase in HEV endothelial cell motility (132,134). Lymphocytes finally

2 These chemokines are not necessarily produced by the HEV endothelial cells, they can synthesised by other LN cells and transcytosed onto the HEV surface (109,127) 39

enter the lymph node parenchyma via defined ‘exit ramps’ between the fibroblastic cells that line the perivascular channel (67).

A notable aspect of lymphocyte entry via HEVs is the dependence of this process on a variety of cells beyond HEV endothelial cells alone. Indeed, dendritic cells are required actively maintain the specialised phenotype of the HEV endothelial cells (98). Moreover, type 3 innate lymphoid cells (ILC3s) are important for maintaining lymphocyte entry via HEVs, although the mechanism by which they mediate this function is unclear as ILC3 deficiency does not change HEV phenotype (135). In addition, expression of nuclear factor inducing kinase (NIK) by LECs is crucial for B cell entry into the dLN and likely linked to CXCL13 production by LECs (127). Finally, the interaction of platelets with FRCs is required to maintain HEV barrier function in the context of a high volume of lymphocyte trafficking in order to prevent spontaneous haemorrhage into the lymph node parenchyma (136). It is thus clear that the entry of lymphocytes via HEVs is a tightly regulated multi-step process orchestrated by a wide variety of cells. This may be necessary to maintain the correct balance of lymphocytes within the dLN and respond rapidly to an infectious challenge as discussed in Section 1.2.2.4.

1.2.2.1.2 Afferent lymphatics Lymphocytes are present in the afferent lymph that drains peripheral tissues, with T cells outnumbering B cells (137,138). As lymph nodes are arranged in serial anatomical chains, the efferent lymph of primary lymph nodes also delivers egressing lymphocytes to downstream secondary and tertiary lymph nodes (56,125). Labelled T cells injected into afferent lymphatics have been observed transmigrating into the lymph node parenchyma from peripheral medullary lymphatic sinuses (85). This transmigration does not require CCR7 but the subsequent migration of these T cells from the medullary cords to the paracortex is CCR7- dependent (85). T cells have also been shown to enter the lymph node parenchyma through the floor of subcapsular sinus but only after it has been disrupted by the entry of migratory dendritic cells (85). Unlike T cells, the mechanisms governing the entry of lymph-borne B cells into the lymph node parenchyma have not been elucidated. Nevertheless, it is clear that the entry of lymph-borne lymphocytes operates in parallel to the continual entry of lymphocytes across HEVs.

1.2.2.2 Intranodal lymphocyte migration and motility

1.2.2.2.1 Intranodal migration Upon exiting the HEV, T cells rapidly migrate throughout the paracortex using the T zone FRC network, whilst B cells initially remain in the close vicinity of the HEV before also using the T zone FRC network to migrate to the base of a lymph node follicle (67,107). Upon entering the follicle, B cells switch to using the FDC network as the stromal underpinning for their migration (67). Chemokines are central to these patterns of intranodal migration as CXCR5-deficient B cells fail to enter the CXCL13-rich follicles (61) and CCR7-deficient T cells or T cells with defective chemokine receptor signalling exhibit impaired migration into the deep paracortex (63–65). Moreover, CD4 T cells are directed by the chemokine receptor Ebi2 to peripheral regions of the paracortex, such that the distribution of CD4 and CD8 T cells is somewhat segregated between peripheral and deep regions of paracortex respectively (76). This serves to colocalise CD4 and CD8 T cells with cDC1 and cDC2 dendritic cells respectively (73,76).

1.2.2.2.2 Intranodal motility

1.2.2.2.2.1 T cells Live cell imaging has shown that T cells are highly motile in the paracortex and scan dendritic cells for cognate antigen (67,139–142). This pattern of migration has been described as a ‘guided random walk’ (143) as T cells exhibit random and independent paths of migration within the confines of the T zone FRC network (67,139,141,142). The high motility of T cells is maintained by the expression of CCR7 ligands (63,64,144) and ICAM-1 (145) and brings T cells into contact with a large number of dendritic cells. Indeed, it is estimated that a single dendritic cell can interact with up to 5000 T cells per hour (141) and each T cells scans approximately 150-300 dendritic cells per lymph node transit (126). Thus, the spatial co- localisation of T cells and dendritic cells in the paracortex combined with high T cell motility promotes efficient scanning of the immune repertoire for cognate T cells.

1.2.2.2.2.2 B cells Like T cells in the paracortex, B cells are highly motile in the follicles (108,139) and this motility is similarly dependent on chemokine signalling (108,146). There is a directional aspect to the overall motility exhibited by B cells as they enter the base of a follicle and progressively move superficially through the follicle with time (107,146). It is thought that this motility enables B cells to scan the follicle for cognate antigen present in the follicle (Section 1.2.4.1). B cell

motility may also help maintain homeostasis of the follicle as B cell-dependent lymphotoxin signalling is required for the survival and maintenance of both follicular dendritic cells and the subcapsular sinus macrophages that overlie the follicle (61,147). Thus, motile B cells simultaneously scan the follicle for cognate antigen and maintain the structure of the lymph node follicle.

1.2.2.3 Lymphocyte egress The egress of lymphocytes out of the lymph node parenchyma and into efferent lymph depends upon a balance of egress and retention factors. The lipid sphingosine-1 phosphate (S1P) is the major egress factor. An S1P concentration gradient exists between the low S1P concentrations of the lymph node parenchyma and the high S1P concentrations maintained in blood and lymph by erythrocytes and lymphatic endothelial cells respectively (89–91,148,149). Disruption of this concentration gradient impairs the egress of lymphocytes from lymph nodes and thereby induces lymphopenia (148). Moreover, deletion or downregulation of sphingosine-1-phosphate receptor 1 (S1PR1) on lymphocytes impairs their egress and induces lymphopenia (150–152)3. Indeed, lymphocytes downregulate and upregulate S1PR1 to enter and egress from lymph nodes respectively (130,146,152). Lymphocytes predominantly egress the lymph node by parenchyma by transmigrating into the cortical lymphatic sinuses (83,84,146), although there is evidence that lymphocytes can also egress via the medullary lymphatic sinuses (82). With regards to precise mechanism by which S1P promotes egress, intravital imaging suggests that S1PR1-deficient T cells do not exhibit S1P-dependent chemotaxis to the cortical sinus endothelium4; rather S1PR1 is required to facilitate the transmigration of T cells across this endothelium (83).

In contrast to the deletion of S1PR1, deletion or antagonism of the chemokine receptors CCR7 and CXCR4 increases the rate of T cell and B cell egress (65,153). The chemokines that bind these receptors are therefore considered retention factors. The retention promoting effect of these chemokines can be modulated as there is evidence that B cells become progressively insensitive to these chemokines as they transit through the lymph node (107). Moreover, the agonism of β2 adrenoceptors on lymphocytes potentiates signalling via CCR7 and CXCR4 and thereby promotes their retention in the lymph node (153,154). The egress of lymphocytes

3 Sinha et al (146) argue that neither S1P or S1PR1 are required for the egress of B cells on the basis that an S1PR1 antagonist is unable to inhibit B cell S1P chemotaxis in vitro. However, the fact that S1PR1- deficient B cells exhibit impaired egress from lymph nodes demonstrates that S1PR1 is necessary for B cell egress in vivo (150,152) 4 Although S1P concentration gradients between different regions of the lymph node parenchyma have been described (90). 42

from lymph nodes therefore depends upon a fine and shifting balance of egress and retention factors.

1.2.2.4 Regulation of lymphocyte recirculation It is apparent from the three previous sections that lymphocyte recirculation is dependent upon a series of complex processes. There is increasing evidence that these processes are integrated and subject to regulation. Indeed, the rates of lymphocyte entry and egress have been shown to exhibit reciprocal patterns of diurnal variation that result in lymph nodes accumulating lymphocytes during the active dark phase and losing lymphocytes during the inactive light phase of a 12 hour light/dark cycle (154,155). This diurnal variation in lymph node cellularity is associated with corresponding changes in the expression of the retention factor CCR7 and the egress factor S1PR1 (154,155). These findings therefore illustrate that the rates of lymphocyte egress and entry are subjected to co-ordinated regulated mechanisms. In addition, that finding that the specific deletion of the clock gene Bmal1 within T cells is sufficient to ablate the diurnal variation in lymph node T cell numbers (155) suggests that lymph node cellularity is intrinsically regulated by lymphocytes. This theory proposes that lymphocytes determine their own entry and egress rates (and thereby lymph node cellularity) by modulating their sensitivity to retention and egress factors. However, Mionnet et al (131) argue that the lymph node itself also regulates the entry and egress of lymphocytes. This is because they provide evidence to suggest that the blockade of lymphocyte egress results in a corresponding reduction in lymphocyte entry5. They theorise that this reflects a competition for physical space within the lymph node, whereby lymphocyte egress is required to ‘make space’ for lymphocytes to enter via HEVs. These findings therefore suggest that diurnal fluctuations in lymph node cellularity must be permitted by corresponding changes in lymph node volume.

Another notable feature of lymphocyte recirculation is the fact that lymphocyte subsets differ in their rates of lymph node transit, with CD4 T cells transiting faster than CD8 T cells and both T cell subsets transiting faster than B cells (125,126). This likely reflects differing antigen surveillance requirements of these lymphocyte subsets. Logic dictates that these different transit times require corresponding differences in entry and egress rates to prevent one lymphocyte subset displacing another. There is evidence to suggest this is the case as the entry

5 This accords with a study demonstrating that the disruption of S1P-dependent egress does not cause an increase in lymph node cellularity (148), although others have shown that this does increase lymph node cellularity (155). 43

(107) and egress rates (125) of B cells are lower than that of T cells but the precise determinants of these differences are unclear. One possibility is that lymphocyte subsets differ in their sensitivity to retention and egress factors. Overall, it is clear that there are still important gaps in the current understanding of how lymph node cellularity and composition are regulated.

1.2.3 Trafficking and distribution of antigen in the draining lymph node Lymph nodes must concentrate and process antigen in order to facilitate its presentation to cognate lymphocytes. Antigen can either passively drain into the lymph node in the flow of afferent lymph or can be actively trafficked into the lymph node within migratory cells.

1.2.3.1 Lymph-borne antigen

1.2.3.1.1 Determinants of lymphatic antigen drainage Numerous murine studies illustrate that afferent lymph delivers protein antigens, viruses and bacteria to the primary dLN within minutes of their subcutaneous injection (71,74,156–160). Moreover, MRI contrast has been used to show that lymphatic drainage is similarly rapid in humans (161). Although tissue oedema promotes the delivery of lymph-borne antigen to the lymph node (162), such drainage does not require the hydraulic pressure generated by the process of injection (71). However, one determinant of such lymphatic drainage is antigen size. Indeed, 20nm-diameter nanoparticles injected into the murine footpad reach the draining popliteal lymph node within 2 hours, whilst the drainage of 500nm-diameter nanoparticles takes between 2 and 24 hours and is dependent on dendritic cells (163). Another determinant is the access of antigen to the tissue interstitium. This is evidenced by the fact that antigens topically applied to a mucosal surface or an abraded skin surface do not to exhibit rapid drainage to the dLN (164,165). Nevertheless, rapid lymph-borne antigen drainage occurs in numerous contexts and notably is sufficient to induce adaptive immune responses (74,158,166,167).

1.2.3.1.2 Distribution of lymph-borne antigen within the draining lymph node Lymph-borne antigen rapidly distributes throughout the subcapsular, medullary and cortical lymphatic sinuses of the dLN (71,84,159,160,168,169) and is rapidly captured by resident macrophages populating the subcapsular and medullary sinuses (159,169–171). Depletion of

these macrophages results in the dissemination of pathogens from the dLN (159,170–173), suggesting that such antigen/pathogen capture is a key component of the barrier function of the dLN. It is also thought to promote adaptive immune responses as subcapsular sinus macrophages help initiate adaptive immune responses by transferring intact antigen to B cells in underlying follicles (159,174,175). Dendritic cells have been shown to perform similar functions. For example, a specialised set of lymph sinus dendritic cells use long motile processes to capture lymph-borne antigen and rapidly present it to cognate T cells (71). Moreover, a subset of medullary dendritic cells use SIGNR1 to capture antigen in the medulla, which they subsequently traffic to the follicles to initiate humoral immune responses (168,169). Thus, a diverse range of phagocytes capture antigen in lymphatic sinuses to both limit the further dissemination of antigen and trigger adaptive immune responses.

Low molecular weight antigens (<70kDa) that are not captured by the phagocytes that line the lymphatic sinuses can enter the conduit networks of the paracortex and follicles (Section 1.2.1.2.4). Dendritic cells in the paracortex as well as B cells and FDCs in the follicles can sample antigen from these conduits (118,122) and such conduit drainage promotes rapid B cell activation (122). Indeed, protease-dependent cleavage of large particulate antigen in the subcapsular sinus has been shown to promote B cell responses, potentially by increasing the drainage of cleaved antigens into these conduit systems (157). In addition to the known role of conduits, protein antigens have also been recently shown to exhibit conduit-independent penetration of the lymphatic sinus endothelium (74). This results in the formation of antigen gradients that extend from the lymphatic sinuses into the lymph node parenchyma (74). Whilst conduits are important for the acquisition of antigen by B cells, the acquisition of lymph-borne antigen by paracortical dendritic cells is much more dependent on this conduit-independent antigen dispersal (74). However, it has also been shown that small numbers of virions are able to rapidly distribute through the conduit network despite its 70kDa size limit and thereby rapidly infect conduit-adjacent paracortical DCs (120). The authors of this study hypothesise that such rapid but limited virion distribution may prove beneficial in terms of its effect upon accelerating the onset of T cell activation (120). Overall, it is clear that a multitude of processes operate in parallel to facilitate the capture and distribution of lymph-borne antigen to antigen- presenting cells and cognate lymphocytes.

1.2.3.2 Cellular trafficking of antigen

1.2.3.2.1 Dendritic cells

1.2.3.2.2 Dendritic cell classification The term dendritic cell (DC) can be used to describe a range of professional antigen presenting cells. In mice, DCs can be divided into conventional and non-conventional DCs on the basis of their ontogeny (176). The differentiation of the conventional dendritic cells (cDCs) is dictated by the transcription factor zDC (177) and the cDCs can be subdivided further into cDC1s and cDC2s. The cDC1s consist of CD8α+ve lymphoid resident DCs and CD103+ve migratory dendritic cells that are specialised for cross-presentation to CD8 T cells and whose differentiation is driven by the transcription factor Batf3 (178–181).The development of cDC2s is less well- defined but is promoted by the transcription factor Irf4 and these cells are more associated with the presentation of antigen to CD4 T cells (74,176,182,183). Notably, these differences in function are reflected by marked differences in their localisation within lymph nodes, with cDC1s concentrated in central paracortical regions and cDC2s distributed more peripherally and adjacent to the lymphatic sinuses (71,73–75,167,168,184).

The non-conventional dendritic cells include monocyte-derived dendritic cells, plasmacytoid dendritic cells and embryonically-derived macrophage-like cells such as Langerhans cells (185). Of these, monocyte derived DCs are of relevance to this thesis and are discussed further in Section 1.3.3.2. However, it is important to note that research continues to refine and redefine dendritic cell classification. For example, there is a subset of monocyte-derived dendritic cells that phenotypically resemble cDC2s but cross-present antigen like cDC1s (186). Moreover, an extra layer of complexity is introduced by the fact that these DC cell subsets have been shown to co-operate in various contexts (184,187–191). The classification of dendritic cells and their functions is therefore an evolving field with scope for further research.

1.2.3.2.3 Dendritic cell trafficking Dendritic cells are the archetypal traffickers of antigen from peripheral tissues to the dLN. Dendritic cells continually migrate from the skin to the dLN in the steady state (125,192) and the rate of such migration is increased by inflammatory stimuli (193). The migration of dendritic cells to the dLN is dependent upon CCR7 (192,194,195), as the CCR7 ligand CCL21 facilitates both the entry and migration of dendritic cells within afferent lymphatic vessels (196,197) as well as the migration of dendritic cells through the floor of the subcapsular sinus into the paracortex (85,88). Once within the paracortex, migratory dendritic cells can present antigen to cognate T cells (164,165,188,191,198). Dendritic cells are also capable of 46

transferring native antigen to B cells (199,200) but it is not clear to what extent this function is performed by lymph node resident or migratory dendritic cells.

Antigen arrives in the dLN in two sequential waves, the first being the rapid cell-free drainage of lymph-borne antigen described in Section 1.2.3.1 and the second being the migration of antigen-bearing dendritic cells (198). Some studies illustrate that this second wave of antigen- bearing migratory dendritic cells is necessary for the induction of effective T cell responses (188,191,198), whilst other studies demonstrate that it is either partially or completely redundant in this regard (74,158,166,167). There is evidence to suggest that migratory dendritic cells play a more important role in T cell priming when antigen does not have ready access to afferent lymphatics, either due to the route of infection (164,165) or due to the size of antigen (163).

1.2.3.2.4 Neutrophils and monocytes

In addition to dendritic cells, there is evidence to suggest that antigen can be trafficked to the dLN by neutrophils and monocytes. Indeed, a wide variety of inflammatory stimuli induce the appearance of large numbers of antigen-bearing neutrophils (201–203) and monocytes (50,187,189,204–208) in the dLN. Moreover, antigen-bearing neutrophils and monocytes have been visualised in afferent lymphatics (201,209,210) or sampled from afferent lymph (211– 214,214–217) during inflammation. However, neutrophils and monocytes appear to predominantly enter lymph nodes via HEVs (Sections 1.3.2.1, 1.3.3.1.2 and 1.3.3.2.2) and thus their uptake of antigen likely represents the phagocytosis of lymph-borne antigen in the dLN. Indeed, there is evidence to suggest that afferent lymphatics express the chemokine- scavenging receptor D6 as a mechanism by which to limit the lymphatic trafficking of inflammatory myeloid cells but not dendritic cells during inflammation (218). Thus, whilst neutrophils and monocytes likely traffic antigen to the dLN, the extent and significance of this trafficking relative to dendritic cell or lymph-borne antigen is unknown.

1.2.4 Activation of lymphocytes in the draining lymph node

1.2.4.1 B cells B cells recognise antigen in its native form using the B cell receptor (BCR) and can acquire both soluble and membrane-bound antigen (219). Intact antigen can be presented to naïve B cells by a number of cells in the dLN. Upon arrival into the lymph node parenchyma, B cells can

acquire cognate antigen from dendritic cells surrounding high endothelial venules (199). B cells can also recognise cognate antigen trafficked into the follicle by overlying subcapsular sinus macrophages (159,174), other B cells (175), dendritic cells (168,169) and the follicular conduit network (122) as well as antigen stored on the surface of follicular dendritic cells (113,114). Once activated, B cells rapidly internalise and degrade cognate antigen to facilitate the presentation of antigenic peptides complexed with MHC II to cognate CD4 T cells (156). Simultaneously, activated B cells exhibit CCR7-dependent migration to the follicle boundary in order to interact with activated cognate T cells in the interfollicular regions of the paracortex (220–222). Cognate B and T cells exhibit extensive interactions in the interfollicular region for 2-3 days following immunisation before cognate B cells migrate back into the follicle to establish germinal centres or migrate to a region under the subcapsular sinus to differentiate into plasmablasts (221). In summary, antigen is rapidly acquired by cognate B cells, which then interact with cognate T cells to initiate humoral immune responses.

1.2.4.2 T cells

1.2.4.2.1 Dynamics of T cell activation T cells use the T cell receptor (TCR) to recognise antigen-derived peptides presented by the major histocompatibility complex (MHC) and continually survey dendritic cells in the paracortex for cognate antigen (Section 1.2.2.2.2.1). Intravital imaging demonstrates that T cells initially make brief contacts with multiple dendritic cells presenting cognate antigen before reducing their motility and forming a stable conjugate with a single antigen-presenting dendritic cell (140). The former brief interactions and latter stable conjugates have been defined as kinapses and synapses respectively, with rapid synapse formation promoted by high affinity antigens (143). T cells bound to antigen-presenting dendritic cells upregulate CD69 and CD25 and produce IL-2 and IFNγ (140). Eventually the T cell becomes refractory to further TCR stimulation and dissociates from the dendritic cell, allowing it to regain its motility and undergo vigorous proliferation (140,223). These processes occur rapidly in the dLN. Clusters of activated cognate T cells and dendritic cells can be observed within 24 hours of immunisation/infection (71,74,165,224,225) and the proliferation of cognate T cells is first detectable between 2-3 days following challenge with protein antigen/adjuvant formulations (50,220,226), viruses (165) bacteria (227–229) and fungi (187). Nevertheless, it must be noted that all these studies assess T cell activation and proliferation following the adoptive transfer of large numbers of antigen-specific T cells, which artificially increases the likelihood of their encounter with dendritic cells presenting cognate antigen. Moreover, there is evidence that

some pathogens delay the onset of T cell activation as mice infected with M. tuberculosis do not exhibit the proliferation of adoptively transferred cognate T cells in the dLN until at least 7 days following infection (230). However, overall, the findings described demonstrate that the activation of cognate T cells is a rapid and efficient process.

1.2.4.2.2 Anatomy of T cell activation T cell activation does not occur uniformly throughout the paracortex. Rather several studies have shown that naïve T cells are preferentially activated in outer regions of the paracortex and interfollicular regions (71,224,231,232). This may be due to the propensity of lymph node resident dendritic cells to acquire antigen in regions adjacent to the lymphatic sinuses (71,74,231) and of migratory dendritic cells to localise around HEVs in the outer paracortex (59,224). Further studies have demonstrated that the activation of naïve CD4 and CD8 T cells is anatomically segregated, with naïve CD4 T cells predominantly activated in the outer regions of the paracortex adjacent to the B cell follicles and lymphatic sinuses, and naïve CD8 T cells predominantly activated in deeper regions of the paracortex (74,76,165,181,184)6. This anatomical segregation of naïve CD4 and CD8 T cell activation reflects their interaction with distinct subtypes of dendritic cells (74,165,181,184), with CD4 T cells preferentially activated by CD11b+ve MHC II specialised cDC2 dendritic cells and CD8 T cells by MHC class I specialised cDC1 dendritic cells (74,76). Moreover, the activation of CD4 T cells appears to be prioritised as CD4 T cell activation has been shown to precede that of CD8 T cells (165) and to require lower doses of antigen (74). This accords with the fact that CD4 T cells are required to license activation of CD8 T cells, a process that requires the subsequent interaction of both CD4 and CD8 T cells with a subset of cross-presenting XCR1+ve dendritic cells in the peripheral paracortex (165,184). Indeed, ablation of the peripheral positioning of CD4 T cells compromises CD8 T cell activation and impairs cell-mediated immunity (76). Overall, it appears that that the priming of T cells is spatiotemporally coordinated in the dLN.

1.2.4.2.3 T cell differentiation Following activation by cognate antigen, CD4 T cells can differentiate into a variety of effector T cell subsets. 5 subsets have been well described thus far; Th1, Th2, Th17, iTreg and Tfh cells. Each of these subsets exhibit specialised effector functions and can be characterised by the

6 Nevertheless, CD8 T cell activation has also been shown to occur in the cortical ridge, peripheral paracortex and interfollicular regions in other contexts (70,71,231). 49

expression of subset-specific transcription factors and hallmark cytokines (233–238). Many studies have illustrated the importance of polarising cytokines in determining the differentiation fate of activated T cells. For example, IFNγ and IL-12 play key roles in the Th1 differentiation of T cells (239–243). However, recent studies also demonstrate that the duration and strength of TCR signalling and co-stimulation are important determinants of differentiation fate that precede the effects of polarising cytokines (244–246). Precisely how this complex array of factors is integrated in order to determine the differentiation fate of T cells is unclear.

There is growing evidence to suggest that the migration of activated T cells to specific regions of the dLN is an important part of their differentiation. Indeed, CXCR3 is required for both the migration of activated T cells to interfollicular and medullary zones and their Th1 differentiation (247) and CXCR5 facilitates the migration of dendritic cells and T cells to perifollicular regions where Th2 differentiation occurs (248). Similarly, Tfh differentiation requires the interaction of activated T cells with cognate B cells in interfollicular regions (221). It has thus been proposed that T cell differentiation occurs in distinct anatomical niches within the dLN (249,250). Such niches could expose T cells to polarising cytokines, although this theory is somewhat undermined by the fact that IFNγ and IL-4 have been shown to permeate throughout the entire dLN (251). Alternatively these niches could facilitate cellular interactions that promote T cell differentiation as has been shown with regard to B cells and Tfh and Th2 responses (221,248). Overall, diverse and overlapping factors appear to regulate T cell differentiation in the dLN and these processes warrant further study. Indeed, similar factors may determine effector and memory cell formation as studies of T cell activation in the spleen have shown that the expression of CXCR3 promotes the localisation of antigen-specific CD8 T cells in antigen-rich areas of the spleen and thereby their differentiation into effector T cells (252,253).

1.3 Adjuvants and innate immune pathways in the draining lymph node

1.3.1 Adjuvants

Vaccines bestow protection through the induction of adaptive immune responses and the formation of immunological memory. The understanding that such protection required exposure to material from the chosen pathogen (i.e. antigens) was sufficient for the development of live attenuated and whole-cell inactivated vaccines in the 19th century (Section 1.1.1). However, in the 20th century, immunologists found that purified antigens were often poorly immunogenic and required combination with adjuvants to induce robust adaptive immune responses (16,254,255). Adjuvants can be broadly defined as any substance that potentiates the immunogenicity of a vaccine. Despite the extensive use of adjuvants in vaccine formulation and immunological research throughout the 20th century, the mechanistic underpinnings of adjuvants were largely unknown; with Charles Janeway famously dubbing them as ‘the immunologists dirty little secret’ in 1989 (254). In the same seminal article, Janeway predicted the discovery of pattern recognition receptors and hypothesised that adjuvants work by licensing antigen-presenting cells to provide the co-stimulatory signals required for lymphocyte activation (254). As predicted, the ensuing 30 years have revolutionised our understanding of innate immune recognition and these insights have driven the development of new vaccine adjuvants.

Adjuvants differ markedly in their structure and composition. Alum is the most widely used adjuvant in human vaccines and is a collective term to describe various aluminium salts. Alum’s adjuvant action was serendipitously discovered in the 1920s as aluminium salts were used to purify antigen preparations (16,256). Another very popularly used adjuvant in the 20th century was a mixture of mineral oil and killed mycobacteria called complete Freund’s adjuvant (CFA) (257), although its use has always been restricted to research purposes on account of its side effect profile. Modern adjuvants have diversified markedly to include oil-in- water emulsions such as MF-59 and TLR agonists such as monophosphoryl lipid A (MPL). In the past two decades it has been discovered that many adjuvants exhibit additive and synergistic properties when combined and thus modern adjuvant design is characterised by such adjuvant combinations (258). A pertinent example is the adjuvant system AS01, which combines the adjuvants monophosphoryl lipid A (MPL, a TLR4 ligand) and QS-21 (a saponin), induces potent T cell responses and has recently been licensed for use in human vaccines against herpes zoster and malaria (259). Table 1.1 details important features of AS01 and other commonly studied adjuvants. Nevertheless, alum is still by far the most commonly used adjuvant, with

MF-59 being the only other adjuvant included in the routine UK immunisation schedule (Appendix 1).

1.3.1.1 Adjuvant mechanisms

1.3.1.1.1 Common features Consistent with the early history of vaccines (Section 1.1.1), adjuvants were first empirically developed with little understanding as to how they potentiated adaptive immune responses (254). However, our understanding of adjuvants has progressed markedly over the past 30 years and several common features have been identified. Firstly, it is clear that adjuvants must be spatiotemporally associated with their antigen (185,260–262). Indeed, adjuvants remain localised to the site of immunisation and dLN (204,263–266) and are not thought to distribute systemically. In the case of alum, its adsorption to antigen is considered a key requirement of its immunogenicity (261,267) although the strict importance of adsorption relative to simple physical association has been challenged (268,269). Whilst there is evidence that the direct conjugation of adjuvants to antigen can increase immunogenicity (270), in other contexts it is sufficient for the adjuvant to be delivered to the site of immunisation at the same time as the antigen (260,262). Nevertheless, the physical properties of an adjuvant can be important as some adjuvants are capable of altering the distribution of antigen within secondary lymphoid organs. For example, the phagocytosis of alum-antigen complexes by follicular B cells is associated with increased humoral immune responses relative to a soluble antigen/adjuvant formulation (271). Furthermore, oil in water emulsions target antigen to interfollicular regions of the dLN and this is associated with potentiated T cell responses (272). It has also been long thought that alum facilitates the slow release of antigen from the site of immunisation (the so- called depot theory) but this has been discounted (166). Nevertheless, it is clear that the spatiotemporal association of antigen and adjuvant is one common determinant of adjuvant action.

Another common feature of adjuvants is their capacity to elicit inflammation. Indeed, all classes of adjuvant have been shown to drive inflammatory gene expression, cytokine production and innate cell recruitment to a greater or lesser extent at the site of immunisation (50,51,260,262,265,273–277) and in many cases the dLN (50,204,242,260,262,265,266,274,277–280). These innate immune pathways contribute to adjuvant action in various ways. Firstly, adjuvants are associated with immune cell infiltration and increased cellular uptake of antigen at the site of immunisation and/or in the dLN (50,51,204,260,262,275,279). Secondly, as Janeway predicted, adjuvants are associated with 52

increased expression of co-stimulatory markers on antigen-presenting cells (51,242,263,265,277,280) and in some instances, have also been shown to drive the differentiation of monocytes into dendritic cells (50,263). This is in combination with the aforementioned cell recruitment is thought to boost antigen presentation capacity in the dLN. Finally, there is evidence that the chemokines and cytokines induced by inflammatory stimuli such as adjuvants in the dLN serve to orchestrate the recruitment of naïve T cells and/or provide key polarising signals that drive their differentiation (242,247,272,277–279). It is in this respect that adjuvants appear to differ most and these differences are discussed in the next section.

1.3.1.1.2 Differentiating features Adjuvants differ markedly in the degree and manner to which they induce inflammation and potentiate the developing adaptive immune response (Table 1.1). In terms of inflammation, these are evidenced by different profiles of inflammatory gene expression (273,274) and differences in the relative importance of different inflammatory pathways and cells in their adjuvant action (Table 1.1). For example, alum elicits minimal inflammation at the site of inflammation and induces weak T cell responses relative to other adjuvants but is nevertheless sufficient to potentiate antibody responses (262,280–283). In contrast, MF-59 elicits a greater inflammatory response at both the site of immunisation and in the dLN and yields higher T cell responses and antibody titres (51,204,273–275,284,285). In addition, MF59 has been shown to elicit cross-protective antibody responses in the context of influenza immunisation (286–288). Despite their common use, the inflammatory pathways engaged by alum and MF59 are only partially understood. Alum has been shown to activate the NALP3 inflammasome via phagosomal destabilisation (185,289), although there are conflicting reports as to whether this contributes to its adjuvant action (185,290). In contrast, MF-59’s activity is independent of the inflammasome but relies upon MyD88, an intracellular adapter central to TLR and IL-1 signalling (276). MF-59 itself does not directly agonise TLRs (276) but may indirectly engage PRRs via the release of DAMPs such as ATP, which has been shown to contribute to its adjuvant effect (291). Moreover, MF-59 has been shown to accumulate in the macrophage- rich subcapsular and medullary compartments of the dLN and thus may mediate its adjuvant activity through activation of lymph node resident macrophages, as has been illustrated for other adjuvants (265,266). Indeed, it is the capacity to target antigen and adjuvants to peripheral regions of the dLN that appears to underlie their adjuvant action of oil in water emulsions (272).

In addition to alum and MF-59, various TLR agonists (e.g. MPL, CpG) have been shown to exhibit adjuvant activity, thereby supporting the importance of PRR agonism in adjuvant action (241,242,260,274). Notably, the combination of TLR agonists with each other or with other adjuvants results in additive or synergistic effects on both the inflammatory response and the developing adaptive immune response (277,278,281,284,292–294). For example, the addition of the TLR-9 ligand CpG to MF-59 results in the strong induction of a Th1 T cell response (284). This property of CpG has been attributed to the infiltration of IL-12 producing monocytes into the dLN (242). Similarly, the adjuvant action of the liposome-based TLR-4 ligand/saponin combination adjuvant AS01 is dependent upon TLR-4 signalling in haematopoietic cells (295). Both AS01 and GLA-SE (a TLR-ligand/emulsion combination adjuvant) induce potent th1 T cell responses and with these adjuvants the rapid production of IFNγ by NK cells and memory CD8 T cells within the dLN is key (277–279,296). These studies provide evidence that lymph node resident macrophages, type I interferons, IL-12 and IL-18 all contribute to this wave of early IFNγ production (277–279,296). Moreover, there is evidence that the interferon-driven chemokines CXCL9 and CXCL10 orchestrate the Th1 response by directing the intranodal migration of T cells (247,272). The production of IL-12 family cytokine IL-27 by lymph node dendritic cells is another factor shown to correlate with and contribute to T cell responses driven by a variety of PAMP-based adjuvants (297,298). In summary, whilst adjuvants share several common features, distinct innate immune pathways appear to drive the manner in which they shape the developing adaptive immune response.

1.3.1.2 Outstanding questions for adjuvant research Adjuvant research and development has progressed markedly over the past three decades, with the vaccine adjuvants AS01, AS03, AS04 and CpG licensed for use in several human vaccines (259). Most notable is probably the AS01-adjuvanted vaccine RTS,S/AS01 (Mosquirix), which is the first licensed vaccine against malaria (299,300). In addition, AS01-adjuvanted vaccines against HIV and TB have also been trialled (301–303). Whilst some results are encouraging, these new vaccine candidates have thus far not been shown to bestow full protection against these important pathogens. Indeed, RTS,S/AS01 has only been shown to bestow 26-51%7 protective efficacy against malaria (300). There is therefore still an unmet need for new adjuvants and therefore research informing adjuvant design.

7 depending on the immunisation regimen and follow up period (300)

The combination of adjuvants into adjuvant systems was a rationale advance in adjuvant design as it better represents the fact that pathogens activate multiple PRRs (304). The fact that certain adjuvant combinations exhibit synergistic effects upon the ensuing inflammatory and immune responses validates this approach (277,278,281,284,292,294). It is now a question of better understanding the pathways driving these adjuvants and determining whether or not they can be improved further through the activation or repression of other inflammatory pathways. The increasing use of high throughput technologies such as microarrays and transcriptomics has been particularly beneficial in this respect as they can be used to compare the biological signatures driven by different vaccines/adjuvants (273,305) and even establish predictors of protection (283). These complex biological networks can be explored and rationalised using computational models (306). Nevertheless, such approaches still need to be complemented with in vivo experiments that inform our understanding of key pathways.

A particularly pertinent pathway discussed in Section 1.3.1.1.2 is the rapid production of IFNγ within the dLN that is associated with the potentiation of th1 T cell responses observed following challenge with the combination adjuvants AS01 and GLA-SE (277–279) . Notably, this phenomenon has also been shown to occur in models of infection (72,90,172,307) and is mirrored by a similarly rapid peak in IFNγ concentration in the blood of human volunteers administered with AS01-adjuvanted vaccines (277,308–310). Moreover, in the case of RTS,S/AS01 this rapid peak in serum IFNγ is somewhat correlated with protection. This suggests that this pathway may be an important adjuvant pathway that could potentially also serve as a correlate of adjuvant activity. That such correlates exist is supported by a recent murine study demonstrating a strong and reliable correlation between the magnitude of early IL-27 production in the dLN and the magnitude of the ensuing T cell responses across variety of PAMP-based adjuvants (298).

A common theme of the preceding discussion is that the dLN often serves as a crucial site of adjuvant action. This is evidenced by the physical drainage of certain adjuvants to the dLN (204,263–266,311) as well as the induction of intranodal gene expression, cellular infiltration and cytokine production (50,204,242,260,262,265,266,274,277–280). The rapid infiltration of neutrophils and monocytes into the dLN is a feature of various adjuvants (204,242,262,263,265,277,278,280,312) and in the case of CFA and CpG they have been shown to modulate the adjuvant-driven immune response (242,312). Furthermore, TLR-4 signalling within haematopoietic cells is required for the adjuvant action of AS01 (295) and immunomodulatory properties have been ascribed to lymph node infiltrating neutrophils and monocytes in various models of infection (Sections 1.3.3.1 and 1.3.3.2). Thus, the question as 55

to how neutrophils and monocytes interact with currently identified adjuvant-driven innate immune pathways within the dLN serves as the focus of this thesis.

Table 1.1 Notable adjuvants and their inflammatory properties Adjuvant Constitution Non-Redundant factors Innate Immune Processes within the Adaptive Immune Responses Licensed Draining Lymph Node Potentiated Vaccines

Alum Aluminium salts Nalp3 inflammasome (185) – disputed Minimal cell infiltration and inflammatory Antibody responses Numerous (see (276,313) gene expression relative to other adjuvants (185,262,265,276,281,284,314, Appendix 1) Type I IFN (small contribution)(274) (204,262,273,274) 315) Uric acid (50), although disputed (185) Weak T cell responses RhoG-dependent phagocytosis of alum (51,281,282) – Th2 bias (50) aggregates by B cells (271) MF59 Oil in water MyD88 (although does not agonise TLRs) Induction of inflammatory gene Antibody responses Fluad emulsion of (276) expression, cytokine production and cell (204,274,276,284) squalene, span- Extracellular ATP (291) infiltration (neutrophils, monocytes, T cell responses (275,284) 85, tween-80 and ASC – although this finding is not dendritic cells) (51,204,263,273) N.B. Combination with CpG citrate (275) replicated across mouse strains (316) results in th1 T cell response + shift in antibody isotype to IgG2a (284) MPL Monophosphoryl No data Increased NFκB activity, cell infiltration Antibody Responses (260) N/A – see AS01 lipid A (TLR4 (monocytes, dendritic cells (260,280)) T cell responses (260,277) agonist) CpG CpG CCR2, Flt3, IL-12 produced by Induction of inflammatory gene Antibody responses (274,292) HEPLISAV-B Oligodeoxynucleo inflammatory monocytes (242). expression, cytokine production and cell T cell responses (Th1 bias) (242) (FDA approved, tides (TLR9 Type I IFN (small contribution) (274) infiltration/expansion (monocytes, pDCs) awaiting EMA agonist) (242,280) approval) QS-21 Saponin in Lymph node resident macrophages Induction of inflammatory gene Antibody Responses (265) N/A – See AS01 liposomes (clodronate), MyD88, Caspase 1, Baft3, expression, cell infiltration (including T cell responses (265) HMGB1 (265) neutrophils, monocytes, dendritic cells). HMGB1 (DAMP) release (265) AS01 MPL (TLR4 IFNγ, IL-12 for T cell response (277) Induction of inflammatory gene Antibody responses Mosquirix, agonist) + IL-18, IL-12 and LN resident macrophages expression, strong IFNγ signature not seen (277,281,282). IFNγ antagonism Shingrix liposomal QS-21 (clodronate) for early IFN production with MPL or QS-21 alone (synergism). Cell reduces IgG2c titres (277) (277) infiltration (neutrophils, monocytes) (277)

T cell responses (277,281,282) - Th1 bias (277,281) N.B. MPL and QS-21 exhibit synergistic effects (277) AS03 Alpha-tocopherol No data Increased NFκB signalling, inflammatory Antibody Responses (262,282) Pandemrix, and squalene in gene expression, cytokine production, cell T cell responses (262,282) Arepanrix an oil in water infiltration (neutrophils, eosinophils) (262) emulsion AS04 MPL + Alum No data Cell infiltration (monocytes dendritic cells) Antibody Responses Fendrix, (260,282,315) cervarix T cell responses (260,282,315) GLA-SE Glucopyranosyl MyD88/TRIF, IFNγ, IL-12, IL-18, Caspase- Production of inflammatory cytokines – Antibody Responses Not yet lipid A (TLR 4 1, LN resident macrophages. Type I IFN rapid IL-18 driven IFNγ production by CD8 T (266,279,317,318) – IgG1 and licensed, trialled agonist) stable (266,278,279,317) cells and neutrophils. Type I interferons IgG2c (279,317) for candidate emulsion also produced (266,278,279) Th1 T cell responses (278,279) TB vaccine (319) (squalene) N.B. Please note that the term clodronate refers to roles for lymph node resident macrophages determined by their depletion with clodronate liposomes.

1.3.2 Innate immune pathways in the draining lymph node

The initiation of adaptive immune responses is time-consuming as it requires the activation, proliferation and differentiation of the small numbers of lymphocytes that bear cognate antigen receptors. In contrast, the innate immune response is rapid and relies upon a system of pattern recognition, in which germ-line encoded pattern recognition receptors (PRRs) recognise structures common to invading pathogens; so called pathogen-associated molecular patterns (PAMPS) (320,321). The agonism of PRRs rapidly elicits acute inflammation, which is typified by processes such as the production of inflammatory cytokines, increased vascular permeability and the recruitment and activation of innate immune cells such as neutrophils, monocytes, macrophages and natural killer cells (320,321). Acute inflammation and innate immune pathways can also profoundly affect the dLN. It is increasingly recognised that in addition to orchestrating the developing adaptive immune response, the dLN serves as a barrier to the dissemination of pathogens that escape infected tissue via afferent lymph. Indeed, several cardinal inflammatory processes such as macrophage activation, cytokine production and neutrophil infiltration have also been described within the dLN. The following sections will review these and other intranodal innate immune pathways (depicted in Figure 1.4) and describe their impact upon concurrently developing adaptive immune responses within the dLN.

1.3.2.1 Innate immune pathways within afferent lymph Afferent lymphatics serve as the conduit between the site of inflammation and the dLN. As discussed in Section 1.2.3.1, afferent lymphatics facilitate the free drainage of antigens ranging from proteins to whole bacteria to the dLN within minutes of inoculation (71,74,156–160). The extent to which the afferent lymph also exports the inflammatory milieu at the site of the inflammation to the dLN is a much-debated question. The direct analysis of afferent lymph is precluded by size constraints in murine studies and thus has mostly been studied by cannulation of modified afferent lymphatics in ovine models. In the 1970s it was established that a subcutaneous challenge with heat-killed E. coli induced sharp increases in neutrophils and inflammatory prostanoids in draining afferent lymph (211). Further studies conducted in the past decade have demonstrated that acute increases in neutrophil trafficking within afferent lymph is a feature of various inflammatory stimuli, including, MPL (212), poly IC (213– 215), CpG (216) and the novel combination adjuvant AS01 (217,322), although not alum (323). Moreover, several of these stimuli have also been shown to elicit smaller increases in monocytes in afferent lymph (212–215,217). However, no appreciable rises in dendritic cell trafficking have been observed during the first 72 hours in such models (212–217,323). 59

Nevertheless, all three of these cell subsets have been shown to carry antigen in afferent lymph (212,213,215–217,322,323) and to exhibit increased expression of inflammatory genes and cell surface markers (214,215,322,324). Finally, in addition to the direct measurement of increased levels of inflammatory prostanoids in afferent lymph (211), there is also evidence from rodent studies that cytokines (e.g. TNFα) and chemokines (e.g. CCL2, CCL19) are transported to the dLN in afferent lymph (109,325–327) where they gain rapid access to HEVs via the LN conduit system (92,109,118,119,325). Moreover, these lymph-borne chemokines are capable of recruiting lymphocytes and monocytes into the dLN via HEVs (109,325).

The presence of these innate cells and mediators within afferent lymph may be read to suggest that the dLN passively relies upon this lymphatic input for its innate barrier function. This is strongly argued against by numerous studies that demonstrate the rapid activation of LN- resident macrophages by lymph-borne PAMPs (72,170,171,266,328) and the endogenous production of inflammatory mediators within the dLN (70,72,170,171,241,242,247,266,312,328–330). Moreover, imaging studies have demonstrated the mass mobilisation of innate immune cells from high endothelial venules (173,202) and photoactivation experiments have demonstrated that only a small fraction of infiltrating neutrophils and monocytes stem from the site of inflammation, further suggesting that HEVs comprise the major source (209,272). With these findings in mind, the role for afferent lymph can be revised to that of supplying the necessary signals to initiate intranodal innate immune pathways. In the majority of circumstances this is probably achieved by the rapid activation of LN-resident macrophages by lymph-borne PAMPs (72,170,171,266,328). However, Wong et al (331) have demonstrated that migratory Langerhans cells are essential orchestrators of the intranodal innate immune response to ectromelia virus as their absence ablates the usual NK cell and monocyte infiltration required for pathogen control. It is likely that the importance of Langerhans cells in this context reflects poor lymphatic drainage of free virions in this model as migratory dendritic cells are identified as the first infected cells within the dLN and the intranodal inflammatory response takes 24 hours to begin, which is much longer than in other models (331). Nevertheless, it further supports the theory that afferent lymph provides the initial signals that trigger endogenous innate immune pathways within the dLN.

1.3.2.2 Lymph node hypertrophy Inflammatory stimuli induce a rapid increase in the cellularity of the dLN. This process is termed lymph node hypertrophy (96,326,327,332–334). Numerous inflammatory cells and mediators have been shown to contribute to lymph node hypertrophy in various contexts,

including dendritic cells (335,336) mast cells (326,327,332), TNFα (326,327), TLR-9 (337), complement (332), LIGHT (333), inflammasome activation and IL-1β (328,338). Lymph node hypertrophy does not initially require the priming of lymphocytes with cognate antigen (96) but is potentiated by primed T cells (336,339). Thus, hypertrophy of the dLN is a common feature of acute inflammation that is induced by a diverse array of inflammatory mediators.

Lymph node hypertrophy is due to the accumulation of large numbers of naïve non- proliferating lymphocytes (96) and accordingly inflammation induces both increased rates of lymphocyte entry (96,325,340,341) and reduced rates of lymphocyte egress (84,342–344) from the dLN. With regards to entry, inducing fever-range thermal stress has been shown to increase lymphocyte homing through the upregulation of CCL21 and ICAM-1 on the HEV endothelium (341). In addition, dLNs exhibit remodelling and growth of the feed arteriole and HEVs (96,345). With regards to egress, various stimuli have been shown to transiently shut down lymphocyte egress into efferent lymph (216,217,343,344,346), with complement activation, prostaglandin production, TNFα and IL-6 evidenced as contributors to this process in ovine lymphatic cannulation models (343,344,346). Moreover, type I interferon-driven upregulation of CD69 has been shown to impair the transmigration of lymphocytes into the cortical lymphatic sinuses and induce lymphopenia (84,342). The relative importance of increased entry and reduced egress in driving lymphocyte accumulation has not been assessed but the transience of the reduction in egress (342–344) coupled with the growth of HEVs suggests increased lymphocyte entry is the dominant driver. The increased throughput of lymphocytes through the dLN is thought to promote the rate at which the immune repertoire is screened for cognate lymphocytes. Indeed, inhibition of the inflammasome-driven lymphocyte accumulation that occurs following MVA infection results in the defective recruitment and activation of antigen-specific T cells in the dLN (328).

Physical expansion of the dLN is required to accommodate the increase in cellularity induced by inflammatory stimuli. CLEC-2 expressing dendritic cells have been shown to facilitate such physical expansion as the interaction of CLEC2 with podoplanin on fibroblastic reticular cells (FRCs) induces relaxation of the FRC cytoskeleton and thus facilitates stretching of the stromal cell networks that underpin the lymph node parenchyma (334,347). Despite this rapid expansion, the distribution of small antigens via the conduit network is maintained within inflamed lymph nodes (348). Indeed, there is evidence that CD11b+ve cells are recruited to the conduit network to increase antigen sampling from the conduit network in inflamed LN (348). LN hypertrophy is also associated with rapid FRC proliferation, a process triggered by dendritic cells and the trapping of naïve lymphocytes (336). Such proliferation can also be driven by the production of IL-17 by activated Th17 T cells (349). When considered in combination with the 61

aforementioned expansion of lymph node vasculature (335,345) it is apparent that the stromal underpinnings of the dLN are remodelled to facilitate lymph node hypertrophy.

1.3.2.3 Lymph node resident macrophages The CD169+ve F4/80-ve and the CD169+ve F4/80+ve macrophages that line and populate the subcapsular and medullary sinuses are crucial to the barrier function of the dLN8. Indeed, their depletion or deletion results in the systemic dissemination of bacteria and viruses from the dLN into the bloodstream and peripheral organs (72,170,173,350). These macrophages rapidly capture both viral (72,159,168,170,171) and bacterial (72,169) pathogens that drain into the lymphatic sinuses and such physical trapping is likely an important mechanism by which they prevent dissemination. In addition these macrophages have been shown to rapidly produce type I interferons, IL-1α, IL-1β and IL-18 in the dLN following an inflammatory challenge (72,170,171,266,328). Their rapid production of type I interferons is necessary to protect intranodal neurons from fatal neuroinvasion and dissemination in the context of VSV infection (147,170). Moreover, macrophage-derived IL-18 also indirectly reduces pathogen dissemination by inducing rapid IFNγ production by strategically positioned lymphoid cells (72). Finally, ablation of LN-resident macrophages or their derived cytokines has been shown to impair the recruitment of innate immune cells into the dLN, including neutrophils (72,328), monocytes (328) and natural killer (NK) cells (172,307,328). Thus, lymph node resident macrophages are likely to bolster the barrier function of the dLN by both directly capturing pathogens and initiating inflammatory processes in the dLN.

The roles of lymph node macrophages also extend to the developing adaptive immune response. Several studies have shown that their prior depletion impairs subsequent T cell (266) and humoral immune responses (266,351) following immunisation or infection. The proposed mechanisms by which lymph node resident macrophages promote adaptive immune responses are varied but include the activation and maturation of dendritic cells (171), the recruitment of naïve T cells (328) and the production of IL-4 by NKT cells (351).

8 Lymph nodes also harbour a network of T cell zone macrophages that populate the paracortex and efferocytose apoptotic lymphocytes during homeostasis (69). Whilst these macrophages proliferate in the draining lymph node following an inflammatory challenge, these macrophages have not yet been shown to play any additional roles during inflammation and thus will not be commented upon further. 62

1.3.2.4 Natural killer cells Natural killer (NK) cells are lymphoid cells that act as part of the innate immune system; classically by inducing the death of virus-infected host cells. Like T and B lymphocytes, NK cells recirculate through lymph nodes; homing to lymph nodes following adoptive transfer (352,353) and egressing from lymph nodes in an S1P-depdendent manner (354). In the steady state, NK cells are motile cells predominantly localised in the medulla, paracortex and interfollicular regions (72,90,352,355). Inflammatory stimuli can elicit the CXCR3-depdendent recruitment of circulating NK cells to the dLN (172,241,307) and the rapid accumulation of NK cells in the subcapsular sinus (172,355) and interfollicular regions (356). Numerous studies have demonstrated that NK cells rapidly produce IFNγ in dLN following an inflammatory challenge (72,90,172,241,352,355,356). Moreover, Fang et al (90) demonstrate that the peripheral positioning of NK cells within the dLN is important to induce their expression of IFNγ. This likely reflects activation of NK cells by other inflammatory cells in the dLN, with subcapsular sinus macrophages and inflammatory monocytes and migratory dendritic cells implicated in this process (172,355,357). The recruitment and activation of NK cells has consequences for both innate and adaptive immunity in the dLN. Both NK cell depletion and antagonism of IFNγ have been shown reduce pathogen growth in and dissemination from the dLN (72,307). In addition, the production of IFNγ by NK cells in the dLN has been shown to drive Th1 immune responses (241). The mechanisms by which NK cells and IFNγ exert these effector functions are unclear. With regard to innate pathogen control, NK cell derived IFNγ is thought to promote antimicrobial effector functions in lymph node resident macrophages but direct evidence of this has not been established (72). Similarly, the precise mechanism by which NK cell derived IFNγ biases T cell differentiation is unclear, although it is notable that NK cells have been shown to closely interact with dendritic cells and activated T cells in outer regions of the paracortex (352). Indeed, NK cell derived IFNγ has recently been shown to potentiate antibody responses following influenza vaccination by driving the production of IL-6 by dendritic cells (356). It is therefore possible that NK cells drive Th1 T cell responses in a similarly indirect fashion.

1.3.2.5 Innate lymphoid cells The innate lymphoid cells (ILCs) are united by their developmental dependence on IL-2Rγ and the transcriptional repressor ID2 (358). Akin to CD4+ve T cell subsets, they can be split into three groups based on their expression of transcription factors and effector cytokines (358). Group 1 ILCs express the Th1 transcription factor T-bet and produce IFNγ, group 2 ILCs express the Th2 transcription factor GATA-3 and produce IL-4, 5 and 13 and the group 3 ILCs express 63

the Th17 transcription factor RORγt and produce IL-17 and IL-22 (358). Each of these groups can be divided into further subsets, most notably group 1 ILCs can be divided into NK cells and ILC1s (358).

All three groups of ILCs can be found in lymph nodes, a proportion of which are migratory cells and another proportion are resident cells (359,360). Akin to NK cells (Section 1.3.2.4), ILC1s recirculate between the vascular and lymphatic systems and produce IFNγ in the dLN following an inflammatory challenge (359). Their precise localisation within the dLN is yet to be characterised. In contrast, group 2 and 3 ILCs have been shown to exhibit a predominantly interfollicular distribution (360). The precise of functions of group 2 ILCs in the dLN is unclear. Group 3 ILCs include the lymphoid tissue inducer cells known to be crucial for lymph node organogenesis (361). In addition, ILC3s have also been shown to actively maintain lymphocyte entry into adult lymph nodes in the steady state (135). However, the role they play in the context of acute inflammation is unclear. Interestingly group 3 ILCs are enriched within lymph nodes that drain mucosal tissues and there is some evidence that they operate to regulate CD4 T cell activation in mucosa-draining lymph nodes (360).

1.3.2.6 Natural killer T cells Natural Killer T (NKT) cells are a subset of T cells that express a restricted set of T cell receptors and recognise glycolipid antigens presented by CD1d (362). A small population of NKT cells are present in lymph nodes where they are predominantly localised in the paracortex but are also found in interfollicular and subcapsular regions (363). Upon inflammation, lymph node resident macrophages have been shown to rapidly activate NKT cells through presentation of glycolipids complexed with CD1d and the production of IL-18 (351,363). Like NK cells and memory CD8 T cells (Sections 1.3.2.4 and 1.3.2.7), activated NKT cells in the dLN exhibit increased expression of IFNγ (72,351). Moreover, NKT cells serve as a major source of IL-4, the rapid production of which initiates antiviral B cell responses (351). These IL-4 producing NKT cells are predominantly localised at the borders of B cell follicles and thus may form part of anatomical niche that orchestrates the developing humoral immune response.

1.3.2.7 Memory CD8 T cells The rapid activation of memory CD8 T cells in the dLN is a common feature of acute inflammation. Indeed, the viral pathogens LCMV, VSV, MVA and ectromelia virus, the bacterial pathogen Pseudomonas aeruginosa and the TLR-4 adjuvant GLA-SE have all been shown to

rapidly elicit IFNγ production by memory CD8 T cells in the dLN (70,278,329,364). Moreover, these activated memory CD8 T cells are predominantly localised in the peripheral medullary, interfollicular and subcapsular regions of the dLN (70,328). There is some debate concerning the factors that determine this peripheral distribution. On the one hand, Sung et al (329) have demonstrated that infection induces the CXCR3-dependent migration of memory T cells from the paracortex to these peripheral regions, whilst on the other hand Kastenmüller et al (70) have shown that memory CD8 T cells are prepositioned in these peripheral regions in the steady state. These contrasting findings are likely due to context dependent factors. Regardless, the presence of memory CD8 T cells in the dLN has been shown to play a key role in preventing the replication and dissemination of pathogens (329,364). Notably, the induction of IFNγ expression by these cells is not dependent upon the presence of cognate antigen (70) but has been shown to require expression of CXCR3 (329) and IL-18 (278). These findings therefore suggest that memory CD8 T cells contribute to the innate barrier function of the dLN even in the absence of their specific pathogen.

1.3.2.8 Cytokines and chemokines in the draining lymph node

1.3.2.8.1 Sources of cytokines and chemokines in the draining lymph node Numerous studies have measured increased concentrations of cytokines and chemokines in the dLN following challenge with a variety of inflammatory stimuli. These cytokines and chemokines can be transported to the dLN in afferent lymph (109,325–327) or be produced by cells within the dLN. A diverse range of cells have been shown to be intranodal producers of cytokines and chemokines, including lymph node resident macrophages (72,170,171,266,328), resident interfollicular lymphoid cells (including γδ T cells, NK cells, NKT cells and innate-like CD8+ve T cells) (72), stromal cells (70,247,329,330), memory CD8+ve T cells (70,329) and recruited neutrophils (312), monocytes (242) and NK cells (241). The precise mechanisms that drive cytokine and chemokine production within the lymph node during inflammation are only partially understood. As lymph node resident macrophages rapidly capture pathogens in the lymphatic sinuses (Sections 1.2.3.1.2 and 1.3.2.3) it seems likely that PAMPs directly drive their rapid production of type I interferons and inflammasome-derived IL-1β and IL-18; although there is currently no direct evidence for this. However, it is clear that once the production of inflammatory cytokines is initiated, it potentiates further cytokine and chemokine production. For example, it has been repeatedly demonstrated that type I interferons and IL-18 induce the production of IFNγ (72,172,278,279) and that type I interferons and IFNγ induce the production of CXCL9 and CXL10 (70,329) within the dLN. Thus, whilst the initial drivers of

cytokine production within the dLN remain to be characterised, there appear to be conserved mechanisms of cytokine and chemokine production that are engaged once this process has been initiated.

1.3.2.8.2 Distribution of cytokines and chemokines in the draining lymph node The highly organised structure of the dLN would suggest that intranodal cytokines exert paracrine effects in the regions that they are produced. However, Perona-Wright et al (251) question this theory, demonstrating that the intranodal IFNγ and IL-4 bind to and induce signalling across the majority of lymphocytes within the dLN. This suggests that cytokines permeate throughout the dLN and are not concentrated in particular regions. In contrast, the expression and localisation of chemokines is strictly defined in lymph nodes, as evidenced by the compartmentalised expression of CCL21 and CXCL13 in the paracortex and follicles respectively (Section 1.2.1.1). Moreover, the expression of CXCL9 and CXCL10 is concentrated in the medullary and interfollicular regions of dLNs during inflammation (70,247,329). Furthermore, CCL21 and S1P have been shown to form concentration gradients within the lymph node parenchyma (88,90,220). Thus, there is evidence that inflammatory mediators can either be compartmentalised within or permeate throughout the dLN. The precise pattern of distribution likely differs according to the inflammatory mediator.

1.3.2.8.3 Functions of cytokines and chemokines in the draining lymph node Cytokines and chemokines can promote both the innate barrier and adaptive immune functions of the dLN. With regards to innate immunity, ablation or antagonism of type I interferons and IFNγ have been shown to increase the dissemination of viral and bacterial pathogens respectively (72,170). The increased expression of CXCL9 and CXCL10 observed in many contexts is also likely to be important in this regard as the CXCR3-dependent recruitment of NK cells and memory CD8 T cells controls pathogen growth within and dissemination from the dLN (72,307,329). With regards to adaptive immunity, the intranodal production of IL-12, IFNγ, type I interferons and CXCR3 ligands have all been associated with the development of Th1-baised T cell responses in a variety of contexts (241,242,247,266,278) and the intranodal production of IL-4 by perifollicular NKT cells is required for optimal B cell responses in the context of influenza infection (351). These findings establish the principle that cytokines and chemokines expressed in the draining lymph during acute inflammation can modulate innate and adaptive immunity. The relative importance and roles of these and other inflammatory mediators differs according to the inflammatory context. This thesis focusses upon the 66

relationship between neutrophils and monocytes and two key families of inflammatory mediators; the COX-derived prostanoids and these type I interferons. These innate immune pathways are discussed in detail in chapters 4 and 5/6 respectively.

1.3.3 Neutrophils and monocytes in the draining lymph node

Neutrophil and monocyte infiltration is a cardinal aspect of the innate immune response. The final section of the introduction reviews out current understanding of this innate immune process within the dLN following an inflammatory challenge. Furthermore, it is increasingly recognised that small populations of neutrophils and monocytes also traffic through lymph nodes in the steady state (173,365,366). In the steady state, neutrophils are primarily localised in the interfollicular regions and are thought to contribute to the innate barrier function of the dLN and to help capture immune complexes circulating in the vascular system (173,365). On the other hand, monocytes constitutively traffic antigens from tissues to the dLN in the steady state (366). These findings are emblematic of our increasing insight into the varied roles of these cardinal myeloid cell subsets within lymph nodes, which will be discussed in the context of inflammation in the following sections.

1.3.3.1 Neutrophils in the draining lymph node

1.3.3.1.1 Determinants of neutrophil infiltration into the draining lymph node A wide variety of inflammatory stimuli have been shown to induce neutrophil infiltration into the dLN. These include immune complexes (203,367), the infectious agents Staphylococcus aureus (173,202,209), Pseudomonas aeruginosa (72), Bacillus Calmette-Guerin (BCG) (201), Modified Vaccinia Ankara (MVA) (328) and Toxoplasma gondii (368), and the adjuvants MF-59 (204), DNA liposomes (369,370), complete Freund’s adjuvant (CFA) (202,203,312,371–374), QS-21 (265), AS01 (277), AS03 (262) and GLA-SE (278). However, not all inflammatory stimuli induce such neutrophil infiltration. Indeed, sterile injury elicits robust neutrophil infiltration at the site of damage but does not elicit a neutrophil influx into the dLN (209). Moreover, whilst the subcutaneous injection of 1 x 107 CFU of P. aeruginosa elicits a lymph node neutrophil infiltrate, the subcutaneous injection of 1 x 107 CFU of S. typhimurium does not (72). The precise determinants of neutrophil infiltration into the dLN are only partially understood. IL-1β produced by lymph node resident macrophages has been shown to promote neutrophil infiltration following challenge with Pseudomonas aeruginosa (72) and MVA (328). However, the depletion of lymph node resident macrophages does not impair the neutrophil influx

induced by S. aureus (173). Rather, in this context neutrophil infiltration is heavily dependent upon complement activation (173). Finally, inhibition or deletion of either cyclooxygenase (COX) 1 or 2 ablates the lymph node neutrophil influx elicited following challenge with CFA, suggesting that COX-derived lipid mediators play an important role in this context (312). Thus, the infiltration of neutrophils into the dLN is a common but not universal feature of inflammation that can be driven a number of inflammatory mediators.

1.3.3.1.2 Mechanisms of neutrophil infiltration into the draining lymph node Neutrophils can enter the dLN from the site of inflammation via afferent lymphatics or directly from the bloodstream via HEVs. With regards to lymphatic entry, numerous studies have visualised neutrophils in afferent lymphatic vessels following the induction of acute inflammation (201,209,367,374) and their migration from the site of inflammation to the dLN has been confirmed using an in vivo photoconversion system (209). The mechanisms by which neutrophils achieve such migration are not clear but there is evidence to suggest that CD11b expression and LFA-1/ICAM-1 interactions are important (209,367,374).

With regards to the direct infiltration of neutrophils from the bloodstream, studies have visualised rapid and substantial neutrophil transmigration across HEVs into the lymph node parenchyma (173,202). Like lymphocytes (Section 1.2.2.1.1), neutrophils use selectins to interact with peripheral node addressin (PNAd) on the HEV endothelium. Neutrophils can use both L-selectin and platelet-derived P-selectin to bind PNAd and the drastic reduction in lymph node neutrophil infiltration observed following PNAd antagonism is only recapitulated by dual antagonism of these two selectins (173). That neutrophil transmigration requires additional integrin and chemokine-based interaction with the HEV endothelium is suggested by the fact that antagonism of LFA-1, CD11b, CXCR4 or S1PR1 also impairs neutrophil infiltration into the dLN (367). It is also notable that increased concentrations of the neutrophil-associated chemokines CXCL1, CCL3 and CCL4 have been reported in the dLN in various contexts (171,266,307,375) and that the chemotactic complement component C5a is crucial for lymph node neutrophil infiltration following challenge with S. aureus (173). However, no studies have yet shown that these chemokines are presented on the surface of the HEV endothelium and thereby facilitate neutrophil transmigration. The fact that PNAd blockade almost completely ablates neutrophil infiltration into the dLN without affecting neutrophil infiltration at the site of inflammation strongly suggests that HEVs are the primary source of neutrophils in the dLN (173).

1.3.3.1.3 Functions of neutrophils in the draining lymph node

1.3.3.1.3.1 Innate immunity Neutrophils are cardinal cells of the innate immune response and are best known for their role in phagocytosing and killing pathogens at the site of inflammation. It is therefore notable that neutrophils are frequently localised in the subcapsular and medullary sinuses of the dLN (72,201,202,209,367,368,371) and often harbour injected antigens and pathogens (201– 203,209,368). Moreover, intravital imaging has been used to visualise both the migration of neutrophils from high endothelial venules to the subcapsular sinus (202), and the phagocytosis of bacteria by neutrophils within the subcapsular sinus (173). Kastenmüller et al (72) argue that neutrophils contribute to the innate barrier function of the dLN as they demonstrate that neutrophil depletion increases the growth and dissemination of Pseudomonas aeruginosa within and from the dLN. However, such depletion does not distinguish between neutrophils within the dLN and neutrophils at the site of inflammation and as such does not prove a role for neutrophils within the lymph node. Bogoslowski et al (173) resolve this confounder as they demonstrate that PNAd antagonism ablates neutrophil infiltration into the dLN but not the site of inflammation. Notably, such lymph node specific neutrophil ablation only increases the growth and dissemination of S. aureus when combined with the depletion of lymph node resident macrophages (173) . This suggests that in this context, the role of neutrophils is secondary to the importance of lymph node resident macrophages in terms of the innate barrier function of the dLN.

1.3.3.1.3.2 Adaptive immunity The infiltration of neutrophils into the dLN is generally thought to have a deleterious effect on the developing adaptive immune response. Indeed, neutrophil depletion has been shown to potentiate both T cell (312,371) and humoral immune responses (202,371). No clear mechanisms have been established for how neutrophils impair the developing adaptive immune response; Yang et al (371) provide evidence that they impair antigen presentation by dendritic cells, Unanue et al (312) illustrate that their production of thromboxane A2 is an important factor and Kamenyeva et al (202) suggest that they limit humoral immune responses by interacting with B cells. This picture is further complicated by the findings of Parsa et al (372) who have demonstrated that neutrophil depletion at the time of immunisation paradoxically drives a secondary wave of neutrophils into the dLN that promote humoral responses through their production of BAFF and interactions with plasma cells. In addition, Castell et al (376) provide evidence that whilst neutrophils initially restrict CD4 T cell

proliferation in the dLN, they ultimately promote CD4 T cell proliferation once they have dissipated. Moreover, other studies have shown neutrophil depletion to have no effect on subsequent humoral immune responses following immunisation with the adjuvants alum and MF59 (204,377). Thus, further work is required to establish the complex mechanisms by which lymph node neutrophils modulate adaptive immune responses in specific contexts.

1.3.3.2 Inflammatory monocytes in the draining lymph node

1.3.3.2.1 Definition and differentiation of monocytes in the draining lymph node Monocytes are mononuclear myeloid cells that differentiate from common monocyte progenitor cells in the bone marrow (378) and circulate in the bloodstream as non-dividing cells. Geissman et al (379) defined two distinct subsets of monocytes that circulate in the bloodstream of mice; a Ly6Chi ‘inflammatory’ subset and a Ly6Clo ‘resident’ subset. Inflammatory Ly6Chi monocytes are a common feature of the acute inflammatory infiltrate (380) and have been shown to infiltrate the dLN following challenge with the pathogens L. major (207), influenza (205), LCMV (381), VSV (381) and T. gondii (382) or the adjuvants alum (50), MF-59 (263), CpG (242), CFA (205), DNA liposomes (369,370), QS-21 (265) and AS01 (277). The majority of these stimuli induce monocyte infiltration into the dLN within 24 hours of challenge (50,242,263,280,370,381). Nevertheless, several inflammatory stimuli have also been described that cause robust monocyte infiltration at the site of inflammation but elicit only small increases in numbers of monocyte-derived cells in the dLN (189,204,383,384). Thus, the rapid influx of monocytes into the dLN is a common but not universal feature of acute inflammation.

The study of inflammatory monocytes is complicated by the fact that monocytes readily differentiate into cells resembling macrophages or dendritic cells upon microbial stimulation (385). Indeed, whilst circulating Ly6Chi inflammatory monocytes do not express the canonical dendritic cell marker CD11c (379), this marker is expressed by Ly6Chi inflammatory monocytes infiltrating the dLN in many contexts (50,205,207,242,263) and such cells are often termed monocyte-derived dendritic cells (50,207,263) or inflammatory dendritic cells (205). To further complicate matters, several authors have identified monocyte-derived dendritic cells in the dLN that have either reduced or lost expression of Ly6C (189,207,242,383,386,387). Thus, acute inflammation can induce the infiltration of a range of monocyte-derived cells into the dLN, from Ly6ChiCD11c-ve cells resembling circulating monocytes to Ly6C-ve CD11c+ve dendritic cells (Figure 1.3). There is currently no evidence to suggest that inflammation induces lymph node monocytes to differentiate into macrophages, although it is notable that the T zone 70

macrophages of the paracortex are replenished by monocytes in the steady state and that subcapsular and medullary sinus macrophages are bone marrow derived cells (328,388).

Figure 1.3: Range of Ly6Chi monocyte-derived cells that have been described in the draining lymph node Mo-DC: Monocyte-derived dendritic cell. Created with biorender.com

1.3.3.2.2 Mechanisms of inflammatory monocyte infiltration into the draining lymph node Inflammatory monocytes and their derivatives can enter the dLN from the site of inflammation via afferent lymphatics or from the bloodstream via HEVs. With regards to lymphatic entry, ovine studies have shown that monocytes rapidly appear in afferent lymph following immunisation (210,214). Moreover, murine studies demonstrate that subcutaneously injected monocytes can migrate to the dLN and that such migration is dependent on CCR7 (207,389). With regards to the entry of monocytes from the bloodstream, it is notable that the monocyte chemokines CCL2 and CXCL10 have been shown to accumulate in HEVs (325,390) and facilitate the arrest of monocytic cells on the HEV endothelium (325). In addition, a wide variety of inflammatory stimuli have been shown to elicit rapid increases in the concentration of CCL2 and other CCR2 ligands in the dLN (205,325,328,369,375,391) and CCR2-deificient monocytes exhibit impaired accumulation in the dLN relative to wild-type monocytes 2 hours following intravenous adoptive transfer (205). Finally, antagonism of L-selectin impairs monocyte infiltration into the dLN (392) suggesting that, like neutrophils and lymphocytes (Sections 1.2.2.1.1 and 1.3.3.1.2), monocytes engage PNAd on the HEV endothelium to transmigrate across HEVs.

The relative importance of afferent lymph and HEVs as sources of monocytes in the dLN is difficult to gauge. This is because antagonism of L-selectin and deletion of CCR2 impair monocyte infiltration at the site of inflammation as well as the dLN (205,392). Nevertheless, Leon et al (207) sought to directly compare lymph and blood as sources of monocytes by phenotyping the monocyte-derived cells in the dLN 72 hours following either subcutaneous or intravenous adoptive transfer of bone marrow monocytes into leishmania-infected mice. 71

Whilst intravenous monocyte transfer resulted in the appearance of Ly6Chi monocytes, Ly6Chi monocyte-derived cells and Ly6Clo monocyte-derived dendritic cells in the dLN, subcutaneous monocyte transfer resulted in the appearance of only Ly6Clo monocyte derived dendritic cells in the dLN. This suggests that both monocytes and monocyte-derived dendritic cells are capable of entering lymph nodes directly from the bloodstream, whilst the latter cells are also capable entering via afferent lymphatics. This conclusion is supported by other studies demonstrating that the infiltration of Ly6Chi cells is not dependent on CCR7, whilst the infiltration of Ly6Clo monocyte-derived dendritic cells is (242,383). Moreover, a recent study in which monocytes stemming from the site of inflammation were marked by a process of photoconversion provides evidence that the vast majority dLN-infiltrating monocytes do not stem from the site (272). Altogether, these findings suggest that the transmigration across the HEV endothelium is primary route by which Ly6Chi monocytes and Ly6Chi monocyte-derived dendritic cells acutely infiltrate the dLN.

1.3.3.2.3 Functions of inflammatory monocytes in the draining lymph node Studies of monocyte function in the dLN have focussed on their potential effects upon the developing adaptive immune response. However, monocytes are known to be important in the innate control of infections in other contexts (393–395) and several authors have demonstrated that lymph node monocytes or monocyte-derived cells harbour antigens or pathogens in the context of acute inflammation (50,187,189,204–208). It is thus reasonable to hypothesise that monocytes contribute to the innate barrier function of the dLN but this hypothesis requires testing.

With regards to the developing adaptive immune response, there is evidence that the differentiation of monocytes into monocyte-derived dendritic cells potentiates T cell responses via antigen presentation. Indeed, studies have demonstrated that antigen is enriched in CD11c+ve Ly6Chi monocyte-derived dendritic cells relative to CD11c-ve Ly6Chi monocytes in the dLN (50,187,205) and that monocyte-derived dendritic cells isolated from dLNs are capable of activating cognate T cells ex vivo, either in terms of eliciting T cell proliferation (189,387,396) and/or cytokine production (205,207,387). That such findings reflect in vivo antigen presentation is supported by studies that demonstrate that CCR2-deficient mice exhibit impaired T cell responses, either in terms of the antigen-specific proliferation (187,396) or IFNγ production (205,242,397). In addition, monocyte-derived dendritic cells can compensate for the depletion of resident CD11c+ve cells in the dLN (50,189). However, others have shown that monocytes perform an important antigen trafficking function without presenting antigen

(398). Indeed, antigen presentation is not the only means by which monocytes can promote T cell responses. De Koker et al (242) demonstrate that the impaired ability of CCR2 knockout mice to generate IFNγ-secreting antigen-specific T cells following OVA/CpG immunisation is due to a lack of monocyte-derived IL-12 rather than any defect in antigen presentation. Thus, monocyte-derived dendritic cells infiltrating the dLN can potentiate T cell responses, especially Th1 T cell responses, by either antigen presentation or cytokine production.

Monocytes have been shown to exhibit deleterious effects on the developing humoral immune response as deficiency or antagonism of CCR2 has been shown to increase antigen-specific antibody titres (369,370,381). Similarly, McCarthy et al (399) demonstrate that infiltrating neutrophils and monocytes reduce the total size of germinal centres within the dLN and reduce the neutralising capacity of the antibodies generated following challenge with Chikungunya virus. Similarly, Sammicheli et al (381) illustrate that monocytes interact with and promote the death of antigen-specific B cells in the dLN following challenge with LCMV. However, this study (381) also demonstrates that this effect is specific to the protracted monocyte infiltration (≥ 7 days) elicited by LCMV as the transient lymph node monocyte influx (<48 hours) elicited by VSV infection does not impair the subsequent humoral immune response. Thus, the infiltration of monocytes into the dLN can have neutral or deleterious effects on the humoral immune response depending on the context.

Figure 1.4: The draining lymph node during acute inflammation Representative diagrams demonstrating (A) the initial cytokine response to pathogens draining in afferent lymph and (B) the subsequent cellular responses to the arrival of pathogens in the draining lymph node. Created with biorender.com

1.4 Summary and aims

The lymph nodes that drain acutely inflamed tissues serve a dual function to both prevent the systemic spread of pathogens and facilitate the initiation of adaptive immune responses. As discussed in the preceding sections, it is increasingly recognised that many of the innate immune pathways long known to occur at the site of inflammation also operate within the dLN. This includes the activation of resident macrophages, the recruitment of innate immune cells and the production of pro-inflammatory cytokines and chemokines. Whilst considerable effort has been employed to delineate the mechanisms by which adaptive immune responses are initiated in the dLN, relatively little is known with regard to the extent to which adaptive immunity is modulated by innate immune pathways within the dLN. In particular, the roles played by infiltrating neutrophils and monocytes within intranodal inflammatory responses and their interaction with the developing adaptive immune response are only partially understood. As such, this thesis is grounded in the following hypothesis:

Neutrophils and monocytes infiltrating the draining lymph node shape the intranodal inflammatory milieu and thereby modulate the developing adaptive immune response.

The term ‘acute inflammation’ can represent the interaction of a huge variety of different cell types and inflammatory mediators that differ in their relative importance depending on the nature of the inciting inflammatory stimulus and the tissue site. This thesis therefore focuses upon the roles played by neutrophils and monocytes with regard to two cardinal innate immune pathways; those of cyclooxygenase-dependent prostanoids and type I interferons. Importantly, there is evidence that both prostanoids and interferons modulate the developing adaptive immune response. However, their roles in shaping both innate and adaptive immune pathways in the dLN are not fully understood.

1.4.1 Aims

• To characterise the infiltration of neutrophils and monocytes into the draining lymph node

• To examine the role of neutrophils and monocytes as sources of cyclooxygenase- dependent prostanoids in the draining lymph node

• To examine the roles played by neutrophils and monocytes in type I interferon-driven inflammation in the draining lymph node

• To examine the effects of these innate immune pathways on lymphocyte activation and retention within the draining lymph node.

In essence, this thesis examines how cells and soluble mediators traditionally associated with innate immunity interact within the draining lymph node and thereby modulate the developing adaptive immune response.

2 Materials and Methods

2.1 Materials

2.1.1 General reagents

Table 2.1: General reagents

Reagent Manufacturer Catalogue Code

2-Mercaptoethanol Sigma M3148 BSA Sigma A9647 BSA (fatty-acid free) Sigma A8806 DMEM with glucose Gibco 41965-039 EDTA Sigma 03690 Fetal Bovine Serum Gibco 10500-064 Goat Serum Thermo Fisher 10000C HEPES Gibco 15630-049 Hydrochloric Acid VWR 20252.20 L-glutamine Gibco 25030-024 Methanol VWR 20847.320 Milk Powder (0.1% Fat, Sainsbury’s N/A Skimmed) Mouse Serum Unknown Unknown PBS Gibco 10010-015 Penicillin/Streptomycin Gibco 15148-122 Rabbit Serum Unknown Unknown Rat Serum Unknown Unknown RPMI 1640 Gibco 31870025 Sodium Azide Sigma S2002 Sodium Chloride Sigma S7653 Sodium Citrate Sigma S1804 Tween-20 Sigma P2287

2.1.2 Formulations

Table 2.2: Cell culture media

Culture Medium Formulation Reference

Chemotaxis RPMI 1640, 0.1% w/v BSA (fatty-acid free), 100U/ml As per Sensken et al Medium penicillin, 100μg/ml streptomycin, 2mM L- (400) glutamine and 25mM HEPES Lymphocyte RPMI 1640, 10% FBS, 2mM L-glutamine, 100U/ml As per Coro et al (401) Culture Medium Penicillin, 100μg/ml Streptomycin and 0.05mM 2- Mercaptoethanol RAW 264.7 DMEM with glucose, 10% FBS, 2mM glutamine, N/A Culture Medium 100U/ml penicillin, 100μg/ml streptomycin See Table 2.1 for Catalogue Numbers

Table 2.3: Flow cytometry buffers

Buffer Formulation

FACS Buffer PBS, 5% w/v FBS, 1% w/v BSA, 0.1% w/v Sodium Azide Wash Buffer PBS, 1% v/v FBS, 2mM EDTA, 0.1% w/v Sodium Azide Table 2.1 for catalogue numbers

Table 2.4: Immunohistochemistry buffers

Buffer Formulation

Antigen retrieval Distilled water, 10mM Sodium Citrate, adjusted to pH 6.0 with 1M buffer hydrochloric acid Block Buffer PBS, 1% w/v BSA, 10% v/v serum in which secondary antibody was raised Staining Buffer PBS, 1% w/v BSA Wash buffer PBS See Table 2.1 for Catalogue Numbers

2.1.3 Antibodies

Table 2.5: Flow cytometry antibodies

Target Fluorochrome Antibody Staining Supplier Catalogue Clone Concentration Number B220/ PerCP-Cy5.5 RA3-6B2 0.5μg/ml BD 552771 CD45R CD11b Percp Cy5.5 M1/70 0.5μg/ml BD 550993 CD11b V450 M1/70 0.5μg/ml BD 560455 CD11b V500 M1/70 0.5μg/ml BD 562127 CD11c APC N418 0.5μg/ml Biolegend 117309 CD11c BV605 N418 0.5μg/ml Biolegend 117333 CD11c FITC N418 1.25μg/ml Biolegend 117305 CD11c PE N418 0.5μg/ml Biolegend 117307 CD19 FITC 6D5 1.67μg/ml Biolegend 115526 CD19 Pacific Blue 6D5 1.67μg/ml Biolegend 115526 CD19 PE 1D3 0.67μg/ml BD 553786 CD19 Percp Cy5.5 1D3 0.5μg/ml BD 551001 CD19 V450 1D3 0.67μg/ml BD 560375 CD3 FITC 17A2 1.67μg/ml Biolegend 100203 CD3 Pacific Blue 17A2 1.67μg/ml Biolegend 100214 (CC) CD3 PE 17A2 0.67μg/ml Biolegend 100205 CD3 V450 17A2 0.67μg/ml BD (CC) 561389 CD4 A488 RM4-5 0.67μg/ml BD 557667 CD4 APC RM4-5 0.67μg/ml BD 553051 CD69 PE H1.2F3 0.5μg/ml Biolegend 104507 CD8 V500 53-6.7 0.67μg/ml BD 560776 CD95/ A488 15A7 1.67μg/ml eBioscience 53-0591 Fas CXCR3/ FITC CXCR3-173 2.5μg/ml Biolegend 126535 CD183 GL-7 A647 GL7 1.67μg/ml Biolegend 144605 Antigen GR-1 FITC RB6-8C5 1.67μg/ml Biolegend 108405 IFNγ APC XMG1.2 1.25μg/ml Biolegend 505809 Ly6C APC AL-21 0.67μg/ml BD 560595 Ly6C APC HK1.4 0.67μg/ml Biolegend 128015 Ly6C fitc AL-21 1.67μg/ml BD 553104 Ly6G Pacific Blue 1A8 1.67μg/ml Biolegend 127611 Ly6G PerCP Cy5.5 1A8 0.5μg/ml Biolegend 127616 MHC-II A700 M5/114.15.2 1.25mg/ml Biolegend 107621 MHC-II FITC M5/114.15.2 1.25mg/ml Biolegend 107605 MHC-II Pacific blue M5/114.15.2 1.25mg/ml Biolegend 107619 NK1.1 A700 PK136 1μg/ml BD 560515 NK1.1 PE PK136 1μg/ml Biolegend 108707 NK1.1 V450 PK136 1μg/ml BD 560524

Table 2.6: Flow cytometry isotype controls Host and Isotype Fluorochrome Clone Staining Manufacturer, Concentration Catalogue Number Armenian PE HTK888 0.5μg/ml Biolegend, 400907 Hamster IgG Rat IgG1κ APC RTK2071 1.25μg/ml Biolegend, 400411 Rat IgG2bκ PE RTK4530 0.67μg/ml Biolegend, 400607

Table 2.7: Immunohistochemistry primary antibodies

Target Clone Staining Antigen Retrieval Antigen Retrieval Manufacturer, Concentration Duration Required? Catalogue Number B220 RA3-6B2 2.5μg/ml 9 min No Biolegend, 103201 Ly6G 1A8 5μg/ml 9 min No Biolegend, 127601 GR-1 RB6-8C5 5μg/ml 9 min No Biolegend, 108401

Table 2.8: Immunohistochemistry isotype controls

Host and Isotype Clone Staining Manufacturer, Catalogue Concentration Number Rat IgG2a κ RTK2758 2.5-5μg/ml Biolegend, 400501 Rat IgG2b κ RTK4530 5μg/ml Biolegend, 400601

Table 2.9: Immunohistochemistry secondary antibodies

Target Host and isotype Clone Staining Manufacturer, Concentration Catalogue Number

Rat IgG Goat IgG (HRP- Polyclonal 2μg/ml Abcam, ab205720 conjugate)

2.1.4 Primer sequences

Table 2.10: Primer sequences

Gene, NCBI Reference Primer Sequences Product Efficiency +ve CTRL size cDNA (Table 2.16) Actb, NM_007393.5 F: CTGTCGAGTCGCGTCCA 87bp 106.05% RAW + R: TCATCCATGGCGAACTGGT LPS/SPL + IFNβ Aim2, NM_001013779.2 F: TTGTATCTAGGCTGATCCTGGGAC 201bp 98.03% SPL + LPS, R: ACCTGCACTTTGAATCAGGTGGTC IFNβ B2m, NM_009735.3 F: CCTTCAGCAAGGACTGGTCT 132bp 98.945 RAW + R: TGTCTCGATCCCAGTAGACG LPS/SPL + IFNβ Ccl2, NM_011333.3 F: TTAAAAACCTGGATCGGAACCAA 121 97.43% RAW + LPS R: GCATTAGCTTCAGATTTACGGGT Cd69, NM_001033122.4 F: TGGTCCTCATCACGTCCTTAATAA 85bp 88% 6hr Lymph R: TCCAACTTCTCGTACAAGCCTG Node Cxcl10, NM_021274.2 F: CCAAGTGCTGCCGTCATTTTC 157 94.32% RAW + LPS R: GGCTCGCAGGGATGATTTCAA Cxcl9, NM_008599.4 F: AATGCACGATGCTCCTGCA 65 95.99% RAW + LPS R: AGGTCTTTGAGGGATTTGTAGTGG Hprt, NM_013556.2 F: AGGAGTCCTGTTGATGTTGCCAGT 134bp 88% RAW + LPS R: GGGACGCAGCAACTGACATTTCTA Ifit1, NM_008331.3 F: CAGAAGCACACATTGAAGAA 157bp 93% RAW + R: TGTAAGTAGCCAGAGGAAGG LPS/SPL + IFNβ Ifit2 F: GGGAAAGCAGAGGAAATCAA 173bp 83% RAW + NM_008332.3 (2bp R: TGAAAGTTGCCATACAGAAG LPS/SPL + mismatch in red) IFNβ Ifit3, NM_010501.2 F: CGCCATGTTCCGCCTAGA 107bp 95% RAW + R:CCAGGAGAACTTTCAGGTACTGGTT LPS/SPL + IFNβ Ifna1, Ifna5, Ifna7, Ifna11, F: ATGGCTAGGCTCTGTGCTTT 107bp 91.99% SPL+ HKEC Ifna12, Ifna14, Ifna15. 1- R: CTCTTGTTCCTGAGGTTAT 3bp mismatch for Ifna2, Ifna4, Ifna6, Ifna9, Ifna13, Ifna16 and Ifnab Ifna4. 1-3bp mismatch for F: ATGGCTAGGCTCTGTGCTTT 110bp 82.75% SPL+ HKEC Ifna1, Ifna2, Ifna5, Ifna6, R: CTCTTGTTCCCGAGGTTAT Ifna7, Ifna11, Ifna12, Ifna13, Ifna14, Ifna1, Ifna16 and Ifnab Ifna6. 1-3bp mismatch for F: ATGGCTAGGCTCTGTGCTTT 107bp 89.74% SPL+ HKEC Ifna1, Ifna2, Ifna4, Ifna5, R: TTCTTGTTCCTGAGGTTAT Ifna7, Ifna11, Ifna12, Ifna13, Ifna14, Ifna1, Ifna16 and Ifnab Ifnb1, NM_010510.1 F: ATGAGTGGTGGTTGCAGGC 82bp 97% RAW + LPS R:TGACCTTTCAAATGCAGTAGATTCA

Ifng, NM_008337.4 F:TGGCATAGATGTGGAAGAAAAGAG 81 101.87% SPL + LPS, R: TGCAGGATTTTCATGTCACCAT IFNβ Il18, NM_008360.2 F: GGTTCCATGCTTTCTGGACT 125 103.68% RAW + LPS R: GGCCAAGAGGAAGTGATTTG Il1b, NM_008361.4 F: GGTCAAAGGTTTGGAAGCAG 94bp 100.14% Justine R: TGTGAAATGCCACCTTTTGA Nlrp3, NM_145827.4 F: AGAGCCTACAGTTGGGTGAAATG 116bp 88.67% SPL + LPS, R: CCACGCCTACCAGGAAATCTC IFNβ

Ppia, NM_008907.1 F: ATGGTCAACCCCACCGTG 103bp 99% RAW + LPS R: TTTCTGCTGTCTTTGGAACTTTGTC Ptges, NM_022415.3 F: ATGAGGCTGCGGAAGAAG 150bp 99% Peritoneal R: GCCGAGGAAGAGGAAAGGATAG Washout Ptgs2, NM_011198.4 F: ACACACTCTATCACTGGCACC 274bp 90% RAW + LPS R: TTCAGGGAGAAGCGTTTGC Tbxas1, NM_011539.3 F: GAAGGTCTGCCGTATCTGGA 200bp 102% Peritoneal R: TCAGGGTCAAAGGTCTCAGG Washout

Table 2.11: Positive control (+ve CTRL) cDNA

cDNA Definition RAW + LPS RAW 264.7 cells stimulated in vitro with 100ng/ml LPS for 6 hours. SPL + HKEC Splenocytes stimulated in vitro with 7.5 x 107 CFU heat-killed E. coli for 6 hours. SPL + LPS, Splenocytes stimulated in vitro with 1μg/ml LPS and 20,000 units/ml IFNβ for 6 IFNβ hours.

2.2 Methods

2.2.1 Animal procedures

2.2.1.1 Mice Wild-type male C57BL/6 mice were purchased from a commercial supplier (Harlan/Envigo) and male IFNAR-deficient mice (Ifnar1tm1Ag strain) were kindly provided by Dr Andreas Wack of the Francis Crick Institute. Mice were housed in individually ventilated cages in specific pathogen- free facilities at University College London. In terms of animal husbandry, mice were provided with food and water ad libatum, were subject to a 12-hour light/dark cycle and were housed with at least one companion at all times. With regards to euthanasia, mice were sacrificed by

CO2 asphyxiation unless plasma had to be harvested by cardiac puncture, in which case mice were sacrificed by terminal anaesthesia. All mice were between 7-8 weeks of age at the beginning of all experiments. Mice were allocated either individually or by cage to undergo either an active or control procedure. This allocation process was not randomised as this was deemed unnecessary. All animal procedures were conducted in accordance with the Animals (Scientific Procedures) Act 1986 under the following UK home office project licenses; 70/8290 (Professor Derek Gilroy), 70/8499 (Professor Claudia Mauri) and P69E3D849 (Professor Derek Gilroy).

The animal experiments presented in this thesis were conducted with regard to the ethical principles of replacement, refinement and reduction of the use of animals in research and are reported with regard to the ARRIVE guidelines. In terms of replacement, the use of mice was necessitated as the mouse model is the gold standard for lymph node (LN) biology research. In terms of refinement, the murine earflap immunisation model used in this thesis was demonstrated to and approved by the named veterinary surgeon (Mercedes Sanchez Garzon). The earflap was chosen over the footpad as the immunisation site in part to reduce the degree of suffering incurred by this procedure (as per project licence 70/82909). Overall, the severity of all procedures conducted in this thesis was deemed to be mild as all mice scored zero on the murine sickness score outlined in project licenses 70/8290 and P69E3D849. Finally, substantial efforts were made to reduce the numbers of animals used in the experiments conducted in this thesis. Firstly, contralateral cervical and inguinal lymph nodes from challenged mice were used as a comparator against the ipsilateral draining lymph node (dLN) where appropriate. This reduced the number of animals used solely to provide control lymph nodes. Secondly, in many instances harvested tissue was subjected to several methods of analysis in parallel in order to maximise the amount of data extracted from any given animal (Table 2.12). Thirdly, as

9 ‘As subplantar injection can be painful, skin/ear sites will be used in preference’ 83

discussed in the statistical analysis section, small sample sizes were utilised to detect large biological differences between control and draining lymph nodes. Finally, mice were challenged with inflammatory stimuli immediately translatable to human studies of inflammation, in order that the data generated from these animal studies could better inform future human studies.

Table 2.12: Overview of the use of animals in this thesis

Number of mice Sex Strain, Experimental Unit Procedure Methods of Figures Treatment Control Genotype Details Duration of Severity Analysis Experiment 4 4 M C57BL6, 2 x ipsilateral Skin injection Ova 24hr Mild Flow cytometry 3.1 WT draining LN (pooled) A647 + Alum 4 4 M C57BL6, 2 x ipsilateral Skin injection E. coli 3 hours Mild Flow cytometry 3.1, 3.2 WT draining LN (pooled) A488 8 4 M C57BL6, 2 x ipsilateral Skin injection 1-4 x 3hrs (4 mice), Mild Flow cytometry 3.3 WT draining LN (pooled) 105 CFU BCG SSI 48hrs (4 mice) 4 1 M C57BL6, 2 x ipsilateral Skin injection 2-8 x 24 hours Mild Flow cytometry 3.3 WT draining LN (pooled) 105 CFU BCG SSI 4 2 M C57BL6, 1 x ipsilateral Skin injection 2-8 x 4 hours Mild Flow cytometry 3.3 WT draining LN 105 CFU BCG SSI 4 2 M C57BL6, 1 x ipsilateral Skin injection 2 x 24 hours Mild Flow cytometry 3.3 WT draining LN 106 CFU BCG Pasteur 6 5 M C57BL6, 1 x ipsilateral Skin injection 2 x 12 weeks Mild IFNγ ELISPOT, 3.4 WT draining LN 106 CFU BCG Flow cytometry Pasteur 15 6 M C57BL6, 1 x ipsilateral Skin injection 1.5 x 3hr (5 mice), Mild Flow cytometry 3.5A-B, 3.7, 5.1C WT draining LN 107 UVKEC 24hr (3 mice), 7 (4 mice), 14 days (3 mice) 8 14 M C57BL6, 1 x ipsilateral Skin injection 1.5 x 2hr (2 mice), 7 Mild Flow cytometry, 3.5C, 4.6 WT draining LN 107 UVKEC, 3mg/kg (8 mice), 14 Anti-mouse IgG indomethacin PO days (8 mice) Antibody ELISA

3 2 M C57BL6, 1 x ipsilateral Skin injection 1.5 x 12hr Mild Immunohistoche 3.6 WT draining LN 107 HKEC mistry

12 6 M C57BL6, 1 x ipsilateral Skin injection 1.5 x 6hr (4 mice), Mild Flow cytometry, 3.8, 3.9, 4.3A, WT draining LN 107 HKEC 24hr (4 mice), qRT-PCR 5.1D, sFig 3.11 48hr (4 mice) 2 0 M C57BL6, 1 x ipsilateral Skin injection 1.5 x 6hr (2 mice) Mild Flow cytometry, 3.9 WT draining LN 107 HKEC Western blot 16 7 M C57BL6, 1 x ipsilateral Skin injection 1.5 x 6hrs (4 mice), Mild Flow cytometry, 4.2, 5.1A-B, 6.3C, WT draining LN 107 HKEC 7 days (4 RT-PCR 6.3G, sFig 3.10, mice), 14 days sFig 6.15C, sFig (4 mice) 6.15G, sFig 6.16 4 0 M C57BL6, 1 x ipsilateral Skin injection 1.5 x 3hr (4 mice), Mild Flow cytometry, 3.9, 4.3B, 5.4A-D, WT draining LN 107 HKEC qRT-PCR 5.5A-B, 5.6A, 5.7A-B, 5.8A, 6.3B, 6.3G, sFig 6.15B, sFig 6.15G, sFig 6.16 8 0 M C57BL6, 1 x ipsilateral Skin injection 1.5 x 6hr (4 mice), Mild Flow cytometry, 3.9, 4.3C, 5.4A-D, WT draining LN 107 HKEC 12hr (4 mice) qRT-PCR 5.5A-B, 5.6A, 5.7A-D, 5.8A 16 0 M C57BL6, 4 x ipsilateral Skin injection 1.5 x 12hr Mild Flow cytometry, 3.9, 4.4, 5.3A-B, WT draining LN pooled 107 HKEC FACS + qRT-PCR 5.4E-H, 5.5C-E, 5.6B-C, 5.7E-H, 5.8B-C 8 8 M C57BL6, 1 x ipsilateral Skin injection 1.5 x 3hrs Mild Flow cytometry 4.4, 5.1C WT draining LN 107 UVKEC, 3mg/kg Indomethacin PO (8 mice only) 12 10 M C57BL6, 1 x ipsilateral Skin injection 1.5 x 6hr (5 x WT, 6 Mild Flow cytometry, 5.2, 5.3C, 5.10, WT draining LN (Flow 107 HKEC x Ifnar1tm1Ag), in vitro 5.12, 5.13, 5.14B, cytometry), lymph 12hr (5 x WT, stimulation assays 6.4A, 6.5, 6.6D, node cell suspensions 6 x Ifnar1tm1Ag) 6.8, 6.9, 6.10, (in vitro) 6.14E-G, 6.11B 4 2 M C57BL6, 1 x ipsilateral Skin injection 1.5 x 12hr Mild Flow cytometry, 3.9, 5.5F-G, 5.9, WT draining LN (Flow 107 HKEC in vitro 5.11, 5.14A, 6.2C, cytometry), LN cell stimulation assays 6.3D, 6.3G, 6.4B, suspensions (in vitro) 6.11A, sFig 6.15D,

sFig 6.15G, sFig 6.16 16 4 M C57BL6, 1 x ipsilateral Skin injection 1.5 x 2hr (4 mice), Mild Flow cytometry 3.9, 6.2A-B, 6.3A- WT draining LN 107 HKEC 6hr (4 mice), C, 6.3E-G, 6.14A- 24hr (4 mice), D, sFig 6.15A-C, 48hr (4 mice) sFig 6.15E-G, sFig 6.16, sFig 3.11 3 2 M C57BL6, 1 x ipsilateral Skin injection 1.5 x 6hr Mild Flow cytometry 6.4A WT draining LN 107 HKEC 0 4 M C57BL/6, LN cell suspensions N/A N/A N/A in vitro 6.6B WT stimulation assays 0 4 M C57BL/6, LN cell suspensions N/A N/A N/A in vitro 6.6C WT stimulation assays 8 1 M WT 2-4 x ipsilateral Skin injection 1.5 x 12hr Mild FACS + qRT-PCR, 3.9, 6.3D, 6.3G C57BL/6 draining LN (pooled) 107 HKEC 6.7, sFig 6.18, sFig 6.15D, sFig 6.15G, sFig 6.15 0 6 M C57BL/6, LN cell suspensions N/A N/A Mild in vitro S1P 6.12C, 6.13C-F, WT chemotaxis sFig 6.17, sFig 6.18 8 0 M C57BL/6, 1 x ipsilateral Skin injection 1.5 x 19hr (4 mice), Mild in vitro S1P 3.9, 6.3E, 6.3G, WT draining LN (flow 107 HKEC 24hr (4 mice) chemotaxis, Flow 6.12D, 6.13G-I, cytometry), LN cell cytometry 6.17, sFig 6.15E, suspensions (in vitro) sFig 6.15G, sFig 6.16, sFig 6.17 0 2 M C57BL/6, Pooled cervical and N/A N/A Mild Flow cytometry sFig 6.19 WT inguinal lymph nodes Total 177 Total 100 Table 2.12: Overview of the use of animals in this thesis This table details all of the animals used to generate the data presented in this thesis. In most cases controls represent mice not injected with an inflammatory stimulus. However, in some cases control refers to mice injected with an inflammatory stimulus in the absence of a genetic defect or a pharmacological procedure. Please see the statistical analysis section (Section 2.2.8) and relevant results figures for details of study design and sample size determination. Abbreviations; FACS: fluorescence-activated cell sorting, HKEC: heat-killed E. coli, IHC: immunohistochemistry, LN: lymph node, qRT-PCR: quantitative reverse transcriptase polymerase chain reaction, S1P: sphingosine-1-phosphate, UVKEC: UV-killed E. coli

2.2.1.2 Murine earflap injection This protocol is based upon methods outlined by Li et al (402). Mice were anaesthetised and their right ear pinna applied onto an injection platform (Figure 2.1). The injection platform is a band of adhesive tape wrapped around a secured 15ml falcon tube (Figure 2.1). The earflap skin was then injected using a specialised 10μl syringe and fitted with a 31G-33G needle or a 0.3ml 30G insulin syringe (BD, 324826). Hamilton microliter syringes were cleaned between experiments and separate syringes were used for injections of different stimuli and their respective control solutions. The following stimuli were prepared and injected as described in the following sections.

Figure 2.1: Murine earflap injection (A) Diagram of the murine earflap injection platform, reproduced from Li et al 2012 (402). Permission to reproduce this figure has been granted by Springer Nature, Nature Protocols. (B) Annotated photo of injection platform used to inject the murine earflap in this thesis: M: Anaesthetic Mask, F: 15ml falcon tube, P: Ear platform.

2.2.1.2.1 BCG Statens Serum Institut (SSI) Lyophilised BCG SSI and BCG vaccine diluent were procured from Public Health England (PHE). One vial of lyophilised BCG contains 2-8 x 106 CFU BCG. 100μl of BCG vaccine diluent was used to resuspend one vial of BCG lyophilate to create a 100μl solution with a concentration of 2-8 x 107 CFU/ml. 5 or 10μl of this solution was then injected using a 10μl syringe (Hamilton, 7635- 01/00) fitted with a 33G needle (Hamilton, 7803-05) to deliver a dose of 1-4 x 105 CFU or 2-8 x 105 CFU respectively. BCG vaccine diluent was used for control injections.

2.2.1.2.2 BCG Pasteur A stock vial of BCG Pasteur (stored at -80℃) kindly provided by Dr Meera Mehta was thawed and subsequently cultured in 20ml of sterile 7H9 Middlebrook broth (kindly provided by Dr Meera Mehta) in a shaking incubator (100rpm, 37℃) for 7 days. BCG solution was supplemented to achieve a glycerol content of 5% v/v, aliquoted at a concentration of

10 8 approximately 2 x 10 CFU/ml (OD600 = 0.6) and stored at -80℃ until required for injection. 10μl of this solution was injected using a 31G 10µl syringe (Hamilton, 80308) to deliver a dose of 2 x 106 CFU. Sterile broth cultured in parallel with BCG was used for control injections.

2.2.1.2.3 Fluorescent E. coli bioparticles A488-labelled E. coli bioparticles (Thermo Fisher, E-13231) were injected at a dose of 1 x 107 bioparticles in a volume of 10μl into the murine earflap using a 31G 10µl syringe needle (Hamilton, 80308). PBS was used for control injections.

2.2.1.2.4 Ovalbumin A647: alum 33μg of A647-conjugated ovalbumin (Thermo Fisher, O34784) mixed with 50μg Alum (Thermo Fisher, 77161) was injected into the murine earflap in a volume of 10μl using a 31G 10μl syringe needle (Hamilton, 80308). Sterile PBS was used for control injections.

2.2.1.2.5 UV-killed E. coli (UVKEC) UV-killed E. coli (strain: NCTC10418) was kindly provided by my colleague Dr Madhur Motwani at a concentration of 1.5 x 109 CFU/ml. 10µl of this solution was injected using a 31G 10μl syringe needle (Hamilton, 80308) to deliver a dose of 1.5 x 107 CFU. PBS was used for control injections.

2.2.1.2.6 Heat-killed E. coli (HKEC) E. coli bacteria (strain: NCTC10418) were cultured, enumerated and heat-killed as described in Section 2.2.3.2. Frozen aliquots with a concentration of 1.6 x 109 CFU/ml were thawed and 10μl was injected using a 30G 0.3ml insulin syringe (BD, 324826) to deliver a dose of 1.6 x 107 CFU.

2.2.1.3 Indomethacin: rationale, preparation and oral gavage Indomethacin was used in this thesis to explore the effects of cyclooxygenase inhibition on LN neutrophil infiltration and adaptive immune responses. These experiments were modelled upon those performed by Yang and Unanue (312). Yang and Unanue also used indomethacin to inhibit cyclooxygenase in vivo and this is the only study to have demonstrated a link

10 determined using a CFU: OD curve for mycobacterium tuberculosis kindly provided by Dr Meera Mehta 89

between cyclooxygenase inhibition, LN neutrophil infiltration and the developing adaptive immune response. Thus, indomethacin was the cyclooxygenase-inhibitor of choice in this thesis as it facilitated better comparison of the results of this thesis with those of Yang and Unanue (312).

Indomethacin (Sigma, I7378) was administered at a dose of 3mg/kg, based on an assumed mouse weight of 25g. Indomethacin was therefore weighed out and resuspended to a concentration of 0.075mg/100μl. Indomethacin powder was crushed using a pestle and mortar and gradually resuspended in the appropriate volume of 1% w/v tragacanth (Sigma, G1128) in distilled water. 100μl of this indomethacin suspension or untreated tragacanth solution (vehicle control) was then delivered to each mouse using an oral gavage needle attached to a 1ml syringe (Terumo, GS572).

2.2.2 Tissue collection and processing

2.2.2.1 Identification of the cervical lymph node draining the murine earflap Lymph nodes draining the murine earflap were identified via injection of 50μl of 10% India ink (diluted in PBS, Winsor & Newton, 1040030) into the murine earflap immediately after death. The murine earflap is drained by cervical lymph nodes (403) and therefore (after allowing 5-10 minutes to allow the ink to drain) the cervical structures of the mouse were explored. One lymph node was stained following this procedure and it is positioned lateral to the ipsilateral mandibular salivary gland and adjacent/superficial to the junction between the facial vein and the lingual vein to form the linguofacial vein. This is consistent with the location of the superficial parotid lymph node (403–405).

2.2.2.2 Peritoneal washout The parietal peritoneum of culled mice was exposed using dissection forceps and scissors and the 2ml of cell dissociation buffer (Gibco, 13151-041) was injected between the visceral and parietal peritoneum using a 26G needle (BD, 303800) fitted to a 5ml syringe (Terumo, GS575). The mouse was then briefly manipulated to ensure mixture of the injected fluid in the peritoneal space. The fluid in the peritoneal space was then aspirated using a sterile Pasteur pipette and transferred to a 1.5ml Eppendorf or 15ml falcon and stored on ice.

2.2.2.3 Plasma Blood samples were obtained via cardiac puncture under terminal anaesthesia. Blood was collected using a 23G needle (BD, 300800) attached to a 1ml syringe (Terumo, GS572) and transferred to a 1.5ml Eppendorf containing 8μl of 0.5M EDTA, gently mixed and stored on ice. Blood was subsequently centrifuged for 15 minutes at 4℃ with the centrifuge brake switched off and the resulting supernatant (plasma) was aliquoted into 0.5ml protein Lobind tubes (Eppendorf, 022431064) for storage at -80℃.

2.2.2.4 Generation of single-cell suspensions

2.2.2.4.1 Lymph nodes Single cell suspensions can be generated from lymph nodes by an array of mechanical and digestive methods. These methods vary substantially between published studies, although certain methods are more commonly used to study particular cell types (Tables 2.13-2.20). Mechanical disaggregation is routinely adopted for the study of lymphocytes (Table 2.13), whereas short digestion protocols are utilised to a greater degree in the study of dendritic cells (Table 2.18) and long detailed digestion protocols are utilised in the study of stromal cells (Table 2.20).

This thesis focussed upon the study of lymphocytes, neutrophils and monocytes and utilised mechanical disaggregation to analyse these cell types in the dLN. Mechanical disaggregation was preferred in this thesis for a number of reasons. Firstly, the speed of mechanical disaggregation relative to digestive methods increased both the number of lymph nodes and the number of analytical methods that could be processed in a single experiment. This ultimately reduced the number of animals used in this thesis. Secondly, several published studies of lymph node lymphocytes, neutrophils and monocytes have also utilised mechanical methods of lymph node disaggregation (Table 2.15). Although other studies have employed digestive methods (Table 2.16), it is unclear whether the yield of these cell types differs between mechanical and digestive methods of lymph node processing as these methods have not been directly compared in the published literature. It can be argued that such a direct comparison should have been performed for this thesis. However, as outlined in Figure 2.2, such an experiment would require the use of a large number of mice to demonstrate even an improbably large 50% difference between mechanical dissociation and just one of the many different published digestion protocols (Figure 2.2). The decision to utilise mechanical lymph node dissociation was therefore justified by the fact that (1) there is no published evidence to suggest that digestive methods are preferable to mechanical methods in the isolation of

neutrophils and monocytes and (2) the experiments required to answer this question would require the use of an unacceptably large number of mice. This would not be compatible with the 3Rs principle of reduction, given the good yield of neutrophils and monocytes achieved by mechanical disaggregation.

Figure 2.2: Sample sizes required to compare the neutrophil and monocyte yield of a mechanical and a digestive method of lymph node disaggregation (A) The yield of neutrophils and monocytes from all lymph nodes harvested 6 and 12 hours following the intradermal/subcutaneous injection of 1.5 x 107 heat-killed E. coli in this thesis is pooled to estimate the sample size required to detect a 50% difference in either neutrophil or monocyte yield between any mechanical and digestive method of lymph node disaggregation with a statistical power of ≥90% and a significance level of 0.05. (B) These sample size estimates assume analysis by the two-sample t-test and therefore assume the data is normally distributed. Thus, normal probability plots are provided for each dataset to illustrate that these datasets are normally distributed. N = 14 x 6hr draining lymph nodes and n= 14 x 12hr draining lymph nodes NC3R: 28 mice in total.

2.2.2.4.1.1 Mechanical disaggregation Excised lymph nodes were immediately immersed in 1ml FACS buffer (Table 2.3), sterile lymphocyte culture medium (Table 2.2) or sterile chemotaxis buffer (Table 2.2) depending on the experiment. Lymph nodes were dissociated from surrounding tissue and fat using two 21G needles (Figure 2.3) and then mechanically disaggregated against a 35µm (Corning, 352235) or 70µm cell strainer (Corning, 352350) using a 1ml or 5ml syringe plunger respectively. The resulting solution was washed through the filter using medium, centrifuged in a 1.5ml Eppendorf or a 15ml falcon tube at 500g for 5 minutes and the resulting cell pellet resuspended in 1ml of appropriate medium. All solutions were supplemented with 10μg/ml brefeldin-A (Biolegend, 420601) if lymph node cells were to be immediately analysed by intracellular cytokine staining.

Figure 2.3: Lymph node isolation from surrounding tissue 2 x india ink stained cervical lymph nodes before (A) and after (B) removal of surrounding tissue using 2 x 21.5G needles. (B) – Removed tissue is circled in red, isolated lymph nodes are circled in black.

2.2.2.4.1.2 Digestion Experiments depicted in Chapter 3 also included a digestion step for the processing of lymph nodes as per Yang and Unanue 2013 (312). However, this step was removed from the protocol when it was illustrated that lymph node neutrophils could still be isolated by simple mechanical disaggregation (Figure 2.4). Removing this step increased the number of lymph nodes that could be processed simultaneously. For digestion, whole lymph nodes were incubated (water bath, 37℃) for 30 minutes in sterile RPMI 1640 solution supplemented with Liberase TL (Roche, 05401020001) to an activity of 1 wunsch unit/ml. Lymph nodes were then mechanically disaggregated and the enzyme mixture neutralised by a dilution and wash in PBS, 4mM EDTA. Thereafter the cell suspension was processed as described in Section 2.2.2.4.1.1.

Figure 2.4: Yield of neutrophils in the absence of digestion Mice were injected with 1.5 x 107 CFU of UV-killed E. coli into the skin of the earflap and ipsilateral (ipsi) and contralateral (contra) superficial parotid lymph nodes harvested 3hrs later. Lymph nodes were derived into a single cell suspension using only mechanical disaggregation and then stained for flow cytometry. (NC3R = 2 mice in total)

2.2.2.4.2 Spleens Spleens were mechanically disaggregated against a 70μm filter (Corning, 352350) using a 5ml syringe plunger. This splenocyte cell suspension was centrifuged at 500g for 5 minutes and the resulting pellet resuspended in 3ml of Ack lysis buffer (Lonza, 10-548E) and incubated for 5-10 minutes at room temperature to lyse erythrocytes. 7ml of PBS was then added and the solution centrifuged at 500g for 5 mins, the resulting pellet being resuspended in 3-8ml of appropriate medium.

Methods of lymph node dissociation used by studies referenced in this thesis Table 2.14: Digestive methods - Lymphocytes

Table 2.13: Mechanical methods - Lymphocytes T cells and B cells Author (et al) Year PD Enzymes Duration Temp T cells and B cells (mins) Author Year Method Catron (157) 2010 Yes Collagenase NS NS Carrasco (160) 2007 NS Collagenase IV, DNAse I 30 37℃ Phan et al (174) 2007 70µm cell strainer Ciabattini et al (228) 2008 Nylon mesh Phan (175) 2009 Yes 0.2mg/ml Liberase Blendzyme 2, 20-30 NS 20ug/ml DNAse I Grigorova et al (83) 2009 70µm cell strainer Olson* (49) 2012 Yes 125U/ml collagenase type II, 60U/ml 30 min 37℃ Suzuki et al (114) 2009 ‘teased apart’ DNAase type II Grigorova et al (84) 2010 70µm cell strainer Mc (167) 2014 NS Liberase DH NS NS Sensken et al (400) 2011 Not specified Gaya (583) 2015 NS 8ug/ml Collagenase IV, 20ug/ml 30 min 37℃ Thangada et al (151) 2010 Not specified DNAse I Mendoza et al (91) 2012 70µm cell strainer Benechet (693) 2016 NS 100U/ml Collagenase NS NS Groom et al (247) 2012 Tweezers NK cells

Tsuboi et al (106) 2013 Nylon mesh Author (et al) Year PD Enzymes Duration Temp

Denton et al* (112) 2014 Frosted slides (mins) Moalli et al (477) 2014 Not specified Wong (357) 2018 Yes 1.67 Wunsch units/ml Liberase TM, NS NS Nakai et al (153) 2014 40µm cell strainer 0.2mg/ml DNAse I Radtke et al (225) 2015 Frosted slides and Nylon Mesh Rantakari et al* (92) 2015 44µm cell strainer Cauwelaert et al (279) 2016 Not specified Desbien et al* (266) 2016 Not specified *studies that utilised mechanical and digestive methods to analyse different cell Suzuki et al (154) 2016 40µm cell strainer types. PD = Prior Mechanical Disruption. NS = Not stated Druzd et al (155) 2017 40-70µm cell strainer NK Cells Author Year Method Coombes et al* (355) 2012 70µm cell strainer Pak-Wittel et al* 2012 70µm cell strainer (307) Denton et al* (112) 2014 Frosted slides

Cauwelaert et al (279) 2016 Not specified

*studies that utilised mechanical and digestive methods to analyse different cell types

Table 2.15: Mechanical methods – Neutrophils and Monocytes Table 2.16: Digestive methods - Neutrophils and Monocytes Neutrophils Neutrophils Author (et al) Year PD Enzymes Duration Temp Author Year Method (mins) Maletto et al* 2006 ‘Gently pressing the organs through Maletto et al* 2006 NS 400U/ml collagenase D, 50ug/ml 45 min 37℃ (203) a stainless-steel mesh’ (203) DNAse I Gorlino et al (367) 2014 Mechanical Chtanova et al 2008 NS Collagenase NS NS Hampton et al* 2015 ‘Mechanical disruption and passed (368) (209) through a 100µm filter’ Yang et al (312) 2013 NS Liberase TL 30 min 37℃ Parsa et al (372) 2016 ‘Mechanical dissociation of the Mohr et al (80) 2009 NS 1mg/ml collagenase II, 0.15mg/ml 20 min Room organs in ice cold PBS’ DNAse I Bogoslowski et al 2018 ‘gently pressed through a 40µm Calabro et al 2011 NS 0.8mg collagenase D, 30 min 37℃ (173) strainer to create a single cell (204) 0.25mg DNAse I suspension’ Hampton et al* 2015 NS 5mg collagenase, NS NS Monocytes (209) 5U RQ1 DNAse Author Year Method Sagoo et al (328) 2016 Yes 1mg/ml collagenase D, 50ng/ml 15 min 37℃ Mitchell et al (369) 2012 Cell strainer DNAse I Mitchell et al (370) 2013 Cell strainer Monocytes Author (et al) Year PD Enzymes Duration Temp (mins) Leon et al (207) 2007 Yes 0.5mg/ml collagenase A, 40mg/ml 10 mins 37℃ *studies that utilised mechanical and digestive methods to analyse different cell DNAse I types. Mohr et al (80) 2009 NS 1mg/ml collagenase II, 0.15mg/ml 20 min, Room DNAse I Temp Lee et al (218) 2011 NS Liberase 3 NS NS Calabro et al 2011 NS 0.8mg collagenase D, 30 min 37℃ (204) 0.25mg DNAse I Coombes (355) 2012 Yes 50mg/ml Type VIII collagenase, 30 min 37℃ Han et al (382) 2014 Yes 50mg/ml Type VIII collagenase, 30 min 37℃ Xu et al (465) 2015 Yes 1.67 Wunsch units/ml Liberase TM, NS NS 0.2mg/ml DNAse I Desbien et al* 2016 NS 8ug/ml collagenase IV, 30 min 37℃ (266) 20ug/ml DNAse I Sagoo et al (328) 2016 Yes 1mg/ml collagenase D, 15 min 37℃ 50ng/ml DNAse I Sammicheli et al 2016 Yes 250mg/ml Liberase CI, 40 min 37℃ (381) 50mg/ml DNase I Cioncada et al 2017 NS 500ug/ml Liberase, 60 min 37℃ (263) 250ug/ml DNAse I De Koker et al 2017 NS Collagenase type IV NS NS (242) Wong et al (357) 2018 Yes 1.67 Wunsch units/ml Liberase TM, NS NS 0.2mg/ml DNAse I

Langlet et al (383) 2012 Yes Collagenase type II, DNAse I 20 min Room Table 2.17: Mechanical methods - Dendritic Cells Temp Plantinga et al 2013 NS Liberase TM, 10U DNase NS NS Dendritic cells (189) Author Year Method Tamoutounour et 2013 Yes Collagenase type II, DNAse NS NS Ohl et al (192) 2004 Nylon mesh al (384) Groom et al (247) 2012 Tweezers Chakarov et al 2014 NS 125ug/ml Liberase TL, 40ug/ml DNAse I NS NS (208) Parsa et al (372) 2016 ‘Mechanical dissociation of the organs in ice cold PBS’ Ulvmar et al (88) 2014 Yes 1mg/ml collagenase D, 1mg/ml Dispase NS NS II, 0.2mg/ml DNAse Denton et al* (112) 2014 Yes 1mg/ml collagnease, 0.1mg/ml DNase I 25 min Room (from Allan 2003) Table 2.18: Digestive methods - Dendritic Cells Eickhoff et al (184) 2015 NS Collagenase D, DNAse NS NS Hor et al* (165) 2015 Yes 1mg/ml collagenase type III, 20ug/ml 20 mins NS DNAse Dendritic Cells Rantakari et al* 2015 NS 1mg/ml collagnease D, 50ug/ml DNAse I 30 min 37℃ Author (et al) Year PD Enzymes Duration Temp (92) (mins) Desbien et al* 2016 NS 8ug/ml collagenase IV, 20ug/ml DNAse I 30 min 37℃ Itano et al (158) 2003 Collagenase 1mg/ml, DNAse 0.02mg/ml 25 mins 22℃ (266) (from Vremec 1992) Druzd et al (155) 2017 Yes 1mg/ml collagenase IV, 0.2mg/ml 30 min 37℃ Allan et al (188) 2006 Yes 1mg/ml collagenase type II, 1mg/ml NS NS DNase I DNAse I Junt et al (159) 2007 Yes 250ug/ml Liberase CI, 50ug/ml DNAse I 40 min 37℃ Jang et al (194) 2006 NS 400 Mandl units/ml collagenase D, 45-90 37℃ Baratin et al (69) 2017 Yes 1mg/ml Liberase, 0.1mg/ml Dnase I 45 min 37℃ 10ug/ml DNAse I min Chatziandreou 2017 Yes 0.5mg/ml Collagenase P, 0.28mg/ml 10 min 37℃ Pape et al (156) 2007 Yes Collagenase 1mg/ml, DNAse 0.02mg/ml 25 mins 22℃ (171) DNAse I, 1U/ml Dispase (from Vremec 1992) Mohr et al (80) 2009 NS 1mg/ml collagenase II, 0.15mg/ml 20 min Room Allenspach et al 2008 Yes 1mg/ml collagenase type II, 0.02mg/ml 25 min 22℃ DNAse I Temp (191) DNAse I (from Vremec 1997) Calabro et al (204) 2011 NS 0.8mg collagenase D, 0.25mg DNAse I 30 min 37℃ ℃ Manolova et al 2008 NS 1mg/ml collagenase D, 0.04mg/ml 30 min 37 Coombes et al 2012 Yes 50mg/ml Type VIII collagenase, 30 min 37℃ (163) DNAse I (355) ℃ Lee et al (164) 2009 Yes 2mg/ml collagenase D, 30ug/ml DNAse I 30 min 37 Sagoo et al (328) 2016 Yes 1mg/ml collagenase D, 50ng/ml DNAse I 15 min 37℃ Nakano et al (205) 2009 Yes 1mg/ml collagenase A, 0.2mg/ml DNAse 35 min 37℃ Cioncada et al 2017 NS 500ug/ml Liberase, 60 min 37℃ I (263) 250ug/ml DNAse I Cheong et al (387) 2010 NS 400U/ml Collagenase D 30 min 37℃ Gonzalez et al 2010 NS Collagenase D or Liberase, DNAse I NS (168) Siddiqui et al (386) 2010 Yes 1mg/ml Collagenase type VIII 40 min 37℃ *studies that utilised mechanical and digestive methods to analyse different cell Braun et al (85) 2011 Yes 100ug/ml Blendzyme2, 0.3mg/ml 30 min 37℃ types. PD = Prior Mechanical Disruption. NS = Not stated DNAse Moussion et al (98) 2011 NS Type D collagnease NS NS Zhu et al (333) 2011 NS 2mg/ml collagenase, 100ug/ml DNAse 30 min 37℃ (from Wang 2005) Caproni et al (274) 2012 Yes Collagenase D, DNAse I 15 min 37℃

Table 2.19: Digestive methods - Macrophages Macrophages Author (et al) Year PD Enzymes Duration Temp Table 2.20: Digestive methods - Stromal Cells (mins) Stromal Cells Gray et al* 2012 Yes 67ug/ml Liberase, 20ug/ml DNAse I 20 minutes NS Author (et al) Year PD Enzymes Duration Temp (388) (mins) Rantakari et 2015 NS 1mg/ml collagnease D, 50ug/ml 30 min 37℃ Link et al (62) 2007 Yes 1mg/ml collagenase IV, DNAse I 50 min (2 37℃ al* (92) DNAse I (40mg/ml), collagenease D stages) Desbien et al* 2016 NS 8ug/ml collagenase IV, 20ug/ml 30 min 37℃ Pham et al (89) 2010 Yes 0.2mg/ml Blendzyme 2, 100ug/ml 25 min 37℃ (266) DNAse I DNase Coombes et al 2012 Yes 50mg/ml Type VIII collagenase, 30 min 37℃ Bao et al (105) 2010 Yes 0.2mg/ml collagenase I, 0.2mg/ml 95 min 37℃ (355) dispase I + trypsin for 5 min Junt et al (159) 2007 Yes 250ug/ml Liberase CI, 50ug/ml DNAse 40 min 37℃ Chyou et al 2011 Yes 564U/ml collagenase type II, 40ug/ml 30 min 37℃ I (335) DNAse I Phan et al 2009 Yes 0.2mg/ml Liberase Blendzyme 2, 20-30 min NS Fletcher et al 2011 Yes 0.2mg/ml Collagenase P, 0.8mg/ml 50-60 min 37℃ (175) 20ug/ml DNAse I (732) Dispase, 0.1mg/ml DNAse I Barral et al 2010 Yes 250ug/ml Liberase CI, 50ug/ml DNAse 40 min 37℃ Malhotra et al 2012 Yes 0.2mg/ml Collagenase P, 0.8mg/ml 50-60 min 37℃ (363) I (330) Dispase, 0.1mg/ml DNAse I (from ℃ Iannacone et al 2010 Yes 250mg/ml Liberase CI, 50mg/ml 40 min 37 Flecter et al 2010) (170) DNase I Sung et al (329) 2012 NS 0.2mg/ml collagenase P, 0.1mg/ml 60-90 min 37℃ ℃ Moseman et al 2012 Yes 250mg/ml Liberase CI, 50mg/ml 40 min 37 DNAse I, 0.8mg/ml Dispase (147) DNase I Bai et al (132) 2013 Yes 0.1% type I collagenase, 2ug/ml 45 min 37℃ ℃ Gaya et al 2015 NS 8ug/ml Collagenase IV 30 min 37 DNAse I (583) Heesters et al 2013 Yes 0.26U Liberase DH, 0.2mg/ml DNase I 45 min 37℃ ℃ Baratin et al 2017 Yes 1mg/ml Liberase, 0.1mg/ml Dnase I 45 min 37 (113) (modified from El Shikh 2006) (69) Benahmed at 2014 Yes 564U/ml collagenase type II, 40ug/ml 30 min 37℃ ℃ Chatziandreou 2017 Yes 0.5mg/ml Collagenase P, 0.28mg/ml 10 min 37 al (338) DNAse I (171) DNAse I, 1U/ml Dispase Yang et al (336) 2014 Yes 1mg/ml collagenase IV, 1mg/ml 50 min (2 37℃ ℃ Sagoo et al 2016 Yes 1mg/ml collagenase D, 50ng/ml 15 min 37 collagenease D stages) (328) DNAse I Acton et al 2014 Yes 0.2mg/ml Collagenase P, 0.8mg/ml 50-60 min 37℃ Wong et al 2018 Yes 1.67 Wunsch units/ml Liberase TM, NS NS (334) Dispase, 0.1mg/ml DNAse I (357) 0.2mg/ml DNAse I Jarjour et al 2014 Yes 0.2mg/ml Collagenase P, 0.8mg/ml 50-60 min 37℃ (117) Dispase, 0.1mg/ml DNAse I Astarita et al 2015 Yes 0.2mg/ml Collagenase P, 0.8mg/ml 50-60 min 37℃ *studies that utilised mechanical and digestive methods to analyse different cell (347) Dispase, 0.1mg/ml DNAse I Mondor et al 2016 NS 400U/ml Collagenase I, 0.1mg/ml 50-60 min 37℃ types. PD = Prior Mechanical Disruption. NS = Not stated (345) DNAse I, 1mg/ml Dispase Huang et al 2018 Yes 3mg/ml Collagenase IV, 40ug/ml 30 min 37℃ (79) DNAse I Yu et al (569) 2017 Yes 0.2mg/ml Collagenase P, 0.8mg/ml 60 min 37℃ Dispase, 0.1mg/ml DNAse I

2.2.2.5 Cell enumeration Cells were counted using either an automated cell counter (Thermo Fisher, Countess) or a haemocytometer (the former was used in the majority of cases). Trypan blue was used as a viability dye to calculate the percentage of live cells in the sample. The following formula was used to count cells using a haemocytometer:

Cells/ml = Average Number of Cells per Quadrant x 104 x Dilution Factor (if applicable)

2.2.3 Bacteria

2.2.3.1 E. coli culture 200ml of lysogeny broth (LB) (Sigma, L7275) was seeded with E. coli bacteria (strain: NCTC10418) using a 10μl inoculating loop and then cultured for a period of 26.5 hours at 37℃ in a shaking incubator at 180rpm. The optical density of the broth was measured every 90 minutes in order to generate a growth curve (Figure 2.5). 6 hours was identified as the earliest time point in the log phase of the growth curve and the bacterial concentration of the solution at this time point was calculated by enumerating colony-forming units on LB agar (Sigma, L2897) plates (Figure 2.5) using the following formula:

CFU/ml = Average Number of CFU per Plate x 10 x Dilution Factor (if applicable)

The optical density (OD595) at 6 hours is approximately 0.5, which equates to a bacterial concentration of approximately 7.5 x 108 CFU/ml (Figure 2.5).

Figure 2.5: Growth and enumeration of E. coli bacteria (A) A growth curve for E. coli bacteria (strain NCTC10418) seeded into 200ml of lysogeny

broth (LB) and cultured in an Erlen-Meyer flask for 26.5 hours at 37℃ in a shaking incubator at 180rpm. (B) Photo depicts colony-forming units (CFUs) on agar plates seeded with 100ul of 6-hour culture solution diluted by a factor of 106. (C) Table summarising the results of 3 experiments performed in order to determine the bacterial concentration after 6 hours of culture.

2.2.3.2 E. coli killing Depletion of the stock of UV-killed E. coli provided by Madhur Motwani rendered it necessary to generate another stock of killed E. coli for injection. However, several attempts at UV-killing failed to achieve 100% killing (Figure 2.6A-B). Therefore, a method of heat-killing was adopted to generate killed E. coli for further experiments (Figure 2.6A-B). 1ml aliquots of E. coli bacteria in PBS (OD595 of 0.9) were heat-killed by exposure to 65℃ in a heat block for 30 minutes. Subsequent culture on agar plates confirmed lack of growth of bacteria from the heat-killed solution (Figure 2.6A-B). A sample of this E. coli solution (OD595 0.9) was spared from heat- killing in order to determine the solution’s bacterial concentration (1.6 x 109 CFU/ml). There was a concern that heat-killing may denature E. coli antigens and thereby alter the inflammatory response relative to UV-killed E. coli. However, the fact that anti-E. coli antibodies generated by UVKEC-immunised mice bound HKEC similarly to UVKEC in a whole-

cell E. coli antibody ELISA (Section 2.2.3.3) suggests that immunogenic antigens are not denatured during the process of heat-killing (Figure 2.6C).

Figure 2.6: Killing of E. coli bacteria (A) Photos of agar plates seeded with E. coli bacteria exposed to room temperature for 30 minutes (left), UV-light for 60 minutes at room temperature (middle) and 65℃ for 30 minutes. (B) Effect of 30-minute exposure to range of temperatures or 1-hour exposure to UV-light on E. coli viability. (C) Whole-cell E. coli antibody ELISA comparing the binding of anti-E. coli IgG antibodies from mice immunised with UV-killed E. coli (UVKEC) to plates coated with either heat-killed E. coli (HKEC) or UVKEC. N = 1 x Day 14 UVKEC plasma and n= 1 x CTRL plasma. Imm: Immunised, CTRL: control plasma. NC3R: 2 mice in total.

2.2.3.3 Whole-Cell E. coli antibody ELISA This protocol was adapted from a protocol kindly provided by Dr Win Yan Chan. Half-area high- binding 96 well ELISA plates (Corning, 3690) were coated with 35μl of killed E. coli solution

(OD600 = 1.18) and incubated overnight at 4 degrees Celsius. Plates were then washed three times using wash buffer (PBS 0.05% Tween-20) and then blocked for 4 hours at 4 degrees Celsius with blocking buffer (PBS 1% BSA). Plates were then washed twice before serial dilutions of murine plasma were added at a volume of 35μl per well incubated overnight at 4℃. Plasma from each mouse was aliquoted at the following dilutions; 1/25, 1/50, 1/100, 1/250, 1/500, 1/1000 and 1/2000. Plates were then washed 5 times before the addition of 35μl/well 1:1000 anti-mouse IgG Fc conjugated to alkaline phosphatase (Sigma, A2429) and incubated at room temperature for 2 hours. Plates were then washed 5 times before the addition of 35μl/well 1mg/ml p-Nitrophenyl Phosphate (Sigma, N1891), which was incubated for 20 minutes at room temperature before the reaction was stopped by the addition of 100

35μl/well of 3M Sodium Hydroxide. The optical density (OD) at 450nm (reference of 630nm) of each well was then immediately measured using a spectrophotometer (BMG-labtech, FLUOstar). The antibody titre was defined as the reciprocal of the highest plasma dilution that gives a reading above the antibody titre threshold (406). The antibody titre threshold was set at an optical density of 0.06 as this figure was more than double the average background optical density and was therefore judged to represent specific antibody binding.

2.2.4 Cell culture and stimulation

Cell culture refers to incubation at 37℃, 5% CO2. All BCG experiments (including IFNγ ELISPOTs) were performed in a microbiological safety cabinet in a category 2 laboratory.

2.2.4.1 BCG recall assays

2.2.4.2 IFNγ ELISPOT

Lymphocyte culture for IFNγ ELISPOTs is based on methods outlined by Minassian et al (407). Lymph nodes and spleens were harvested from BCG-vaccinated and unvaccinated mice and processed as described above to generate single-cell suspensions. Cell solutions were resuspended in lymphocyte culture medium to a concentration of 2.5 x 106 cells/ml and then supplemented with 1mg/ml tuberculin purified protein derivative (PPD) (Statens Serum Institut, 2390) to achieve a final PPD concentration of 20μg/ml. Cells were cultured for 20 hours. Cells cultured in the absence of PPD and in the presence of 2.5ng/ml phorbol myristate acetate (PMA, BioVision, 1544-5) and 500ng/ml ionomycin (Cayman, 10004974) served as negative and positive controls respectively (Figure 2.7A).

IFNγ ELISPOTs were performed using a murine IFNγ ELISPOT set (Diaclone, 862.031.005) and sterile ELISPOT plates (Millipore, MSIPS4510). This assay was performed according to manufacturer’s instructions and therefore cells were cultured at a volume of 100ul/well in 96- well ELISPOT plates pre-coated with murine IFNγ capture antibody. Once processed, ELISPOT plates were analysed using an ELISPOT Reader (AID, ViruSpot). Count settings were set through a combination of trial and error and software guidance provided by Mabtech (408). All ELISPOT wells were enumerated using the same count settings.

101

Figure 2.7: IFNγ ELISPOT controls (A) Examples of positive (2.5ng/ml PMA and 500ng/ml ionomycin) and negative (no stimulant) control wells from an IFNγ ELISPOT plate. (B) Example flow cytometry plots illustrating the population of CD4+ve IFNγ+ve cells that appear following in vitro stimulation of ipsilateral lymph node cells from BCG Pasteur (2 x 106 CFU)-immunised mice with PPD. (C) Graphs comparing the numbers of IFNγ spot-forming units (SFUs) and CD4+ve IFNγ+ve cells detected using an IFNγ ELISPOT and intracellular cytokine staining respectively (conducted in parallel). N = 2 x BCG immunised dLN, 2 x CTRL LN, 2 x BCG immunised spleen and 2 x CTRL spleen. NC3R: 4 mice in total. IFNγ: interferon- gamma, Imm: immunised, dLN: draining lymph node, SPL: spleen, CTRL: control, PPD: mycobacterial purified protein derivative. 2.2.4.3 Intracellular cytokine staining

Lymph node and spleen cells from BCG-vaccinated or control mice were cultured in the presence or absence of 20μg/ml PPD at a concentration of 5 x 106 cells/ml. Cells were cultured in a 24-well tissue culture plate (Corning, 3527) in a volume of 1.5ml/well. The culture duration was 22 hours, with cells being cultured in the presence of 10μg/ml brefeldin-A (Sigma, B5936) for the final 6 hours of culture as per Nadakumar et al (409). Cells were thereafter stained for intracellular IFNγ (Section 2.2.5.1.2).

2.2.4.4 In vitro stimulation of lymph node and spleen cells Lymph node cells or splenocytes were derived into single-cell suspensions as described in Section 2.2.2.4 and then resuspended in lymphocyte culture medium to a concentration of 1 x 106 cells/ml or 2 x 106 cells/ml. 500μl or 1ml of these cell suspensions were then aliquoted into 102

the wells of a 48-well tissue culture treated plate (Corning, 353078) and cultured in the presence of 200-20,000 units/ml of IFNβ (R&D, 8234-MB-010), 20ng/ml IFNγ (Peprotech, 315- 05) or 7.5. x 107 CFU/ml of HKEC for a period of 2-6 hours. Thereafter, cells were processed for analysis by flow cytometry and/or qRT-PCR as described in sections 2.2.5 and 2.2.6. Culture medium was not supplemented with 10μg/ml brefeldin-A (Biolegend, 420601), even if cells were to be subsequently analysed by intracellular cytokine staining (Section 2.2.5.1.2).

2.2.4.5 Chemotaxis assays This S1P chemotaxis protocol was based on methods outlined by Sensken et al (400). Lymph nodes and spleens were derived into single cell suspensions as described in Section 2.2.2.4 and resuspended in chemotaxis medium (Table 2.2) to a concentration of 2.5 x 106 cells/ml. 2 x 106 cells were seeded into the wells of a 48-well tissue culture treated plate (Corning, 353078) in a volume of 800μl and cultured for 2-4 hours (unless otherwise indicated) in the presence or absence of 2000 or 10,000units/ml IFNβ (R&D, 8234-MB-010).

All chemotaxis assays were performed using transwell inserts (polycarbonate membrane, 5μm pore size) in a 24-well transwell plate (Corning, 3421). Bottom chambers were filled with 600μl of chemotaxis medium (Table 2.2) supplemented with 1-20nM sphingosine-1-phosphate (Sigma, S9666-1MG), methanol (S1P diluent control), or 300ng/ml CXCL12 (Peprotech, 250- 20A). 2 x 106 live cells were added to the top chambers in a volume of 100μl and the transwell plate was cultured for 3 hours. Transmigrated cells from the bottom chamber and remaining cells in the top chamber were harvested and stained separately for flow cytometry. Accucheck counting beads (Thermo Fisher, PCB100) were used to enumerate the number of cells that transmigrated into the bottom chamber as described in Figure 2.8. Beads were resuspended and then added to cell samples just prior to flow cytometric analysis. Beads were added at a volume: volume (beads: cell solution) ratio of 1:1 (as per manufacturer’s instructions) or 1:3 (in order to reduce cost of using beads). Figure 2.8C illustrates that the 1:3 bead: cell solution ratio yields a reliable overestimate of cell count relative to a 1:1 ratio.

103

TM Figure 2.8: Accucheck counting beads (A) Formulas used to calculate total cell count using Accucheck™ counting beads. The bead concentration is provided by the manufacturer. (B) Example of the gating strategy for Accucheck™ counting beads. The bead solution consists of two types of beads that can be discriminated by their FITC fluorescence. The 50:50 (+/-5%) ratio of these two types of beads is an internal control to confirm adequate resuspension of the bead solution. (C) A comparison of the total cell counts of the same cell solution calculated from either a 1:1 or 1:3 volume/volume mixtures of bead and cell solutions. 4 technical replicates were performed for each bead: cell ratio.

2.2.4.6 RAW 264.7 cell culture and stimulation

An aliquot of RAW 264.7 cells were resuscitated from liquid nitrogen storage. The cell solution was defrosted in a water bath at 37℃ and then diluted in 15ml of warm RAW 264.7 culture medium (Table 2.2) for culture in a T75 flask. The culture medium was changed the following day to discard the non-adherent cells. Once confluent, the cells were passaged every 2 -3 days. Each passage consisted of replacing the culture medium before using a cell scraper (Fisher, 08- 100-241) to lift the adherent cells into the fresh medium, which was then used to seed new T75 flasks with cells at a 1:3 dilution of the original flask in a total volume of 15ml RAW 264.7 culture medium (Table 2.2).

104

For stimulation, RAW 264.7 cells were grown to 2/3rd confluence and stimulated for 6 hours with 100ng/ml LPS (Hycult Biotech, HC4056) in RAW 264.7 culture medium (Table 2.2). RAW 264.7 cells were subsequently scraped from the flask, centrifuged and 500g for 5 minutes and

6 then counted. Several aliquots of unstimulated and stimulated RAW 264.7 cells (1 or 3 x 10 cells) were lysed with 350μl RLT buffer (Qiagen) supplemented with 2-mercaptoethanol and stored at -80℃. Another set of RAW 264.7 cells were stimulated 100ng/ml LPS for 24 hours. Several aliquots of these cells (20-30 x 106 ells were then lysed in 1ml of RIPA buffer (Sigma, R0287) supplemented with 1:10 with protease inhibitor (Sigma, P8340) and stored at -80℃. Figure 2.9 demonstrates that 6 hours of LPS stimulation increases COX-2 expression by RAW264.7 cells.

Figure 2.9: Lipopolysaccharide stimulation of RAW 264.7 cells Expression of cyclooxygenase 2 (COX2) mRNA by RAW 264.7 cells cultured for 6 hours in absence or presence of 100ng/ml LPS as determined by end-point (A) or quantitative (B) reverse- transcriptase polymerase chain reaction (PCR). bp: base pair, NO RT: no reverse transcriptase control, RT: reverse transcribed, LPS: lipopolysaccharide, Unstim: unstimulated

105

2.2.5 Flow Cytometry and fluorescence-activated cell sorting (FACS)

2.2.5.1 Flow cytometry

2.2.5.1.1 Extracellular staining 3 x 105 – 1 x 106 cells (lymph node cells or splenocytes) were aliquoted into a low-binding 96 well v-bottom plate (Thermo, 249944) and centrifuged at 500g for 5 minutes. To stain with fluorophore-conjugated antibodies, the cell pellets were resuspended in 50μl of the determined antibody mastermix (described below) and incubated at 4℃ for 30 minutes. Cells were then washed11 3 times with wash buffer and fixed in wash buffer supplemented 1:1 with 1% formaldehyde PBS. Samples were stored (maximum of 3 days) in the dark at 4℃ until analysis.

The fluorescently-conjugated antibodies listed in Table 2.5 were used to generate the data presented in this thesis. These antibodies were combined in different combinations (termed ‘mastermixes’) in order to stain cells. Such mastermixes consisted of up to 7 different antibodies diluted to their staining concentration in FACS buffer, supplemented with rat serum (2% v/v), mouse serum (2% v/v), rabbit serum (2% v/v) and anti-mouse CD16/CD32 (0.2% v/v) (ebioscience, 14-0161-85).

2.2.5.1.2 Intracellular staining Prior to intracellular cytokine staining, cells were extracellularly stained as described in Section 2.2.5.1.1 but all solutions were supplemented with 10μg/ml brefeldin-A (Biolegend, 420601) (unless it was in vitro stimulation experiment (Section 2.2.4.4)). Cells were then fixed and permeabilised in order to stain for intracellular antigens using the BD Cytofix/Cytoperm kit (BD, 554714) or Biolegend’s fixation (Biolegend, 420801) and intracellular permeabilisation wash buffers (Biolegend, 421002). To intracellularly stain with fluorophore-conjugated antibodies, cells were fixed in a 100μl volume of fixative, then washed twice with 200-300μl of permeabilisation wash buffer and stained for 20 minutes at room temperature in 100μl of permeabilisation wash buffer supplemented with chosen antibody. Thereafter, cells were washed twice with 200-300μl permeabilisation wash buffer (BD or Biolegend) and resuspended in 300μl of conventional wash buffer. Samples were stored for (maximum of 1 day) in the dark at 4℃ until analysis.

11 Wash = (1) Resuspension of cell pellet with 150μl-200μl wash buffer, (2) centrifugation at 650g, (3) discard of supernatant and (4) Resuspension in chosen buffer. 106

2.2.5.1.3 Analysis Samples were analysed using an LSR Fortessa (BD) or an LSR2 flow cytometer (BD). Subsequent data analysis was performed using FlowJo software (Treestar). All flow cytometry data was compensated using single-stained compensation beads (Thermo Fisher, 01-2222). The doublet exclusion strategy presented in Figure 2.10A was used for all flow cytometry data. All gates were set using fluorescence minus one (FMO) controls and/or isotype controls (Figure 2.10).

107

D Neutrophils and Monocytes (Chapters 4-6)

CD11b Ly6C

Ly6G Ly6G

CD11b FMO Ly6C FMO Ly6G FMO FMO

Ly6C CD11b

Ly6G Ly6G E Germinal Centre B Cells

FSC CD95

GL-7 B220 B220 FMO GL-7 FMO CD95 FMO

CD95 FSC

B220 GL-7

F NK Cells NK1.1 FMO CD11b FMO

CD11b CD11b

NK1.1 NK1.1

108

G +ve CD8 Cells

CD8 CD11b

CD8 NK1.1

CD8 FMO CD11b FMO NK1.1 FMO

CD11b CD8

CD8 NK1.1

H I Anti-IFNγ APC Rat IgG1k APC

Area -

FSC

APC

J All Cells K NK Cells Anti-IFNγ APC Rat IgG1k APC Anti-IFNγ APC Rat IgG1k APC

CD11b NK1.1

APC APC

109

+ve L CD8 Cells Anti-IFNγ APC Rat IgG1κ APC

CD11b

APC

M T cells Unstimulated PMA + Ionomycin FMO Isotype Control

CD3 CD3

CD69 CD69 N B cells

Unstimulated PMA + Ionomycin FMO Isotype Control

CD19 CD19

CD69 CD69

Figure 2.10: Gating strategies, fluorescence-minus one (FMO) and isotype controls (A) Doublet exclusion strategy used in this thesis. (B-H) Gating strategies and controls used to define the following cell types; (B) T and B cells, (C) neutrophils (Chapter 3 only), (D) neutrophils and monocytes (Chapters 4-6), (E) germinal centre B cells, (F) NK cells and (G) CD8+ve cells. (H-L) Optimisation of intracellular IFNγ Cytokine Staining (H) Flow cytometry plots demonstrating specific intracellular IFNγ

110

expression by splenocytes stimulated in vitro with 2.5ng/ml PMA and 500ng/ml ionomycin. (I) Titration of anti-IFNγ antibody against its isotype control to determine the optimal staining concentration (1.25μg/ml) for this antibody (minimising non-specific binding). (J-L) Gating strategies and controls used to define IFNγ+ve cells among (J) all single cells, (K) NK cells and (L) CD8+ve cells. (M-N) Gating strategies and controls used to define CD69+ve (M) T cells and (N) B cells in this thesis. (O) Summary table outlining the flow cytometry phenotype ascribed to cells types studied in this thesis. CTRL: control, FMO: fluorescence-minus one. FSC: forward scatter, SSC: side scatter.

2.2.5.1.4 Measurement of CD69 expression by flow cytometry

Figure 2.10 demonstrates how CD69 expression is quantified by the proportion of T cells (Figure 2.10M) and B cells (Figure 2.10N) that are CD69+ve, which in turn is defined as staining greater than FMO or isotype control stained samples. This is more appropriate than measuring CD69 expression via median fluorescence intensity (MFI) because the experiments presented in this thesis determine CD69 expression using a variety of different flow cytometry panels. This incurs differences in flow cytometry compensation and photomultiplier voltage settings that in turn lead to intrinsic differences in MFI between these experiments. In contrast, measuring CD69 expression as the percentage of CD69+ve cells relative to an internal control (as demonstrated in Figures 2.10M and N) facilitates adjustment for these differences and therefore comparison and consolidation of these data as depicted in Figure 6.3 of Chapter 6. Nevertheless, the same data is presented as CD69 MFI in Supplementary Figure 6.15 in the interests of transparency.

2.2.5.2 Fluorescence-activated cell sorting (FACS)

Two cell sorting strategies were employed in this thesis, a sorting strategy to isolate neutrophils and monocytes and a sorting strategy to isolate CD11b+ve cells as well as T and B cells (Figure 2.11). Draining cervical lymph nodes were harvested 12 hours post injection as this was the earliest time-point feasible for FACS. Due to the small size of the lymph node neutrophil population, the ipsilateral lymph nodes from 4 mice had to be pooled in order to sort lymph node neutrophils and monocytes. Cells (lymph node cells or splenocytes) were aliquoted into 15ml falcon tubes and stained with fluorescent antibodies (50μl of antibody mastermix per million live cells) for 30 minutes at 4℃. Cells were then washed twice12 before being resuspended to a concentration of 2.5 x 107 cells/ml. This cell solution was passed through a 35μm filter into a 5ml polypropylene FACS tube (Corning, 352063) and stored in ice.

12 Wash = (1) Resuspension of cell pellet with 5ml wash buffer, (2) centrifugation at 650g, (3) discard of supernatant and (4) resuspension of the cell pellet with chosen buffer. 111

Cells were then sorted into 10% FBS PBS using a FACS ARIA (BD). The purities of these sorted populations are outlined in Figure 2.11.

2.2.6 RNA extraction and analysis

2.2.6.1 RNA extraction

Single cell suspensions were lysed using RLT buffer (Qiagen) supplemented with 10μl of 14.3M 2-mercaptoethanol (2-ME) per ml of RLT buffer. 350μl of RLT+2-ME was used to lyse >1 x 105 cells and 75μl was used to lyse ≤1 x 105 cells. Such RLT lysates were stored at -80℃ until RNA extraction using an RNeasy minikit (Qiagen, 74104) or microkit (Qiagen, 74004) as per manufacturer’s instructions.

In order to extract RNA from intact tissue, tissue (lymph node/ear) was immediately submerged in 1-3ml of RNA later (Qiagen, 76104) following dissection and stored at -20℃. To extract RNA, tissue (max 30mg) was transferred from RNA later into 600μl RLT buffer for disruption and homogenisation using a TissueRuptor homogeniser (Qiagen, 9002757). The resulting tissue homogenate was then spun at 18620g for 3 minutes and RNA was extracted from the supernatant using an RNeasy minikit (Qiagen, 74104) as per manufacturer’s instructions. The concentration of extracted RNA was measured using a spectrophotometer (Nanodrop, ND-1000).

112

Figure 2.11: Cell sort strategies and purities (A) Cell sorting strategy for neutrophils, monocytes, ‘other CD11b+ve cells’ and CD11b-ve cells. Populations: P3 = CD11b+ve cells, P4 = CD11b-ve cells, P5 = Monocytes, P6 = Other CD11b+ve cells, P7 = Neutrophils. Panel: V500 = CD11b, APC = Ly6C, Percp Cy5.5 = Ly6G. (B) Table outlining the population purities of all cell sorts undertaken with this sorting strategy. (C) Cell sorting strategies for CD11b+ve cells, T cells and B cells. Populations: P3 = CD11b+ve cells, P8 = T cells, P9 = B cells. Panel: Pacific blue = CD3, FITC = CD19, V500 = CD11b, Percp Cy5.5 = Ly6G. (D) Table outlining the population purities of all cell sorts undertaken with this sorting strategy. CTRL: control, Contra: contralateral, LN: lymph node, 12hr LN: 12hr draining lymph node.

113

2.2.6.2 Reverse transcription

Depending on the experiment, either 250ng or 500ng of RNA of each sample was reverse transcribed. If the yield of RNA from a sample was <250ng or <500ng then the maximum amount of RNA available was reverse transcribed. RNA was heat shocked (70℃ for 5 minutes and then cooled to 4℃) in the presence of oligo-DT nucleotides (Promega, C1101) and random primers (Promega, C1181) both at a concentration of 52.63μg/ml. RNA was subsequently reverse transcribed in a 20μl or 40μl volume using a thermocycler (Techne, TC-512) set to run the following program; 25℃ for 10 mins, 40℃ for 50 mins and then 75℃ for 10 mins before cooling to 4℃. The reverse transcriptase reaction mixture is detailed in Table 2.21. The reaction product (cDNA) was diluted to a total volume of 200μl using molecular grade water (Sigma, W4502) before being aliquoted into either 50μl or 66.6μl aliquots and stored at -20℃. A no reverse transcriptase control (NO RT control) control reaction was run in parallel to the reverse transcriptase reaction in order to test for genomic DNA contamination in subsequent polymerase chain reactions.

Table 2.21: Reverse Transcription Reaction Mixture

Reagent Manufacturer, Stock Final Volume Per Catalogue Number Concentration Concentration 20μl Reaction Heat-shocked N/A N/A N/A 9.5μl RNA H2O Sigma, W4502 N/A N/A 5μl MMLV RT Promega, M1701 5x 1x 4μl buffer MMLV RT Promega, M1701 200units/μl 5 units/μl 0.5μl dNTP mix Thermo Fisher, RO192 10mM 500μM 1μl

2.2.6.3 End-point polymerase chain reaction

A 12μl volume PCR reaction mixture was formulated as described in Table 2.22 for each sample (both cDNA samples and corresponding NO RT controls) and subjected to the following reaction conditions in a thermocycler (Techne, TC-512); 5 mins at 95℃ (initial denaturation), 40 cycles of 15 seconds at 95℃ then 20 seconds at 60℃ then 20 seconds at 72℃, followed by a final 10 min extension phase at 72℃ before cooling to 4℃. 9.5μl of each reaction product was loaded into the wells of a 3% agarose gel supplemented with the nucleic acid stain GelRed (Biotium, 41003) at a ratio of 3μl GelRed/100ml agarose gel. This agarose gel was subjected to electrophoresis (90-120 minutes at 150-200 volts) before the separated DNA was visualised by a 0.125 second exposure to UV light in an image processor (ImageQuant, LAS 4000).

114

Table 2.22: End-Point PCR Reaction Mixture

Reagent Manufacturer, Stock Final Volume Catalogue Number Concentration Concentration required for a 12μl reaction 10x dreamtaq Thermo Fisher, B71 10x 1x 1.2μl green buffer dNTP mix Thermo Fisher, R0192 10nM 200μM 0.24μl Primers (1:1 mix N/A 10μM 250nM 0.3μl of forward and reverse primer) H2O Sigma, W4502 N/A N/A 5.04μl DMSO Sigma, D5879 100% 3% 0.36μl Dreamtaq Thermo Fisher, 5U/μl 1.25U/50μl 0.06μl polymerase EP0702 cDNA N/A N/A N/A 4.8μl

2.2.6.4 Real-time polymerase chain reaction

A 10μl PCR reaction mixture was formulated as described in Table 2.23 for each sample (both cDNA samples and NO RT controls). Each sample was aliquoted in triplicate into a 384-well plate (Applied Biosystems, 4309849) and sealed with an optical adhesive film (Applied Biosystems, 4311971). The reaction mixture was then subjected to the following reaction conditions in an ABI Prism 7900HT Sequence Detection System (Applied Biosystems) - 50℃ for 2 minutes, 95℃ for 10 minutes then 40 cycles of 95℃ for 15 seconds and 60℃ for 1 minute. ROX was used as the reference dye. Both a melt curve analysis and gel electrophoresis (Section 2.2.6.3) were subsequently performed for most of the reactions in order to confirm that the reaction of product was of the correct size.

Table 2.23: Real-Time PCR Reaction Mixture

Reagent Catalogue Stock Final Volume Required number concentration Concentration for a 10μl reaction Power SYBR 4367659 2x 1x 5μl Green PCR (Applied Master Mix BIosystems) RNAse free H2O W4502 (Sigma) N/A N/A 3.25μl Primers (1:1 mix N/A 10μM 500nM 0.5μl of forward and reverse primer) cDNA N/A N/A N/A 1.25μl

115

2.2.6.5 Analysis of real-time PCR data

Real-time PCR data was analysed using SDS RQ manager (Applied Biosystems, version 2.4) and Microsoft Excel 2010. Relative gene expression data is presented using the 2-ΔCt method as described by Livak et al (410). This method determines the ratio of expression of the target gene relative to a reference gene within the same sample (see formula below). This 2-ΔCt method was chosen over the 2-ΔΔCt method as the former facilitates presentation of qPCR data as individual data points. At least two reference genes were run for all samples and both produced similar results unless otherwise stated.

ΔCt = Ct of Target Gene – Ct of Reference Gene

2-ΔCt= Expression Ratio of Target Gene Relative to the Reference gene

2.2.6.6 Primer design and validation The primer sequences used in this thesis are outlined in Table 2.10. Most of these primer sequences were either previously designed in-house or published by others. Primers that were specifically designed for this project were generated using NCBI’s Primerblast software. These primers were designed to span exon-exon junctions, although most primers used in this thesis were not exon-spanning. Lyophilised primers were supplied by sigma and resuspended to a concentration of 100μM using molecular grade water (Sigma, W4502) and stored at -20℃. The amplification efficiency (Figure 2.12) of all primers was determined at an annealing and extension temperature of 60℃ and only primers with a percentage efficiency between 80%- 120% were used (as described by Livak et al (410)). Gel electrophoresis was used to confirm that all primers generated a single reaction product with the number of base pairs.

116

Figure 2.12: Calculation of primer amplification efficiencies

(A) Actb amplification curves for 3-fold serial dilutions of cDNA (B) Standard curve of cycle threshold (CT) of amplification curves vs the logarithm of the cDNA dilution factor. (C) Formula used to calculate the primer amplification efficiency. (D) Example calculation of amplification efficiency for the Actb primer pair (Table 2.10).

2.2.7 Immunohistochemistry It was initially intended that frozen lymph nodes embedded in OCT be imaged by immunofluorescent staining as this is the current gold-standard from the immunohistochemical analysis of lymph nodes. However, despite numerous attempts, sectioning of OCT-embedded lymph nodes was unsuccessful and thus lymph nodes were instead imaged by paraffin-based immunohistochemistry.

2.2.7.1 Paraffin infiltration of tissue Lymph nodes and spleens were harvested from mice and stored in 2% FBS PBS on ice for transfer back to the laboratory. Lymph nodes were then stripped of surrounding tissue using 2 x 21G needles and a dissecting microscope. Both lymph nodes and spleens were then fixed in 4% PFA PBS (freshly made up from a stock of 16% paraformaldehyde (Agar Scientific, R1026) for one hour. Tissue was briefly immersed in PBS to wash off excess fixative and then immersed in 70% ethanol. Tissues were dehydrated and infiltrated with paraffin wax (as per Table 2.24) using an automated tissue processor (Leica, TP1050). Tissues were then embedded

117

in paraffin wax at an embedding station (Sakura, TEC-5) and the resulting paraffin blocks were stored at 4℃.

Table 2.24: Paraffin embedding program

Step Reagent Duration Temperature (℃) (minutes) 1 70% IMS 30 37 2 80% IMS 30 37 3 90% IMS 30 37 4 Absolute Ethanol 30 37 5 Absolute Ethanol 30 37

6 Absolute Ethanol 30 37 7 Xylene 30 37 8 Xylene 30 37 9 Xylene 45 37 10 Paraffin Wax 30 60 11 Paraffin Wax 45 60 12 Paraffin Wax 60 60

2.2.7.2 Sectioning of paraffin-embedded tissue Samples were sectioned at a thickness of 5μm using a microtome (Thermo Fisher, HM-325) fitted with S35 microtome blades (Feather, JDA-0100-00A) at a 4° angle. Sections were left to flatten on the surface of warm water (45℃) before being mounted onto SuperFrost microscope slides (Thermo, J1800AMNZ) and left to dry overnight at room temperature.

2.2.7.3 Immunohistochemical staining Excess paraffin wax was melted from the sections by first incubating the slides at 63.5℃ in an oven (Stuart Scientific, S102H) for 20 minutes. Slides were then further dewaxed (as per Table 2.25) in an autostainer (Sakura, DRS-2000E-D2). Following dewax; sections were briefly immersed in distilled water and then incubated in PBS for 10 minutes at room temperature. If performed, antigen retrieval was undertaken by incubating sections in antigen retrieval buffer at 95℃ in a water bath for the time periods stated in Table 2.7. To quench endogenous peroxidase activity, slides were incubated for 10 minutes in in ice-cold methanol supplemented with H2O2 to a final concentration of 1%. Slides then underwent two 5-minute washes in PBS before a hydrophobic barrier was drawn around the tissue section using a hydrophobic barrier pen (Vector labs, H-4000). Slides then underwent a further 5-minute wash in PBS before the sections were blocked for 2 hours at room temperature using block buffer. Slides were then washed in PBS for 5 minutes before being stained overnight at room temperature with the primary antibody diluted in staining buffer (Tables 2.4 and 2.7). Following primary antibody staining, slides underwent three 5-minute washes in PBS before 118

being stained with the secondary antibody (Table 2.9) diluted in staining buffer for 1 hour at room temperature. Slides then underwent three-15-minute washes in PBS before 100-200μl of Diaminobenzidine (DAB) chromogen solution (Dako, K3467) was applied to the tissue section and incubated at room temperature for 5 – 10 minutes. Slides then underwent two 10-minute washes in distilled water before mounting with a coverslip (VWR, 631-0137) using an aqueous mounting medium (Vector labs, H-5501). Images of the tissue sections were then captured with a digital slide scanner (Hamamatsu, NanoZoomer 2.0-HT) and analysed using NanoZoomer digital pathology software (Hamamatsu). Isotype control antibodies were used to control for non-specific staining (Figure 2.13).

Table 2.25: Dewax protocol Step Reagent Duration (minutes) 1 Xylene 10 2 Xylene 10 3 Absolute Ethanol 5 4 Absolute Ethanol 5 5 70% Ethanol 5 6 30% Ethanol 5

Figure 2.13: Isotype controls for immunohistochemical staining Paraffin-infiltrated sections of a superficial parotid lymph node harvested 12 hours following injection of heat-killed E. coli into the ipsilateral earflap. Sections were stained with either (A) anti- B220, anti-Ly6G, anti-GR-1 or (B) their respective isotype controls overnight at room temperature. Non -specific staining attributable to the isotype control was delineated through comparison with sections not stained with a primary antibody (no primary antibody control)

119

2.2.8 Statistical analysis and sample size determination

The majority of experiments performed in this thesis were designed to detect large effect sizes (several fold differences between control and treated groups) and hence small sample sizes were sufficient and therefore frequently adopted. This is consistent with 3R’s principle of reducing animal usage wherever possible and was performed with the view that if large differences were not demonstrated then the data generated could be used to inform sample size estimates for larger experiments to detect smaller differences (if these were deemed to be biologically meaningful). If large differences were demonstrated then further experiments would seek to repeat the finding using a complementary method (e.g. confirming increases in RNA expression with increases in protein expression) as this was deemed to be a more informative and efficient use of animals.

The small sample sizes generally adopted in this thesis in many cases precluded a meaningful analysis of whether or not the data was normally distributed. As such, differences were subject to Mann-Whitney U test unless otherwise stated. This non-parametric test would be selected in favour of its parametric equivalent (the unpaired t-test) either because the sample size was too small to test whether the data is normally distributed or because the data failed to satisfy the homogeneity of variance assumption (411). In this context, the Mann-Whitney U test is a more conservative approach and the priority was to avoid producing misleading statistics. All tandem FACS qRT-PCR data were not subject to statistical analysis as the sample size (n = 4) was insufficient to determine statistical significance using a non-parametric paired analysis (the Wilcoxon matched pairs signed rank test). All statistical analyses were performed using Graphpad prism software (version 7.0) or the InVivoStat statistical software package.

120

3 Investigations of Neutrophil and Monocyte Infiltration into the Draining Lymph Node

3.1 Abstract

The acute infiltration of neutrophils and monocytes into the draining lymph node (dLN) is a feature common to various inflammatory stimuli. Whilst a plethora of immunodulatory functions have been ascribed to these cells, the significance of this phenomenon is still unclear, especially in contexts applicable to studies of human immunisation and inflammation. This chapter therefore sought to characterise and compare neutrophil and monocyte infiltration into the dLN following challenge with Bacillus Calmette Guerin (BCG) or killed E. coli (KEC); two inflammatory stimuli directly relevant to human research.

Wild-type male C57BL/6 mice were injected with preparations of BCG or KEC into the skin of the earflap and the draining ipsilateral superficial parotid lymph node was identified and harvested for analysis by flow cytometry, ELISPOT or immunohistochemistry. Flow cytometric analysis revealed no discernible influx of neutrophils into the draining lymph node during the first 48 hours following challenge with various strains and doses of BCG. In contrast, challenge with KEC elicited an acute and robust infiltrate of neutrophils and monocytes. The influx of neutrophils peaked between 2 and 6 hours and therefore preceded the monocyte influx which peaked between 6 and 24 hours. Paraffin-based immunohistochemistry demonstrated that neutrophils are localised in peripheral regions of the draining lymph nodes following challenge. Phenotypic profiling of infiltrating monocytes revealed that this population of cell exhibited increased expression of the dendritic cell markers CD11c and MHC-II between 6 and 24 hours following inflammatory challenge. In addition to the infiltration of neutrophils and monocytes, lymphocytes within the draining lymph node significantly upregulated the activation marker CD69 following challenge killed E. coli. CD69 upregulation is associated with type I interferons and notably was not observed following challenge with BCG.

In summary, skin challenge with KEC induces the robust and sequential infiltrate of neutrophils and monocytes into the draining lymph node, whilst challenge with BCG does not. In addition, KEC also significantly increases expression of the type I interferon associated activation marker CD69. Thus, KEC is an appropriate inflammatory stimulus with which to explore the relationship between infiltrating neutrophils and monocytes and cardinal innate immune pathways; cyclooxygenase-derived prostanoids (Chapter 4) and type I interferons (Chapter 5).

121

3.2 Introduction

The infiltration of neutrophils and monocytes into the draining lymph node (dLN) is a key feature of the acute inflammatory response elicited by a wide variety of inflammatory stimuli (Section 1.3.3). These cells have been shown modulate both the innate barrier and adaptive immune functions of the dLN (Section 1.3.3). However, the mechanisms by which these cells mediate these functions have not been characterised. Moreover, it is unclear in what contexts (if any), neutrophils and monocytes infiltrate the dLN in humans. Thus, this chapter sought to establish whether neutrophils infiltrate the dLN following challenge with Bacillus Calmette- Guerin (BCG) and killed E. coli (KEC). These two inflammatory stimuli are regularly used in humans and are therefore good candidates for the characterisation of neutrophil and monocyte infiltration into the dLN in mice.

3.2.1 Bacillus Calmette-Guerin (BCG) Bacillus Calmette-Guerin (BCG) is a live attenuated form of Mycobacterium Bovis (M. bovis); the predominant causative agent of tuberculosis in cattle (412). The BCG vaccine is the only licensed vaccine for the prevention of tuberculosis and it is one of the most widely administered vaccines in human history; with >3 billion doses administered over the past century (31). With regard to the aims of this chapter, it is notable that the injection of BCG bacilli into the murine earflap has been shown to elicit the influx of neutrophils into the dLN (201). This chapter aims to characterise this finding in greater detail in order to then explore how infiltrating neutrophils may modulate the developing adaptive immune response to BCG. It thus pertinent to discuss the mechanisms by which BCG protects against tuberculosis.

3.2.2 BCG vaccine efficacy

Despite extensive use, the BCG vaccine only bestows partial protection against tuberculosis. The results of randomised controlled trials (RCTs) comparing BCG vaccination (413) vary significantly, ranging from a large UK study illustrating approximately 80% protective efficacy (414) to a large Indian trial illustrating 0% protective efficacy (415). In light of BCG’s partially protective effect, it is difficult to ethically justify further BCG vs placebo RCTs. Therefore, observational studies tend to be used to investigate BCG vaccine efficacy in humans nowadays. Roy et al (416) recently performed a systematic review of 14 such studies, which focussed upon children with known exposure to M. tuberculosis; either via a household contact with tuberculosis or via a local tuberculosis outbreak. BCG vaccine status exhibited 19% (95%

122

confidence intervals 8%-29%) protective efficacy against infection with M. tuberculosis and 71% (42%-85%) protective efficacy against active tuberculosis (416). The discord between the minimal protection bestowed against infection and the considerable protection bestowed against active tuberculosis suggests that BCG vaccination largely protects by preventing the progression from M. tuberculosis infection to active disease. This theory is supported by animal studies, which demonstrate that BCG vaccination elicits an approximately 1-3 log reduction in the number of M. tuberculosis bacilli following exposure to aerosolised M. tuberculosis (417).

3.2.3 Mechanisms of BCG-mediated protection against tuberculosis

M. tuberculosis is predominantly an intracellular pathogen of phagocytes (especially macrophages) and the prevailing theory is that T cells are central to the control of M. tuberculosis (32,418). Th1 T cells have been implicated in particular, due to their ability to secrete interferon-gamma (IFNγ), a cytokine capable of increasing the microbicidal capacity of macrophages (419,420). Mice deficient in either CD4+ve T cells or IFNγ exhibit increased susceptibility to tuberculosis, in terms of both increased mycobacterial burden and mortality post challenge (421–424). In addition, depletion of CD4+ve T cells in a mouse model of latent tuberculosis results in an increase in bacterial burden (425) and the adoptive transfer of mycobacteria-specific T cells prior to an M. tuberculosis challenge reduces the bacterial burden post challenge (230,426). However, the protection bestowed by these adoptively transferred T cells is preserved even if they are knocked out for either IFNγ or TNFα, suggesting that the these cytokines are redundant for the control of M. tuberculosis (426). The importance of IFNγ in the human context is illustrated by Mendelian susceptibility to mycobacterial disease (MSMD), a primary immunodeficiency disorder characterised by severe mycobacterial infections in childhood that is strongly associated with single-gene defects in components of the interferon gamma signalling axis (427). In summary, T cells and IFNγ, are important for the control of M. tuberculosis to varying extents.

Numerous murine BCG vaccine studies assess the immunogenicity of the vaccine by measuring the number of mycobacteria-specific IFNγ-producing T cells in a range of organs (e.g. dLN, spleen, lungs) post vaccination (407,409,428–433). A comprehensive study of the natural history of BCG in mice (409), demonstrated that the kinetics of both BCG-induced T cell responses and BCG-mediated protection against tuberculosis followed the same pattern; peaking around 8 months post vaccination and waning thereafter (mice were analysed up to 2 years post-vaccination), although a definitive correlation analysis of these two factors was not

123

presented. In addition, numerous studies in which protection against tuberculosis has been improved upon through the use of either genetically modified BCG (434–439), alternative vaccine constructs (440–442) or host-targeted strategies (429,443), have also documented increases in T cell responses. Furthermore, T cells adoptively transferred from mice vaccinated with either a new BCG construct or a construct of Mycobacterium smegmatis are able confer protection against tuberculosis (434,441). Thus, BCG vaccination generates mycobacteria- specific T cells that are protective against tuberculosis and the numbers of these cells appear to be a correlate of protection in animal studies. However, a relatively recent large-scale human study found that frequencies of mycobacteria-specific T cells induced following BCG vaccination were not an immune correlate of protection against tuberculosis in infants (444). Indeed the current absence of a correlate of protection against tuberculosis in humans is a major limitation in the ongoing efforts to design more effective tuberculosis vaccines (31–34). Nevertheless, the induction of mycobacteria-specific IFNγ-secreting T cells are still considered to be an important mechanism by which BCG mediates protection against tuberculosis and the question of whether dLN infiltrating neutrophils regulate this process are worthy of further study.

3.2.4 Killed E. coli (KEC) Escherichia coli bacteria are Gram-negative facultative anaerobes that form part of the commensal microflora of vertebrate gastrointestinal systems (445). The Gilroy laboratory has demonstrated that the intradermal injection of UV-killed E. coli into the forearms of healthy human volunteers can serve as a human model of acute skin inflammation (446). Indeed, suction blisters formed at the site of injection demonstrate an acute increase in the numbers of neutrophils and monocytes in the blister fluid during the first 72 hours following injection (446). Intriguingly, several volunteers reported axillary discomfort during the first 24 hours following the intradermal injection of UV-killed E. coli (446), suggesting that that this stimulus induces acute swelling and/or inflammation of the draining axillary lymph nodes. Moreover, Johnston et al (211,447) have illustrated that the subcutaneous injection of heat-killed E. coli into a sheep’s hock elicits substantial increase in the numbers of neutrophils in the afferent and efferent lymph of the draining popliteal lymph node. This increase in neutrophils was observed during the first 24 hours following injection and thus temporally fits with the infiltration of neutrophils at the site of inflammation described by Motwani et al (446). It thus seems likely that the intradermal injection of killed E. coli (KEC) is capable of eliciting a neutrophil influx into the dLN. Unlike BCG, the study of UV-killed E. coli is not of clinical use. However, if infiltrating neutrophils and/or monocytes were shown to modulate the innate or 124

adaptive immune function in the dLN following challenge with this stimulus then proof of concept studies could be rapidly undertaken to replicate such findings in humans.

3.2.5 The murine earflap immunisation model BCG and UV-killed E. coli (UVKEC) are injected intradermally into humans (446,448). As a result, the study of neutrophil and monocyte following challenge with these inflammatory stimuli requires a murine model that facilitates study of the dLN following skin injections of inflammatory stimuli. Studies of murine dLNs most commonly use the footpad as the site of injection/immunisation, with subsequent analysis of popliteal lymph node. However, several studies have also adopted the murine earflap immunisation model described by Li et al (402), in which material is injected into the skin of the murine earflap, with subsequent analysis of ipsilateral draining cervical lymph nodes (403,405). This latter model was adopted for the purposes of this chapter and thesis for two main reasons. Firstly, the dorsum of the murine earflap is an easily identifiable and consistent anatomical site amenable to skin injections and was therefore deemed to be a better representation of human intradermal injections than injection into the murine footpad. Secondly, Abadie et al (201) used this model to demonstrate that BCG challenge induces neutrophil infiltration into the dLN and repetition of this finding with the vaccine strain and dose of BCG is a key aim of this chapter.

3.2.6 Summary Infiltrating neutrophils and monocytes have been shown to modulate various aspects of both the innate barrier and adaptive immune function of the dLN (Section 1.3.3). However, these processes have not previously been studied in the context of inflammatory stimuli that regularly used in humans for clinical or research purposes. BCG and killed E. coli are examples of such inflammatory stimuli and are also likely to induce neutrophil infiltration into the dLN. This chapter therefore seeks to first test the hypothesis that these stimuli induce neutrophil infiltration into the dLN using the murine earflap immunisation model before further temporal and phenotypic characterisation of both neutrophil and monocyte infiltration into the dLN. This is with a view to further investigation of the functions of these cells in the dLN in subsequent chapters of this thesis.

125

3.2.7 Aims

• Validate the murine earflap immunisation model as an appropriate model for the study of neutrophil infiltration into the draining lymph node.

• Determine whether or not challenge with the vaccine strain and dose of BCG induces neutrophil infiltration into the draining lymph node.

• Determine whether or not challenge with killed E. coli induces neutrophil infiltration into the draining lymph node.

• Establish the temporal profile or any neutrophil/monocyte influxes elicited with killed E. coli and/or BCG.

126

3.3 Results

3.3.1 The ipsilateral superficial parotid lymph node drains the murine earflap

For the reasons outlined in the introduction to this chapter, Bacillus Calmette Guerin and killed E. coli (KEC) were chosen as the two inflammatory stimuli for the study of neutrophil infiltration into the dLN. In addition, the murine earflap immunisation model was the chosen method by which to address the aims of this chapter. The murine earflap is drained by cervical lymph nodes (Figure 3.1A) (403,405). As described in Section 2.2.2.1, the injection of 50μl of 10% India ink into the murine earflap immediately post mortem revealed the ipsilateral superficial parotid lymph node as an earflap-draining lymph node (Figure 3.1B).

In order to confirm that the drainage of India ink depicted in Figure 3.1B was not an artefact of the large injection volume (50μl), the earflaps of anaesthetised mice were injected with a 10μl 1:1 mixture of alum and fluorescently labelled ovalbumin (OVA-A647). Both the ipsilateral and contralateral superficial parotid lymph nodes of these mice as well the ipsilateral lymph nodes of control mice (injected with 10μl PBS) were harvested 24 hours later to identify A647- fluorescent cells by flow cytometry. Whilst very few A647-fluorescent cells were detected in either ipsilateral control or contralateral lymph nodes, 2-4% of cells in the ipsilateral lymph nodes of OVA-A647 injected mice exhibited A647 fluorescence (Figure 3.1C). Larger particulate antigens also exhibit this pattern of lymphatic drainage as A488-positive cells appeared in the ipsilateral superficial parotid lymph node 3 hours following a 10μl injection of fluorescently labelled E. coli bioparticles (E. coli-A488) into the earflap (Figure 3.1D). In both these experiments it was assumed that non-draining control and contralateral lymph nodes would not harbour any A647+ve cells and thus the presence of A647+ve and A488+ve cells in the dLN would provide a clear binary signal to illustrate the drainage. Thus, a sample size of 2 per group was selected for both of these experiments so as to limit the number of mice used for these validatory experiments. As has been described, a clear signal was described, although with regard to the drainage of E. coli A488 bioparticles there was a degree of A488 autofluorescence that had to be gated out to demonstrate the signal (Figure 3.1D). In summary, these experiments illustrate the superficial parotid lymph node reliably drains both soluble and particulate antigens injected into the murine earflap.

127

Figure 3.1: The superficial parotid lymph node drains the murine earflap A) Murine cervical lymph node anatomy. Left panel is reproduced with permission from Van den Broeck et al with ‘3’ corresponding to the superficial parotid lymph node. Right panel is a diagram illustrating the location of the superficial parotid lymph node (circled) adjacent to the junction between the lingual vein (LV) and facial vein (FV) and lateral to the mandibular salivary gland (M). (B) Photo of an ipsilateral superficial parotid lymph node 20 minutes following injection of India ink into the murine earflap post mortem (C) Flow cytometry dot plots illustrating the appearance of A647-positive cells 24 hours following injection with 10μl of a mixture of OVA-A647 (33μg) and Alum (50μg). (D) The percentage of A488-positive cells 3 hours following injection with 1 x 107 A488-conjugated E. coli bioparticles. Sample sizes; (C) n = 2 ipsi LN, n = 2 Con LN and n = 1 CTRL LN (lymph nodes from two mice were pooled prior to analysis). (D) n = 2 ipsi LN, n = 2 Con LN, n = 2 CTRL LN. NC3Rs: 9 mice in total. CTRL: control, Con: contralateral. OVA-A647: ovalbumin conjugated to alexa fluor 647, LN: lymph node.

128

3.3.2 Labelled E. coli bioparticles elicit neutrophil infiltration into the draining lymph node The study of neutrophils infiltrating the draining lymph node is central to the aims of this chapter. It is thus notable that the intradermal injection of fluorescently-labelled E. coli bioparticles (described in Section 3.3.1) led to a substantial influx of neutrophils (defined as CD11b+ve Ly6G+ve cells by flow cytometry) into the ipsilateral superficial parotid lymph node within the first 3 hours following injection. Indeed, whilst neutrophils constitute <0.2% of cells in control or contralateral lymph nodes, they comprise 2-4% of cells in ipsilateral superficial parotid lymph node 3 hours following injection (Figure 3.2A). Moreover, approximately 75% of

+ve the A488 cells in the ipsilateral lymph node were neutrophils (Figure 3.2B) and these neutrophils exhibit substantially greater A488 fluorescence than splenic neutrophils from the same mice (Figure 3.2C), indicating that E. coli bioparticles within the dLN were largely phagocytosed by neutrophils at this time point. In summary, these findings illustrate that inactive E. coli bioparticles elicit a rapid and marked infiltration of neutrophils into the dLN and that these neutrophils have phagocytosed said bioparticles.

3.3.3 Skin injection of BCG does not elicit a marked neutrophil influx into the draining lymph node

Figures 3.1 and 3.2 demonstrate that the murine earflap immunisation model is appropriate for the study of neutrophil infiltration into the dLN. However, it is not known whether neutrophils infiltrate the dLN following challenge with inflammatory stimuli that are used clinically or for research purposes in humans. Bacillus Calmette Guerin is one such stimulus with Abadie et al (201) reporting that the intradermal injection of 1 x 106 CFU of BCG Pasteur into the murine earflap elicits a ‘massive’13 neutrophil influx into the dLN 24 hours following immunisation. Human BCG vaccination in the UK is performed using the SSI strain of BCG at an inoculum dose of 2-8 x 105 CFU. To determine whether 2-8 x 105 CFU BCG SSI is also capable of inducing a neutrophil influx into the dLN, human vaccine-grade BCG SSI was injected into murine earflap and the ipsilateral superficial parotid lymph node was subsequently analysed by flow cytometry.

13 This study provides microscopic evidence of neutrophil infiltration and flow cytometric evidence that lymph node neutrophils harbour BCG bacilli. However, it does not quantify the size of this infiltrate as discussed later in this chapter 129

In terms of sample size determination, the expected size of the neutrophil influx was unclear as Abadie et al did not quantify this in their study (201). However, given that they described this neutrophil influx as ‘massive’, it was assumed that it would be readily detectable using a small sample size as non-dLNs harbour only a very small population of neutrophils. Indeed, it was considered more important to gain a preliminary understanding over what time course neutrophils infiltrated the dLN following BCG challenge and thus a sample size of 2-4 per group was adopted at 4 time points; 3 hours, 4 hours, 24 hours and 48 hours. These experiments demonstrated that injection of 1-4 x 105 CFU of BCG SSI (half the human dose) did not lead to an appreciable increase in either the percentage or number of neutrophils in the ipsilateral lymph node at either 3- or 48-hours post-immunisation (Figure 3.3A). As mice tolerated this dose of BCG SSI well, it was increased to the full human dose of 2-8 x 105 CFU for the 4 hour and 24-hour mice. Nevertheless, injection of 2-8 x 105 CFU of BCG SSI did not result in a significant increase in either the percentage or number of neutrophils in the ipsilateral lymph node at either of these time points (Figures 3.3B and 3.3C). This initial screen therefore failed to replicate the ‘massive’ (but notably not quantified) neutrophil influx described by Abadie et al (201).

It is possible that the neutrophil infiltration observed by Abadie et al (201) resulted from their use of a different strain of BCG (BCG Pasteur) at a higher inoculum dose (1 x 106 CFU). Thus, mice were injected with 2 x 106 CFU of BCG Pasteur and the superficial parotid lymph nodes analysed by flow cytometry 24 hours later. Again, a sample of 4 mice was selected as this was deemed sufficient to try to identify a ‘massive’ neutrophil influx. However, as with BCG SSI, no increase in the either the percentage or number of neutrophils was observed in the ipsilateral superficial parotid lymph node following challenge with BCG Pasteur (Figure 3.3D). In summary, the injection of BCG SSI or Pasteur at a range of inoculum sizes into the murine earflap did not elicit a significant influx of neutrophils into the dLN.

130

Figure 3.2: E. coli bioparticles predominantly associate with neutrophils in the draining lymph node (A) Percentage and number of neutrophils in superficial parotid lymph nodes 3 hours following injection of 1 x 107 E. coli-A488 bioparticles into the murine earflap. (B) Phenotype of A488-positive cells in the ipsilateral superficial parotid lymph node. (C) A488 fluorescence of neutrophils from an ipsilateral lymph node relative to splenic neutrophils. Sample sizes: n = 2 ipsi LN, n= 2 Con LN, n = 2 CTRL LN. NC3R’s: 4 mice in total. CTRL: Control, Con: Contralateral, Ipsi: ipsilateral, LN: lymph node, SPL: spleen. FSC-A: forward scatter area, MFI: median fluorescence intensity.

131

Figure 3.3: Skin injection of BCG bacilli does not induce a significant neutrophil influx into the draining lymph node The percentage and number of neutrophils in the superficial parotid lymph node 3 to 48 hours following skin injection of (A) 1-4 x 106 CFU of BCG SSI, (B and C) 2-4 x 106 CFU of BCG SSI or (D) 2 x 106 CFU of BCG Pasteur into the murine earflap. Sample sizes: (A and B) n = 2 ipsi LN per time point, n = 3-4 Con LN, n = 1-2 CTRL LN (superficial parotid lymph nodes from two mice were pooled prior to analysis). (C) n = 4 ipsi LN, n = 3 Con, n = 2 CTRL LN. (D) n = 4 ipsi LN, n= 2 Con LN, n = 2 CTRL LN. NC3Rs: 29 mice in total. CFU: colony forming unit, hr: hour, LN: lymph node, CTRL: control, Con: contralateral, Ipsi: ipsilateral. There was no statistically significant difference between any of the groups in these experiments.

132

3.3.4 Skin injection of BCG reliably induces a T cell response but also occasionally induces lymphadenopathy

In light of the fact that BCG immunisation did not elicit a neutrophil influx into the dLN, it was questioned whether the mice were responding to the BCG injected in these experiments and thereby eliciting an adaptive immune response. The T cell response to BCG is commonly quantified using an IFNγ ELISPOT assay, which can be used to enumerate the number of cells that specifically produce IFNγ when stimulated with mycobacteria-specific antigens in vitro (449). Indeed, IFNγ ELISPOTs have demonstrated that the number of IFNγ-secreting BCG- specific T cells in both the dLN and the spleen gradually increase up until at least 12 weeks post-immunisation (407,409). Thus, the spleens and ipsilateral superficial parotid lymph nodes of BCG SSI immunised mice were harvested 12 weeks following immunisation for analysis by IFNγ ELISPOT. This confirmed a robust T cell response to the injected BCG as lymph node and spleen cells from BCG-immunised mice only produced IFNγ following in vitro co-culture with mycobacterial purified protein derivative (PPD) (Figure 3.4A). Unexpectedly, some of the BCG- immunised mice also exhibited abnormally extensive enlargement of the ipsilateral superficial parotid lymph node 12 weeks following immunisation that is consistent with the mycobacterial lymphadenopathy (450,451). Whilst control lymph nodes and two of the 12-week ipsilateral lymph nodes consisted of <3 million live cells, the other four 12-week lymph nodes ranged from 15-82 million cells in total and had a diameter of approximately 8mm (Figure 3.4B). The composition of two of these abnormally enlarged 12-week lymph nodes was determined by flow cytometry and found to be broadly similar to that of control and contralateral lymph nodes, being largely composed of lymphocytes and exhibiting no increase in the proportion of neutrophils or other CD11b+ve cells (Figure 3.4C). Nevertheless, these abnormally enlarged 12- week dLNs harboured substantially greater numbers of mycobacteria-specific IFNγ-producing cells than regularly sized 12-week dLNs on account of their increased overall cellularity (Figure 3.4B). Thus, the skin injection of BCG SSI reliably induces a T cell response in the dLN and spleen but also variably causes lymphadenopathy of the dLN. This phenomenon is not associated with a neutrophil infiltrate (Figure 3.4C).

133

Figure 3.4: Skin injection of BCG reliably elicits a T cell response but variably induces lymphadenopathy (A) The proportion of mycobacteria-specific T cells present in the ipsilateral superficial parotid lymph nodes and spleens of mice injected with 2-8 x 105 CFU of BCG SSI 12 weeks previously, as determined by IFNγ ELISPOT. (B) Absolute numbers of live cells and mycobacteria-specific IFNγ SFUs in control and draining lymph nodes. Accompanying photos are examples of abnormally enlarged draining lymph nodes (upper photos) and regularly-sized control and contralateral lymph nodes (lower photos). Each tick mark on the ruler represents 1mm, black staining is India ink injected post-mortem. (C) Cellular composition of two of the grossly enlarged ipsilateral lymph nodes presented in (A-B) relative to all control and contralateral lymph nodes analysed in this chapter. Sample sizes: (A and B) n = 6 x BCG Ipsi LN, n = 5 x CTRL Ipsi LN, (C) n = 2 x BCG ipsi LN, n = 14 x control lymph nodes and 38 x contralateral lymph nodes. CTRL: control, PPD: purified protein derivative, BCG: spleens or ipsilateral lymph nodes from BCG immunised mice, ipsi: ipsilateral, LN: lymph node. The Mann-Whitney U test was used to test for statistical significance. ** p-value of 0.0043. Error bars in (C) represent standard deviation 134

3.3.5 Skin injection of killed E. coli induces acute neutrophil infiltration into the draining lymph node

The Gilroy laboratory has shown that the intradermal injection of 1.5 x 107 UV-killed E. coli induces acute skin inflammation in healthy human volunteers (446). Moreover, several of these volunteers reported axillary discomfort during the first 24 hours following injection (446). It was therefore questioned whether this axillary discomfort represented acute inflammatory changes in the draining axillary lymph nodes and by extension whether this is was reflective of acute neutrophil infiltration into dLNs. Mice were therefore injected with 1.5 x 107 killed E. coli into the murine earflap and draining superficial parotid lymph nodes analysed by flow cytometry 3 and 24 hours later. As is demonstrated in Figures 3.2 and 3.3, lymph nodes harbour very few neutrophils in the steady state and thus an influx of >20,000 neutrophils (as shown in Figure 3.2A) is easily discernible with very small numbers of mice. Taking this into account, a sample size of 3 per group was deemed sufficient to demonstrate a neutrophil influx into the dLN. This experiment demonstrated that skin injection of 1.5 x 107 killed E. coli leads to a marked increase in the percentage and number of neutrophils in the ipsilateral superficial parotid lymph nodes at 3 and 24 hours of injection (Figure 3.5A). Whilst non-draining control and contralateral lymph nodes harboured <5000 neutrophils, ipsilateral dLNs harboured 20-50,000 neutrophils at both 3- and 24-hours following injection (Figure 3.5A).

Figure 3.5A illustrates that challenge with killed E. coli induces an acute neutrophil influx into the dLN. However, several studies have also documented neutrophil infiltration into the dLN at much later time points using various other types of inflammatory stimuli (80,202,312,371). It was therefore questioned whether this phenomenon extended to the skin injection of 1.5 x 107 killed E. coli. As discussed previously, lymph nodes harbour very few neutrophils in the steady state (173) and thus sample sizes of 3-4 mice were injected with 1.5 x 107 killed E. coli and their dLNs analysed for neutrophils 7 and 14 days later. This experiment illustrated that there was no difference between the percentage and number of neutrophils in non-draining control and contralateral lymph nodes relative to dLNs harvested at days 7 and 14 (Figure 3.5B). The opportunity was taken to repeat this experiment with a set of day 7 and day 14 mice primarily being used to address a different question (see Figure 4.6) and this again demonstrated no increase in neutrophils in the dLN at days 7 and 14 (Figure 3.5C). In summary, skin injection of 1.5 x 107 killed E. coli induces the acute infiltration of neutrophils into the dLN during the first 24 hours of injection but this influx is not protracted to days 7 and 14 as has been demonstrated in the context of other inflammatory stimuli (80,202,312,371).

135

Figure 3.5: Skin injection of killed E. coli induces acute neutrophil infiltration into the draining lymph node 1.5 x 107 killed E. coli were injected into the murine earflap. The percentage and number neutrophils in the superficial parotid lymph node during (A) the first 24 hours and (B) the first 14 days following injection with example flow cytometry plots of lymph node neutrophils. (C) A repeat of the experiment described in (A and B). Sample sizes: (A) n = 1 x CTRL LN, 5 x Con LN, 5 x 3hr ipsi LN, 3 x 24hr ipsi LN. (B) n = 5 x CTRL LN, 9 x Con LN, 2 x 3hr ipsi LN, 4 x Day 7 Ipsi LN, 3 x Day 14 Ipsi LN. (C) n = 4 x CTRL LN, 12 x Con LN, 2 x 2hr ipsi LN, 4 x Day 7 ipsi LN, 4 x Day 14 ipsi LN. NC3R’s: 35 mice in total. The Mann-Whitney U test was used to test for statistical significance. *p<0.05 relative to contralateral LN. Con: contralateral, CTRL: control, ipsi: ipsilateral, LN: lymph node

136

3.3.6 Neutrophils are predominantly localised in peripheral regions of the draining lymph node

Spatial organisation and compartmentalisation are key features of lymph node biology. Thus, the distribution of infiltrating neutrophils within the dLN was investigated 12 hours following injection of heat-killed E. coli. Lymph nodes were imaged by paraffin-based immunohistochemistry, with antigens stained separately on serial sections. The B cell marker B220 was first used to define the location of the B cell follicles in both control and draining LN (Figure 3.6A). The neutrophil-specific marker Ly6G was subsequently used to identify neutrophils in serial sections of these lymph nodes (Figure 3.6B). Figure 3.6B illustrates that Ly6G staining is absent in control lymph nodes but marked in the peripheral regions of 12-hour dLNs. Moreover, this Ly6G staining appeared to be either peripheral to or between B cell follicles (Figure 3.6B). This is consistent with previous descriptions of neutrophils in the subcapsular sinus, interfollicular regions and medulla of the dLN (72,201,202,209,278,368,371).

3.3.7 Skin injection of killed E. coli induces acute CD69 upregulation by lymphocytes in the draining lymph node

CD69 is an activation marker whose upregulation by lymphocytes is known to be induced by type I interferons (IFNs) (278,342,401,452,453). It is therefore significant that the acute neutrophil influx described in Figure 3.5 is mirrored by an increase in CD69 expression by both B and T cells in the ipsilateral superficial parotid lymph nodes at both 3- and 24-hours following injection of KEC (Figure 3.7A and 3.7C). This suggests that type I IFNs are active in the KEC- draining LN. CD69 upregulation was particularly marked on B cells, approximately 90% of which were CD69+ve in the 24-hour dLN (Figure 3.7A). Moreover, as with neutrophils, the percentage of CD69+ve lymphocytes had largely returned to baseline at days 7 and 14 post- injection (Figures 3.7B and 3.7D). Thus, the skin injection of KEC elicits an acute inflammatory response that drives a rapid neutrophil influx into the dLN as well as substantial increases in CD69 expression by lymph node lymphocytes.

137

A 12hr Ipsilateral LN 1 2 3

B220

LY6G

B 1 CTRL LN 2

B220

LY6G

Figure 3.6: Infiltrating neutrophils are localised in peripheral regions of the KEC-draining lymph node Ipsilateral superficial parotid lymph nodes were harvested from mice (A) 12 hours following skin injection of 1.5 x 107 killed E. coli (KEC) or (B) from uninjected control mice. Lymph nodes were embedded in paraffin, sectioned and stained with the monoclonal antibodies B220 (stains B cells) and Ly6G (stains neutrophils). Sample sizes: n = 3 x 12hr ipsilateral LN, n = 2 x CTRL LN. NC3Rs: 5 mice in total. CTRL: control, LN: lymph node.

138

Figure 3.7: Acute CD69 upregulation in the superficial parotid lymph node following injection of killed E. coli into the murine earflap 1.5 x 107 killed E. coli were injected into the murine earflap. (A and D) The percentage of CD69+ve (A-B) B cells and (C-D) T cells in the superficial parotid lymph node within the first 24 hours (A and (C) and the first 14 days (B and D) following injection with example flow cytometry dot plots. CD69+ve gate was determined using fluorescence minus one controls as outlined in methods Section 2.2.5.1.4. Sample sizes: (C and E) n = 1 x CTRL LN, 5 x Con LN, 3 x 3hr ipsi LN, 3 x 24hr ipsi LN. (D and F) n = 5 x CTRL LN, 9 x Con LN, 2 x 3hr ipsi LN, 4 x Day 7 Ipsi LN, 3 x Day 14 Ipsi LN. NC3R’s: 21 mice in total. The Mann-Whitney U test was used to test for statistical significance. *p<0.05 relative to contralateral LN. Con/Contra: contralateral, CTRL: control, Ipsi: ipsilateral, LN: lymph node

3.3.8 Ly6Chi monocytes infiltrate the draining lymph node following skin injection of killed E. coli (KEC)

+ve hi In addition to neutrophils, CD11b Ly6C monocytes and migratory dendritic cells have been shown to rapidly infiltrate the dLN following challenge with a wide a variety of inflammatory stimuli (Sections 1.2.3.2.3 and 1.3.3.2). To determine whether or not this also applies following challenge with killed E. coli, dLNs were harvested at 6, 24- and 48-hours following challenge and subjected to flow cytometric analysis to better characterise the cellular dynamics during this acute time period. In this regard, lymph node cells were stained with Ly6C to identify infiltrating monocytes as well as CD11c and MHC II to identify migratory dendritic cells (192,242). Monocytes are known to constitute only a very small proportion of the cells present in lymph nodes in the steady state (366) and prior experiments had revealed a population of ~100,000 CD11b+ve Ly6Glo cells that appeared in the dLN 6 hours following challenge and were 139

deemed likely to mostly Ly6Chi monocytes (Supplementary Figure 3.10). A sample size of 4 mice per time point was therefore deemed sufficient to detect an infiltrate of at least 50,000

+ve hi monocytes relative to baseline. Indeed, whilst CD11b Ly6C monocytes cells were largely absent from non-draining control and contralateral lymph nodes, a marked increase in both the percentage and number of monocytes was evident in dLNs harvested 6- and 24-hours following injection (Figure 3.8A). However, monocyte numbers had largely returned to baseline by 48 hours following injection (Figure 3.8A). When compared with monocytes, the infiltration of migratory dendritic cells (defined as CD11c+ve MHC IIhi cells 174) was far less pronounced, with these cells exhibiting only a small increase in their number at 24 hours following injection (Figure 3.8B).

The study of monocytes in the context of acute inflammation is complicated by the fact that monocytes readily differentiate into cells resembling macrophages or dendritic cells upon microbial stimulation (385). Indeed, other descriptions of CD11b+ve Ly6Chi cells infiltrating the

-ve -ve hi +ve hi dLN range from CD11c MHC II cells resembling Ly6C blood monocytes to CD11c MHC II cells resembling monocyte-derived dendritic cells (50,187,205,207,242,263,379,396). It is thus

+ve hi notable that CD11b Ly6C cells from 6-hour dLNs are largely negative for CD11c and MHC II

+ve hi expression, whilst CD11b Ly6C cells from 24-hour dLNs are largely CD11c MHC II double- positive (Figure 3.8C). Thus, the data depicted in Figure 3.8 demonstrates that CD11b+ve Ly6Chi monocytes rapidly infiltrate the dLN following skin challenge with 1.5 x 107 killed E. coli and suggests that these monocytes differentiate into monocyte-derived dendritic cells within 24 hours of entering the dLN.

140

Figure 3.8: Ly6Chi monocytes infiltrate the draining lymph node (A and B) Gating strategy and temporal profile of the percentage and number of (A) CD11b+ve Ly6Chi Ly6G-ve monocytes and (B) CD11c+ve MHC IIhi migratory dendritic cells (as defined by Ohl et al (192) in the draining lymph node following injection of 1.5 x 107 killed E. coli (KEC). (C) Temporal profile of CD11c and MHC II expression by monocytes in the KEC-draining lymph node. Sample sizes: n = 6 x CTRL LN, 9 x Con LN, 4 x 6hr LN, 4 x 24hr LN, 4 x 48hr LN, NC3Rs: 18 mice in total. CTRL: control, Con: contralateral, hr: hour, LN: lymph node, MFI: median fluorescence intensity, M: monocytes, N: neutrophils, mDC: migratory dendritic cells, SPL: spleen. The Mann-Whitney U test was used to test for statistical significance. *p<0.05 **p<0.01 relative to control lymph nodes.

141

3.3.9 Neutrophil infiltration precedes monocyte infiltration in the draining lymph node

The infiltration of neutrophils and monocytes is a cardinal feature of acute inflammation and classically the infiltration of neutrophils precedes that of monocytes (454,455). However, it is unclear whether this pattern of myeloid cell infiltration extends to the dLN during inflammation. Figure 3.9 is a retrospective analysis compiled from all the experiments in this thesis in which the numbers of neutrophils and monocytes were quantified during the first 48 hours following injection of heat-killed E. coli. These data include two-time courses (Supplementary Figure 3.11) and numerous independent experiments conducted at single time points. Being retrospective, these experiments were not powered to define the patterns of neutrophil and monocyte infiltration. Nevertheless, it is clear from this analysis that neutrophils outnumber monocytes in the dLN at 2-3 hours following challenge, whilst at 6-, 12- , 24- and 48-hours monocytes substantially outnumber neutrophils (Figure 3.9A). Consolidation of these data into a single graph suggests that neutrophil numbers peak between 2- and 6-hours post injection, whereas monocytes peak between 6 and 24 hours (Figure 3.9B). Thus, these data provide strong evidence that neutrophil infiltration precedes monocyte infiltration into the dLN.

Figure 3.9: Neutrophil infiltration precedes monocyte infiltration in the draining lymph node (A) Paired analysis of the number of neutrophils and monocytes present in all draining lymph nodes analysed in this thesis. (B) Data from (A) pooled into a single graph that describes the temporal profiles of neutrophil and monocyte populations in the draining lymph node following injection of 1.5 x 107 killed E. coli (KEC). Sample sizes: n =10 x control, 4 x 2hr, 4 x 3hr, 14 x 6hr, 14 x 12hr, 12 x 24hr, 8 x 48hr. NC3Rs: 66 mice in total. CTRL: control, LN: lymph node, MFI: median fluorescence intensity. The Wilcoxon matched-pairs signed rank test was used to test for statistical significance. *p<0.05 **p<0.01 ***p<0.001. Error bars represent standard deviation.

142

Supplementary Figure 3.10: Skin injection of killed E. coli elicits the acute infiltration of neutrophils and unidentified CD11b+ve Ly6Glo cells The skin of the earflaps of mice were injected with 1.5 x 107 killed E. coli (KEC) and superficial parotid lymph nodes were harvested for analysis by flow cytometry. (A) Example flow cytometry dot plots and (B) The percentage of lymph node cells that are CD11b+ve Ly6G+ve neutrophils or CD11b+ve Ly6Glo cells 6 hours following injection of KEC. Sample sizes: n = 2 x CTRL LN, 4 x Con LN and 4 x 6hr LN. NC3Rs: 6 mice in total. The Mann-Whitney U test was used to test for statistical significance. *p<0.05 relative to contralateral LN. CTRL: control, con: contralateral, ipsi: ipsilateral, neut: neutrophil.

143

Supplementary Figure 3.11: Kinetics of neutrophil and monocyte infiltration into the KEC- draining lymph node (A and B) Temporal profiles of the percentage and number of neutrophils and monocytes in the draining lymph node in two separate time course experiments spanning the first 48 hours following skin injection of 1.5 x 107 killed E. coli (KEC). (C) Total number of cells in LN following challenge with KEC. Sample sizes: Time course 1 n = 6 x CTRL LN, 4 x 6hr LN, 4 x 24hr LN, 4 x 48hr LN. Time course 2, n = 4 x CTRL LN, 4 x 2hr LN, 4 x 6hr LN, 4 x 24hr LN, 4 x 48hr LN. NC3Rs: 38 mice in total. The Mann-Whitney U test was used to test for statistical significance. *p<0.05 relative to control LN (neutrophils specifically in A-B), #p<0.05 relative control LN monocytes. CTRL: control, contra/con: contralateral, LN: lymph node.

144

Supplementary Figure 3.12: Lymphocytes in the draining superficial parotid lymph node do not significantly upregulate CD69 following BCG challenge (A) Example flow cytometry dot plots. (B and C) The percentage of (B and C) B cells and (D and E) T cells that are CD69+ve in the superficial parotid lymph node 3-48 hours following injection of (B and D) BCG SSI or (C and E) BCG Pasteur (inoculum dose stated on each graph). This data was generated from the same experiments described in Figure 3.3. Sample sizes: (B and D) n = 2-4 ipsi LN per time point, n = 3-4 Con LN per time point, n = 1-2 CTRL LN per time point (superficial parotid lymph nodes from two mice were pooled prior to analysis). (C and E) n = 4 ipsi LN, n = 2 Con LN, n = 1 CTRL LN. (F) n = 4 ipsi LN, n= 2 Con LN, n = 2 CTRL LN. NC3Rs: 29 mice in total. BCG: Bacillus Calmette-Guerin, SSI: Statens Serum Institut, CFU: colony forming unit, hr: hour, LN: lymph node, CTRL: control, contra: contralateral, ipsi: ipsilateral. There was no statistically significant difference between any of the groups in these experiments.

145

3.4 Discussion

The data presented in this chapter demonstrates that the injection of inflammatory stimuli into the skin of the murine earflap is an appropriate model in which to study neutrophil and monocyte infiltration into the draining superficial parotid lymph node. Moreover, it compares two inflammatory stimuli that are regularly used for clinical or research purposes in humans; killed E. coli and BCG. Notably, KEC induces robust neutrophil infiltration into the dLN but vaccine-grade BCG does not. The implications and limitations of each of these findings will be discussed separately in the following sections. This will be followed by an overall discussion of how these findings inform subsequent results chapters of this thesis.

3.4.1 The murine earflap immunisation model The data presented in this chapter clearly demonstrates that the ipsilateral superficial parotid lymph node drains the murine earflap and is infiltrated by neutrophils and monocytes following challenge with killed E. coli; two criteria that are fundamental to address the aims of this thesis. As KEC is used to study acute inflammation in humans (446), it pertinent to question the direct comparison of injections into the murine earflap relative to human skin. Both BCG and killed E. coli are injected intradermally in human skin, and this is defined by the formation of a raised blanched bleb (456). Whilst murine earflap injections also induced bleb formation and were performed at shallow angle as per Li et al (402), it is not clear whether these injections are strictly intradermal given the differences in thickness between human and mouse skin (457). Similarly, the extent to which the injection of a 10µl volume into mouse skin is comparable to the injection of a 100µl volume into human skin can also be questioned. Indeed, it has been argued that the hydraulic pressure generated by injections into mouse skin induce local tissue damage (402) and propel lymph-borne antigens to the dLN (162). However, is important to note that intradermally injected MRI contrast exhibits similarly rapid lymphatic drainage in humans (161) and that antigens inoculated by scarification rather than injection still exhibit rapid free-drainage to the dLN (71). Nevertheless, whilst these pieces of evidence are reassuring, they do not exclude potentially important differences between the murine earflap injection model used in this thesis and the intradermal injections used in human studies of inflammation and vaccination (446,448).

146

3.4.2 Bacillus Calmette-Guerin (BCG)

In many respects, BCG represents the ideal stimulus with which to study innate immune pathways within the dLN as it is of great clinical significance (Sections 3.2.1 - 3.2.3) and has previously been shown to induce a ‘massive’ neutrophil influx into the dLN by Abadie et al (201). The demonstrated absence of an acute neutrophil influx into the dLN following challenge with BCG SSI or BCG Pasteur (Figure 3.3) was therefore unexpected. It is difficult to reconcile the divergent findings of this thesis and the findings of Abadie et al (201), which is the only other study of neutrophils in the dLN following challenge with BCG. This is because BCG was injected into the murine earflap and at equivalent doses in both studies. The BCG injected by Abadie et al (201) was engineered to express green fluorescent protein and it is possible that this genetically transformed strain of BCG is more virulent than the BCG strains used in this study. This explanation seems unlikely and even if it were proven it would merely underscore the importance of using human vaccine-grade BCG as is done in the experiments outlined in this chapter. Moreover, Abadie et al (201) do not quantify the size of the neutrophil infiltrate observed14. It is therefore difficult to judge how different the results presented in this chapter are from those of Abadie et al (201). Indeed, the findings of Abadie et al (201) could be consistent with the free-drainage of BCG bacilli to the dLN and their subsequent phagocytosis by the small population of neutrophils that reside within lymph nodes in the steady state (173), negating the need for a neutrophil influx. A direct replication of the experiments conducted by Abadie et al using the same fluorescent strain of BCG could clarify this issue.

The fact that BCG challenges have been shown to induce neutrophil infiltration into skin (201,432) and lung (432,458–460) makes the absence of a neutrophil influx into the dLN described in this chapter all the more interesting. Indeed, whilst viable BCG bacteria are known to reside in the dLN (407,409), the mechanisms by which they reach the dLN and the cell types they interact with upon arrival are unclear. Abadie et al (201) suggest neutrophils traffic BCG bacteria from the site of inflammation via afferent lymphatics but it is equally possible BCG bacteria exhibit rapid cell-free drainage and subsequent phagocytosis by neutrophils or other cells within the dLN. Indeed, very rapid cell-free drainage has been demonstrated following challenge with S. aureus15 (71). If it is assumed that BCG exhibits a similar cell-free pattern of lymph-borne drainage then it is pertinent to question how lymph-borne BCG bacilli are handled by the various resident macrophages and dendritic cells that filter afferent lymph percolating through the dLN (Sections 1.2.3.1.2 and 1.3.2.3). In this respect, it is notable that

14 Rather, this study provides microscopic evidence of neutrophil infiltration and flow cytometric evidence that lymph node neutrophils harbour BCG bacilli. 15 the rapid appearance of labelled E. coli bioparticles used in Figure 3.2 also likely represents such lymph-borne drainage. 147

BCG infect macrophages like other mycobacteria but lack the RD1 gene locus that is responsible for the production of type I IFNs by mycobacteria-infected macrophages (439,461). This is supported by the lack of CD69 upregulation in BCG-dLNs (Supplementary Figure 3.12) and it is therefore possible that BCG bacilli infect and subvert lymph node resident macrophages through aversion of the type I IFN response.

Given the fact that mycobacteria are well known for their capacity to establish chronic infections in lymph nodes and induce lymphadenopathy (450,451,462) (Figure 3.4), it is remarkable that basic questions as to how mycobacteria interact with resident innate immune cells in the dLN have not been explored. This represents a gap in our current understanding of the pathogenesis of mycobacterial infections and could be investigated using confocal immunofluorescence and intravital multiphoton imaging (as per (72,169,328)) to visualise both lymph node resident macrophages and fluorescent strains of mycobacteria during the first days following inoculation. These are important questions but were felt to be outside the remit of this thesis; especially given the fact that killed E. coli was established as a stimulus that induces neutrophil and monocyte infiltration into the dLN; these innate immune processes being central to the aims of this thesis. Thus, killed E. coli was adopted in favour of BCG as the human translatable stimulus to be studied in this thesis.

3.4.3 Killed E. coli

In stark contrast to BCG, skin injection of 1.5 x 107 killed E. coli drives neutrophil infiltration into the dLN during the first 24 hours following injection (Figure 3.5 and Supplementary Figure 3.11). This neutrophil infiltrate is followed by a larger influx of inflammatory monocytes that persist in the dLN for 24-48 hours following challenge (Figure 3.8). This pattern of inflammatory myeloid cell infiltration (Figure 3.9) closely mirrors that observed in human skin following intradermal challenge with the same stimulus (446). This strongly suggests that the phenomena described in murine ipsilateral superficial parotid lymph nodes are representative of the draining axillary lymph node in humans. Direct confirmation of neutrophil and monocyte infiltration into the dLN in human subjects is challenging but could be achieved by intravenous transfer of radiolabelled neutrophils and monocytes at the time of challenge and subsequently quantifying radioactivity in the axillae (as per the methods of Smith et al (463)). However, further investigation of the underpinnings of myeloid cell infiltration into the dLN would be precluded in humans and thus an appropriate mouse model is required. The fact that challenge with killed E. coli is established therefore provides a platform for the study of the mechanistic underpinnings of these processes. This is discussed in the following section.

148

3.4.4 Neutrophil and monocyte infiltration into the draining lymph node

3.4.4.1 Kinetics of neutrophil and monocyte infiltration A notable aspect of the neutrophil influx elicited following challenge with killed E. coli is that it is acute and transient; peaking within the first 6 hours of challenge, largely dissipating by 24 hours and not rebounding at days 7 and 14 (Figure 3.9). This is significant because inflammatory stimuli have been shown induce either an acute neutrophil influx in the dLN that resolves within the first 24-72 hours (72,202,204,209) or a more protracted increase in neutrophils that persists from days 7-21 following injection (80,202,312,371). Figure 3.9 therefore demonstrates that killed E. coli belongs to the former category of inflammatory stimuli. This is important as it restricts the study of neutrophils to the first 48 hours following challenge, and thereby excludes mechanisms by which neutrophils infiltrating at later time points modulate the developing humoral immune response (372). The reason why killed E. coli elicits only an acute neutrophil influx is not clear. It may reflect rapid clearance of the killed E. coli as Kamenyeva et al (202) have illustrated that killed S. aureus induces a similarly acute neutrophil influx into the dLN, whereas live S. aureus induces a protracted influx up until at least day 716.

The infiltration of monocytes is similarly acute but it is slightly delayed and of greater magnitude relative to that of neutrophils (Figure 3.9). The sequential infiltration of first neutrophils and then monocytes is a classic pattern of the acute inflammatory response (454,455) but this is the first study to demonstrate that it also extends to the lymph node draining the site of inflammation. This could be interpreted as evidence of the passive drainage of inflammatory myeloid cells from the site of inflammation via afferent lymphatics. However, as discussed in sections 1.3.2.1, 1.3.3.1.2 and 1.3.3.2.2, the balance of evidence suggests that neutrophils and monocytes predominantly infiltrate the dLN via HEVs under the influence of a myriad of inflammatory mediators. It is therefore pertinent to question which mediators are most relevant to the neutrophil and monocyte influxes described in this chapter.

3.4.4.2 Determinants of neutrophil and monocyte infiltration As discussed extensively in Section 1.3.3.1.1 of the introduction, the determinants of neutrophil infiltration into the dLN are only partially understood. IL-1β produced by lymph

16 Moreover, CFA is another stimulus shown to elicit protracted neutrophil infiltration into the draining lymph node (312,372), and is associated with chronic granulomatous inflammation (464). 149

node resident macrophages has been shown to promote neutrophil infiltration following challenge with Pseudomonas aeruginosa (72) and modified Vaccinia virus Ankara (328). However, the depletion of lymph node resident macrophages does not impair the neutrophil influx induced by S. aureus (173). Rather, in this context neutrophil infiltration is heavily dependent upon complement activation (173). Finally, inhibition or deletion of either cyclooxygenase (COX) 1 or 2 ablates the lymph node neutrophil influx elicited following challenge with CFA, suggesting that COX-derived lipid mediators play an important role in this context (312). It is this latter mechanism that is most pertinent with regard to the model established in this chapter. This is because challenge with heat-killed E. coli has previously been shown to induce a significant and acute increase in both the number of neutrophils and the concentration of prostanoids in the afferent and efferent lymph of the dLN in ovine lymphatic cannulation models (211,447). In addition, the acute production of prostanoids by neutrophils infiltrating the dLN has been shown to limit the developing T cell response. For these reasons, and because cyclooxygenase inhibition can also be readily applied to human studies of inflammation, the investigation of prostanoid production in the dLN following challenge with killed E. coli represents a tractable target in the study of infiltrating neutrophils and monocytes and is thus the focus of chapter 4 of this thesis.

In contrast to neutrophils, the infiltration of monocytes into the dLN is well-established as a CCR2-dependent process (205,242,369,370,381). The relative importance of different CCR2 ligands varies according to the inflammatory context (205,325,328,369,375,390,391,465) and a role for CXCR3 ligands has also been implicated (390). However, the precise source and drivers of CCR2-ligand production in the dLN is less clear. Notably, Sammicheli et al have illustrated that the dLN monocyte infiltrate elicited following challenge with LCMV is completely ablated in mice deficient for the type I IFN αβ receptor (IFNAR) (381). Moreover, type I IFNs have been shown to induce expression of CCR2 ligands (466–470). This is significant because the upregulation of CD69 in the KEC-dLN (Figure 3.7) suggests that type I IFNs are signalling in the dLN (278,342,401,452,453). Thus, type I IFNs may also be responsible for the described monocyte infiltrate. In addition, type I IFNs have also been implicated in a variety of other innate immune pathways in the dLN which serve to bolster the innate and adaptive immune functions of the dLN (Chapter 5). The extent to which type I IFNs utilise infiltrating monocytes and/or neutrophils to mediate these functions are unknown and this forms the focus of Chapter 5 of this thesis.

150

3.4.5 Summary and conclusions

The primary aim of this chapter was to establish a murine model in which the infiltration of neutrophils and monocytes into the dLN could be studied. This chapter achieves this aim. Firstly, it illustrates that the murine earflap immunisation model is appropriate. Secondly, it illustrates that challenge with vaccine-preparations of Bacillus Calmette-Guerin (BCG) do not drive neutrophil infiltration into the dLN. This raises important and unexplored questions with regard to the interactions between BCG and resident innate immune cells in the dLN but renders this stimulus inappropriate for the aims of this thesis. Finally, this chapter demonstrates in addition to its use in studying acute inflammation in humans (446), skin challenge with 1.5 x 107 killed E. coli is an inflammatory stimulus that induces the infiltration of both neutrophils and monocytes into the dLN. Moreover, it provides a detailed temporal profile of these cellular influxes that defines the first 72 hours following challenge as the time window in which to study the functions of these cell types. The data presented in this chapter therefore serves as a robust foundation for the study of infiltrating neutrophils and monocytes in relation to other innate immune pathways in the dLN. In this regard, Section 3.4.4.2 highlights the potential role played by cyclooxygenase-derived prostanoids and type I IFNs on both the recruitment and function of neutrophils and monocytes in the dLN and accordingly these inflammatory pathways serve as the focus of chapters 4 and 5 of this thesis.

151

4 Investigations of Prostanoid Synthases in the Draining Lymph Node

4.1 Abstract

The synthesis of prostanoid lipid mediators by cyclooxygenases and downstream terminal prostanoid synthases is a key process in many physiological and inflammatory contexts. Studies of cyclooxygenase function in the draining lymph node (dLN) demonstrate that cyclooxygenase activity can both limit and potentiate the developing adaptive immune response depending on the inflammatory context. Notably, neutrophils infiltrating the dLN have been shown to produce prostanoids that limit the developing T cell response (312). This chapter sought to extend these findings by characterising the expression of cyclooxygenase-2 (COX-2), microsomal PGE synthase-1 (mPGES-1) and thromboxane synthase (TBXAS) by neutrophils and monocytes infiltrating the dLN. Furthermore, the effect of acute cyclooxygenase inhibition on the developing humoral immune response was evaluated.

Significant increases in the expression of COX-2, mPGES-1 and TBXAS were measured in the dLN during the first 48 hours following challenge with KEC. Tandem FACS and qRT-PCR analysis further demonstrated that neutrophils and monocytes were the major expressers of these prostanoid synthases in the dLN. In addition, whilst cyclooxygenase inhibition at the time of challenge reduced the influx of neutrophils into the dLN, it did not modulate the humoral immune response generated following challenge with killed E. coli.

In summary, this chapter demonstrates that infiltrating neutrophils and monocytes are largely responsible for the acute upregulation of COX-2, mPGES-1 and TBXAS in the dLN. In particular, the novel finding that monocytes represent strong expressers of these prostanoid synthases broadens our current understanding of prostanoid production in the dLN. Moreover, the fact that acute cyclooxygenase inhibition has no discernible effect upon the developing humoral immune response illustrates that the immunomodulatory effects of prostanoids in the dLN are context-dependent. The next two chapters of this thesis therefore explore the role of a separate innate immune pathway in the KEC-draining lymph node; that of type I interferons.

152

4.2 Introduction

Chapter 3 demonstrates that the skin injection of 1.5 x 107 killed E. coli drives the acute infiltration of neutrophils and monocytes into draining lymph node (dLN). Their infiltration has been associated with the rapid production of prostanoids, a class of lipid mediators with a plethora of functions in the initiation and resolution of inflammation. There is evidence that prostanoids are required for the infiltration of neutrophils into the dLN (312,372) and that neutrophils are the cardinal source of prostanoids in the dLN (312). However, no role has yet been identified for monocytes in the production of prostanoids in the dLN and the synthases utilised by neutrophils and/or monocytes have not been characterised. To do so would be significant, as at present, there is conflicting evidence as to whether and how prostanoids regulate the developing adaptive immune response within the dLN (see Section 4.2.7). This chapter therefore seeks to clarify the kinetics and mechanisms of prostanoid production in the dLN in order to inform novel hypotheses as to how prostanoids regulate the developing adaptive immune response. Specifically, to delineate whether or not infiltrating neutrophils and monocytes are major producers of inflammatory prostanoids in the dLN and whether or not this contributes to their immunomodulatory functions. Such insights could inform approaches to modulate the developing adaptive immune response through inhibition of cyclooxygenases, specific prostanoid synthases or antagonism of prostanoid receptors.

4.2.1 Prostanoids The prostanoids that belong to the family of lipid mediators known as the eicosanoids. The eicosanoids are unified by the fact that they are derived from unsaturated fatty acids with a 20-carbon chain. The major eicosanoid precursor is the 20-carbon lipid arachidonic acid, which is generated by the action of phospholipase A2 on membrane phospholipids. Arachidonic acid can be metabolised by cyclooxygenase (COX) to generate prostaglandin H2, which can then be metabolised by a variety of different synthases to generate any member of the prostanoid family of lipid mediators (471–473) (Figure 4.1). The biological importance of prostanoids was first recognised in the early 20th century, through investigations of the effect of seminal fluid on various excised tissues (473). In the 1970s it was discovered that non-steroidal anti- inflammatory drugs (NSAIDs), such as acetylsalicylic acid (aspirin) ablate the production of prostanoids through the inhibition of cyclooxygenase (474,475). Indeed, whilst prostanoids

153

play important roles in various physiological settings, they are best known as key mediators of inflammation.

Figure 4.1: The synthesis of prostanoids from arachidonic acid by the action of cyclooxygenases and terminal prostanoid synthases. Created with biorender.com

Few studies have explored the roles played by prostanoids in the dLN during inflammation. Nevertheless, infiltrating neutrophils have been shown to produce prostanoids in the dLN (312) and the inhibition of prostanoids has been shown to modulate the developing adaptive immune response (discussed in Section 4.2.7). These studies generally focus upon the deletion or inhibition of cyclooxygenases but specific roles for prostaglandin E2 (PGE2) and thromboxane

A2 (TBXA2) have been demonstrated in the context of T cell responses (476–479). The prominent role described for neutrophils in prostanoid production in the dLN is thus clearly relevant to the acute neutrophil influx described in Chapter 3. This introduction therefore first provides a general description of the biology of cyclooxygenases, PGE2 and TBXA2 before reviewing what is known of their roles in the dLN.

154

4.2.2 Cyclooxygenases

Cyclooxygenases (COX) catalyse the conversion of arachidonic acid into prostaglandin H2, which is the rate-limiting step for the synthesis of all the lipid mediators in the prostanoid family (472). Two distinct isoforms of COX exist in mammals; COX-1 and COX-2 (472). These enzymes are encoded by separate genes but are structurally very similar; both being homodimers, with each dimer subunit composed of a membrane-spanning domain, an epidermal growth factor domain and a catalytic domain (472). With regards to their subcellular distribution, COX-1 is shared relatively evenly between these endoplasmic reticulum and nuclear membranes, whereas COX-2 is localised to a greater extent on the nuclear membrane (480). However, the major difference between these two isoforms of cyclooxygenase lies in the regulation of their expression.

COX-1 is widely regarded as a constitutively expressed enzyme that performs housekeeping functions in a wide variety of tissues (481–484). In contrast, COX-2 was discovered on account of the fact that it is highly inducible and strongly expressed following exposure to mitogenic stimuli (485–487). The discovery of such a highly inducible isoform of COX rapidly led to the ‘COX-2 hypothesis’, which theorised that COX-1 is responsible for the homeostatic production of prostanoids in the steady state, whereas COX-2 is responsible for the production of prostanoids in the context of inflammation (472). This is reflected in the structure of their respective genes. The 5’ region of COX-1 gene is consistent with that of a housekeeping gene, being largely devoid of regulatory elements and lacking a TATA box (488). In contrast, the 5’ region of COX-2 gene is littered with transcription factor binding sites (484,489–491). This includes two binding sites for NF-Kβ, a major transcription factor that transduces signalling induced by various pattern recognition receptors and inflammatory cytokines (484,490). Moreover, COX-2 expression can also be downregulated; most notably by corticosteroids (486,492). In addition, COX-1 and COX-2 also differ in their post-transcriptional regulation (484). COX-1 mRNA and protein are both significantly more stable than COX-2 mRNA and protein respectively (492,493). This is on account of AU-rich instability elements in the 3’ untranslated region of the COX-2 mRNA (494) and a 19 amino-acid cassette adjacent to the C- terminus of the COX-2 protein (495) that target COX-2 mRNA and protein for degradation respectively. The fact that dexamethasone (a potent anti-inflammatory glucocorticoid) decreases the stability and half-life of COX-2 mRNA (496) further illustrates that the inducible nature of COX-2 is central to the regulation of inflammation. Thus, as would be predicted from the COX-2 hypothesis, the expression and degradation of COX-2 is regulated to a much greater extent than that of COX-1. However, the original COX-2 hypothesis has been modified due to the fact that COX-2 has since been shown to be constitutively expressed in specific tissues

155

(most notably kidney, thymus, brain and gastrointestinal tract) and thereby perform homeostatic functions (497–499). Moreover, there is also evidence to suggest that COX-2- derived lipids are important in the resolution of inflammatory immune responses (500). Thus, COX-2 is the primary source of prostanoids in the context of inflammation but this inducible enzyme also plays important roles in both homeostasis and the resolution of inflammation.

4.2.3 Cyclooxygenase inhibitors Non-steroidal anti-inflammatory drugs (NSAIDs) are routinely used in medicine for a variety of purposes, including the treatment of pain and fever as well as the prevention of platelet aggregation. In the 1970s it was discovered that the majority of NSAIDs inhibit the production of prostanoids through the inhibition of COX (474,475). These drugs can be broadly divided into three groups according their mechanism of COX inhibition; (1) rapidly-reversible inhibitors such as ibuprofen, (2) time-dependent slowly-reversible inhibitors such as indomethacin and (3) irreversible inhibitors such as aspirin (501–503). The discovery of COX-2 expanded the classification of these drugs with regard to their relative selectivity for COX-1 and COX-2 (504– 506). The COX-2 hypothesis described in Section 4.2.2 drove the rapid development of COX-2 selective inhibitors in the hope that these drugs would achieve the anti-inflammatory benefits of traditional COX-inhibitors whilst avoiding the adverse effects that result from the inhibition of physiological prostanoid production. However, this promise was not realised as COX-2 selective inhibitors were associated with significant cardiovascular adverse events, which ultimately resulted in the withdrawal of rofecoxib from the market and the restricted use of other COX-2 selective inhibitors (501,507–509). As a result, the research aims of this field have shifted to focus on understanding the physiological functions of COX-2 in order to inform the design of safer methods of selective COX-2 inhibition (497).

4.2.4 Prostaglandin E2

Prostaglandin E2 (PGE2) is a member of the prostanoid family of lipid mediators and it plays cardinal roles in numerous physiological and inflammatory processes (510). Notable examples of the former include ovulation (511), blood pressure regulation (512) and maintenance of the gastric mucosal barrier (513). The multiple roles played by PGE2 in the inflammatory response include the induction of vasodilation and increased vascular permeability (514), lowering of the pain threshold (515) and generation of the febrile response (516,517). PGE2 exerts its actions through the agonism of four G-protein coupled receptors (GPCRs); EP1-4 (510). These

156

GPCRs differ with regard to both their tissue distribution and the G-proteins to which they are coupled. EP1 is coupled to Gq/11 and thereby induces calcium signalling (518,519). EP2 couples to Gs and thereby stimulates adenylate cyclase (510,520,521). The various isoforms of EP3

(generated by alternative splicing) are largely coupled to Gi, Gs or Go and thereby either inhibit or stimulate adenylate cyclase or induce calcium signalling (510,522,523) and EP4 couples with both Gs and Gai thereby both stimulate adenylate cyclase and PI3K signalling (510,524).

As with all prostanoids, the synthesis of PGE2 first requires the conversion of arachidonic acid to PGH2 by COX. PGH2 is then converted into PGE2 via one of three terminal synthases; membrane-bound prostaglandin E synthase 1 (mPGES-1), membrane-bound prostaglandin E synthase 2 (mPGES-2) or cytosolic prostaglandin E synthase (cPGES) (525–527). mPGES-2 and cPGES are constitutively expressed across a wide range of tissues and are thought to be the major producers of PGE2 in the context of homeostasis (525,526). In contrast, mPGES-1 is considered the major driver of prostaglandin E2 synthesis in the context of inflammation. Similar to the COX-2 gene, the mPGES-1 gene harbours numerous transcription factor binding sites and its expression is induced following challenge with inflammatory stimuli and is downregulated by dexamethasone (517,527–529). Furthermore, there is evidence that mPGES-1 and COX-2 are functionally coupled to augment PGE2 production in the context of inflammation (527,529), although this has been disputed (530,531). Finally, mPGES-1 deficient mice have demonstrated the cardinal role played by mPGES-1 in various inflammatory processes, including the febrile response (517), pain hypersensitivity (532), experimental autoimmune encephalitis (533) and collagen-induced arthritis (532,534,535). However, as with

COX-2, mPGES-1 has also been shown to contribute to homeostatic PGE2 production and is required for various homeostatic physiological processes (531,536–538) and has even been shown to exert anti-inflammatory actions in certain contexts (539,540). Nevertheless, it is clear that mPGES-1 plays important, if not fully understood, functions in the regulation of inflammation. Overall, the diversity of PGE2 synthases and receptors described facilitate the numerous functions of PGE2, of which many are still not known or fully understood, including in the dLN.

4.2.5 Thromboxane A2

Thromboxane A2 (TBXA2) is synthesised from PGH2 via thromboxane A synthase (TBXAS), a nuclear/ER membrane-bound enzyme of the cytochrome p450 family (515,541,542). TBXA2 exerts its action on target cells through agonism of the thromboxane receptor (TP), a GPCR that exists as two isoforms (generated by alternative splicing) and couples with Gq and various

157

other G-proteins (543–545). TBXA2 is best known as a prothrombotic agent, as it mediates vasoconstriction and platelet aggregation, the latter driven by TP-induced platelet activation and conformational change (546–549). In addition to platelets, the gene encoding thromboxane synthase is constitutively expressed in a variety of other tissues including lung, liver, kidney and spleen (550,551). Whilst the TBXAS gene harbours several putative transcription factor binding sites, there is no evidence to suggest that it is induced by inflammatory stimuli as per the genes encoding COX-2 and mPGES-1 (551,552). Nevertheless, there is evidence that TBXA2 contributes to inflammatory processes, having been implicated in allergic airway inflammation (553,554), sepsis (555,556) and the modulation of T cell driven inflammation (476,557). It is this latter finding that is of greatest interest with regard to the study of prostanoids in the dLN as thromboxane A2 has been shown to disrupt interactions between dendritic cells and T cells (476,477). Further characterisation of the production and actions of thromboxane A2 in the dLN are therefore warranted to evaluate its potential importance in the modulation of vaccine-driven adaptive immune responses.

4.2.6 Prostanoid production in the draining lymph node

There is substantial evidence that prostanoid concentrations are elevated in the dLN following an inflammatory challenge. In the 1970s, an ovine model of efferent lymphatic cannulation was used to demonstrate rapid increases in the concentration of PGE and PGF prostaglandins in the efferent lymph of the popliteal lymph node within 12 hours of hock challenge with inflammatory stimuli, including killed E. coli (211,343,447). In addition, increased concentrations of the prostanoids PGE2, TBXA2, PGD2 and PGF2 have also been measured in the murine popliteal dLN 2 hours following footpad challenge with OVA/CFA (312). These findings could reflect passive drainage of prostanoids from the site of inflammation via afferent lymphatics and/or intranodal production of prostanoids. The latter has been shown in numerous studies. Firstly, ovine lymphatic cannulation studies have shown that direct infusions of inflammatory stimuli (including killed E. coli) into afferent lymph leads to cyclooxygenase-dependent increases in prostanoid concentrations in efferent lymph (211,343,447). Secondly, several studies have demonstrated expression of cyclooxygenases and terminal prostanoid synthases in the dLN. COX-1 and TBXAS are constitutively expressed in lymph nodes (558,559) and several studies have demonstrated increased expression of COX-2 (558–562), mPGES-1 (559,560) and prostacyclin synthase (559). The majority of these studies demonstrate that the upregulation of these enzymes occurs acutely in the first 72 hours following challenge (558,559,561,562), which is consistent with the previously discussed rapid increases in prostanoids in the lymph node and efferent lymph. However, it is notable that 158

Kojima et al have demonstrated increased COX-2 and mPGES-1 expression at the much later time points of days 10 and day 21 (560). There are therefore two potential time windows in which prostanoid production is increased in the dLN following an inflammatory challenge; the first 72 hours (211,312,343,447,558,559,561,562) and between days 10 and 21 following challenge (560).

Several different cell types have been implicated in the production of prostanoids in the dLN. Unanue and Yang provide strong evidence that neutrophils are the major source of prostanoids in the dLN 2 hours following challenge with OVA/CFA (312). This is supported by the fact that CD11b+ve cells have been shown to be responsible for acute COX-2 expression in the mesenteric lymph nodes of mice orally challenged with salmonella typhimurium (558). However, as demonstrated in Chapter 3, neutrophils are not the only CD11b+ve cells in the dLN. It is therefore notable that Nagamachi et al have reported a significant increase in the number of mPGES-1+ve CD11c+ve cells in the dLN within the first 24 hours following challenge, although the precise location of these cells within the dLN was not elucidated (563). As discussed in Chapter 3, these CD11c+ve cells could represent Ly6Chi monocytes, dendritic cells or lymph node resident CD11c+ve cells. There is also evidence that stromal cells produce prostanoids in the dLN. Kawamura et al (562) have immunohistochemically co-localised COX-2 expression with the stromal cell markers α smooth muscle actin and desmin in the dLN, which they suggest represents fibroblastic reticular cells in the paracortex. This is in accord with several studies that have demonstrated expression of COX-1 (564,565), COX-2 (564–566), mPGES-1 (564) and PGIS (567,568) by cell lines derived from fibroblastic reticular cells (FRCs) and follicular dendritic cells (FDCs). Moreover, their expression of COX-2 and mPGES-1 is increased by inflammatory stimuli (564–566). Finally, recent17 studies have demonstrated high levels of COX-2 expression by FRC harvested from steady state lymph nodes (569,570) and monocytes trafficking through lymph nodes in the steady state have also been shown to upregulate COX-2 (366). These findings conflict with previous studies that demonstrate that COX-2 expression is absent or minimal in lymph nodes in the steady state (558–562).

4.2.7 Prostanoids and developing adaptive immune responses Numerous studies have investigated the roles played by prostanoids in the developing adaptive immune response. The literature in this field is extensive and ranges from in vivo

17 i.e. published subsequent to the experiments presented in this chapter 159

studies of COX-deficient, COX-inhibited or prostanoid receptor deficient mice to largely in vitro studies detailing the mechanisms of prostanoid action on T cell and dendritic cell function.

There is robust evidence that prostanoids are important for the developing humoral immune response. This is because COX-1 deficient mice, COX-2 deficient mice and mice subject to chronic COX inhibition exhibit reduced antibody responses (571–574). Kojima et al have further demonstrated that mPGES-1 deficient mice exhibit similarly defective antibody responses (534,560). The precise mechanism by which prostanoids mediate this effect is unclear. In vitro studies provide evidence that PGE2 and prostacyclin produced by follicular dendritic cells promote B cell survival (575–577) suggesting that these prostanoids are important for germinal centre reactions. This is supported by the fact that prolonged supplementation with a stable prostacyclin analogue potentiates the antibody response to

KLH/CFA, although no effect was observed with PGE2 – potentially because a stable analogue of PGE2 was not utilised (574). Nevertheless, there is strong evidence overall that both PGE2 and prostacyclin are required for the development of optimal humoral immune responses in mice. However, one human study has shown that COX-inhibition for 12 days following influenza vaccination had no effect upon the antibody response (578). This suggests that the importance of prostanoids for antibody responses is somewhat dependent on species or stimulus-related factors.

In contrast to humoral immune responses, studies that have investigated the effect of prostanoids on developing T cell responses have yielded contrasting findings. With regards to in vivo effects, COX-inhibition has been shown to potentiate T cell responses (312,477,573,579). The study published by Unanue and Yang is particularly notable as it demonstrates that TBXA2 produced by dLN-infiltrating neutrophils limits the number of antigen-specific T cells generated in the dLN and as such T cells numbers can be significantly increased if COX is inhibited during the first 24 hours following challenge (312). This concurs with other studies demonstrating that TBXA2 inhibits T cell dendritic cell interaction and that

TP-deficient mice exhibit increased T cell responses (476,477). PGE2 has also been shown to modulate T cell responses. T cells express the PGE2 receptors EP2 and EP4 (580) and EP4 signalling is required for the Th1 and Th17 T cell responses in vivo (478,479). These studies clearly demonstrate that PGE2 exerts this function during the sensitisation phase as opposed to the effector phase of the T cell response (478,479) . Further in vitro studies suggest that this improved sensitisation is mechanistically underpinned by EP4-driven PI3-K signalling in T cells and IL-23 production by dendritic cells (479). EP1 signalling during sensitisation has also been shown to be important for Th1 responses in vivo but the mechanism is less clear in this context

(563). However, there is also substantial evidence that PGE2 limits T cell responses. Indeed, 160

mPGES-1 deficient and EP2/4 double-deficient mice exhibit augmented T cell responses following a viral challenge (581). Moreover, production of PGE2 by lymph node fibroblastic reticular cells has been shown to limit developing T cell responses (569,570). In summary, the literature presents divergent findings with regard to the effects of PGE2 on T cell responses, highlighting the need for further clarification of PGE2 production and action within the dLN.

4.2.8 Prostanoid functions within the draining lymph node The preceding section provides substantial evidence that prostanoids are both produced in the dLN and can modulate the developing adaptive immune response in various contexts. However, it is not clear whether prostanoids modulate the latter specifically within the dLN. Indeed, very few studies have provided direct evidence of prostanoid function within the dLN. These studies have provided us with three key pieces of information: firstly, that COX- inhibition with indomethacin drastically reduces neutrophil infiltration into the dLN (312,372), secondly, that TP-deficient T cells exhibit increased interaction times with DCs presenting cognate antigen in the dLN (477) and finally, that the specific deletion of COX-2 in FRCs potentiates T cell responses in the dLN (570)18. Given the divergent findings with regard to the effects of prostanoids on the developing adaptive immune response (Section 4.2.7), there is clearly a need to better understand the details of prostanoid production and function within the dLN.

4.2.9 Summary There is strong evidence that prostanoids are produced in the dLN following an inflammatory challenge. There are two potential time windows in for such prostanoid production; most evidence favours acute production within the first 72 hours (211,312,343,447,558,559,561,562) but there is also evidence for a later window between days 10 and 21 (560). Myeloid cells and resident stromal cells have both been implicated in the production of prostanoids in the dLN but their relative contribution and importance remains unclear. Of the studies discussed, the one considered to be most applicable to the KEC- draining lymph node model established in Chapter 3 was that of Unanue and Yang (312). This study demonstrated that (1) COX-inhibition ablated neutrophil infiltration into the dLN, (2) that neutrophils serve as the major source of prostanoids in the dLN and (3) that neutrophil- derived TBXA2 limits the developing T cell response and that this could be reversed by either

18 N.B. this study was published 3 years after the experiments presented in this chapter were conducted. 161

COX-inhibition or TP antagonism in the first 24 hours following an inflammatory challenge. This thesis chapter seeks to extend these findings through further characterisation of the kinetics and cell types responsible for prostanoid production in the dLN.

Firstly, it is unclear which prostanoid synthases are responsible for this acute prostanoid production and the relative expression during the first 24 hours relative to later time points.

The expression of COX-2, mPGES-1 and TBXAS is particularly important as PGE2 and TBXA2 are the two prostanoids principally implicated in the studies discussed in this introduction. Secondly, with regards to the cell types responsible for the expression of these synthases, Chapter 3 demonstrates that the infiltration of monocytes eclipses that of neutrophils following challenge with killed E. coli (Figure 3.9) and thus it is pertinent to question whether infiltrating neutrophils and/or monocytes express these synthases. Finally, it is pertinent to question whether acute cyclooxygenase inhibition with indomethacin19 is also able to ablate neutrophil infiltration in this model and potentiate the developing humoral immune response. The latter is of particular interest, as it is well established that prolonged COX-inhibition is deleterious to antibody responses (571–574) but the effect of COX-inhibition strictly restricted to the acute time window (≤72 hours) has not been studied. In addition, neutrophil depletion at the time of challenge has been shown to potentiate humoral immune responses (202,371,372)20, suggesting that there may be an acute time window in which prostanoids limit rather than promote the developing humoral immune response. Overall, the overarching hypothesis informing the experiments presented in this chapter can be outlined as follows:

Infiltrating neutrophils and/or monocytes limit the developing humoral immune response via the production of prostanoids in the dLN.

This hypothesis seeks to inform our understanding of whether and how infiltrating myeloid cells modulate adaptive immune responses via the production of prostanoids.

19 Indomethacin is the preferred NSAID in this context. This is because it is was utilised by Unanue and Yang to demonstrate the effect of prostanoids on T cell responses in the draining lymph node (312) and also because it inhibits both COX-1 and COX-2 and exhibits slowly-reversible inhibition kinetics (504,582). 20 With Parsa et al (372) also implicating a role for prostanoids 162

4.2.10 Aims

• Compare the expression of COX-2, mPGES-1 and TBXAS in steady state lymph nodes with draining lymph nodes harvested ≤48 hours, day 7 and day 14 following challenge with 1.5 x 107 killed E. coli

• Determine whether or not infiltrating neutrophils and monocytes are responsible for any increases in the expression of COX-2, mPGES-1 and TBXAS in the draining lymph nodes.

• Determine whether or not acute COX-inhibition with indomethacin ablates neutrophil infiltration in the draining lymph node following challenge with 1.5 x 107 killed E. coli

• Determine whether or not acute COX-inhibition with indomethacin potentiates the humoral immune responses elicited following challenge with 1.5 x 107 killed E. coli

163

4.3 Results

4.3.1 Skin injection of killed E. coli induces the acute expression of cyclooxygenase-2 in the draining lymph node

A central tenet of the hypothesis informing the experiments presented in this chapter is that infiltrating neutrophils and monocytes are the primary source of prostanoids in the dLN following challenge with KEC. Other studies have demonstrated strong expression of COX-2 by lymph node stromal cells (564–566,566,569) and it has been proposed that they promote developing germinal centre reactions via the production of prostanoids (575–577). It was therefore important to demonstrate whether COX-2 expression is increased in the dLN following challenge with KEC and if this is restricted to the acute time window (≤48 hours) consistent with neutrophil/monocyte infiltration or days 7 and 14; time points consistent with germinal centre reactions (221,583). Mice were thus injected with 1.5x 107 killed E. coli and their dLNs were analysed for COX-2 expression by end-point reverse-transcriptase polymerase chain reaction (RT-PCR) 6 hours, 7 and 14 days later. To ensure RNA from lymph node stromal cells was captured, half of the lymph nodes analysed in this experiment had their RNA extracted from whole lymph nodes as opposed to lymph node suspensions, with the latter preparation likely to underrepresent stromal cells relative to haematopoietic cells (Figure 4.2A outlines this experimental design).

As COX-2 expression has previously been shown to be absent from lymph nodes in the steady state (558,560), a sample size of 4 mice per group was used to illustrate the binary outcome of whether or not COX-2 expression was induced. End-point RT-PCR was utilised in favour of quantitative RT-PCR (qRT-PCR) as it was deemed that this would be a better method of demonstrating absence of expression21. This method clearly demonstrated that COX-2 expression was very minimal or absent from non-draining control and contralateral lymph nodes but marked in 6-hour draining ipsilateral lymph nodes (Figures 4.2B and 4.2C). In addition, COX-2 expression was absent from day 7 and 14 dLNs, with Figure 4.2D confirming that lymph nodes harbour increased numbers of GL-7+ve CD95+ve germinal centre B cells at these time points. Finally, there was no marked difference in COX-2 expression between RNA extracts from homogenised whole lymph nodes relative to cell suspensions (Figure 4.2C). These findings therefore demonstrate that the dLN becomes a site of acute COX-2 expression following the skin injection of killed E. coli.

21 In retrospect this was an erroneous decision as the reaction products of a qRT-PCR experiment could have been subsequently run on an electrophoresis gel to confirm lack of expression (as has been done for all other RT-PCR experiments presented in this thesis). 164

Figure 4.2: Acute expression of cyclooxygenase-2 in the draining lymph node following skin injection of killed E. coli (A) Experiment Design: Mice were injected into the skin of the earflap with 1.5 x 107 killed E. coli and superficial parotid lymph nodes were harvested at 6 hours, 7 days and 14 days for analysis by end-point reverse transcriptase polymerase chain reaction. RNA was extracted from either whole lymph nodes (W) or single cell suspensions generated from lymph nodes (S). (B and C) Expression of (B) the reference gene Gapdh or (C) the gene encoding cyclooxygenase-2 (Ptgs2) in draining and non-draining lymph nodes. (D) The number of CD95+ve GL-7+ve germinal centre B cells in draining and non-draining lymph nodes. Sample Size: n = 2 x CTRL LN, 4 x Con LN, 4 x 6hr LN, 4 x Day 7 LN and 4 x Day 14 LN. NC3Rs: 16 mice in total. Con/Contra: contralateral: CTRL = control, hr: hour, LN: lymph node.

165

4.3.2 Expression of cyclooxygenase-2, microsomal prostaglandin E synthase-1 and thromboxane synthase are increased in the KEC- draining lymph node Figure 4.2 demonstrates that COX-2 expression is induced acutely in the dLN following skin challenge with killed E. coli. However, the synthesis of prostanoids is also regulated by a variety of terminal prostanoid synthases downstream of COX-2. The synthases microsomal prostaglandin E synthase-1 (mPGES-1) and thromboxane synthase (TBXAS) are of particular note with regard to study of the dLN given the roles attributed to their products; PGE2 and

TBXA2 (Sections 4.2.6 – 4.2.8). Thus, in parallel to the flow cytometry presented in Figure 3.8, lymph node cell suspensions harvested at 6, 24 and 48 hours following KEC injection were analysed by qRT-PCR for COX-2, mPGES-1 and TBXAS expression. It was assumed that, as with COX-2, the expression of these synthases would be negligible in lymph nodes in the steady state but increased manifold if induced in the context of inflammation. Indeed, this analysis confirmed that the expression of COX-2, mPGES-1 and TBXAS were all increased at 6 hours following injection of killed E. coli (Figure 4.3A). Whilst COX-2 and mPGES-1 expression appeared to have decreased by 24 hours, the expression of TBXAS was similarly increased at 24 hours relative to 6 hours (Figure 4.3A). Further experiments illustrated that COX-2 expression was increased as early as 3 hours following injection (Figure 4.3B) and that the expression of COX-2 and mPGES-1 appeared to decrease between 6 and 12 hours following injection, whilst expression of TBXAS was similarly elevated at these two time points (Figure 4.3C). These data therefore demonstrate that COX-2, mPGES-1 and TBXAS are strongly induced in the dLN during the first 24 hours of this inflammatory challenge and therefore suggests that the dLN becomes a site of increased prostanoid production during this time period.

166

Figure 4.3: Increased expression of COX-2, mPGES- 1 and TBXAS in the KEC-draining lymph node (A) Expression of the genes encoding COX-2, mPGES-1 and TBXAS in the draining lymph node at 6, 24- and 48-hours following injection of killed E. coli (KEC). (B) Expression of COX-2 in the draining lymph node at 3 hours following injection of KEC. (C) Expression of COX-2, mPGES-1 and TBXAS in the draining lymph node at 6- and 12-hours following injection of KEC. Sample sizes: (A) n = 6 x CTRL LN, 6 x Con LN, 4 x 6hr LN, 4 x 24hr LN, 4 x 48hr LN. (B) n = 4 x Con LN, 3 x 3hr LN. (C) n = 4 x Con LN, 4 x 6hr LN and 4 x 12hr LN. NC3Rs: 30 mice in total. The Mann-Whitney U test was used to determine statistical significance. *p<0.05 **p<0.01 relative to contralateral or control LN. LN: lymph node, CTRL: control, Con: contralateral, Ipsi: ipsilateral.

167

4.3.3 Infiltrating neutrophils and monocytes express COX-2, mPGES-1 and TBXAS in the KEC-draining lymph node

It is clear from Chapter 3 and Figures 4.2-4.3 that skin challenge with 1.5 x 107 killed E. coli (KEC) rapidly induces both the acute infiltration of inflammatory myeloid cells and the acute expression of the prostanoid synthases COX-2, mPGES-1 and TBXAS in the dLN. Prior studies have suggested that neutrophils produce prostanoids in the dLN (312). Moreover, monocytes trafficking through lymph nodes in the steady have also been shown to express COX-2 (366) but their role in prostanoid production has not previously been examined in the context of inflammation. It was thus hypothesised that both infiltrating neutrophils and monocytes serve as major expressers of prostanoid synthases in the dLN in this model. Thus, neutrophils and monocytes were isolated from the dLNs of mice challenged with 1.5 x 107 killed E. coli using fluorescence-activated cell sorting (FACS, as per Figure 4.4A) and their expression of COX-2, mPGES-1 and TBXAS compared with the other CD11b+ve and CD11b-ve cells present in the lymph node cell suspensions. The relatively small absolute number of neutrophils in the KEC- dLN necessitated pooling of 4 dLNs to perform the tandem FACS-qRT-PCR analysis. As neutrophils and monocytes were expected to be major expressers of at least COX-2, a sample size of 4 pooled lymph node cell suspensions was chosen in order to minimise the number of animals used. Tandem FACS and qRT-PCR analysis of the dLN demonstrated that neutrophils and monocytes exhibit increased expression of COX-2, mPGES-1 and TBXAS relative to other

+ve -ve CD11b and CD11b cells (Figure 4.4B-D). Moreover, dLN neutrophils and monocytes also exhibited increased expression of COX-2 and mPGES-1 relative to splenic neutrophils and monocytes, although their expression of TBXAS was similar or reduced relative to their splenic counterparts (Figures 4.4B-D). These data therefore demonstrate that neutrophils and monocytes are major expressers of COX-2, mPGES-1 and TBXAS in the KEC-dLN and suggest that COX-2 and mPGES-1 are specifically induced within infiltrating neutrophils and monocytes.

168

Figure 4.4: Infiltrating neutrophils and monocytes express COX-2, mPGES-1 and TBXAS in the KEC- draining lymph node (A) Dot plot demonstrating the cell populations isolated from the draining lymph node for qRT-PCR. (B- D) Expression of the genes encoding (B) COX-2, (C) mPGES-1 and (D) TBXAS by neutrophils and monocytes isolated from the draining lymph node or spleen 12 hours following injection of killed E. coli (KEC). Sample sizes: n = 4 x 12hr LN Neut samples, 4 x 12hr LN Mono samples, 4 x 12hr LN OTH samples, 4 x 12hr LN CD11b-ve samples, 4 x 12hr SPL Neut samples, 4 x 12hr SPL Mono samples. NC3Rs: 16 mice in total (LN had to be pooled from 4 mice to generate LN Neut samples). LN: lymph node, SPL: spleen, Neut: neutrophils, Mono: monocytes, Other: other CD11b+ve cells. Gene expression determined by qRT- PCR. The sample highlighted in red in (B) is contaminated as described in Section 4.4.1.

169

4.3.4 Cyclooxygenase inhibition reduces neutrophil infiltration into the draining lymph node following challenge with killed E. coli

It is clear from Figure 4.4 that neutrophils are likely to be a source of prostanoids in the dLN. However, there is also evidence to suggest that prostanoids modulate neutrophil infiltration. Indeed, Yang and Unanue (312) have illustrated that neutrophil infiltration into the dLN following challenge can be completely ablated by prior cyclooxygenase inhibition with indomethacin. In order to investigate whether cyclooxygenase inhibition also ablates neutrophil infiltration into the dLN following challenge with killed E. coli, mice were administered with 3mg/kg of indomethacin by oral gavage 2 hours prior to injection and their ipsilateral superficial parotid lymph nodes harvested 3 hours following injection for analysis by flow cytometry. As Unanue and Yang (312) demonstrated a complete ablation of neutrophil infiltration by COX inhibition, it was deemed prudent to carry out a pilot experiment with a sample size of 2 per group to determine whether or not this dramatic finding also applies in the context of skin challenge with killed E. coli. This experiment showed that lymph node neutrophil infiltration was not ablated22 in mice treated with indomethacin, although their dLNs did exhibit reduced numbers and percentages of neutrophils relative to those of mice that did not receive indomethacin (Figure 4.5A). This experiment was repeated with a larger sample size of 6 mice per group and this yielded the same result (Figure 4.5B). These data therefore confirm that this regimen of cyclooxygenase inhibition does not ablate neutrophil infiltration in this context. Nevertheless, there was a statistically significant 70% reduction in the percentage and number of neutrophils in the dLNs of indomethacin-treated mice relative to untreated controls. In summary, these data demonstrate that cyclooxygenase inhibition reduces but does not completely ablate neutrophil infiltration into the dLN following skin challenge with 1.5 x 107 killed E. coli.

22 i.e. reduced to the percentage or number of neutrophils present in non-draining contralateral lymph nodes. 170

Figure 4.5: Cyclooxygenase inhibition reduces but does not ablate neutrophil infiltration into the draining lymph node. Mice were administered with 3mg/kg indomethacin by oral gavage 2 hours prior to injection of 1.5 x 107 killed E. coli. Ipsilateral superficial parotid lymph nodes were harvested 3 hours following injection and the percentage and number of neutrophils was determined by flow cytometry. (A) Trial experiment with a sample size of 2 per treatment arm. (B) Repeat experiment with a sample size of 6 per treatment arm with example flow cytometry dot plots. Sample sizes: (A) n = 2 x Contra LN, 2 x Ipsi LN without INDO, 2 x Ipsi LN with INDO. (B) n = 12 x Contra LN, 6 x Ipsi LN minus INDO, 6 x Ipsi LN + INDO. NC3Rs: 16 mice in total. The Mann-Whitney U test was used to determine statistical significance. *p<0.05 **p<0.01.

4.3.5 Cyclooxygenase inhibition at the time of challenge does not potentiate the humoral immune response to killed E. coli

There is evidence that neutrophils infiltrating the dLN limit the developing humoral immune responses (202,371). Indeed, neutrophil depletion has been shown to increase antibody titre (371) and the numbers of germinal centre B cells in the dLN (202) following challenge with CFA and S. aureus respectively. As lymph node neutrophils have previously been shown to limit the developing T cell response via the production of prostanoids (312), it was hypothesised that prostanoids produced by the infiltrating COX-2/mPGES-1/TBXAS expressing neutrophils and monocytes described in this chapter may limit the developing humoral immune response following challenge with killed E. coli. Thus, mice were administered 3mg/kg of indomethacin by oral gavage 18 hours before, 2 hours before and 18 hours after injection of 1.5 x 107 killed E. coli and at days 7 and 14 following injection, superficial parotid lymph nodes and blood were harvested for analysis of germinal centre B cells and circulating anti-E. coli IgG respectively

171

(Figure 4.6A). A meaningful sample size calculation was precluded by the lack of background data to inform both the expected increase and variability in germinal centre B cell numbers or anti-E. coli antibody titre. Thus, a sample size of 4 mice was selected for each group as this would be sufficient to demonstrate a gross difference between the treatment groups as has been previously demonstrated by Unanue and Yang in the context of cyclooxygenase inhibition and T cell responses (312).

As expected, the ipsilateral lymph nodes of all mice injected with killed E. coli exhibited an increase in the percentage and number of germinal centre B cells at both days 7 and 14 post injection (Figure 4.6B). However, indomethacin treatment was not associated with any gross difference in the percentage or number of germinal centre B cells in the dLN at either day 7 and 14 (Figure 4.6B). As a second measure of the humoral immune response to killed E. coli, the amount of anti-E. coli IgG in plasma was determined at days 7 and 14 following injection using a whole-cell E. coli ELISA (Section 2.2.3.3). As expected, plasma harvested from mice 14 days following injection harboured substantially greater amounts of anti-E. coli IgG relative to the plasma of control mice (Figure 4.6C). However, no difference in anti-E. coli IgG was observed between mice administered indomethacin or its vehicle control (Figure 4.6C). Thus, acute cyclooxygenase inhibition does not does not appear to significantly modulate the humoral immune response following challenge with killed E. coli.

172

Figure 4.6: Acute cyclooxygenase inhibition does not influence the developing humoral immune response following skin challenge with killed E. coli (A) Experiment design: mice were orally gavaged with 3mg/kg indomethacin before and after injection of 1.5 x 107 killed E. coli into the murine earflap. Superficial parotid lymph nodes and plasma were harvested at days 7 and 14 post injection for analysis of (B) germinal centre B cells (B220+ve, CD95+ve, GL- 7+ve) and (C) anti-E. coli IgG respectively. Anti-E. coli IgG was measured using a whole-cell E. coli antibody ELISA wherein optical density reflects the amount of anti-E. coli IgG (Section 2.2.3.3). Error bars represent range, error bars omitted from the day 7 graph for clarity. Sample sizes: (B) n = 4 x CTRL LN, 10 x Con LN (+INDO and –INDO pooled), 4 x Day 7 +INDO LN, 4 x Day 7 –INDO LN, 4 x Day 14 +INDO LN, 4 x Day 14 –INDO LN. (C) n = 4 x CTRL plasma, 4 x Day 7 +INDO plasma, 4 x Day 7 –INDO plasma, 4 x Day 14 +INDO plasma, 4 x Day 14 –INDO plasma. NC3Rs: 20 mice in total. CTRL: control, p.o.: per os, GC: germinal centre, Ipsi: ipsilateral. The Mann-Whitney U test was used to test for statistical significance. NS = p-value >0.1.

173

4.4 Discussion

The prostanoid synthases COX-2, mPGES-1 and TBXAS and their products PGE2 and TBXA2 have been implicated in various lymph node processes (Sections 4.2.6 - 4.2.8). However, the time course over which these synthases are expressed within the dLN and the cells responsible for their expression have not been well characterised. The data presented in this chapter addresses this knowledge gap by demonstrating that the expression of these synthases peaks within the dLN during the first 48 hours following challenge with killed E. coli (Figures 4.2-4.3) and that infiltrating neutrophils and monocytes are cardinal expressers of these synthases (Figure 4.4). However, further experiments seeking to delineate the potential functions of these prostanoids in the dLN yielded negative results. The principle findings of this chapter are summarised below and their limitations and implications are discussed in the following sections.

• Skin challenge with 1.5 x 107 killed E. coli induces the acute expression of the prostanoid synthases COX-2, mPGES-1 and TBXAS in the dLN

• Infiltrating neutrophils and monocytes are major expressers of COX-2, mPGES-1 and TBXAS in the dLN.

• Cyclooxygenase inhibition with 3mg/kg indomethacin reduces but does not ablate neutrophil trafficking into the dLN following challenge with 1.5 x 107 killed E. coli

• Cyclooxygenase inhibition with 3mg/kg indomethacin does not significantly modulate the humoral immune response that is initiated following challenge with 1.5 x 107 killed E. coli

4.4.1 Technical limitation A mistake was made in one of the four cell sorts (presented in Figure 4.4), which resulted in the contamination of one of the ‘other CD11b+ve samples with isolated monocytes. This contaminated sample was included in all analyses in the interest of transparency and is highlighted in red in all relevant graphs.

174

4.4.2 The expression of cyclooxygenase-2, microsomal prostaglandin E synthase-1 and thromboxane synthase in the draining lymph node

The acute expression of COX-2, mPGES-1 and TBXAS described in this chapter is consistent with studies of the dLN in the context of oral salmonella infection (558) and carrageenan- induced pleurisy (559,561,562). Moreover, this finding is consistent with ovine lymphatic cannulation studies that have demonstrated a sharp increase in the prostanoid concentrations within the first 12 hours following hock challenge with heat-killed E. coli (211,447). In contrast to Kojima et al (560), no increase in COX-2 expression was demonstrable 7 and 14 days following challenge with 1.5 x 107 killed E. coli (Figure 4.2C). Lymph node stromal cells are thought to be responsible for COX-2 expression at these time points (534,560) and have been shown to express COX-2 in the steady state (569,570) so the lack of a COX-2 signal is somewhat unexpected. Indeed, COX-2 expression was even absent among RNA extracts of whole lymph node homogenates (Figure 4.2C), which should include these cell types. It is possible that a stromal cell COX-2 signal was diluted by other cell types and thus qRT-PCR of sorted stromal cell subsets would be a more sensitive method of measuring such COX-2 expression. Nevertheless, it is clear from Figure 4.2 that the COX-2 expression observed at the 6 hour time point far exceeds any steady state expression and any potential minor increases at days 7 and 14. This highlights the acute onset phase of the inflammatory response as the key time window for prostanoid production in this model. This is especially pertinent given Unanue and Yang’s evidence that this is the time period in neutrophils produce immunomodulatory prostanoids in the dLN (312).

With regards to the cell types responsible for the expression of these prostanoid synthases, Figure 4.4 identified infiltrating neutrophils and monocytes at the 12-hour time point. This is supported by the findings of Bowman and Bost (558), which demonstrated that COX-2 was predominantly induced in the CD11b+ve cells of the dLN. However, it contradicts Unanue and Yang’s assertion neutrophils are the major source of prostanoids in the dLN (312). Indeed, the fact that monocytes infiltrate the dLN in significantly greater numbers and for a longer duration than neutrophils (Figure 3.9) suggests that they may be a more important source of prostanoids in the dLN in this model. This could be determined by comparing the prostanoid concentrations of dLNs rendered deficient for neutrophils and monocytes. It must also be noted that resident LN stromal cells have also been shown to upregulate prostanoid synthases following exposure to inflammatory stimuli (564–566), but Figure 4.4 does not account for this as these cell types are likely excluded from the cell suspensions subjected to tandem FACS + qRT-PCR. In combination with the substantial synthase expression by monocytes described in

175

this chapter, this challenges Unanue and Yang’s description of neutrophils as the primary producer of immunomodulatory prostanoids in the dLN (312).

4.4.3 Drivers of prostanoid synthase expression in the draining lymph node

It is pertinent to question what factors drive the strong expression of COX-2, mPGES-1 and TBXAS by infiltrating neutrophils and monocytes. It is clear from Figure 4.4 that neutrophils and monocytes infiltrating the dLN exhibit substantially greater expression of COX-2 and mPGES-1 than their splenic counterparts. In contrast, the difference in TBXAS expression between lymph node and splenic neutrophils and monocytes is much more equivocal (Figure 4.4D). These findings suggest that COX-2 and mPGES-1 are specifically upregulated within neutrophils and monocytes infiltrating the draining lymph node, whilst the increased expression of TBXAS observed in Figure 4.4D may just reflect the infiltration of neutrophils and monocytes exhibiting constitutive TBXAS expression.

Notably, Jakubzick et al (366) have provided evidence that monocytes circulating through lymph nodes in the steady state exhibit increased expression of COX-2 relative to monocytes circulating through blood and tissues. This suggests that something intrinsic to the lymph node microenvironment drives expression of COX-2 by monocytes, although Jakubzick et al did not identify any such factor. However, it seems unlikely that this could fully explain the marked COX-2 and mPGES-1 expression described in Figures 4.4B-C when one considers the fact that both COX-2 and mPGES-1 are known to be strongly induced by both PAMPs and inflammatory cytokines (517,528,584–587). With regards to PAMPs, it would be interesting to compare the COX-2 and mPGES-1 expression exhibited by infiltrating neutrophils and monocytes that have phagocytosed E. coli with those that have not as increased expression among E. coli-bearing myeloid cells would suggest that such gene expression is predominantly PAMP-driven. This could be achieved through the use of fluorescent E. coli bioparticles in combination with tandem FACS + qRT-PCR. Cytokines may also play an important role. The significant increases in CD69 expression described in Chapter 3 (Figure 3.7) strongly suggest that type I interferons (IFNs) are active in the KEC-dLN (278,342,401,452,453) and COX-2 has been shown to be driven by interferon regulatory factors (587,588), as well as IL-1β (589,590) and IFNγ (588,591). The latter cytokines are pertinent as expression of both IL-1β and IFNγ can be induced by type I IFNs (172,279,466,592–595) including in the dLN with respect to IFNγ (121, 256). However, whilst several complex inflammatory networks have been described in the dLN, no studies

176

have investigated the role played by prostanoid synthases in these networks. This represents a knowledge gap that this model is well placed to explore.

4.4.4 Functions of prostanoid synthase expression in the draining lymph node

This chapter sought to test two hypotheses with regard to the function of acute prostanoid synthase expression in the dLN based on the findings of Unanue and Yang (312).

Hypothesis 1: Cyclooxygenase inhibition ablates the infiltration of neutrophils into the draining lymph node.

Figure 4.5 does demonstrate that acute cyclooxygenase inhibition significantly reduces the size of the neutrophil infiltrate into the dLN23 but fails to replicate the complete ablation described following challenge with complete Freund’s adjuvant (CFA) (312). This suggests that challenge with 1.5 x 107 killed E. coli drives both prostanoid-dependent and independent mechanisms of neutrophil recruitment. As discussed in Section 1.3.3.1.2, the mechanisms by which neutrophils infiltrate the dLN are only partially understood. Moreover, the mechanisms by which prostanoids drive this process have not been elucidated. In this regard, Lemos et al (596) have demonstrated that prostaglandin E2 promotes neutrophil infiltration via potentiation of the IL-23/IL-17 axis in the separate context of antigen-induced arthritis. It is possible that a similar mechanism may operate within dLN as Gray et al (388) have described a population of IL-17-committed innate-like lymphocytes positioned in the lymph node periphery24. Alternatively, prostanoid-driven tissue oedema has been shown to increase the free drainage of antigen to the dLN (162) and thus cyclooxygenase inhibition may reduce the number of killed E. coli bacilli reaching the dLN and thereby reduce the number of infiltrating neutrophils.

On a broader note, it is clear that a better understanding of the determinants of neutrophil infiltration into the dLN is required to inform hypotheses with regard to how prostanoids potentiate this process. For example, whilst monocyte infiltration is well understood to be a CCR2-dependent process (205,242,369,370,381), the chemokines and chemokine receptors directly responsible for neutrophil infiltration are not known. Studies have described increased

23 Notably, this mirrors human experiments performed in parallel by other members of the Gilroy laboratory, which shows that cyclooxygenase inhibition similarly reduces but does not ablate neutrophil infiltration into the site of inflammation following intradermal challenge with 1.5 x 107 killed E. coli (446). 24 Moreover, Shibata et al (597) have demonstrated that IL-23-driven production of IL-17 by resident γδ T-cells is partially responsible for the acute neutrophil influx induced by intraperitoneal injection of E. coli. 177

concentrations of the neutrophil chemokines CXCL1, CCL3 and CXCL2 in the dLN following various inflammatory stimuli (171,266,328) but their relative importance with regard to lymph node neutrophil infiltration has not been delineated via deletion or antagonism of their respective receptors. Indeed, the only chemokine receptor that has been shown to be non- redundant for neutrophil infiltration into the dLN is the complement 5a receptor (173). This is relevant to the data presented in this chapter as rapid complement activation and prostanoid production have both been described in ovine studies of the dLN (343,344). It is thus possible that prostanoids recruit neutrophils to the dLN via the potentiation of complement activation or vice versa.

Hypothesis 2: Acute cyclooxygenase inhibition potentiates the developing humoral immune response.

This hypothesis was primarily based on two findings; firstly that acute cyclooxygenase inhibition can potentiate T cell responses by inhibiting the production of prostanoids by lymph node infiltrating neutrophils (312) and secondly that neutrophil depletion at the time of challenge potentiates humoral immune responses (202,371,372)25. However, Figure 4.6 illustrates that acute COX-inhibition 0-48hrs following challenge with killed E. coli is not associated with gross potentiation of the humoral immune response. It is possible that this negative finding relates to differences between killed E. coli and the two inflammatory stimuli used to demonstrate potentiation of the humoral immune response following neutrophil depletion/COX-inhibition (202,312,371,372). Indeed, it is notable that these two stimuli, S. aureus and CFA, elicit protracted neutrophil influxes into the dLN (138,215–217), whereas the neutrophil influx induced by killed E. coli is much shorter in duration and resolves within 24 hours (Chapter 3, Figure 3.9). In addition, Calabro et al (140) have reported that neutrophil depletion has no effect on the antibody response to an influenza vaccine preparation, further suggesting that the potentiation described in references (202,371,372) is not a universal phenomenon. Finally, the small sample size used in this experiment only facilitated detection of large increases in antibody titre and germinal centre B cells akin to the large increases in antigen-specific T cells described by Unanue and Yang (312). It is therefore possible that acute COX-inhibition has more subtle effects on the developing humoral immune response that this experiment was not powered to detect.

The aspects of the adaptive immune response measured (germinal centre B cells and plasma anti-E. coli IgG) were similarly chosen on the basis of previous studies of lymph node neutrophils (202,371). However, one has to question whether these aspects are necessarily

25 With Parsa et al (372) also implicating a role for prostanoids 178

the best parameters of lymph node function to measure in the context of COX-inhibition as prior studies have focussed upon the effect of prostanoids on T cell responses and the dynamics of T cell: Antigen-presenting cell interaction (476,477). The fact that monocytes are identified as major expressers of COX-2, mPGES-1 and TBXAS is particularly notable in this regard as they upregulate markers consistent with differentiation into antigen-presenting dendritic cells (Chapter 3, Figure 3.8C). Thus, further investigations of the effect of prostanoids on the developing adaptive immune response would be better focussed on imaging and studying the interaction between prostanoid synthase-expressing monocytes and antigen- specific T cells within the dLN with and without cyclooxygenase inhibition.

4.4.5 Summary

This chapter encompasses a detailed analysis of the expression of inducible prostanoid synthases by myeloid cells infiltrating the dLN in the context of acute inflammation. Indeed, this characterisation validates neutrophils as a source of prostanoids (as per Unanue and Yang (312)) and highlight inflammatory monocytes as major expressers of prostanoid synthases in the dLN. Moreover, the significantly larger size and more prolonged duration of the monocyte infiltrate compared to the neutrophil infiltrate (Chapter 3, Figure 3.9) strongly undermines previous assertions that neutrophils are the major source of prostanoids in the dLN (312). With regards to the functions of this acute prostanoid synthase expression, COX-inhibition was shown to reduce the numbers of infiltrating neutrophils but did not potentiate the humoral immune response during the first 14 days following immunisation.

The chapter links the acute expression of inducible prostanoid synthases with the acute infiltration of neutrophils and monocytes described in Chapter 3. However, it is unclear how these infiltrating cells and their expression of prostanoid synthases relate to other inflammatory/immunological pathways operating within the dLN. One such pathway which has been shown to play a fundamental role in various inflammatory processes within the dLN, is type I IFN driven gene expression. Notably, type I IFNs have been shown to drive monocyte infiltration into the dLN (381) and thus this innate immune pathway is directly relevant to the findings of both chapters 3 and 4. In addition, the robust increase in CD69 expression demonstrated in Chapter 3 (Figure 3.7) suggests type I IFNs are active in KEC-dLN (278,342,401,452,453). Consequently, the next chapter of this thesis focuses upon the mechanisms by which type I IFNs shape the inflammatory milieu within the KEC-draining lymph node.

179

5 Investigations of Type I Interferons in the Draining Lymph Node

5.1 Abstract

The preceding chapters of this thesis have demonstrated that skin challenge with killed E. coli (KEC) induces an acute infiltrate of inflammatory myeloid cells into the draining lymph node and that these cells are potential sources of inflammatory prostanoids. The marked expression of prostanoid synthases exhibited by these cells suggests that they also drive other innate immune pathways in the dLN. It is increasingly recognised that type I interferons (IFNs) play an important role in driving innate and adaptive immune processes in the draining lymph node. Moreover, E. coli challenges are known to induce to type 1 interferon responses. This chapter therefore sought to explore the relationship between neutrophils and monocytes and type I IFN in the draining lymph node following challenge with KEC. In particular, the potential role played by type I interferons in driving cellular infiltration, activation and IFNγ production in the dLN were investigated using tandem cell sort and qRT-PCR, in vitro stimulation assays and mice deficient for the interferon-alpha/beta receptor (IFNAR).

Challenge with KEC induced robust type I IFN gene signature in the dLN. This consisted of increased expression of both the classic interferon stimulated genes Ifit1, Ifit2, Ifit3 and Cd69 as well as inflammatory mediators known to be associated with type I interferon responses; namely IFNγ, CCL2, CXCL9, CXCL10, NLRP3 and IL-1β. Infiltrating neutrophils and monocytes shared this type I IFN gene signature and were the major expressers of these interferon- associated inflammatory genes the draining lymph node, with the notable exception of IFNγ, which was predominantly produced by NK cells in the dLN. In contrast to previous studies of viral inflammation, monocyte recruitment to the draining lymph node was unaltered in IFNAR- deficient mice. However, these IFNAR-deficient mice exhibited defective production of IFNγ relative to wild-type mice following challenge with KEC, demonstrating that type I IFN are non- redundant for the production of IFNγ in vivo. However, in vitro experiments demonstrated that type I IFN are neither sufficient nor necessary to drive IFNγ production by lymphoid cell suspensions. Rather, the in vitro production of IFNγ was positively correlated with the frequency of monocytes in the cell suspension. Together, these results suggest that both type I IFN and monocytes synergistically drive the production of IFNγ in the KEC-draining lymph node. This suggests that monocytes orchestrate type I IFN responses within the dLN.

180

5.2 Introduction

5.2.1 Overview of type I interferons In 1957, Isaacs and Lindenmann demonstrated that tissues stimulated with heat-inactivated influenza virus produced a soluble factor that interfered with viral replication; accordingly they named this factor interferon (IFN) (598). Three classes of interferons have since been described; type I (interferons α, β, ε, κ, ω), type II (interferon γ) and type III (interferon λ) (599,600). These three types of IFN agonise distinct receptors; the interferon αβ receptor (IFNAR), the interferon γ receptor and the interferon λ receptor respectively (599,600). The agonism of IFNAR by type I IFNs results in the increased expression of hundreds of genes, termed interferon-stimulated genes (ISGs) (600,601). IFNAR agonism drives ISG expression via multiple signalling pathways (including JAK-STAT (600,602,603) and p38 MAP kinase (604) pathways) which initiate chromatin remodelling (604–606) and the binding of transcription factors to regulatory regions of ISGs (600,607).

Type I IFNs bestow protection against numerous pathogens, particularly viruses. This is demonstrable by the fact that IFNAR-deficient mice exhibit impaired control of viral (608) and bacterial (609) pathogens. Similarly, defects in type I IFN production or signalling predispose humans to viral infections (610,611). Type I IFNs exert this protective effect by a variety of mechanisms. Many ISGs encode protein products that directly limit viral replication within host cells by mechanisms such as translational inhibition (601,612,613). In addition to these cell- intrinsic effects, type I IFNs also modulate the wider immune response through the recruitment and activation of effector immune cells (307,395,466,614,615) and the optimal development of adaptive immune responses (270,279,616). However, it must be noted that type I IFNs can also have deleterious effects. Indeed, type I IFNs are associated with the impaired control of mycobacterial infections (617–619) and in excess can cause immunopathology (620) and autoimmune responses (621).

5.2.2 Type I interferons and lymph node barrier function

Type I IFNs bolster the barrier function of the draining lymph node (dLN) by multiple mechanisms. The rapid production of type I IFNs by lymph node resident macrophages is a feature of viral inflammation (147,170,171). In the context of vesicular stomatitis virus (VSV) infection, this rapid IFN production is essential to prevent the fatal dissemination of VSV to the central nervous system via neurons in the dLN (147,170). Type I IFNs are also an important driver of CXCL9, CXCL10 (70,329) and IFNγ (172,279,466) expression; processes known to

181

restrict the replication and dissemination of viral and bacterial pathogens within and from the dLN (72,307,329) and peripheral tissues (466,622). In addition, the recruitment and activation of monocytes has been shown to be a major mechanism by which type I IFNs control viral infections in peripheral tissues (395,466,467). This is particularly notable in the context of this thesis, as Sammicheli et al have demonstrated that monocyte infiltration into the dLN is completely dependent upon type I IFNs in the context of LCMV infection (381). Furthermore, there is evidence that type I IFNs promote lymphocyte effector functions, as they have been shown to potentiate early antibody production in the mediastinal lymph nodes of influenza- infected mice (401). Finally, Loo et al have demonstrated that type I IFNs restrict the drainage of free virus to the dLN through the remodelling of afferent lymphatic vessels (53). It is thus clear that type I IFN regulate numerous effector mechanisms that limit pathogen dissemination from the dLN.

5.2.3 Type I interferons and the developing adaptive immune response

Numerous studies have demonstrated that type I IFNs can potentiate adaptive immune responses. This includes studies that show reduced T cell priming in the context of IFNAR antagonism or deletion (270,279,616) and increased T cell priming and antibody titres when recombinant IFNα or IFNβ is administered as an adjuvant (171,270,623). Nevertheless, it must be noted that type I IFNs are not a pre-requisite for adaptive immune responses, as some adjuvants have been shown to potentiate adaptive immune responses in a type I IFN independent manner (274).

How type I IFNs potentiate adaptive immune responses is not clear, but several mechanisms have been implicated. The abrogation of IFNAR-driven inflammation can reduce antigen uptake by dendritic cells (270) and impair their maturation (171,616), which could impair the capacity to present antigen. The fact that type I IFNs increase the capacity of dendritic cells to cross-present antigen is also notable in this regard (623–625). With regard to processes known to be driven by type I IFNs in the dLN, it is notable that the IFN-driven production of IL-18, IFNγ and CXCR3 ligands have all been shown to promote th1-biased T –cell responses (241,247,278). Moreover, the CD69-induced retention of lymphocytes (84,342,626) may increase the likelihood of lymphocytes encountering cognate antigen (Section 6.2.2.3). The fact that type I IFNs exhibit such pleiotropic effects on the dLN make it difficult to discern which mechanisms are most important for the developing adaptive immune response. It is thus

182

important to develop an integrated understanding of the many ways in which type I IFNs act in the dLN.

5.2.4 Mechanisms of type I interferon-driven inflammation in the draining lymph node It is clear from the preceding sections that type I IFNs are cardinal inflammatory cytokines implicated in numerous important functions of the dLN during acute inflammation. This chapter of the thesis focuses on investigating the type I IFN response in the KEC-draining LN in the context of three IFN-driven processes that are pertinent to lymph node biology; namely chemokine production, monocyte infiltration, inflammasome activation and IFNγ expression. These processes have only previously been separately studied in varies models of inflammation and thus this chapter aims to both deepen current understanding of these processes and suggest mechanisms by which they interact and synergise to promote the barrier and/or adaptive functions of the dLN.

5.2.4.1 Chemokine production in the draining lymph node Numerous studies have demonstrated that various inflammatory stimuli rapidly increase the production of chemokines in the dLN (70,171,247,266,328,329). Type I IFNs are known to contribute to this phenomenon as they have been shown to drive production of the CXCR3 ligands CXCL9 and CXCL10 (70,329). These chemokines rapidly recruit memory CD8 T cells to the medullary and interfollicular regions of the dLN to bolster its innate barrier function in a process that has been termed ‘peripheralisation’ (70,329). In addition, as discussed in Section 5.2.2, Sammichelli et al have demonstrated that type I IFNs are required for the infiltration of monocytes into the dLN following challenge with LCMV (381). This is likely secondary to type I IFN-driven chemokine production as monocyte entry into the dLN is CCR2-dependent (205,242,369,370,381) and type I IFNs are known to induce expression of the CCR2 ligand CCL2 in other tissues (466–470). However, it is unclear whether IFN-driven monocyte infiltration into the dLN by Sammicheli et al (381) is specific to LCMV or extends to other inflammatory stimuli. Type I IFNs can therefore direct both the recruitment of cells to the dLN and their positioning within the dLN; although the mechanisms by which type I IFNs regulate these processes have not been fully delineated.

The mechanisms by which type I IFNs increase chemokine production are only partially understood. Indeed, type I IFN can both directly and indirectly stimulate chemokine production. For example, whilst type I IFN directly induce the expression of CXCL10, they 183

indirectly induce the expression of CXCL9 via the production of IFNγ (329,627). However, the cell types upon which type I IFNs act to induce chemokine production are unclear. Several studies implicate lymph node resident macrophages as sources of chemokines in the dLN (171,266,328). These findings are based on the depletion of said macrophages, a methodology which does not directly show chemokine production by macrophages and fails to account for chemokine production by cells recruited by LN-resident macrophages. In this regard, it is notable that infiltrating CD11b+ve GR-1+ve cells (329) and dendritic cells (247) have been shown to express CXCL9 and CXCL10 in the dLN. With regards to the former, CD11b+ve GR-1+ve cells encompass both neutrophils and monocytes, which as shown in Chapter 3, infiltrate the dLN following challenge with KEC. Thus, in addition to determining whether or not type I IFNs recruit monocytes to the KEC-draining LN, it is pertinent to question whether or not they stimulate infiltrating neutrophils and monocytes to express CXCL9 and CXCL10.

5.2.4.2 Inflammasome activation within the draining lymph node Inflammasomes are multi-protein complexes that post-transcriptionally regulate the production of IL-1β and IL-18 by cleavage of pro-IL-1β and pro-IL-18 (628–630). These complexes consist of an NLR protein, an ASC adaptor protein and caspase-1 and they rapidly assemble in the cytoplasm in response to a wide variety of inflammatory stimuli (628,631,632). Evidence of increased inflammasome activation within the dLN has been reported following challenge with P. aeruginosa, S. typhimurium, Modified Vaccinia Ankara, and the TLR-4 adjuvant GLA-SE (72,266,278,328). Moreover, inflammasomes have been shown to contribute to important processes within the dLN, including the recruitment of neutrophils, monocytes, NK cells and circulating lymphocytes, thereby limiting the dissemination of pathogens from the dLN and potentiating the developing T cell response (72,328).

Given the importance of both inflammasomes and type I IFNs (Sections 5.2.2 and 5.2.3) in the dLN, it is pertinent to explore how these two inflammatory pathways intersect in this context. There is evidence that type I IFNs drive inflammasome activation in other contexts. For example, type I IFNs are required for the production of IL-1β and IL-18 following in vitro stimulation of myeloid cells with S. pneumoniae (593), F. tularensis (594), L. monocytogenes (594) and E. coli (595). Moreover, these findings have been replicated in vivo in the context of S. pneumoniae and E. coli infections (593,595). However, type I IFNs have also been shown to have a negative impact on inflammasome activity in other contexts (633,634). The effect of IFNs on inflammasomes is therefore a complex context-dependent question that has not yet been applied to the dLN. Inflammasome activity is regulated at both the transcriptional and

184

post-transcriptional level (72,635–639) and both may be subject to regulation by type I IFN (595,633,634). Moreover, the cellular effectors of the inflammasome activity in the dLN have not been fully characterised. Evidence of inflammasome activity has been shown in lymph node resident macrophages (72,328) but no other cells have yet been implicated. The prominent monocyte influx described in Chapter 3 (Figure 3.9) is significant in this regard as type I IFN-driven inflammasome activity has been demonstrated in monocytes in HSV-infected vaginal tissue (466). This chapter seeks to explore the relationship between type I IFNs and inflammasomes in the dLN in terms of whole-lymph node and cell-specific gene expression.

5.2.4.3 IFNγ in the draining lymph node The rapid production of IFNγ in the dLN is a prominent feature of numerous models of inflammation, including challenge with P. aeruginosa (72), S. typhimurium (72,90), vaccinia virus (172,307), LPS-matured dendritic cells (241), and various adjuvants (241,277–279). Various cell types contribute to this process, including neutrophils (278), CD8 T cells (72,278,279), γδ T cells (72) NKT (72) and NK cells (72,241,279). With regards to function, IFNγ has been shown to be important in both innate and adaptive immune responses in the dLN. Kastenmüller et al have illustrated that IFNγ-producing cells are predominantly localised in close proximity to the lymphatic sinuses and that IFNγ is required for the rapid control of bacterial replication within and prevention of dissemination from the dLN (72). Furthermore, IFNγ produced by infiltrating NK cells has been shown to be critical for the induction of Th1 differentiation (241). The mechanisms by which IFNγ exerts these functions in the dLN are unclear but it is notable that IFNγ is known to potently induce expression of the CXCR3 ligand CXCL9 (70,329,627) and thereby may serve to recruit as well as activate innate and adaptive immune cells in the dLN.

Type I IFNs are known to be a driver of acute IFNγ production in various contexts (172,279,466,592), including the dLN (172,279). However, the mechanisms by which type I IFNs drive IFNγ production have not been delineated. Type I IFN may directly target cells capable of IFNγ expression such as NK cells (592) but there is evidence to suggest that type I IFNs indirectly induce IFNγ production by the stimulation of accessory cell type that then induces the expression of IFNγ in the target cell (466,640). This accessory cell could be any one of a range of dLN cells and there is evidence that NK cell IFNγ production can be induced by cell-cell interactions with migratory dendritic cells via NKG2D (357). Furthermore, given the substantial influx of monocytes into the KEC-draining LN (Chapter 3), it is notable that monocytes stimulated by type I IFN have been shown to drive IFNγ expression by NK cells in a

185

mucosal herpes simplex virus (HSV) infection (466). Whether this inflammatory pathway extends to the dLN is not known. As type I IFNs can also drive monocyte infiltration (381,395,466,467), it is pertinent to question whether type I IFNs drive the production of IFNγ via the recruitment and/or stimulation of monocytes within the dLN.

5.2.5 Summary

Chapter 3 of this thesis demonstrated that the skin injection of killed E. coli induces an acute infiltrate of inflammatory myeloid cells into the dLN. Type I IFNs are known to be important in shaping the inflammatory milieu that develops acutely in the dLN following challenge with various stimuli. E. coli challenges are known to induce type I IFN responses and Figure 3.7 demonstrates that KEC induces upregulation of the CD69, a well-recognised marker of stimulation with type I IFNs. This chapter therefore sought to explore the expression and functions of type I IFNs in the dLN following challenge with killed E. coli (KEC). Whilst numerous studies have determined roles for type I IFNs in driving various inflammatory processes within the dLN, these IFN-driven pathways tend to be studied in isolation and the cellular effectors of type I IFN stimulation remain uncharacterised. This chapter therefore seeks to specifically address several aims. Firstly, IFNAR-deficient mice are used to determine whether or not type I IFNs are required for the infiltration of monocytes into the dLN as has been described in other tissues. Secondly, RNA extracts generated from whole lymph node cell suspensions and FACS- isolated cell subsets are utilised to both characterise the kinetics and cellular sources of type I IFN production in the dLN and characterise the cellular targets of type I IFNs. More specifically, these methods are utilised to characterise gene expression in the context of three major type I IFN associated inflammatory pathways: (1) intranodal cell migration driven by the CXCR3 ligands CXCL9 and CXCL10, (2) activation of the inflammasome and (3) the production of IFNγ. The overall aim of this chapter is therefore to identify connections between these type I IFN- driven processes and infiltrating myeloid cells in order to develop a deeper understanding of the overall mechanisms and functions of type I IFNs in the dLN.

186

5.2.6 Aims

• Characterise expression of the classic interferon-stimulated genes Ifit1, Ifit2, Ifit3 and Cd69 in the KEC-draining lymph node.

• Determine whether or not mice deficient for the interferon αβ receptor exhibit defects in the recruitment of monocytes to the draining lymph node following challenge with KEC.

• Characterise the expression of the following interferon-associated inflammatory mediators in the KEC-draining lymph node; the chemokines CCL2, CXCL9 and CXCL10, the inflammasome components IL-1β, IL-18, NLRP3 and Aim2 and the cardinal cytokine IFNγ

• Determine the expression of these interferon-associated genes among neutrophils and monocytes infiltrating the draining lymph node relative to other cells in the draining lymph node

• Determine whether or not mice deficient for the interferon αβ receptor exhibit defects in the acute expression of IFNγ

• Determine whether or not type I interferons are necessary or sufficient to drive the production of IFNγ by lymph node cell suspensions in vitro.

187

5.3 Results

5.3.1 The expression of type I interferon-stimulated genes (ISGs) is increased in the KEC-draining lymph node

Type I interferons (IFNs) are known to be important cytokines in the context of E. coli infections (609). Moreover, type I IFNs are a known driver of CD69 expression on lymphocytes (278,342,401,452,453) and it is thus notable that increased CD69 expression was exhibited by lymphocytes within the dLNs of mice injected with killed E. coli in Chapter 3 (Figure 3.7). Coro and Chang et al (401,641) have illustrated that influenza infection induces a robust type I IFN- dependent transcriptional signature in the dLN, which includes marked increases in the expression of the genes encoding IFIT1, IFIT2 and IFIT3. Figure 5.1 illustrates that not only does the skin injection of killed E. coli (KEC) induce increased expression of CD69 on the cell surface of lymph node lymphocytes (Figures 5.1A-C); it also increases transcription of the genes encoding CD69, IFIT1, IFIT2 and IFIT3 in the dLN (Figure 5.1D). These increases were most marked at 6- and 24-hours following injection (Figure 5.1D). An additional curious feature of these results is that CD69 was upregulated to a greater extent by B cells than T cells in the dLN (Figures 5.1B-C). This differential pattern of CD69 expression is discussed in detail in Chapter 6 of this thesis. Overall, the data presented in Figure 5.1 strongly suggest that the injection of killed E. coli elicits a type I IFN response within the dLN.

5.3.2 IFNAR-deficient mice exhibit no defect in monocyte infiltration into the KEC-draining lymph node Type I IFNs are necessary for monocyte infiltration into peripheral tissues in a variety of contexts (395,466,467), including the dLN during LCMV infection (381). There is also evidence to suggest that type I IFNs suppress neutrophil infiltration (467,642) and promote NK cell infiltration (241,307). It was thus hypothesised that type I IFNs modulate the infiltration of these cell subsets into the KEC-draining LN. Sammicheli et al have previously shown that deletion of IFNAR results in a near-total ablation of monocyte infiltration into the dLN (381) and thus a sample size of 5-6 mice per group at two time points (6 and 12 hours) was deemed sufficient to replicate this finding in the context of challenge with KEC. Unexpectedly, flow cytometry revealed no differences in the percentage or number of monocytes in the dLNs of wild-type and IFNAR-deficient mice at 6 and 12 hours following the skin injection of KEC (Figure 5.2A and 5.2B). Moreover, no differences were observed in the number or percentage of neutrophils or NK cells in these dLNs (Figures 5.2C and 5.2D). These results therefore

188

suggest that type I IFNs are redundant for the rapid infiltration of neutrophils, monocytes and NK cells into the KEC-draining LN.

Figure 5.1: Increased expression of type I interferon-stimulated genes (ISGs) in the KEC-draining lymph node (A) Percentage of lymph node B and T cells that are CD69-positive 6 hours following injection of killed E. coli (KEC). (B-C) CD69 expression exhibited by paired B and T cells from the same draining lymph node either (B) 6 hours or (C) 3 hours following injection of killed E. coli. N.B. (C) represents data pooled from experiments presented in chapter 3. (D) Expression of the genes encoding CD69, IFIT1, IFIT2 and IFIT3 in the draining lymph node 6, 24- and 48-hours following injection of KEC. Sample sizes: (A-B) n = 4 x CTRL LN, 4 x 6hr LN. (C) n = 13 x 3hr LN (D) n = 6 x CTRL LN, 4 x 6hr LN, 4 x 24hr LN, 4 x 48hr LN. NC3Rs: 40 mice in total. CTRL: control and contralateral LN, Ipsi: ipsilateral, LN: lymph node. (A and D) The Mann-Whitney U test was used to determine statistical significance. *p<0.05 **p<0.01 relative to CTRL LN. (C) The Wilcoxon matched pairs test was used to test for statistical significance as these are paired analyses respectively, ***p = 0.002.

189

Figure 5.2: The infiltration of neutrophils and monocytes is unimpaired in the KEC-draining lymph nodes of IFNAR-deficient mice (A) Representative flow cytometry dot plot depicting the neutrophil (Ly6C+ve Ly6G+ve) and monocyte (Ly6Chi Ly6Glo) populations present in the draining lymph nodes of IFNAR-deficient mice 6 hours following the skin injection of KEC. (B and C) The percentage (left) and number (right) of (B) monocytes (C) neutrophils and (D) NK cells in the draining lymph nodes of wild-type and IFNAR-deficient mice 6- and 12-hours following injection of KEC. Sample sizes: n = 15 x WT CTRL LN, 15 x KO CTRL LN, 5 x 6hr WT LN, 5 x 12hr WT LN, 6 x 6hr KO LN, 6 x 12hr KO LN. NC3Rs: 24 mice in total (1 x WT 6hr LN and 1 x WT 12hr LN excluded due to a lack of response).CTRL: contralateral and inguinal LN, KEC: killed E. coli, LN: lymph node, KO: knockout (IFNAR-deficient), IFNAR: interferon αβ Receptor, WT: wild-type. The Mann Whitney U test was used to test for statistical significance, # P<0.05 relative to respective CTRL LN.

190

5.3.3 Neutrophils and monocytes infiltrating the KEC-draining lymph node exhibit increased expression of interferon-stimulated genes (ISGs)

As type I IFNs are redundant for the infiltration of neutrophils and monocytes into the KEC- draining lymph node (Figures 5.2A-C), it is pertinent to question whether type I IFNs exert any influence upon these cells in the dLN. Figures 5.3A and 5.3B demonstrate that infiltrating neutrophils and monocytes exhibit increased expression of the ISGs Ifit1, Ifit2, Ifit3 and Cd69 relative to splenic neutrophils and monocytes and therefore share the type I IFN gene expression signature exhibited by the dLN as a whole (Figure 5.1). That these changes in gene expression are indeed driven by type I IFNs is validated by the significantly reduced expression of CD69 exhibited by neutrophils and monocytes infiltrating the dLNs of IFNAR-deficient mice (Figure 5.3C). Thus, type I IFNs stimulate neutrophils and monocytes to upregulate expression of interferon-stimulated genes (ISGs) in the KEC-draining LN.

5.3.4 The genes encoding type I interferons are not significantly expressed in the KEC-draining lymph node

In light of the increased expression of ISGs and the interferon-dependent expression of CD69 in the KEC-draining LN (Figures 5.1A-D and 5.3A-C), qRT-PCR was used to determine whether or not the transcription of type I IFNs is increased in the dLN at 3-, 6- and 12- hours following skin injection of killed E. coli. This was achieved using 4 primers that together were capable of amplifying mRNA encoding 14 different subtypes of interferon-alpha (IFNα) and the mRNA encoding the single subtype of interferon-beta (IFNβ). Figures 5.4A-D illustrate that no increase in the expression of either IFNα or IFNβ was detectable in the dLN at 3-, 6- or 12- hours following injection of KEC, with the exception of a small and variable increase in IFNβ expression was observed at 12 hours (Figure 5.4D). A tandem cell sort and qPCR analysis (outlined in Figure 5.4E) was used to identify the cells responsible for the small increase in IFNβ expression observed at 12 hours. Figure 5.4F demonstrates a small increase in IFNα4 and IFNβ expression among lymph node neutrophils and monocytes relative to other lymph node cells. However, lymph node neutrophils exhibited no increase in IFNα4 or IFNβ expression

26 relative to splenic neutrophils (Figure 5.4G), whilst lymph node monocytes exhibited only a

27 small increase in IFNα4 and IFNβ expression relative to splenic monocytes (Figure 5.4H). In summary, despite the marked effect of type I IFNs in the expression of CD69 and other classical ISGs, there was no robust increase in their expression in the dLN.

26 Neutrophils isolated from the spleens of mice injected into the earflap with KEC. 27 Monocytes isolated from the spleens of mice injected into the earflap with KEC. 191

Figure 5.3: Neutrophils and monocytes infiltrating the KEC-draining lymph node exhibit increased expression of interferon-stimulated genes (ISGs) Expression of the ISGs Cd69, Ifit1, Ifit2, Ifit3 by (A) neutrophils and (B) monocytes isolated from the draining lymph node 12 hours following injection of KEC. (C) The median fluorescence intensity of CD69 on neutrophils and monocytes infiltrating the draining lymph nodes of wild-type and IFNAR- deficient mice 6 and 12 hours following the skin injection of KEC. Sample sizes: (A) n = 4 x 12hr LN neutrophil samples, 4 x 12hr SPL neutrophil samples (B) n = 4 x 12hr LN monocyte samples , 4 x 12hr SPL monocyte samples (C) n = 3 x 6hr WT LN neutrophils/monocytes, 4 x 6hr KO LN neutrophils/monocytes, 5 x 12hr WT LN neutrophils/monocytes, 6 x KO 12hr LN neutrophils/monocytes. The Mann Whitney U test was used to test for statistical significance, *P<0.05, **P<0.01, # P<0.01 relative to respective (i.e. WT or KO) SPL. ISG: interferon-stimulated Gene, LN: lymph node, SPL: spleen, WT: wild-type, KEC: killed E. coli, KO: knockout (IFNAR-deficient), IFNAR: interferon αβ receptor, MFI: median fluorescence intensity. NC3Rs: 34 mice in total. N.B. lymph nodes from 4 mice pooled for each data point in A and B.

192

Figure 5.4: The expression of type I interferons is not marked in the KEC-draining lymph node (A-D) Expression of the genes encoding (A) 14 IFNα subtypes, (B) IFNα4 (C) IFNα6 and (D) IFNβ in the draining lymph node 3, 6- and 12-hours following injection of 1.5 x 107 killed E. coli (KEC). (E) Cell populations isolated by fluorescence-activated cell sorting from the draining lymph node and spleen 12 hours following injection of KEC and (F-H) their relative expression of IFNα4 and IFNβ. Sample sizes: (A-D) left graph: n = 4 x CTRL LN, 3 x 3hr LN, right graph n = 4 x CTRL LN, 4 x 6hr LN and 4 x 12hr LN. (E-H) n = 4 x 12hr LN neut samples, 4 x 12hr LN mono samples, 4 x 12hr LN other samples, 4 x 12hr LN CD11b-ve samples, 4 x 12hr SPL neut samples, 4 x 12hr SPL mono samples. NC3Rs: 28 mice in total (LN had to be pooled from 4 mice to generate LN neut samples). LN: lymph node, SPL: spleen, WT: wild-type, neut: neutrophil, mono: monocyte. Other: other CD11b+ve cells. The Mann-Whitney U test was used to test for statistical significance. *p<0.05 relative to CTRL LN. The sample highlighted in red in (F)is contaminated as described in Section 5.4.2. 193

5.3.5 Neutrophils and monocytes infiltrating the KEC-draining lymph node exhibit increased expression of the interferon-induced chemokines CXCL9 and CXCL10 Type I IFNs have been shown to drive production of the chemokines CXCL9 and CXCL10, a process that induces the rapid CXCR3-dependent migration of effector and memory T cells to peripheral regions of the dLN (70,329). As the KEC-draining LN exhibits a strong type I IFN gene expression signature (Figure 5.1), it was hypothesised that the expression of CXCL9 and CXCL10 would be similarly increased. This is confirmed in Figures 5.5A and 5.5B, which demonstrate that the expression of CXCL9 and CXCL10 is substantially increased at 3-, 6- and 12- hours following injection of heat-killed E. coli. Given the particularly strong expression of other ISGs exhibited by neutrophils and monocytes infiltrating the dLN, it was hypothesised that these cells may express CXCL9 and CXCL10 to a greater degree than other cells of the dLN. This hypothesis was tested using tandem FACS and qRT-PCR of the dLN at 12 hours following challenge (outlined in Figure 5.5C). This identified neutrophils and monocytes as major expressers of these chemokines in the dLN and further demonstrated that lymph node neutrophils and monocytes exhibited substantially increased expression of these chemokines relative to splenic neutrophils and monocytes (Figures 5.5D and 5.5E). These findings strongly suggest neutrophils and monocytes are major producers of CXCL9 and CXCL10 in the KEC- draining lymph node and that these cells induce the production of these chemokines following stimulation by type I IFNs within the dLN.

In addition to the observed increase in CXCL9 and CXCL10 transcription, Figure 5.5 provides evidence that these chemokines are active in the draining LN. This is because CD8+ve T cells and NK cells within KEC-draining lymph nodes exhibit CXCR3 downregulation relative to their counterparts in control lymph nodes (Figures 5.5F and 5.5G). This is consistent with agonist- induced internalisation of CXCR3 by CXCL9 and CXCL10 (643). In summary, these findings strongly suggest that IFN-stimulated neutrophils and monocytes produce CXCL9 and CXCL10 and thereby influence the migratory behaviour of CD8 T cells and NK cells within the KEC- draining LN.

194

195

Figure 5.5: Increased expression of CXCL9 and CXCL10 in the KEC-draining lymph node (A-B) Expression of the genes encoding (A) CXCL9 and (B) CXCL10 in the draining lymph node 3, 6- and 12- hours following injection of killed E. coli (KEC). (C-E) Expression of the gene encoding CXCL9 and CXCL10 by cell populations isolated from the draining lymph node 12 hours following injection of KEC with additional comparisons against splenic neutrophils and monocytes; (C) representative dot plot of cell population, (D) CXCL9 and (E) CXCL10. (F) Percentage of CD8 T cells that are CXCR3+ve in control and 12 hour KEC-draining LN and the CXCR3 MFI exhibited by CXCR3+ve CD8 T cells in control and 12 hour KEC-draining LN. (G) CXCR3 MFI exhibited by NK cells in control and 12 hour KEC-draining LN Sample sizes: (A) n = 4 x Con LN and 3 x 3hr LN, (B) n = 4 x Con LN, 4 x 6hr LN and 4x 12hr LN. 4 x 3hr, 4 x 6hr, 4 x 12hr. (C-E) n = 4 x 12hr LN neut samples, 4 x 12hr LN mono samples, 4 x 12hr LN OTH samples, 4 x 12hr LN CD11b-ve samples, 4 x 12hr SPL neut samples, 4 x 12hr SPL mono samples. (F and G) n = 6 x CTRL LN and 4 x 12hr LN. NC3Rs: 34 mice in total. LN: lymph node, SPL: spleen, Ipsi: ipsilateral, Con: contralateral, CTRL: control and contralateral LN, neut: neutrophil, mono: monocytes, other: other CD11b+ve cells, NK: natural killer cells, MFI: median fluorescence intensity. The Mann-Whitney U test was used to determine statistical significance. *p<0.05, **p<0.01 relative to contralateral or CTRL LN respectively. One 3hr ipsilateral lymph node sample was excluded due to contamination with genomic DNA. The sample highlighted in red in (D) and (E) is contaminated as described in Section 5.4.2.

5.3.6 Neutrophils and monocytes infiltrating the KEC-draining lymph node exhibit increased expression of the interferon-induced chemokine CCL2

Another chemokine that is known to be induced by type I IFNs is CCL2 (466–470). CCL2 is a ligand for CCR2, which is the major chemokine receptor responsible for monocyte infiltration into the dLN (205,242,369,370,381). Several studies have reported increased levels of CCL2 in the dLN acutely following immunisation/infection (171,328,369,375) and CCL2 is thought to be instrumental in the process of monocyte infiltration into the dLN (205,325). It is clear from Figure 5.2B that type I IFNs are redundant for the infiltration of monocytes into the KEC- draining and it was therefore questioned whether or not the expression of CCL2 is increased in the KEC-draining LN. Figure 5.6A demonstrates that the expression of CCL2 is increased in the dLN at 3-, 6- and 12- hours following injection of heat-killed E. coli. The increased expression observed at 3 hours is particularly pertinent as this precedes the peak of monocyte infiltration (Figure 3.9). Tandem FACS and qRT-PCR was subsequently utilised to determine the cellular sources of CCL2 in the dLN (strategy outlined in Figure 5.6B). This illustrated that neutrophils and monocytes are the major expressers of CCL2 in the draining lymph 12 hours following injection of KEC (Figure 5.6C). Moreover, these dLN neutrophils and monocytes exhibit substantially greater expression of CCL2 than their splenic counterparts (Figure 5.6C). Thus, despite the redundancy of type I IFNs for the infiltration of monocytes into the dLN, challenge with KEC does induce increased expression of CCL2, particularly within neutrophils and monocytes infiltrating the dLN.

196

Figure 5.6: CCL2 expression is increased in the KEC-draining lymph node (A) Expression of the gene encoding CCL2 in the draining lymph node at 3, 6- and 12-hours following injection of 1.5 x 107 killed E. coli (KEC). (B) Cell populations isolated from the draining lymph node 12 hours following injection of KEC. (C) Expression of CCL2 by neutrophils and monocytes isolated from the draining lymph node or spleen 12 hours following injection of KEC. Sample sizes: (A) left graph: n = 4 x CTRL LN, 3 x 3hr LN, right graph n = 4 x CTRL LN, 4 x 6hr LN and 4 x 12hr LN. (B-C) n = 4 x 12hr LN neut samples, 4 x 12hr LN mono samples, 4 x 12hr LN other samples, 4 x 12hr LN CD11b-ve samples, 4 x 12hr SPL neut samples, 4 x 12hr SPL mono samples. NC3Rs: 28 mice in total (LN had to be pooled from 4 mice to generate LN Neut samples). LN: lymph node, SPL: spleen, Neut: neutrophils, Mono: monocytes, Other: other CD11b+ve cells. The Mann-Whitney U test was used to determine statistical significance. *p<0.05 relative to contralateral LN. The sample highlighted in red in (C) is contaminated as described in Section 5.4.2.

197

5.3.7 Neutrophils and monocytes infiltrating the KEC-draining lymph node exhibit increased expression of the inflammasome components NLRP3, pro-IL-1β and pro-IL-18 Evidence of increased inflammasome activation within the dLN has been reported following challenge with P. aeruginosa, S. typhimurium, Modified Vaccinia Ankara, and the TLR-4 adjuvant GLA-SE (72,266,278,328). Inflammasomes are multi-protein complexes that consist of an NLR protein, an ASC adaptor protein and caspase-1 and they rapidly assemble in the cytoplasm in response to a wide variety of inflammatory stimuli (628,631,632). Inflammasomes post-transcriptionally regulate the production of IL-1β and IL-18 by cleavage of pro-IL-1β and pro-IL-18 (628–630). IL-1β production is also regulated at the level of transcription and TLR stimuli such as LPS can increase pro-IL-1β expression via NFκB signalling (635–638). In addition, there is evidence that type I IFNs can drive inflammasome activity in other tissues (593,595), including in the context of challenge with E .coli (595). qRT-PCR was therefore utilised to profile the expression of major inflammasome components in the KEC- draining lymph node, namely the NLR proteins NLRP3 and AIM2, as well the genes encoding the pro-forms of IL-1β and IL-18. Figures 5.7A and 5.7C demonstrate that expression of the genes encoding pro-IL-1β and NLRP3 were significantly increased in the dLN 3-, 6- and 12- hours following injection of KEC. In contrast, the expression of pro-IL-18 was only mildly increased at 3-, 6- and 12- hours following injection (Figure 5.7B) and the expression of AIM2, was not increased (Figure 5.7D). Furthermore, tandem FACS and qRT-PCR demonstrated that neutrophils and monocytes exhibit greater expression of NLRP3, IL-1β and IL-18 relative to other cells in the 12-hour dLN as well as their splenic counterparts (Figures 5.7E-H). Overall, these data suggest that IL-1β and IL-18 (to a lesser extent) are rapidly produced in the KEC- draining lymph node by infiltrating neutrophils and monocytes bearing NLRP3 inflammasomes.

198

199

Figure 5.7: Increased expression of inflammasome components by neutrophils and monocytes infiltrating the KEC-draining lymph node Expression of the genes encoding (A) IL-1β, (B) IL-18, (C) NLRP3 and (D) AIM2 in the draining lymph node 3 (A and B only), 6- and 12-hours following injection of 1.5 x 107 killed E. coli (KEC). (E-H) Expression of the genes encoding (F) NLRP3, (G) IL-1β and (H) IL-18 by cell populations isolated from the draining lymph node or spleen 12 hours following injection of killed E. coli (KEC). Sample sizes: (A-D) left graph: n = 4 x CTRL LN, 3 x 3hr LN, right graph n = 4 x CTRL LN, 4 x 6hr LN and 4 x 12hr LN. (E-H) n = 4 x 12hr LN neut samples, 4 x 12hr LN mono samples, 4 x 12hr LN OTH samples, 4 x 12hr LN CD11b-ve samples, 4 x 12hr SPL neut samples, 4 x 12hr SPL mono samples. NC3Rs: 28 mice in total (LN had to be pooled from 4 mice to generate LN Neut samples). LN: lymph node, SPL: spleen, Ipsi: ipsilateral, Con: contralateral, CTRL: control and contralateral LN, neut: neutrophil, mono: monocytes, other: other CD11b+ve cells, NK: natural killer cells, MFI: median fluorescence intensity, hr: hour. The Mann-Whitney U test was used to determine statistical significance. *p<0.05 relative to contralateral lymph nodes. One 3hr ipsilateral lymph node sample was excluded due to contamination with genomic DNA

5.3.8 NK cells are the major expresser of IFNγ in the KEC-draining lymph node

The rapid production of IFNγ in the dLN is feature of the inflammatory response induced by various stimuli (Section 5.2.4.3). qRT-PCR and tandem FACS + qRT-PCR were therefore utilised to determine whether KEC is another inflammatory stimulus capable of stimulating rapid IFNγ expression in the dLN. This analysis revealed that the expression of IFNγ is substantially increased as early as 3 hours following injection of KEC and remains elevated at both 6- and 12-hours following injection (Figure 5.8A). Moreover, tandem FACS and qRT-PCR analysis (Figure 5.8B) demonstrated that IFNγ expression was strongest within a population of CD11b+ve cells that were neither infiltrating neutrophils nor monocytes (although dLN neutrophils and monocytes did exhibit a small increase in IFNγ expression relative to their splenic counterparts) (Figure 5.8C). NK cells are known to express CD11b (644) and are a recognised source of intranodal IFNγ (72,241,278,279) and it was thus deemed likely that they were likely to represent the IFNγ-expressing population of CD11b+ve cells identified by tandem FACS + qRT- PCR. This was investigated via intracellular cytokine staining of cell suspensions generated from dLNs 12 hours following injection of KEC. Given the large differences in IFNγ expression described in Figure 5.8A, it was judged that 6 mice (4 x challenged and 2 x control) was sufficient to demonstrate these stark differences in IFNγ expression between draining and control and contralateral lymph nodes if they were translated to the protein level. Accordingly, dLNs exhibited a significantly higher percentage of IFNγ+ve cells relative to control and contralateral LN (Figure 5.9A and 5.9B). Moreover, this analysis demonstrated that CD11b+ve NK1.1+ve NK cells are the major expressers of IFNγ in the KEC-draining lymph node (Figures

200

5.9C-F). Altogether, these findings demonstrate the rapid expression of IFNγ by NK cells in the dLN 12 hours following skin challenge with KEC.

Figure 5.8: IFNγ expression is increased in the KEC-draining lymph node (A) Expression of the gene encoding IFNγ in the draining lymph node 3, 6- and 12-hours following injection of 1.5 x 107 killed E. coli (KEC). (B) Cell populations isolated from the draining lymph node and spleen by FACS. (C) Expression of gene encoding IFNγ by cell populations FACS-isolated from the draining lymph node or spleen 12 hours following injection of KEC. Sample sizes: (A) left graph: n = 4 x CTRL LN, 3 x 3hr LN, right graph n = 4 x CTRL LN, 4 x 6hr LN and 4 x 12hr LN. (B-C) n = 4 x 12hr LN neut samples, 4 x 12hr LN mono samples, 4 x 12hr LN other samples, 4 x 12hr LN CD11b-ve samples, 4 x 12hr SPL neut samples, 4 x 12hr SPL mono samples. NC3Rs: 28 mice in total (LN were pooled from 4 mice to generate LN Neut samples). LN: lymph node, SPL: spleen, Ipsi: ipsilateral, Con: contralateral, FACS: fluorescence-activated cell sorting, Neut: neutrophils, Mono: monocytes, Other = other CD11b+ve cells. The Mann-Whitney U test was used to determine statistical significance. *p<0.05 relative to contralateral LN. The sample highlighted in red in (B) is contaminated as described in Section 5.4.2.

201

Figure 5.9: CD11b+ve NK cells, neutrophils and monocytes express IFNγ protein in the KEC- draining lymph node Lymph nodes were harvested 12 hours following skin injection of KEC and analysed for intracellular IFNγ protein by flow cytometry. (A) Gating strategy for IFNγ+ve cells in the draining lymph node. (B) Percentage of lymph node cells that are IFNγ+ve. (C) Proportion of IFNγ+ve cells that are neutrophils, natural killer cells and monocytes. (D) Histogram illustrating the relative expression of IFNγ by IFNγ+ve neutrophils, monocytes and NK cells. (E) IFNγ MFI of IFNγ+ve neutrophils, monocytes and NK cells. (F) CD11b MFI of IFNγ+ve and IFNγ-ve NK cells. Sample sizes: n= 6 x CTRL LN and 4 x 12hr LN. NC3Rs: 6 mice in total. The Mann-Whitney U test was used to test for statistical significance. *p<0.05, **p<0.01 relative to CTRL LN. CTRL: control and contralateral LN, LN: lymph node, ipsi = ipsilateral, neut: neutrophils, mono: monocytes, NK: natural killer cells, MFI: median fluorescence intensity.

202

5.3.9 IFNγ production is impaired in the KEC-draining lymph nodes of IFNAR-deficient mice

As described in Figure 5.1, the KEC-draining lymph node exhibits increased expression of type I interferon-stimulated genes (ISGs). Type I IFNs have previously been shown to be a driver of acute IFNγ production (172,279,466,592). It was therefore hypothesised that type I IFNs drive the acute IFNγ production described in Figures 5.8 and 5.9. This hypothesis was tested using intracellular flow cytometry to compare IFNγ expression within the dLNs of IFNAR-deficient mice and wild-type mice challenged with KEC. Previous studies have demonstrated a complete ablation of IFNγ production in the context of IFNAR deletion or antagonism (172,279) and thus a sample size of 5-6 mice per group was deemed sufficient to demonstrate such a stark difference. Indeed, Figures 5.10A-C illustrate that the percentage of NK cells (Figure 5.10B) and CD8 T cells (Figure 5.10C) that were IFNγ+ve was significantly reduced in the dLNs of IFNAR- deficient mice relative to wild-type mice, although a small increase was still observed relative to non-draining LNs. This pattern was also evident in terms of the number of IFNγ+ve NK cells and CD8 T-cells in the dLNs of wild-type and IFNAR deficient mice (Figure 5.10D). These results therefore demonstrate that type I IFNs are a non-redundant requirement for the production of IFNγ in the KEC-draining lymph node.

Figure 5.10: IFNγ production is impaired in the KEC-draining lymph nodes of IFNAR-deficient mice (A) Representative flow cytometry dot plots for (B-C). (B-D) The percentage and number of IFNγ+ve (B, D) NK cells and (C, D) CD8+ve cells in the draining lymph nodes of wild-type and IFNAR-deficient mice 6 hours following the skin injection of KEC. Sample sizes: n = 9 x WT CTRL LN, 9 x KO CTRL LN, 5 x 6hr WT LN, 6 x 6hr KO LN. NC3Rs: 12 mice in total (1 x 12hr WT LN excluded due to lack of response). The Mann Whitney U test was used to test for statistical significance, **p<0.01, # p<0.05 relative to respective CTRL or KO LN. CTRL: contralateral and inguinal LN, KEC: killed E. coli, LN: lymph node, KO: knockout (IFNAR-deficient), IFNAR: interferon αβ receptor, WT: wild-type.

203

5.3.10 In vitro stimulation of lymphoid cell suspensions with KEC reveals increased IFNγ expression by NK cells within spleen cell suspensions relative to non-draining lymph node cell suspensions In light of the rapid IFNγ production observed in the dLN following skin challenge with KEC, it was questioned whether in vitro stimulation of non-draining LN cell suspensions with KEC would induce IFNγ production. This is pertinent because it would demonstrate that lymph node resident cells are sufficient to drive such IFNγ production and do not require infiltrating cells such as neutrophils and monocytes. Figure 5.11A demonstrates that 5.5 hours of in vitro stimulation with 7.5 x 107 KEC only elicited a small increase in the percentage of IFNγ+ve NK cells in the cell suspensions generated from non-draining LNs28. In contrast, in vitro stimulation of spleen cell suspensions with KEC elicits a substantial increase in the percentage of IFNγ+ve NK cells (Figure 5.11B). This suggests that KEC-driven IFNγ production is attributable to a cell type or factor present in spleen cell suspensions but not non-draining LN cell suspensions. This could represent neutrophils or monocytes for example.

Figure 5.11: In vitro stimulation of lymphoid cell suspensions with KEC elicits IFNγ expression by NK cells The percentage of IFNγ+ve NK cells within cell suspensions generated from (A) non-draining lymph nodes and (B) spleens following 5.5 hours of in vitro stimulation with 7.5. x 107 killed E. coli (KEC). Sample sizes: n = 5 x non-draining LN cell suspensions that were divided and cultured in the presence or absence of KEC (B) n = 4 x spleen cell suspensions cultured in the presence or absence of KEC. NC3Rs: 6 mice in total. LN: lymph node, SPL: spleen, KEC: killed E. coli, Unstim: unstimulated. The Mann Whitney U test was used to test for statistical significance, *p<0.05.

28 These consisted of cell suspensions generated from contralateral cervical lymph nodes as well as inguinal lymph nodes. 204

5.3.11 In vitro stimulation of lymphoid cell suspensions with IFNβ and/or IFNγ induces a small increase in IFNγ expression by NK cells

As the increased percentage of IFNγ+ve NK cells observed in the KEC-draining lymph node is largely dependent on IFNAR (Figure 5.10), it was questioned whether stimulation of lymphoid cell suspensions with IFNβ would be sufficient to induce IFNγ expression in vitro. This question was addressed by stimulating cell suspensions generated from non-draining LNs and spleens with 3000 units/ml IFNβ for 5.5 hours in vitro. Figures 5.12A and 5.12B demonstrate that in contrast to KEC, which induces approximately 20-25% of splenic NK cells to express IFNγ, IFNβ only induces approximately 5% of NK cells to express IFNγ. Co-stimulation of spleen cells with IFNβ and IFNγ elicited no increase above IFNβ stimulation alone (Figure 5.12B). Very similar findings were observed following stimulation of non-draining LN cell suspensions, where KEC induced 15-20% of NK cells to express IFNγ whilst co-stimulation with IFNβ and IFNγ only induced approximately 5% of NK cells to express IFNγ (Figure 5.12C). These findings strongly suggest that stimulation with type I IFNs alone is insufficient to elicit IFNγ production by NK cells. It is notable that in contrast to Figure 5.11A, in vitro stimulation of non-draining LN cell suspensions with KEC elicited robust IFNγ expression in Figure 5.12C. These contradictory findings are discussed further in Section 5.3.13.

Figure 5.12: In vitro stimulation of lymphoid cell suspensions with IFNβ and/or IFNγ induces a small increase in IFNγ expression by NK cells. (A) A representative flow cytometry histogram demonstrating NK cell IFNγ expression following in vitro stimulation with IFNβ or KEC. (B and C) The percentage of IFNγ+ve NK cells within cell suspensions generated from (B) spleens and (C) non-draining lymph nodes following 5.5 hours of in vitro stimulation with 3000 units/ml IFNβ, 20ng/ml IFNγ or 7.5. x 107 killed E. coli (KEC). Sample sizes: 4 x (B) spleen or (C) non-draining lymph node cell suspensions divided and cultured in the presence or absence of IFNβ +/- IFNγ +/- KEC. NC3Rs: 4 mice in total. IFN: interferon, LN: lymph node, SPL: spleen, KEC: killed E. coli, Unstim: unstimulated. The Mann Whitney U test was used to test for statistical significance, *p<0.05 relative to indicated samples, # p<0.05 relative to unstimulated samples.

205

5.3.12 NK cells can produce IFNγ independent of the interferon αβ receptor (IFNAR) signalling

The increase in IFNγ expression observed in the KEC-draining LN is largely dependent on IFNAR (Figures 5.10). In order to determine whether the IFNγ production induced by in vitro KEC stimulation (Figures 5.11 and 5.12) is similarly dependent on IFNAR, cell suspensions generated from the non-draining LNs, spleens and draining lymph nodes of wild-type and IFNAR-deficient mice were stimulated with KEC for 5.5 hours in vitro. Stimulation of cell suspensions generated from non-draining LNs revealed increased IFNγ production by NK cells among wild-type but not IFNAR-deficient cell suspensions (Figures 5.13A and 5.13B). However, stimulation of IFNAR- deficient spleen cell suspensions with KEC resulted in IFNγ production by NK cells, although this was reduced relative to NK cells in wild-type spleen cell suspensions (Figure 5.13C). Finally, cell suspensions generated from IFNAR-deficient and wild-type KEC-draining LNs exhibited equally substantial expression of IFNγ by NK cells following in vitro stimulation with KEC (Figure 5.13D). These findings therefore clearly demonstrate that NK cells can be induced to express IFNγ in the absence of type I IFNs in vitro. This is in stark contrast to the IFNAR-dependence of IFNγ production observed in vivo (Figure 5.10).

206

Figure 5.13: NK cells can produce IFNγ independent of the interferon αβ receptor (IFNAR) (A) Representative flow cytometry histograms demonstrating IFNγ expression by NK cells within IFNAR-deficient (KO) cell suspensions stimulated with 7.5 x 107 KEC. (B-D) The percentage of IFNγ+ve NK cells within wild-type (WT) and IFNAR-deficient (KO) cell suspensions generated from (B) non- draining lymph nodes, (C) spleens and (D) 12hr KEC-draining lymph nodes following 5.5 hours of in vitro stimulation with 7.5. x 107 killed E. coli (KEC). Sample sizes: n = 6 x WT non-draining LN cell suspensions, 6 x KO non-draining LN cell suspensions, 6 x WT spleen cell suspensions, 6 x KO spleen cell suspensions, 5 x 12hr WT draining LN cell suspensions and 6 x KO spleen cell suspensions that were split and cultured in either the presence or absence of KEC. NC3Rs: 12 mice in total (1 x 12hr WT LN excluded due to lack of response). IFN: interferon, LN: lymph node, KECL killed E. coli, Unstim: unstimulated, WT: wild-type, KO: IFNAR-deficient. The Mann Whitney U test was used to test for statistical significance, **p<0.01, *p<0.05, # p<0.05 relative to respective unstimulated control.

5.3.13 Monocyte frequency positively correlates with NK cell IFNγ expression following in vitro stimulation with KEC

Cell suspensions derived from non-draining LNs29 were stimulated with KEC in two independent experiments. These two experiments yielded divergent results (compare figures 5.11A and 5.12C) as KEC stimulation elicited a minimal increase in the percentage of IFNγ+ve NK cells in experiment 1 but a robust increase in the percentage of IFNγ+ve NK cells in experiment 2 (Figure 5.14A). A notable difference between these two experiments was the anomalously high percentage of monocytes present in the non-draining LN cell suspensions used in experiment 2 relative to those used in experiment 1 (Figure 5.14B). These results suggest the presence of monocytes facilitates IFNγ expression by NK cells following in vitro challenge with KEC. A combined analysis of all the data presented in figures 5.11-5.13 supports this hypothesis, as it demonstrates a strong positive correlation between the percentage of monocytes present in a lymphoid cell suspension and the percentage of NK cells induced to express IFNγ following stimulation with KEC (Figure 5.14C-F). Notably, this correlation was also observed among IFNAR-deficient cell suspensions, although this dataset is smaller than that for wild-type cell suspensions (Figure 5.14G). These positive correlations therefore suggest that monocytes drive the expression of IFNγ by NK cells following in vitro stimulation with KEC.

29 These consisted of cell suspensions generated from contralateral cervical lymph nodes as well as inguinal lymph nodes. 207

Figure 5.14: Monocyte frequency positively correlates with NK cell IFNγ expression following in vitro stimulation with KEC Two separate experiments were performed in which cell suspensions generated from non-draining lymph nodes and spleens were stimulated in vitro with 7.5. x 107 KEC for a period of 5.5 hours. (A) The percentage of IFNγ+ve NK cells within the cell suspensions stimulated with KEC in experiments 1 and experiment 2. (B) The percentage of monocytes in the non-draining lymph node cell suspensions stimulated in experiments 1 and 2. (C-F) The correlation between the percentage of monocytes prior to stimulation and the percentage of IFNγ+ve NK cells following stimulation of wild-type, (C) non-draining lymph node, (D) spleen and (E) 12hr KEC-draining lymph node cell suspensions with KEC in experiments 1 and 2. (F) Combined analysis of the date presented in C-E. (G) The same as (F) but for IFNAR-deficient cell suspensions. Sample sizes: (A-B) Exp 1: n = 5 x non-draining LN cell suspensions, 4 x spleen cell suspensions. Exp 2: n = 6 x non- draining LN cell suspensions, 6 x spleen cell suspensions. (C-D) Data combined from (A-B), i.e. n = 11 x non- draining LN cell suspensions, 10 x spleen cell suspensions. (E) n = 7 x WT 12hr draining LN (1 x 12hr WT draining LN excluded due to lack of response). (F) Data combined from (C-E) i.e. n = 28 WT LN/SPL cell suspensions. (G) n = 18 x KO LN/SPL cell suspensions (6 x non-draining LN, 6 x SPL, 6 x 12hr draining LN). Non-draining lymph nodes refer to control, contralateral and inguinal lymph nodes. NC3Rs: 18 mice in total LN: lymph node, SPL: spleen, KEC: killed E. coli. (A and B) The Mann Whitney U test was used to test for statistical significance, **p<0.01, * p<0.05, # = p<0.05 relative to unstimulated. (C-G) Correlation statistics were determined using the Pearson correlation coefficient.

208

5.4 Discussion

5.4.1 Summary of findings:

• The skin injection of KEC induces type I interferon response within the draining lymph node characterised by robust increases in the expression of the classic interferon stimulated genes Ifit1, Ifit2, Ifit3 and Cd69.

• Type I interferons are not required for the infiltration of neutrophils and monocytes into the KEC-draining LN. However, type I interferons do induce expression of interferon-stimulated genes by neutrophils and monocytes infiltrating the draining lymph node.

• Infiltrating neutrophils and monocytes are major expressers of the type I interferon- associated chemokines CCL2, CXCL9, CXCL10 and the inflammasome components NLRP3, pro-IL-1B and to a lesser extent IL-18 in the KEC-draining LN, whilst NK cells are the major expressers of IFNγ

• Whilst type I interferons are non-redundant for the expression of IFNγ in the draining lymph node in vivo, they are neither sufficient nor necessary to drive IFNγ production by lymphoid cell suspensions in vitro. Rather, in this in vitro context the production of IFNγ was positively correlated with the frequency of monocytes in the cell suspension. This suggests monocytes orchestrate IFNγ production by NK cells in the draining lymph node.

5.4.2 Technical limitations

There are two major technical limitations to the data presented in this chapter. Firstly, a mistake was made in one of the four cell sorts which resulted in the contamination of one of the ‘other CD11b+ve’ samples with isolated monocytes. This contaminated sample was included in all analyses for completeness but is highlighted in red in all relevant graphs. Secondly, it must be noted that the wild-type mice used in this chapter were not the littermates of the IFNAR-deficient mice to which they were compared. Rather, they were age and strain-matched mice purchased from a commercial supplier. It is therefore possible that random genetic or phenotypic differences exist between these two sets of mice, although it is unlikely that these influence the results of these experiments.

209

5.4.3 Type I interferon independent monocyte infiltration into the draining lymph node

It was deemed likely that type I IFN contributed to the acute infiltration of monocytes into the KEC-draining LN as type I IFNs have previously been shown to drive the infiltration of monocytes into various tissues (395,466,467), including the draining lymph node (381). However, Figure 5.2 unexpectedly demonstrated that monocyte infiltration into the KEC- draining LN is unaltered in IFNAR-deficient mice. Thus, whilst there is a robust type I IFN response in the KEC-draining LN (Figures 5.1 and 5.3), this is the first demonstration of type I IFN-independent monocyte infiltration into the draining lymph node. Whilst Sammicheli et al (381) did not delineate the mechanism by which type I IFNs drive monocyte infiltration in their model, it is likely driven by the induction of CCR2 ligands as monocyte infiltration into the draining lymph node is CCR2-dependent (205,242,369,370,381) and type I IFN are known to induce expression of these chemokines (466–470). Thus, the fact CCL2 (a major CCR2 ligand) expression was increased in the KEC-draining LN suggests that KEC induces type I IFN- independent CCL2 expression. The TLR adapter protein Myd88 has been shown to drive CCL2 production and monocyte infiltration in the absence of IFNAR (645). It is thus possible that KEC elicits IFNAR-independent CCL2 production and monocyte infiltration via TLR and MyD88 signalling. This is supported by the fact that Xu et al have described MyD88-dependent monocyte infiltration in the draining lymph nodes of mice infected with ectromelia virus (465). It would thus be informative to establish whether or not KEC-induced monocyte infiltration is similarly MyD88-dependent using MyD88-deficient mice and mice with cell-type specific deletions of MyD88 (to facilitate identification of the cell types responsible for driving monocyte infiltration). Overall, the contrast between the type I IFN-dependent monocyte infiltration described following LCMV challenge by Sammicheli et al (381) and the type I IFN- independent monocyte infiltration described following challenge with KEC (Figure 5.2B) serves to underscore the fact that inflammatory stimuli intrinsically differ in the mechanisms by which they induce inflammatory processes in the draining lymph node.

5.4.4 Infiltrating neutrophils and monocytes as effectors of type I IFN stimulation in the draining lymph node Whilst type I IFNs have been shown to underpin various inflammatory processes in the draining lymph node, the cellular targets that they co-opt to mediate these processes have not been characterised. This chapter highlights infiltrating neutrophils and monocytes as targets of type I IFNs in the draining lymph node. Figures 5.3A and 5.3B clearly demonstrate that dLN neutrophils and monocytes exhibit marked increases in the expression of classic ISGs relative

210 to their splenic counterparts and Figure 5.3C confirms that this is driven by type I IFNs in the context of CD69 expression. This is notable as these cell types have not previously been considered as targets of type I IFN in the draining lymph node. Moreover, this finding extends to type I IFN-associated inflammatory processes in the dLN as neutrophils and monocytes are identified as the cardinal expressers of the chemokines CXCL9, CXCL10, CCL2 (Figures 5.5 and 5.6) and the inflammasome components NLRP3, pro-IL-1β and to a lesser extent pro-IL-18 (Figure 5.7).

The marked expression of CXCL9 and CXCL10 by infiltrating neutrophils and monocytes described in Figure 5.7D-E is supported by Sung et al, as these authors identified CD11b+ve GR- 1+ve cells as major producers of these chemokines in the context of a secondary challenge with LCMV (329). The data presented in this chapter extends these findings both through its more specific identification of neutrophils and monocytes and by demonstrating this in the context of a primary antigen challenge. Given these findings, it is pertinent to question why type I IFN may target neutrophils and monocytes to induce CXCL9 and CXCL10 expression in the draining lymph node. Previous studies have illustrated that these chemokines are concentrated in the medulla and interfollicular regions of the draining lymph node (70,167,247,329) and thereby drive the rapid CXCR3-dependent recruitment of memory CD8 T cells and activated CD4 T cells from the central paracortex to peripheral interfollicular areas (a process termed ‘peripheralisation’) (70,247,329). Moreover, CXCR3 ligands are necessary for the recruitment of circulating NK cells to the draining lymph node (172,241,307). The notion that such processes are at play in this model is suggested by CXCR3 downregulation exhibited in CD8+ve cells and NK cells in KEC-draining LN (Figures 5.7F-G) as this chemokine receptor is known to undergo agonist-induced internalisation (643). It is therefore reasonable to hypothesise that infiltrating neutrophils and monocytes contribute to these processes of peripheralisation and NK cell recruitment and thereby mobilise cells to the lymph node periphery.

Such a focal role for neutrophils and monocytes as orchestrators of intranodal migration has not been previously suggested. The peripheral localisation of neutrophils in the KEC draining lymph node (Chapter 3, Figure 3.6) as well as other models (72,201,202,209,278,368,371) is consistent with this hypothesis as it overlaps with the peripheral distribution of CXCL9 and CXCL10 (72,167,247,329). However, the distribution of monocytes in the draining lymph node has not been well-characterised. Attempts to localise monocytes in this model with GR-1 were inconclusive and whilst other studies have described monocytes in various compartments of the draining lymph node including the central paracortex (242), peripheral interfollicular (381) and medullary (263) regions, each of these studies utilising imperfect methods of monocyte identification (discussed further in Chapter 7, Section 7.2.4.2). Clarity is therefore required

211 with regard to the localisation of infiltrating monocytes within the draining lymph node in order to inform the hypothesis that type I IFNs co-opt them as effector cells. If it is assumed that the distribution of monocytes is similar to the peripheral distribution of neutrophils in the KEC-draining LN, then it is reasonable to hypothesise that type I IFN stimulate these cells to recruit CXCR3+ve cells such as memory CD8 T cells and NK cells to the lymph node periphery.

The fact that neutrophils and monocytes are also identified as major expressers of COX-2, mPGES-1, and TBXAS in Chapter 4 of this thesis demonstrates that these cells are a hub of inflammatory gene expression (summarised in Table 5.1 below) and therefore may serve as a focal point of several innate immune pathways in the draining lymph node. Indeed, monocytes are likely to be more important than neutrophils in this regard as their infiltration is greater in terms of both cell number and duration (Chapter 3, Figure 3.9). In addition, the substantial CCL2 expression exhibited by infiltrating monocytes (Figure 5.6) suggests that they establish a positive feedback loop which fosters further monocyte recruitment. Similarly, as IFNγ is known to induce expression of the CXCR3 ligand CXCL9 in the draining lymph node (70,329), IFNγ-produced by CXCR3+ve CD8 and NK cells (Figures 5.9 and 5.10) may act on monocytes to promote further CXCR3-driven recruitment of these cells in another positive feedback loop. With this perspective it can be seen how neutrophils and monocytes may serve to recruit and activate inflammatory cells in the lymph node periphery under the influence of type I IFNs. Testing of this hypothesis requires 1) imaging to describe the spatial distribution of monocytes in the draining lymph node and their relationship/interaction with CXCR3+ve expressing NK cells and CD8 T cells and 2) mice with monocyte-specific deletion of IFNAR to determine whether or not this system is dependent on the stimulation of these cells by type I IFN.

Table 5.1: Expression of pro-inflammatory genes by neutrophils, monocytes and other CD11b+ve cells in the KEC-draining lymph node Population Mean fold increase in expression relative to CD11b-ve cells (2-ΔΔCT) Prostanoid Synthase Inflammasome Genes Chemokine Genes Other Genes Ptgs2 Ptges Tbxas1 Il1b Il18 Nlrp3 Ccl2 Cxcl9 Cxcl10 Ifng Neutrophils 1652 23920 133 136121 72 44548 4098 2461 360 4 Monocytes 438 20917 232 2756 28 2349 4894 2579 108 3 Other 78 249 22 355 5 108 378 181 6 82 CD11b+ve N.B. The contaminated ‘other CD11b+ve’ sample (see Section 5.4.2) is excluded from this analysis.

212

5.4.5 Regulation of IFNγ expression by type I interferons in the KEC- draining lymph node

The marked and rapid IFNγ expression observed in the KEC-draining LN (Figures 5.8 and 5.9) is consistent with several studies of various other inflammatory stimuli (72,90,172,241,278,279,307). NK cells and CD8+ve cells appear to be the major source of IFNγ in the KEC-draining LN (Figures 5.9 and 5.10) and this is also consistent with previous studies (72,241,278,279). Furthermore, several studies have previously demonstrated that type I IFNs are necessary for the production of IFNγ within the draining lymph node (172,279,466,592) and this finding is replicated in Figure 5.10, which demonstrates that IFNAR-deficient mice exhibit defective IFNγ production in the KEC-draining LN. However, the mechanisms by which type I IFN induce IFNγ expression in the draining lymph node have not been delineated and the in vitro experiments conducted in this chapter shed light on this knowledge gap.

In stark contrast to the defective IFNγ expression exhibited by IFNAR-deficient KEC-draining LNs in vivo, in vitro stimulation of lymph node and spleen cell suspensions with KEC demonstrated that type I IFNs are neither sufficient (Figure 5.12) nor necessary (Figure 5.13) to induce NK cell IFNγ expression. This reveals the existence of a factor that is required for NK cell IFNγ expression and that can be induced in the absence of IFNAR. The apparent contradiction that type I IFNs are redundant in vitro but not in vivo is clarified when considered in the context of the wider literature. Particularly notable are the studies conducted by Garcia et al (172), Lee et al (466) and Coombes et al (355). Firstly, Garcia et al (172) have demonstrated that type I IFNs indirectly induce NK cell IFNγ production within the draining lymph node via the activation of accessory cells. Secondly, Lee et al (466) demonstrate that NK cell IFNγ production is dependent upon the stimulation of monocytes by type I IFNs in HSV-infected mucosal tissue. Finally, Coombes et al (355) have demonstrated that draining lymph node monocytes potently stimulate NK cell IFNγ production in vitro. It is thus reasonable to hypothesise the following:

Type I interferons induce NK cell IFNγ production in the KEC-draining LN via the activation of infiltrating monocytes.

This hypothesis is strongly supported by Figure 5.14, which demonstrates that a strong positive correlation exists between the percentage of monocytes present in a lymphoid cell suspension prior to stimulation and the percentage of NK cells that express IFNγ following stimulation. However, this hypothesis has to explain how monocytes induce IFNγ production independent of IFNAR in vitro (Figure 5.13). It is possible that the direct exposure of monocytes to KEC in vitro induces the production of a secondary factor that is normally induced by type I IFNs in

213 vivo. There is strong evidence to suggest that IL-18 could be this secondary factor. This is for two main reasons. Firstly, IL-18 receptor deficient mice have been shown to exhibit reduced IFNγ production in the draining lymph node (72,278) and secondly type I IFNs have been shown to drive IL-18 production by monocytes (and thereby NK cell IFNγ expression) in HSV- infected vaginal tissue (466). It is thus notable that monocytes in the KEC-draining LN exhibit increased expression of NLRP3 and IL-18 (Figures 5.7F and H). The hypothesis can therefore be updated as follows;

IL-18 produced by interferon-stimulated monocytes drives the production of IFNγ by NK cells in the KEC draining lymph node.

A few key experiments would test this hypothesis. Firstly, the injection of KEC into monocyte deficient or monocyte-depleted mice30 would confirm whether or not monocytes are required to induce NK cell IFNγ production. Secondly, the production of IL-18 would also need to be confirmed. The identification of active inflammasomes within monocytes using a fluorescent inhibitor of caspase 1 (FLICA) or microscopic examination of the dLNs of inflammasome assembly reporter mice ( as per (328)) would be supportive in this regard. Another approach would be to measure IFNγ expression in mice with a monocyte-specific deletion of IL-18 or to simply measure IL-18 levels in draining lymph nodes of monocyte-depleted mice. Finally, further experiments would be required to delineate whether or not type I IFN drives IL-18 production. Indeed, whilst this chapter demonstrates significant increases in NLRP3 and pro-IL- 1β expression, the increase in IL-18 expression is very mild (Figure 5.7H). It would therefore be pertinent to investigate mechanisms by which type I IFNs may increase IL-18 production at the post-transcriptional level via increased inflammasome activity. Caspase-11 may be important in this regard as its expression caspase-11 is induced by type I IFN and it activates the inflammasome via cleavage of caspase-1 into its active form (595). Nevertheless, the study of IL-18 production and IFNγ expression in the KEC-draining LNs of mice harbouring specifically IFNAR-deficient monocytes would ultimately be needed to test the hypothesis outlined above and summarised diagrammatically in Figure 5.15.

30 CCR2-deficient and anti-CCR2 treated mice respectively 214

Figure 5.15: Proposed mechanism for the induction of IFNγ production by type I IFN-activated monocytes in the draining lymph node. IFN: interferon, IFNAR: interferon αβ receptor, Mono: monocyte, NK: natural killer. Created with biorender.com.

5.4.6 Summary In summary, this chapter demonstrates that type I IFNs are a key component of inflammatory response initiated in the draining lymph node following challenge with KEC. Moreover, it highlights infiltrating myeloid cells, particularly monocytes, as effector cells of type I IFN-driven inflammation in the draining lymph node. This is a novel finding and the data presented both in this chapter and in Chapter 4 suggests that monocytes +/- neutrophils are focal cells of the intranodal inflammatory response which serve to recruit and activate other inflammatory cells following stimulation with type I IFN. This is best characterised by the proposed model depicted in Figure 5.15 in which type I IFNs stimulate infiltrating monocytes to produce IL-18 and thereby induce IFNγ expression by NK cells. The data presented in the chapter therefore provides a solid foundation for the design of further experiments that test this and other hypotheses, which are discussed in greater detail in Chapter 7. Indeed, other studies of inflammatory processes in draining lymph nodes have ascribed a central role for lymph node macrophages that can appear to be at odds with the emphasis placed on neutrophils and monocytes in this chapter. This apparent paradox is also discussed extensively in the final discussion chapter of this thesis (Chapter 7) as are the implications of the findings of this chapter with regards to our current understanding of the innate barrier and adaptive functions of the draining lymph node.

This chapter has focussed upon type I IFNs in the novel context of myeloid cells infiltrating the draining lymph node. However, type I IFNs also stimulate lymphocytes in the draining lymph

215 node. One consequence of this is the rapid upregulation of CD69 on lymphocytes, which leads to their retention within the draining lymph node via inhibition of S1P-dependent egress (49,50). It was noted in figures 5.1B and 5.1C that CD69 is differentially upregulated by B cells and T cells in the KEC-draining LN. This suggests that type I IFN may differentially regulate the retention of B cells and T cells in the dLN with unknown consequences for lymphocyte recirculation during inflammation. This is an unstudied phenomenon and is the focus of the next chapter of this thesis (Chapter 6). Many of the experiments conducted in chapter 6 were conducted in parallel to those presented in this chapter and together they provide a holistic overview of the numerous actions of type I IFN in the draining lymph node in the context of acute inflammation.

216

6 Regulation of CD69 Expression in the Draining Lymph Node

6.1 Abstract

A curious feature of the preceding chapter is the differential increase in CD69 expression exhibited by lymphocytes in the draining lymph node (dLN), with B cells exhibiting significantly greater CD69 expression than T cells (Figure 5.1). Type I interferons are known to drive the expression of CD69 and its upregulation serves to retain recirculating lymphocytes within the draining lymph node by preventing their sphingosine-1-phosphate (S1P) directed egress into efferent lymph. It is therefore pertinent to question (1) whether type I interferons are responsible for the differential increases in CD69 expression reported in the preceding chapter and (2) if this differential CD69 expression dictates increased retention of B cells relative to T cells within the draining lymph node. Such a finding would suggest that type I interferons differentially modulate lymphocyte recirculation through the dLN, which has implication for strategies employed by naïve T and B cells to scan the draining lymph node for cognate antigen in the context of acute inflammation.

The data presented in this chapter demonstrates that CD4 T cells, CD8 T cells and B cells exhibit marked differences in CD69 expression under both steady state and inflammatory conditions. In the steady state, the proportion of CD69+ve cells is highest among CD4 T cells, followed by CD8 T cells and then B cells (CD4 > CD8 > B cells). This pattern is reversed in the dLN following challenge with killed E. coli (KEC) (B cells > CD8 > CD4). Type 1 interferons are the major driver of CD69 expression in the KEC-draining lymph node and are sufficient to drive these differences in CD69 expression observed between lymphocyte subsets. However, in vitro stimulation of wild-type and IFNAR-deficient cell suspensions demonstrates that IFNγ and KEC are also capable of driving this differential pattern of CD69 expression independently of type 1 interferons. These findings strongly suggest that lymphocyte subsets exhibit intrinsic differences in the regulation of CD69 expression. Finally, efforts to determine whether or not these differences in CD69 expression are reflected in differences in lymphocyte migration to S1P were inconclusive. Indeed, whilst CD69 expression impaired the migration of T cells to S1P as expected, B cells were unexpectedly refractory to S1P migration under all conditions tested.

In summary, lymphocyte subsets exhibit intrinsic differences in the regulation of CD69 expression. Unfortunately, efforts to determine whether or not this dictates differences between lymphocyte subsets in terms of S1P-dependent lymph node egress were inconclusive. Nevertheless, the data presented in this chapter informs a series of novel experiments that would significantly contribute to our understanding of lymphocyte recirculation through the dLN in the context of inflammation.

217

6.2 Introduction

Chapter 5 describes various aspects of the type I IFN response within the KEC-draining LN from the perspective of infiltrating neutrophils and monocytes. An unexpected but notable finding of these experiments was that draining lymph node (dLN) B cells exhibit significantly greater expression of the type I IFN-driven activation marker CD69 than dLN T cells (Figure 5.1)). As will be discussed in the following sections, CD69 is a multifunctional cell surface protein that is rapidly upregulated by activated lymphocytes and is a central regulator of lymphocyte egress from the dLN during inflammation. This chapter investigates the intriguing and marked difference in CD69 expression exhibited by B and T cells in the KEC-draining LN and explores its effect on sphingosine-1-phospate (S1P)-dependent lymphocyte egress. Thus, chapter 5 and this chapter together investigate the effects of type I IFNs on both infiltrating myeloid cells and lymphocytes within the dLN respectively.

6.2.1 Regulation of CD69 expression

CD69 is a type II transmembrane C-type lectin (646) that is expressed by a wide range of haematopoietic cells upon activation. This includes T cells (84,191,198,228,274,278,452,453,641,646–654), B cells (84,274,401,453,641,646,649,651,653,655–657), dendritic cells (649,658,659), macrophages (171,660,661) and NK cells (274,662,663). The drivers of CD69 expression are similarly diverse, but for the purposes of the following discussion will be divided into factors that drive CD69 expression in the steady state and in the context of inflammation. This will be followed by a discussion of the transcriptional and post-transcriptional regulation of CD69 expression and finally a discussion of the currently identified functions of CD69 in the mammalian immune system.

6.2.1.1 CD69 expression in the steady state 10-20% of CD4+ve T cells in secondary lymphoid organs and approximately 50% of CD4+ve T cells in the intestinal lamina propria express CD69 in the steady state (452). This steady state expression of CD69 appears to be largely driven by commensal microflora, as both germ-free mice and mice treated with broad-spectrum antibiotics exhibit a profound reduction in the percentage of CD69+ve CD4+ve T cells, particularly in the lamina propria (452). The precise mechanisms by which the commensal microflora exert this effect is unclear but it is preserved

218 in mice deficient for the interferon αβ receptor and can thus be considered to be independent of type I IFNs.

In addition to the commensal microflora, it is likely that previous infections also contribute to the CD69 expression observed in the steady state. Indeed, CD69 is expressed constitutively by subsets of memory of regulatory T cells (654,664,665). Moreover, OT-II T cell receptor transgenic mice exhibit reduced CD69 expression in the steady state relative to wild type mice, indicating that T cell receptor signalling is a contributing factor at some stage. Steady-state CD69 expression is also observed in the thymus at discrete stages of thymocyte development (666,667). There is, therefore, ample evidence of T cell CD69 expression in the steady state in in a wide variety of contexts, including primary lymphoid organs, secondary lymphoid organs and peripheral tissues.

6.2.1.2 CD69 expression in the context of inflammation

6.2.1.2.1 Cytokine-driven CD69 expression CD69 expression can be induced in vitro by the pathogen associated molecular patterns (PAMPs) LPS (653,658,659,661) and CpG (453,658,659), the cytokines TNFα (659) and type I IFNs (401,453,655,657) and infectious agents (660). Similarly, in vivo challenge with PAMPs31 or viral pathogens32 has been shown to elicit upregulation of CD69 by lymphocytes in the dLN. However, this is not a universal feature of inflammation as the adjuvants alum, MF-59, CpG33 and Pam3CSK4, do not induce increased expression of CD69 in the dLN (274). Similarly, the skin injection of Bacillus Calmette-Guerin does not elicit a substantial increase in CD69 expression in the dLN (Chapter 3, Supplementary Figure 3.12).

Type I IFNs have been shown to non-redundantly drive CD69 expression in vivo following challenge with the TLR3 ligand poly IC, the TLR-4 adjuvant GLA-SE, the TLR9 ligand CpG-rich DNA and influenza (278,342,401,452,453). The effect of type I IFNs is likely direct as they induce CD69 expression on purified populations of lymphocytes (401,453) and the CD69 gene harbours an interferon regulatory factor 4 binding site (668). Cytokines other than type I IFNs have also been implicated in the regulation of CD69 expression. Desbien et al have demonstrated that acute upregulation of CD69 in the dLN is partially reduced by antagonism of IFNγ, deletion of the IL-18 receptor or deletion of caspase 1/11 (278). The authors further

31 the TLR3 agonist Poly IC (84,342,452,646), the TLR4 agonists LPS (653,656) and GLA-SE (278), the TLR7/8 ligand Resiquimod (274) and the TLR9 ligand CpG-rich DNA (453,658,659) 32 influenza (171,401,641,649) and West Nile virus (651). 33 Note that this study contradicts other studies that show that CpG does elicit CD69 expression in the draining LN. 219 illustrated that this effect is likely independent of type I IFN production, as adoptively transferred IFNAR-deficient T cells still exhibit CD69 upregulation in the dLN, albeit to a much lesser extent than their wild-type counterparts. Furthermore, Freeman et al have demonstrated that cytokines interact synergistically to induce CD69 expression on T cells, with the most potent drivers of CD69 expression being combinations of the cytokines IL-18, IL-15, IL-33, TNFα and type I IFNs (669). In summary, type I IFNs have been identified as the primary driver of CD69 expression in the context of inflammation, but this effect is likely potentiated by other pro-inflammatory cytokines.

6.2.1.2.2 Antigen-driven expression of CD69 T cells exhibit increased expression of CD69 when presented with cognate antigen (191,198,228,652). This is true of T cells exposed to cognate antigen either in vitro through an antigen presentation assay (228) or in vivo following immunisation with cognate antigen (191,198,652). Moreover, such CD69 expression is not observed if T cells are challenged with non-cognate antigen (228) or if antigen presentation is impaired (191). This strongly suggests that TCR signalling is the major driver of CD69 expression in this context. Similarly, CD69 expression can be induced on B cells through stimulation of the B cell receptor (BCR) with cognate antigen, or stimulation of toll-like receptor 4 (TLR-4) with LPS (670). Indeed, concomitant BCR and TLR-4 signalling synergistically induce CD69 expression on B cells (670). Thus, CD69 expression is a feature of lymphocytes activated by their cognate antigen.

6.2.1.3 Transcriptional regulation of CD69 expression The gene encoding CD69 is located in the natural killer complex, which lies on chromosome 12 in humans and chromosome 6 in mice (671,672). This gene is poised for rapid transcription, as evidenced by the fact that its promoter is constitutively associated with active chromatin modifications (646) and is constitutively bound by RNA polymerase II (673). Indeed, lymph node T cells exhibit increased levels of CD69 mRNA within 30 minutes of stimulation in vitro (671). CD69 mRNA has a half-life of <60 minutes in T cells and this has been attributed to AU- rich regions of its 3’ untranslated region (674). As a consequence, increases in CD69 mRNA observed following in vitro stimulation are rapid but transient (671,674).

The CD69 gene is associated with a multitude of regulatory elements. These include a promoter sequence that harbours binding sites for several transcription factors, including NFκB, AP-1, OCT, CREB and EGR (675) as well as 4 upstream conserved non-coding sequences

220

(CNS’s) that also contain transcription factor binding sites and undergo histone modifications during lymphocyte activation (646,675). Reporter gene assays have demonstrated that these CNS regions exhibit both positive and negative effects on CD69 expression and notably they differentially regulate expression of a reporter gene in B and T cells (668,675). In addition to these 5’ promoter-distal elements, a regulatory element is also present in intron 1 of the CD69 gene and this also harbours active chromatin modifications and an interferon regulatory factor 4 binding site (668). The CD69 gene is therefore subject to significant regulation at the level of transcription and there is evidence that this regulation differs between B and T cells.

6.2.1.4 Post-transcriptional regulation of CD69 expression The expression of CD69 is subject to several mechanisms of post-transcriptional regulation. Firstly, CD69 is subject to translational repression by the miR-17~92 family of microRNAs in B cells (676). Secondly, Risso et al claim to visualise an intracellular pool of CD69 in resting T cells that facilitates rapid CD69 expression independent of de novo synthesis, although these data are not convincing (677). CD69 is also regulated at the cell surface by the sphingosine phosphate receptor 1. As will be discussed in subsequent sections, CD69 is known to bind S1P1 on the cell surface and thereby induce its internalisation and degradation (342,626). Thus, S1P1 may reciprocally induce the internalisation of CD69, evidenced by the fact that S1P1 deletion is associated with increased CD69 expression (150), and conversely, that S1P1 overexpression or agonism is associated with reduced CD69 expression (678–680). In summary, several post-transcriptional mechanisms of CD69 expression have been identified. This combined with the aforementioned transcriptional controls of CD69 expression (Section 6.2.1.3) suggests that CD69 plays important functions that warrant such a high degree of regulation.

6.2.2 Functions of CD69

CD69 has been shown to play a functional role in three fields of immunological research; the study of immunoregulation, the study of sphingosine-1 phosphate-dependent cell migration and the study of memory T cells.

6.2.2.1 CD69 and immunoregulation The importance of CD69 in immunoregulation has been demonstrated by numerous studies showing that CD69-deficient mice exhibit increased immunopathology relative to wild-type

221 mice following an inflammatory challenge. This has been shown in the context of autoimmune myocarditis (681), Listeria monocytogenes infection (660), allergic airway and skin inflammation (682), peritoneal fibrosis (683) and inflammatory colitis (452). The best described mechanism by which CD69 limits inflammatory responses is by the impairment of Th17 T cell responses (648,684). Galectin-1 expressed on the cell surface of dendritic cells has been shown to negatively regulate Th17 differentiation by acting as a ligand of CD69 (684). Moreover, the cytoplasmic tail of CD69 has been shown to facilitate intracellular signalling pathways that limit Th17 differentiation (648). Thus, it is apparent that CD69 acts to limit T cell driven immunopathology, at least in part by suppression of Th17 differentiation.

In contrast to the above studies, Cibrian et al have demonstrated that CD69 potentiates psoriatic skin inflammation through increasing IL-22 production by dermal γδ T cells (685). This IL-22 production is due to increased tryptophan uptake, which is facilitated by interaction of CD69 with the amino acid transporter LAT1. This finding has led to speculation that metabolic reprogramming is another mechanism by which CD69 may regulate immune responses (686). Indeed, it is postulated that CD69’s interaction with S1P1 is relevant in this regard as S1P1 has been shown to modulate T cell differentiation through its effect on the mTOR signalling pathway (686,687). In summary, the effect of CD69 on inflammatory responses is context- dependent and mediated by a variety of mechanisms.

6.2.2.2 CD69 and memory T cells CD69 has proven to be a protein of interest with regard to the study of both tissue-resident memory T cells and memory T cells within the bone marrow. Firstly, CD69 is one of the key markers used to phenotype tissue resident memory (TRM) T cells; a non-circulating subset of T cells strategically positioned within peripheral tissues that facilitate rapid responses to pathogens upon reinfection (688,689). CD69 deficiency has been shown to limit the generation of TRM T cells in the skin (689). It has been proposed that CD69 exerts this effect through its interaction with S1P1 (Section 6.2.2.3) as CD69 has been shown to prevent T cell egress from inflamed skin (690) and the transcriptional downregulation of S1PR1 is key to the development of TRM cells (688). However, Takamura et al have demonstrated that CD69 expression is not required for the development of TRM T cells in the lung (691), illustrating that the importance of CD69 in this process is context-dependent.

In 2012, Shinoda et al demonstrated that CD69-deficient mice exhibit an impaired long-term humoral immune response (654). This defect is due to the impaired migration of effector T cells from the secondary lymphoid organs to the bone marrow, a process that is required for

222 their differentiation into memory T cells. Notably, CD69 promotes the interaction of T cells with the bone marrow stromal cells and thus may facilitate retention of these cells in the bone marrow, although a role for reduced S1P-dependent egress from the bone marrow has also been proposed (654). In summary, CD69 has been shown to be an important factor in the generation of memory T cells in two separate contexts and its ability to modulate cell migration is implicated in both these contexts.

6.2.2.3 CD69 and S1P-dependent cell migration CD69 expression has been shown to prevent the egress of lymphocytes from lymph nodes (342,626) and Peyer’s patches (692). This is due to the fact that CD69 binds the sphingosine-1 phosphate receptor S1P1, thereby inducing its internalisation and degradation (Figure 6.1A) (342,626). S1P1 is a G-protein coupled receptor for the egress factor sphingosine-1 phosphate (S1P), which facilitates the transmigration of lymphocytes from the lymph node parenchyma into efferent lymph (Figure 6.1B) (84,150). CD69 upregulation therefore renders lymphocytes refractory to S1P and thereby prevents their egress from the lymph node (342,626). Indeed, confocal imaging has demonstrated that CD69+ve lymphocytes are excluded from the cortical lymphatic sinuses, which serve as the portals of lymphocyte egress from the lymph node (84). Thus, CD69 expression promotes the retention of lymphocytes within secondary lymphoid organs.

Figure 6.1: CD69-dependent regulation of S1P1 expression and lymphocyte egress from lymph nodes Diagrammatic representations of (A) the internalisation and degradation of S1P1 by CD69 on the cell surface and (B) the resulting defect in lymphocyte egress from the lymph node parenchyma exhibited by CD69-positive lymphocytes. LN: lymph node, S1P: sphingosine-1-phosphate, S1P1: sphingosine-1- phosphate receptor 1. Created with biorender.com.

The physiological function of CD69-induced lymphocyte retention in the dLN is not known. One theory is that such retention increases the likelihood of T and B cells encountering cognate

223 antigen by increasing the number of lymphocytes and their residence time within the dLN. This function would be most applicable to cytokine-driven CD69 expression, which affects lymphocytes regardless of antigen specificity. Another theory is that the CD69 expression observed following stimulation with cognate antigen functions to prevent the egress of cognate lymphocytes from the dLN in order to optimise their differentiation into effector and memory cells. This theory is supported by the fact that S1PR1 expression determines whether or not effector T cells egress from the dLN (693,694). These theories are not mutually exclusive, and both predict that CD69 expression promotes the optimal development of adaptive immune responses. These theories are somewhat undermined by the finding that CD69-deficient mice exhibit no defect in T cell priming in the spleen following intraperitoneal infection with vaccinia virus (658). However, this latter study provides no evidence that this infectious challenge upregulates CD69 in either lymph nodes or the spleen. Moreover, it is possible that the effect of CD69 is redundant in this systemic model of infection, in which multiple secondary lymphoid organs may bear antigen.

6.2.3 Summary CD69 is rapidly expressed by haematopoietic cells in response to a wide variety of stimuli and is implicated in numerous functions within the immune response at baseline and during acute inflammation. It is evident from Figure 5.1 (Chapter 5) that the skin injection of KEC induces significantly greater upregulation of CD69 on B cells relative to T cells in the dLN. This chapter therefore seeks to determine the inflammatory stimuli responsible for this previously unappreciated differential pattern of CD69 expression and explore its impact on the egress of lymphocytes from the KEC-draining LN.

6.2.4 Aims

• To temporally characterise the differential upregulation of CD69 exhibited by T and B cells in the KEC-draining lymph node and demonstrate whether or not CD69 expression also differs between CD4 and CD8 T cells.

• To determine whether or not this differential pattern of CD69 expression is driven by type I interferons or by the synergistic action of different inflammatory mediators.

• To determine whether or not this differential pattern of CD69 expression results in B and T cells exhibiting a differential pattern of migration to the egress factor sphingosine-1 phosphate (S1P) – namely that B cell migration to S1P is impaired to a greater extent than T cell migration to S1P.

224

6.3 Results

6.3.1 CD69 is upregulated by both lymphocytes and myeloid cells in the draining lymph node following skin injection of killed E. coli (KEC)

Increased expression of CD69 by lymphocytes in the KEC-draining LN was reported in Chapter 5 (Figure 5.1) of this thesis. Figure 6.2A extends these findings to demonstrate that the percentage of T and B cells expressing CD69 is increased as early as 2 hours following injection of KEC and is prominent at 6 and 24 hours, before reducing towards baseline levels at 48 hours (Figure 6.2A). Concurrent analysis of neutrophils and monocytes in the dLN revealed that these cells also exhibit increased expression of CD69 relative to splenic neutrophils and monocytes (Figure 6.2B). This was true of neutrophils and monocytes at all time points examined, although the absence of neutrophils from the dLN at 24 and 48 hours precluded measurement of neutrophil CD69 expression at these time points. In addition, a separate analysis of dLNs harvested 12 hours following injection of killed E. coli demonstrated that NK cells also upregulate CD69 in the dLN (Figure 6.2C). In summary, increased CD69 expression is exhibited by both lymphocytes and myeloid cells in the KEC-draining LN.

225

Figure 6.2: CD69 is upregulated by both lymphocytes and myeloid cells in the KEC-draining lymph node (A-B) The percentage of (A) B cells and T cells and (B) neutrophils and monocytes that are CD69+ve in the draining lymph 2-48 hours following skin injection of KEC. (C) The CD69 MFI of NK cells in the draining lymph node 12 hours following injection of KEC. Sample sizes: (A-B) n = 12 x CTRL LN, 4 x 2hr LN, 4 X 6hr LN, 4 x 24hr LN, 4 x 48hr LN and 19 x SPL. (C) 6 x CTRL LN, 4 x 12hr Ipsi LN. NC3Rs: 26 mice in total. LN: lymph node, SPL: spleen, Ipsi: ipsilateral, CTRL: control and contralateral, MFI: median fluorescence intensity. The Mann Whitney U test was used to determine statistical significance, **p<0.01 relative to CTRL LN.

6.3.2 Lymphocyte subsets differentially express CD69 in the KEC-draining lymph node A notable feature of the increased CD69 expression described in Figure 5.1 (Chapter 5) is that the proportion of B cells expressing CD69 is substantially higher than that of T cells. Figure 6.3A-G presents a summation of all the lymphocyte CD69 expression data collected in this thesis and illustrates that this difference in CD69 expression is remarkably conserved. Small but significant increases in CD69 expression occur within the first 3 hours following challenge but the difference between B and T cells was not significant (Figure 6.3A and 6.3B). However, as with Figure 5.1, substantially increased expression of CD69 is observed on B cells relative to T cells at 6 hours following injection of killed E. coli (KEC) (Figure 6.3C) and this is maintained at 12- and 24-hours following challenge (Figures 6.3D-E). At 48 hours following challenge, CD69 expression has almost retuned to baseline and the difference between B and T cells becomes a non-significant trend (Figure 6.3F). Data from all 6 of these time points is summarised in the graph depicted in Figure 6.3G. This pattern is also apparent when CD69 expression is measured via median fluorescence intensity (MFI) (Supplementary Figure 6.15) despite the fact that this parameter is not optimal for the analysis of these experiments (for the reasons outlined in Chapter 2, Section 2.2.5.1.4). A notable additional finding is that the pattern of CD69 expression observed in draining lymph nodes is the reverse of what is observed in non-draining control lymph nodes, where a higher proportion of T cells express CD69 relative to B cells (Figure 6.3B-E).

A similar difference in CD69 expression is also observed between CD4 and CD8 T cells, although the difference is less marked than that observed between T and B cells. In non- draining control lymph nodes, a slightly smaller proportion of CD8 T cells are CD69+ve relative to CD4 T cells (Figure 6.4A-B). However, at 6- and 12-hours following injection of killed E. coli the proportion of CD69+ve cells approximately 5-10% greater among CD8 T cells relative to CD4 T cells (Figure 6.4A-B). Therefore, the expression of CD69 is differentially regulated by T cell subsets and B cells within lymph nodes in the steady state and during acute inflammation.

226

Figure 6.3: B and T cells differentially express CD69 in the KEC-draining lymph node Summation of CD69 expression data collected in this thesis. Figures A-F each consist of two graphs representing two different analyses of the same data. The left graph compares CD69 expression between T and B cells in draining and non-draining lymph nodes, whilst the right graph compares CD69 expression between T and B cells within the same lymph node. (A-F) Portrays this data for lymphocytes in the draining lymph node (A) 2, (B) 3, (C) 6, (D) 12, (E) 24 and (F) 48 hours following injection of KEC. (G) A summation of the data presented in (A-F). Sample sizes: n = 57 x CTRL LN, 4 x 2hr LN, 4 x 3hr LN, 18 x 6hr LN, 15 x 12hr LN, 8 x 24hr LN and 4 x 48hr LN. NC3Rs: 63 mice in total. LN: lymph node, Ipsi: ipsilateral, CTRL: control and contralateral. The Mann Whitney U test and the Wilcoxon matched pairs test were used to test for statistical significance in unpaired (left graphs) and paired (right graphs) analyses respectively *p<0.05, **p<0.01, ****p<0.0001. (G) error bars = standard deviation.

227

Figure 6.4: CD4 and CD8 T cells differentially express CD69 in the KEC-draining lymph node Summation of CD4 and CD8 T cell CD69 expression data collected in this thesis. (A -B) The percentage of CD69+ve CD4 and CD8 T cells in the draining lymph node (A) 6 and (B) 12 hours following injection of KEC. The two graphs in A and B represent two different analyses of the same data. The left graph compares the difference in CD69 expression between draining and non-draining lymph nodes, whereas the graph to the right compares CD69 expression between CD4 and CD8 T cells within the same lymph node. Sample sizes: (A) n = 13 x CTRL LN and 8 x 6hr LN. (B) n = 6 x CTRL LN and 4 x 12hr LN. NC3Rs: 14 mice in total. LN: lymph node, Ipsi: ipsilateral, CTRL: control and/or contralateral. The Mann Whitney U test and the Wilcoxon matched pairs test were used to determine statistical significance in unpaired (left graphs) and paired (right graphs) analyses respectively *p<0.05, **p<0.01, ***p<0.001.

6.3.3 The upregulation of CD69 in the KEC-draining lymph node is largely dependent upon the interferon α/β receptor (IFNAR). Type I IFNs have previously been shown to drive acute expression of CD69 in the dLN (84,278,342) and the KEC-draining lymph node exhibits increased expression of type I interferon stimulated genes (ISGs) (Figure 5.1, Chapter 5). Thus, type I IFNs were deemed to be the likely driver of CD69 expression in the KEC-draining LN. This hypothesis was tested by the injection of KEC into the earflaps of mice deficient for the interferon receptor α/β receptor (IFNAR). In accord with this hypothesis, the expression of CD69 was significantly reduced among dLN lymphocytes from IFNAR-deficient mice relative to wild-type mice (Figures 6.5A and 6.5B). Indeed, the KEC-draining LNs of IFNAR-deficient mice exhibited only a small increase in the mean percentage of CD69+ve B cells (~16%) relative to non-draining LNs (4.7%) (Figure 6.5A) and no accompanying increase in the percentage of CD69+ve T cells was observed (Figure 228

6.5A and 6.5B). Therefore, it can be inferred that type I IFNs are responsible for most of the increased CD69 expression exhibited by lymphocytes in the KEC-draining lymph node.

Figure 6.5: The upregulation of CD69 in the KEC-draining lymph node is largely dependent on the interferon α/β receptor (IFNAR) (A) The percentage of CD69+ve B cells, and T cells in the draining lymph nodes of wild-type and IFNAR-deficient mice 6- and 12-hours following injection of KEC. (B) The percentage of CD69+ve CD4 T cells and CD8 T cells in the draining lymph nodes of wild-type and IFNAR-deficient mice 6 hours following injection of KEC. Sample sizes: n = 15 x WT CTRL LN, 15 x KO CTRL LN, 5 x 6hr WT LN, 5 x 12hr WT LN, 6 x 6hr KO LN, 6 x 12hr KO LN. NC3Rs: 24 mice in total (1 x WT 6hr LN and 1 x WT 12hr LN excluded due to a lack of response). LN: lymph node, Ipsi: ipsilateral, CTRL: contralateral and inguinal LN, IFNAR: interferon αβ receptor, WT: wild-type, KO: IFNAR-deficient. The Mann Whitney U test was used to test for statistical significance **p<0.01, # = p<0.01 relative to respective CTRL LN

6.3.4 In vitro stimulation with interferon-β is sufficient to induce differential upregulation of CD69 by lymphocyte subsets Figure 6.5 demonstrates that type I IFNs are responsible for the majority of the increase in CD69 expression observed in the KEC-draining LN. However, it was not clear whether type I IFNs alone were sufficient to induce the differential increase in CD69 expression exhibited by different lymphocyte subsets. Indeed, it is possible that these differences in CD69 expression result from the synergistic interactions of type I IFNs with other cytokines. To address this question, cell suspensions generated from non-draining LNs were stimulated in vitro with various concentrations of interferon-beta (IFNβ) for a period of 2-6 hours. Figures 6.6A and

229

6.6B shows that IFNβ rapidly increased expression of CD69 in a dose-dependent manner by both T and B cells present in the lymph node cell suspensions. In addition, IFNβ induced greater upregulation of CD69 among B cells relative to T cells, regardless of the dose or duration of IFNβ stimulation (Figures 6.6B-6.6C). Notably, stimulation with PMA and ionomycin upregulates CD69 on T and B cells to a similar extent, illustrating that T cells are not intrinsically limited in their ability to upregulate CD69 (Figure 6.6A). Further experiments with splenocyte cell suspensions illustrated that IFNβ stimulation also induces greater upregulation of CD69 among CD8 T cells than CD4 T cells (Figure 6.6D and 6.6E). In summary, these experiments demonstrate that stimulation of lymph node or spleen cell suspensions with type I IFNs is sufficient to induce the differential CD69 expression observed in the KEC-draining LN.

230

Figure 6.6: In vitro stimulation with interferon β is sufficient to induce differential upregulation of CD69 by lymphocyte subsets (A) Representative flow cytometry histograms demonstrating the effect of stimulation with IFNβ (2000 units/ml) or PMA and ionomycin on the expression of CD69 by T and B cells in a lymph node cell suspension. (B) The percentage of CD69+ve B cells and T cells following 6 hours of in vitro stimulation with varying doses of IFNβ. (C) The percentage of CD69+ve B cells and T cells following 2-6 hours of in vitro stimulation with 2000 units/ml IFNβ. (D) The percentage of CD69+ve CD4 and CD8 T cells following 5.5 hours of in vitro stimulation with 10,000 units/ml IFNβ. (E) A paired analysis of the data presented in (D) illustrating the difference in CD69 expression exhibited by IFNβ-stimulated CD4 and CD8 T cells in the same cell suspension. Sample sizes: (B) n = 4 x lymph node cell suspensions divided and cultured in the absence or presence of 200, 2000, or 20,000 units/ml IFNβ. (C) n = 4 x lymph node cell suspensions divided and cultured in the presence of 2000 units/ml IFNβ for 0, 2, 3, 4 or 6 hours. (D-E) n = 4 x spleen cell suspensions divided and cultured in the presence or absence of 10,000 units/ml IFNβ. NC3Rs: 12 mice in total. Unstim: unstimulated, IFNβ: interferon β, hr: hour. (B-D) The Mann Whitney U test was used to determine statistical significance. (E) The Wilcoxon matched pairs test was used to determine statistical significance. *p<0.05, **p<0.01.

231

6.3.5 Both T and B cells exhibit increased expression of type I interferon- stimulated genes in the KEC-draining lymph node

One possible explanation for the reduced CD69 expression exhibited by T cells relative to B cells is that B cells exhibit a greater sensitivity to type I IFNs than T cells. It was hypothesised that such a difference would be reflected by increased expression of interferon-stimulated genes (ISGs) by B cells than T cells. Thus, ISG expression was compared between T cell and B cells isolated from 12-hour KEC-draining LNs by tandem FACS and qRT-PCR. This experiment demonstrated that T cells do not exhibit a gross defect in ISG expression relative to B cells. Indeed, T cells exhibited increased expression of Ifit1 relative to B cells (also reported by Fensterl et al (439)), whilst B cells exhibited increased expression of Ifit2 relative to T cells and both exhibited similar upregulation of Ifit3 (Figure 6.7A-C). These results suggest that type I IFNs induce different sets of ISGs in T and B cells. Unexpectedly, T cells and B cells exhibited similar upregulation of CD69 mRNA (Figure 6.7D). This suggests that post-transcriptional mechanisms of CD69 expression underlie the differences in cell surface CD69 expression described using flow cytometry. However, it is also possible that this analysis of the 12-hour time point missed the peak of CD69 mRNA transcription, which may differ between B and T cells.

Figure 6.7: T and B cells in the KEC-draining lymph node exhibit increased expression of interferon- stimulated genes Expression of the genes encoding (A) IFIT1 (B) IFIT2, (C) IFIT3, and (D) CD69 by T and B cells isolated by FACS from the draining lymph node 12 hours following injection of KEC. The proteins encoded by each gene is stated in brackets next to each gene. Sample sizes: n = 3 x CTRL LN and 3 x 12hr LN. Each data point represents 12hr draining or non-draining (CTRL) lymph node cells pooled from 2-4 mice. NCR3s: 9 mice in total. LN: lymph node, CTRL: control and contralateral, FACS: fluorescence activated cell sorting, T: T cells, B: B cells, KEC: killed E. coli. No statistical analysis was performed as n= 3 is insufficient to determine significance using the Mann Whitney U test.

232

6.3.6 In vitro stimulation with KEC induces IFNAR-independent CD69 expression among B cells but not T cells

Type I IFNs may be produced at the site of inflammation and reach the dLN via afferent lymphatics or they may be produced by cells within the lymph node. To determine whether type I interferon-driven CD69 upregulation can occur independent of the site of inflammation, cell suspensions generated from the non-draining LNs of wild-type and IFNAR-deficient mice were stimulated with 7.5 x 107 killed E. coli (KEC) for 5.5 hours and CD69 expression was subsequently assessed using flow cytometry. This experiment demonstrated that lymphocytes within wild-type lymph node cell suspensions exhibited significantly greater CD69 expression than lymphocytes within IFNAR-deficient cell suspensions (Figure 6.8A-D). However, the B cells present in IFNAR-deficient lymph node cell suspensions also exhibited substantial CD69 upregulation, whilst IFNAR-deficient T cells exhibit no increase in CD69 expression (Figure 6.8A-D). Very similar results were observed following in vitro stimulation of splenocyte cell suspensions with KEC (Figure 6.8E-G). This demonstrates that (1) KEC induces the production of type I IFNs by lymph node cells and thereby upregulates CD69 on B cells and T cells in an IFNAR-dependent manner and (2) that KEC can drive significant CD69 expression independent of type I IFNs on B cells but not T cells.

233

Figure 6.8: In vitro stimulation with KEC induces interferon α/β Receptor (IFNAR) dependent and independent CD69 expression Cell suspensions generated from the non-draining (CTRL) lymph nodes and spleens of wild-type and IFNAR-deficient (KO) mice were subjected to 5.5 hours of in vitro stimulation with 7.5. x 107 killed E. coli (KEC). (A) Representative flow cytometry histograms comparing the expression of CD69 by KEC- stimulated wild-type (WT) and IFNAR-deficient (KO) B cells, CD4 T cells and CD8 T cells. (B) The percentage of wild-type (WT) and IFNAR-deficient (KO) CD69+ve B cells following in vitro stimulation with KEC. (C) The CD69 MFI of CD69+ve B cells following in vitro stimulation with KEC. (D) The percentage of wild-type (WT) and IFNAR-deficient (KO) CD69+ve CD4 T cells and CD8 T cells following in vitro stimulation with KEC. (E-G) Same as (B-D) but using spleen cell suspensions. Sample sizes: n = 6 x WT LN cell suspensions, 6 x KO LN cell suspensions, 6 x WT SPL cell suspensions and 6 x KO SPL cell suspensions.NC3Rs: 12 mice in total. CTRL: contralateral and inguinal LN, IFNAR: interferon αβ receptor, WT: wild-type, KO: IFNAR-deficient. The Mann Whitney U test was used to determine statistical significance. **p<0.01, # = p<0.01 relative to respective CTRL LN

234

6.3.7 In vitro stimulation with IFNγ induces IFNAR-independent CD69 expression among B cells but not T cells

The IFNAR-independent upregulation of CD69 exhibited by B cells in Figure 6.8 may be driven by a direct effect of KEC on B cells and/or cytokines produced in response to KEC. IFNγ was considered a potential IFNAR-independent driver of CD69 expression, as deletion of the IFNγ receptor has been shown to impair CD69 upregulation in the dLN (278). Figure 6.9 demonstrates that stimulation of lymph node cell suspensions with IFNγ induces the upregulation of CD69 on wild-type T cells and B cells. IFNγ also induced upregulation of CD69 on IFNAR-deficient B cells, although this was less marked than the CD69 upregulation observed among wild-type B cells (Figure 6.9A and B), which suggests that IFNγ induces the production of type I IFNs. IFNAR-deficient T cells exhibited no increase in CD69 expression following stimulation with IFNγ (Figure 6.9B). Very similar results were observed following in vitro stimulation of splenocyte cell suspensions with IFNγ (Figure 6.9C). These results demonstrate that (1) IFNγ can drive the production of type I IFNs in lymph node and spleen cell suspensions and (2) that IFNγ elicits IFNAR-independent expression of CD69 on B cells but not T cells.

235

A B cells CD4 T cells CD8 T cells +ve +ve +ve CD69 CD69 CD69

WT KO WT KO KO WT

CD69 B

Figure 6.9: In vitro stimulation with IFNγ induces interferon α/β receptor (IFNAR) dependent and independent CD69 expression Cell suspensions generated from the non-draining lymph nodes and spleens of wild-type and IFNAR-deficient (KO) mice were subjected to 5.5 hours of in vitro stimulation with 20ng/ml IFNγ. (A) Representative flow cytometry histograms comparing the expression of CD69 by IFNγ-stimulated wild-type (WT) and IFNAR-deficient (KO) B cells, CD4 T cells and CD8 T cells. (B) The percentage of wild-type (WT) and IFNAR-deficient (KO) CD69+ve B cells, CD4 T cells and CD8 T cells following in vitro stimulation of lymph node cell suspensions with IFNγ. (C) The percentage of wild-type (WT) and IFNAR-deficient (KO) CD69+ve B cells, CD4 T cells and CD8 T cells following in vitro stimulation of spleen cell suspensions with IFNγ. Sample sizes: n = 4 x WT LN cell suspensions, 3 x KO LN cell suspensions, 4 x WT SPL cell suspensions and 4 x KO SPL cell suspensions. NC3Rs: 8 mice in total. IFNγ: interferon-gamma, IFNAR: interferon αβ receptor, WT: wild-type, KO: IFNAR-deficient. The Mann Whitney U test was used to determine statistical significance. *p<0.05, # = p<0.01 relative to respective unstimulated cells. N.B. due to insufficient cell yield, IFNγ stimulation of lymph node cells could only be performed for 3 of the 4 IFNAR-deficient mice – hence the lack of statistical analysis for this condition in (B).

236

6.3.8 In vitro re-stimulation of cell suspensions generated from KEC- draining lymph nodes with KEC induces IFNAR-independent CD69 expression by T cells Figures 6.8 and 6.9 demonstrate that B cells exhibit IFNAR-independent upregulation of CD69 following in vitro stimulation with either KEC or IFNγ, whilst T cells do not. This pattern of CD69 expression is also observed in vivo in the KEC-draining LNs of IFNAR-deficient mice (Figure 6.5). These findings suggest that type I IFNs are non-redundant for CD69 expression on T cells. Figures 6.10A and 6.10B refute this hypothesis, as it depicts IFNAR-independent expression of CD69 on CD4 (Figure 6.10A) and CD8 (Figure 6.10B) T cells following re-stimulation of cell suspensions generated from 12-hour KEC-draining LNs with KEC in vitro. Notably, this IFNAR- independent CD69 expression was more pronounced on CD8 T cells relative to CD4 T cells (Figure 6.10C). These findings demonstrate that whilst T cells are resistant to IFNAR- independent CD69 expression relative to B cells, this resistance is not absolute and can be overcome through repeated stimulation.

Figure 6.10: Re-stimulation of KEC-draining lymph node cells with KEC in vitro induces IFNAR-independent CD69 expression by T cells Cell suspensions generated from the draining lymph nodes of wild-type and IFNAR-deficient (KO) mice 12 hours following injection of KEC were subjected to 5.5 hours of in vitro stimulation with 7.5. x 107 killed E. coli (KEC). (A-B) The effect of in vitro KEC stimulation upon the percentage of CD69+ve (A) CD4 and (B) CD8 T cells within draining lymph node cell suspensions derived from wild-type and IFNAR deficient mice. (C) A paired analysis of the percentage of CD69+ve CD4 T cells and CD8 T cells within the same lymph node cell suspension. Sample sizes: n = 5 x WT 12hr draining LN cell suspensions and 6 x IFNAR-deficient 12hr draining LN cell suspensions. NC3Rs: 11 mice in total. KEC: killed E. coli, IFNAR: interferon αβ receptor, WT: wild-type, KO: IFNAR-deficient. (A and B) The Mann Whitney U test was used to determine statistical significance. (C) The Wilcoxon matched pairs test was used to determine statistical significance. **p<0.01, * p<0.05.

237

6.3.9 The extent to which in vitro stimulation with KEC induces CD69 on T cells is positively correlated with the percentage of monocytes in the cell suspension Initial experiments in which cell suspensions were stimulated with KEC in vitro demonstrated that T cells within spleen cell suspensions exhibited greater CD69 expression than T cells within lymph node cell suspensions (Figure 6.11A). However, this difference was not observed upon repetition of these experiments, with T cells from both lymph node and spleen cell suspensions exhibiting similar upregulation of CD69 (Figure 6.11B). Closer examination of these data revealed a significant difference in the percentage of monocytes within the lymph node cell suspensions stimulated in these two sets of experiments (Figure 6.11C). As monocytes are present in spleen cell suspensions, these findings suggest that monocytes drive upregulation of CD69 on T cells. This hypothesis is supported by an analysis of this dataset demonstrating a strong positive correlation between the percentage of monocytes present within the cell suspension prior to stimulation and the percentage of CD69+ve T cells following stimulation (Figure 6.11D-F). Moreover, there is a marked temporal overlap between the infiltration of monocytes and the upregulation of CD69 on T cells within the KEC-draining LN (Supplementary Figure 6.16C). Further research is therefore warranted to establish whether these correlations reflect a causal relationship and thus whether infiltrating monocytes induce CD69 expression in the KEC-draining LN.

238

Figure 6.11: In vitro stimulation reveals a positive correlation between monocyte frequency and the percentage of CD69+ve T cells in a lymph node or spleen cell suspension Two separate experiments were performed in which cell suspensions generated from non-draining lymph nodes and spleens were stimulated in vitro with KEC for a period of 5.5 hours. (A-B) CD69 expression of CD4 T cells and CD8 T cells within these cell suspensions in (A) experiment 1 and (B) experiment 2. (C) The percentage of monocytes in the lymph node cell suspensions stimulated in experiments 1 and 2. (D-E) Analyses of the correlation between the percentage of monocytes prior to stimulation and the percentage of CD69+ve T cells following stimulation of (D) lymph node and (E) spleen cell suspensions with KEC in experiments 1 and 2. (F) Combined analysis of the date presented in (D-E). Sample sizes: (A) n = 5 x non-draining LN cell suspensions, 4 x spleen cell suspensions. (B) n = 6 x non-draining LN cell suspensions, 6 x spleen cell suspensions. (C-F) Data combined from (A-B) i.e. n = 11 x non-draining LN cell suspensions, 10 x spleen cell suspensions. NC3Rs: 12 mice in total. LN: lymph node, SPL: spleen, KEC: killed E. coli. (A – C) The Mann Whitney U test was used to determine statistical significance, **p<0.01, * p<0.05, # = p<0.05 relative to unstimulated. (D-F) Correlation values and significance were determined by the Pearson correlation coefficient.

239

6.3.10 Type I interferons impair the chemotaxis of T cells to sphingosine-1- phosphate (S1P) but B cells do not respond to this chemokine

Type I IFNs are known to impair sphingosine-1-phosphate (S1P) chemotaxis through the upregulation of CD69, which binds and internalises the S1P receptor S1PR1 from the lymphocyte cell surface (342,626). It was therefore hypothesised that the increased expression of CD69 exhibited by B cells following stimulation with type I IFNs would translate into a greater reduction in S1P chemotaxis among B cells relative to T cells. To test this hypothesis, steady state lymph node cell suspensions were exposed to an S1P concentration gradient in vitro through a transwell migration assay (depicted in Figures 6.12A and 6.12B). Consistent with a previous study conducted by Sensken et al (400), the presence of 10nM S1P in the bottom chamber of the transwell drove the transmigration of approximately 60,000 T cells from the starting population of 2 x 106 lymph node cells seeded in the top chamber of the transwell (Figure 6.12C). Moreover, pre-stimulation of lymph node cells with 10,000 units/ml IFNβ significantly reduced the number of T cells that transmigrated into the bottom chamber (Figure 6.12C). In contrast, the presence of 10nM S1P in the bottom chamber did not elicit any increase in the number of B cells in the bottom chamber (Figure 6.12C). Moreover, B cell migration was not observed at any concentration of S1P tested (1-20nM, see Supplementary Figure 6.17A). However, B cells were capable of migration towards the chemoattractant CXCL12, demonstrating that they did not exhibit a general defect in chemotaxis (Figure 6.12C). In order to determine whether lymphocytes in the dLN exhibit impaired S1P chemotaxis, cell suspensions generated from 19-hour and 24-hour KEC-draining LNs were subjected to this in vitro S1P chemotaxis assay. This experiment demonstrated that T cells from non-draining and draining LNs transmigrate to a similar extent, whilst B cells exhibit no transmigration (Figure 6.12D). The defect in B cell S1P chemotaxis precluded testing of the hypothesis that differential CD69 expression by T and B cells engenders differential chemotaxis towards S1P.

240

Figure 6.12: Type I interferons impair the chemotaxis of T cells to sphingosine-1-phosphate (S1P) Lymphocyte chemotaxis to S1P was assessed in vitro using a transwell migration assay. (A) Diagram of transwell system. (B) Representative flow cytometry dot plots demonstrating the cellular composition of the bottom chamber of the transwell following exposure to different chemotactic stimuli. (C) The number of T cells (left) and B cells (right) from non-draining lymph node cell suspensions that migrate into the bottom chamber of the transwell in response to S1P and CXCL12. Non-draining lymph node cell suspensions were incubated for 4 hours in vitro in the presence or absence of 10,000 units/ml IFNβ prior to chemotaxis. (D) The number of T cells (left) and B cells (right) from CTRL or 19hr-24hr KEC-draining lymph node cell suspensions that migrate into the bottom chamber of the transwell in response to S1P and CXCL12. Sample sizes: (C) n = 6 x non-draining lymph node cell suspensions divided and subjected to different chemotactic conditions (n =2 for CXCL12 positive controls). (D) n = 8 x draining lymph node cell suspensions (4 x 24hr LN and 4 x 19hr LN) divided and subjected to different chemotactic conditions (n = 2 for CXCL12 positive controls). NC3Rs: 14 mice in total. LN: lymph node, KEC: killed E. coli, S1P: sphingosine-1-phosphate, CTRL: non-draining LN cells (contralateral or inguinal LN), Ipsi: ipsilateral lymph node cells. The Mann Whitney U test was used to determine statistical significance, **p<0.01.

241

6.3.11 CD69+ve T cells exhibit impaired S1P chemotaxis relative to CD69-ve T cells

Because CD69 is known to impair S1P chemotaxis (342,626), one would expect that S1P induces the selective migration of CD69-ve lymphocytes in a transwell migration assay. Flow cytometry was therefore used to determine the proportions of CD69+ve cells in the top and bottom chambers of the transwell following S1P chemotaxis. This revealed that the percentage of CD69+ve T cells was lower in the bottom chamber relative to the top chamber in all contexts in which S1P chemotaxis was assessed (Figure 6.13A, B, D, E, F, H, I). This includes T cells among unstimulated and IFNβ-stimulated non-draining LN cell suspensions (Figure 6.13D-E) as well as T cells within 24-hour KEC-draining LN cell suspensions (Figure 6.13H). Indeed, CD69+ve T cells harvested from the 24-hour KEC-draining LN exhibited the largest defect in transmigration relative to their CD69-ve counterparts. (Figure 6.13H). This demonstrates that S1P preferentially induces the chemotaxis of CD69-ve T cells relative to CD69+ve T cells in a transwell migration. That this effect is specific to S1P is suggested by the unimpaired CXCL12 chemotaxis exhibited by CD69+ve T cells (Figures 6.13F and I). The fact that S1P-dependent chemotaxis of CD4 and CD8 T cells was not investigated in this study represents a missed opportunity. This resulted from the fact that the differential CD69 expression exhibited by CD4 and CD8 T cells in the KEC-draining LN was not appreciated at the time of these experiments. Overall, these findings demonstrate that CD69 expression limits the chemotaxis of T cells to S1P and that this is especially true of CD69+ve T cells in the KEC-draining LN.

A notable but separate finding was that the percentage of CD69+ve T cells and B cells is increased among the small numbers of T cells that transmigrate into the bottom chamber in the absence of any chemotactic stimulus (Figures 6.13C and G). This chemokine-independent migration suggests that CD69+ve T cells exhibit a higher degree of random motility relative to CD69-ve T cells.

242

Figure 6.13: CD69+ve T cells exhibit impaired S1P chemotaxis (A-B) Representative flow cytometry plots illustrating the CD69+ve T cell populations in the top and bottom chambers of a transwell after (A) non-draining lymph node and (B) draining lymph node cell suspensions are subjected to S1P chemotaxis. (C-F) Graphs illustrating the difference in CD69 expression in the top and bottom chambers of transwells following exposure of non-draining lymph node cell suspensions to (C) no chemokine, (D) S1P, (E) S1P after IFNβ stimulation and (F) CXCL12. (G-I) Graphs illustrating the difference in CD69 expression in the top and bottom chambers of transwells following exposure of draining lymph node cell suspensions to (G) no chemokine, (H) S1P and (I) CXCL12. Sample sizes: (C-F) n = 6 x non-draining lymph node cell suspensions divided and subjected to different chemotactic conditions (n =2 for CXCL12 positive controls). (G-I) n = 8 x draining lymph node cell suspensions (4 x 24hr LN and 4 x 19hr LN) divided and subjected to different chemotactic conditions (n = 2 for CXCL12 positive controls). NC3Rs: 14 mice in total. LN: lymph node, KEC: killed E. coli, S1P: sphingosine-1-phosphate. The Wilcoxon matched pairs test was used to test for statistical significance. *p<0.05, **p<0.01 Top>Bottom, # p<0.05 Bottom > Top.

243

6.3.12 B cells accumulate in the KEC-draining lymph node to a greater extent than T cells

The skin injection of KEC into the murine earflap rapidly and substantially increases the cellularity of the draining superficial parotid lymph node (Figure 6.14A, see also Supplementary Figure 3.11C of Chapter 3). The rate of lymphocyte egress is one of the parameters that determine lymphocyte accumulation in the dLN. Thus, the hypothesis that the differential CD69 expression exhibited by lymphocyte subsets (B cells > CD8 T cells > CD4 T cells) determines differential lymph node egress rates predicts that lymphocyte subsets should differentially accumulate in the dLN. It is therefore notable that the B cells accumulate to a greater extent than T cells in the KEC-draining LN (Figure 6.14B-D). Indeed, whilst the ratio of B cells to T cells <1:1 in non-draining LNs, this ratio is significantly increased to >1:1 in the dLN 48 hours following injection of KEC (Figure 6.14D). These findings are therefore consistent with an increased retention of B cells owing to their increased expression of CD69. However, it is also notable that the dLNs of IFNAR-deficient mice accumulate lymphocytes to the same extent as the dLNs of wild-type mice during the first 12 hours following injection of KEC (Figure 6.14E). Moreover, no enrichment of B cells is observed in either wild-type or IFNAR-deficient dLNs during this time period (Figure 6.14F-G). These data suggest that if CD69 drives the preferential retention of B cells in the KEC-draining LN then the consequent B cell enrichment manifests itself between 12- and 48-hours following injection.

244

Figure 6.14: Lymphocytes exhibit differential accumulation in the draining lymph node (A) Live cell counts of draining lymph nodes harvested 2-48 hours following skin injection of KEC. (B) Representative flow cytometry plots illustrating the proportions of B and T Cells in CTRL and 48hr KEC-draining lymph nodes. (C-D) The (C) percentage of B cells and T cells and (D) the ratio of B cells to T cells in 2-48-hour KEC-draining lymph nodes. (F-G) The (F) percentage of B cells and T cells and (G) the ratio of B cells to T cells in the 12hr KEC-draining lymph nodes of wild-type and IFNAR- deficient mice. Sample sizes: (A-D) n = 4 x CTRL LN, 9 x contralateral LN, 4 x 2hr ipsi LN, 4 x 6hr ipsi LN, 4 x 24hr ipsi LN, 4 x 48hr ipsi LN. (E-G) n = 15 x WT contra LN, 15 x KO contra LN, 5 x WT 6hr LN, 6 x KO 6hr LN, 5 x WT 12hr LN and 6 x KO 12hr LN. NC3Rs: n = 44 mice in total. LN: lymph node, Ipsi: ipsilateral, CTRL: control, Con/ Contra: contralateral, KO: IFNAR-deficient, WT: wild-type. The Mann Whitney U test was used to determine statistical significance, *p<0.05, **p<0.01 relative to CTRL or contra LN, # = p<0.01 relative to respective contra LN

245

Supplementary Figure 6.15: Measurement of CD69 expression on B and T cells by median fluorescence intensity (MFI). Replication of Figure 6.3 but with CD69 expression measured by MFI as opposed to percentage of cells deemed positive. Figures A-F each consist of two graphs representing two different analyses of the same data. The left graph compares CD69 expression between T and B cells in draining and non-draining lymph nodes, whilst the right graph compares CD69 expression between T and B cells within the same lymph node. (A-F) Portrays this data for lymphocytes in the draining lymph node (A) 2, (B) 3, (C) 6, (D) 12, (E) 24 and (F) 48 hours following injection of KEC. (G) A summation of the data presented in (A-F). Sample sizes: n = 57 x CTRL LN, 4 x 2hr LN, 4 x 3hr LN, 18 x 6hr LN, 15 x 12hr LN, 8 x 24hr LN and 4 x 48hr LN. NC3Rs: 63 mice in total. LN: lymph node, Ipsi: ipsilateral, CTRL: control and contralateral, MFI: median fluorescence intensity. The Mann Whitney U test and the Wilcoxon matched pairs test were used to test for statistical significance in unpaired (left graphs) and paired (right graphs) analyses respectively *p<0.05, **p<0.01, ****p<0.0001. (G) error bars = standard deviation.

246

Supplementary Figure 6.16: The infiltration of monocytes is temporally associated with the upregulation of CD69 by T cells within the KEC-draining lymph node (A) Graphs that plot the percentage of monocytes against the percentage of CD69+ve T cells in draining lymph nodes 2-48 hours following injection of KEC. (B) Summation of all the data presented in (A). (C) Alternative presentation of the data presented in (A), illustrating the percentage of monocytes and the percentage of CD69+ve B cells (left) and CD69+ve T cells (right) in the draining lymph node over time. Sample sizes: n = 12 x CTRL LN, 4 x 2hr LN, 4 x 3hr LN, 11 x 6hr LN, 15 x 12hr LN, 8 x 24hr LN and 4 x 48hr LN. NC3Rs: 50 mice in total. LN: lymph node, CTRL: control and contralateral LN. Correlation values and significance were determined by the Pearson correlation coefficient. N.B. Data presented in this figure are combined from numerous experiments described in other parts of this thesis.

247

Supplementary Figure 6.17: The effects of sphingosine-1-phosphate concentration and in vitro pre- incubation on lymphocyte chemotaxis (A) The number of lymph node T cells (left) and B cells (right) that transmigrate into the bottom chamber of the transwell in response to 1-20nM S1P and 300ng/ml CXCL12. (B) The number of lymph node T cells (left) and B cells (right) that transmigrate into the bottom chamber of the transwell in response to 10nM S1P following 0, 2 or 4 hours of prior incubation. Sample sizes: (A) n = 14 x LN cell suspensions divided and cultured in the presence of 0nM S1P (n = 12), 1nM S1P (n = 2), 5nM S1P (n=2), 10nM S1P (n =14), 20nM S1P (n =1) or 300ng/ml CXCL12. (B) n = 16 x LN cell suspensions divided and cultured in the presence of 0nM or 10nM S1P following 0hr (n = 2), 2hr (n = 10) or 4 hours (n = 4) of prior incubation. NC3Rs: 14 mice in total. S1P: sphingosine-1-phosphate, hr: hour. The Mann Whitney U test was used to test for statistical significance, *p<0.05, ***p<0.001.

248

Supplementary Figure 6.18: The expression of interferon-stimulated genes (ISGs) by B and T cells relative to four different reference genes These data relate to Figure 6.7. Expression of the genes encoding CD69, IFIT1, IFIT2 and IFIT3 by T cells and B cells isolated by FACS from the draining lymph node 12 hours following injection of KEC. The expression of these genes relative to the following references genes (A) Ppia, (B) Hprt, (C) Actb, (D) B2m. Sample sizes: n = 3 x CTRL LN T cell samples, 3 x CTRL LN B cell samples, 3 x 12hr LN T cell samples and 3 x 12hr LN B cell samples. NCR3s: 9 mice in total. Each data point represents draining or non-draining (CTRL) lymph node cells pooled from 2-4 mice. LN: lymph node, CTRL: control or contralateral, T: T cells, B: B cells, KEC: killed E. coli. No statistical analysis was performed as n= 3 is insufficient to demonstrate significance using the Mann Whitney U test.

249

Figure 6.19: Flow cytometry of permeabilised lymphocytes does not reveal an intracellular store of CD69 Flow cytometry of permeabilised lymph node cells was used to compare the intracellular and extracellular expression of CD69. Extracellular CD69 expression refers to cells stained with an anti- CD69 antibody prior to permeabilization, whereas intracellular CD69 expression refers to cells stained an anti-CD69 antibody following permeabilization. (A) Representative flow cytometry histograms comparing the extracellular and intracellular expression of CD69 exhibited by B cells and T cells. (B) The percentage of CD69+ve B and T cells following extracellular (non-perm) and intracellular staining (perm) with an anti-CD69 antibody. (C) The median fluorescence intensity of CD69 on B and T cells following extracellular and intracellular staining with an anti-CD69 antibody. Perm = permeabilised. Sample size: n = 2 x LN cell suspensions.

250

6.4 Discussion

The data presented in this chapter demonstrate that the acute expression of CD69 observed in the KEC-draining LN is predominantly driven by type I IFNs (Figure 6.5). Moreover, these data also demonstrate that IFNγ and KEC can upregulate CD69 on lymphocytes independent of the interferon α/β receptor (IFNAR) (Figures 6.8 – 6.10). Further still, this chapter clearly demonstrates that B cells, CD4 T cells and CD8 T cells intrinsically differ in their regulation of CD69 expression. Indeed, the fact that both IFNAR-dependent and IFNAR-independent CD69 expression is greater among B cells relative to CD8 and CD4 T cells is the major novel finding of this chapter and it strongly suggests that B cells preferentially upregulate CD69 in the context of inflammation. Unfortunately, attempts to determine whether or not this differential CD69 expression translated to differences in S1P chemotaxis were inconclusive (Figures 6.12 and 6.13). Nevertheless, these findings entail important implications for the recirculation of different lymphocyte subsets through the dLN in the context of acute inflammation and these are discussed in the following sections.

6.4.1 IFNAR-dependent mechanisms of CD69 expression This chapter demonstrates that type I IFNs are the major driver of CD69 in KEC-draining LN. This is similar to previous studies, which have demonstrated that the TLR3 ligand poly IC, the TLR-4 ligand GLA-SE, the TLR9 ligand CpG-rich DNA and influenza infection also drive CD69 expression in the dLN in a largely type I IFN dependent manner (278,401,452,453). In order to elicit the production of type I IFNs, KEC must be recognised by pattern recognition receptors (PRRs). KEC likely stimulates multiple PRRs and the relative importance of each would be best determined by the injection of KEC into mice deficient for different PRRs. Toll-like receptor 4 (TLR4) is likely to be important, as lipopolysaccharide is a major component of the outer membrane of the E. coli cell wall and the TLR4 agonist GLA has been previously shown to elicit type I interferon-dependent CD69 expression in the dLN (278). The same is true of TLR9 ligands (453,658,659) and it is feasible that DNA released from E. coli bacteria lysed during the process of killing would agonise TLR9. The stimulation of PRRs could directly induce the production of type I IFNs or trigger the production of cytokines that then induce CD69 expression. The fact that IFNγ-driven expression of CD69 is partially dependent on IFNAR is evidence of the latter pathway. This is significant, as it suggests that IFNγ produced by NK cells within the KEC- draining LN (Figure 5.9, Chapter 5) may indirectly induce CD69 expression by potentiating the production of type I IFNs. Also notable is the strong positive correlation between monocytes and T cell CD69 expression in the context of in vitro stimulation with KEC (Figure 6.11). This

251 correlation suggests that monocytes are a source of either type I IFNs or another CD69- inducing cytokine in the dLN. Monocytes are unlikely to be the initial driver of CD69 expression in the KEC-draining LN as CD69 expression precedes their arrival into the dLN (Supplementary Figure 6.16C). However, the temporal association between monocyte infiltration and CD69 expression in the KEC-draining LN (Supplementary Figure 6.16C) suggests that monocytes may promote and maintain CD69 expression. This could be determined by profiling the expression of CD69 following the injection of KEC into mice genetically or pharmacologically rendered monocyte-deficient34. If this were shown, then the mechanism by which monocytes elicit T cell CD69 expression could be determined by the co-culture of purified populations of wild-type or IFNAR-deficient monocytes with T cells in the presence of KEC.

6.4.2 IFNAR-independent mechanisms of CD69 expression This chapter also identifies IFNAR-independent mechanisms of CD69 expression in the context of lymph node inflammation. In vivo, this was demonstrated by the small but significant increase in the percentage of CD69+ve B cells observed in dLNs of IFNAR-deficient mice (Figure 6.5A). In vitro experiments demonstrated that stimulation with either KEC or IFNγ elicits substantial IFNAR-independent upregulation of CD69 by B cells (Figures 6.8 and 6.9). The IFNAR-independent effect of KEC is particularly striking and could be a direct response of B cells to the bacteria, as LPS has been shown to induce CD69 expression on purified populations of B cells in a TLR4-dependent manner (656). The much smaller increase in IFNAR-dependent B cell CD69 expression observed in vivo could reflect poor access of KEC bacilli in the lymphatic sinuses to B cells within follicles. Indeed, in this context, the small increase in CD69+ve B cells could represent B cells underlying the subcapsular sinus that receive KEC bacteria from overlying macrophages (160,174).

It is notable that IFNAR-independent CD69 expression was not observed on T cells following stimulation of non-draining LN or spleen cell suspensions with KEC and IFNγ (Figures 6.8 and 6.9) but was observed following KEC stimulation of cell suspensions generated from 12-hour KEC-draining LNs (Figure 6.10). The fact that CD69 expression was induced on 10-20% of T cells in these cultures strongly suggests that this does not reflect T cell receptor-driven CD69 expression. Rather, it suggests that IFNAR-deficient dLN cell suspensions produce a cytokine that can induce CD69 expression independent of IFNAR. IL-18 is a good candidate as IL-18 receptor deficient mice exhibit impaired T cell CD69 expression (278) and IL-18 can induce CD69 expression on purified populations of CD8 T cells (669). Moreover, IL-18 may contribute

34 By either genetic or pharmacological means 252 to IFNAR-dependent CD69 expression, as type I IFNs have been shown to be necessary for the production of IL-18 by monocytes (466). These data, combined with the increased expression of inflammasome-associated genes exhibited by monocytes (Figure 5.7, Chapter 5) and the positive correlation between monocytes and CD69 expression in vitro (Figure 6.11) suggests that interferon-stimulated monocytes may promote CD69 expression in the dLN via the production of IL-18.

6.4.3 Differential regulation of CD69 expression by lymphocyte subsets

The major finding of this chapter is the profound difference in CD69 expression exhibited by B cells, CD8 T cells and CD4 T cells (B cells > CD8 T cells > CD4 T cells). There is some precedent for this differential pattern of expression following in vitro stimulation of splenocytes with insect DNA or CpG DNA (B cells > CD8 T cells > CD4 T cells) (453) and in the dLN following injection of poly IC or infection with influenza (B cells > T cells) (84,641). This chapter builds upon these prior findings by (1) characterising the temporal profile of this differential CD69 expression in vitro and in vivo and (2) demonstrating that this pattern of CD69 expression is a remarkably conserved feature among lymphocytes in the context of inflammation. Indeed, this chapter demonstrates that this differential CD69 expression is observed following both in vivo and in vitro stimulation with KEC or IFNβ and is induced by both IFNAR-dependent and IFNAR- independent drivers of CD69 expression. It is thus pertinent to question how lymphocyte subsets differentially regulate CD69 expression.

The differential CD69 expression observed could be explained by lymphocyte subsets exhibiting differing levels of sensitivity to CD69-inducing stimuli. This theory predicts B cells are better able to detect and respond to the inflammatory stimuli used in this chapter, namely type I IFNs, IFNγ and KEC. B cells could exhibit such an increase in sensitivity by increased expression of receptors for these inflammatory stimuli relative to T cells or by differences in intracellular signalling upon receptor agonism. Similar differences in receptor expression and/or signalling would also have to be observed between CD4 and CD8 T cells according to this theory. No direct evidence of differences in the expression of the receptors for type I IFNs, IFNγ or the likely KEC PRRs, TLR4 and TLR9, could be found upon a literature search. In addition, the theory that B cells are more sensitive to type I IFNs than T cells is undermined by the fact that B cells did not exhibit an overall increase in ISG expression relative to T cells in the KEC-draining LN (Figure 6.7). This suggests that cell-intrinsic differences in the transcriptional or post-transcriptional regulation of CD69 are responsible for its differential expression by B cells, CD4 T cells and CD8 T cells in response to type I IFNs.

253

As described in the introduction, the gene encoding CD69 is rapidly transcribed upon lymphocyte activation and harbours numerous regulatory elements. That CD69 transcription is differentially regulated in T and B cells is suggested by the fact that specific regulatory regions of the CD69 gene have been shown to differentially regulate the expression of a reporter gene in T cells and B cells (646). Moreover, the CD69 gene harbours different epigenetic modifications in B cells and T cells (646). It is thus plausible that increased transcription of CD69 in B cells relative to T cells underlies the differential CD69 expression demonstrated by flow cytometry in this thesis. However, this theory is somewhat undermined by fact that T and B cells isolated from the 12-hour KEC-draining LN express similar amounts of CD69 mRNA (Figure 6.7D and Supplementary Figure 6.18). Further work is therefore required to establish whether or not CD69 is differentially transcribed by different lymphocyte subsets. Firstly, a transcription inhibitor such as actinomycin D would determine whether CD69 transcription is required for the increased CD69 expression observed following in vitro stimulation with type I IFNs. This finding would exclude a role for putative intracellular stores of CD69 (677), which could not be demonstrated using flow cytometry of permeabilised lymphocytes (Supplementary Figure 6.19). Secondly, a qRT-PCR time course of CD69 expression following stimulation of purified populations of B cells, CD4 T cells and CD8 T cells would be informative. This is because CD69 transcription has been shown to be both rapid and transient (671,674) and any difference in CD69 mRNA may only be evident at the peak of transcription. If this was shown then it would strongly suggest that transcription is the primary driver of differential CD69 expression exhibited by lymphocyte subsets, although it would not exclude a role for post-transcriptional mechanisms of regulation. Further research is also required to identify the mechanisms through which type I IFNs increase CD69 expression. Indeed, despite the multitude of regulatory elements present in the CD69 gene, only one is directly associated with type I IFNs (an IRF4 binding site located in intron 1 (668)) and its relative importance in CD69 regulation is unknown.

In summary, the expression of CD69 is clearly a highly regulated process. This chapter highlights the fact that CD69 is differentially expressed by different lymphocyte subsets with B in particular intrinsically primed to rapidly upregulate CD69. Further experiments are required to determine the mechanisms that underpin this differential pattern of CD69 expression.

254

6.4.4 Regulation of lymphocyte sphingosine-1-phosphate (S1P) chemotaxis by CD69

CD69 is known to limit the S1P-dependent egress of lymphocytes from the lymph node parenchyma into efferent lymph. It was thus hypothesised that due to their increased CD69 expression, interferon-stimulated B cells would exhibit a greater impairment in S1P chemotaxis relative to T cells. Unfortunately, attempts to test this hypothesis using an in vitro S1P chemotaxis assay failed, as B cell S1P chemotaxis could not be elicited. This discussion will first address the potential reasons for this unexpected finding before further discussing evidence supporting this hypothesis and its biological implications.

6.4.5 Analysis of the impaired S1P chemotaxis exhibited by B cells

The impaired B cell migration to S1P described in Figure 6.12 was an unexpected finding. This is because several studies have previously shown that B cells exhibit S1P chemotaxis in the same model system (107,146,342,400). Indeed, there is no clear methodological reason to explain the observed defect in B cell S1P chemotaxis (Table 6.1)35. The fact that B cells exhibit robust CXCL12 chemotaxis shows that they do not harbour any general chemotactic defect (Figure 6.12). Moreover, the S1P chemotaxis exhibited by T cells within the same cell suspension demonstrates that S1P was an active chemoattractant in this model system (Figure 6.12). It is thus unclear why B cells did not migrate to S1P in these experiments.

No previous studies have reported that B cells are incapable of S1P chemotaxis as demonstrated in Figure 6.12. However, close examination of prior studies reveals that B cells do exhibit decreased S1P chemotaxis relative to T cells, although this difference is not commented upon (148,342,400). Moreover, there is precedent for differential S1P migration among other lymphocyte subsets; namely between CD4 and CD8 T cells (126) and between follicular and marginal zone B cells (146,695). It is therefore possible that the lack of B cell S1P chemotaxis observed in this thesis may reflect a true difference in T cell and B cell S1P sensitivity. If this is the case, then any factor that impairs S1P chemotaxis could ablate B cell chemotaxis but preserve T cell chemotaxis. Counterintuitively, S1P itself is the most likely cause of such an impairment in S1P chemotaxis. This is because S1P induces the internalisation and degradation of its receptor S1P1, rendering lymphocytes unresponsive to further stimulation with S1P (148,152). Indeed, such agonist-induced desensitisation is one of the

35In addition, this finding was discussed by email with Professor Mehrdad Matloubian and Dr Joao Pereira (who have both published work on S1P-driven lymphocyte chemotaxis) and they were also unable to account for this finding. 255 mechanisms of action of the novel immunomodulatory agent fingolimod (151,696). Crucially, Sensken et al (400) demonstrated that freshly isolated lymph node cells exhibit impaired S1P chemotaxis because of their prior exposure to S1P in the lymph node microenvironment. Indeed, the incubation of isolated lymph node lymphocytes in S1P-deprived medium for 1-3 hours prior to chemotaxis increased their subsequent migration, a finding that is replicated in Supplementary Figure 6.17. Even though the lymphocytes described in Figures 6.12 were incubated for 2-4 hours in S1P-deprived medium prior to chemotaxis, the lack of B cell migration observed may nevertheless be due to prior exposure to contaminating S1P from the lymph node microenvironment.

This discussion therefore suggests number of methods through which B cell S1P chemotaxis could be restored. This includes increased washing of lymph node cell suspensions to remove contaminating S1P36 and longer incubation of lymph node cell suspensions prior to chemotaxis in order to allow more time for B cells to regain sensitivity to S1P. In this regard, analysis of S1P1 expression on B cells would be informative as a reduction in this would be indicative of their desensitisation to S1P (148,152). If S1P chemotaxis were recovered using these measures then this would facilitate testing of the original hypothesis regarding the effect of differential CD69 expression on S1P chemotaxis. Moreover, the demonstration of a difference in S1P sensitivity between T and B cells would be a novel finding in itself that could explain the differences in lymphocyte egress exhibited by T and B cells in the steady state (125).

6.4.6 Implications of differential CD69 expression on lymphocyte egress from the draining lymph node

The hypothesis that the differential CD69 expression observed in this chapter serves to differentially regulate lymphocyte egress from the dLN is supported by two pieces of evidence. Firstly, the preferential accumulation of B cells observed in the KEC-draining LN (Figure 6.14C and D) is consistent with the increased CD69 expression exhibited by B cells relative to T cells. Secondly, lymphocyte subsets are known to differ in their rates of egress from lymph nodes in the steady state (125,126). Strikingly, the pattern of CD69 expression observed in the KEC- draining LN (B cells > CD8 T cells > CD4 T cells) mirrors the differences in lymphocyte egress rate observed in the steady state (CD4 T cells > CD8 T cells > B cells (125,126). It is therefore

36 In this regard, it is notable that lymph node cells were subjected to fewer washes prior to chemotaxis in this study compared to Sensken et al (400). The concentration of contaminating S1P may therefore be higher in the chemotaxis assays performed in this thesis. 256 reasonable to hypothesise that the differential CD69 expression observed in the KEC-draining LN serves to reinforce the pattern of lymphocyte egress that exists in the steady state.

This hypothesis requires two key experiments to provide supporting evidence. Firstly, it would be necessary to quantify the egress rates of different lymphocyte subsets from the KEC- draining LN. This could be achieved using the same methods used to determine egress rates in the steady state (125,126). As per Mandl et al (126), lymphocytes could be adoptively transferred prior to the induction of lymph node inflammation and their rate of egress determined by their frequencies in the dLN at different time points following entry blockade. Surprisingly, no previous studies have determined the egress rates of different lymphocyte subsets in the context of inflammation and this in itself would be novel research. The relative importance of CD69 in this context could be then be determined by comparing the egress rates of adoptively transferred WT and CD69-deficient B cells, CD4 T cells and CD8 T cells from the KEC-draining LN.

The continual recirculation of lymphocytes between blood and secondary lymphoid organs is an evolved mechanism that optimises the detection of antigen by the small number of cognate lymphocytes present at any given time. As CD4+ve T cells, CD8+ve T cells and B cells recognise antigens in different forms37, it is conceivable that differences in lymph node egress rates optimise their detection of each of these different forms of antigen. No research has been undertaken to address this question, despite the known differences in lymphocyte egress rate in the steady state (125,126). Alternatively, it is possible that differential CD69 expression serves to bolster the innate barrier function of the dLN. Indeed, CD69 and S1P1 have been shown to be (659,689–691,697) important regulators of lymphocyte and dendritic cell egress from inflamed peripheral tissues. Thus, the differential expression of CD69 may act to limit pathogen dissemination through the preferential accumulation of CD8 T cells and B cells.

6.4.7 Conclusion

The data presented in this chapter comprehensively characterises CD69 expression in the inflamed dLN and sheds new light on the mechanisms by which CD69 is regulated during inflammation. Moreover, this chapter highlights a profound difference in CD69 expression between lymphocyte subsets and explores the effects this has on lymphocyte chemotaxis. Indeed, the data presented in this chapter proposes a series of novel experiments that would

37 MHC-II: peptide complexes, MHC-I: peptide complexes and intact antigen respectively 257 significantly contribute to the study of lymphocyte recirculation in the steady state and during inflammation.

258

Table 6.1: Comparison of S1P Chemotaxis Methods

Transwell Chemotaxis Media Pre-Chemotaxis Cells seeded into Chemotaxi S1P Incubation top chamber s Duration Concentration This 24-well, polycarbonate RPMI 1640, 0.1% w/v fatty-acid free 0hr, 2hr, 4hr 2 x 106 lymph node 3 hours 1nM, 5nM, 10nM. Thesis membrane (bare), 5μm pore size, BSA, 100U/ml penicillin, 100ug/ml cells in 100μl 20nM (Corning, 3421). streptomycin, 2mM L-glutamine and volume 25mM HEPES buffer Sensken 24-well, polycarbonate RPMI 1640, 0.1% w/v fatty-acid free 0hr, 1hr, 2hr, 3hr 2 x 106 lymph node 4 hours 20nM et al (400) membrane (collagen-coated), BSA, 100U/ml penicillin, 100mg/ml cells in 100μl 5μm pore size, (Corning). streptomycin, 2mM L-glutamine and volume 25mM HEPES buffer

Shiow et ‘Transwell filter’ (bare), 5μm pore Not stated 0hr - T cells Purified T cells and 3 hours 1nM, 10nM, al (342) size, (Corning). 10hrs - B cells38 B cells 100nM, 1μM.

Sinha et al 24 well, transwell chamber, 5μm Not stated N/A Isolated B cells 2 hours 10nM, 25nM. (146) pore size, (Corning). 50nM, 75nM, 100nM Kleinwort 24 well plate, 5μm pore size Not stated N/A 5 x 105 Peritoneal Not stated 1nM, 10nM, 50nM, et al (695) transwell inserts, (Grenier). cells 100nM, 1μM.

38 From text of Shiow et al ‘Although B cells migrate poorly to S1P directly ex vivo, they acquire increased chemotactic responsiveness after several hours in vitro incubation (Fig. 1f)’.

259

7 Discussion

7.1 Summary of findings

This thesis seeks to characterise the regulation and function of innate pathways in the draining lymph node (dLN) following a skin challenge with killed E. coli (KEC). The following key findings were established in the results chapters (see Figure 7.1 for a diagrammatic representation):

• Neutrophils and Ly6Chi monocytes rapidly infiltrate into the draining lymph node following skin challenge with killed E. coli.

• Infiltrating neutrophils and Ly6Chi monocytes have been identified as major expressers of various cardinal inflammatory mediators. This includes prostanoid synthases (COX- 2, mPGES-1, TBXAS) chemokines (CCL2, CXCL9, CXCL10) and inflammasome components (NLRP3, IL-1β).

• Type I interferons are rapidly active in the draining lymph node and modulate gene expression in infiltrating neutrophils and Ly6Chi monocytes as well as lymphocytes

• Type I interferons are redundant for the infiltration of neutrophils and Ly6Chi monocytes but are necessary for the production of IFNγ by NK cells in the dLN.

• Type I Interferons indirectly drive NK cell IFNγ production by inducing the production of an unidentified mediator, which is likely produced by infiltrating monocytes.

• Type I interferons drive the differential expression of the activation marker CD69 on different lymphocyte subsets (in B cells to the greatest extent, followed by CD8 T cells, then CD4 T cells), which has implications for the recirculation of lymphocytes through the draining lymph node.

This thesis places a strong emphasis upon characterising the infiltration kinetics and expression profiles of neutrophils and Ly6Chi monocytes within the dLN and identifies a clear relationship between type I interferons (IFNs) and infiltrating myeloid cells within the dLN. Therefore, I propose that type I IFNs are central regulators of the function of these myeloid cells; in particular Ly6Chi monocytes as they infiltrate the dLN in greater numbers and for a longer duration than neutrophils (Figure 3.9B). This discussion will address these insights into the relationship between type I IFNs and Ly6Chi monocytes, the hypotheses they generate and the methods by which to test them. This will be followed by a wider discussion of the implications of these findings upon our current understanding of innate immune pathways within the dLN and the field of adjuvant design.

260

Figure 7.1: Diagrammatic representation of main thesis findings. Visual representation of innate immune pathways characterised in the KEC-draining lymph node and their relationship with each other. This includes neutrophil and Ly6Chi monocyte infiltration and their expression profiles, type I interferon signalling, IFNγ production by NK cells and CD8 T cells and the differential upregulation of CD69 exhibited by B and T cells. Created with biorender.com.

261

7.2 The relationship between type I interferons and Ly6Chi monocytes within the draining lymph node

7.2.1 Ly6Chi monocytes as effectors of type I interferon responses in the draining lymph node This thesis provides strong evidence that type I IFNs heavily modulate gene expression within dLN-infiltrating Ly6Chimonocytes, as they exhibit significant upregulation of classic interferon- stimulated genes (ISGs) (Figure 5.3B) and the interferon-driven inflammatory mediators CCL2, CXCL9, CXCL10, NLRP3 and pro-IL-1β (Figures 5.5 D-E, 5.6A-C and 5.7A,C,F and G), as well as the IFNAR-dependent upregulation of CD69 (Figure 5.3C). Surprisingly, type I IFNs were shown to be dispensable for the infiltration of Ly6Chi monocytes into the dLN, in stark contrast to previous descriptions of monocyte infiltration into virus-infected tissues (395,466,698) and their dLNs (381). This novel finding has very recently39 been replicated by McCarthy et al (399), who describe type I IFN-independent monocyte infiltration into the dLN in the context of Chikungunya virus infection. Rather than type I IFNs, this study highlights a non-redundant role for MyD88 in dLN monocyte infiltration, something that has also been described in the context of ectromelia virus infection (465) and is likely to apply to the KEC-draining lymph node (KEC- draining LN) as Myd88 signalling is induced following challenge with KEC (699). Since type I IFNs are redundant for monocyte recruitment, it is pertinent to question the function of type I IFN stimulated Ly6Chimonocytes in the KEC-draining LN. Figures 5.10A-D demonstrate that type I IFNs are required for the rapid expression of IFNγ by NK cells and CD8 T cells in the dLN and as discussed in Chapter 5 (Section 5.4.5) I hypothesise that type I IFNs indirectly stimulate IFNγ production via the activation of monocytes. This is based on evidence from this thesis and the wider literature. With regard to the former, it is clear that NK cell IFNγ production can be driven in the absence of IFNAR (Figure 5.13D) and that stimulation with type I IFNs alone is insufficient to elicit IFNγ production. Moreover, analysis of the in vitro experiments conducted in Chapter 5 demonstrates a strong positive correlation between the percentage of Ly6Chimonocytes in a cell suspension and the percentage of IFNγ+ve NK cells following stimulation (Figures 5.14C-G). With regards to the wider literature, Coombes et al (355) have demonstrated that monocytes isolated from dLNs can potently stimulate NK cells to produce IFNγ ex vivo. Moreover, Lee et al (466) have demonstrated that type I IFN-activated monocytes drive NK cell IFNγ production in HSV-infected vaginal tissue via the production of

39 This study was published after the experiments presented in this thesis were completed 262 inflammasome-derived IL-18. Thus, in summary, the following hypothesis can be inferred from existing evidence and these novel findings:

Inflammatory monocytes infiltrating the draining lymph node are activated by type I interferons to induce the production of IFNγ by NK cells and CD8 T cells via activation of the inflammasome.

In addition to IFNγ production, type I IFNs are also the dominant driver of the CD69 upregulation evident in the KEC-draining LN (Figures 6.5A-B). However, there is also evidence to suggest that Ly6Chimonocytes also drive CD69 upregulation in the dLN. Firstly, the percentage of monocytes in cell suspensions positively correlates with CD69 upregulation on T cells following in vitro stimulation (Figures 6.11D-F) and the temporal kinetics of monocyte infiltration closely match the expression of CD69 in vivo (Supplementary Figure 6.16C). Secondly, monocytes are known to be a crucial source of type I IFNs in the dLN in other models (465,700), although only a very small increase in their expression by monocytes was detectable by qRT-PCR in this model (Figure 5.4H). Thirdly, monocytes strongly express the inflammasome components NLRP3 and pro-IL-1b and the inflammasome has been shown to drive CD69 upregulation on lymphocytes within the dLN (296) and the inflammasome product IL-18 upregulates CD69 on T cells (669). It is therefore possible that type I IFN-activated monocytes assemble inflammasomes that contribute to CD69 upregulation on lymphocytes within the dLN. The hypothesis outlined above can therefore be updated as follows (diagrammatic depiction in Figure 7.2):

Ly6Chi monocytes infiltrating the draining lymph node are activated by type I interferons to induce the production of IFNγ by NK cells and CD8 T cells as well as the expression of CD69 by lymphocytes via activation of the inflammasome.

Several methods could be used to test this hypothesis. Primary amongst these would be to determine the effect of monocyte depletion upon the percentages of IFNγ+ve NK/CD8 T cells and CD69+ve lymphocytes in the dLN (Figure 7.3). The value of such an approach is that it would immediately refute the outlined hypothesis if monocyte depletion had no effect upon these parameters. Monocyte depletion could be achieved with the anti-CCR2 antibody clone MC-21, a single intraperitoneal dose of which should be sufficient to deplete monocytes for up to 72 hours (701–704). One alternative would be to use CCR2-deficient mice, which are known to exhibit grossly impaired monocyte infiltration into the dLN (205,381). Another alternative would be to utilise CCR2-DTR mice, which unlike CCR2-deficient mice facilitate time-specific and transient depletion of monocytes (398,705–708). With regard to the details of the experimental design, this hypothesis asserts that monocytes are fundamental to IFNγ

263 production and thus it is reasonable to predict a 50% reduction in this parameter at the very least. Based on the data presented in this thesis, a 50% reduction in the percentage of IFNγ+ve NK cells at a significance level of 0.05 with a statistical power of 90% would require a sample size of 6 mice per group (Figure 7.3B). The actual required sample size is likely to be smaller as one would expect a larger reduction in IFNγ production than 50% (Figure 7.3B). A prediction of a 50% reduction in lymphocyte CD69 expression is reasonable as Seydoux et al (296) have reported an approximately 50% reduction in dLN-lymphocyte CD69 expression in the context of inflammasome deficient mice challenged with the TLR-4 based adjuvant GLA-SE. A sample size of 8 mice per group would be required to demonstrate a 50% reduction in lymphocyte CD69 expression in the KEC-draining LN at a significance level of 0.05 with a statistical power of 90% (Figure 7.3C). Thus, a sample size of 8 mice per group would be sufficient to test both elements of outlined hypothesis. Indeed, this one experiment has the power to refute the outlined hypothesis and is therefore essential prior to further exploration of the mechanisms that this hypothesis proposes.

7.2.2 Inflammasome activation as the link between Ly6Chi monocytes and type I interferons The hypothesis outlined in the previous section (diagrammatically represented in Figure 7.2) asserts that type I IFNs exert their positive effect on IFNγ expression and CD69 expression via inflammasome activation within infiltrating Ly6Chi monocytes. This is supported by the increased expression of the inflammasome components NLRP3, IL-1β and IL-18 exhibited by monocytes infiltrating the KEC-draining LN (Figure 5.7F-H). Moreover, ASC and IL-18R deficient mice exhibit impaired IFNγ production (72,278,296) and reduced CD69 upregulation (296)40 in the dLNs of mice challenged with TLR-4 agonising adjuvant GLA-SE. Finally, Lee et al (466) demonstrate that type I IFN mediated inflammasome activation is the mechanism by which monocytes stimulate NK cell IFNγ production in virally infected vaginal tissue.

If one assumes that Ly6Chi monocytes are central to the processes of IFNγ production and CD69 upregulation as suggested, then it would be pertinent to determine the relative importance of inflammasome activation with regards to this monocyte function. This would be best achieved through targeted deletion of a gene encoding a cardinal inflammasome component (e.g. ASC) specifically within monocytes. However, this approach is complicated by the fact that a truly monocyte-specific Cre/LoxP system does not yet exist (709). LysM-Cre and CX3CR1-Cre mice can be used to study monocytes but the former also targets neutrophils (709) and both models

40 IL-18 is also known to directly upregulate CD69 on T cells in vitro (669) 264 target lymph node (LN) resident macrophages (69,710). CCR2-Cre or CCR2 Cre-ER mice are likely to be more specific as they target monocytes (705,711) with evidence that they spare LN resident macrophages (712), although they deplete resident macrophages in other tissues (705). Similarly, bone marrow chimeras would also likely result in gene deletion in LN-resident macrophages (69). Whilst imperfect, utilisation of any of these Cre-LoxP models to target deletion of the type I IFN receptor (IFNAR) or cardinal inflammasome components (e.g. ASC, NLRP3) would have the capacity to demonstrate whether IFNAR-activated myeloid cells operate via inflammasome activation. Further delineation of Ly6Chi monocytes as the key cell type could be undertaken by further supportive, albeit not definitive, experiments. For example, dLN-monocytes could be isolated from IFNAR or ASC-deficient mice by fluorescence- activated cell sorting and co-cultured with NK cells to see if they exhibit an impaired capacity to stimulate NK cell IFNγ production relative to dLN monocytes isolated from wild-type mice (akin to the methods described by Coombes et al (355)). Alternatively, the effects of monocyte depletion upon concentrations of the inflammasome-derived cytokines IL-1β and IL-18 within the dLN would also be informative. Nevertheless, it would be hard to fully dissociate between monocytes and LN-resident macrophages in the absence of monocyte-specific gene deletion.

265

Figure 7.2: Ly6Chi monocytes infiltrating the draining lymph node are activated by type I interferons to induce the production of IFNγ by NK cells and CD8 T cells as well as the expression of CD69 by lymphocytes via activation of the inflammasome. Created with biorender.com.

266

Figure 7.3: Experiment design to determine the impact of monocyte depletion on IFNγ production and CD69 upregulation in the draining lymph node. (A) Experiment outline. (B and C) Sample size calculations for number of mice required to demonstrate 50-90% reductions in the percentage of (B) IFNγ and C) CD69 expressing cells in draining lymph nodes at a significance level of 0.05 with a statistical power of 90%. (A) created with biorender.com.

267

7.2.3 Re-evaluation of the importance of infiltrating Ly6Chi monocytes relative to lymph node resident macrophages

One criticism of the hypothesis depicted in Figure 7.2 is that it places too much emphasis upon infiltrating Ly6Chi monocytes and does not consider the role of other innate immune cells within the dLN; neutrophils and LN resident macrophages in particular. With regard to neutrophils, it is notable that neutrophils exhibit the same patterns of gene expression as Ly6Chi monocytes in this thesis, including type I IFN-stimulated genes (Figures 5.3A and C), chemokines (Figures 5.5A-C and 5.6C) and inflammasome components (Figures 5.7E-H). However, as mentioned previously, neutrophils infiltrate the dLN in smaller numbers and for a shorter duration than monocytes (Figure 3.9B). It is therefore possible that neutrophils play a role in stimulating IFNγ production and CD69 upregulation, but if so, it is likely to be secondary to that of monocytes and restricted to very early time points. However, the argument that this hypothesis ignores the role of LN resident macrophages is more compelling. This is because LN resident macrophages are well-recognised to be amongst the first cells to capture microbes and antigens draining in afferent lymph (72,159,168–171) and are thereby thought to prevent the systemic spread of pathogens (72,170,173,350). Moreover, there is evidence that they are an important source of key pro-inflammatory mediators within the dLN including type I IFNs, IL-1α, IL-1β and IL-18 (72,170,171,266,328). These findings are invariably based on experiments that deplete LN resident macrophages using clodronate liposomes (72,170,171,266,350) or CD169-DTR mice (171,266)41. However, two crucial factors need to be borne in mind when interpreting such studies. Firstly, it is now recognised that a plethora of inflammatory stimuli induce the rapid death of subcapsular and medullary sinus macrophages en masse (171,328,713). Secondly, the depletion of LN resident macrophages or antagonism of the cytokines that they release impairs the infiltration of neutrophils42 (72,328), monocytes (328) and NK cells (172,307,328,356) into the dLN. The phenotypes described in mice depleted of LN resident macrophages may therefore reflect the functions of innate cells recruited by said macrophages rather than the effector functions of the macrophages per se.

The idea that monocytes perform effector functions attributed to LN resident macrophages is supported by a very recent study43 demonstrating that monocytes are primarily responsible for phagocytosis of the cellular debris generated by dying LN resident macrophages; a process that occurs within 24 hours following challenge with a novel nanoparticulate adjuvant (713).

41 The exception being Sagoo et al (328) as they implicate LN resident macrophages in inflammasome activation on the basis of imaging 42 Although this is refuted by Bogoslowski et al (173) who show that the depletion of LN resident macrophages does not impair the neutrophil influx induced by S. aureus 43 This study was published after the experiments presented in this thesis were completed 268

Notably, these monocytes were shown to present antigen and interact with antigen-specific T cells at levels comparable to dendritic cells (713). Moreover, Pizzagalli et al (712) have demonstrated that CD169-DTR and CCR2-deficient mice exhibit equivalent reductions in CXCL1 concentration in the dLN, which opens up the possibility that monocytes may be the source of mediators attributed to LN resident macrophages. However, contrary to the outlined hypothesis (Figure 7.2), Farsakoglu et al (356) have recently published evidence to suggest that LN resident macrophages directly activate NK cells in the dLN. Whilst this study utilised macrophage depletion experiments (with their aforementioned limitations), they also used imaging techniques to show that NK cells closely interact with LN resident macrophages (356). This suggests that LN macrophages do directly activate NK cells to some degree. Nevertheless, the effect of macrophage depletion on NK cell activation is only partial and the authors themselves admit they can’t exclude a role for other cell types. It could thus be argued that these findings are consistent with the hypothesis outlined in this discussion, envisaging that LN resident macrophages serve to activate a portion of NK cells very early on before dying and being replaced by infiltrating monocytes as the major effector cell. Thus, rather than ignoring LN resident macrophages, this hypothesis has the power to reshape our understanding of their function, potentially re-defining them as sentinel cells that serve to recruit the monocytes that activate NK cells in the dLN.

7.2.4 Functions of interferon-activated monocytes in the draining lymph node

7.2.4.1 Interferon-driven CXCR3 ligand production may be central to monocyte functions in the draining lymph node In tandem with the increasing focus on dLN monocytes, recent studies have strengthened links between type I IFNs and monocytes. For example, a novel IFN-stimulated response element (ISRE) reporter mouse identified monocytes as the chief cellular target of type I IFNs in the context of influenza infection (698). Furthermore, within the dLNs of Chikungunya-infected mice, infiltrating neutrophils and monocytes have been shown to damage lymph node architecture and impair B cell responses, in part through the type I IFN-driven expression of iNOS by monocytes (399). In contrast, Barbet et al illustrate that monocytes augment Tfh and B cell responses within the spleen through type I IFN-licensed activation of inflammasomes within monocytes (714), akin to the hypothesis outlined in Figure 7.2. This latter study is particularly interesting as it utilised killed and live E. coli as their inflammatory stimulus, albeit via the intraperitoneal route as opposed to the skin injection used in this thesis. However, the crucial difference with this study is that the monocytes described by Barbet et al (714) are of

269 the non-classical subtype (CX3CR1hi CCR2-ve Ly6C-ve) as opposed to the Ly6Chi classical monocytes described in this thesis (379,714,715). Indeed, Barbet et al (714) demonstrate that Ly6Chi monocytes are redundant for the Tfh differentiation they describe. Thus, Barbet et al (714) establish type I IFN driven inflammasome activation as a key pathway within splenic non- classical monocytes but the function of this pathway in classical Ly6Chi monocytes in the dLN is still unknown, underscoring the importance of the hypothesis and experiments proposed in figure 7.2 and 7.3.

In addition to the putative mechanisms by which type I IFNs activate Ly6Chi monocytes and drive IFNγ production and lymphocyte CD69 upregulation, it is pertinent to question how these processes may impact the wider functions of the dLN. Significant in this regard is the strong expression of the CXCR3 ligands CXCL9 and CXCL10 exhibited by dLN monocytes (Figure 5.5D- E). This notable as CXCR3 directs the trafficking of NK cells (172,241,307), CD8 memory T cells (70,329) and activated CD4 T cells (247) to and within the dLN. The fact that NK cells and CD8 T cells downregulate CXCR3 in the KEC-draining LN (Figures 5.5F-G) strongly suggests that they are responding to these chemokines, as CXCR3 is known to undergo agonist-induced internalisation (643,716). Notably, NK cells and CD8 T cells both produce IFNγ in the KEC- draining LN (Figure 5.10). Moreover, CXCL10 and CXCL9 are known to be predominantly driven by type I IFNs and IFNγ respectively (70,329,627). Altogether, this suggests that a positive feedback loop is established wherein type I IFNs stimulate Ly6Chi monocytes to produce CXCL10 and inflammasome products to recruit and activate CXCR3-expressing NK and CD8 memory T cells, which then produce IFNγ and thereby stimulate Ly6Chi monocytes to produce CXCL9 and recruit and activate further CXCR3+ve cells (Figure 7.4). Such a feedback loop would suggest that Ly6Chi monocytes, NK cells and CXCR3+ve CD8 memory T cells would cluster in the same location within the KEC-draining LN. Interestingly, monocyte/CD8 T cell/ NK cell clusters have been shown to co-localise with IFNγ and CXCL9 expression within the spleen during the acute phase of listeria infection (706,707,716). The question is therefore whether such clusters are also found in dLNs and if so where within the LN and to what purpose?

270

Figure 7.4: Proposed positive feedback loop between Ly6Chi monocytes, NK cells and CD8+ve memory T cells triggered by type I interferons and maintained by CXCR3 ligands and IFNγ 1) Type I IFN induce CXCL10, which attracts CXCR3+ve NK cells and CD8+ve memory T cells. 2) Type I IFN activated Ly6Chi monocytes assemble inflammasomes whose products stimulate recruited NK and T cells. 3) IFNγ from activated NK/T cells induces CXCL9 production by monocytes, which recruits further NK and T cells for activation. Created with biorender.com.

7.2.4.2 Ly6Chi monocytes, NK cells and CXCR3+ve T cells may exhibit CXCR3- dependent clustering in interfollicular and medullary regions of the draining lymph node With regard to the question of where Ly6Chi monocytes interact with NK cells and CD8+ve memory T cells, the medullary and interfollicular regions of the dLN are the most likely location. This is because CXCL9 and CXCL10 expression is concentrated in these regions (70,167,232,247,329) and NK cells (72,90,352,355), CXCR3+ve T cells (70,247,329) and IFNγ (72,90) have been visualised there as well. Indeed, the recruitment of T cells to these peripheral regions is CXCR3-dependent (70,247,329) and NK cells have also been shown to rapidly accumulate in peripheral subcapsular, interfollicular and medullary regions (90,172,232,355), with their IFNγ production dependent upon this peripheral positioning (90).

271

Moreover, the peripheral distribution of neutrophils demonstrated in the KEC-draining LN (Figure 3.6) shows that these regions are active areas of inflammation in this model. Finally, the aforementioned splenic NK/T cell/monocyte cell clusters localise to the marginal zone and adjacent regions of the red pulp (706,707,716), which are considered equivalent to peripheral regions of the lymph node (43). Nevertheless, in contrast to neutrophils (72,201,202,209,278,368,712), CXCR3+ve T cells (70,247,329) and NK cells (72,90,352,355), the localisation and trafficking of inflammatory Ly6Chi monocytes within the dLN are poorly understood and this represents a gap in our understanding of lymph node biology.

Monocytes have been described in various lymph node compartments, including the paracortex (242), medulla (263,399), interfollicular areas (232,381) and subcapsular sinus (399), although each of these studies uses methods that are flawed to some degree with regards to monocyte specificity44. The use of CX3CR1GFP/+ CCR2RFP/+ mice (in the work of De Giovanni (232) and Sammicheli et al (381)) represents the best method45 with almost 100% of all Ly6Chi monocytes being fluorescent in these mice, although it must be noted that only 51% of GFP RFP double-positive cells were Ly6Chi monocytes (381). This low specificity could be overcome through the adoptive transfer of CX3CR1GFP/+ CCR2RFP/+ Ly6Chi monocytes into wild- type mice and characterising their distribution within the KEC-draining LN relative to NK cells, memory CD8 T cells, IFNγ, CXCL9 and CXCL10 by immunofluorescence. Moreover, intravital imaging could be utilised to visualise interactions between monocytes, NK cells and CXCR3+ve CD8+ve memory T cells46, something that has thus far not been characterised in the aforementioned splenic studies47 (706,707,716). Even if these experiments failed to demonstrate such clustering, the characterisation of monocyte distribution within the dLN would address an important knowledge gap, especially if this were done at several time points, as the range of locations in which monocytes have been localised (albeit with limitations) (242,263,381,399) suggests that they may traffic between different lymph node compartments. Nevertheless, the primary hypothesis is that Ly6Chi monocytes, NK cells and T cells exhibit CXCR3-dependent clustering and IFNγ production within interfollicular and

44 De Koker et al (242) use CD64 to define monocytes, but this marker cannot be used to distinguish between infiltrating monocytes and resident macrophages. Cioncada et al (263) define monocyte- derived dendritic cells as CD11c+ve antigen+ve double positive cells but this approach fails to stain CD11c- ve or antigen-ve monocytes and false-positively stains antigen+ve bona fide dendritic cells. Sammicheli et al (381) define monocytes as CXC3CR1+ve CCR2+ve cells, although only 51% of CXC3CR1+ve CCR2+ve in the draining lymph node are CD11b+ve Ly6Chi monocytes. McCarthy et al (399) used GR-1 to stain monocytes but this antibody does not distinguish between neutrophils and monocytes. 45 In addition, it mirrors the CCR2-reporter mice used to characterise the cell clusters in the spleen (706,707) 46 Imaging the interactions of monocytes with NK cells would require a fluorescent NK cell reporter mouse strain such as NCR1GFP/+ mice (355) and necessitate the adoptive transfer of singly-fluorescent CCR2-reporter monocytes as per Soudja et al (706,707). 47 Admittedly, intravital imaging of the spleen is likely more technically challenging (717) 272 medullary regions of the dLN (Figure 7.5). This hypothesis has implications for our understanding of both innate and adaptive immunity within the dLN.

Figure 7.5: Putative intranodal localisation of CXCR3-dependent clusters of Ly6Chi monocytes, NK cells and CD8+ve T cells. Created with biorender.com.

7.2.4.3 Potential innate immune functions of Ly6Chi monocyte, NK cell, CD8+ve T cell clusters in the draining lymph node IFNγ reduces the numbers of bacteria within the dLN and limits their spread into the systemic circulation during the first 8 hours of a bacterial challenge (72). However, the mechanisms by which IFNγ mediates this innate barrier function within the dLN have not been elucidated. The positive feedback loop depicted in Figure 7.4 has the potential to shed light on this, as IFNγ could primarily function to amplify the local innate immune response through the further recruitment of NK cells and CXCR3+ve T cells via CXCL9 production. Notably, such a Ly6Chi monocyte/NK cell /CXCL9 axis functions within the female reproductive tract to rapidly recruit CD8+ve effector T cells in response to even low levels of inflammation (718). In addition, some NK cells and memory CD8+ve T cells are pre-positioned in the peripheral regions of lymph

273 nodes (70,72) and these pre-positioned cells may rapidly cluster with monocytes48 when they first arrive in order to help kick-start the positive feedback loop as soon as possible.

Once recruited and activated, NK cells and CXCR3+ve effector and/or memory T cells may contribute to innate control through direct killing of infected cells (70,622,719). In addition, they may act indirectly through the rapid mobilisation of neutrophils and monocytes (707) and licensing of their killing mechanisms (720). In this regard, it is notable that IFNγ increases iNOS and TNFα expression by monocytes (707,721). Moreover, IFNγ signalling within monocytes, dendritic cells and macrophages is crucial for acute control of listeria infection, and it is notable that these mice exhibit the aforementioned CXCR3-dependent clustering in the spleen (707). Indeed, as dLN monocytes are known to harbour antigens and pathogens in a variety of contexts (50,187,189,204–208), it is reasonable to hypothesise NK cells and CXCR3+ve CD8+ve memory T cells contribute to the innate barrier function of the dLN at least in part by the activation of killing mechanisms within dLN monocytes. This innate barrier function may be particularly strong in cases of re-infection. This is because memory CD8+ve T cells are the T cell subset most associated with CXCR3-driven peripheralisation within the dLN (46,47) and there is evidence that the activation of memory T cells by cognate antigen induces a stronger IFNγ response and better pathogen control in the spleen relative to bystander activation (722). Thus, it can be hypothesised that memory T cells are rapidly directed by CXCR3 ligands to scan infected Ly6Chi monocytes and that the recognition of cognate antigen potentiates IFNγ production and cluster formation (by supercharging the positive feedback loop outlined in Figure 7.449), resulting in the increased recruitment and activation of innate immune cells that neutralise pathogens and prevent their dissemination from the dLN (diagrammatic depicted in Figure 7.6).

48 or with LN resident macrophages prior to the arrival of monocytes 49 This is supported by Sung et al (329), who demonstrate much stronger CXCL9 expression in the dLN in the context of secondary infections relative to primary infections. 274

Figure 7.6: Putative innate immune functions of NK cell, CD8+ve memory T cell, Ly6Chi monocyte clusters 1) Direct cytotoxicity; NK cells and CD8+ve memory T cells are activated by infected monocytes and as a result induce cell death pathways in the latter. 2) IFNγ produced by NK cells and CD8+ve memory T cells activates killing mechanisms within monocytes harbouring pathogens in intracellular phagosomes. 3) Interferon-activated monocytes secrete chemokines that recruit neutrophils and further monocytes to phagocytose cell-free pathogens. Created with biorender.com.

275

7.2.4.4 Potential adaptive immune functions of Ly6Chi monocyte, NK cell, CD8+ve T cell clusters in the draining lymph node The question of how the proposed CXCR3-dependent clusters of Ly6Chi monocytes, NK cells and memory CD8+ve T cells and the resulting IFNγ production influences the developing adaptive immune responses is pertinent to the field of adjuvant design. Indeed, it is notable that Ly6Chi monocytes (242), NK cells (241), IFNγ (241,277,278), CXCR3 (247), inflammasomes (266,278,296) and type I IFN (279) have all been implicated in the optimal development of adaptive immune responses, especially Th1-biased T cell responses (241,242,247,278,279,296). Moreover, this animal data is supported by human studies that propose an association between acute IFNγ signatures in peripheral blood post-vaccination with the immunogenicity of the novel TLR-4-based combination adjuvant AS01 (277,283,308). The proposed model of CXCR3-dependent clustering and activation of Ly6Chi monocytes, NK cells and CXCR3+ve memory CD8+ve T cells has the potential to shed light on how this myriad of inflammatory pathways intersect to potentiate the developing adaptive immune response.

The initiation of adaptive immune responses requires the rapid selection of cognate lymphocytes from the naïve repertoire recirculating between the vascular and lymphatic systems (Section 1.2). Inflammasome activation accelerates this process by increasing lymphocyte numbers in the dLN (328). This may be achieved through increased lymphocyte recruitment from high endothelial venules and/or reduced lymphocyte egress via cortical lymphatic sinuses50. The notion that inflammasome activation reduces egress is supported by the fact that it has recently been shown to be responsible for approximately 50% of the CD69 upregulation exhibited by lymphocytes within the dLNs of mice challenged with the TLR-4- based adjuvant GLA-SE (296). Although type I IFNs are the major driver of CD69 expression in the KEC-draining LN (Figure 6.5A-B), and can act directly on lymphocytes (401,453), CXCR3- dependent clustering may amplify CD69 upregulation either via the production of other CD69- inducing cytokines (e.g. IL-18 (669) or IFNγ (Figure 6.9) or type I IFNs themselves through a positive feedback mechanism. One can envisage a situation in which CXCR3-dependent clustering helps to rapidly shut down lymphocyte egress from the dLN and thereby increase the rate at which the naïve lymphocyte repertoire is scanned for cognate lymphocytes51.

The fact that Ly6Chi monocytes (242), NK cells (241), IFNγ (241,277,278), CXCR3 (247), inflammasomes (278,296) and type I IFN (279) have all been implicated in the promotion of

50 Sagoo et al (328) demonstrate inflammasome-driven increases in lymphocyte numbers at 18 hours following challenge, which is too early for lymphocyte proliferation to contribute to this in any meaningful way. 51 Precisely why B cell, CD4 T cells and CD8 T cells differ so markedly in CD69 regulation (Figures 6.3 and 6.4) is an interesting but separate question that is addressed in the discussion section of Chapter 6. 276

Th1-biased T cell responses is striking, as the precise mechanisms that underpin the generation of Th1 T cells have not been elucidated. It is increasingly recognised that the activation of different T cell subsets is anatomically segregated within the dLN, with naïve CD4+ve T cells predominantly activated in the outer regions of the paracortex and naïve CD8+ve T cells predominantly activated in deeper regions of the paracortex (74,165,181,184)52. The idea that anatomical localisation within the dLN is fundamental to Th1 differentiation is supported by the work of Groom et al, who demonstrated that CXCR3 directs newly activated CD4+ve T cells to the interfollicular and medullary regions of the dLN and argue that this explains why CXCR3 is necessary for Th1 differentiation (247). Thus, newly activated CD4+ve T cells may be guided towards clusters CXCL9/10-producing Ly6Chi monocytes clustered with NK cells and memory CD8+ve T cells, which as discussed in Section 7.2.4.2 may also be located in the interfollicular and medullary regions of the dLN. Indeed, De Giovanni et al have very recently shown that antigen-specific CD4+ve T cells co-localise with Ly6Chi monocytes and NK cells within the interfollicular regions of LCMV-infected dLNs (232). It is therefore possible that such clusters help form an anatomical niche for Th1 differentiation, although this begs the question as to how they would drive this process.

A key feature that potentially links CXCR3-dependent clustering with Th1 polarisation is the fact that IFNγ can drive the differentiation of Ly6Chi monocytes into CD11c+ve MHC-II+ve monocyte-derived dendritic cells (Mo-DCs) that produce the Th1 polarising cytokine IL-12 (723,724). Notably, Ly6Chi monocytes upregulate the dendritic cell markers CD11c and MHC-II during the first 48 hours within the KEC-draining LN (Figure 3.8C). Furthermore, De Koker et al (242) have shown that such Ly6Chi CD11c+ve MHC-II+ve monocytes are the crucial source of IL-12 in the dLN that drives Th1 T cell differentiation following challenge with a CpG-based adjuvant. It would therefore be informative to determine whether monocytes in the KEC-draining LN also express IL-12 using IL-12 reporter mice as per Goldzsmid et al (724). In addition to IL-12, IFNγ itself can directly drive Th1 differentiation pathways as it induces expression of the canonical Th1 transcription factor T-bet within T cells (243,725). Indeed, even transient T-bet expression can bestow a lasting IFNγ-producing capacity upon T cells, as has been recently showed with respect to IFNγ-producing T-follicular helper cells (726). Thus, one can envisage a scenario in which CXCR3-dependent dependent clusters of activated NK cells, memory T cells and monocytes/monocyte-derived DCs attract newly activated naïve T cells in a CXCR3- dependent manner and then exposing them to the Th1 polarising effects of IL-12 and IFNγ (diagrammatically represented in Figure 7.7). One challenge to this hypothesis is the finding

52 Nevertheless, CD8 T cell activation has also been shown to occur in the cortical ridge, peripheral paracortex and interfollicular regions in other contexts (70,71,231). 277 that polarising cytokines such as IFNγ can permeate through the dLN and thereby polarise T cells remotely (251). There are questions about the extent to which this study accounts for potential concentration gradients for cytokines within the dLN as has been established for certain chemokines (88,90,220). However, if applicable it would undermine the outlined hypothesis and would suggest that the location of the proposed clusters of activated Ly6Chi monocytes, NK cells and memory CD8+ve T cells serves a different purpose, for example through direct cellular interactions with differentiating T cells.

A further challenge to this hypothesis stems from the very recent work of De Giovanni et al, who demonstrate that despite the co-localisation of monocytes and NK cells with activated CD4+ve T cells in interfollicular regions of the dLN, depletion of either of these cell types has no impact upon Th1 differentiation in the context of LCMV infection (232). This contradicts previous studies highlighting essential roles for monocytes and NK cells for this process following an adjuvant challenge (241,242). The importance of these cell subsets is therefore context-dependent and suggests that more than one innate immune pathway can drive Th1 differentiation. This very principle is illustrated by the study of De Giovanni et al (232), who demonstrate that an acute peak of type I IFN within the dLN is crucial to determining T cell fate between Tfh and Th1 cells in the context of VSV-infection but a much weaker role in the context of LCMV infection. Given the redundance for monocytes/Mo-DCs and NK cells illustrated by De Giovanni et al (232), it would be interesting to determine whether or not these cells exhibit similarly strong expression of CXCR3 ligands, inflammasome components and IFNγ within the context of their model in comparison to the model used in this thesis. Indeed, there is evidence that the functions of Mo-DCs extend beyond Th1 differentiation. For example, Mo-DCs have been implicated in the promotion of memory as opposed to effector T cell differentiation (723). Similarly, Mo-DCs have also been shown to drive T follicular helper cell differentiation through the production of IL-6 (232,727). This suggests that Mo-DCs are not a homogenous cell type and exhibit significant plasticity. This is notable because there is evidence that a division of labour exists between conventional and Mo-DCs in which the former are specialised for inducing T cell proliferation and the latter for T cell polarisation (190). In such a scenario, a capacity for Mo-DCs to engage a range of different effector programs would prove to be a very useful attribute. It is thus crucial to better understand the processes that underlie monocyte differentiation and their subsequent interactions within activated T cells in the dLN, both in terms of molecular cues and microanatomy. The hypothesis that monocytes actively cluster with and activate NK cell and CD8 memory T cells in a CXCR3-dependent manner within peripheral regions of the dLN has the potential to shed light on this important knowledge gap. This would certainly inform the design of future vaccine adjuvants. 278

Figure 7.7: Putative adaptive immune functions of NK cell, CD8 Memory T cell, Ly6Chi monocyte clusters 1) Clusters may potentiate CD69 upregulation by lymphocytes and therefore increase their lymph node residence time, promoting efficient scanning of the naïve repertoire for cognate lymphocytes. 2) Cluster-derived IFNγ may be instrumental in driving the differentiation of monocytes into monocyte-derived dendritic cells within the draining lymph node. 3) Cluster-derived monocyte-derived dendritic cells may provide important polarisation signals to recently activated naïve T cells. Created with biorender.com.

279

7.3 The KEC-draining lymph node as a model that informs the design of TLR-4 based adjuvants

A further question that can be posed with regard to this thesis is to ask whether there is any benefit in studying KEC as an inflammatory stimulus, as opposed to an established vaccine adjuvant. Indeed, several (albeit not all) of the inflammatory processes described in this thesis have also recently been implicated as contributors to the immunogenicity of the novel TLR-4- based adjuvants GLA-SE and AS01 (266,277–279,296). These processes include type I IFN signalling (279), IFNγ production (277–279,296) and inflammasome activation (266,277,278,296) within the dLN. It could be argued that further investigation of these processes in the context of an established or developing adjuvant would prove far more insightful with regard to characterising adjuvant mechanisms than a heterogeneous stimulus such as KEC. However, such an argument fails to appreciate the value of using whole-microbial challenges such as KEC as a point of comparison against purified adjuvants. By their very nature microbes express a range of PAMPs in varying ratios (304) and modern adjuvants try to emulate this natural phenomenon by combining PRR agonists with each other and various lipid components or emulsifying agents (258,277,278,281,284,292). Nevertheless, such adjuvants are unlikely to fully mimic the complex PAMP combinations exhibited by microbes and therefore a potential gap exists between the innate immune pathways engaged by adjuvants and whole microbes; some of which may prove crucial to the potentiation of adaptive immune responses. The power of such a comparative approach is highlighted by the work of JM Blander’s group, who have identified a novel class of viability-associated PAMPs (vita-PAMPs) by comparing the innate and adaptive immune responses elicited following challenge with killed and live E. coli (699,714). KEC could be similarly compared with the novel TLR-4-based adjuvants GLA-SE and AS01 to identify novel KEC-associated pathways. For example, GLA-SE and AS01 are known to potentiate Th1 T cells responses (277–279,296) and the Th1 polarising capacity of KEC could be directly compared with these adjuvants following challenge with KEC/adjuvant mixed with a well-characterised protein antigen such as ovalbumin. Such an experiment would be informative regardless of the outcome. This is because a potentiated response induced by KEC would suggest the presence of other immunogenic pathways not engaged by the chosen adjuvant and the inverse result would suggest the opposite. Systems biology methods such as transcriptomics could then be used to formulate targeted hypotheses and/or identify innate signatures of immunogenicity or protection; an approach that is increasingly being adopted in the field of adjuvant research (273,308,728–730). Indeed, such an approach could be targeted at specific microanatomical regions of interest within the dLN by the novel method of niche-sequencing (232,731). This would be particularly illuminating if

280 monocytes/NK cells and CD8 memory T cells were found to exhibit CXCR3-dependent clustering within peripheral regions of the dLN as outlined in Figure 7.5. Nevertheless, even without such systems-based methods, this hypothesis is both eminently testable and would improve our understanding the innate immune networks operating in the dLN. It is hoped that further research to delineate the novel findings of the research presented in this thesis may help to inform future adjuvant design and aid us in the production of effective vaccines in a world that remains under continuous and evolving threat from infectious disease.

281

Bibliography

1. Doherty M, Buchy P, Standaert B, Giaquinto C, Prado- Cohrs D. Vaccine impact: Benefits for human health. Vaccine. 2016 Dec 20;34(52):6707–14.

2. van Wijhe M, McDonald SA, de Melker HE, Postma MJ, Wallinga J. Effect of vaccination programmes on mortality burden among children and young adults in the Netherlands during the 20th century: a historical analysis. Lancet Infect Dis. 2016 May 1;16(5):592–8.

3. Simonsen L, Viboud C. The power of historical data for assessment of childhood vaccine benefits. Lancet Infect Dis. 2016 May 1;16(5):516–8.

4. Plotkin S. History of vaccination. Proc Natl Acad Sci U S A. 2014 Aug 26;111(34):12283–7.

5. Gross CP, Sepkowitz KA. The myth of the medical breakthrough: smallpox, vaccination, and Jenner reconsidered. Int J Infect Dis IJID Off Publ Int Soc Infect Dis. 1998 Sep;3(1):54–60.

6. Hajj Hussein I, Chams N, Chams S, El Sayegh S, Badran R, Raad M, et al. Vaccines Through Centuries: Major Cornerstones of Global Health. Front Public Health [Internet]. 2015 Nov 26 [cited 2019 Dec 15];3. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4659912/

7. Riedel S. Edward Jenner and the history of smallpox and vaccination. Proc Bayl Univ Med Cent. 2005 Jan;18(1):21–5.

8. Carroll DS, Emerson GL, Li Y, Sammons S, Olson V, Frace M, et al. Chasing Jenner’s vaccine: revisiting cowpox virus classification. PloS One. 2011;6(8):e23086.

9. Rappuoli R. Inner Workings: 1885, the first rabies vaccination in humans. Proc Natl Acad Sci. 2014 Aug 26;111(34):12273–12273.

10. Wright AE, Semple D. Remarks on Vaccination against Typhoid Fever. Br Med J. 1897 Jan 30;1(1883):256–9.

11. LUCA S, MIHAESCU T. History of BCG Vaccine. Mædica. 2013 Mar;8(1):53–8.

12. Enders JF, Weller TH, Robbins FC. Cultivation of the Lansing Strain of Poliomyelitis Virus in Cultures of Various Human Embryonic Tissues. Science. 1949 Jan 28;109(2822):85–7.

13. Katz SL, Kempe CH, Black FL, Lepow ML, Krugman S, Haggerty RJ, et al. Studies on an Attenuated Measles-Virus Vaccine. N Engl J Med. 1960 Jul 28;263(4):180–4.

14. Hilleman MR, Buynak EB, Weibel RE, Stokes J. Live, Attenuated Mumps-Virus Vaccine. N Engl J Med. 1968 Feb 1;278(5):227–32.

15. Glenny AT, Hopkins BE. Diphtheria Toxoid as an Immunising Agent. Br J Exp Pathol. 1923 Oct;4(5):283–8.

16. Glenny AM, Pope C, Waddington CH, Falacce U. The antigenic value of toxoid precipitated by potassium alum. 1926 Jan 1 [cited 2020 Jan 2]; Available from: https://www.scienceopen.com/document?vid=bc980448-6b84-4518-86a0-a8449e0ef636

17. Lockhart S. Conjugate vaccines. Expert Rev Vaccines. 2003 Oct 1;2(5):633–48.

282

18. Schneerson R, Barrera O, Sutton A, Robbins JB. Preparation, characterization, and immunogenicity of Haemophilus influenzae type b polysaccharide-protein conjugates. J Exp Med. 1980 Aug 1;152(2):361–76.

19. Van Epps HL. Michael Heidelberger and the demystification of antibodies. J Exp Med. 2006 Jan 23;203(1):5.

20. Winau F, Westphal O, Winau R. Paul Ehrlich — in search of the magic bullet. Microbes Infect. 2004 Jul 1;6(8):786–9.

21. Wright AE, Douglas SR, Burdon-Sanderson JS. An experimental investigation of the rôle of the blood fluids in connection with phagocytosis. Proc R Soc Lond. 1904 Jan 1;72(477– 486):357–70.

22. Thakur A, Pedersen LE, Jungersen G. Immune markers and correlates of protection for vaccine induced immune responses. Vaccine. 2012 Jul 13;30(33):4907–20.

23. Plotkin SA. Correlates of Protection Induced by Vaccination. Clin Vaccine Immunol CVI. 2010 Jul;17(7):1055–65.

24. Vesikari T, Matson DO, Dennehy P, Van Damme P, Santosham M, Rodriguez Z, et al. Safety and Efficacy of a Pentavalent Human–Bovine (WC3) Reassortant Rotavirus Vaccine. N Engl J Med. 2006 Jan 5;354(1):23–33.

25. Clark HF, Offit PA, Plotkin SA, Heaton PM. The new pentavalent rotavirus vaccine composed of bovine (strain WC3) -human rotavirus reassortants. Pediatr Infect Dis J. 2006 Jul;25(7):577–83.

26. Giuliani MM, Adu-Bobie J, Comanducci M, Aricò B, Savino S, Santini L, et al. A universal vaccine for serogroup B meningococcus. Proc Natl Acad Sci U S A. 2006 Jul 18;103(29):10834–9.

27. Rueckert C, Guzmán CA. Vaccines: From Empirical Development to Rational Design. PLOS Pathog. 2012 Nov 8;8(11):e1003001.

28. Graham BS, Sullivan NJ. Emerging viral diseases from a vaccinology perspective: preparing for the next pandemic. Nat Immunol. 2018 Jan;19(1):20–8.

29. Lurie N, Saville M, Hatchett R, Halton J. Developing Covid-19 Vaccines at Pandemic Speed. N Engl J Med. 2020 Mar 30;

30. Le TT, Andreadakis Z, Kumar A, Román RG, Tollefsen S, Saville M, et al. The COVID-19 vaccine development landscape. Nat Rev Drug Discov. 2020 Apr 9;19(5):305–6.

31. Lalvani A, Sridhar S. BCG vaccination: 90 years on and still so much to learn .. Thorax. 2010 Dec;65(12):1036–8.

32. Nunes-Alves C, Booty MG, Carpenter SM, Jayaraman P, Rothchild AC, Behar SM. In search of a new paradigm for protective immunity to TB. Nat Rev Microbiol. 2014 Apr;12(4):289– 99.

33. Abebe F. Is interferon-gamma the right marker for bacille Calmette-Guérin-induced immune protection? The missing link in our understanding of tuberculosis immunology. Clin Exp Immunol. 2012 Sep;169(3):213–9.

283

34. Wilkie MEM, McShane H. TB vaccine development: where are we and why is it so difficult? Thorax. 2014 Nov 28;thoraxjnl-2014-205202.

35. Davis MM, Bjorkman PJ. T-cell antigen receptor genes and T-cell recognition. Nature. 1988 Aug 4;334(6181):395–402.

36. Blattman JN, Antia R, Sourdive DJD, Wang X, Kaech SM, Murali-Krishna K, et al. Estimating the Precursor Frequency of Naive Antigen-specific CD8 T Cells. J Exp Med. 2002 Mar 4;195(5):657–64.

37. Whitmire JK, Benning N, Whitton JL. Precursor Frequency, Nonlinear Proliferation, and Functional Maturation of Virus-Specific CD4+ T Cells. J Immunol. 2006 Mar 1;176(5):3028– 36.

38. Moon JJ, Chu HH, Pepper M, McSorley SJ, Jameson SC, Kedl RM, et al. Naive CD4+ T Cell Frequency Varies for Different Epitopes and Predicts Repertoire Diversity and Response Magnitude. Immunity. 2007 Aug 24;27(2):203–13.

39. Press JL, Klinman NR. Frequency of hapten-specific B cells in neonatal and adult murine spleens. Eur J Immunol. 1974 Mar 1;4(3):155–9.

40. The diversity of the influenza-specific primary B-cell repertoire in BALB/c mice. J Exp Med. 1978 Mar 1;147(3):776–87.

41. Owen JA, Sigal NH, Klinman NR. Heterogeneity of the BALB/c IgM anti-phosphorylcholine antibody response. Nature. 1982 Jan 28;295(5847):347–8.

42. van Heijst JWJ, Gerlach C, Swart E, Sie D, Nunes-Alves C, Kerkhoven RM, et al. Recruitment of antigen-specific CD8+ T cells in response to infection is markedly efficient. Science. 2009 Sep 4;325(5945):1265–9.

43. Junt T, Scandella E, Ludewig B. Form follows function: lymphoid tissue microarchitecture in antimicrobial immune defence. Nat Rev Immunol. 2008 Oct;8(10):764–75.

44. Miyawaki S, Nakamura Y, Suzuka H, Koba M, Yasumizu R, Ikehara S, et al. A new mutation, aly, that induces a generalized lack of lymph nodes accompanied by immunodeficiency in mice. Eur J Immunol. 1994 Feb;24(2):429–34.

45. Shinkura R, Kitada K, Matsuda F, Tashiro K, Ikuta K, Suzuki M, et al. Alymphoplasia is caused by a point mutation in the mouse gene encoding Nf-kappa b-inducing kinase. Nat Genet. 1999 May;22(1):74–7.

46. Shinkura R, Matsuda F, Sakiyama T, Tsubata T, Hiai H, Paumen M, et al. Defects of somatic hypermutation and class switching in alymphoplasia (aly) mutant mice. Int Immunol. 1996 Jul;8(7):1067–75.

47. Fütterer A, Mink K, Luz A, Kosco-Vilbois MH, Pfeffer K. The lymphotoxin beta receptor controls organogenesis and affinity maturation in peripheral lymphoid tissues. Immunity. 1998 Jul;9(1):59–70.

48. Boehm T, Hess I, Swann JB. Evolution of lymphoid tissues. Trends Immunol. 2012 Jun 1;33(6):315–21.

284

49. Olson MR, McDermott DS, Varga SM. The Initial Draining Lymph Node Primes the Bulk of the CD8 T Cell Response and Influences Memory T Cell Trafficking after a Systemic Viral Infection. PLOS Pathog. 2012 Dec 6;8(12):e1003054.

50. Kool M, Soullié T, van Nimwegen M, Willart MAM, Muskens F, Jung S, et al. Alum adjuvant boosts adaptive immunity by inducing uric acid and activating inflammatory dendritic cells. J Exp Med. 2008 Apr 14;205(4):869–82.

51. Liang F, Lindgren G, Sandgren KJ, Thompson EA, Francica JR, Seubert A, et al. Vaccine priming is restricted to draining lymph nodes and controlled by adjuvant-mediated antigen uptake. Sci Transl Med. 2017 Jun 7;9(393).

52. Ols S, Yang L, Thompson EA, Pushparaj P, Tran K, Liang F, et al. Route of Vaccine Administration Alters Antigen Trafficking but Not Innate or Adaptive Immunity. Cell Rep. 2020 Mar 24;30(12):3964-3971.e7.

53. Loo CP, Nelson NA, Lane RS, Booth JL, Loprinzi Hardin SC, Thomas A, et al. Lymphatic Vessels Balance Viral Dissemination and Immune Activation following Cutaneous Viral Infection. Cell Rep. 2017 Sep 26;20(13):3176–87.

54. Young B, O’Dowd G, Woodford P. Wheater’s functional histology: a text and colour atlas. Chapter 8: The Lymph Vascular System (pg 156-57). Sixth edition. Philadelphia, PA: Churchill Livingston/Elsevier; 2014. 452 p.

55. Young B, O’Dowd G, Woodford P. Wheater’s functional histology: a text and colour atlas. Chapter 11: Lymph Nodes (pg 207-215). Sixth edition. Philadelphia, PA: Churchill Livingston/Elsevier; 2014. 452 p.

56. Förster R, Braun A, Worbs T. Lymph node homing of T cells and dendritic cells via afferent lymphatics. Trends Immunol. 2012 Jun;33(6):271–80.

57. Girard J-P, Moussion C, Förster R. HEVs, lymphatics and homeostatic immune cell trafficking in lymph nodes. Nat Rev Immunol. 2012 Nov;12(11):762–73.

58. Cremasco V, Woodruff MC, Onder L, Cupovic J, Nieves-Bonilla JM, Schildberg FA, et al. B cell homeostasis and follicle confines are governed by fibroblastic reticular cells. Nat Immunol. 2014 Oct;15(10):973–81.

59. Katakai T, Hara T, Lee J-H, Gonda H, Sugai M, Shimizu A. A novel reticular stromal structure in lymph node cortex: an immuno-platform for interactions among dendritic cells, T cells and B cells. Int Immunol. 2004 Aug 1;16(8):1133–42.

60. Wang X, Cho B, Suzuki K, Xu Y, Green JA, An J, et al. Follicular dendritic cells help establish follicle identity and promote B cell retention in germinal centers. J Exp Med. 2011 Nov 21;208(12):2497–510.

61. Ansel KM, Ngo VN, Hyman PL, Luther SA, Förster R, Sedgwick JD, et al. A chemokine-driven positive feedback loop organizes lymphoid follicles. Nature. 2000 Jul 20;406(6793):309–14.

62. Link A, Vogt TK, Favre S, Britschgi MR, Acha-Orbea H, Hinz B, et al. Fibroblastic reticular cells in lymph nodes regulate the homeostasis of naive T cells. Nat Immunol. 2007 Nov;8(11):1255–65.

63. Okada T, Cyster JG. CC chemokine receptor 7 contributes to Gi-dependent T cell motility in the lymph node. J Immunol Baltim Md 1950. 2007 Mar 1;178(5):2973–8.

285

64. Hwang I-Y, Park C, Kehrl JH. Impaired trafficking of Gnai2+/- and Gnai2-/- T lymphocytes: implications for T cell movement within lymph nodes. J Immunol Baltim Md 1950. 2007 Jul 1;179(1):439–48.

65. Pham THM, Okada T, Matloubian M, Lo CG, Cyster JG. S1P1 receptor signaling overrides retention mediated by Gαi-coupled receptors to promote T cell egress. Immunity. 2008 Jan;28(1):122–33.

66. Nakano H, Mori S, Yonekawa H, Nariuchi H, Matsuzawa A, Kakiuchi T. A novel mutant gene involved in T-lymphocyte-specific homing into peripheral lymphoid organs on mouse chromosome 4. Blood. 1998 Apr 15;91(8):2886–95.

67. Bajénoff M, Egen JG, Koo LY, Laugier JP, Brau F, Glaichenhaus N, et al. Stromal cell networks regulate lymphocyte entry, migration, and territoriality in lymph nodes. Immunity. 2006 Dec;25(6):989–1001.

68. Lindquist RL, Shakhar G, Dudziak D, Wardemann H, Eisenreich T, Dustin ML, et al. Visualizing dendritic cell networks in vivo. Nat Immunol. 2004 Dec;5(12):1243–50.

69. Baratin M, Simon L, Jorquera A, Ghigo C, Dembele D, Nowak J, et al. T Cell Zone Resident Macrophages Silently Dispose of Apoptotic Cells in the Lymph Node. Immunity. 2017 Aug 15;47(2):349-362.e5.

70. Kastenmüller W, Brandes M, Wang Z, Herz J, Egen JG, Germain RN. Peripheral prepositioning and local CXCL9 chemokine-mediated guidance orchestrate rapid memory CD8+ T cell responses in the lymph node. Immunity. 2013 Mar 21;38(3):502–13.

71. Gerner MY, Torabi-Parizi P, Germain RN. Strategically localized dendritic cells promote rapid T cell responses to lymph-borne particulate antigens. Immunity. 2015 Jan 20;42(1):172–85.

72. Kastenmüller W, Torabi-Parizi P, Subramanian N, Lämmermann T, Germain RN. A Spatially- Organized Multicellular Innate Immune Response in Lymph Nodes Limits Systemic Pathogen Spread. Cell. 2012 Sep 14;150(6):1235–48.

73. Gerner MY, Kastenmuller W, Ifrim I, Kabat J, Germain RN. Histo-cytometry: a method for highly multiplex quantitative tissue imaging analysis applied to dendritic cell subset microanatomy in lymph nodes. Immunity. 2012 Aug 24;37(2):364–76.

74. Gerner MY, Casey KA, Kastenmuller W, Germain RN. Dendritic cell and antigen dispersal landscapes regulate T cell immunity. J Exp Med. 2017 Oct 2;214(10):3105–22.

75. Stoltzfus CR, Filipek J, Gern BH, Olin BE, Leal JM, Wu Y, et al. CytoMAP: A Spatial Analysis Toolbox Reveals Features of Myeloid Cell Organization in Lymphoid Tissues. Cell Rep. 2020 Apr 21;31(3):107523.

76. Baptista AP, Gola A, Huang Y, Milanez-Almeida P, Torabi-Parizi P, Urban JF, et al. The Chemoattractant Receptor Ebi2 Drives Intranodal Naive CD4+ T Cell Peripheralization to Promote Effective Adaptive Immunity. Immunity. 2019 21;50(5):1188-1201.e6.

77. Gray EE, Cyster JG. Lymph node macrophages. J Innate Immun. 2012;4(5–6):424–36.

78. Hargreaves DC, Hyman PL, Lu TT, Ngo VN, Bidgol A, Suzuki G, et al. A Coordinated Change in Chemokine Responsiveness Guides Plasma Cell Movements. J Exp Med. 2001 Jul 2;194(1):45–56.

286

79. Huang H-Y, Rivas-Caicedo A, Renevey F, Cannelle H, Peranzoni E, Scarpellino L, et al. Identification of a new subset of lymph node stromal cells involved in regulating plasma cell homeostasis. Proc Natl Acad Sci. 2018 Jul 2;201712628.

80. Mohr E, Serre K, Manz RA, Cunningham AF, Khan M, Hardie DL, et al. Dendritic cells and monocyte/macrophages that create the IL-6/APRIL-rich lymph node microenvironments where plasmablasts mature. J Immunol Baltim Md 1950. 2009 Feb 15;182(4):2113–23.

81. Fooksman DR, Schwickert TA, Victora GD, Dustin ML, Nussenzweig MC, Skokos D. Development and Migration of Plasma Cells in the Mouse Lymph Node. Immunity. 2010 Jul 23;33(1):118–27.

82. Wei SH, Rosen H, Matheu MP, Sanna MG, Wang S-K, Jo E, et al. Sphingosine 1-phosphate type 1 receptor agonism inhibits transendothelial migration of medullary T cells to lymphatic sinuses. Nat Immunol. 2005 Dec;6(12):1228–35.

83. Grigorova IL, Schwab SR, Phan TG, Pham THM, Okada T, Cyster JG. Cortical sinus probing, S1P1-dependent entry and flow-based capture of egressing T cells. Nat Immunol. 2009 Jan;10(1):58–65.

84. Grigorova IL, Panteleev M, Cyster JG. Lymph node cortical sinus organization and relationship to lymphocyte egress dynamics and antigen exposure. Proc Natl Acad Sci U S A. 2010 Nov 23;107(47):20447–52.

85. Braun A, Worbs T, Moschovakis GL, Halle S, Hoffmann K, Bölter J, et al. Afferent lymph– derived T cells and DCs use different chemokine receptor CCR7–dependent routes for entry into the lymph node and intranodal migration. Nat Immunol. 2011 Sep;12(9):879– 87.

86. Fujimoto N, He Y, D’Addio M, Tacconi C, Detmar M, Dieterich LC. Single-cell mapping reveals new markers and functions of lymphatic endothelial cells in lymph nodes. PLOS Biol. 2020 Apr 6;18(4):e3000704.

87. Takeda A, Hollmén M, Dermadi D, Pan J, Brulois KF, Kaukonen R, et al. Single-Cell Survey of Human Lymphatics Unveils Marked Endothelial Cell Heterogeneity and Mechanisms of Homing for Neutrophils. Immunity. 2019 17;51(3):561-572.e5.

88. Ulvmar MH, Werth K, Braun A, Kelay P, Hub E, Eller K, et al. The atypical chemokine receptor CCRL1 shapes functional CCL21 gradients in lymph nodes. Nat Immunol. 2014 Jul;15(7):623–30.

89. Pham THM, Baluk P, Xu Y, Grigorova I, Bankovich AJ, Pappu R, et al. Lymphatic endothelial cell sphingosine kinase activity is required for lymphocyte egress and lymphatic patterning. J Exp Med. 2010 Jan 18;207(1):17–27.

90. Fang V, Chaluvadi VS, Ramos-Perez WD, Mendoza A, Baeyens A, Rivera R, et al. Gradients of the signaling lipid S1P in lymph nodes position natural killer cells and regulate their interferon-γ response. Nat Immunol. 2017 Jan;18(1):15–25.

91. Mendoza A, Bréart B, Ramos-Perez WD, Pitt LA, Gobert M, Sunkara M, et al. The transporter Spns2 is required for secretion of lymph but not plasma sphingosine-1- phosphate. Cell Rep. 2012 Nov 29;2(5):1104–10.

287

92. Rantakari P, Auvinen K, Jäppinen N, Kapraali M, Valtonen J, Karikoski M, et al. The endothelial protein PLVAP in lymphatics controls the entry of lymphocytes and antigens into lymph nodes. Nat Immunol. 2015 Apr;16(4):386–96.

93. Cohen JN, Tewalt EF, Rouhani SJ, Buonomo EL, Bruce AN, Xu X, et al. Tolerogenic Properties of Lymphatic Endothelial Cells Are Controlled by the Lymph Node Microenvironment. PLOS ONE. 2014 Feb 4;9(2):e87740.

94. Tewalt EF, Cohen JN, Rouhani SJ, Guidi CJ, Qiao H, Fahl SP, et al. Lymphatic endothelial cells induce tolerance via PD-L1 and lack of costimulation leading to high-level PD-1 expression on CD8 T cells. Blood. 2012 Dec 6;120(24):4772–82.

95. Cohen JN, Guidi CJ, Tewalt EF, Qiao H, Rouhani SJ, Ruddell A, et al. Lymph node-resident lymphatic endothelial cells mediate peripheral tolerance via Aire-independent direct antigen presentation. J Exp Med. 2010 Apr 12;207(4):681–8.

96. Soderberg KA, Payne GW, Sato A, Medzhitov R, Segal SS, Iwasaki A. Innate control of adaptive immunity via remodeling of lymph node feed arteriole. Proc Natl Acad Sci U S A. 2005 Nov 8;102(45):16315–20.

97. von Andrian UH, Mempel TR. Homing and cellular traffic in lymph nodes. Nat Rev Immunol. 2003 Nov;3(11):867–78.

98. Moussion C, Girard J-P. Dendritic cells control lymphocyte entry to lymph nodes through high endothelial venules. Nature. 2011 Nov 24;479(7374):542–6.

99. Miyasaka M, Tanaka T. Lymphocyte trafficking across high endothelial venules: dogmas and enigmas. Nat Rev Immunol. 2004 May 1;4(5):360–70.

100. Uchimura K, Gauguet J-M, Singer MS, Tsay D, Kannagi R, Muramatsu T, et al. A major class of L-selectin ligands is eliminated in mice deficient in two sulfotransferases expressed in high endothelial venules. Nat Immunol. 2005 Nov;6(11):1105–13.

101. Kawashima H, Petryniak B, Hiraoka N, Mitoma J, Huckaby V, Nakayama J, et al. N- acetylglucosamine-6-O-sulfotransferases 1 and 2 cooperatively control lymphocyte homing through L-selectin ligand biosynthesis in high endothelial venules. Nat Immunol. 2005 Nov;6(11):1096–104.

102. Warnock RA, Askari S, Butcher EC, von Andrian UH. Molecular mechanisms of lymphocyte homing to peripheral lymph nodes. J Exp Med. 1998 Jan 19;187(2):205–16.

103. Stein JV, Rot A, Luo Y, Narasimhaswamy M, Nakano H, Gunn MD, et al. The CC chemokine thymus-derived chemotactic agent 4 (TCA-4, secondary lymphoid tissue chemokine, 6Ckine, exodus-2) triggers lymphocyte function-associated antigen 1- mediated arrest of rolling T lymphocytes in peripheral lymph node high endothelial venules. J Exp Med. 2000 Jan 3;191(1):61–76.

104. Okada T, Ngo VN, Ekland EH, Förster R, Lipp M, Littman DR, et al. Chemokine requirements for B cell entry to lymph nodes and Peyer’s patches. J Exp Med. 2002 Jul 1;196(1):65–75.

105. Bao X, Moseman EA, Saito H, Petryniak B, Petryanik B, Thiriot A, et al. Endothelial heparan sulfate controls chemokine presentation in recruitment of lymphocytes and dendritic cells to lymph nodes. Immunity. 2010 Nov 24;33(5):817–29.

288

106. Tsuboi K, Hirakawa J, Seki E, Imai Y, Yamaguchi Y, Fukuda M, et al. Role of high endothelial venule-expressed heparan sulfate in chemokine presentation and lymphocyte homing. J Immunol Baltim Md 1950. 2013 Jul 1;191(1):448–55.

107. Park C, Hwang I-Y, Sinha RK, Kamenyeva O, Davis MD, Kehrl JH. Lymph node B lymphocyte trafficking is constrained by anatomy and highly dependent upon chemoattractant desensitization. Blood. 2012 Jan 26;119(4):978–89.

108. Han S-B, Moratz C, Huang N-N, Kelsall B, Cho H, Shi C-S, et al. Rgs1 and Gnai2 regulate the entrance of B lymphocytes into lymph nodes and B cell motility within lymph node follicles. Immunity. 2005 Mar;22(3):343–54.

109. Baekkevold ES, Yamanaka T, Palframan RT, Carlsen HS, Reinholt FP, von Andrian UH, et al. The Ccr7 Ligand ELC (Ccl19) Is Transcytosed in High Endothelial Venules and Mediates T Cell Recruitment. J Exp Med. 2001 May 7;193(9):1105–12.

110. Boscacci RT, Pfeiffer F, Gollmer K, Sevilla AIC, Martin AM, Soriano SF, et al. Comprehensive analysis of lymph node stroma-expressed Ig superfamily members reveals redundant and nonredundant roles for ICAM-1, ICAM-2, and VCAM-1 in lymphocyte homing. Blood. 2010 Aug 12;116(6):915–25.

111. Chang JE, Turley SJ. Stromal infrastructure of the lymph node and coordination of immunity. Trends Immunol. 2015 Jan;36(1):30–9.

112. Denton AE, Roberts EW, Linterman MA, Fearon DT. Fibroblastic reticular cells of the lymph node are required for retention of resting but not activated CD8+ T cells. Proc Natl Acad Sci. 2014 Aug 19;111(33):12139–44.

113. Heesters BA, Chatterjee P, Kim Y-A, Gonzalez SF, Kuligowski MP, Kirchhausen T, et al. Endocytosis and Recycling of Immune Complexes by Follicular Dendritic Cells Enhances B Cell Antigen Binding and Activation. Immunity. 2013 Jun 27;38(6):1164–75.

114. Suzuki K, Grigorova I, Phan TG, Kelly LM, Cyster JG. Visualizing B cell capture of cognate antigen from follicular dendritic cells. J Exp Med. 2009 Jul 6;206(7):1485–93.

115. Katakai T, Suto H, Sugai M, Gonda H, Togawa A, Suematsu S, et al. Organizer-like reticular stromal cell layer common to adult secondary lymphoid organs. J Immunol Baltim Md 1950. 2008 Nov 1;181(9):6189–200.

116. Katakai T. Marginal reticular cells: a stromal subset directly descended from the lymphoid tissue organizer. Front Immunol. 2012;3:200.

117. Jarjour M, Jorquera A, Mondor I, Wienert S, Narang P, Coles MC, et al. Fate mapping reveals origin and dynamics of lymph node follicular dendritic cells. J Exp Med. 2014 Jun 2;211(6):1109–22.

118. Sixt M, Kanazawa N, Selg M, Samson T, Roos G, Reinhardt DP, et al. The conduit system transports soluble antigens from the afferent lymph to resident dendritic cells in the T cell area of the lymph node. Immunity. 2005 Jan;22(1):19–29.

119. Gretz JE, Norbury CC, Anderson AO, Proudfoot AEI, Shaw S. Lymph-Borne Chemokines and Other Low Molecular Weight Molecules Reach High Endothelial Venules via Specialized Conduits While a Functional Barrier Limits Access to the Lymphocyte Microenvironments in Lymph Node Cortex. J Exp Med. 2000 Nov 20;192(10):1425–40.

289

120. Reynoso GV, Weisberg AS, Shannon JP, McManus DT, Shores L, Americo JL, et al. Lymph node conduits transport virions for rapid T cell activation. Nat Immunol. 2019 May;20(5):602–12.

121. Bajénoff M, Germain RN. B-cell follicle development remodels the conduit system and allows soluble antigen delivery to follicular dendritic cells. Blood. 2009 Dec 3;114(24):4989–97.

122. Roozendaal R, Mempel TR, Pitcher LA, Gonzalez SF, Verschoor A, Mebius RE, et al. Conduits mediate transport of low-molecular-weight antigen to lymph node follicles. Immunity. 2009 Feb 20;30(2):264–76.

123. Thierry GR, Kuka M, Giovanni MD, Mondor I, Brouilly N, Iannacone M, et al. The conduit system exports locally secreted IgM from lymph nodes. J Exp Med. 2018 Dec 3;215(12):2972–83.

124. Westermann J, Puskas Z, Pabst R. Blood transit and recirculation kinetics of lymphocyte subsets in normal rats. Scand J Immunol. 1988 Aug;28(2):203–10.

125. Tomura M, Yoshida N, Tanaka J, Karasawa S, Miwa Y, Miyawaki A, et al. Monitoring cellular movement in vivo with photoconvertible fluorescence protein “Kaede” transgenic mice. Proc Natl Acad Sci. 2008 Aug 5;105(31):10871–6.

126. Mandl JN, Liou R, Klauschen F, Vrisekoop N, Monteiro JP, Yates AJ, et al. Quantification of lymph node transit times reveals differences in antigen surveillance strategies of naïve CD4+ and CD8+ T cells. Proc Natl Acad Sci. 2012 Oct 30;109(44):18036–41.

127. Yang J, Zhang S, Zhang L, Xie X, Wang H, Jie Z, et al. Lymphatic endothelial cells regulate B-cell homing to lymph nodes via a NIK-dependent mechanism. Cell Mol Immunol. 2019;16(2):165–77.

128. Ebisuno Y, Tanaka T, Kanemitsu N, Kanda H, Yamaguchi K, Kaisho T, et al. Cutting edge: the B cell chemokine CXC chemokine ligand 13/B lymphocyte chemoattractant is expressed in the high endothelial venules of lymph nodes and Peyer’s patches and affects B cell trafficking across high endothelial venules. J Immunol Baltim Md 1950. 2003 Aug 15;171(4):1642–6.

129. Shamri R, Grabovsky V, Gauguet J-M, Feigelson S, Manevich E, Kolanus W, et al. Lymphocyte arrest requires instantaneous induction of an extended LFA-1 conformation mediated by endothelium-bound chemokines. Nat Immunol. 2005 May;6(5):497–506.

130. Arnon TI, Xu Y, Lo C, Pham T, An J, Coughlin S, et al. GRK2-dependent S1PR1 desensitization is required for lymphocytes to overcome their attraction to blood. Science. 2011 Sep 30;333(6051):1898–903.

131. Mionnet C, Sanos SL, Mondor I, Jorquera A, Laugier J-P, Germain RN, et al. High endothelial venules as traffic control points maintaining lymphocyte population homeostasis in lymph nodes. Blood. 2011 Dec 1;118(23):6115–22.

132. Bai Z, Cai L, Umemoto E, Takeda A, Tohya K, Komai Y, et al. Constitutive lymphocyte transmigration across the basal lamina of high endothelial venules is regulated by the autotaxin/lysophosphatidic acid axis. J Immunol Baltim Md 1950. 2013 Mar 1;190(5):2036–48.

290

133. Park EJ, Peixoto A, Imai Y, Goodarzi A, Cheng G, Carman CV, et al. Distinct roles for LFA- 1 affinity regulation during T-cell adhesion, diapedesis, and interstitial migration in lymph nodes. Blood. 2010 Feb 25;115(8):1572–81.

134. Hata E, Sasaki N, Takeda A, Tohya K, Umemoto E, Akahoshi N, et al. Lysophosphatidic acid receptors LPA4 and LPA6 differentially promote lymphocyte transmigration across high endothelial venules in lymph nodes. Int Immunol. 2016 Jun 1;28(6):283–92.

135. Yang J, Cornelissen F, Papazian N, Reijmers RM, Llorian M, Cupedo T, et al. IL-7– dependent maintenance of ILC3s is required for normal entry of lymphocytes into lymph nodes. J Exp Med. 2018 Feb 22;jem.20170518.

136. Herzog BH, Fu J, Wilson SJ, Hess PR, Sen A, McDaniel JM, et al. Podoplanin maintains high endothelial venule integrity by interacting with platelet CLEC-2. Nature. 2013 Oct 3;502(7469):105–9.

137. Mackay CR, Marston WL, Dudler L. Naive and memory T cells show distinct pathways of lymphocyte recirculation. J Exp Med. 1990 Mar 1;171(3):801–17.

138. Scollay R, Hall J, Orlans E. Studies on the lymphocytes of sheep. II. Some properties of cells in various compartments of the recirculating lymphocyte pool. Eur J Immunol. 1976 Feb;6(2):121–5.

139. Miller MJ, Wei SH, Parker I, Cahalan MD. Two-photon imaging of lymphocyte motility and antigen response in intact lymph node. Science. 2002 Jun 7;296(5574):1869–73.

140. Mempel TR, Henrickson SE, Von Andrian UH. T-cell priming by dendritic cells in lymph nodes occurs in three distinct phases. Nature. 2004 Jan 8;427(6970):154–9.

141. Miller MJ, Hejazi AS, Wei SH, Cahalan MD, Parker I. T Cell Repertoire Scanning Is Promoted by Dynamic Dendritic Cell Behavior and Random T Cell Motility in the Lymph Node. Proc Natl Acad Sci U S A. 2004;101(4):998–1003.

142. Miller MJ, Wei SH, Cahalan MD, Parker I. Autonomous T cell trafficking examined in vivo with intravital two-photon microscopy. Proc Natl Acad Sci U S A. 2003 Mar 4;100(5):2604–9.

143. Moreau HD, Lemaître F, Garrod KR, Garcia Z, Lennon-Duménil A-M, Bousso P. Signal strength regulates antigen-mediated T-cell deceleration by distinct mechanisms to promote local exploration or arrest. Proc Natl Acad Sci U S A. 2015 Sep 29;112(39):12151– 6.

144. Worbs T, Mempel TR, Bölter J, von Andrian UH, Förster R. CCR7 ligands stimulate the intranodal motility of T lymphocytes in vivo. J Exp Med. 2007 Mar 19;204(3):489–95.

145. Katakai T, Habiro K, Kinashi T. Dendritic Cells Regulate High-Speed Interstitial T Cell Migration in the Lymph Node via LFA-1/ICAM-1. J Immunol. 2013 Aug 1;191(3):1188–99.

146. Sinha RK, Park C, Hwang I-Y, Davis MD, Kehrl JH. B Lymphocytes Exit Lymph Nodes through Cortical Lymphatic Sinusoids by a Mechanism Independent of Sphingosine-1- Phosphate-Mediated Chemotaxis. Immunity. 2009 Mar 20;30(3):434–46.

147. Moseman EA, Iannacone M, Bosurgi L, Tonti E, Chevrier N, Tumanov A, et al. B cell maintenance of subcapsular sinus macrophages protects against a fatal viral infection independent of adaptive immunity. Immunity. 2012 Mar 23;36(3):415–26.

291

148. Schwab SR, Pereira JP, Matloubian M, Xu Y, Huang Y, Cyster JG. Lymphocyte sequestration through S1P lyase inhibition and disruption of S1P gradients. Science. 2005 Sep 9;309(5741):1735–9.

149. Pappu R, Schwab SR, Cornelissen I, Pereira JP, Regard JB, Xu Y, et al. Promotion of lymphocyte egress into blood and lymph by distinct sources of sphingosine-1-phosphate. Science. 2007 Apr 13;316(5822):295–8.

150. Matloubian M, Lo CG, Cinamon G, Lesneski MJ, Xu Y, Brinkmann V, et al. Lymphocyte egress from thymus and peripheral lymphoid organs is dependent on S1P receptor 1. Nature. 2004 Jan 22;427(6972):355–60.

151. Thangada S, Khanna KM, Blaho VA, Oo ML, Im D-S, Guo C, et al. Cell-surface residence of sphingosine 1-phosphate receptor 1 on lymphocytes determines lymphocyte egress kinetics. J Exp Med. 2010 Jul 5;207(7):1475–83.

152. Lo CG, Xu Y, Proia RL, Cyster JG. Cyclical modulation of sphingosine-1-phosphate receptor 1 surface expression during lymphocyte recirculation and relationship to lymphoid organ transit. J Exp Med. 2005 Jan 17;201(2):291–301.

153. Nakai A, Hayano Y, Furuta F, Noda M, Suzuki K. Control of lymphocyte egress from lymph nodes through β2-adrenergic receptors. J Exp Med. 2014 Dec 15;211(13):2583–98.

154. Suzuki K, Hayano Y, Nakai A, Furuta F, Noda M. Adrenergic control of the adaptive immune response by diurnal lymphocyte recirculation through lymph nodes. J Exp Med. 2016 Nov 14;213(12):2567–74.

155. Druzd D, Matveeva O, Ince L, Harrison U, He W, Schmal C, et al. Lymphocyte Circadian Clocks Control Lymph Node Trafficking and Adaptive Immune Responses. Immunity. 2017 Jan 17;46(1):120–32.

156. Pape KA, Catron DM, Itano AA, Jenkins MK. The humoral immune response is initiated in lymph nodes by B cells that acquire soluble antigen directly in the follicles. Immunity. 2007 Apr;26(4):491–502.

157. Catron DM, Pape KA, Fife BT, van Rooijen N, Jenkins MK. A protease-dependent mechanism for initiating T-dependent B cell responses to large particulate antigens. J Immunol Baltim Md 1950. 2010 Apr 1;184(7):3609–17.

158. Itano AA, McSorley SJ, Reinhardt RL, Ehst BD, Ingulli E, Rudensky AY, et al. Distinct Dendritic Cell Populations Sequentially Present Antigen to CD4 T Cells and Stimulate Different Aspects of Cell-Mediated Immunity. Immunity. 2003 Jul 1;19(1):47–57.

159. Junt T, Moseman EA, Iannacone M, Massberg S, Lang PA, Boes M, et al. Subcapsular sinus macrophages in lymph nodes clear lymph-borne viruses and present them to antiviral B cells. Nature. 2007 Nov 1;450(7166):110–4.

160. Carrasco YR, Batista FD. B cells acquire particulate antigen in a macrophage-rich area at the boundary between the follicle and the subcapsular sinus of the lymph node. Immunity. 2007 Jul;27(1):160–71.

161. Liu N-F, Lu Q, Jiang Z-H, Wang C-G, Zhou J-G. Anatomic and functional evaluation of the lymphatics and lymph nodes in diagnosis of lymphatic circulation disorders with contrast magnetic resonance lymphangiography. J Vasc Surg. 2009 Apr;49(4):980–7.

292

162. Zanoni I, Ostuni R, Barresi S, Di Gioia M, Broggi A, Costa B, et al. CD14 and NFAT mediate lipopolysaccharide-induced skin edema formation in mice. J Clin Invest. 2012 May;122(5):1747–57.

163. Manolova V, Flace A, Bauer M, Schwarz K, Saudan P, Bachmann MF. Nanoparticles target distinct dendritic cell populations according to their size. Eur J Immunol. 2008 May;38(5):1404–13.

164. Lee HK, Zamora M, Linehan MM, Iijima N, Gonzalez D, Haberman A, et al. Differential roles of migratory and resident DCs in T cell priming after mucosal or skin HSV-1 infection. J Exp Med. 2009 Feb 16;206(2):359–70.

165. Hor JL, Whitney PG, Zaid A, Brooks AG, Heath WR, Mueller SN. Spatiotemporally Distinct Interactions with Dendritic Cell Subsets Facilitates CD4+ and CD8+ T Cell Activation to Localized Viral Infection. Immunity. 2015 Sep 15;43(3):554–65.

166. Hutchison S, Benson RA, Gibson VB, Pollock AH, Garside P, Brewer JM. Antigen depot is not required for alum adjuvanticity. FASEB J. 2012 Mar;26(3):1272–9.

167. Mc W, Ba H, Cn H, Jr G, Pg T, Ad L, et al. Trans-nodal migration of resident dendritic cells into medullary interfollicular regions initiates immunity to influenza vaccine., Trans- nodal migration of resident dendritic cells into medullary interfollicular regions initiates immunity to influenza vaccine. J Exp Med J Exp Med. 2014 Jul 28;211, 211(8, 8):1611, 1611–21.

168. Gonzalez SF, Lukacs-Kornek V, Kuligowski MP, Pitcher LA, Degn SE, Kim Y-A, et al. Capture of influenza by medullary dendritic cells via SIGN-R1 is essential for humoral immunity in draining lymph nodes. Nat Immunol. 2010 May;11(5):427.

169. Heesters BA, Carroll MC. The Role of Dendritic Cells in S. pneumoniae Transport to Follicular Dendritic Cells. Cell Rep. 2016 Sep 20;16(12):3130–7.

170. Iannacone M, Moseman EA, Tonti E, Bosurgi L, Junt T, Henrickson SE, et al. Subcapsular sinus macrophages prevent CNS invasion on peripheral infection with a neurotropic virus. Nature. 2010 Jun 24;465(7301):1079–83.

171. Chatziandreou N, Farsakoglu Y, Palomino-Segura M, D’Antuono R, Pizzagalli DU, Sallusto F, et al. Macrophage Death following Influenza Vaccination Initiates the Inflammatory Response that Promotes Dendritic Cell Function in the Draining Lymph Node. Cell Rep. 2017 Mar 7;18(10):2427–40.

172. Garcia Z, Lemaître F, van Rooijen N, Albert ML, Levy Y, Schwartz O, et al. Subcapsular sinus macrophages promote NK cell accumulation and activation in response to lymph- borne viral particles. Blood. 2012 Dec 6;120(24):4744–50.

173. Bogoslowski A, Butcher EC, Kubes P. Neutrophils recruited through high endothelial venules of the lymph nodes via PNAd intercept disseminating Staphylococcus aureus. Proc Natl Acad Sci U S A. 2018 Mar 6;115(10):2449–54.

174. Phan TG, Grigorova I, Okada T, Cyster JG. Subcapsular encounter and complement- dependent transport of immune complexes by lymph node B cells. Nat Immunol. 2007 Sep;8(9):992–1000.

293

175. Phan TG, Green JA, Gray EE, Xu Y, Cyster JG. Immune complex relay by subcapsular sinus macrophages and noncognate B cells drives antibody affinity maturation. Nat Immunol. 2009 Jul;10(7):786–93.

176. Eisenbarth SC. Dendritic cell subsets in T cell programming: location dictates function. Nat Rev Immunol. 2019 Feb;19(2):89–103.

177. Meredith MM, Liu K, Darrasse-Jeze G, Kamphorst AO, Schreiber HA, Guermonprez P, et al. Expression of the zinc finger transcription factor zDC (Zbtb46, Btbd4) defines the classical dendritic cell lineage. J Exp Med. 2012 Jun 4;209(6):1153–65.

178. Hildner K, Edelson BT, Purtha WE, Diamond M, Matsushita H, Kohyama M, et al. Batf3 Deficiency Reveals a Critical Role for CD8α+ Dendritic Cells in Cytotoxic T Cell Immunity. Science. 2008 Nov 14;322(5904):1097–100.

179. Edelson BT, Kc W, Juang R, Kohyama M, Benoit LA, Klekotka PA, et al. Peripheral CD103+ dendritic cells form a unified subset developmentally related to CD8α+ conventional dendritic cells. J Exp Med. 2010 Apr 12;207(4):823–36.

180. Bedoui S, Whitney PG, Waithman J, Eidsmo L, Wakim L, Caminschi I, et al. Cross- presentation of viral and self antigens by skin-derived CD103+ dendritic cells. Nat Immunol. 2009 May;10(5):488–95.

181. Kitano M, Yamazaki C, Takumi A, Ikeno T, Hemmi H, Takahashi N, et al. Imaging of the cross-presenting dendritic cell subsets in the skin-draining lymph node. Proc Natl Acad Sci. 2016 Jan 26;113(4):1044–9.

182. Vander Lugt B, Khan AA, Hackney JA, Agrawal S, Lesch J, Zhou M, et al. Transcriptional programming of dendritic cells for enhanced MHC class II antigen presentation. Nat Immunol. 2014 Feb;15(2):161–7.

183. Bajaña S, Turner S, Paul J, Ainsua-Enrich E, Kovats S. IRF4 and IRF8 Act in CD11c+ Cells To Regulate Terminal Differentiation of Lung Tissue Dendritic Cells. J Immunol Baltim Md 1950. 2016 Feb 15;196(4):1666–77.

184. Eickhoff S, Brewitz A, Gerner MY, Klauschen F, Komander K, Hemmi H, et al. Robust Anti-viral Immunity Requires Multiple Distinct T Cell-Dendritic Cell Interactions. Cell. 2015 Sep 10;162(6):1322–37.

185. Eisenbarth SC, Colegio OR, O’Connor W, Sutterwala FS, Flavell RA. Crucial role for the Nalp3 inflammasome in the immunostimulatory properties of aluminium adjuvants. Nature. 2008 Jun 19;453(7198):1122–6.

186. Sheng J, Chen Q, Soncin I, Ng SL, Karjalainen K, Ruedl C. A Discrete Subset of Monocyte-Derived Cells among Typical Conventional Type 2 Dendritic Cells Can Efficiently Cross-Present. Cell Rep. 2017 Oct 31;21(5):1203–14.

187. Ersland K, Wüthrich M, Klein BS. Dynamic interplay among monocyte-derived, dermal, and resident lymph node dendritic cells during the generation of vaccine immunity to fungi. Cell Host Microbe. 2010 Jun 25;7(6):474–87.

188. Allan RS, Waithman J, Bedoui S, Jones CM, Villadangos JA, Zhan Y, et al. Migratory dendritic cells transfer antigen to a lymph node-resident dendritic cell population for efficient CTL priming. Immunity. 2006 Jul;25(1):153–62.

294

189. Plantinga M, Guilliams M, Vanheerswynghels M, Deswarte K, Branco-Madeira F, Toussaint W, et al. Conventional and Monocyte-Derived CD11b+ Dendritic Cells Initiate and Maintain T Helper 2 Cell-Mediated Immunity to House Dust Mite Allergen. Immunity. 2013 Feb 21;38(2):322–35.

190. Chow KV, Lew AM, Sutherland RM, Zhan Y. Monocyte-Derived Dendritic Cells Promote Th Polarization, whereas Conventional Dendritic Cells Promote Th Proliferation. J Immunol. 2016 Jan 15;196(2):624–36.

191. Allenspach EJ, Lemos MP, Porrett PM, Turka LA, Laufer TM. Migratory and lymphoid- resident dendritic cells cooperate to efficiently prime naive CD4 T cells. Immunity. 2008 Nov 14;29(5):795–806.

192. Ohl L, Mohaupt M, Czeloth N, Hintzen G, Kiafard Z, Zwirner J, et al. CCR7 Governs Skin Dendritic Cell Migration under Inflammatory and Steady-State Conditions. Immunity. 2004 Aug 1;21(2):279–88.

193. Tomura M, Hata A, Matsuoka S, Shand FHW, Nakanishi Y, Ikebuchi R, et al. Tracking and quantification of dendritic cell migration and antigen trafficking between the skin and lymph nodes. Sci Rep. 2014 Aug 12;4:6030.

194. Jang MH, Sougawa N, Tanaka T, Hirata T, Hiroi T, Tohya K, et al. CCR7 Is Critically Important for Migration of Dendritic Cells in Intestinal Lamina Propria to Mesenteric Lymph Nodes. J Immunol. 2006 Jan 15;176(2):803–10.

195. Förster R, Schubel A, Breitfeld D, Kremmer E, Renner-Müller I, Wolf E, et al. CCR7 coordinates the primary immune response by establishing functional microenvironments in secondary lymphoid organs. Cell. 1999 Oct 1;99(1):23–33.

196. Tal O, Lim HY, Gurevich I, Milo I, Shipony Z, Ng LG, et al. DC mobilization from the skin requires docking to immobilized CCL21 on lymphatic endothelium and intralymphatic crawling. J Exp Med. 2011 Sep 26;208(10):2141–53.

197. Russo E, Teijeira A, Vaahtomeri K, Willrodt A-H, Bloch JS, Nitschké M, et al. Intralymphatic CCL21 Promotes Tissue Egress of Dendritic Cells through Afferent Lymphatic Vessels. Cell Rep. 2016 Feb 23;14(7):1723–34.

198. Itano AA, McSorley SJ, Reinhardt RL, Ehst BD, Ingulli E, Rudensky AY, et al. Distinct dendritic cell populations sequentially present antigen to CD4 T cells and stimulate different aspects of cell-mediated immunity. Immunity. 2003 Jul;19(1):47–57.

199. Qi H, Egen JG, Huang AYC, Germain RN. Extrafollicular activation of lymph node B cells by antigen-bearing dendritic cells. Science. 2006 Jun 16;312(5780):1672–6.

200. Roux DL, Bon AL, Dumas A, Taleb K, Sachse M, Sikora R, et al. Antigen stored in dendritic cells after macropinocytosis is released unprocessed from late endosomes to target B cells. Blood. 2012 Jan 5;119(1):95–105.

201. Abadie V, Badell E, Douillard P, Ensergueix D, Leenen PJM, Tanguy M, et al. Neutrophils rapidly migrate via lymphatics after Mycobacterium bovis BCG intradermal vaccination and shuttle live bacilli to the draining lymph nodes. Blood. 2005 Sep 1;106(5):1843–50.

202. Kamenyeva O, Boularan C, Kabat J, Cheung GYC, Cicala C, Yeh AJ, et al. Neutrophil Recruitment to Lymph Nodes Limits Local Humoral Response to Staphylococcus aureus. PLoS Pathog. 2015 Apr 17;11(4):e1004827.

295

203. Maletto BA, Ropolo AS, Alignani DO, Liscovsky MV, Ranocchia RP, Moron VG, et al. Presence of neutrophil-bearing antigen in lymphoid organs of immune mice. Blood. 2006 Nov 1;108(9):3094–102.

204. Calabro S, Tortoli M, Baudner BC, Pacitto A, Cortese M, O’Hagan DT, et al. Vaccine adjuvants alum and MF59 induce rapid recruitment of neutrophils and monocytes that participate in antigen transport to draining lymph nodes. Vaccine. 2011 Feb 17;29(9):1812–23.

205. Nakano H, Lin KL, Yanagita M, Charbonneau C, Cook DN, Kakiuchi T, et al. Blood- derived inflammatory dendritic cells in lymph nodes stimulate acute T helper type 1 immune responses. Nat Immunol. 2009 Apr;10(4):394–402.

206. Hohl TM, Rivera A, Lipuma L, Gallegos A, Shi C, Mack M, et al. Inflammatory monocytes facilitate adaptive CD4 T cell responses during respiratory fungal infection. Cell Host Microbe. 2009 Nov 19;6(5):470–81.

207. León B, López-Bravo M, Ardavín C. Monocyte-Derived Dendritic Cells Formed at the Infection Site Control the Induction of Protective T Helper 1 Responses against Leishmania. Immunity. 2007 Apr 27;26(4):519–31.

208. Chakarov S, Fazilleau N. Monocyte-derived dendritic cells promote T follicular helper cell differentiation. EMBO Mol Med. 2014 May;6(5):590–603.

209. Hampton HR, Bailey J, Tomura M, Brink R, Chtanova T. Microbe-dependent lymphatic migration of neutrophils modulates lymphocyte proliferation in lymph nodes. Nat Commun. 2015;6:7139.

210. Bonneau M, Epardaud M, Payot F, Niborski V, Thoulouze M-I, Bernex F, et al. Migratory monocytes and granulocytes are major lymphatic carriers of Salmonella from tissue to draining lymph node. J Leukoc Biol. 2006 Feb;79(2):268–76.

211. Johnston MG, Hay JB, Movat H. The Distribution of Prostaglandins in Afferent and Efferent Lymph From Inflammatory Sites. Am J Pathol. 1980 Jun;99(3):695–714.

212. de Veer M, Kemp J, Chatelier J, Elhay MJ, Meeusen ENT. Modulation of soluble and particulate antigen transport in afferent lymph by monophosphoryl lipid A. Immunol Cell Biol. 2012 Apr;90(4):404–10.

213. de Veer M, Neeland M, Burke M, Pleasance J, Nathanielsz J, Elhay M, et al. Cell recruitment and antigen trafficking in afferent lymph after injection of antigen and poly(I:C) containing liposomes, in aqueous or oil-based formulations. Vaccine. 2013 Feb 4;31(7):1012–8.

214. Burke ML, Veer M de, Pleasance J, Neeland M, Elhay M, Harrison P, et al. Innate immune pathways in afferent lymph following vaccination with poly(I:C)-containing liposomes. Innate Immun. 2014 Jul;20(5):501–10.

215. Neeland MR, Elhay MJ, Meeusen ENT, de Veer MJ. Vaccination with liposomal poly(I:C) induces discordant maturation of migratory dendritic cell subsets and anti-viral gene signatures in afferent lymph cells. Vaccine. 2014 Oct 29;32(47):6183–92.

216. Neeland MR, Elhay MJ, Nathanielsz J, Meeusen ENT, Veer MJ de. Incorporation of CpG into a Liposomal Vaccine Formulation Increases the Maturation of Antigen-Loaded

296

Dendritic Cells and Monocytes To Improve Local and Systemic Immunity. J Immunol. 2014 Apr 15;192(8):3666–75.

217. Neeland MR, Shi W, Collignon C, Taubenheim N, Meeusen ENT, Didierlaurent AM, et al. The Lymphatic Immune Response Induced by the Adjuvant AS01: A Comparison of Intramuscular and Subcutaneous Immunization Routes. J Immunol Baltim Md 1950. 2016 01;197(7):2704–14.

218. Lee KM, McKimmie CS, Gilchrist DS, Pallas KJ, Nibbs RJ, Garside P, et al. D6 facilitates cellular migration and fluid flow to lymph nodes by suppressing lymphatic congestion. Blood. 2011 Dec 1;118(23):6220–9.

219. Batista FD, Iber D, Neuberger MS. B cells acquire antigen from target cells after synapse formation. Nature. 2001 May;411(6836):489–94.

220. Okada T, Miller MJ, Parker I, Krummel MF, Neighbors M, Hartley SB, et al. Antigen- engaged B cells undergo chemotaxis toward the T zone and form motile conjugates with helper T cells. PLoS Biol. 2005 Jun;3(6):e150.

221. Kerfoot SM, Yaari G, Patel JR, Johnson KL, Gonzalez DG, Kleinstein SH, et al. Germinal center B cell and T follicular helper cell development initiates in the interfollicular zone. Immunity. 2011 Jun 24;34(6):947–60.

222. Reif K, Ekland EH, Ohl L, Nakano H, Lipp M, Förster R, et al. Balanced responsiveness to chemoattractants from adjacent zones determines B-cell position. Nature. 2002 Mar 7;416(6876):94–9.

223. Bohineust A, Garcia Z, Beuneu H, Lemaître F, Bousso P. Termination of T cell priming relies on a phase of unresponsiveness promoting disengagement from APCs and T cell division. J Exp Med. 2018 May 7;215(5):1481–92.

224. Bajénoff M, Granjeaud S, Guerder S. The Strategy of T Cell Antigen-presenting Cell Encounter in Antigen-draining Lymph Nodes Revealed by Imaging of Initial T Cell Activation. J Exp Med. 2003 Sep 1;198(5):715–24.

225. Radtke AJ, Kastenmüller W, Espinosa DA, Gerner MY, Tse S-W, Sinnis P, et al. Lymph- node resident CD8α+ dendritic cells capture antigens from migratory malaria sporozoites and induce CD8+ T cell responses. PLoS Pathog. 2015 Feb;11(2):e1004637.

226. Pettini E, Prota G, Ciabattini A, Boianelli A, Fiorino F, Pozzi G, et al. Vaginal Immunization to Elicit Primary T-Cell Activation and Dissemination. PLOS ONE. 2013 Dec 5;8(12):e80545.

227. Foulds KE, Shen H. Clonal Competition Inhibits the Proliferation and Differentiation of Adoptively Transferred TCR Transgenic CD4 T Cells in Response to Infection. J Immunol. 2006 Mar 1;176(5):3037–43.

228. Ciabattini A, Pettini E, Andersen P, Pozzi G, Medaglini D. Primary Activation of Antigen- Specific Naive CD4+ and CD8+ T Cells following Intranasal Vaccination with Recombinant Bacteria. Infect Immun. 2008 Jan 12;76(12):5817–25.

229. Bollampalli VP, Harumi Yamashiro L, Feng X, Bierschenk D, Gao Y, Blom H, et al. BCG Skin Infection Triggers IL-1R-MyD88-Dependent Migration of EpCAMlow CD11bhigh Skin Dendritic cells to Draining Lymph Node During CD4+ T-Cell Priming. PLoS Pathog. 2015 Oct 6;11(10):e1005206.

297

230. Gallegos AM, Pamer EG, Glickman MS. Delayed protection by ESAT-6–specific effector CD4+ T cells after airborne M. tuberculosis infection. J Exp Med. 2008 Sep 29;205(10):2359–68.

231. Hickman HD, Takeda K, Skon CN, Murray FR, Hensley SE, Loomis J, et al. Direct priming of antiviral CD8+ T cells in the peripheral interfollicular region of lymph nodes. Nat Immunol. 2008 Feb;9(2):155–65.

232. De Giovanni M, Cutillo V, Giladi A, Sala E, Maganuco CG, Medaglia C, et al. Spatiotemporal regulation of type I interferon expression determines the antiviral polarization of CD4+ T cells. Nat Immunol. 2020;21(3):321–30.

233. Yamane H, Paul WE. Early signaling events that underlie fate decisions of naive CD4+ T cells toward distinct T-helper cell subsets. Immunol Rev. 252(1):12–23.

234. Zhu J, Min B, Hu-Li J, Watson CJ, Grinberg A, Wang Q, et al. Conditional deletion of Gata3 shows its essential function in T(H)1-T(H)2 responses. Nat Immunol. 2004 Nov;5(11):1157–65.

235. Ivanov II, McKenzie BS, Zhou L, Tadokoro CE, Lepelley A, Lafaille JJ, et al. The orphan nuclear receptor RORgammat directs the differentiation program of proinflammatory IL- 17+ T helper cells. Cell. 2006 Sep 22;126(6):1121–33.

236. Bettelli E, Carrier Y, Gao W, Korn T, Strom TB, Oukka M, et al. Reciprocal developmental pathways for the generation of pathogenic effector TH17 and regulatory T cells. Nature. 2006 May 11;441(7090):235–8.

237. Szabo SJ, Kim ST, Costa GL, Zhang X, Fathman CG, Glimcher LH. A novel transcription factor, T-bet, directs Th1 lineage commitment. Cell. 2000 Mar 17;100(6):655–69.

238. Johnston RJ, Poholek AC, DiToro D, Yusuf I, Eto D, Barnett B, et al. Bcl6 and Blimp-1 are reciprocal and antagonistic regulators of T follicular helper cell differentiation. Science. 2009 Aug 21;325(5943):1006–10.

239. Hsieh CS, Macatonia SE, Tripp CS, Wolf SF, O’Garra A, Murphy KM. Development of TH1 CD4+ T cells through IL-12 produced by Listeria-induced macrophages. Science. 1993 Apr 23;260(5107):547–9.

240. Lighvani AA, Frucht DM, Jankovic D, Yamane H, Aliberti J, Hissong BD, et al. T-bet is rapidly induced by interferon-gamma in lymphoid and myeloid cells. Proc Natl Acad Sci U S A. 2001 Dec 18;98(26):15137–42.

241. Martín-Fontecha A, Thomsen LL, Brett S, Gerard C, Lipp M, Lanzavecchia A, et al. Induced recruitment of NK cells to lymph nodes provides IFN-gamma for T(H)1 priming. Nat Immunol. 2004 Dec;5(12):1260–5.

242. De Koker S, Van Hoecke L, De Beuckelaer A, Roose K, Deswarte K, Willart MA, et al. Inflammatory monocytes regulate Th1 oriented immunity to CpG adjuvanted protein vaccines through production of IL-12. Sci Rep [Internet]. 2017 Jul 20 [cited 2017 Sep 6];7. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5519561/

243. Schulz EG, Mariani L, Radbruch A, Höfer T. Sequential polarization and imprinting of type 1 T helper lymphocytes by interferon-gamma and interleukin-12. Immunity. 2009 May;30(5):673–83.

298

244. Tubo NJ, Pagán AJ, Taylor JJ, Nelson RW, Linehan JL, Ertelt JM, et al. Single Naive CD4+ T Cells from a Diverse Repertoire Produce Different Effector Cell Types during Infection. Cell. 2013 May 9;153(4):785–96.

245. Tubo NJ, Jenkins MK. TCR signal quantity and quality in CD4+ T cell differentiation. Trends Immunol. 2014 Dec 1;35(12):591–6.

246. van Panhuys N, Klauschen F, Germain RN. T-cell-receptor-dependent signal intensity dominantly controls CD4(+) T cell polarization In Vivo. Immunity. 2014 Jul 17;41(1):63–74.

247. Groom JR, Richmond J, Murooka TT, Sorensen EW, Sung JH, Bankert K, et al. CXCR3 chemokine receptor-ligand interactions in the lymph node optimize CD4+ T helper 1 cell differentiation. Immunity. 2012 Dec 14;37(6):1091–103.

248. León B, Ballesteros-Tato A, Browning JL, Dunn R, Randall TD, Lund FE. Regulation of T(H)2 development by CXCR5+ dendritic cells and lymphotoxin-expressing B cells. Nat Immunol. 2012 May 27;13(7):681–90.

249. Matloubian M, Cyster JG. Th1 cell induction in lymph nodes according to a red-blue chemokine map. Immunity. 2012 Dec 14;37(6):954–6.

250. Lian J, Luster AD. Chemokine-guided cell positioning in the lymph node orchestrates the generation of adaptive immune responses. Curr Opin Cell Biol. 2015 Oct;36:1–6.

251. Perona-Wright G, Mohrs K, Mohrs M. Sustained signaling by canonical helper T cell cytokines throughout the reactive lymph node. Nat Immunol. 2010 Jun;11(6):520–6.

252. Hu JK, Kagari T, Clingan JM, Matloubian M. Expression of chemokine receptor CXCR3 on T cells affects the balance between effector and memory CD8 T-cell generation. Proc Natl Acad Sci U S A. 2011 May 24;108(21):E118-127.

253. Kurachi M, Kurachi J, Suenaga F, Tsukui T, Abe J, Ueha S, et al. Chemokine receptor CXCR3 facilitates CD8(+) T cell differentiation into short-lived effector cells leading to memory degeneration. J Exp Med. 2011 Aug 1;208(8):1605–20.

254. Janeway CA. Pillars article: approaching the asymptote? Evolution and revolution in immunology. Cold spring harb symp quant biol. 1989. 54: 1-13. J Immunol Baltim Md 1950. 2013 Nov 1;191(9):4475–87.

255. Glenny AT. INSOLUBLE PRECIPITATES IN DIPHTHERIA AND TETANUS IMMUNIZATION. Br Med J. 1930 Aug 16;2(3632):244–5.

256. Glenny AT, Barr M. The precipitation of diphtheria toxoid by potash alum. J Pathol Bacteriol. 1931;34(2):131–8.

257. Sensitization to horse serum by means of adjuvants: Freund, J., and McDermott, K.: Proc. Soc. Exper. Biol. & Med. 49: 548, 1942. J Allergy. 1942 Jul 1;13(5):529.

258. Mutwiri G, Gerdts V, van Drunen Littel-van den Hurk S, Auray G, Eng N, Garlapati S, et al. Combination adjuvants: the next generation of adjuvants? Expert Rev Vaccines. 2011 Jan;10(1):95–107.

259. Del Giudice G, Rappuoli R, Didierlaurent AM. Correlates of adjuvanticity: A review on adjuvants in licensed vaccines. Semin Immunol. 2018;39:14–21.

299

260. Didierlaurent AM, Morel S, Lockman L, Giannini SL, Bisteau M, Carlsen H, et al. AS04, an aluminum salt- and TLR4 agonist-based adjuvant system, induces a transient localized innate immune response leading to enhanced adaptive immunity. J Immunol Baltim Md 1950. 2009 Nov 15;183(10):6186–97.

261. Chang M, Shi Y, Nail SL, HogenEsch H, Adams SB, White JL, et al. Degree of antigen adsorption in the vaccine or interstitial fluid and its effect on the antibody response in rabbits. Vaccine. 2001 Apr 6;19(20–22):2884–9.

262. Morel S, Didierlaurent A, Bourguignon P, Delhaye S, Baras B, Jacob V, et al. Adjuvant System AS03 containing α-tocopherol modulates innate immune response and leads to improved adaptive immunity. Vaccine. 2011 Mar 16;29(13):2461–73.

263. Cioncada R, Maddaluno M, Vo HTM, Woodruff M, Tavarini S, Sammicheli C, et al. Vaccine adjuvant MF59 promotes the intranodal differentiation of antigen-loaded and activated monocyte-derived dendritic cells. PloS One. 2017;12(10):e0185843.

264. Cantisani R, Pezzicoli A, Cioncada R, Malzone C, De Gregorio E, D’Oro U, et al. Vaccine adjuvant MF59 promotes retention of unprocessed antigen in lymph node macrophage compartments and follicular dendritic cells. J Immunol Baltim Md 1950. 2015 Feb 15;194(4):1717–25.

265. Detienne S, Welsby I, Collignon C, Wouters S, Coccia M, Delhaye S, et al. Central Role of CD169+ Lymph Node Resident Macrophages in the Adjuvanticity of the QS-21 Component of AS01. Sci Rep. 2016 Dec 20;6:39475.

266. Desbien AL, Cauwelaert ND, Reed SJ, Bailor HR, Liang H, Carter D, et al. IL-18 and subcapsular lymph node macrophages are essential for enhanced B cell responses with TLR4 agonist adjuvants. J Immunol Baltim Md 1950. 2016 Dec 1;197(11):4351–9.

267. Cain DW, Sanders SE, Cunningham MM, Kelsoe G. Disparate adjuvant properties among three formulations of ‘alum’. Vaccine. 2013 Jan 11;31(4):653–60.

268. Hansen B, Sokolovska A, HogenEsch H, Hem SL. Relationship between the strength of antigen adsorption to an aluminum-containing adjuvant and the immune response. Vaccine. 2007 Sep 4;25(36):6618–24.

269. Romero Méndez IZ, Shi Y, HogenEsch H, Hem SL. Potentiation of the immune response to non-adsorbed antigens by aluminum-containing adjuvants. Vaccine. 2007 Jan 15;25(5):825–33.

270. Kastenmüller K, Wille-Reece U, Lindsay RWB, Trager LR, Darrah PA, Flynn BJ, et al. Protective T cell immunity in mice following protein-TLR7/8 agonist-conjugate immunization requires aggregation, type I IFN, and multiple DC subsets. J Clin Invest. 2011 May;121(5):1782–96.

271. Martínez-Riaño A, Bovolenta ER, Mendoza P, Oeste CL, Martín-Bermejo MJ, Bovolenta P, et al. Antigen phagocytosis by B cells is required for a potent humoral response. EMBO Rep. 2018;19(9).

272. Lian J, Ozga AJ, Sokol CL, Luster AD. Targeting Lymph Node Niches Enhances Type 1 Immune Responses to Immunization. Cell Rep. 2020 May 26;31(8):107679.

300

273. Mosca F, Tritto E, Muzzi A, Monaci E, Bagnoli F, Iavarone C, et al. Molecular and cellular signatures of human vaccine adjuvants. Proc Natl Acad Sci U S A. 2008 Jul 29;105(30):10501–6.

274. Caproni E, Tritto E, Cortese M, Muzzi A, Mosca F, Monaci E, et al. MF59 and Pam3CSK4 boost adaptive responses to influenza subunit vaccine through an IFN type I-independent mechanism of action. J Immunol Baltim Md 1950. 2012 Apr 1;188(7):3088–98.

275. Calabro S, Tritto E, Pezzotti A, Taccone M, Muzzi A, Bertholet S, et al. The adjuvant effect of MF59 is due to the oil-in-water emulsion formulation, none of the individual components induce a comparable adjuvant effect. Vaccine. 2013 Jul 18;31(33):3363–9.

276. Seubert A, Calabro S, Santini L, Galli B, Genovese A, Valentini S, et al. Adjuvanticity of the oil-in-water emulsion MF59 is independent of Nlrp3 inflammasome but requires the adaptor protein MyD88. Proc Natl Acad Sci. 2011 Jul 5;108(27):11169–74.

277. Coccia M, Collignon C, Hervé C, Chalon A, Welsby I, Detienne S, et al. Cellular and molecular synergy in AS01-adjuvanted vaccines results in an early IFNγ response promoting vaccine immunogenicity. Npj Vaccines. 2017 Sep 8;2(1):25.

278. Desbien AL, Reed SJ, Bailor HR, Dubois Cauwelaert N, Laurance JD, Orr MT, et al. Squalene emulsion potentiates the adjuvant activity of the TLR4 agonist, GLA, via inflammatory caspases, IL-18, and IFN-γ. Eur J Immunol. 2015 Feb;45(2):407–17.

279. Cauwelaert ND, Desbien AL, Hudson TE, Pine SO, Reed SG, Coler RN, et al. The TLR4 Agonist Vaccine Adjuvant, GLA-SE, Requires Canonical and Atypical Mechanisms of Action for TH1 Induction. PLOS ONE. 2016 Jan 5;11(1):e0146372.

280. Kwissa M, Nakaya HI, Oluoch H, Pulendran B. Distinct TLR adjuvants differentially stimulate systemic and local innate immune responses in nonhuman primates. Blood. 2012 Mar 1;119(9):2044–55.

281. Dendouga N, Fochesato M, Lockman L, Mossman S, Giannini SL. Cell-mediated immune responses to a varicella-zoster virus glycoprotein E vaccine using both a TLR agonist and QS21 in mice. Vaccine. 2012 Apr 26;30(20):3126–35.

282. Leroux-Roels G, Marchant A, Levy J, Van Damme P, Schwarz TF, Horsmans Y, et al. Impact of adjuvants on CD4(+) T cell and B cell responses to a protein antigen vaccine: Results from a phase II, randomized, multicenter trial. Clin Immunol Orlando Fla. 2016;169:16–27.

283. Burny W, Callegaro A, Bechtold V, Clement F, Delhaye S, Fissette L, et al. Different Adjuvants Induce Common Innate Pathways That Are Associated with Enhanced Adaptive Responses against a Model Antigen in Humans. Front Immunol [Internet]. 2017 Aug 14 [cited 2019 Dec 30];8. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5557780/

284. Wack A, Baudner BC, Hilbert AK, Manini I, Nuti S, Tavarini S, et al. Combination adjuvants for the induction of potent, long-lasting antibody and T-cell responses to influenza vaccine in mice. Vaccine. 2008 Jan 24;26(4):552–61.

285. Lofano G, Mancini F, Salvatore G, Cantisani R, Monaci E, Carrisi C, et al. Oil-in-Water Emulsion MF59 Increases Germinal Center B Cell Differentiation and Persistence in Response to Vaccination. J Immunol Baltim Md 1950. 2015 Aug 15;195(4):1617–27.

301

286. Ansaldi F, Bacilieri S, Durando P, Sticchi L, Valle L, Montomoli E, et al. Cross-protection by MF59-adjuvanted influenza vaccine: neutralizing and haemagglutination-inhibiting antibody activity against A(H3N2) drifted influenza viruses. Vaccine. 2008 Mar 17;26(12):1525–9.

287. Ansaldi F, Zancolli M, Durando P, Montomoli E, Sticchi L, Del Giudice G, et al. Antibody response against heterogeneous circulating influenza virus strains elicited by MF59- and non-adjuvanted vaccines during seasons with good or partial matching between vaccine strain and clinical isolates. Vaccine. 2010 Jun 7;28(25):4123–9.

288. Bihari I, Pánczél G, Kovacs J, Beygo J, Fragapane E. Assessment of antigen-specific and cross-reactive antibody responses to an MF59-adjuvanted A/H5N1 prepandemic influenza vaccine in adult and elderly subjects. Clin Vaccine Immunol CVI. 2012 Dec;19(12):1943–8.

289. Hornung V, Bauernfeind F, Halle A, Samstad EO, Kono H, Rock KL, et al. Silica crystals and aluminum salts activate the NALP3 inflammasome through phagosomal destabilization. Nat Immunol. 2008 Aug;9(8):847–56.

290. Franchi L, Núñez G. The NLRP3 Inflammasome is Critical for Alum-Mediated IL-1β Secretion but Dispensable for Adjuvant Activity. Eur J Immunol. 2008 Aug;38(8):2085–9.

291. Vono M, Taccone M, Caccin P, Gallotta M, Donvito G, Falzoni S, et al. The adjuvant MF59 induces ATP release from muscle that potentiates response to vaccination. Proc Natl Acad Sci. 2013 Dec 24;110(52):21095–100.

292. Ko E-J, Lee Y, Lee Y-T, Kim Y-J, Kim K-H, Kang S-M. MPL and CpG combination adjuvants promote homologous and heterosubtypic cross protection of inactivated split influenza virus vaccine. Antiviral Res. 2018 Aug;156:107–15.

293. Goff PH, Hayashi T, He W, Yao S, Cottam HB, Tan GS, et al. Synthetic Toll-Like Receptor 4 (TLR4) and TLR7 Ligands Work Additively via MyD88 To Induce Protective Antiviral Immunity in Mice. J Virol. 2017 01;91(19).

294. Madan-Lala R, Pradhan P, Roy K. Combinatorial Delivery of Dual and Triple TLR Agonists via Polymeric Pathogen-like Particles Synergistically Enhances Innate and Adaptive Immune Responses. Sci Rep. 2017 31;7(1):2530.

295. Van Maele L, Fougeron D, Cayet D, Chalon A, Piccioli D, Collignon C, et al. Toll-like receptor 4 signaling in hematopoietic-lineage cells contributes to the enhanced activity of the human vaccine adjuvant AS01. Eur J Immunol. 2019 Dec;49(12):2134–45.

296. Seydoux E, Liang H, Dubois Cauwelaert N, Archer M, Rintala ND, Kramer R, et al. Effective Combination Adjuvants Engage Both TLR and Inflammasome Pathways To Promote Potent Adaptive Immune Responses. J Immunol Baltim Md 1950. 2018 01;201(1):98–112.

297. Pennock ND, Gapin L, Kedl RM. IL-27 is required for shaping the magnitude, affinity distribution, and memory of T cells responding to subunit immunization. Proc Natl Acad Sci U S A. 2014 Nov 18;111(46):16472–7.

298. Kilgore AM, Pennock ND, Kedl RM. cDC1 IL-27p28 Production Predicts Vaccine-Elicited CD8+ T Cell Memory and Protective Immunity. J Immunol Baltim Md 1950. 2019 Dec 23;

302

299. RTS,S Clinical Trials Partnership. Efficacy and safety of RTS,S/AS01 malaria vaccine with or without a booster dose in infants and children in Africa: final results of a phase 3, individually randomised, controlled trial. Lancet Lond Engl. 2015 Jul 4;386(9988):31–45.

300. Vandoolaeghe P, Schuerman L. The RTS,S/AS01 malaria vaccine in children 5 to 17 months of age at first vaccination. Expert Rev Vaccines. 2016;15(12):1481–93.

301. Dinges W, Girard P-M, Podzamczer D, Brockmeyer NH, García Felipe, Harrer T, et al. The F4/AS01B HIV-1 Vaccine Candidate Is Safe and Immunogenic, But Does Not Show Viral Efficacy in Antiretroviral Therapy-Naive, HIV-1-Infected Adults. Medicine (Baltimore) [Internet]. 2016 Feb 12 [cited 2020 Jan 3];95(6). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4753889/

302. Tait DR, Hatherill M, Van Der Meeren O, Ginsberg AM, Van Brakel E, Salaun B, et al. Final Analysis of a Trial of M72/AS01E Vaccine to Prevent Tuberculosis. N Engl J Med. 2019 Dec 19;381(25):2429–39.

303. Van Der Meeren O, Hatherill M, Nduba V, Wilkinson RJ, Muyoyeta M, Van Brakel E, et al. Phase 2b Controlled Trial of M72/AS01E Vaccine to Prevent Tuberculosis. N Engl J Med. 2018 Oct 25;379(17):1621–34.

304. Querec T, Bennouna S, Alkan S, Laouar Y, Gorden K, Flavell R, et al. Yellow fever vaccine YF-17D activates multiple dendritic cell subsets via TLR2, 7, 8, and 9 to stimulate polyvalent immunity. J Exp Med. 2006 Feb 20;203(2):413–24.

305. Obermoser G, Presnell S, Domico K, Xu H, Wang Y, Anguiano E, et al. Systems scale interactive exploration reveals quantitative and qualitative differences in response to influenza and pneumococcal vaccines. Immunity. 2013 Apr 18;38(4):831–44.

306. Buckley PR, Alden K, Coccia M, Chalon A, Collignon C, Temmerman ST, et al. Application of Modeling Approaches to Explore Vaccine Adjuvant Mode-of-Action. Front Immunol [Internet]. 2019 Sep 12 [cited 2020 May 9];10. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6751289/

307. Pak-Wittel MA, Yang L, Sojka DK, Rivenbark JG, Yokoyama WM. Interferon-γ mediates chemokine-dependent recruitment of natural killer cells during viral infection. Proc Natl Acad Sci. 2013 Jan 2;110(1):E50–9.

308. van den Berg RA, Coccia M, Ballou WR, Kester KE, Ockenhouse CF, Vekemans J, et al. Predicting RTS,S Vaccine-Mediated Protection from Transcriptomes in a Malaria-Challenge Clinical Trial. Front Immunol [Internet]. 2017 [cited 2020 Apr 10];8. Available from: https://www.frontiersin.org/articles/10.3389/fimmu.2017.00557/full

309. Vandepapelière P, Horsmans Y, Moris P, Van Mechelen M, Janssens M, Koutsoukos M, et al. Vaccine Adjuvant Systems containing monophosphoryl lipid A and QS21 induce strong and persistent humoral and T cell responses against hepatitis B surface antigen in healthy adult volunteers. Vaccine. 2008 Mar 4;26(10):1375–86.

310. Leroux-Roels I, Forgus S, De Boever F, Clement F, Demoitié M-A, Mettens P, et al. Improved CD4+ T cell responses to Mycobacterium tuberculosis in PPD-negative adults by M72/AS01 as compared to the M72/AS02 and Mtb72F/AS02 tuberculosis candidate vaccine formulations: A randomized trial. Vaccine. 2013 Apr 19;31(17):2196–206.

311. White RG, Coons AH, Connolly JM. Studies on antibody production. III. The alum granuloma. J Exp Med. 1955 Jul 1;102(1):73–82.

303

312. Yang C-W, Unanue ER. Neutrophils control the magnitude and spread of the immune response in a thromboxane A2-mediated process. J Exp Med. 2013 Feb 11;210(2):375–87.

313. Franchi L, Núñez G. The Nlrp3 inflammasome is critical for aluminium hydroxide- mediated IL-1β secretion but dispensable for adjuvant activity. Eur J Immunol. 2008;38(8):2085–9.

314. Gavin AL, Hoebe K, Duong B, Ota T, Martin C, Beutler B, et al. Adjuvant-enhanced antibody responses in the absence of toll-like receptor signaling. Science. 2006 Dec 22;314(5807):1936–8.

315. Giannini SL, Hanon E, Moris P, Van Mechelen M, Morel S, Dessy F, et al. Enhanced humoral and memory B cellular immunity using HPV16/18 L1 VLP vaccine formulated with the MPL/aluminium salt combination (AS04) compared to aluminium salt only. Vaccine. 2006 Aug 14;24(33–34):5937–49.

316. Ellebedy AH, Lupfer C, Ghoneim HE, DeBeauchamp J, Kanneganti T-D, Webby RJ. Inflammasome-independent role of the apoptosis-associated speck-like protein containing CARD (ASC) in the adjuvant effect of MF59. Proc Natl Acad Sci U S A. 2011 Feb 15;108(7):2927–32.

317. Orr MT, Duthie MS, Windish HP, Lucas EA, Guderian JA, Hudson TE, et al. MyD88 and TRIF synergistic interaction is required for TH1-cell polarization with a synthetic TLR4 agonist adjuvant. Eur J Immunol. 2013 Sep;43(9):2398–408.

318. Hill DL, Pierson W, Bolland DJ, Mkindi C, Carr EJ, Wang J, et al. The adjuvant GLA-SE promotes human Tfh cell expansion and emergence of public TCRβ clonotypesThe adjuvant GLA-SE enhances human Tfh responses. J Exp Med. 2019 Aug 5;216(8):1857–73.

319. Coler RN, Day TA, Ellis R, Piazza FM, Beckmann AM, Vergara J, et al. The TLR-4 agonist adjuvant, GLA-SE, improves magnitude and quality of immune responses elicited by the ID93 tuberculosis vaccine: first-in-human trial. Npj Vaccines. 2018 Sep 4;3(1):1–9.

320. Medzhitov R. Origin and physiological roles of inflammation [Internet]. Nature. 2008 [cited 2018 Jul 4]. Available from: https://www.nature.com/articles/nature07201

321. Takeuchi O, Akira S. Pattern Recognition Receptors and Inflammation. Cell. 2010 Mar 19;140(6):805–20.

322. Neeland MR, Shi W, Collignon C, Meeusen ENT, Didierlaurent AM, de Veer MJ. The adjuvant system AS01 up-regulates neutrophil CD14 expression and neutrophil-associated antigen transport in the local lymphatic network. Clin Exp Immunol. 2018;192(1):46–53.

323. de Veer M, Kemp J, Chatelier J, Elhay MJ, Meeusen ENT. The kinetics of soluble and particulate antigen trafficking in the afferent lymph, and its modulation by aluminum- based adjuvant. Vaccine. 2010 Sep 14;28(40):6597–602.

324. Neeland MR, Elhay MJ, Powell DR, Rossello FJ, Meeusen ENT, de Veer MJ. Transcriptional profile in afferent lymph cells following vaccination with liposomes incorporating CpG. Immunology. 2015 Mar;144(3):518–29.

325. Palframan RT, Jung S, Cheng G, Weninger W, Luo Y, Dorf M, et al. Inflammatory Chemokine Transport and Presentation in HEV. J Exp Med. 2001 Nov 5;194(9):1361–74.

304

326. McLachlan JB, Hart JP, Pizzo SV, Shelburne CP, Staats HF, Gunn MD, et al. Mast cell– derived tumor necrosis factor induces hypertrophy of draining lymph nodes during infection. Nat Immunol. 2003 Dec;4(12):1199–205.

327. Kunder CA, St. John AL, Li G, Leong KW, Berwin B, Staats HF, et al. Mast cell–derived particles deliver peripheral signals to remote lymph nodes. J Exp Med. 2009 Oct 26;206(11):2455–67.

328. Sagoo P, Garcia Z, Breart B, Lemaître F, Michonneau D, Albert ML, et al. In vivo imaging of inflammasome activation reveals a subcapsular macrophage burst response that mobilizes innate and adaptive immunity. Nat Med. 2016 Jan;22(1):64–71.

329. Sung JH, Zhang H, Moseman EA, Alvarez D, Iannacone M, Henrickson SE, et al. Chemokine Guidance of Central Memory T Cells Is Critical for Anti-Viral Recall Responses in Lymph Nodes. Cell. 2012 Sep 14;150(6):1249–63.

330. Malhotra D, Fletcher AL, Astarita J, Lukacs-Kornek V, Tayalia P, Gonzalez SF, et al. Transcriptional profiling of stroma from inflamed and resting lymph nodes defines immunological hallmarks. Nat Immunol. 2012 Apr 1;13(5):499–510.

331. Wong E, Montoya B, Stotesbury C, Ferez M, Xu R-H, Sigal LJ. Langerhans Cells Orchestrate the Protective Antiviral Innate Immune Response in the Lymph Node. Cell Rep. 2019 03;29(10):3047-3059.e3.

332. Jawdat DM, Rowden G, Marshall JS. Mast cells have a pivotal role in TNF-independent lymph node hypertrophy and the mobilization of Langerhans cells in response to bacterial peptidoglycan. J Immunol Baltim Md 1950. 2006 Aug 1;177(3):1755–62.

333. Zhu M, Yang Y, Wang Y, Wang Z, Fu Y-X. LIGHT regulates inflamed draining lymph node hypertrophy. J Immunol Baltim Md 1950. 2011 Jun 15;186(12):7156–63.

334. Acton SE, Farrugia AJ, Astarita JL, Mourão-Sá D, Jenkins RP, Nye E, et al. Dendritic cells control fibroblastic reticular network tension and lymph node expansion. Nature. 2014 Oct 23;514(7523):498–502.

335. Chyou S, Benahmed F, Chen J, Kumar V, Tian S, Lipp M, et al. Coordinated regulation of lymph node vascular-stromal growth first by CD11c+ cells and then by T and/or B cells. J Immunol Baltim Md 1950. 2011 Dec 1;187(11):5558–67.

336. Yang C-Y, Vogt TK, Favre S, Scarpellino L, Huang H-Y, Tacchini-Cottier F, et al. Trapping of naive lymphocytes triggers rapid growth and remodeling of the fibroblast network in reactive murine lymph nodes. Proc Natl Acad Sci U S A. 2014 Jan 7;111(1):E109-118.

337. Carvalho LP, Petritus PM, Trochtenberg AL, Zaph C, Hill DA, Artis D, et al. Lymph node hypertrophy following Leishmania major infection is dependent upon TLR9. J Immunol Baltim Md 1950. 2012 Feb 1;188(3):1394–401.

338. Benahmed F, Chyou S, Dasoveanu D, Chen J, Kumar V, Iwakura Y, et al. Multiple CD11c+ cells collaboratively express IL-1β to modulate stromal vascular endothelial growth factor and lymph node vascular-stromal growth. J Immunol Baltim Md 1950. 2014 May 1;192(9):4153–63.

339. Kumamoto Y, Mattei LM, Sellers S, Payne GW, Iwasaki A. CD4+ T cells support cytotoxic T lymphocyte priming by controlling lymph node input. Proc Natl Acad Sci U S A. 2011 May 24;108(21):8749–54.

305

340. Cahill RN, Frost H, Trnka Z. The effects of antigen on the migration of recirculating lymphocytes through single lymph nodes. J Exp Med. 1976 Apr 1;143(4):870–88.

341. Chen Q, Fisher DT, Clancy KA, Gauguet J-MM, Wang W-C, Unger E, et al. Fever-range thermal stress promotes lymphocyte trafficking across high endothelial venules via an interleukin 6 trans-signaling mechanism. Nat Immunol. 2006 Dec;7(12):1299–308.

342. Shiow LR, Rosen DB, Brdicková N, Xu Y, An J, Lanier LL, et al. CD69 acts downstream of interferon-alpha/beta to inhibit S1P1 and lymphocyte egress from lymphoid organs. Nature. 2006 Mar 23;440(7083):540–4.

343. Hopkins J, McConnell I, Pearson JD. Lymphocyte traffic through antigen-stimulated lymph nodes. II. Role of Prostaglandin E2 as a mediator of cell shutdown. Immunology. 1981 Feb;42(2):225–31.

344. McConnell I, Hopkins J. Lymphocyte traffic through antigen-stimulated lymph nodes. I. Complement activation within lymph nodes initiates cell shutdown. Immunology. 1981 Feb;42(2):217–23.

345. Mondor I, Jorquera A, Sene C, Adriouch S, Adams RH, Zhou B, et al. Clonal Proliferation and Stochastic Pruning Orchestrate Lymph Node Vasculature Remodeling. Immunity. 2016 18;45(4):877–88.

346. Wee JL-K, Greenwood DLV, Han X, Scheerlinck J-PY. Inflammatory cytokines IL-6 and TNF-α regulate lymphocyte trafficking through the local lymph node. Vet Immunol Immunopathol. 2011 Nov 15;144(1):95–103.

347. Astarita JL, Cremasco V, Fu J, Darnell MC, Peck JR, Nieves-Bonilla JM, et al. The CLEC-2- podoplanin axis controls the contractility of fibroblastic reticular cells and lymph node microarchitecture. Nat Immunol. 2015 Jan;16(1):75–84.

348. Martinez VG, Pankova V, Krasny L, Singh T, Makris S, White IJ, et al. Fibroblastic Reticular Cells Control Conduit Matrix Deposition during Lymph Node Expansion. Cell Rep. 2019 Nov 26;29(9):2810-2822.e5.

349. Majumder S, Amatya N, Revu S, Jawale CV, Wu D, Rittenhouse N, et al. IL-17 metabolically reprograms activated fibroblastic reticular cells for proliferation and survival. Nat Immunol. 2019 May;20(5):534–45.

350. Farrell HE, Davis-Poynter N, Bruce K, Lawler C, Dolken L, Mach M, et al. Lymph Node Macrophages Restrict Murine Cytomegalovirus Dissemination. J Virol. 2015 Jul 15;89(14):7147–58.

351. Gaya M, Barral P, Burbage M, Aggarwal S, Montaner B, Warren Navia A, et al. Initiation of Antiviral B Cell Immunity Relies on Innate Signals from Spatially Positioned NKT Cells. Cell. 2018 Jan 25;172(3):517-533.e20.

352. Bajénoff M, Breart B, Huang AYC, Qi H, Cazareth J, Braud VM, et al. Natural killer cell behavior in lymph nodes revealed by static and real-time imaging. J Exp Med. 2006 Mar 20;203(3):619–31.

353. Garrod KR, Wei SH, Parker I, Cahalan MD. Natural killer cells actively patrol peripheral lymph nodes forming stable conjugates to eliminate MHC-mismatched targets. Proc Natl Acad Sci U S A. 2007 Jul 17;104(29):12081–6.

306

354. Jenne CN, Enders A, Rivera R, Watson SR, Bankovich AJ, Pereira JP, et al. T-bet- dependent S1P5 expression in NK cells promotes egress from lymph nodes and bone marrow. J Exp Med. 2009 Oct 26;206(11):2469–81.

355. Coombes JL, Han S-J, van Rooijen N, Raulet DH, Robey EA. Infection-induced regulation of NK cells by macrophages and collagen at the lymph node subcapsular sinus. Cell Rep. 2012 Jul 26;2(1):124–35.

356. Farsakoglu Y, Palomino-Segura M, Latino I, Zanaga S, Chatziandreou N, Pizzagalli DU, et al. Influenza Vaccination Induces NK-Cell-Mediated Type-II IFN Response that Regulates Humoral Immunity in an IL-6-Dependent Manner. Cell Rep. 2019 26;26(9):2307-2315.e5.

357. Wong E, Xu R-H, Rubio D, Lev A, Stotesbury C, Fang M, et al. Migratory Dendritic Cells, Group 1 Innate Lymphoid Cells, and Inflammatory Monocytes Collaborate to Recruit NK Cells to the Virus-Infected Lymph Node. Cell Rep. 2018 Jul 3;24(1):142–54.

358. Spits H, Artis D, Colonna M, Diefenbach A, Di Santo JP, Eberl G, et al. Innate lymphoid cells — a proposal for uniform nomenclature. Nat Rev Immunol. 2013 Feb;13(2):145–9.

359. Dutton EE, Gajdasik DW, Willis C, Fiancette R, Bishop EL, Camelo A, et al. Peripheral lymph nodes contain migratory and resident innate lymphoid cell populations. Sci Immunol. 2019 31;4(35).

360. Mackley EC, Houston S, Marriott CL, Halford EE, Lucas B, Cerovic V, et al. CCR7- dependent trafficking of RORγ+ ILCs creates a unique microenvironment within mucosal draining lymph nodes. Nat Commun. 2015 Jan 9;6:5862.

361. Melo‐Gonzalez F, Hepworth MR. Functional and phenotypic heterogeneity of group 3 innate lymphoid cells. Immunology. 2017 Mar;150(3):265–75.

362. Cerundolo V, Silk JD, Masri SH, Salio M. Harnessing invariant NKT cells in vaccination strategies. Nat Rev Immunol. 2009 Jan;9(1):28–38.

363. Barral P, Polzella P, Bruckbauer A, van Rooijen N, Besra GS, Cerundolo V, et al. CD169(+) macrophages present lipid antigens to mediate early activation of iNKT cells in lymph nodes. Nat Immunol. 2010 Apr;11(4):303–12.

364. Xu R-H, Fang M, Klein-Szanto A, Sigal LJ. Memory CD8+ T cells are gatekeepers of the lymph node draining the site of viral infection. Proc Natl Acad Sci U S A. 2007 Jun 26;104(26):10992–7.

365. Lok LSC, Dennison TW, Mahbubani KM, Saeb-Parsy K, Chilvers ER, Clatworthy MR. Phenotypically distinct neutrophils patrol uninfected human and mouse lymph nodes. Proc Natl Acad Sci. 2019 Sep 17;116(38):19083–9.

366. Jakubzick C, Gautier EL, Gibbings SL, Sojka DK, Schlitzer A, Johnson TE, et al. Minimal differentiation of classical monocytes as they survey steady-state tissues and transport antigen to lymph nodes. Immunity. 2013 Sep 19;39(3):599–610.

367. Gorlino CV, Ranocchia RP, Harman MF, García IA, Crespo MI, Morón G, et al. Neutrophils exhibit differential requirements for homing molecules in their lymphatic and blood trafficking into draining lymph nodes. J Immunol Baltim Md 1950. 2014 Aug 15;193(4):1966–74.

307

368. Chtanova T, Schaeffer M, Han S-J, van Dooren GG, Nollmann M, Herzmark P, et al. Dynamics of neutrophil migration in lymph nodes during infection. Immunity. 2008 Sep;29(3):487–96.

369. Mitchell LA, Henderson AJ, Dow SW. Suppression of vaccine immunity by inflammatory monocytes. J Immunol Baltim Md 1950. 2012 Dec 15;189(12):5612–21.

370. Mitchell LA, Hansen RJ, Beaupre AJ, Gustafson DL, Dow SW. Optimized dosing of a CCR2 antagonist for amplification of vaccine immunity. Int Immunopharmacol. 2013 Feb;15(2):357–63.

371. Yang C-W, Strong BSI, Miller MJ, Unanue ER. Neutrophils influence the level of antigen presentation during the immune response to protein antigens in adjuvants. J Immunol Baltim Md 1950. 2010 Sep 1;185(5):2927–34.

372. Parsa R, Lund H, Georgoudaki A-M, Zhang X-M, Ortlieb Guerreiro-Cacais A, Grommisch D, et al. BAFF-secreting neutrophils drive plasma cell responses during emergency granulopoiesis. J Exp Med. 2016 Jul 25;213(8):1537–53.

373. Beauvillain C, Cunin P, Doni A, Scotet M, Jaillon S, Loiry M-L, et al. CCR7 is involved in the migration of neutrophils to lymph nodes. Blood. 2011 Jan 27;117(4):1196–204.

374. Arokiasamy S, Zakian C, Dilliway J, Wang W, Nourshargh S, Voisin M-B. Endogenous TNFα orchestrates the trafficking of neutrophils into and within lymphatic vessels during acute inflammation. Sci Rep. 2017 Mar 13;7:44189.

375. Hickman HD, Li L, Reynoso GV, Rubin EJ, Skon CN, Mays JW, et al. Chemokines control naive CD8+ T cell selection of optimal lymph node antigen presenting cells. J Exp Med. 2011 Nov 21;208(12):2511–24.

376. Castell SD, Harman MF, Morón G, Maletto BA, Pistoresi-Palencia MC. Neutrophils Which Migrate to Lymph Nodes Modulate CD4+ T Cell Response by a PD-L1 Dependent Mechanism. Front Immunol [Internet]. 2019 [cited 2020 May 9];10. Available from: https://www.frontiersin.org/articles/10.3389/fimmu.2019.00105/full

377. Fooksman DR, Nussenzweig MC, Dustin ML. Myeloid cells limit production of antibody- secreting cells after immunization in the lymph node., Myeloid cells Limit Production of Antibody Secreting cells After Immunization in the Lymph Node. J Immunol Baltim Md 1950 J Immunol Baltim Md 1950. 2014 Feb 1;192, 192(3, 3):1004, 1004–12.

378. Hettinger J, Richards DM, Hansson J, Barra MM, Joschko A-C, Krijgsveld J, et al. Origin of monocytes and macrophages in a committed progenitor. Nat Immunol. 2013 Aug;14(8):821–30.

379. Geissmann F, Jung S, Littman DR. Blood monocytes consist of two principal subsets with distinct migratory properties. Immunity. 2003 Jul;19(1):71–82.

380. Shi C, Pamer EG. Monocyte recruitment during infection and inflammation. Nat Rev Immunol. 2011 Oct 10;11(11):762–74.

381. Sammicheli S, Kuka M, Di Lucia P, de Oya NJ, De Giovanni M, Fioravanti J, et al. Inflammatory monocytes hinder antiviral B cell responses. Sci Immunol [Internet]. 2016 Oct 21 [cited 2017 Jun 25];1(4). Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5111729/

308

382. Han S-J, Melichar HJ, Coombes JL, Chan SW, Koshy AA, Boothroyd JC, et al. Internalization and TLR-dependent type I interferon production by monocytes in response to Toxoplasma gondii. Immunol Cell Biol. 2014 Nov;92(10):872–81.

383. Langlet C, Tamoutounour S, Henri S, Luche H, Ardouin L, Grégoire C, et al. CD64 expression distinguishes monocyte-derived and conventional dendritic cells and reveals their distinct role during intramuscular immunization. J Immunol Baltim Md 1950. 2012 Feb 15;188(4):1751–60.

384. Tamoutounour S, Guilliams M, Montanana Sanchis F, Liu H, Terhorst D, Malosse C, et al. Origins and Functional Specialization of Macrophages and of Conventional and Monocyte-Derived Dendritic Cells in Mouse Skin. Immunity. 2013 Nov 14;39(5):925–38.

385. Menezes S, Melandri D, Anselmi G, Perchet T, Loschko J, Dubrot J, et al. The Heterogeneity of Ly6Chi Monocytes Controls Their Differentiation into iNOS+ Macrophages or Monocyte-Derived Dendritic Cells. Immunity. 2016 Dec 20;45(6):1205–18.

386. Siddiqui KRR, Laffont S, Powrie F. E-cadherin marks a subset of inflammatory dendritic cells that promote T cell-mediated colitis. Immunity. 2010 Apr 23;32(4):557–67.

387. Cheong C, Matos I, Choi J-H, Dandamudi DB, Shrestha E, Longhi MP, et al. Microbial Stimulation Fully Differentiates Monocytes to DC-SIGN/CD209+ Dendritic Cells for Immune T Cell Areas. Cell. 2010 Oct 29;143(3):416–29.

388. Gray EE, Friend S, Suzuki K, Phan TG, Cyster JG. Subcapsular Sinus Macrophage Fragmentation and CD169+ Bleb Acquisition by Closely Associated IL-17-Committed Innate-Like Lymphocytes. PLOS ONE. 2012 Jun 1;7(6):e38258.

389. Leirião P, del Fresno C, Ardavín C. Monocytes as effector cells: activated Ly-6C(high) mouse monocytes migrate to the lymph nodes through the lymph and cross-present antigens to CD8+ T cells. Eur J Immunol. 2012 Aug;42(8):2042–51.

390. Janatpour MJ, Hudak S, Sathe M, Sedgwick JD, McEvoy LM. Tumor Necrosis Factor– dependent Segmental Control of MIG Expression by High Endothelial Venules in Inflamed Lymph Nodes Regulates Monocyte Recruitment. J Exp Med. 2001 Nov 5;194(9):1375–84.

391. Chatziandreou N, Farsakoglu Y, Palomino-Segura M, D’Antuono R, Pizzagalli DU, Sallusto F, et al. Macrophage Death following Influenza Vaccination Initiates the Inflammatory Response that Promotes Dendritic Cell Function in the Draining Lymph Node. Cell Rep. 2017 Mar 7;18(10):2427–40.

392. León B, Ardavín C. Monocyte migration to inflamed skin and lymph nodes is differentially controlled by L-selectin and PSGL-1. Blood. 2008 Mar 15;111(6):3126–30.

393. Xiong H, Keith JW, Samilo DW, Carter RA, Leiner IM, Pamer EG. Innate Lymphocyte/Ly6C(hi) Monocyte Crosstalk Promotes Klebsiella Pneumoniae Clearance. Cell. 2016 Apr 21;165(3):679–89.

394. Haist KC, Burrack KS, Davenport BJ, Morrison TE. Inflammatory monocytes mediate control of acute alphavirus infection in mice. PLOS Pathog. 2017 Dec 15;13(12):e1006748.

395. Goritzka M, Makris S, Kausar F, Durant LR, Pereira C, Kumagai Y, et al. Alveolar macrophage–derived type I interferons orchestrate innate immunity to RSV through recruitment of antiviral monocytes. J Exp Med. 2015 May 4;212(5):699–714.

309

396. Hohl TM, Rivera A, Lipuma L, Gallegos A, Shi C, Mack M, et al. Inflammatory monocytes facilitate adaptive CD4 T cell responses during respiratory fungal infection. Cell Host Microbe. 2009 Nov 19;6(5):470–81.

397. Peters W, Dupuis M, Charo IF. A mechanism for the impaired IFN-gamma production in C-C chemokine receptor 2 (CCR2) knockout mice: role of CCR2 in linking the innate and adaptive immune responses. J Immunol Baltim Md 1950. 2000 Dec 15;165(12):7072–7.

398. Samstein M, Schreiber HA, Leiner IM, Susac B, Glickman MS, Pamer EG. Essential yet limited role for CCR2+ inflammatory monocytes during Mycobacterium tuberculosis- specific T cell priming. eLife. 2013 Nov 12;2:e01086.

399. McCarthy MK, Reynoso GV, Winkler ES, Mack M, Diamond MS, Hickman HD, et al. MyD88-dependent influx of monocytes and neutrophils impairs lymph node B cell responses to chikungunya virus infection via Irf5, Nos2 and Nox2. PLOS Pathog. 2020 Jan 30;16(1):e1008292.

400. Sensken S-C, Nagarajan M, Bode C, Gräler MH. Local Inactivation of Sphingosine 1- Phosphate in Lymph Nodes Induces Lymphopenia. J Immunol. 2011 Mar 15;186(6):3432– 40.

401. Coro ES, Chang WLW, Baumgarth N. Type I IFN receptor signals directly stimulate local B cells early following influenza virus infection. J Immunol Baltim Md 1950. 2006 Apr 1;176(7):4343–51.

402. Li JL, Goh CC, Keeble JL, Qin JS, Roediger B, Jain R, et al. Intravital multiphoton imaging of immune responses in the mouse ear skin. Nat Protoc. 2012 Feb;7(2):221–34.

403. Van den Broeck W, Derore A, Simoens P. Anatomy and nomenclature of murine lymph nodes: Descriptive study and nomenclatory standardization in BALB/cAnNCrl mice. J Immunol Methods. 2006 May 30;312(1–2):12–9.

404. Morphological Mouse Phenotyping - 1st Edition [Internet]. [cited 2017 Aug 16]. Available from: https://www.elsevier.com/books/morphological-mouse- phenotyping/ruberte/978-0-12-812805-3

405. Kawashima Y. Lymph System in Mice. Jpn J Veternary Res. 1964;

406. Frey A, Di Canzio J, Zurakowski D. A statistically defined endpoint titer determination method for immunoassays. J Immunol Methods. 1998 Dec 1;221(1–2):35–41.

407. Minassian AM, Ronan EO, Poyntz H, Hill AVS, McShane H. Preclinical development of an in vivo BCG challenge model for testing candidate TB vaccine efficacy. PloS One. 2011;6(5):e19840.

408. Mabtech. ELISpot Tutorial - How to Count Spots Using an AID ELISpot Reader [Internet]. 2015 [cited 2016 Jan 11]. Available from: https://www.youtube.com/watch?v=SPuFjr44U-I

409. Nandakumar S, Kannanganat S, Posey JE, Amara RR, Sable SB. Attrition of T-cell functions and simultaneous upregulation of inhibitory markers correspond with the waning of BCG-induced protection against tuberculosis in mice. PloS One. 2014;9(11):e113951.

310

410. Schmittgen TD, Livak KJ. Analyzing real-time PCR data by the comparative CT method. Nat Protoc. 2008 Jun;3(6):1101–8.

411. Bate ST, Clark RA. The design and statistical analysis of animal experiments. Cambridge, United Kingdom: Cambridge University Press; 2014. 310 p.

412. Herr HW, Morales A. History of bacillus Calmette-Guerin and bladder cancer: an immunotherapy success story. J Urol. 2008 Jan;179(1):53–6.

413. Mangtani P, Abubakar I, Ariti C, Beynon R, Pimpin L, Fine PEM, et al. Protection by BCG against tuberculosis: a systematic review of randomised controlled trials. Clin Infect Dis. 2013 Dec 13;cit790.

414. BCG and vole bacillus vaccines in the prevention of tuberculosis in adolescence and early adult life. Bull World Health Organ. 1972;46(3):371–85.

415. Fifteen year follow up of trial of BCG vaccines in south India for tuberculosis prevention. Tuberculosis Research Centre (ICMR), Chennai. Indian J Med Res. 1999 Aug;110:56–69.

416. Roy A, Eisenhut M, Harris RJ, Rodrigues LC, Sridhar S, Habermann S, et al. Effect of BCG vaccination against Mycobacterium tuberculosis infection in children: systematic review and meta-analysis. The BMJ. 2014 Aug 5;349:g4643.

417. McShane H, Williams A. A review of preclinical animal models utilised for TB vaccine evaluation in the context of recent human efficacy data. Tuberc Edinb Scotl. 2014 Mar;94(2):105–10.

418. Ernst JD. The immunological life cycle of tuberculosis. Nat Rev Immunol. 2012 Aug;12(8):581–91.

419. Muñoz-Fernández MA, Fernández MA, Fresno M. Synergism between tumor necrosis factor-alpha and interferon-gamma on macrophage activation for the killing of intracellular Trypanosoma cruzi through a nitric oxide-dependent mechanism. Eur J Immunol. 1992 Feb;22(2):301–7.

420. Herbst S, Schaible UE, Schneider BE. Interferon gamma activated macrophages kill mycobacteria by nitric oxide induced apoptosis. PloS One. 2011;6(5):e19105.

421. Flynn JL, Chan J, Triebold KJ, Dalton DK, Stewart TA, Bloom BR. An essential role for interferon gamma in resistance to Mycobacterium tuberculosis infection. J Exp Med. 1993 Dec 1;178(6):2249–54.

422. Cooper AM, Dalton DK, Stewart TA, Griffin JP, Russell DG, Orme IM. Disseminated tuberculosis in interferon gamma gene-disrupted mice. J Exp Med. 1993 Dec 1;178(6):2243–7.

423. Mogues T, Goodrich ME, Ryan L, LaCourse R, North RJ. The relative importance of T cell subsets in immunity and immunopathology of airborne Mycobacterium tuberculosis infection in mice. J Exp Med. 2001 Feb 5;193(3):271–80.

424. Caruso AM, Serbina N, Klein E, Triebold K, Bloom BR, Flynn JL. Mice deficient in CD4 T cells have only transiently diminished levels of IFN-gamma, yet succumb to tuberculosis. J Immunol Baltim Md 1950. 1999 May 1;162(9):5407–16.

311

425. Scanga CA, Mohan VP, Yu K, Joseph H, Tanaka K, Chan J, et al. Depletion of CD4(+) T cells causes reactivation of murine persistent tuberculosis despite continued expression of interferon gamma and nitric oxide synthase 2. J Exp Med. 2000 Aug 7;192(3):347–58.

426. Gallegos AM, van Heijst JWJ, Samstein M, Su X, Pamer EG, Glickman MS. A gamma interferon independent mechanism of CD4 T cell mediated control of M. tuberculosis infection in vivo. PLoS Pathog. 2011 May;7(5):e1002052.

427. Bustamante J, Boisson-Dupuis S, Abel L, Casanova J-L. Mendelian susceptibility to mycobacterial disease: genetic, immunological, and clinical features of inborn errors of IFN-γ immunity. Semin Immunol. 2014 Dec;26(6):454–70.

428. Darrah PA, Patel DT, De Luca PM, Lindsay RWB, Davey DF, Flynn BJ, et al. Multifunctional TH1 cells define a correlate of vaccine-mediated protection against Leishmania major. Nat Med. 2007 Jul;13(7):843–50.

429. Waeckerle-Men Y, Bruffaerts N, Liang Y, Jurion F, Sander P, Kündig TM, et al. Lymph node targeting of BCG vaccines amplifies CD4 and CD8 T-cell responses and protection against Mycobacterium tuberculosis. Vaccine. 2013 Feb 4;31(7):1057–64.

430. Garcia-Pelayo MC, Bachy VS, Kaveh DA, Hogarth PJ. BALB/c mice display more enhanced BCG vaccine induced Th1 and Th17 response than C57BL/6 mice but have equivalent protection. Tuberculosis [Internet]. [cited 2014 Dec 15]; Available from: http://www.sciencedirect.com/science/article/pii/S1472979213202945

431. Sable SB, Cheruvu M, Nandakumar S, Sharma S, Bandyopadhyay K, Kellar KL, et al. Cellular immune responses to nine Mycobacterium tuberculosis vaccine candidates following intranasal vaccination. PloS One. 2011;6(7):e22718.

432. Kozakiewicz L, Chen Y, Xu J, Wang Y, Dunussi-Joannopoulos K, Ou Q, et al. B cells regulate neutrophilia during Mycobacterium tuberculosis infection and BCG vaccination by modulating the interleukin-17 response. PLoS Pathog. 2013;9(7):e1003472.

433. Goonetilleke NP, McShane H, Hannan CM, Anderson RJ, Brookes RH, Hill AVS. Enhanced immunogenicity and protective efficacy against Mycobacterium tuberculosis of bacille Calmette-Guérin vaccine using mucosal administration and boosting with a recombinant modified vaccinia virus Ankara. J Immunol Baltim Md 1950. 2003 Aug 1;171(3):1602–9.

434. Vogelzang A, Perdomo C, Zedler U, Kuhlmann S, Hurwitz R, Gengenbacher M, et al. Central memory CD4+ T cells are responsible for the recombinant Bacillus Calmette-Guérin ΔureC::hly vaccine’s superior protection against tuberculosis. J Infect Dis. 2014 Dec 15;210(12):1928–37.

435. Jagannath C, Lindsey DR, Dhandayuthapani S, Xu Y, Hunter RL, Eissa NT. Autophagy enhances the efficacy of BCG vaccine by increasing peptide presentation in mouse dendritic cells. Nat Med. 2009 Mar;15(3):267–76.

436. Khatri B, Whelan A, Clifford D, Petrera A, Sander P, Vordermeier HM. BCG Δzmp1 vaccine induces enhanced antigen specific immune responses in cattle. Vaccine. 2014 Feb 7;32(7):779–84.

437. Sander P, Clark S, Petrera A, Vilaplana C, Meuli M, Selchow P, et al. Deletion of zmp1 improves Mycobacterium bovis BCG-mediated protection in a guinea pig model of tuberculosis. Vaccine. 2015 Mar 10;33(11):1353–9.

312

438. Johansen P, Fettelschoss A, Amstutz B, Selchow P, Waeckerle-Men Y, Keller P, et al. Relief from Zmp1-mediated arrest of phagosome maturation is associated with facilitated presentation and enhanced immunogenicity of mycobacterial antigens. Clin Vaccine Immunol CVI. 2011 Jun;18(6):907–13.

439. Gröschel MI, Sayes F, Shin SJ, Frigui W, Pawlik A, Orgeur M, et al. Recombinant BCG Expressing ESX-1 of Mycobacterium marinum Combines Low Virulence with Cytosolic Immune Signaling and Improved TB Protection. Cell Rep. 2017 14;18(11):2752–65.

440. Aagaard C, Hoang T, Dietrich J, Cardona P-J, Izzo A, Dolganov G, et al. A multistage tuberculosis vaccine that confers efficient protection before and after exposure. Nat Med. 2011 Feb;17(2):189–94.

441. Sweeney KA, Dao DN, Goldberg MF, Hsu T, Venkataswamy MM, Henao-Tamayo M, et al. A recombinant Mycobacterium smegmatis induces potent bactericidal immunity against Mycobacterium tuberculosis. Nat Med. 2011 Oct;17(10):1261–8.

442. Aagaard C, Hoang TTKT, Izzo A, Billeskov R, Troudt J, Arnett K, et al. Protection and Polyfunctional T Cells Induced by Ag85B-TB10.4/IC31® against Mycobacterium tuberculosis Is Highly Dependent on the Antigen Dose. PLoS ONE. 2009 Jun 16;4(6):e5930.

443. Pitt JM, Stavropoulos E, Redford PS, Beebe AM, Bancroft GJ, Young DB, et al. Blockade of IL-10 signaling during bacillus Calmette-Guérin vaccination enhances and sustains Th1, Th17, and innate lymphoid IFN-γ and IL-17 responses and increases protection to Mycobacterium tuberculosis infection. J Immunol Baltim Md 1950. 2012 Oct 15;189(8):4079–87.

444. Kagina BMN, Abel B, Scriba TJ, Hughes EJ, Keyser A, Soares A, et al. Specific T cell frequency and cytokine expression profile do not correlate with protection against tuberculosis after bacillus Calmette-Guérin vaccination of newborns. Am J Respir Crit Care Med. 2010 Oct 15;182(8):1073–9.

445. Tenaillon O, Skurnik D, Picard B, Denamur E. The population genetics of commensal Escherichia coli. Nat Rev Microbiol. 2010 Mar 1;8(3):207–17.

446. Motwani MP, Flint JD, De Maeyer RP, Fullerton JN, Smith AM, Marks DJ, et al. Novel translational model of resolving inflammation triggered by UV-killed E. coli. J Pathol Clin Res. 2016 Jul;2(3):154–65.

447. Johnston MG, Hay JB, Movat HZ. Kinetics of prostaglandin production in various inflammatory lesions, measured in draining lymph. Am J Pathol. 1979 Apr;95(1):225–38.

448. Ramsay M. Chapter 32: Tuberculosis. In: Immunisation against Infectious Diseases [Internet]. Public Health England; 2013. p. 1–16. Available from: https://www.gov.uk/government/publications/tuberculosis-the-green-book-chapter-32

449. Smith SG, Joosten SA, Verscheure V, Pathan AA, McShane H, Ottenhoff THM, et al. Identification of Major Factors Influencing ELISpot-Based Monitoring of Cellular Responses to Antigens from Mycobacterium tuberculosis. PLoS ONE. 2009 Nov 24;4(11):e7972.

450. Wolinsky E. Mycobacterial lymphadenitis in children: a prospective study of 105 nontuberculous cases with long-term follow-up. Clin Infect Dis Off Publ Infect Dis Soc Am. 1995 Apr;20(4):954–63.

313

451. Goraya JS, Virdi VS. Bacille Calmette-Guérin lymphadenitis. Postgrad Med J. 2002 Jun 1;78(920):327–9.

452. Radulovic K, Manta C, Rossini V, Holzmann K, Kestler HA, Wegenka UM, et al. CD69 regulates type I IFN-induced tolerogenic signals to mucosal CD4 T cells that attenuate their colitogenic potential. J Immunol Baltim Md 1950. 2012 Feb 15;188(4):2001–13.

453. Sun S, Zhang X, Tough DF, Sprent J. Type I Interferon-mediated Stimulation of T Cells by CpG DNA. J Exp Med. 1998 Dec 21;188(12):2335–42.

454. Soehnlein O, Lindbom L, Weber C. Mechanisms underlying neutrophil-mediated monocyte recruitment. Blood. 2009 Nov 19;114(21):4613–23.

455. Hurst SM, Wilkinson TS, McLoughlin RM, Jones S, Horiuchi S, Yamamoto N, et al. IL-6 and Its Soluble Receptor Orchestrate a Temporal Switch in the Pattern of Leukocyte Recruitment Seen during Acute Inflammation. Immunity. 2001 Jun 1;14(6):705–14.

456. Ramsay M. Immunisation Procedures. In: Immunisation Against Infectious Diseases (The Green Book). Public Health England; 2017.

457. Wei JCJ, Edwards GA, Martin DJ, Huang H, Crichton ML, Kendall MAF. Allometric scaling of skin thickness, elasticity, viscoelasticity to mass for micro-medical device translation: from mice, rats, rabbits, pigs to humans. Sci Rep. 2017 Nov 21;7(1):15885.

458. Fulton SA, Reba SM, Martin TD, Boom WH. Neutrophil-Mediated Mycobacteriocidal Immunity in the Lung during Mycobacterium bovis BCG Infection in C57BL/6 Mice. Infect Immun. 2002 Sep;70(9):5322–7.

459. Fulton SA, Martin TD, Redline RW, Henry Boom W. Pulmonary immune responses during primary mycobacterium bovis- Calmette-Guerin bacillus infection in C57Bl/6 mice. Am J Respir Cell Mol Biol. 2000 Mar;22(3):333–43.

460. Lombard R, Doz E, Carreras F, Epardaud M, Le Vern Y, Buzoni-Gatel D, et al. IL-17RA in Non-Hematopoietic Cells Controls CXCL-1 and 5 Critical to Recruit Neutrophils to the Lung of Mycobacteria-Infected Mice during the Adaptive Immune Response. PLoS ONE [Internet]. 2016 Feb 12 [cited 2017 Nov 15];11(2). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4752258/

461. Novikov A, Cardone M, Thompson R, Shenderov K, Kirschman KD, Mayer-Barber KD, et al. Mycobacterium tuberculosis triggers host type I interferon signaling to regulate IL-1β production in human macrophages. J Immunol Baltim Md 1950. 2011 Sep 1;187(5):2540– 7.

462. Ganchua SKC, Cadena AM, Maiello P, Gideon HP, Myers AJ, Junecko BF, et al. Lymph nodes are sites of prolonged bacterial persistence during Mycobacterium tuberculosis infection in macaques. PLOS Pathog. 2018 Nov 1;14(11):e1007337.

463. Smith AM, Rahman FZ, Hayee B, Graham SJ, Marks DJB, Sewell GW, et al. Disordered macrophage cytokine secretion underlies impaired acute inflammation and bacterial clearance in Crohn’s disease. J Exp Med. 2009 Aug 31;206(9):1883–97.

464. Kimura M, Suzuki J, Amemiya K. Mouse granuloma pouch induced by Freund’s complete adjuvant with croton oil. J Pharmacobiodyn. 1985 Jun;8(6):393–400.

314

465. Xu R-H, Wong EB, Rubio D, Roscoe F, Ma X, Nair S, et al. Sequential activation of two pathogen-sensing pathways is required for type I interferon expression and resistance to an acute DNA virus infection. Immunity. 2015 Dec 15;43(6):1148–59.

466. Lee AJ, Chen B, Chew MV, Barra NG, Shenouda MM, Nham T, et al. Inflammatory monocytes require type I interferon receptor signaling to activate NK cells via IL-18 during a mucosal viral infection. J Exp Med. 2017 Apr 3;214(4):1153–67.

467. Seo S-U, Kwon H-J, Ko H-J, Byun Y-H, Seong BL, Uematsu S, et al. Type I interferon signaling regulates Ly6C(hi) monocytes and neutrophils during acute viral pneumonia in mice. PLoS Pathog. 2011 Feb;7(2):e1001304.

468. Hokeness KL, Kuziel WA, Biron CA, Salazar-Mather TP. Monocyte chemoattractant protein-1 and CCR2 interactions are required for IFN-alpha/beta-induced inflammatory responses and antiviral defense in liver. J Immunol Baltim Md 1950. 2005 Feb 1;174(3):1549–56.

469. Lin KL, Suzuki Y, Nakano H, Ramsburg E, Gunn MD. CCR2+ monocyte-derived dendritic cells and exudate macrophages produce influenza-induced pulmonary immune pathology and mortality. J Immunol Baltim Md 1950. 2008 Feb 15;180(4):2562–72.

470. Lehmann MH, Torres-Domínguez LE, Price PJR, Brandmüller C, Kirschning CJ, Sutter G. CCL2 expression is mediated by type I IFN receptor and recruits NK and T cells to the lung during MVA infection. J Leukoc Biol. 2016 Jun;99(6):1057–64.

471. Kawahara K, Hohjoh H, Inazumi T, Tsuchiya S, Sugimoto Y. Prostaglandin E2-induced inflammation: Relevance of prostaglandin E receptors. Biochim Biophys Acta. 2015 Apr;1851(4):414–21.

472. Rouzer CA, Marnett LJ. Cyclooxygenases: structural and functional insights. J Lipid Res. 2009 Apr;50 Suppl:S29-34.

473. Baker RR. The eicosanoids: a historical overview. Clin Biochem. 1990 Oct;23(5):455–8.

474. Vane JR. Inhibition of Prostaglandin Synthesis as a Mechanism of Action for Aspirin-like Drugs. Nature. 1971 Jun 23;231(25):232–5.

475. Roth GJ, Stanford N, Majerus PW. Acetylation of prostaglandin synthase by aspirin. Proc Natl Acad Sci. 1975 Aug 1;72(8):3073–6.

476. Kabashima K, Murata T, Tanaka H, Matsuoka T, Sakata D, Yoshida N, et al. Thromboxane A2 modulates interaction of dendritic cells and T cells and regulates acquired immunity. Nat Immunol. 2003 Jul;4(7):694–701.

477. Moalli F, Cupovic J, Thelen F, Halbherr P, Fukui Y, Narumiya S, et al. Thromboxane A2 acts as tonic immunoregulator by preferential disruption of low-avidity CD4+ T cell- dendritic cell interactions. J Exp Med. 2014 Dec 15;211(13):2507–17.

478. Esaki Y, Li Y, Sakata D, Yao C, Segi-Nishida E, Matsuoka T, et al. Dual roles of PGE2-EP4 signaling in mouse experimental autoimmune encephalomyelitis. Proc Natl Acad Sci U S A. 2010 Jul 6;107(27):12233–8.

479. Yao C, Hirata T, Soontrapa K, Ma X, Takemori H, Narumiya S. Prostaglandin E2 promotes Th1 differentiation via synergistic amplification of IL-12 signalling by cAMP and PI3-kinase. Nat Commun. 2013 Apr 9;4:1685.

315

480. Morita I, Schindler M, Regier MK, Otto JC, Hori T, DeWitt DL, et al. Different intracellular locations for prostaglandin endoperoxide H synthase-1 and -2. J Biol Chem. 1995 May 5;270(18):10902–8.

481. Zidar N, Odar K, Glavač D, Jerše M, Zupanc T, Štajer D. Cyclooxygenase in normal human tissues – is COX-1 really a constitutive isoform, and COX-2 an inducible isoform? J Cell Mol Med. 2009 Sep;13(9b):3753–63.

482. O’Neill GP, Ford-Hutchinson AW. Expression of mRNA for cyclooxygenase-1 and cyclooxygenase-2 in human tissues. FEBS Lett. 1993 Sep 13;330(2):156–60.

483. Okamoto T, Hino O. Expression of cyclooxygenase-1 and -2 mRNA in rat tissues: tissue- specific difference in the expression of the basal level of mRNA. Int J Mol Med. 2000 Oct;6(4):455–7.

484. Kang Y-J, Mbonye UR, DeLong CJ, Wada M, Smith WL. Regulation of intracellular cyclooxygenase levels by gene transcription and protein degradation. Prog Lipid Res. 2007 Mar;46(2):108–25.

485. Kujubu DA, Fletcher BS, Varnum BC, Lim RW, Herschman HR. TIS10, a phorbol ester tumor promoter-inducible mRNA from Swiss 3T3 cells, encodes a novel prostaglandin synthase/cyclooxygenase homologue. J Biol Chem. 1991 Jul 15;266(20):12866–72.

486. Kujubu DA, Herschman HR. Dexamethasone inhibits mitogen induction of the TIS10 prostaglandin synthase/cyclooxygenase gene. J Biol Chem. 1992 Apr 25;267(12):7991–4.

487. Fletcher BS, Kujubu DA, Perrin DM, Herschman HR. Structure of the mitogen-inducible TIS10 gene and demonstration that the TIS10-encoded protein is a functional prostaglandin G/H synthase. J Biol Chem. 1992 Mar 5;267(7):4338–44.

488. Wang LH, Hajibeigi A, Xu XM, Loosemitchell D, Wu KK. Characterization of the Promoter of Human Prostaglandin H Synthase-1 Gene. Biochem Biophys Res Commun. 1993 Jan 29;190(2):406–11.

489. Tanabe T, Tohnai N. Cyclooxygenase isozymes and their gene structures and expression. Prostaglandins Other Lipid Mediat. 2002 Aug;68–69:95–114.

490. Kosaka T, Miyata A, Ihara H, Hara S, Sugimoto T, Takeda O, et al. Characterization of the human gene (PTGS2) encoding prostaglandin-endoperoxide synthase 2. Eur J Biochem. 1994 May 1;221(3):889–97.

491. Tazawa R, Xu XM, Wu KK, Wang LH. Characterization of the genomic structure, chromosomal location and promoter of human prostaglandin H synthase-2 gene. Biochem Biophys Res Commun. 1994 Aug 30;203(1):190–9.

492. DeWitt DL, Meade EA. Serum and glucocorticoid regulation of gene transcription and expression of the prostaglandin H synthase-1 and prostaglandin H synthase-2 isozymes. Arch Biochem Biophys. 1993 Oct;306(1):94–102.

493. Mbonye UR, Song I-S. Posttranscriptional and posttranslational determinants of cyclooxygenase expression. BMB Rep. 2009;42(9):552–60.

494. Dixon DA, Kaplan CD, McIntyre TM, Zimmerman GA, Prescott SM. Post-transcriptional control of cyclooxygenase-2 gene expression. The role of the 3’-untranslated region. J Biol Chem. 2000 Apr 21;275(16):11750–7.

316

495. Mbonye UR, Wada M, Rieke CJ, Tang H-Y, DeWitt DL, Smith WL. The 19-amino Acid Cassette of Cyclooxygenase-2 Mediates Entry of the Protein into the Endoplasmic Reticulum-associated Degradation System. J Biol Chem. 2006 Nov 24;281(47):35770–8.

496. Newton R, Seybold J, Kuitert LME, Bergmann M, Barnes PJ. Repression of Cyclooxygenase-2 and Prostaglandin E2Release by Dexamethasone Occurs by Transcriptional and Post-transcriptional Mechanisms Involving Loss of Polyadenylated mRNA. J Biol Chem. 1998 Nov 27;273(48):32312–21.

497. Kirkby NS, Chan MV, Zaiss AK, Garcia-Vaz E, Jiao J, Berglund LM, et al. Systematic study of constitutive cyclooxygenase-2 expression: Role of NF-κB and NFAT transcriptional pathways. Proc Natl Acad Sci. 2016 Jan 12;113(2):434–9.

498. Qi Z, Hao C-M, Langenbach RI, Breyer RM, Redha R, Morrow JD, et al. Opposite effects of cyclooxygenase-1 and -2 activity on the pressor response to angiotensin II. J Clin Invest. 2002 Jul;110(1):61–9.

499. Ahmetaj-Shala B, Kirkby NS, Knowles R, Al’Yamani M, Mazi S, Wang Z, et al. Evidence That Links Loss of Cyclooxygenase-2 With Increased Asymmetric Dimethylarginine. Circulation. 2015 Feb 17;131(7):633–42.

500. Gilroy DW, Colville-Nash PR, Willis D, Chivers J, Paul-Clark MJ, Willoughby DA. Inducible cyclooxygenase may have anti-inflammatory properties. Nat Med. 1999 Jun;5(6):698–701.

501. Blobaum AL, Marnett LJ. Structural and functional basis of cyclooxygenase inhibition. J Med Chem. 2007 Apr 5;50(7):1425–41.

502. Rome LH, Lands WE. Structural requirements for time-dependent inhibition of prostaglandin biosynthesis by anti-inflammatory drugs. Proc Natl Acad Sci U S A. 1975 Dec;72(12):4863–5.

503. Kulmacz RJ, Lands WE. Stoichiometry and kinetics of the interaction of prostaglandin H synthase with anti-inflammatory agents. J Biol Chem. 1985 Oct 15;260(23):12572–8.

504. Mitchell JA, Akarasereenont P, Thiemermann C, Flower RJ, Vane JR. Selectivity of nonsteroidal antiinflammatory drugs as inhibitors of constitutive and inducible cyclooxygenase. Proc Natl Acad Sci U S A. 1993 Dec 15;90(24):11693–7.

505. Warner TD, Giuliano F, Vojnovic I, Bukasa A, Mitchell JA, Vane JR. Nonsteroid drug selectivities for cyclo-oxygenase-1 rather than cyclo-oxygenase-2 are associated with human gastrointestinal toxicity: A full in vitro analysis. Proc Natl Acad Sci. 1999 Jun 22;96(13):7563–8.

506. Chandrasekharan NV, Dai H, Roos KLT, Evanson NK, Tomsik J, Elton TS, et al. COX-3, a cyclooxygenase-1 variant inhibited by acetaminophen and other analgesic/antipyretic drugs: Cloning, structure, and expression. Proc Natl Acad Sci U S A. 2002 Oct 15;99(21):13926–31.

507. Solomon SD, Wittes J, Finn PV, Fowler R, Viner J, Bertagnolli MM, et al. Cardiovascular risk of celecoxib in 6 randomized placebo-controlled trials: the cross trial safety analysis. Circulation. 2008 Apr 22;117(16):2104–13.

317

508. Bresalier RS, Sandler RS, Quan H, Bolognese JA, Oxenius B, Horgan K, et al. Cardiovascular Events Associated with Rofecoxib in a Colorectal Adenoma Chemoprevention Trial. N Engl J Med. 2005 Mar 17;352(11):1092–102.

509. Aldington S, Shirtcliffe P, Weatherall M, Beasley R. Increased risk of cardiovascular events with parecoxib/valdecoxib: a systematic review and meta-analysis. N Z Med J. 2005 Nov 25;118(1226):U1755.

510. Sugimoto Y, Narumiya S. Prostaglandin E receptors. J Biol Chem. 2007 Apr 20;282(16):11613–7.

511. Hizaki H, Segi E, Sugimoto Y, Hirose M, Saji T, Ushikubi F, et al. Abortive expansion of the cumulus and impaired fertility in mice lacking the prostaglandin E receptor subtype EP(2). Proc Natl Acad Sci U S A. 1999 Aug 31;96(18):10501–6.

512. Wang J, Liu M, Zhang X, Yang G, Chen L. Physiological and pathophysiological implications of PGE2 and the PGE2 synthases in the kidney. Prostaglandins Other Lipid Mediat. 2018 Jan 1;134:1–6.

513. Takeuchi K. Gastric cytoprotection by prostaglandin E₂ and prostacyclin: relationship to EP1 and IP receptors. J Physiol Pharmacol Off J Pol Physiol Soc. 2014 Feb;65(1):3–14.

514. Omori K, Kida T, Hori M, Ozaki H, Murata T. Multiple roles of the PGE2 -EP receptor signal in vascular permeability. Br J Pharmacol. 2014 Nov;171(21):4879–89.

515. Ueno A, Matsumoto H, Naraba H, Ikeda Y, Ushikubi F, Matsuoka T, et al. Major roles of prostanoid receptors IP and EP(3) in endotoxin-induced enhancement of pain perception. Biochem Pharmacol. 2001 Jul;62(2):157–60.

516. Ushikubi F, Segi E, Sugimoto Y, Murata T, Matsuoka T, Kobayashi T, et al. Impaired febrile response in mice lacking the prostaglandin E receptor subtype EP3. Nature. 1998 Sep 17;395(6699):281–4.

517. Engblom D, Saha S, Engström L, Westman M, Audoly LP, Jakobsson P-J, et al. Microsomal prostaglandin E synthase-1 is the central switch during immune-induced pyresis. Nat Neurosci. 2003 Nov;6(11):1137–8.

518. Katoh H, Watabe A, Sugimoto Y, Ichikawa A, Negishi M. Characterization of the signal transduction of prostaglandin E receptor EP1 subtype in cDNA-transfected Chinese hamster ovary cells. Biochim Biophys Acta. 1995 May 11;1244(1):41–8.

519. Ji R, Chou C-L, Xu W, Chen X-B, Woodward DF, Regan JW. EP1 Prostanoid Receptor Coupling to Gi/o Up-Regulates the Expression of Hypoxia-Inducible Factor-1α through Activation of a Phosphoinositide-3 Kinase Signaling Pathway. Mol Pharmacol. 2010 Jun;77(6):1025–36.

520. Bastien L, Sawyer N, Grygorczyk R, Metters KM, Adam M. Cloning, functional expression, and characterization of the human prostaglandin E2 receptor EP2 subtype. J Biol Chem. 1994 Apr 22;269(16):11873–7.

521. Honda A, Sugimoto Y, Namba T, Watabe A, Irie A, Negishi M, et al. Cloning and expression of a cDNA for mouse prostaglandin E receptor EP2 subtype. J Biol Chem. 1993 Apr 15;268(11):7759–62.

318

522. Negishi M, Namba T, Sugimoto Y, Irie A, Katada T, Narumiya S, et al. Opposite coupling of prostaglandin E receptor EP3C with Gs and G(o). Stimulation of Gs and inhibition of G(o). J Biol Chem. 1993 Dec 15;268(35):26067–70.

523. Sugimoto Y, Negishi M, Hayashi Y, Namba T, Honda A, Watabe A, et al. Two isoforms of the EP3 receptor with different carboxyl-terminal domains. Identical ligand binding properties and different coupling properties with Gi proteins. J Biol Chem. 1993 Feb 5;268(4):2712–8.

524. Fujino H, Regan JW. EP(4) prostanoid receptor coupling to a pertussis toxin-sensitive inhibitory G protein. Mol Pharmacol. 2006 Jan;69(1):5–10.

525. Tanioka T, Nakatani Y, Semmyo N, Murakami M, Kudo I. Molecular identification of cytosolic prostaglandin E2 synthase that is functionally coupled with cyclooxygenase-1 in immediate prostaglandin E2 biosynthesis. J Biol Chem. 2000 Oct 20;275(42):32775–82.

526. Murakami M, Nakashima K, Kamei D, Masuda S, Ishikawa Y, Ishii T, et al. Cellular prostaglandin E2 production by membrane-bound prostaglandin E synthase-2 via both cyclooxygenases-1 and -2. J Biol Chem. 2003 Sep 26;278(39):37937–47.

527. Murakami M, Naraba H, Tanioka T, Semmyo N, Nakatani Y, Kojima F, et al. Regulation of prostaglandin E2 biosynthesis by inducible membrane-associated prostaglandin E2 synthase that acts in concert with cyclooxygenase-2. J Biol Chem. 2000 Oct 20;275(42):32783–92.

528. Naraba H, Yokoyama C, Tago N, Murakami M, Kudo I, Fueki M, et al. Transcriptional regulation of the membrane-associated prostaglandin E2 synthase gene. Essential role of the transcription factor Egr-1. J Biol Chem. 2002 Aug 9;277(32):28601–8.

529. Claveau D, Sirinyan M, Guay J, Gordon R, Chan C-C, Bureau Y, et al. Microsomal prostaglandin E synthase-1 is a major terminal synthase that is selectively up-regulated during cyclooxygenase-2-dependent prostaglandin E2 production in the rat adjuvant- induced arthritis model. J Immunol Baltim Md 1950. 2003 May 1;170(9):4738–44.

530. Camacho M, Gerbolés E, Escudero J-R, Antón R, García‐Moll X, Vila L. Microsomal prostaglandin E synthase-1, which is not coupled to a particular cyclooxygenase isoenzyme, is essential for prostaglandin E2 biosynthesis in vascular smooth muscle cells. J Thromb Haemost. 2007;5(7):1411–9.

531. Boulet L, Ouellet M, Bateman KP, Ethier D, Percival MD, Riendeau D, et al. Deletion of Microsomal Prostaglandin E2 (PGE2) Synthase-1 Reduces Inducible and Basal PGE2 Production and Alters the Gastric Prostanoid Profile. J Biol Chem. 2004 May 28;279(22):23229–37.

532. Kamei D, Yamakawa K, Takegoshi Y, Mikami-Nakanishi M, Nakatani Y, Oh-Ishi S, et al. Reduced pain hypersensitivity and inflammation in mice lacking microsomal prostaglandin e synthase-1. J Biol Chem. 2004 Aug 6;279(32):33684–95.

533. Takeuchi C, Matsumoto Y, Kohyama K, Uematsu S, Akira S, Yamagata K, et al. Microsomal prostaglandin E synthase-1 aggravates inflammation and demyelination in a mouse model of multiple sclerosis. Neurochem Int. 2013 Feb;62(3):271–80.

534. Kojima F, Frolov A, Matnani R, Woodward JG, Crofford LJ. Reduced T cell-dependent humoral immune response in microsomal prostaglandin E synthase-1 null mice is

319

mediated by nonhematopoietic cells. J Immunol Baltim Md 1950. 2013 Nov 15;191(10):4979–88.

535. Trebino CE, Stock JL, Gibbons CP, Naiman BM, Wachtmann TS, Umland JP, et al. Impaired inflammatory and pain responses in mice lacking an inducible prostaglandin E synthase. Proc Natl Acad Sci U S A. 2003 Jul 22;100(15):9044–9.

536. Jia Z, Zhang A, Zhang H, Dong Z, Yang T. Deletion of microsomal prostaglandin E synthase-1 increases sensitivity to salt loading and angiotensin II infusion. Circ Res. 2006 Nov 24;99(11):1243–51.

537. Soodvilai S, Jia Z, Wang M-H, Dong Z, Yang T. mPGES-1 deletion impairs diuretic response to acute water loading. Am J Physiol Renal Physiol. 2009 May;296(5):F1129- 1135.

538. Takemiya T. Prostaglandin E2 produced by microsomal prostaglandin E synthase-1 regulates the onset and the maintenance of wakefulness. Neurochem Int. 2011 Nov;59(6):922–4.

539. Frolov A, Yang L, Dong H, Hammock BD, Crofford LJ. Anti-inflammatory properties of prostaglandin E2: Deletion of microsomal prostaglandin E synthase-1 exacerbates non- immune inflammatory arthritis in mice. Prostaglandins Leukot Essent Fatty Acids. 2013 Oct 1;89(5):351–8.

540. Henkel J, Coleman CD, Schraplau A, Jöhrens K, Weiss TS, Jonas W, et al. Augmented liver inflammation in a microsomal prostaglandin E synthase 1 (mPGES-1)-deficient diet- induced mouse NASH model. Sci Rep. 2018 Oct 31;8(1):16127.

541. Haurand M, Ullrich V. Isolation and characterization of thromboxane synthase from human platelets as a cytochrome P-450 enzyme. J Biol Chem. 1985 Dec 5;260(28):15059– 67.

542. Shen RF, Tai HH. Immunoaffinity purification and characterization of thromboxane synthase from porcine lung. J Biol Chem. 1986 Sep 5;261(25):11592–9.

543. Knezevic I, Borg C, Le Breton GC. Identification of Gq as one of the G-proteins which copurify with human platelet thromboxane A2/prostaglandin H2 receptors. J Biol Chem. 1993 Dec 5;268(34):26011–7.

544. Offermanns S, Laugwitz KL, Spicher K, Schultz G. G proteins of the G12 family are activated via thromboxane A2 and thrombin receptors in human platelets. Proc Natl Acad Sci U S A. 1994 Jan 18;91(2):504–8.

545. Ushikubi F, Nakamura K, Narumiya S. Functional reconstitution of platelet thromboxane A2 receptors with Gq and Gi2 in phospholipid vesicles. Mol Pharmacol. 1994 Nov;46(5):808–16.

546. Palmer MA, Piper PJ, Vane JR. The release of rabbit aorta contracting substance (RCS) from chopped lung and its antagonism by anti-inflammatory drugs. Br J Pharmacol. 1970 Nov;40(3):581P-582P.

547. Hamberg M, Svensson J, Samuelsson B. Thromboxanes: a new group of biologically active compounds derived from prostaglandin endoperoxides. Proc Natl Acad Sci U S A. 1975 Aug;72(8):2994–8.

320

548. Paul BZS, Jin J, Kunapuli SP. Molecular Mechanism of Thromboxane A2-induced Platelet Aggregation ESSENTIAL ROLE FOR P2T AC and α2ARECEPTORS. J Biol Chem. 1999 Aug 10;274(41):29108–14.

549. Yu I-S, Lin S-R, Huang C-C, Tseng H-Y, Huang P-H, Shi G-Y, et al. TXAS-deleted mice exhibit normal thrombopoiesis, defective hemostasis, and resistance to arachidonate- induced death. Blood. 2004 Jul 1;104(1):135–42.

550. Zhang LQ, Chase MB, Shen RF. Molecular Cloning and Expression of Murine Thromboxane Synthase. Biochem Biophys Res Commun. 1993 Jul 30;194(2):741–8.

551. Miyata A, Yokoyama C, Ihara H, Bandoh S, Takeda O, Takahashi E, et al. Characterization of the human gene (TBXAS1) encoding thromboxane synthase. Eur J Biochem. 1994 Sep 1;224(2):273–9.

552. Yaekashiwa M, Wang L-H. Transcriptional control of the human thromboxane synthase gene in vivo and in vitro. J Biol Chem. 2002 Jun 21;277(25):22497–508.

553. Liu T, Laidlaw TM, Feng C, Xing W, Shen S, Milne GL, et al. Prostaglandin E2 deficiency uncovers a dominant role for thromboxane A2 in house dust mite-induced allergic pulmonary inflammation. Proc Natl Acad Sci U S A. 2012 Jul 31;109(31):12692–7.

554. Lin DP-C, Chang H-H, Yang L-C, Huang T-P, Liu H-J, Chang L-S, et al. Assessment of ultraviolet B-blocking effects of weekly disposable contact lenses on corneal surface in a mouse model. Mol Vis. 2013;19:1158–68.

555. Boffa J-J, Just A, Coffman TM, Arendshorst WJ. Thromboxane receptor mediates renal vasoconstriction and contributes to acute renal failure in endotoxemic mice. J Am Soc Nephrol JASN. 2004 Sep;15(9):2358–65.

556. Takayama K, Yuhki K, Ono K, Fujino T, Hara A, Yamada T, et al. Thromboxane A 2 and prostaglandin F 2α mediate inflammatory tachycardia. Nat Med. 2005 May;11(5):562–6.

557. Thomas DW, Rocha PN, Nataraj C, Robinson LA, Spurney RF, Koller BH, et al. Proinflammatory actions of thromboxane receptors to enhance cellular immune responses. J Immunol Baltim Md 1950. 2003 Dec 15;171(12):6389–95.

558. Bowman CC, Bost KL. Cyclooxygenase-2-mediated prostaglandin E2 production in mesenteric lymph nodes and in cultured macrophages and dendritic cells after infection with Salmonella. J Immunol Baltim Md 1950. 2004 Feb 15;172(4):2469–75.

559. Nakano M, Denda N, Matsumoto M, Kawamura M, Kawakubo Y, Hatanaka K, et al. Interaction between cyclooxygenase (COX)-1- and COX-2-products modulates COX-2 expression in the late phase of acute inflammation. Eur J Pharmacol. 2007 Mar 22;559(2– 3):210–8.

560. Kojima F, Kapoor M, Yang L, Fleishaker EL, Ward MR, Monrad SU, et al. Defective generation of a humoral immune response is associated with a reduced incidence and severity of collagen-induced arthritis in microsomal prostaglandin E synthase-1 null mice. J Immunol Baltim Md 1950. 2008 Jun 15;180(12):8361–8.

561. Fujisawa H, Nakagawa S, Ohkubo Y, Matsui M, Yamaguchi S, Kawamura M, et al. Local and systemic expression of inducible nitric oxide synthase in comparison with that of cyclooxygenase-2 in rat carrageenin-induced pleurisy. Nitric Oxide Biol Chem. 2005 Mar;12(2):80–8.

321

562. Kawamura M, Tada Y, Kadoya Y, Obata S, Harada Y. COX-2 expression in stromal fibroblasts self-limits their numbers in lymph node inflammatory responses. Prostaglandins Other Lipid Mediat. 2013 Oct;106:79–90.

563. Nagamachi M, Sakata D, Kabashima K, Furuyashiki T, Murata T, Segi-Nishida E, et al. Facilitation of Th1-mediated immune response by prostaglandin E receptor EP1. J Exp Med. 2007 Nov 26;204(12):2865–74.

564. Lee IY, Cho W, Kim J, Park C-S, Choe J. Human follicular dendritic cells interact with T cells via expression and regulation of cyclooxygenases and prostaglandin E and I synthases. J Immunol Baltim Md 1950. 2008 Feb 1;180(3):1390–7.

565. Cho W, Kim Y, Kim J, Park S, Park D, Kim B-C, et al. Suppressor of cytokine signaling 1 is a positive regulator of TGF-β-induced prostaglandin production in human follicular dendritic cell-like cells. J Immunol Baltim Md 1950. 2015 May 1;194(9):4287–97.

566. Siegert S, Huang H-Y, Yang C-Y, Scarpellino L, Carrie L, Essex S, et al. Fibroblastic Reticular Cells From Lymph Nodes Attenuate T Cell Expansion by Producing Nitric Oxide. PLOS ONE. 2011 Nov 14;6(11):e27618.

567. Lee IY, Ko E-M, Kim S-H, Jeoung D-I, Choe J. Human follicular dendritic cells express prostacyclin synthase: a novel mechanism to control T cell numbers in the germinal center. J Immunol Baltim Md 1950. 2005 Aug 1;175(3):1658–64.

568. Nishikawa Y, Hikida M, Magari M, Kanayama N, Mori M, Kitamura H, et al. Establishment of lymphotoxin beta receptor signaling-dependent cell lines with follicular dendritic cell phenotypes from mouse lymph nodes. J Immunol Baltim Md 1950. 2006 Oct 15;177(8):5204–14.

569. Yu M, Guo G, Zhang X, Li L, Yang W, Bollag R, et al. Fibroblastic reticular cells of the lymphoid tissues modulate T cell activation threshold during homeostasis via hyperactive cyclooxygenase-2/prostaglandin E 2 axis. Sci Rep. 2017 Jun 13;7(1):1–15.

570. Schaeuble K, Cannelle H, Favre S, Huang H-Y, Oberle SG, Speiser DE, et al. Attenuation of chronic antiviral T-cell responses through constitutive COX2-dependent prostanoid synthesis by lymph node fibroblasts. PLoS Biol [Internet]. 2019 Jul 15 [cited 2019 Aug 22];17(7). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6657915/

571. Blaho VA, Buczynski MW, Dennis EA, Brown CR. Cyclooxygenase-1 orchestrates germinal center formation and antibody class-switch via regulation of IL-17. J Immunol Baltim Md 1950. 2009 Nov 1;183(9):5644–53.

572. Ryan EP, Malboeuf CM, Bernard M, Rose RC, Phipps RP. Cyclooxygenase-2 Inhibition Attenuates Antibody Responses against Human Papillomavirus-Like Particles. J Immunol. 2006 Jan 12;177(11):7811–9.

573. Bernard MP, Bancos S, Chapman TJ, Ryan EP, Treanor JJ, Rose RC, et al. Chronic inhibition of cyclooxygenase-2 attenuates antibody responses against vaccinia infection. Vaccine. 2010 Feb 3;28(5):1363–72.

574. Lee E, Kim J, Kim Y-M, Ha KS, Jeoung D-I, Sin J-I, et al. Beraprost enhances production of antigen-specific IgG isotypes without modulating germinal center B cell generation and the affinity maturation. Int Immunopharmacol. 2013 Apr;15(4):735–42.

322

575. Kim J, Lee S, Kim Y-M, Jeoung D-I, Choe J. Human follicular dendritic cells promote germinal center B cell survival by providing prostaglandins. Mol Immunol. 2013 Oct;55(3– 4):418–23.

576. Magari M, Nishikawa Y, Fujii Y, Nishio Y, Watanabe K, Fujiwara M, et al. IL-21- dependent B cell death driven by prostaglandin E2, a product secreted from follicular dendritic cells. J Immunol Baltim Md 1950. 2011 Oct 15;187(8):4210–8.

577. Mongini PKA, Inman JK, Han H, Fattah RJ, Abramson SB, Attur M. APRIL and BAFF promote increased viability of replicating human B2 cells via mechanism involving cyclooxygenase 2. J Immunol Baltim Md 1950. 2006 Jun 1;176(11):6736–51.

578. Goodwin JS, Selinger DS, Messner RP, Reed WP. Effect of indomethacin in vivo on humoral and cellular immunity in humans. Infect Immun. 1978 Feb;19(2):430–3.

579. Sharma S, Zhu L, Yang SC, Zhang L, Lin J, Hillinger S, et al. Cyclooxygenase 2 inhibition promotes IFN-gamma-dependent enhancement of antitumor responses. J Immunol Baltim Md 1950. 2005 Jul 15;175(2):813–9.

580. Boniface K, Bak-Jensen KS, Li Y, Blumenschein WM, McGeachy MJ, McClanahan TK, et al. Prostaglandin E2 regulates Th17 cell differentiation and function through cyclic AMP and EP2/EP4 receptor signaling. J Exp Med. 2009 Mar 16;206(3):535–48.

581. Chen JH, Perry CJ, Tsui Y-C, Staron MM, Parish IA, Dominguez CX, et al. Prostaglandin E2 and programmed cell death 1 signaling coordinately impair CTL function and survival during chronic viral infection. Nat Med. 2015 Apr;21(4):327–34.

582. Walenga RW, Wall SF, Setty BNY, Stuart MJ. Time-dependent inhibition of platelet cyclo-oxygenase by indomethacin is slowly reversible. Prostaglandins. 1986 Apr 1;31(4):625–37.

583. Gaya M, Castello A, Montaner B, Rogers N, Sousa CR e, Bruckbauer A, et al. Inflammation-induced disruption of SCS macrophages impairs B cell responses to secondary infection. Science. 2015 Jun 2;347(6222):667–72.

584. Xiao L, Ornatowska M, Zhao G, Cao H, Yu R, Deng J, et al. Lipopolysaccharide-Induced Expression of Microsomal Prostaglandin E Synthase-1 Mediates Late-Phase PGE2 Production in Bone Marrow Derived Macrophages. PLoS ONE [Internet]. 2012 Nov 30 [cited 2016 Oct 8];7(11). Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3511480/

585. Bogdan D, Falcone J, Kanjiya MP, Park SH, Carbonetti G, Studholme K, et al. Fatty acid- binding protein 5 controls microsomal prostaglandin E synthase 1 (mPGES-1) induction during inflammation. J Biol Chem. 2018 06;293(14):5295–306.

586. Barrios-Rodiles M, Tiraloche G, Chadee K. Lipopolysaccharide modulates cyclooxygenase-2 transcriptionally and posttranscriptionally in human macrophages independently from endogenous IL-1 beta and TNF-alpha. J Immunol Baltim Md 1950. 1999 Jul 15;163(2):963–9.

587. Zhang S, Thomas K, Blanco JCG, Salkowski CA, Vogel SN. The role of the interferon regulatory factors, IRF-1 and IRF-2, in LPS-induced cyclooxygenase-2 (COX-2) expression in vivo and in vitro. J Endotoxin Res. 2002;8(5):379–88.

323

588. Blanco JC, Contursi C, Salkowski CA, DeWitt DL, Ozato K, Vogel SN. Interferon regulatory factor (IRF)-1 and IRF-2 regulate interferon gamma-dependent cyclooxygenase 2 expression. J Exp Med. 2000 Jun 19;191(12):2131–44.

589. Laflamme N, Lacroix S, Rivest S. An essential role of interleukin-1beta in mediating NF- kappaB activity and COX-2 transcription in cells of the blood-brain barrier in response to a systemic and localized inflammation but not during endotoxemia. J Neurosci Off J Soc Neurosci. 1999 Dec 15;19(24):10923–30.

590. Li S, Wang Y, Matsumura K, Ballou LR, Morham SG, Blatteis CM. The febrile response to lipopolysaccharide is blocked in cyclooxygenase-2−/−, but not in cyclooxygenase-1−/− mice. Brain Res. 1999 Apr 17;825(1–2):86–94.

591. Vila-del Sol V, Fresno M. Involvement of TNF and NF-kappa B in the transcriptional control of cyclooxygenase-2 expression by IFN-gamma in macrophages. J Immunol Baltim Md 1950. 2005 Mar 1;174(5):2825–33.

592. Martinez J, Huang X, Yang Y. Direct Action of Type I IFN on NK Cells Is Required for Their Activation in Response to Vaccinia Viral Infection In Vivo. J Immunol. 2008 Feb 1;180(3):1592–7.

593. Fang R, Hara H, Sakai S, Hernandez-Cuellar E, Mitsuyama M, Kawamura I, et al. Type I Interferon Signaling Regulates Activation of the Absent in Melanoma 2 Inflammasome during Streptococcus pneumoniae Infection. Infect Immun. 2014 Jun;82(6):2310–7.

594. Henry T, Brotcke A, Weiss DS, Thompson LJ, Monack DM. Type I interferon signaling is required for activation of the inflammasome during Francisella infection. J Exp Med. 2007 May 14;204(5):987–94.

595. Rathinam VAK, Vanaja SK, Waggoner L, Sokolovska A, Becker C, Stuart LM, et al. TRIF licenses caspase-11-dependent NLRP3 inflammasome activation by gram-negative bacteria. Cell. 2012 Aug 3;150(3):606–19.

596. Lemos HP, Grespan R, Vieira SM, Cunha TM, Verri WA, Fernandes KSS, et al. Prostaglandin mediates IL-23/IL-17-induced neutrophil migration in inflammation by inhibiting IL-12 and IFNγ production. Proc Natl Acad Sci. 2009 Jul 4;106(14):5954–9.

597. Shibata K, Yamada H, Hara H, Kishihara K, Yoshikai Y. Resident Vdelta1+ gammadelta T cells control early infiltration of neutrophils after Escherichia coli infection via IL-17 production. J Immunol Baltim Md 1950. 2007 Apr 1;178(7):4466–72.

598. Isaacs A, Lindenmann J. Virus interference. I. The interferon. Proc R Soc Lond B. 1957 Sep 12;147(927):258–67.

599. Wack A, Terczyńska-Dyla E, Hartmann R. Guarding the frontiers: the biology of type III interferons. Nat Immunol. 2015 Aug;16(8):802–9.

600. Platanias LC. Mechanisms of type-I- and type-II-interferon-mediated signalling. Nat Rev Immunol. 2005 May;5(5):375–86.

601. Schoggins JW, Wilson SJ, Panis M, Murphy MY, Jones CT, Bieniasz P, et al. A diverse range of gene products are effectors of the type I interferon antiviral response. Nature. 2011 Apr;472(7344):481–5.

324

602. Darnell JE, Kerr IM, Stark GR. Jak-STAT pathways and transcriptional activation in response to IFNs and other extracellular signaling proteins. Science. 1994 Jun 3;264(5164):1415–21.

603. Li X, Leung S, Qureshi S, Darnell JE, Stark GR. Formation of STAT1-STAT2 heterodimers and their role in the activation of IRF-1 gene transcription by interferon-alpha. J Biol Chem. 1996 Mar 8;271(10):5790–4.

604. Li Y, Sassano A, Majchrzak B, Deb DK, Levy DE, Gaestel M, et al. Role of p38alpha Map kinase in Type I interferon signaling. J Biol Chem. 2004 Jan 9;279(2):970–9.

605. Chang H-M, Paulson M, Holko M, Rice CM, Williams BRG, Marié I, et al. Induction of interferon-stimulated gene expression and antiviral responses require protein deacetylase activity. Proc Natl Acad Sci U S A. 2004 Jun 29;101(26):9578–83.

606. Nusinzon I, Horvath CM. Interferon-stimulated transcription and innate antiviral immunity require deacetylase activity and histone deacetylase 1. Proc Natl Acad Sci U S A. 2003 Dec 9;100(25):14742–7.

607. Levy DE, Kessler DS, Pine R, Reich N, Darnell JE. Interferon-induced nuclear factors that bind a shared promoter element correlate with positive and negative transcriptional control. Genes Dev. 1988 Apr;2(4):383–93.

608. Müller U, Steinhoff U, Reis LF, Hemmi S, Pavlovic J, Zinkernagel RM, et al. Functional role of type I and type II interferons in antiviral defense. Science. 1994 Jun 24;264(5167):1918–21.

609. Mancuso G, Midiri A, Biondo C, Beninati C, Zummo S, Galbo R, et al. Type I IFN Signaling Is Crucial for Host Resistance against Different Species of Pathogenic Bacteria. J Immunol. 2007 Mar 1;178(5):3126–33.

610. Jouanguy E, Zhang S-Y, Chapgier A, Sancho-Shimizu V, Puel A, Picard C, et al. Human primary immunodeficiencies of type I interferons. Biochimie. 2007 Jul;89(6–7):878–83.

611. Lafaille FG, Pessach IM, Zhang S-Y, Ciancanelli MJ, Herman M, Abhyankar A, et al. Impaired intrinsic immunity to HSV-1 in human iPSC-derived TLR3-deficient CNS cells. Nature. 2012 Nov 29;491(7426):769–73.

612. Daffis S, Szretter KJ, Schriewer J, Li J, Youn S, Errett J, et al. 2’-O methylation of the viral mRNA cap evades host restriction by IFIT family members. Nature. 2010 Nov 18;468(7322):452–6.

613. Brass AL, Huang I-C, Benita Y, John SP, Krishnan MN, Feeley EM, et al. The IFITM proteins mediate cellular resistance to influenza A H1N1 virus, West Nile virus, and dengue virus. Cell. 2009 Dec 24;139(7):1243–54.

614. Goritzka M, Durant LR, Pereira C, Salek-Ardakani S, Openshaw PJM, Johansson C. Alpha/Beta Interferon Receptor Signaling Amplifies Early Proinflammatory Cytokine Production in the Lung during Respiratory Syncytial Virus Infection. J Virol. 2014 Jun;88(11):6128–36.

615. Urban SL, Berg LJ, Welsh RM. Type 1 interferon licenses naïve CD8 T cells to mediate anti-viral cytotoxicity. Virology. 2016 Jun 1;493:52–9.

325

616. Longhi MP, Trumpfheller C, Idoyaga J, Caskey M, Matos I, Kluger C, et al. Dendritic cells require a systemic type I interferon response to mature and induce CD4+ Th1 immunity with poly IC as adjuvant. J Exp Med. 2009 Jul 6;206(7):1589–602.

617. Dorhoi A, Yeremeev V, Nouailles G, Weiner J, Jörg S, Heinemann E, et al. Type I IFN signaling triggers immunopathology in tuberculosis-susceptible mice by modulating lung phagocyte dynamics. Eur J Immunol. 2014 Aug;44(8):2380–93.

618. Redford PS, Mayer-Barber KD, McNab FW, Stavropoulos E, Wack A, Sher A, et al. Influenza A virus impairs control of Mycobacterium tuberculosis coinfection through a type I interferon receptor-dependent pathway. J Infect Dis. 2014 Jan 15;209(2):270–4.

619. Mayer-Barber KD, Andrade BB, Oland SD, Amaral EP, Barber DL, Gonzales J, et al. Host- directed therapy of tuberculosis based on interleukin-1 and type I interferon crosstalk. Nature. 2014 Jul 3;511(7507):99–103.

620. Davidson S, Crotta S, McCabe TM, Wack A. Pathogenic potential of interferon αβ in acute influenza infection. Nat Commun. 2014 May 21;5:3864.

621. Das A, Heesters BA, Bialas A, O’Flynn J, Rifkin IR, Ochando J, et al. Follicular Dendritic Cell Activation by TLR Ligands Promotes Autoreactive B Cell Responses. Immunity. 2017 Jan 17;46(1):106–19.

622. Hickman HD, Reynoso GV, Ngudiankama BF, Cush SS, Gibbs J, Bennink JR, et al. CXCR3 Chemokine Receptor Enables Local CD8+ T Cell Migration for the Destruction of Virus- Infected Cells. Immunity. 2015 Mar 17;42(3):524–37.

623. Lorenzi S, Mattei F, Sistigu A, Bracci L, Spadaro F, Sanchez M, et al. Type I IFNs control antigen retention and survival of CD8α(+) dendritic cells after uptake of tumor apoptotic cells leading to cross-priming. J Immunol Baltim Md 1950. 2011 May 1;186(9):5142–50.

624. Oh JZ, Kurche JS, Burchill MA, Kedl RM. TLR7 enables cross-presentation by multiple dendritic cell subsets through a type I IFN-dependent pathway. Blood. 2011 Sep 15;118(11):3028–38.

625. Wei J, Waithman J, Lata R, Mifsud NA, Cebon J, Kay T, et al. Influenza A infection enhances cross-priming of CD8+ T cells to cell-associated antigens in a TLR7- and type I IFN-dependent fashion. J Immunol Baltim Md 1950. 2010 Nov 15;185(10):6013–22.

626. Bankovich AJ, Shiow LR, Cyster JG. CD69 Suppresses Sphingosine 1-Phosophate Receptor-1 (S1P1) Function through Interaction with Membrane Helix 4. J Biol Chem. 2010 Jul 16;285(29):22328–37.

627. Groom JR, Luster AD. CXCR3 ligands: redundant, collaborative and antagonistic functions. Immunol Cell Biol. 2011 Feb;89(2):207–15.

628. van de Veerdonk FL, Netea MG, Dinarello CA, Joosten LAB. Inflammasome activation and IL-1β and IL-18 processing during infection. Trends Immunol. 2011 Mar;32(3):110–6.

629. Ghayur T, Banerjee S, Hugunin M, Butler D, Herzog L, Carter A, et al. Caspase-1 processes IFN-gamma-inducing factor and regulates LPS-induced IFN-gamma production. Nature. 1997 Apr 10;386(6625):619–23.

326

630. Gu Y, Kuida K, Tsutsui H, Ku G, Hsiao K, Fleming MA, et al. Activation of interferon- gamma inducing factor mediated by interleukin-1beta converting enzyme. Science. 1997 Jan 10;275(5297):206–9.

631. Bryan NB, Dorfleutner A, Rojanasakul Y, Stehlik C. Activation of inflammasomes requires intracellular redistribution of the apoptotic speck-like protein containing a caspase recruitment domain (ASC). J Immunol Baltim Md 1950. 2009 Mar 1;182(5):3173– 82.

632. Lu A, Magupalli VG, Ruan J, Yin Q, Atianand MK, Vos MR, et al. Unified polymerization mechanism for the assembly of ASC-dependent inflammasomes. Cell. 2014 Mar 13;156(6):1193–206.

633. Guarda G, Braun M, Staehli F, Tardivel A, Mattmann C, Förster I, et al. Type I interferon inhibits interleukin-1 production and inflammasome activation. Immunity. 2011 Feb 25;34(2):213–23.

634. Kopitar-Jerala N. The Role of Interferons in Inflammation and Inflammasome Activation. Front Immunol [Internet]. 2017 Jul 25 [cited 2019 Aug 4];8. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5525294/

635. Cogswell JP, Godlevski MM, Wisely GB, Clay WC, Leesnitzer LM, Ways JP, et al. NF- kappa B regulates IL-1 beta transcription through a consensus NF-kappa B binding site and a nonconsensus CRE-like site. J Immunol Baltim Md 1950. 1994 Jul 15;153(2):712–23.

636. Scheibel M, Klein B, Merkle H, Schulz M, Fritsch R, Greten FR, et al. IκBβ is an essential co-activator for LPS-induced IL-1β transcription in vivo. J Exp Med. 2010 Nov 22;207(12):2621–30.

637. Radwan M, Stiefvater R, Grunert T, Sharif O, Miller I, Marchetti-Deschmann M, et al. Tyrosine kinase 2 controls IL-1ß production at the translational level. J Immunol Baltim Md 1950. 2010 Sep 15;185(6):3544–53.

638. Colomar A, Marty V, Médina C, Combe C, Parnet P, Amédée T. Maturation and release of interleukin-1beta by lipopolysaccharide-primed mouse Schwann cells require the stimulation of P2X7 receptors. J Biol Chem. 2003 Aug 15;278(33):30732–40.

639. Puren AJ, Fantuzzi G, Dinarello CA. Gene expression, synthesis, and secretion of interleukin 18 and interleukin 1beta are differentially regulated in human blood mononuclear cells and mouse spleen cells. Proc Natl Acad Sci U S A. 1999 Mar 2;96(5):2256–61.

640. Baranek T, Manh T-PV, Alexandre Y, Maqbool MA, Cabeza JZ, Tomasello E, et al. Differential responses of immune cells to type I interferon contribute to host resistance to viral infection. Cell Host Microbe. 2012 Oct 18;12(4):571–84.

641. Chang WLW, Coro ES, Rau FC, Xiao Y, Erle DJ, Baumgarth N. Influenza virus infection causes global respiratory tract B cell response modulation via innate immune signals. J Immunol Baltim Md 1950. 2007 Feb 1;178(3):1457–67.

642. Brzoza-Lewis KL, Hoth JJ, Hiltbold EM. Type I interferon signaling regulates the composition of inflammatory infiltrates upon infection with Listeria monocytogenes. Cell Immunol. 2012;273(1):41–51.

327

643. Meiser A, Mueller A, Wise EL, McDonagh EM, Petit SJ, Saran N, et al. THE CHEMOKINE RECEPTOR CXCR3 IS DEGRADED FOLLOWING INTERNALIZATION AND IS REPLENISHED AT THE CELL SURFACE BY DE NOVO SYNTHESIS OF RECEPTOR. J Immunol Baltim Md 1950. 2008 May 15;180(10):6713–24.

644. Abboud G, Tahiliani V, Desai P, Varkoly K, Driver J, Hutchinson TE, et al. Natural Killer Cells and Innate Interferon Gamma Participate in the Host Defense against Respiratory Vaccinia Virus Infection. J Virol. 2015 Oct 14;90(1):129–41.

645. Jia T, Leiner I, Dorothee G, Brandl K, Pamer EG. MyD88 and Type I Interferon Receptor- Mediated Chemokine Induction and Monocyte Recruitment during Listeria monocytogenes Infection. J Immunol. 2009 Jul 15;183(2):1271–8.

646. Vazquez BN, Laguna T, Carabana J, Krangel MS, Lauzurica P. CD69 gene is differentially regulated in T and B cells by evolutionarily conserved promoter-distal elements. J Immunol Baltim Md 1950. 2009 Nov 15;183(10):6513–21.

647. La Porta J, Matus-Nicodemos R, Valentín-Acevedo A, Covey LR. The RNA-Binding Protein, Polypyrimidine Tract-Binding Protein 1 (PTBP1) Is a Key Regulator of CD4 T Cell Activation. PLoS ONE [Internet]. 2016 Aug 11 [cited 2017 Nov 30];11(8). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4981342/

648. Martín P, Gómez M, Lamana A, Cruz-Adalia A, Ramírez-Huesca M, Ursa MA, et al. CD69 association with Jak3/Stat5 proteins regulates Th17 cell differentiation. Mol Cell Biol. 2010 Oct;30(20):4877–89.

649. Gao Y, Majchrzak-Kita B, Fish EN, Gommerman JL. Dynamic accumulation of plasmacytoid dendritic cells in lymph nodes is regulated by interferon-beta. Blood. 2009 Sep 24;114(13):2623–31.

650. Mudd JC, Murphy P, Manion M, Debernardo R, Hardacre J, Ammori J, et al. Impaired T- cell responses to sphingosine-1-phosphate in HIV-1 infected lymph nodes. Blood. 2013 Apr 11;121(15):2914–22.

651. Thackray LB, Shrestha B, Richner JM, Miner JJ, Pinto AK, Lazear HM, et al. Interferon Regulatory Factor 5-Dependent Immune Responses in the Draining Lymph Node Protect against West Nile Virus Infection. J Virol. 2014 Oct;88(19):11007–21.

652. Blomgran R, Ernst JD. Lung Neutrophils Facilitate Activation of Naïve Antigen Specific CD4+ T Cells During Mycobacterium tuberculosis Infection. J Immunol Baltim Md 1950. 2011 Jun 15;186(12):7110–9.

653. Vilanova M, Tavares D, Ferreira P, Oliveira L, Nóbrega A, Appelberg R, et al. Role of Monocytes in the Up-Regulation of the Early Activation Marker CD69 on B and T Murine Lymphocytes Induced by Microbial Mitogens. Scand J Immunol. 1996 Feb 1;43(2):155–63.

654. Shinoda K, Tokoyoda K, Hanazawa A, Hayashizaki K, Zehentmeier S, Hosokawa H, et al. Type II membrane protein CD69 regulates the formation of resting T-helper memory. Proc Natl Acad Sci. 2012 Aug 5;109(19):7409–14.

655. Fink K, Lang KS, Manjarrez-Orduno N, Junt T, Senn BM, Holdener M, et al. Early type I interferon-mediated signals on B cells specifically enhance antiviral humoral responses. Eur J Immunol. 2006 Aug 1;36(8):2094–105.

328

656. Lu M, Munford R. LPS stimulates IgM production in vivo without help from non-B cells. Innate Immun. 2016 Jul 1;22(5):307–15.

657. Swanson CL, Wilson TJ, Strauch P, Colonna M, Pelanda R, Torres RM. Type I IFN enhances follicular B cell contribution to the T cell–independent antibody response. J Exp Med. 2010 Jul 5;207(7):1485–500.

658. Alari-Pahissa E, Notario L, Lorente E, Vega-Ramos J, Justel A, López D, et al. CD69 does not affect the extent of T cell priming. PloS One. 2012;7(10):e48593.

659. Lamana A, Martin P, de la Fuente H, Martinez-Muñoz L, Cruz-Adalia A, Ramirez-Huesca M, et al. CD69 modulates sphingosine-1-phosphate-induced migration of skin dendritic cells. J Invest Dermatol. 2011 Jul;131(7):1503–12.

660. Vega-Ramos J, Alari-Pahissa E, Valle JD, Carrasco-Marín E, Esplugues E, Borràs M, et al. CD69 limits early inflammatory diseases associated with immune response to Listeria monocytogenes infection. Immunol Cell Biol. 2010 Oct;88(7):707–15.

661. Marzio R, Jirillo E, Ransijn A, Mauël J, Corradin SB. Expression and function of the early activation antigen CD69 in murine macrophages. J Leukoc Biol. 1997 Sep;62(3):349–55.

662. Craston R, Koh M, Mc Dermott A, Ray N, Prentice HG, Lowdell MW. Temporal dynamics of CD69 expression on lymphoid cells. J Immunol Methods. 1997 Nov 10;209(1):37–45.

663. Notario L, Alari-Pahissa E, de Molina A, Lauzurica P. CD69 Deficiency Enhances the Host Response to Vaccinia Virus Infection through Altered NK Cell Homeostasis. J Virol. 2016 Jul 15;90(14):6464–74.

664. Han Y, Guo Q, Zhang M, Chen Z, Cao X. CD69+CD4+CD25− T Cells, a New Subset of Regulatory T Cells, Suppress T Cell Proliferation through Membrane-Bound TGF-β1. J Immunol. 2009 Jan 1;182(1):111–20.

665. Bergsbaken T, Bevan MJ, Fink PJ. Local Inflammatory Cues Regulate Differentiation and Persistence of CD8+ Tissue-Resident Memory T Cells. Cell Rep. 2017 Apr 4;19(1):114–24.

666. Alfonso C, McHeyzer-Williams MG, Rosen H. CD69 down-modulation and inhibition of thymic egress by short- and long-term selective chemical agonism of sphingosine 1- phosphate receptors. Eur J Immunol. 2006 Jan 1;36(1):149–59.

667. Nakayama T, Kasprowicz DJ, Yamashita M, Schubert LA, Gillard G, Kimura M, et al. The generation of mature, single-positive thymocytes in vivo is dysregulated by CD69 blockade or overexpression. J Immunol Baltim Md 1950. 2002 Jan 1;168(1):87–94.

668. Vazquez BN, Laguna T, Notario L, Lauzurica P. Evidence for an intronic cis-regulatory element within CD69 gene. Genes Immun. 2012 Jun;13(4):356–62.

669. Freeman BE, Hammarlund E, Raué H-P, Slifka MK. Regulation of innate CD8+ T-cell activation mediated by cytokines. Proc Natl Acad Sci U S A. 2012 Jun 19;109(25):9971–6.

670. Minguet S, Dopfer EP, Pollmer C, Freudenberg MA, Galanos C, Reth M, et al. Enhanced B-cell activation mediated by TLR4 and BCR crosstalk. Eur J Immunol. 2008 Sep;38(9):2475–87.

329

671. Ziegler SF, Levin SD, Johnson L, Copeland NG, Gilbert DJ, Jenkins NA, et al. The mouse CD69 gene. Structure, expression, and mapping to the NK gene complex. J Immunol Baltim Md 1950. 1994 Feb 1;152(3):1228–36.

672. Kelley J, Walter L, Trowsdale J. Comparative Genomics of Natural Killer Cell Receptor Gene Clusters. PLoS Genet [Internet]. 2005 Aug [cited 2017 Dec 25];1(2). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1193534/

673. Sutcliffe EL, Parish IA, He YQ, Juelich T, Tierney ML, Rangasamy D, et al. Dynamic Histone Variant Exchange Accompanies Gene Induction in T Cells. Mol Cell Biol. 2009 Apr;29(7):1972–86.

674. Santis AG, López-Cabrera M, Sánchez-Madrid F, Proudfoot N. Expression of the early lymphocyte activation antigen CD69, a C-type lectin, is regulated by mRNA degradation associated with AU-rich sequence motifs. Eur J Immunol. 1995 Aug;25(8):2142–6.

675. Laguna T, Notario L, Pippa R, Fontela MG, Vázquez BN, Maicas M, et al. New insights on the transcriptional regulation of CD69 gene through a potent enhancer located in the conserved non-coding sequence 2. Mol Immunol. 2015 Aug 1;66(2):171–9.

676. Jin HY, Oda H, Chen P, Yang C, Zhou X, Kang SG, et al. Differential Sensitivity of Target Genes to Translational Repression by miR-17~92. PLOS Genet. 2017 Feb 27;13(2):e1006623.

677. Risso A, Smilovich D, Capra MC, Baldissarro I, Yan G, Bargellesi A, et al. CD69 in resting and activated T lymphocytes. Its association with a GTP binding protein and biochemical requirements for its expression. J Immunol Baltim Md 1950. 1991 Jun 15;146(12):4105–14.

678. Gräler MH, Huang M-C, Watson S, Goetzl EJ. Immunological Effects of Transgenic Constitutive Expression of the Type 1 Sphingosine 1-Phosphate Receptor by Mouse Lymphocytes. J Immunol. 2005 Feb 15;174(4):1997–2003.

679. Chu P, Pardo J, Zhao H, Li CC, Pali E, Shen MM, et al. Systematic identification of regulatory proteins critical for T-cell activation. J Biol. 2003 Sep 15;2:21.

680. Rosen H, Alfonso C, Surh CD, McHeyzer-Williams MG. Rapid induction of medullary thymocyte phenotypic maturation and egress inhibition by nanomolar sphingosine 1- phosphate receptor agonist. Proc Natl Acad Sci U S A. 2003 Sep 16;100(19):10907–12.

681. Cruz-Adalia A, Jiménez-Borreguero LJ, Ramírez-Huesca M, Chico-Calero I, Barreiro O, López-Conesa E, et al. CD69 limits the severity of cardiomyopathy after autoimmune myocarditis. Circulation. 2010 Oct 5;122(14):1396–404.

682. Martín P, Gómez M, Lamana A, Marín AM, Cortés JR, Ramírez-Huesca M, et al. The leukocyte activation antigen CD69 limits allergic asthma and skin contact hypersensitivity. J Allergy Clin Immunol. 2010 Aug 1;126(2):355-365.e3.

683. Liappas G, González-Mateo GT, Sánchez-Díaz R, Lazcano JJ, Lasarte S, Matesanz-Marín A, et al. Immune-Regulatory Molecule CD69 Controls Peritoneal Fibrosis. J Am Soc Nephrol. 2016 Jan 12;27(12):3561–76.

684. de la Fuente H, Cruz-Adalia A, Martinez del Hoyo G, Cibrián-Vera D, Bonay P, Pérez- Hernández D, et al. The Leukocyte Activation Receptor CD69 Controls T Cell Differentiation through Its Interaction with Galectin-1. Mol Cell Biol. 2014 Jul;34(13):2479–87.

330

685. Cibrián Vera D, Saiz ML, de la Fuente H, Sánchez-Díaz R, Moreno-Gonzalo O, Jorge Cerrudo I, et al. CD69 controls L-Trp uptake through LAT1-CD98 and AhR-dependent IL-22 secretion in psoriasis. Nat Immunol. 2016 Aug;17(8):985–96.

686. Cibrián D, Sánchez-Madrid F. CD69: from activation marker to metabolic gatekeeper. Eur J Immunol. 2017 Jun;47(6):946–53.

687. Liu G, Yang K, Burns S, Shrestha S, Chi H. The S1P1-mTOR axis directs the reciprocal differentiation of TH1 and Treg cells. Nat Immunol. 2010 Nov;11(11):1047–56.

688. Skon CN, Lee J-Y, Anderson KG, Masopust D, Hogquist KA, Jameson SC. Transcriptional downregulation of S1pr1 is required for the establishment of resident memory CD8+ T cells. Nat Immunol. 2013 Dec;14(12):1285–93.

689. Mackay LK, Rahimpour A, Ma JZ, Collins N, Stock AT, Hafon M-L, et al. The developmental pathway for CD103+CD8+ tissue-resident memory T cells of skin. Nat Immunol. 2013 Dec;14(12):1294–301.

690. Mackay LK, Braun A, Macleod BL, Collins N, Tebartz C, Bedoui S, et al. Cutting Edge: CD69 Interference with Sphingosine-1-Phosphate Receptor Function Regulates Peripheral T Cell Retention. J Immunol. 2015 Mar 1;194(5):2059–63.

691. Takamura S, Yagi H, Hakata Y, Motozono C, McMaster SR, Masumoto T, et al. Specific niches for lung-resident memory CD8+ T cells at the site of tissue regeneration enable CD69-independent maintenance. J Exp Med. 2016 Dec 12;213(13):3057–73.

692. Schulz O, Ugur M, Friedrichsen M, Radulovic K, Niess J-H, Jalkanen S, et al. Hypertrophy of infected Peyer’s patches arises from global, interferon-receptor, and CD69-independent shutdown of lymphocyte egress. Mucosal Immunol. 2014 Jul;7(4):892–904.

693. Benechet AP, Menon M, Xu D, Samji T, Maher L, Murooka TT, et al. T cell-intrinsic S1PR1 regulates endogenous effector T-cell egress dynamics from lymph nodes during infection. Proc Natl Acad Sci. 2016 Feb 23;113(8):2182–7.

694. Breart B, Bousso P. S1P1 downregulation tailors CD8+ T-cell residence time in lymph nodes to the strength of the antigenic stimulation. Eur J Immunol. 46(12):2730–6.

695. Kleinwort A, Lührs F, Heidecke C-D, Lipp M, Schulze T. S1P Signalling Differentially Affects Migration of Peritoneal B Cell Populations In Vitro and Influences the Production of Intestinal IgA In Vivo. Int J Mol Sci. 2018 Jan 29;19(2).

696. Zhi L, Kim P, Thompson BD, Pitsillides C, Bankovich AJ, Yun S-H, et al. FTY720 blocks egress of T cells in part by abrogation of their adhesion on the lymph node sinus. J Immunol Baltim Md 1950. 2011 Sep 1;187(5):2244–51.

697. Ledgerwood LG, Lal G, Zhang N, Garin A, Esses SJ, Ginhoux F, et al. The sphingosine 1- phosphate receptor 1 causes tissue retention by inhibiting the entry of peripheral tissue T lymphocytes into afferent lymphatics. Nat Immunol. 2008 Jan;9(1):42–53.

698. Uccellini MB, García-Sastre A. ISRE-Reporter Mouse Reveals High Basal and Induced Type I IFN Responses in Inflammatory Monocytes. Cell Rep. 2018 Dec 4;25(10):2784- 2796.e3.

331

699. Sander LE, Davis MJ, Boekschoten MV, Amsen D, Dascher CC, Ryffel B, et al. Detection of prokaryotic mRNA signifies microbial viability and promotes immunity. Nature. 2011 May 22;474(7351):385–9.

700. Han S-J, Melichar HJ, Coombes JL, Chan SW, Koshy AA, Boothroyd JC, et al. Internalization and TLR-dependent type I interferon production by monocytes in response to Toxoplasma gondii. Immunol Cell Biol. 2014 Nov;92(10):872–81.

701. Mack M, Cihak J, Simonis C, Luckow B, Proudfoot AE, Plachý J, et al. Expression and characterization of the chemokine receptors CCR2 and CCR5 in mice. J Immunol Baltim Md 1950. 2001 Apr 1;166(7):4697–704.

702. Brühl H, Cihak J, Plachý J, Kunz‐Schughart L, Niedermeier M, Denzel A, et al. Targeting of Gr-1+,CCR2+ monocytes in collagen-induced arthritis. Arthritis Rheum. 2007;56(9):2975–85.

703. Hammond MD, Taylor RA, Mullen MT, Ai Y, Aguila HL, Mack M, et al. CCR2+Ly6Chi Inflammatory Monocyte Recruitment Exacerbates Acute Disability Following Intracerebral Hemorrhage. J Neurosci. 2014 Mar 12;34(11):3901–9.

704. Schumak B, Klocke K, Kuepper JM, Biswas A, Djie-Maletz A, Limmer A, et al. Specific Depletion of Ly6Chi Inflammatory Monocytes Prevents Immunopathology in Experimental Cerebral Malaria. PLoS ONE [Internet]. 2015 Apr 17 [cited 2019 May 22];10(4). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4401438/

705. Heung LJ, Hohl TM. Inflammatory monocytes are detrimental to the host immune response during acute infection with Cryptococcus neoformans. PLOS Pathog. 2019 Mar 21;15(3):e1007627.

706. Soudja SM, Ruiz AL, Marie JC, Lauvau G. Inflammatory monocytes activate memory CD8(+) T and innate NK lymphocytes independent of cognate antigen during microbial pathogen invasion. Immunity. 2012 Sep 21;37(3):549–62.

707. Soudja SM, Chandrabos C, Yakob E, Veenstra M, Palliser D, Lauvau G. Memory-T-cell- derived interferon-γ instructs potent innate cell activation for protective immunity. Immunity. 2014 Jun 19;40(6):974–88.

708. Johndrow CT, Goldberg MF, Johnson AJ, Ng TW, Kunnath-Velayudhan S, Lauvau G, et al. Suppression of Th1 Priming by TLR2 Agonists during Cutaneous Immunization Is Mediated by Recruited CCR2+ Monocytes. J Immunol Baltim Md 1950. 2018 15;201(12):3604–16.

709. Shi J, Hua L, Harmer D, Li P, Ren G. Cre Driver Mice Targeting Macrophages. Methods Mol Biol Clifton NJ. 2018;1784:263–75.

710. Frederico B, Chao B, Lawler C, May JS, Stevenson PG. Subcapsular sinus macrophages limit acute gammaherpesvirus dissemination. J Gen Virol. 2015 Aug;96(Pt 8):2314–27.

711. Croxford AL, Lanzinger M, Hartmann FJ, Schreiner B, Mair F, Pelczar P, et al. The Cytokine GM-CSF Drives the Inflammatory Signature of CCR2+ Monocytes and Licenses Autoimmunity. Immunity. 2015 Sep 15;43(3):502–14.

712. Pizzagalli DU, Latino I, Pulfer A, Palomino-Segura M, Virgilio T, Farsakoglu Y, et al. Characterization of the Dynamic Behavior of Neutrophils Following Influenza Vaccination.

332

Front Immunol [Internet]. 2019 [cited 2020 Apr 3];10. Available from: https://www.frontiersin.org/articles/10.3389/fimmu.2019.02621/full

713. Scales HE, Meehan GR, Hayes AJ, Benson RA, Watson E, Walters A, et al. A Novel Cellular Pathway of Antigen Presentation and CD4 T Cell Activation in vivo. Front Immunol [Internet]. 2018 [cited 2020 Apr 3];9. Available from: https://www.frontiersin.org/articles/10.3389/fimmu.2018.02684/full

714. Barbet G, Sander LE, Geswell M, Leonardi I, Cerutti A, Iliev I, et al. Sensing Microbial Viability through Bacterial RNA Augments T Follicular Helper Cell and Antibody Responses. Immunity. 2018 20;48(3):584-598.e5.

715. Jakubzick CV, Randolph GJ, Henson PM. Monocyte differentiation and antigen- presenting functions. Nat Rev Immunol. 2017 Jun;17(6):349–62.

716. Maurice NJ, McElrath MJ, Andersen-Nissen E, Frahm N, Prlic M. CXCR3 enables recruitment and site-specific bystander activation of memory CD8 + T cells. Nat Commun. 2019 Nov 1;10(1):1–15.

717. Ferrer M, Martin-Jaular L, Calvo M, del Portillo HA. Intravital Microscopy of the Spleen: Quantitative Analysis of Parasite Mobility and Blood Flow. J Vis Exp JoVE [Internet]. 2012 Jan 14 [cited 2020 Apr 9];(59). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3462559/

718. Zaric M, Becker PD, Hervouet C, Kalcheva P, Doszpoly A, Blattman N, et al. Skin immunisation activates an innate lymphoid cell-monocyte axis regulating CD8+ effector recruitment to mucosal tissues. Nat Commun [Internet]. 2019 May 17 [cited 2020 Apr 9];10. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525176/

719. Chu T, Tyznik AJ, Roepke S, Berkley AM, Woodward-Davis A, Pattacini L, et al. Bystander-activated memory CD8 T cells control early pathogen load in an innate-like, NKG2D-dependent manner. Cell Rep. 2013 Mar 28;3(3):701–8.

720. Narni-Mancinelli E, Soudja SM, Crozat K, Dalod M, Gounon P, Geissmann F, et al. Inflammatory Monocytes and Neutrophils Are Licensed to Kill during Memory Responses In Vivo. PLOS Pathog. 2011 Dec 29;7(12):e1002457.

721. Nakanishi Y, Sato T, Takahashi K, Ohteki T. IFN-γ-dependent epigenetic regulation instructs colitogenic monocyte/macrophage lineage differentiation in vivo. Mucosal Immunol. 2018;11(3):871–80.

722. Martin MD, Badovinac VP. Antigen-dependent and –independent contributions to primary memory CD8 T cell activation and protection following infection. Sci Rep. 2015 Dec 10;5(1):1–13.

723. Shin K-S, Jeon I, Kim B-S, Kim I-K, Park Y-J, Koh C-H, et al. Monocyte-Derived Dendritic Cells Dictate the Memory Differentiation of CD8+ T Cells During Acute Infection. Front Immunol [Internet]. 2019 Aug 16 [cited 2020 Apr 9];10. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6706816/

724. Goldszmid RS, Caspar P, Rivollier A, White S, Dzutsev A, Hieny S, et al. NK cell-derived interferon-γ orchestrates cellular dynamics and the differentiation of monocytes into dendritic cells at the site of infection. Immunity. 2012 Jun 29;36(6):1047–59.

333

725. Lighvani AA, Frucht DM, Jankovic D, Yamane H, Aliberti J, Hissong BD, et al. T-bet is rapidly induced by interferon-gamma in lymphoid and myeloid cells. Proc Natl Acad Sci U S A. 2001 Dec 18;98(26):15137–42.

726. Fang D, Cui K, Mao K, Hu G, Li R, Zheng M, et al. Transient T-bet expression functionally specifies a distinct T follicular helper subset. J Exp Med. 2018 05;215(11):2705–14.

727. Chakarov S, Fazilleau N. Monocyte-derived dendritic cells promote T follicular helper cell differentiation. EMBO Mol Med. 2014 May;6(5):590–603.

728. Bucasas KL, Franco LM, Shaw CA, Bray MS, Wells JM, Niño D, et al. Early patterns of gene expression correlate with the humoral immune response to influenza vaccination in humans. J Infect Dis. 2011 Apr 1;203(7):921–9.

729. Zak DE, Aderem A. Systems integration of innate and adaptive immunity. Vaccine. 2015 Sep 29;33(40):5241–8.

730. Bidet K, Ho V, Chu CW, Naim ANH, Thazin K, Chan KR, et al. Mimicking immune signatures of flavivirus infection with targeted adjuvants improves dengue subunit vaccine immunogenicity. NPJ Vaccines. 2019;4:27.

731. Medaglia C, Giladi A, Stoler-Barak L, Giovanni MD, Salame TM, Biram A, et al. Spatial reconstruction of immune niches by combining photoactivatable reporters and scRNA-seq. Science. 2017 Dec 22;358(6370):1622–6.

732. Fletcher AL, Malhotra D, Acton SE, Lukacs-Kornek V, Bellemare-Pelletier A, Curry M, et al. Reproducible isolation of lymph node stromal cells reveals site-dependent differences in fibroblastic reticular cells. Front Immunol. 2011;2:35.

334

Appendix 1: Vaccines Included in the UK Immunisation Regimen (1)

Vaccine (Trade Name) Constituents Vaccine Type Adjuvant Protective Against Age and site of Administration Infanrix Hexa (2) Diphtheria toxoid Subunit Adsorbed on Diphtheria, Tetanus, 8, 12 and 16 weeks, i.m. Tetanus toxoid Subunit aluminium hydroxide Pertussis (whooping cough) Bordetella pertussis antigens; Pertussis toxoid, Subunit Filamentous haemagglutinin, Pertactin Hepatitis B Surface Antigen Subunit Adsorbed on aluminium phosphate Haemophilus influenzae type b polysaccharide Subunit conjugated to tetanus toxoid Inactivated Poliovirus (Types 1-3) Inactivated N/A Prevenar 13 (3) Pneumococcal polysaccharides – 13 serotypes, each Subunit adsorbed on Pneumococcal pneumonia 8 weeks, 1 year, i.m. conjugated to a carrier protein aluminium phosphate (13 serotypes) Bexsero (4) Recombinant N. meningitidis proteins Neisserial Subunit adsorbed on Meningitis 8 weeks, 16 weeks, 1- heparin binding antigen (NHBA), Neisseria adhesion aluminium hydroxide Neisseria meningitidis year i.m. A, and factor H binding protein. group B Neisseria meningitides outer membrane vesicles Rotarix (5) Human rotavirus RIX4414 strain Live Attenuated N/A Rotavirus Gastroenteritis 8 weeks, 12 weeks, PO Menitorix (6) Haemophilus influenzae type b polysaccharide Subunit N/A Haemophilus and 1 year old, i.m. conjugated to tetanus toxoid Meningitis C Neisseria meningitidis serogroup C (strain C11) polysaccharide conjugated to tetanus toxoid as carrier protein MMR VaxPRO (7) Measles virus Enders’ Edmonston strain (live, Live Attenuated N/A Measles, mumps and 1 year, 3 years 4 months attenuated) rubella old, i.m. Mumps virus Jeryl Lynn™ [Level B] strain Rubella virus Wistar RA 27/3 strain Priorix (8) measles virus (Schwarz strain) Live Attenuated N/A Measles, mumps and 1 year, 3 years 4 months mumps virus (RIT 4385 strain, derived from Jeryl rubella old i.m. Lynn strain) rubella virus2 (Wistar RA 27/3 strain)

335

Gardasil (9) Human Papillomavirus (types 6, 11, 18 and 18) L1 Subunit adsorbed on Human Papilloma Virus 12-13 years of age, 2 proteins amorphous Cancers, genital warts doses, 6 months apart, aluminium i.m. hydroxyphosphate sulphate Revaxis (10) Diphtheria toxoid Subunit Adsorbed on Tetanus, diphtheria and 14 years of age, i.m. Tetanus toxoid Subunit aluminium hydroxide polio Inactivated Poliomyelitis virus (Types 1-3) Inactivated Fluenz Tetra (11) 4 strains of reassortant influenza virus (strains Live Attenuated N/A Influenza Eligible Paediatric Age change annually) Groups (12). Intranasal. Nimenrix (13) Neisseria Meningitidis group A, C, W-135 and Y Subunit N/A Meningitis ACWY 14 years of age, i.m. polysaccharides conjugated to carrier protein Menveo (14) Neisseria Meningitidis group A, C, W-135 and Y Subunit N/A Meningitis ACWY 14 years of age, i.m. oligosaccharides conjugated to carrier protein Pneumococcal Polysaccharide Pneumococcal polysaccharides – 23 serotypes Subunit N/A Pneumococcal Pneumonia 65 years of age, i.m. Vaccine (15) (23 serotypes) Fluad - Adjuvanted Trivalent Influenza virus surface antigens (haemagglutinin Inactivated/Subunit MF-59 Influenza ≥65 years of age, i.m. Inactivated Vaccine (aTIV) (16) and neuraminidase) from 3 strains (combination varies seasonally) Quadrivalent Inactivated Inactivated split influenza virions from 4 different Inactivated None Influenza Children aged 6 months Influenza Vaccine, egg-grown strains (combination varies seasonally) to 2 years and Adults (QIVe) e.g. Fluarix Tetra (17) aged 18-64, i.m. (1,18) Quadrivalent Inactivated Influenza virus surface antigens (haemagglutinin Inactivated/Subunit None Influenza Adults aged 18-64, i.m. Influenza Vaccine, cell-grown and neuraminidase) from 4 strains (combination (QIVc) e.g. Flucelvax Tetra (19) varies seasonally) Trivalent Influenza Vaccine (split Inactivated split influenza virions from 3 different Inactivated None Influenza ≥65 years of age, i.m. virion, inactivated) – High Dose strains (combination varies seasonally) – high dose (TIV-HD) (20) Zostavax (21) Live Attenuated Varicella Zoster Virus Live Attenuated None Shingles 70 years old, i.m. or s/c

Non-routine vaccines BCG SSI (22) Bacillus Calmette Guerin (Live-attenuated Live Attenuated None Tuberculosis At birth if TB incidence Mycobacterium Bovis) ≥40/100,000 or infant with a parent/grandparent from high incidence country, i.d.

336

Engerix B (23) Recombinant Hepatitis B Surface Antigen Subunit None Hepatitis B Babies Born to HBV- infected mothers. Given at birth, 4 weeks and 12 months old. i.m. HBvaxPRO (24) Recombinant Hepatitis B Surface Antigen Subunit Adsorbed on Hepatitis B Babies Born to HBV- amorphous infected mothers. Given aluminium at birth, 4 weeks and 12 hydroxyphosphate months old. i.m. sulfate Boostrix IPV (25) Diphtheria toxoid Subunit adsorbed on Pertussis Pregnant women, i.m. Tetanus toxoid Subunit aluminium hydroxide, hydrated (Al(OH)3) Bordetella Pertussis antigens (filamentous Subunit and aluminium haemagglutinin, pertactin), phosphate (AlPO4) Inactivated poliovirus (3 strains) Inactivated None Repevax (26) Diphtheria toxoid Subunit Adsorbed on Pertussis Pregnant women, i.m. Tetanus toxoid Subunit Aluminium Phosphate Bordetella Pertussis antigens (filamentous Subunit haemagglutinin, pertactin, fimbriae types 2 and 3) Inactivated poliovirus (3 strains) Inactivated Avaxim (27) Inactivated Hepatitis A Virus Inactivated Adsorbed on Hepatitis A Chronic liver conditions, hydrated aluminium haemophilia, booster hydroxide required, i.m. or s/c

337

References

1. Complete routine immunisation schedule [Internet]. GOV.UK. [cited 2020 Jun 18]. Available from: https://www.gov.uk/government/publications/the-complete-routine-immunisation-schedule

2. Anonymous. Infanrix Hexa [Internet]. European Medicines Agency. 2018 [cited 2020 Jun 18]. Available from: https://www.ema.europa.eu/en/medicines/human/EPAR/infanrix-hexa

3. Anonymous. Prevenar 13 [Internet]. European Medicines Agency. 2018 [cited 2020 Jun 18]. Available from: https://www.ema.europa.eu/en/medicines/human/EPAR/prevenar-13

4. Anonymous. Bexsero [Internet]. European Medicines Agency. 2018 [cited 2020 Jun 18]. Available from: https://www.ema.europa.eu/en/medicines/human/EPAR/bexsero

5. Anonymous. Rotarix [Internet]. European Medicines Agency. 2018 [cited 2020 Jun 18]. Available from: https://www.ema.europa.eu/en/medicines/human/EPAR/rotarix

6. Anonymous. Menitorix [Internet]. European Medicines Agency. 2018 [cited 2020 Jun 18]. Available from: https://www.ema.europa.eu/en/medicines/human/referrals/menitorix

7. Anonymous. M-M-RVaxPro [Internet]. European Medicines Agency. 2018 [cited 2020 Jun 18]. Available from: https://www.ema.europa.eu/en/medicines/human/EPAR/m-m-rvaxpro

8. Priorix powder and solvent for solution for injection in a pre-filled syringe - Summary of Product Characteristics (SmPC) - (emc) [Internet]. [cited 2020 Jun 18]. Available from: https://www.medicines.org.uk/emc/product/1159/smpc

9. Anonymous. Gardasil 9 [Internet]. European Medicines Agency. 2018 [cited 2020 Jun 18]. Available from: https://www.ema.europa.eu/en/medicines/human/EPAR/gardasil-9

10. REVAXIS - Summary of Product Characteristics (SmPC) - (emc) [Internet]. [cited 2020 Jun 18]. Available from: https://www.medicines.org.uk/emc/medicine/15259

11. Anonymous. Fluenz Tetra [Internet]. European Medicines Agency. 2018 [cited 2020 Jun 18]. Available from: https://www.ema.europa.eu/en/medicines/human/EPAR/fluenz-tetra

338

12. Ramsay M. Chapter 19: Influenza. In: Immunisation against Infectious Diseases [Internet]. Public Health England; 2013. p. 1–27. Available from: https://www.gov.uk/government/publications/influenza-the-green-book-chapter-19

13. Anonymous. Nimenrix [Internet]. European Medicines Agency. 2018 [cited 2020 Jun 18]. Available from: https://www.ema.europa.eu/en/medicines/human/EPAR/nimenrix

14. Anonymous. Menveo [Internet]. European Medicines Agency. 2018 [cited 2020 Jun 18]. Available from: https://www.ema.europa.eu/en/medicines/human/EPAR/menveo

15. Pneumococcal Polysaccharide Vaccine - Summary of Product Characteristics (SmPC) - (emc) [Internet]. [cited 2020 Jun 18]. Available from: https://www.medicines.org.uk/emc/product/1061/smpc#PRODUCTINFO

16. Fluad, Suspension for injection in pre-filled syringe - Summary of Product Characteristics (SmPC) - (emc) [Internet]. [cited 2020 Jun 18]. Available from: https://www.medicines.org.uk/emc/product/9223/smpc

17. Fluarix Tetra - Summary of Product Characteristics (SmPC) - (emc) [Internet]. [cited 2020 Jun 18]. Available from: https://www.medicines.org.uk/emc/medicine/27537

18. Inactivated Flu Vaccine | Vaccine Knowledge [Internet]. [cited 2020 Jun 18]. Available from: https://vk.ovg.ox.ac.uk/vk/inactivated-flu-vaccine

19. Anonymous. Flucelvax Tetra [Internet]. European Medicines Agency. 2018 [cited 2020 Jun 18]. Available from: https://www.ema.europa.eu/en/medicines/human/EPAR/flucelvax-tetra

20. Trivalent Influenza Vaccine (Split Virion, Inactivated) High Dose - Summary of Product Characteristics (SmPC) - (emc) [Internet]. [cited 2020 Jun 18]. Available from: https://www.medicines.org.uk/emc/product/10012/smpc

21. Anonymous. Zostavax [Internet]. European Medicines Agency. 2018 [cited 2020 Jun 18]. Available from: https://www.ema.europa.eu/en/medicines/human/EPAR/zostavax

22. BCG Vaccine AJV - Summary of Product Characteristics (SmPC) - (emc) [Internet]. [cited 2020 Jun 18]. Available from: https://www.medicines.org.uk/emc/product/9890

23. Anonymous. Engerix B [Internet]. European Medicines Agency. 2018 [cited 2020 Jun 18]. Available from: https://www.ema.europa.eu/en/medicines/human/referrals/engerix-b

339

24. Anonymous. HBVaxPro [Internet]. European Medicines Agency. 2018 [cited 2020 Jun 18]. Available from: https://www.ema.europa.eu/en/medicines/human/EPAR/hbvaxpro

25. Boostrix-IPV suspension for injection in pre-filled syringe - Summary of Product Characteristics (SmPC) - (emc) [Internet]. [cited 2020 Jun 18]. Available from: https://www.medicines.org.uk/emc/product/5302/smpc

26. REPEVAX, suspension for injection, in pre-filled syringe - Summary of Product Characteristics (SmPC) - (emc) [Internet]. [cited 2020 Jun 18]. Available from: https://www.medicines.org.uk/emc/product/5580/smpc

27. AVAXIM suspension for injection in a pre-filled syringe - Summary of Product Characteristics (SmPC) - (emc) [Internet]. [cited 2020 Jun 18]. Available from: https://www.medicines.org.uk/emc/product/1394/smpc

340

341