Characterization of the Immunoregulatory Roles of IFN-Β in T Cells and Dendritic Cells

Home , Eleanor Fish

Characterization of the immunoregulatory roles of IFN-β in T cells and dendritic cells

Leesa Pennell

A thesis submitted in conformity with the requirements for the degree

Doctor of Philosophy

Graduate Department of Immunology

University of Toronto

Characterization of the immunoregulatory roles of IFN-β in T cells and dendritic cells

Leesa Pennell Doctor of Philosophy Department of Immunology University of Toronto 2017 Abstract

Multiple sclerosis (MS) is an autoimmune disease that targets the central nervous system (CNS).

Interferon (IFN)-β was the first approved therapy for relapsing-remitting MS more than 20 years ago, however, its mechanism of action remains ill-defined. Using a myelin oligodendrocyte glycoprotein (MOG)-induced murine experimental autoimmune encephalomyelitis (EAE) model for MS, our earlier studies identified that IFN-β-/- mice exhibit an earlier onset and a more rapid progression of disease compared to IFN-β+/+ mice. CD4+ T cells, specifically of the Th17 lineage, are posited to be pathogenic in MS and in EAE, and CD11c+ dendritic cells (DCs) are critical antigen-presenting cells that have the potential to regulate pathogenic T cells in MS and

EAE. Accordingly, we investigated the immunoregulatory effects of IFN-β on CD4+ T cells and

DCs. Our studies revealed that CD4+ T cells isolated from IFN-β-/- mice are primed to polarize to the Th17 lineage, associated with expression of Th17-associated cytokine receptors.

Stimulation with a cocktail of Th17-inducing cytokines led to increased expression of Th17- associated genes in IFN-β-/- Th17 cells compared to IFN-β+/+ Th17 cells, suggestive of a regulatory role for IFN-β in determining the Th17 cell transcriptome. Consistent with these findings, we observed a greater proportion of Th17 cells in the LNs of IFN-β-/- mice compared with IFN-β+/+ mice during EAE, with increased numbers of CD4+ T cells in the CNS of IFN-β-/- mice, regardless of stage of disease. We identified that IFN-β exerts immunoregulatory effects on DCs, associated with determining cytokine production and expression of co-stimulatory activation markers. IFN-β-/- DCs drive increased proliferation of MOG-transgenic CD4+ T cells,

and produce more IL-6 and IL-23, critical for induction of Th17 cells. Finally, we provide evidence that IFN-β regulates the migration of DCs into the CNS during EAE, by modulating

STAT1-dependent CCR7 expression. Taken together, our data indicate immunoregulatory roles for IFN-β in suppression of Th17 cells and in limiting the activation and trafficking of DCs during EAE.

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Acknowledgements

First and foremost, I would like to thank my supervisor, Dr. Eleanor Fish, for taking me under your wing when I first came to Toronto and giving me the opportunity to work in your lab. I have learned so much from you, Eleanor. You have taught me how to design thoughtful experiments, how to communicate my work with others, and how to be a successful female scientist. You have been a source of inspiration and a role model that I will always look up to. Thank you so, so much. To my committee members, Dr. Michele Anderson and Dr. Shannon Dunn. Thank you for all of the support and guidance you have given me throughout my PhD. Whether our discussions happened during my committee meetings or at departmental seminars or events, I valued each and every one and came away with new ideas that helped to shape my work. To the members of the Fish Lab, past and present (Beata, Carole, Daniel, Erin, Olivia, Ben and Darrin). Thank you for putting up with my slightly OCD tendencies when it came to my lab markers and labelling of everything I possibly could. Our lunchtime discussions and coffee breaks saved my sanity during long days of experiments. Beata, you make the lab run. Thank you for all your help and support in the lab and otherwise. Carole, thank you for starting up the project that I took over. Our scientific discussions and your valuable input over the years were so important to me. Thank you, also, for teaching me not to be afraid of multi-colour flow cytometry. To my parents and my family. Thank you for your understanding and support when I said I would ‘still be in school a bit longer’ for so many years. I know it wasn’t easy to understand but I appreciate your love and patience throughout this process. To my husband, Tomas. You are a source of inspiration every day. You have encouraged me, supported me, and urged me to follow my dreams. I can’t wait for the rest of our future together and only hope I can be just as supportive for you as you have been for me. To all of the members of the Department of Immunology and friends I’ve made over the years. Your support and friendship helped motivate me through the tough times and you were always there to celebrate success. All of the scientific and non-scientific discussions we had certainly made for an unforgettable journey. I will always rememeber the IGSA events and meetings, pub nights, intramural activites, and all the times we spent together. My time here would not have been the same without these experiences and for that, I am so grateful.

List of Publications

Pennell LM, Fish EN. 2017. Interferon-β regulates dendritic cell activation and migration in experimental autoimmune encephalomyelitis. (Manuscript under review).

Pennell LM, Fish EN. 2014. Immunoregulatory effects of interferon-β in suppression of Th17 cells. J Interferon Cytokine Res. 34(5):330–41

Pennell, LM., Galligan, CL. and Fish, EN. 2012. Sex Affects Immunity. J Autoimmun. 38(2-3): J282-91

Galligan CL, Pennell LM, Murooka TT, Baig E, Majchrzak-Kita B, et al. 2010. Interferon-beta is a key regulator of proinflammatory events in experimental autoimmune encephalomyelitis. Mult Scler. 16(12):1458–73

Table of Contents

Abstract ...... ii-iii Acknowledgements ...... iv List of Publications ...... v Table of Contents ...... vi-vii List of Tables ...... viii List of Figures ...... ix List of Abbreviations ...... x-xii Chapter 1: Introduction ...... 1-47 1.1 Interferons ...... 2 1.1.1 Classification of IFNs ...... 2 1.1.1.1 Type I IFNs ...... 3 1.1.1.2 Type II and III IFNs ...... 4 1.1.2 Type I IFN induction and signaling ...... 4 1.1.3 Regulation of type I IFN responses ...... 7 1.2 CD4+ T helper cells ...... 7 1.2.1 CD4+ T helper subsets ...... 8 1.2.1.1 Th1 cells ...... 10 1.2.1.2 Th2 cells ...... 10 1.2.1.3 Th17 cells ...... 11 1.2.1.4 Regulatory T cells ...... 12 1.2.2 Activation of T cells, TCR signaling & T cell migration ...... 13 1.2.2.1 Activation of T cells and TCR signaling ...... 14 1.2.2.2 Migration of T cells ...... 16 1.2.3 IFN effects on T cells ...... 20 1.3 Dendritic cells ...... 21 1.3.1 Types of DCs ...... 22 1.3.1.1 cDCs ...... 24 1.3.1.2 pDCs ...... 26 1.3.1.3 moDCs ...... 26 1.3.2 Activation and migration of DCs ...... 27 1.3.2.1 Activation of DCs ...... 27 1.3.2.2 Migration of DCs ...... 31 1.3.3 IFN-β effects on DCs ...... 33 1.4 Multiple Sclerosis and Experimental Autoimmune Encephalomyelitis ...... 34 1.4.1 MS pathogenesis ...... 35 1.4.2 The EAE model of MS ...... 38 1.4.3 T cells in MS and EAE ...... 39 1.4.4 DCs in MS and EAE ...... 40 1.4.5 Therapies for MS ...... 41 1.4.5.1 IFN-β effects on T cells in MS and EAE ...... 43 1.4.5.2 IFN-β effects on DCs in MS and EAE ...... 45

1.5 Hypothesis and Objectives ...... 47 Chapter 2: Materials and Methods ...... 48-56 2.1 Mice ...... 49 2.2 Genotyping ...... 49 2.3 EAE induction ...... 49 2.4 Magnetic Cell Separation (CD4+ T cells & CD11c+ DCs) ...... 50 2.5 Immunoblotting ...... 50 2.6 Th17 cell generation and sorting ...... 51 2.7 RNA extraction and gene expression analysis using PCR Arrays ...... 52 2.8 Real-Time PCR ...... 52 2.9 Intracellular Cytokine Staining for Fluoresence-Activated Cell Sorting (FACS) ...... 53 2.10 Surface staining for FACS ...... 54 2.11 Cell proliferation assays ...... 54 2.12 Enzyme-linked Immunosorbent Assay (ELISA) & FlowCytomix Cytokine Analysis ... 55 2.13 Bone marrow derived dendritic cell generation ...... 55 2.14 Gene expression analysis ...... 55 2.15 Adoptive transfer ...... 56 Chapter 3: Immunoregulatory effects of Interferon-beta in suppression of Th17 cells .. 57-75 3.1 Abstract ...... 58 3.2 Introduction ...... 59 3.3 Results ...... 61 3.4 Discussion ...... 72 Chapter 4: Interferon-β regulates dendritic cell activation and migration in experimental autoimmune encephalomyelitis ...... 76-94 4.1 Abstract ...... 77 4.2 Introduction ...... 78 4.3 Results ...... 79 4.4 Discussion ...... 90 Chapter 5: Discussion and Future Directions ...... 95-107 5.1 Thesis Summary ...... 96 5.2 Discussion and areas of future study ...... 99 5.3 Summary Statement ...... 104 Chapter 6: References ...... 108

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List of Tables

Chapter 1

Table 1.1 Chemokine receptors and S1P receptors expressed by different T cell subsets that influence their migration ...... 19 Table 1.2 Chemokine receptor, TLR and S1P receptor expression on DC subsets ...... 32

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List of Figures

Chapter 1

Figure 1.1 Subtypes of CD4+ T cells...... 9 Figure 1.2 T cell receptor signaling cascade...... 15 Figure 1.3 Classification of DC subsets in mice and humans...... 23 Figure 1.4 TLR signaling cascades...... 29 Figure 1.5 Overview of MS pathogenesis...... 37

Chapter 3

Figure 3.1 IFN-β CD4+ T cells secrete IL-17A after anti-CD3/anti-CD28 stimulation...... 62 Figure 3.2 IFN-β influences IRF4, but not S1PR1 expression in CD4+ T cells...... 64 Figure 3.3 IFN-β regulates levels of Th17-associated cell surface receptors...... 66 Figure 3.4 IFN-β influences the ‘Th17 transcriptome’...... 69 Figure 3.5 IFN-β influences Th17 polarization in vivo...... 71

Chapter 4

Figure 4.1 Activation of IFN-β+/+ and IFN-β-/- DCs leads to differential cytokine production. .. 80 Figure 4.2 DCs from IFN-β-/- mice drive increased MOG-transgenic CD4+ T cell proliferation.82 Figure 4.3 LPS stimulation modulates co-stimulatory molecule and MHCII expression on splenic DCs from IFN-β+/+ and IFN-β-/- mice...... 84 Figure 4.4 DCs from IFN-β-/- mice with EAE have increased CD80 and MHCII expression and drive increased proliferation of MOG-transgenic CD4+ T cells...... 86 Figure 4.5 Activated IFN-β-/- DCs produce pro-Th17 cytokines and drive Th17 polarization ex vivo...... 87 Figure 4.6 IFN-β affects CCR7 expression on DCs thereby contributing to their migratory capacity to the CNS...... 89

Chapter 5

Figure 5.1 Immunoregulatory effects of IFN-β on DCs and CD4+ T cells...... 98

List of Abbreviations

APC Antigen presenting cell BBB Blood-brain barrier BMDC Bone marrow-derived dendritic cell BMM Bone marrow-derived macrophage BSA Bovine serum albumin CCL Chemokine (C-C motif) ligand CCR Chemokine (C-C motif) receptor CD Cluster of Differentiation cDNA Complementary DNA CFA Complete Freund’s adjuvant CLR C-type lectin receptor CNS Central nervous system CO2 Carbon dioxide CPD Cell proliferation dye CrkL Crk-like protein CSF Cerebrospinal fluid CSK C-terminal src kinase CTLA-4 Cytotoxic T lymphocyte associated protein 4 CXCL Chemokine (C-X-C motif) ligand CXCR Chemokine (C-X-C motif) receptor DAG Diacylglycerol DC Dendritic cell DMSO Dimethyl sulfoxide DNA Deoxyribonucleic acid DTT Dithiothreitol EAE Experimental autoimmune encephalomyelitis EDTA Ethylenediaminetetracetic Acid ELISA Enzyme-linked immunosorbent assay ERK Extracellular regulated kinase FACS Fluorescence-activated cell sorting FCS Fetal calf serum GAS Gamma activated sequence GEF Guanine exchange factor GM-CSF Granulocyte-macrophage colony stimulating factor GWAS Genome-wide association study HDM House dust mite HEV High endothelial venule HLA Human leukocyte antigen HMGB1 High mobility group box 1 HPRT Hypoxanthine guanine phosphoribosyltransferase HSC Hematopoeitic stem cell ICAM1 Intercellular adhesion molecule 1 ICOS Inducible T cell co-stimulator IDO Indoleamine 2,3-deoxygenase

IFN Interferon IFNAR Interferon alpha receptor IFNGR Interferon gamma receptor IFNLR Interferon lambda receptor Ig Immunoglobulin IKK IκB kinase IKKε IκB kinase ε IL Interleukin ILC Innate lymphoid cell IP3 Inositol triphosphate IRAK IL-1R associated kinase IRF Interferon regulatory factor ISRE Interferon-stimulated response element ITAM Immunoreceptor tyrosine-based activation motif ITIM Immunoreceptor tyrosine-based inihbitory motif ITK Inducible T cell kinase JAK Janus kinase JNK c-Jun N-Terminal kinase KO Knock out LAT Linker for activated T cells LCMV Lymphocytic choriomeningitis virus LFA1 Lymphocyte function associated antigen 1 LN Lymph node LPS lipopolysaccharide MAL MyD88 adapter-like MAPK Mitogen activated protein kinase MBP Myelin basic protien MHCI Major histocompatibility complex type I MHCII Major histocompatibility complex type II miR MicroRNA mL Mililiter mM Millimolar MOG Myelin oligodendrocyte glycoprotein MRI Magnetic resonance imaging MS Multiple Sclerosis mTOR Mammalian target of rapamycin MyD88 Myeloid differentiation primary-response protein-88 NFAT Nuclear factor of activated T cells NFκB Nuclear Factor-κB ng Nanogram NK Natural killer NLR Nuclear oligomerization domain (NOD)-like receptor PBS Phosphate buffered saline PCR Polymerase chain reaction PD-1 Programmed cell death protein 1 pg Picogram

PI3K Phosphatidylinositol 3’-kinase PIAS Protein inhibitor of activated STAT PIP2 Phosphotidylinositol biphosphate PKC Protein kinase C PLC Phosphoinositide-specific phospholipase C PLP Proteolipid protein PMA Phorbol 12-myristate 13-acetate PNAd Peripheral node addressin PPMS Primary progressive MS PRR Pattern recognition receptor PTX Pertussis toxin RA Rheumatoid arthritis RBC Red blood cell RLR Retinoic acid-inducible gene (RIG)-I-like receptor RNA Ribonucleic acid RPMI Roswell park memorial institute (medium) RRMS Relapsing-remitting MS S1P Sphingosine-1-phosphate SDS Sodium dodecyl sulfate SHP-1 SH2 domain-containing protein tyrosine phosphatase 1 SLE Systemic lupus erythematosus SLO Secondary lymphoid organs SLP-76 Src homology 2-domain-containing leukocyte protein of 76 kDa SOCS Suppresor of cytokine signaling SPMS Secondary progressive MS STAT Signal transducer and activator of transcription TAK1 TGF-β activated kinase-1 TBK Tank binding kinase TBS Tris-buffered saline TCR T cell receptor TGF-β Transforming growth factor-beta TIR Toll-IL-1-resistance TLR Toll like receptor TMEV Theiler’s murine encephalitis virus TNF Tumor necrosis factor Treg Regulatory T cell TRIF TIR domain-containing adapter protein inducing IFN-β Tyk2 Tyrosine kinase 2 USP18 Ubiquitin carboxy-terminal hydrolase VLA-4 Very late antigen 4 WT Wild type ZAP-70 Zeta-associated protein kinase, 70 kD µg Microgram µM Micromolar µm Micrometer

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Chapter 1

Introduction

Chapter 1: Introduction

1.1 Interferons Interferons (IFNs) were first identified by Isaacs and Lindenmann in 1957 as factors that interfered with viral replication in chicken cells (1). In the decades since their discovery, much more about IFNs, their receptors and their pleiotropic cellular effects has been elucidated. The IFN family of cytokines signals through distinct cell surface receptors and trigger various signaling pathways leading to an antiviral state, growth inhibition and immunomoduation. While IFNs have been studied in the context of viral clearance and cancers, they also have multifaceted roles in regulating various immune processes (2, 3). The broad immunomodulatory effects of IFNs in the context of disease are demonstrated by their clinical use for treatment of viral infections including hepatitis B and C, various cancers and multiple sclerosis (MS) (4). This section will describe the different types of IFNs, how type I IFNs signal, and how these signals are regulated in an immune response.

1.1.1 Classification of IFNs

There are three families of IFNs, each classified by the receptors that they bind and the effects that they have on immune cells. Mammalian type I IFNs consist of 9 different subtypes – 13 IFN-α subtypes, IFN-β, IFN-ε, IFN-τ, IFN-κ, IFN-ω, IFN-δ, IFN-ν and IFN-ζ (5). This family of cytokines binds the type I IFN receptor (IFNAR) complex and the subsequent signaling induces various biological responses in different cell populations (4). The single type II IFN, IFN-γ, binds the interferon gamma receptor (IFNGR) complex and predominantly plays a role in activation of adaptive immune responses (4). More recently, Type III IFNs (four types in humans and two in mice) were identified and these bind an IL10R2-containing complex and trigger antiviral, type I IFN-like, responses, mainly at mucosal surfaces, where the interferon lambda receptor (IFNLR) complex is expressed (6). All IFNs share basic structural similarities, in that they are five helical bundle cytokines. Additionally, binding to their respective cognate receptors leads to activation of distinct and shared signaling pathways, resulting in both unique and overlapping biological responses (7).

1.1.1.1 Type I IFNs Type I IFNs were the first IFNs characterized, based on their ability to interfere with viral infection. IFNs-α and -β are produced by many cell types and their receptor, the IFNAR complex, is likewise ubiquitously expressed on all cells. The IFNAR complex is made up of two trans-membrane subunits, IFNAR1 and IFNAR2. IFNAR2 is the high-affinity subunit that initially binds type I IFNs, leading to IFNAR1 engagement and subsequent IFN signaling. While IFNs-α/β induce an antiviral state in a cell, they may also induce growth inhibition, apoptosis and regulate immune responses in different cell types. IFN-β signaling can exacerbate inflammation in certain bacterial infections, yet exerts protective effects during fungal infections or infection with protozoa (8-10). IFN-β signaling can also exacerbate sepsis, mediated by the release of the inflammatory mediator high mobility group box 1 (HMGB1) via activation of IFNAR1, and blockade of IFNAR signaling reduces this effect (11). Type I IFNs promote natural killer (NK) cell responses to viral infection (12-14), B cell survival and humoral immunity (15, 16), and are important for the cross-priming of T cells (17, 18). Additional evidence for the importance of endogenous type I IFNs in vivo has been identified with IFNAR null mice. Type I IFNs are required to support normal hematopoietic stem cell (HSC) growth and maintenance, as IFNAR null mice have reduced total HSCs (19). Cells of myeloid lineage, including macrophages and dendritic cells (DCs), require endogenous type I IFN signaling to regulate the immune response to pathogens and elicit activation of T cells (20-23). In different autoimmune diseases, type I IFNs can have opposing effects. While protective or therapeutic in central nervous system (CNS) autoimmunity, type I IFNs are associated with negative outcomes in systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) (24). IFN-β is especially important in the CNS for protection from CNS-tropic viral infections and during autoimmunity, as IFN-α is not present in the CNS and IFN-β is used as a therapy in MS (25, 26). Conditional deletion of IFNAR1 on myeloid cells led to exacerbated CNS autoimmunity in a murine model of MS, experimental autoimmune encephalomyelitis (EAE). This revealed an essential protective role for type I IFNs, specifically IFN-β, in these cells, whereas the deletion of IFNAR1 on T or B cells did not exacerbate disease (27). Therefore, even though the IFNAR complex is expressed on all cells, the regulation of IFN production and cell-specific modulation of IFN-induced signal transduction may be different for the type I IFN subtypes. The effects of

IFNs, specifically on T cells and DCs and in the context of autoimmunity, will be discussed in detail later.

1.1.1.2 Type II and III IFNs The type II IFN, IFN-γ, is produced mainly by lymphocytes during an adaptive immune response. IFN-γ can be produced in response to type I IFN signals by CD8+ T cells, CD4+ Th1 cells, γδ T cells, innate lymphoid cells (ILCs), NK cells, and NKT cells. IFN-γ is also important for responses to viral infections, to intracellular bacterial infection, for tumor cell elimination, and can be anti-inflammatory in type 2 immune responses such as allergy and asthma (28). Whereas type I and type III IFNs signal as monomers, IFN-γ signals as a homodimer and binds a complex composed of two high-affinity IFNGR1 chains and two low-affinity IFNGR2 chains (7). The family of type III IFNs contains 4 members in humans (IFNλ1-4) and two genes encode IFN-λ in mice. Type III IFNs, though similar to type I IFNs in the signaling events they invoke, bind a receptor complex composed of a dedicated IFNLR1 chain, and a component of the IL-10 receptor, IL10R2, which is also utilized by IL-10, IL-22 and IL-26 (6). Type III IFNs are unique in that their effects are induced in a tissue-specific manner, based on where the Type III IFN receptor complex is expressed (29). Even though type I and type III IFNs are induced in response to viral infections, the type III IFNs are thought to be expressed in areas that are at a higher risk of infection. The type III IFN receptor is mainly restricted to epithelial cells in mucosal barriers such as the lung and the gastrointestinal tract (30, 31). Given the expression pattern of the IFNLR complex, the type III IFNs are thought to have evolved to offer immediate protection in barrier tissues while preventing systemic inflammatory responses induced by type I IFN signaling (6).

1.1.2 Type I IFN induction and signaling

Type I IFNs are induced upon recognition of bacterial or viral elements by pathogen recognition receptors (PRRs). PRRs may be expressed on the cell surface, in the cytoplasm, and endosomally. Additionally, type I IFNs can be produced in response to different cytokines such as tumor necrosis factor (TNF)-α (32, 33). After PRR ligation, a complex of transcription factors forms that includes interferon regulatory factors (IRFs), nuclear factor -κB (NF-κB) and c-

Jun/ATF2 (AP-1) (34). This leads to transcription of type I IFNs. Not only are IFNs produced in response to microbial detection, but they are also constitutively expressed, to regulate different components of innate and adaptive immune responses, and to ensure a rapid antiviral response. The basal production of IFNs has recently been proposed as induced by commensal microbiota (35, 36) and can be amplified by immunoreceptor tyrosine associated motif (ITAM) binding to endogenous ligands (37, 38). The antiviral IFN response is rapid and robust, and requires low levels of IFNs to be induced, perhaps as a consequence of basal expression of IFNAR, Jak1, Tyk2, STAT1, STAT2 and IRF9 (39). It has been suggested that immune cells respond to low levels of IFNs due to their basal expression of STAT1 and IRF9 (40). In contrast, the antiproliferative effects of IFNs are largely cell-type specific and require much higher levels of IFNs. Further, whereas low density cell surface IFNAR expression is sufficient for an antiviral response, higher receptor density is required for a growth inhibitory responses to IFN (41). In addition, there is accumulating evidence that differences in the binding affinities of IFN-αs and IFN-β and cell surface receptor stability influence the profile of IFN-inducible genes (42). IFN- β has the highest affinity for both IFNAR1 and IFNAR2, and IFN-αs bind IFNAR1 with relatively low affinity (43-45). Several differential effects of IFN-α and IFN-β have been shown by studies involving mutating different IFNs and receptor components. Specific mutations in IFNAR2 rendered cells unresponsive to IFN-α, while partially responsive to IFN-β, indicating an absolute requirement of IFNAR2 for IFN-α signal transduction (46). Studies with different IFN-α subtypes and IFN-β have resulted in the identification of specific amino acid residues on the surface of the IFNs associated with directly contacting the extracellular regions of IFNAR1 and IFN AR2, thereby activating the receptor complex (47-50). Engagement of the IFNAR complex by an IFN leads to stabilization of the ternary complex and activation of the kinases associated with each receptor chain – Tyk2 for IFNAR1 and Jak1 for IFNAR2. Notably, the IFNAR chains have no intrinsic kinase ability, and rely on the kinases associated with each chain for downstream signaling (51). Activated Jak1 and Tyk2 phosphorylate specific tyrosine residues on the intracellular regions of IFNAR1 and IFNAR2, which serve as docking sites for the cytoplasmic transcription factors signal transducer and activators of transcription, STATs. These, in turn, are then phosphorylated by Jak1 and Tyk2, resulting in their dissociation from the receptor subunits and dimerization (52). Phosphorylated STATs dimerize to form STAT1:1 and STAT3:3 homodimers or STAT1:2 and STAT1:3

6 heterodimers, or may associate with non-STAT molecules, e.g. Crk-like protein (CrkL) (STAT5:CrkL) (53) and IRF-9 (STAT1:STAT2: IRF-9 (ISGF3)) (54). The interferon-stimulated gene factor 3 (ISGF3) complex binds to interferon sensitive response elements (ISRE) that are present in the promoter regions of IFN stimulated genes (ISG), driving production of proteins associated with an antiviral state (55). STAT1:1, STAT3:3 and STAT5:CrkL complexes bind gamma activated sequences (GAS) (2). Other STAT homo- and heterodimers can be activated by IFNAR signaling. These include STAT2:3, STAT4:4, STAT1:4, STAT1:5, STAT5:5, and STAT5:6 (56). In addition to the JAK/STAT pathway, type I IFNs can activate a number of other signaling cascades that lead to regulation of proliferation, cell activation and differentiation. These include the mitogen-activated protein kinase (MAPK), PI3-Kinase (PI3K), protein kinase C (PKC), and mammalian target of rapamycin (mTOR) pathways. MAPK pathways can be segregated into 3 branches – the p38 MAPK pathway, the extracellular regulated kinase (ERK) pathway and the c-Jun NH2-terminal kinase (JNK) pathway (56). IFNAR engagement leads to activation of the p38 MAPK by the activation of Rac1 and other small G-proteins. Activation of p38 MAPK is essential for type I IFN mediated induction of apoptosis and antiproliferative effects on leukemic cell lines and in normal hematopoiesis (57, 58). Induction of these growth- inhibitory responses by IFN-activated p38 MAPK may be mediated by the Schlafen proteins (59). ERK activation by IFNAR signaling leads to regulation of gene expression, and can mediate IFN-α induced apoptosis (60, 61). Activation of JNK by IFNAR signaling is important for induction of apoptosis and pro-apoptotic activities (61). It has been proposed that activation of PKC-θ in human T cells may be important for activation of the JNK pathway (62). Initiation of translation of IFN-induced genes is regulated by mTOR. IFNAR signaling activates PI3K (63), leading to the activation of the mTOR complex and inactivation of the translational repressor 4E-BP1, and initiation of mRNA translation (64, 65). The growth-inhibitory effects of type I IFNs can also be mediated through CrkL antagonism of the Ras pathway (66). Finally, in addition to the pathways indicated above, there is evidence for activation of NFκB by type I IFN signaling (67).

1.1.3 Regulation of type I IFN responses

IFN responses may be regulated at multiple levels. IFN signaling can be repressed by a number of negative regulators, can be increased or decreased by modulation of receptor expression, and can be regulated at the transcriptional level by the expression of different STAT molecules which can be influenced by various cytokines, including the IFNs. Type I IFNs can activate all of the known STATs and the type of STAT dimers that are engaged can dictate the response induced. Antiviral responses are associated mainly with STAT1:STAT2 heterodimers in combination with IRF9, whereas STAT1:STAT1 dimers drive inflammatory responses and STAT3:STAT3 dimers drive anti-inflammatory responses (39). Additionally, different STATs can be activated through type I IFN stimulation in various subsets of immune cells, including B cells, monocytes and T cells (68). STATs are also activated by signaling invoked by other cytokines, which may augment IFN signaling and promote or inhibit inflammatory responses (69). Suppressor of cytokine signaling (SOCS) proteins and the ubiquitin carboxy-terminal hydrolase (USP18) are induced by type I IFN signaling as part of a negative feedback mechanism that serves to dampen type I IFN responses (70, 71). SOCS1 specifically competes with Tyk2 for binding to IFNAR1 (72) and USP18 can displace Jak1 from IFNAR2 (73). Negative regulation of IFN responses can also occur through modulation of IFNAR expression. Upon ligation, the IFNAR complex is down-regulated or internalized (74, 75). Other signals from different cytokines and growth factors can also modulate IFNAR expression. Stress- activated protein kinase p38 can phosphorylate an IFNAR1 serine residue that targets the receptor for ubiquitination, leading to a reduction in type I IFN signaling (76). Finally, the protein inhibitor of activated STAT (PIAS) family of proteins can negatively regulate STAT functions by blocking STAT1- and STAT3- DNA binding activity, leading to repression of STAT1- and STAT3- activated gene expression (77).

1.2 CD4+ T helper cells CD4+ T cells exhibit multifaceted roles in an adaptive immune response. They are instrumental in eliminating infections and cancerous cells, in part by activation of CD8+ T cells, and also by producing cytokines and chemokines associated with the recruitment and activation of innate immune cells (78). CD4+ T cells can also provide help for B cells in generating an antibody response. While many functions of CD4+ T cells support immune activation and

8 clearance of infection, aberrant CD4+ T cell responses to self can lead to autoimmunity. Additionally, CD4+ regulatory T cells (Tregs) are important for regulating homeostatic immune function, immune responses to tumors and controlling autoimmunity (78). In Chapter 3 of this thesis, we show that IFN-β exerts immunoregulatory effects on the Th17 subset of CD4+ helper T cells. The following serves to summarize what is known about the Th1, Th2, Th17 and Treg subsets and how IFN-β regulates these T cells in the context of an immune response.

1.2.1 CD4+ T helper subsets

The original characterization of CD4+ cell subsets was based on their ability to provide B cell help in different contexts, rather than based on the cytokines they produced (79-81). The first study that defined the differences in cytokine production between Th1 and Th2 cells was by Mosmann and Coffman in 1986 (82). Their seminal work identified the Th1 subset and the Th2 subset from a panel of T cell clones, based on differences in cytokine production in response to antigen specific stimulation. As more was understood about CD4+ T cells and their roles in adaptive immunity, the classification of CD4 helper subsets expanded to include regulatory T cells (Tregs), Th17 cells, Th9 cells, Th22 cells and T follicular helper cells (Tfh) (78). CD4+ T cells are thought to differentiate into their different lineages in a two-phase process. First, the activation of the T cell receptor (TCR) leads to induction of transcription factors which begin to direct the lineage commitment. Then, a polarization stage follows, whereby cytokines drive further expression of the key factors that regulate each lineage, and the cells become differentiated (83). Figure 1.1 provides an overview of CD4+ polarization into the different subtypes of Th1, Th2, Th17 and Treg, noting the cytokines that drive the lineage, the transcription factors that are required for commitment, and the effector cytokines produced by each lineage. The roles that CD4+ T cells have in immune responses are diverse and ever- expanding. While immune responses largely involve an orchestration of several CD4+ T helper cell subsets, autoimmunity is mainly attributed to the Th1, Th17 and Treg subsets and, as such, their differentiation, activation, and role in immune responses will be the focus of this section.

Figure 1.1 Subtypes of CD4+ T cells. Polarization of naïve CD4+ T cells in response to cytokine cues, into the Th1, Th2, Th17 and Treg lineages. Cytokines that induce each lineage, the transcription factors that regulate and sustain the lineages, as well as important cytokine receptors and signature cytokines produced by each lineage are indicated.

1.2.1.1 Th1 cells Th1 cells were identified as IFN-γ producing cells that are critical for invoking CD8+ T cell responses to intracellular bacteria and viruses. The key finding that IL-12 was the driving cytokine in Th1 induction was by Murphy and colleagues in 1993. They demonstrated that the incorporation of Listeria monocytogenes in macrophage-T cell co-cultures induced a Th1 phenotype (IFN-γ production) in the CD4+ T cells, which was directly linked to macrophage production of IL-12 (84). Subsequent to that finding, it was shown that IL-12 was the key cytokine that induced STAT4 phosphorylation, which led to the differentiation of Th1 cells (85). It was later shown that the transcription factor T-bet drives Th1 differentiation and production of IFN-γ. This work also revealed that T-bet expression could repress the Th2 program and the related hallmark cytokines, IL-4 and IL-5 (86). T-bet is the master regulator of Th1 programming and it is capable of inducing its own expression, the expression of the IL-12Rβ2 chain, and the initiation of IFN-γ transcription (87). IFN-γ produced by Th1 cells serves to further amplify the Th1 lineage by inducing STAT1 in activated macrophages, driving IL-12 production which can feed back on the Th1 cells (88). The typical Th1 cytokines are IFN-γ and IL-2, but Th1 cells can also produce TNF-α, lymphotoxin, and granulocyte macrophage colony stimulating factor (GM-CSF) (89). Commitment to the Th1 lineage is sustained by STAT4, but also by STAT1. STAT4 is activated in response to IL-12 signals through the IL-12R mediated by Jak2/Tyk2, leading to STAT4 phosphorylation and transcription of IFN-γ (90). STAT1 is part of a regulatory loop that stabilizes Th1 commitment, initially being induced by IFN-γ signaling, which induces T-bet expression and further IFN-γ transcription. Th1 cells are important for the clearance of viral and bacterial infections, but also may have detrimental effects in regard to induction and amplification of autoimmunity. Certainly, Th1 cells have been implicated in numerous autoimmune diseases, such as rheumatoid arthritis (RA), MS, Type 1 diabetes and SLE (89).

1.2.1.2 Th2 cells At the same time that Th1 cells were characterized, the Th2 subset was defined as producing IL-3, IL-4 and IL-5 (91). Th2 cells are important for responses to parasites and are also involved in allergic inflammatory diseases and asthma. IL-4, one of the hallmark Th2

11 cytokines, is also critical for inducing the Th2 program (92, 93). Signaling through the IL-4 receptor activates STAT6 which binds to and upregulates GATA3 (94), the transcription factor controlling Th2 differentiation (95, 96). GATA3 binds the promoter regions of the IL-5 and IL- 13 genes, activating their expression (97, 98), and directly influences IL-4 expression by binding the IL-4 gene enhancer (99). GATA3 expression also inhibits Th1 differentiation (100). The importance of STAT6 in Th2 cells is highlighted by a study where ectopic expression of activated STAT6 could induce GATA3 and Th2 cytokines in CD4+ Th1 cells (101). In addition to STAT6 and GATA3, STAT5 is required for the lineage commitment to Th2 cells. The Th2 phenotype can be driven in vitro by IL-2, which induces STAT5-driven IL-4Rα expression, IL-4 production and GATA3 expression (102-104). On the other hand, STAT5 can be activated in vivo by IL-2, IL-7 and thymic stromal lymphopoeitin (TSLP) (105).

1.2.1.3 Th17 cells The discovery of Th17 cells was led by several groups in 2003, using various mouse models of autoimmunity. These models were originally thought to be driven by Th1 cells, since blockade of the IL-12 receptor or IFN-γ deficiency was protective in disease (106, 107). IL-12 is a heterodimer of two subunits, p35 and p40, and the p40 subunit is shared with IL-23. IL-23 is composed of IL-23p19 and IL-12p40, and mice deficient in IL-23p19 were shown to be resistant to EAE, where IL-12p35 mice were not (108). In another study, it was shown that mice null for IL-23 were resistant to collagen induced arthritis, related to the absence of CD4+ IL-17 producing T cells (109). This suggested that IL-23 may be driving autoreactive T cells, rather than IL-12. Finally, in 2005 it was shown that Th17 cells are distinct from Th1 and Th2 CD4 lineages and do not share precursor intermediates (110, 111). Th17 cells produce IL-17A, a pro- inflammatory cytokine, as well as IL-17F, IL-21 and IL-22 (112). More recently it was found that Th17 cells can also produce GM-CSF, which has been shown to be pathogenic in models of EAE (113, 114). Differentiation of murine Th17 cells is inhibited by the Th1 and Th2 cytokines IFN-γ and IL-4, respectively (111) and promoted by IL-6 and transforming growth factor (TGF)-β (115, 116). IL-6 drives the expression of IL-21, which acts to drive its own expression and upregulate expression of the IL-23 receptor. Even though IL-23 was one of the first factors identified in driving the Th17 lineage, it is now thought to be a factor that promotes Th17

12 survival and maintenance, and may contribute to the pathogenicity of Th17 cells in autoimmunity (117, 118). IL-21 expression, together with TGF-β and IL-23, induce STAT3 and the transcription factor RORγT, to drive expression of IL-17 in the murine system (119). RORγT expression is induced by TGF-β at low concentrations, while TGF-β at higher concentrations leads to induction of the transcription factor Foxp3 and subsequently lineage polarization towards Tregs (120). While TGF-β was only recently reported to be necessary for the generation of Th17 cells in humans (121), Th17 lineage commitment in both humans and mice requires RORγT (122) and STAT3 (123, 124). RORγT is the master regulator of the Th17 lineage, promoting transcription of IL-17. Lack of RORγT expression leads to a deficiency in Th17 cells (122). The Th17 lineage is also stabilized by STAT3, as its expression maintains RORγT expression. STAT3-deficient CD4+ T cells do not polarize to the Th17 lineage in the presence of TGF-β, IL-21 and IL-23, but rather begin to express Foxp3, suggestive of its importance for maintaining the Th17/Treg balance (125). IL-6 promotes the expression of the IL-1 receptor, and IL-1β is necessary to promote expression of the transcription factor IRF4, which further enhances expression of RORγT (126). IL-1β also invokes mTOR signaling, which promotes the expansion of Th17 cells (127). Even though Th17 cells were defined in autoimmune models, a protective role for these cells has been identified through study of the human immunodeficiency, Job’s disease – where mutations in STAT3 lead to a deficiency in Th17 cells and recurring fungal and bacterial infections in mucosal tissues (128).

1.2.1.4 Regulatory T cells CD4+ Tregs occur naturally and are also inducible. Natural (n)Tregs develop in the thymus and are not derived from the same CD4+ T cells that polarize into other T helper lineages (129). Inducible (i)Tregs develop in the periphery from naïve CD4+ T cells upon exposure to antigen and cytokine stimulation. Regulatory CD4+ T cells were first identified by Sakaguchi and colleagues, who showed that peripheral CD4+ CD25+ cells were essential for preventing autoimmunity and limiting graft rejection (130). The identification of Foxp3 as the hallmark transcription factor driving this peripheral population of regulatory T cells came from studies of the Scurfy mouse and patients with immune dysregulation, polyendocrinopathy, enteropathy, X-linked (IPEX) syndrome. Scurfy mice have scaly, ruffled skin, enlarged spleens and lymph nodes and IPEX patients have severe inflammation, neonatal diabetes mellitus,

13 infections and IPEX is usually lethal in infancy. In both cases it was found that mutations in Foxp3 led to the disease phenotype (131-133). It was later shown that Foxp3 was expressed by CD4+CD25+ cells and transfer of these cells into Foxp3 deficient mice could revert the autoimmune phenotype (134) and ectopic Foxp3 expression induced naïve CD4+ T cells to have a regulatory phenotype (135), highlighting the importance of Foxp3 in driving the Treg lineage. iTregs differentiate from naïve CD4+ T cells in the presence of TGF-β (136). TGF-β signaling leads to Smad3 and nuclear factor of activated T cells (NFAT) binding to the Foxp3 enhancer to drive Foxp3 expression (137). Additionally, IL-2 has been shown to play a role in TGF-β induction of Foxp3 (138). This may be due to IL-2 activation of STAT5, which stabilizes the Treg lineage by binding to the Foxp3 gene and inducing its expression (139, 140). Tregs, while protective in autoimmunity (141) and required for limiting inflammatory responses (142), can have a detrimental role in the detection and clearance of tumors (143). Tregs secrete IL-10 which can act on surrounding cells to limit inflammation (144). Tregs can also produce granzyme B, IL-9, TGF-β and IL-35, which may exert immunosuppressive functions (145). Tregs that are deficient in IL-10 production fail to control inflammatory responses in a colitis model in mice, leading to gut inflammation (146). The tumor microenvironment may also promote IL-10 production by Tregs, leading to immune suppression and escape of immune recognition (147). Suppressive functions of Tregs may also occur in a contact-dependent fashion, whereby Treg-expressed cytotoxic T lymphocyte associated protein 4 (CTLA-4) binding to CD80 or CD86 can induce production of the immunosuppressive molecule indoleamine 2,3-deoxygenase (IDO) by DCs and Treg LAG-3 binding to MHCII on target DCs can inhibit their maturation and function (148).

1.2.2 Activation of T cells, TCR signaling & T cell migration

Naïve CD4+ T cells encounter antigen-bearing DCs or other antigen presenting cells (APC)s in secondary lymphoid organs such as the spleen or lymph nodes (LN). Upon interaction with the APC, the T cell receives several signals from the APC – first, an antigenic stimulus through the T cell receptor (TCR) and major histocompatibility complex type II (MHCII) interaction, second, a co-stimulatory signal through CD28 on the T cell and a B7 family molecule on the APC (CD80 or CD86) (149, 150). This section will summarize the

14 signaling events downstream of the TCR after activation and how T cells migrate to secondary lymphoid organs and sites of inflammation.

1.2.2.1 Activation of T cells and TCR signaling Upon TCR ligation with the cognate antigen in the context of MHCII, the TCR signaling cascade is initiated. Figure 1.2 provides an overview of the pathways invoked by activation of the TCR. Co-stimulatory signals are supplied the interactions of CD80/CD86 on the APC with CD28 on the T cell. Additional co-stimulatory signals can be transmitted through CD40L and inducible T cell co-stimulator (ICOS) on the T cell by binding to CD40 and ICOSL on the APC (151). These co-stimulatory signals feed into the signaling cascade described below. Signals are not transduced by the TCR as it possesses no intrinsic kinase activity, therefore it forms a complex with the CD3 chains and the CD4 co-receptor molecule (152). CD4 binds MHCII to enhance TCR recognition of the peptide in the context of MHCII and is also associated with the membrane proximal Src-family kinase, LCK. Contact of CD4 with the peptide:MHCII complex brings LCK in close proximity to the CD3 complex and initiates LCK phosphorylation of the ITAM motifs in the CD3 γ, δ, ε, and ζ chains (153). Phosphorylated CD3 ζ chains recruit and activate the zeta chain-associated protein kinase of 70 kDa (ZAP70) (154), which then phosphorylates the scaffold protein linker for activated T cells (LAT) (155), and subsequently, IL-2-inducible T cell kinase (ITK) and Src homology 2-domain-containing leukocyte protein of 76 kDa (SLP76) (156). ITK then activates phosphoinositide-specifc phospholipase C (PLC)γ1.

Figure 1.2 T cell receptor signaling cascade. Representation of the signaling pathways downstream of TCR ligation.

Activated PLCγ1 continues the cascade by hydrolyzing the membrane component phosphotidylinositol biphosphate (PIP2) into the signaling intermediates diacylglycerol (DAG) and inositol triphosphate (IP3), which feed into several downstream pathways (157). The three main pathways are the Ca2+/Calcineurin pathway, the MAPK pathway and the NFκB pathway which induce gene expression, cytoskeletal re-arrangement and subsequent differentiation of the T cell (157). When components of the TCR pathway are perturbed, the balance between different T helper subsets can be skewed. For instance, the deletion of IL-2-inducible T cell kinase, ITK, skews CD4 T cells to polarize toward a Foxp3-expressing Treg lineage under Th17 polarizing conditions (158). Blocking of NFAT (downstream of the Ca2+/Calcineurin pathway) interactions with Foxp3 leads to inhibition of the Treg program and increased T helper cytokine production (IL-2, IFN-γ, IL-17) in response to TCR stimulation (159). The signal strength from the TCR can regulate the different T helper lineages after activation – a strong signal can induce Th1 responses, and weak signals can induce Th2 and Treg responses (160). Interestingly, the Treg/Th balance may also be controlled by NFκB signaling and TCR signal strength together, as strong TCR signals lead to cytokine production and NFκB activation, which, in turn, can inhibit Foxp3 activation of the Treg program (161). As with other signaling cascades, TCR signaling can be negatively regulated by several mechanisms: LCK can be inactivated by phosphorylation of the inhibitory tyrosine 505 by the C-terminal src kinase (CSK/CD45) (162); the SH2 domain-containing protein-tyrosine phosphatase (SHP)-1 can also inactivate LCK and ZAP70 (163, 164); CTLA-4 binding to CD80 or CD86 leads to recruitment of SHP-1 and other phosphatases (165); Programmed cell death protein 1 (PD-1) can bind it’s ligand, PD-L1, on the surface of APCs leading to inhibition of TCR signaling by recruitment of SHP-1 (166).

1.2.2.2 Migration of T cells Naïve T cells circulate through secondary lymphoid organs (SLO), scanning APCs for antigen:MHC complexes that can be recognized by their TCR. However, to gain entry into the SLO from the bloodstream requires an orchestration of receptors and molecules that drive cell arrest and extravasation into the SLO. The high endothelial venules (HEV) are post-capillary venules in SLOs that constitutively express receptors and homing molecules to trigger cell arrest. Specifically, naïve CD4+ T cells express CD62L which binds a family of molecules

17 known as peripheral node addresin (PNAd)s to slow the T cell to a ‘roll’ (167). At this phase the chemokine CCL21, expressed on the HEV surface by heparan sulfate, can bind to its receptor, CCR7, on the naïve T cell (168). This interaction leads to the activation of lymphocyte function associated antigen 1 (LFA1), which binds to intercellular adhesion molecule (ICAM1) (169). This interaction stops the T cell from ‘rolling’, allowing for extravasation into the SLO. Once in the SLO, the T cell can migrate throughout the T cell zone, mediated by further signaling through CCR7 by another ligand, CCL19. Notably, mice lacking CCR7 or the ligands CCL19 and CCL21, have significantly reduced numbers of naïve T cells in their LNs (170, 171). Alternatively, T cells can migrate through the lymphatics to adjoining LNs. In the T cell zone the T cell is arrested, due to desensitization of CCR7 by CCL19 (172, 173), and scans DCs for its cognate antigen (174). During an inflammatory response, naïve T cells may respond to inflamed or ‘reactive’ LNs that express CCL2 or TNF-α either within the LN or in the surrounding tissue (175-177). Reactive LNs also express CXCL10 and CXCL9, which position CXCR3+ effector T cells for activation by DCs (178). If activated, the T cell remains in the T cell zone in contact with the DC, where it begins to proliferate and further differentiation occurs. Another ligand:receptor interaction is important at this stage: sphingosine-1-phosphate (S1P) binding the S1P receptor triggers lymphocyte egress from the SLO (179). As such, S1P is expressed mainly in the afferent and efferent lymphatics, where activated cells that begin to express the S1P receptor can respond to S1P signals and exit the lymph nodes (180). In order to counteract S1P signals, recently activated T cells express CD69, which prevents the expression of the S1P receptor and allows for appropriate activation of the T cell before egress into the periphery (181). Chemokine:chemokine receptor interactions are critical for the migration of T cells and organization of other lymphocytes in lymphoid tissues, and also for inducing migration of different CD4+ subsets to sites of inflammation. Distinct chemokine receptors are expressed on different subsets of CD4+ T cells and this may allow for responses to chemokine cues in specific compartments where these cells are required (182). As mentioned above, all naïve CD4+ T cells express CCR7 to draw them toward SLOs where they can be activated by DCs or other APCs. After activation and differentiation, Th1 cells express CXCR3 and CCR5, Th2 cells express CCR4 and CCR8, Th17 cells express CCR6, and Tregs express a variety of different chemokine receptors which reflects their requirement in many tissues to dampen immune responses (183,

184). Expression of different chemokine receptors on T cell subsets and their potential roles in immunity is summarized in Table 1.1.

Table 1.1 Chemokine receptors and S1P receptors expressed by different T cell subsets that influence their migration Cell types discussed in this thesis are highlighted in bold font Receptor T cell expression Key Functions CXCR1 CD8+ T eff (some) Mainly neutrophil trafficking CXCR2 CD8+ T (some) Mainly neutrophil trafficking, some B cell lymphopoiesis CXCR3 Th1, CD8+, Tfh, Treg Th1 adaptive immunity CXCR4 All T cells Hematopoiesis, bone marrow homing CXCR5 Tfh, CD8 T cell trafficking to B cell areas CXCR6 Th1, Th17, γδT, NKT Innate lymphoid cell function, adaptive immune responses CCR1 Th1 Innate/adaptive immune responses CCR2 Th1 Monocyte trafficking, Th1 responses CCR3 Th2 Th2 responses CCR4 Th2, Treg (skin homing), Th17 Homing of T cells to skin and lung, Th2 responses CCR5 Th1, CD8+ Th1 responses CCR6 Th17, γδT, Treg, Tfh Th17 responses CCR7 Naïve T, memory T cells T cell migration in & out of SLOs CCR8 Th2, Treg, γδT Skin immune surveillance, Th2 responses CCR9 Gut homing T, thymocytes T cell homing to gut, GALT development CCR10 Skin homing T cells Immune surveillance in skin CX3CR1 Th1, CD8+ T, γδT Th1 responses S1PR1 All subsets Chemotaxis, differentiation, effector responses S1PR4 All subsets Chemotaxis, inhibition of differentiation & effector responses

Perturbations in chemokine receptor expression can alter the T cell phenotype affecting immune responses. For instance, Treg expression of CXCR3 is critical for controlling EAE, as mice null for CXCR3 have increased disease scores, in part due to lack of Treg migration into the CNS (185). Tregs, similar to Th17 cells, can also express CCR6, dependent on STAT3 expression in Tregs. CCR6-deficient Tregs fail to migrate to the gut to suppress inflammation, indicative of a role for CCR6 in Treg function in vivo (186). Similarly, CCR6 deficient Th17 cells are impaired in their ability to induce EAE, and fewer CCR6 deficient Tregs migrate to the CNS during EAE (187). Tregs therefore utilize the same chemokine receptors as different T helper subsets to migrate to tissues to suppress immune responses.

1.2.3 IFN effects on T cells

Constitutive expression of IFN-β is required by T cells for tonic signaling to maintain normal T cell levels and responses to pathogens (40). Among the first non antiviral functions of type I IFNs identified were antiproliferative and growth inhibitory effects on lymphocytes (188) and this was later shown to be dependent on TCR components in T cells (189). Exogenous IFN- α protects against early apoptosis upon TCR engagement of human naïve CD4+ T cells, but later upregulation of surface Fas expression suggests increased sensitivity to antigen-induced cell death (190). IFN-α stimulation can also upregulate expression of the immunoregulatory cytokine IL-10 in human CD4+ T cells in concert with TCR stimulation through CD28 (191). IFN-β will promote CCL2, CCL7 and CXCL10 expression, thereby enabling chemotaxis of T cells expressing CCR2 and CXCR3 (192). IFN-β may also modulate T cell migration by upregulation of CD69 and inhibition of the response to S1P, resulting in decreased T cell migration out of draining LNs (181). There is evidence that type I IFNs regulate CD4+ T cell differentiation into the different lineages. Th1 cells are both positively and negatively affected by type I IFNs. Initially it was observed that human T cells treated with type I IFNs led to STAT4 phosphorylation, driving Th1 polarization, however, murine T cells did not respond in the same way (193). It is generally accepted that Th1 responses are supported by type I IFNs, as IFNs will stimulate DCs to produce IL-12 which drives the Th1 lineage (194). However, in a mouse model of persistent viral infection, type I IFN inhibits Th1 responses and this effect can be reversed by blocking

21 type I IFN signaling (195). In another study, treatment of CD4+ Th1 cells with IFN-β led to activation of STAT1 and decreases in STAT4; notably, this was in the absence of APCs. This study also showed that IFN-β-treated Th1 cells failed to induce EAE in lymphocyte-deficient Rag1-/- mice (196). In Ifnar-/- mice, expression of STAT1 is impaired and the balance shifts to STAT4 activation and Th1 cell proliferation (197). Treatment of mice with IFN-β during acute influenza A infection skews the CD4+ T cell response to Th1 and diminishes the Th2 response (198). These studies suggest apparently conflicting roles for type I IFNs in regulating the Th1 lineage, that may be in part explained by differences in the human and murine systems and by differences in the cytokine milieu during different inflammatory responses. Th2 and Th17 lineages are negatively regulated by type I IFNs (18). Type I IFNs inhibit Th2 polarization and release of Th2-related cytokines from human T cells (199, 200). More recently it has been shown that IL-5 transcription in Th2 cells is blocked by IFN-β treatment in a STAT4-dependent manner (201). Different studies in mice and humans have demonstrated that IFN-β will inhibit Th17 polarization, IL-17 production, and skew the T helper response in EAE (202-205). Dependent on the immune circumstance, Treg numbers and function can be either enhanced or inhibited by type I IFNs. In mice with T cell-mediated colitis, type I IFNs regulate intestinal homeostasis by maintaining Foxp3 expression on Tregs in the colon (206). IFNAR signaling has also been shown to be required for optimal Treg responses, mediated by a requirement of STAT5 activation by type I IFN (207). However, Tregs can also be inhibited by type I IFN, shown in a model of lymphocytic choriomeningitis virus (LCMV) infection, where Tregs are suppressed to allow for optimal T helper clearance of the infection (208). Type I IFNs may also have a suppressive role on Tregs in cancer, where gene delivery of IFN-α reduced the frequency of intra-tumoral Tregs (209). On the other hand, in MS patients and in the EAE mouse model of MS, IFN-β treatment improves the frequency and suppressive function of Tregs (210). Much of the study of IFN-β effects on Th17 and Treg lineages has been in patients with relapsing and remitting MS and in the EAE model, and these effects will be described later.

1.3 Dendritic cells Dendritic cells (DCs) have a critical role in initiating immune responses by bridging the innate and adaptive immune systems. DCs constantly sample tissue and blood antigens within lymphoid and non-lymphoid tissues during both homeostasis and during inflammation. These

22 phagocytic cells are unique in their ability to induce an adaptive immune response for several key reasons. DCs are able to sense a variety of ‘danger signals’ through cell-surface and intracellulary expressed PRRs, including the toll-like receptors (TLRs) (211). Once activated, DCs process antigens and present them to CD8+ T cells in the context of MHC class I molecules and to CD4+ T cells in the context of MHC class II molecules. Certain types of DCs can also ‘cross-present’ extracellularly derived antigens in the context of MHCI, when traditionally, extracellularly derived antigens would be presented by MHCII (212). These activated, antigen- loaded DCs express chemokine receptors and co-stimulatory molecules, thereby enabling their migration to T cell zones within lymphoid tissues where they can interact with and prime naïve T cells to induce an immune response (211).

1.3.1 Types of DCs

The original classification of DCs in mice was by cell surface marker expression (213- 215). With advances in multicolour flow cytometry, it became evident that these surface markers are expressed by multiple DC subsets (211). As such, DC classification has moved to a more transcription factor-centric approach, whereby the major lineages of classical (c)DCs and plasmacytoid (p)DCs are defined by the expression of specific transcription factors, and then on the basis of surface marker expression (216). Additionally, monocytes can give rise to DCs during inflammation; these are designated monocyte-derived (moDC). This system of DC classification allows for a better understanding of the different types of DCs invoked during different immune responses and provides context for their differential production of cytokines and differential ability to induce distinct helper T cell subsets. The classes of DCs described herein and their surface markers and defining transcription factors are outlined in Figure 1.3.

Figure 1.3 Classification of DC subsets in mice and humans. Surface marker expression, key transcription factors and types of immune responses each subset invokes are indicated.

1.3.1.1 cDCs In mice, cDCs are CD11c+ and MHCII+. However, they can also be identified by a number of other surface markers, depending on their location. Further cDC subset classification is based on the transcription factors Irf8 and Irf4. Irf8+ DCs are generally involved in immune responses to intracellular pathogens and type 1 immune responses (IFN-γ-inducing), whereas Irf4+ DCs represent a more heterogeneous population of DCs that can be involved in type 2 (IL- 4-inducing) and type 3 (IL-17-inducing) responses. Surface XCR1 and SIRPα expression are present on Irf8+ and Irf4+ cDCs, respectively (217). These markers are expressed independently of cDC location. Irf8+ cDCs are present in lymphoid tissues and are CD8+ XCR1+ in the spleen, while in the periphery, they may express CD24 and CD103. The Irf8+ subset of DCs also includes those that develop into pDCs. A specific mutation in Irf8 in mice and in humans leads to an ablation of the CD8a+ DC subset, leaving the pDC population intact (218, 219), while Irf8-/- mice are completely devoid of pDCs , and have significantly reduced CD8+ DCs which are impaired in their ability to activate T cells (220). Irf8+ cDCs are also differentially dependent on several other transcription factors. Batf3 expression is important for cross-presentation, antiviral responses and differentiation of non-lymphoid tissue CD103+ DCs (221, 222). Nfil3-/- mice lack CD8+ DCs but not pDCs or CD8- DCs, and are unable to cross-present antigen to CD8+ T cells (223). Id2 is required for epidermal DC (Langerhans cells, LC) development, as mice lacking Id2 are completely deficient in LCs and have a reduced contingent of splenic CD8+ DCs (224). Bcl6 is important for the differentiation of intestinal CD103+ CD11b- DCs (225). In humans, the most similar subset to the Irf8+ cDCs are CD141+ DCs, which also express XCR1, have the ability to cross-present antigen and can drive Th1 type responses (226). cDCs that are Irf4+ are more heterogeneous and may express CD4, CD11b, ESAM, CD103 and CX3CR1, and may be reliant on Notch2 or Klf4. Analysis of splenic DC subsets in Irf4-/- mice revealed an absence of CD4+ cDCs and slightly reduced numbers of pDCs, while CD8+ DC numbers were unaffected (227). Irf4+ CD8- (whether CD11b+ or CD11b-) cDCs tend to be primed for antigen presentation to CD4+ T cells (228), and this is dependent on Irf4 expression (229). CCR7-dependent migration of dermal DCs (CD11b+CD103+) from the skin to LNs is impaired in Irf4-/- mice, suggesting a role for Irf4 in promoting DC migration during

25 inflammation (230). Notch2+ CD11b+ cDCs are essential in inducing Th17 responses. This has been demonstrated using Citrobacter rodentium infection, a murine model for enteropathogenic Escherichia coli infection, where a conditional deletion of Notch2 in cDCs led to an inability to clear the infection, attributed to the lack of IL-23 production and induction of Th17 cells (231). In another study, the conditional deletion of Notch2 in cDCs led to decreased numbers of Th17 cells in mesenteric LNs (232). Together, these studies highlight a role for Irf4+ CD11b+ Notch2- dependent cDCs in type 3 immunity. Irf4+ cDCs are also implicated in type 2 immunity, supported by mouse studies of parasitic infections and a house dust mite (HDM) model of allergy. Depletion of CD11c+ DCs using a CD11c-DTR mouse results in compromised Th2 responses during Schistosoma infection (233). In the HDM allergy setting, a population of CD11b+FcεR1+ cDCs was required to take up and present antigen to induce Type 2 immunity (234). While depletion of CD11c+ DCs does not prescribe a specific subset of DCs, conditional deletion of Irf4 in cDCs led to mice that were deficient in the induction of lung Th2 responses, yet were able to effectively clear pulmonary viral infections. This study also showed that Th2-type stimuli could induce Irf4 expression in cDCs, and that Irf4 could target the type 2 cytokines IL-10 and IL-33 (235). Further study of the role of Irf4-dependent cDCs in type 2 immunity revealed that conditional deletion of the transcription factor Klf4 in CD11c+ cDCs leads to reduced Th2 responses both in Schistosoma infection and in the HDM allergy model, but does not affect the ability of these mice to clear a Citrobacter infection, suggesting that Th17 responses are intact (236). The human counterparts to the Irf4-dependent, CD11b+ cDCs, are the CD1c+ DCs, which are implicated in generating Th2 and Th17 responses to extracellular pathogens (226). A third subset of dermal-resident DCs exists in humans but not in mice, the CD14+ DCs, which are similar to monocytes and macrophages, but with distinctly higher expression of MHCII and CD11c (237, 238). These DCs can induce T cell help and isotype switching of B cells (237), but appear not to express CCR7 for homing to LNs (239). Human CD14+ DCs may be extravasated monocytes rather than DCs, given their resemblance to monocytes in terms of surface marker expression, transcriptome and function, as this extravasation of monocytes in homeostasis has been described in mice (240).

1.3.1.2 pDCs pDCs are major producers of type I IFNs in response to viral infections and can be defined by their expression of CD11c, B220, Siglec-H and Bst2 (mPDCA-1) in mice (216). Human pDCs do not express CD11c or Siglec-H, but can express CD4 and the IL-3 receptor, which has been shown to be important for maintaining human pDCs in vitro (241). pDCs develop fully in the bone marrow, are dispersed through the body via the blood to the lymphoid tissues in the steady state, but can migrate to non-lymphoid tissues and inflamed sites during infection or inflammation (242). While cDCs are generally considered to be the most potent inducers of T cell responses from naïve T cells, upon activation, pDCs gain the ability to stimulate T cells, albeit to a lesser extent than cDCs (242). As mentioned above, murine pDCs are dependent on Irf8 expression and Irf8-/- mice are completely deficient in pDCs. Additionally, murine pDCs rely on the transcription factor E2-2, as conditional deletion of this transcription factor from mature pDCs forces their conversion back to cDCs (243). E2-2 deletion in fetal liver cells used to reconstitute irradiated mice leads to a complete lack of pDCs in E2-2-/- recipients and E2-2 was also shown to activate Irf8 (244). FLT3 and FLT3L are required for pDC development and the lack of Flt3 signaling in mice results in lower frequencies of pDCs in the lymphoid tissues and bone marrow (245). E2-2 expression is triggered by FLT3L activation of STAT3 expression, and is repressed by GM-CSF activation of STAT5 and the E2-2 repressor, ID2 (246).

1.3.1.3 moDCs DCs can also arise from monocytes after migration into tissues during an inflammatory response. This occurs in both murine and human systems. Exposure of human monocytes to GM-CSF and IL-4 can produce DCs with cDC-like characteristics (247). Murine monocytes can differentiate into inflammatory DCs upon transfer into mice during inflammation (248). Monocytes differentiate from a bone marrow precursor, the common monocyte progenitor (cMoP), which expresses CD115 (M-CSFR) but not FLT3, and therefore does not give rise to cDCs or pDCs (249). The transcriptional program for commitment from cMoP to monocytes or macrophages has not yet been defined, so it is unclear what the molecular underpinnings of this differentiation are (216). Following LPS stimulation or bacterial activation, moDCs express DC- SIGN, that may influence this differentiation (250). Other studies have shown that moDCs have

27 some characteristics of cDCs, and are present within DC populations in the intestines (251, 252), spleen (232) and muscles (253) in the steady state.

1.3.2 Activation and migration of DCs

Activation of DCs can be mediated through PRR which are expressed on the surface of DCs, or inside the cell, in the cytosol or endosomes. These ‘danger’ signals trigger antigen uptake, processing and presentation on MHCII molecules. PRRs that induce DC activation may be TLRs, C-type lectin receptors (CLRs), nuclear oligomerization domain (NOD)-like receptors (NLRs), and retinoic acid-inducible gene (RIG)-I-like receptors (RLRs) (254). In addition to presentation of antigen in the context of MHCII, activated DCs also upregulate expression of co-stimulatory molecules, required for the successful activation of naïve CD4+ T cells. Migration of DCs is orchestrated by chemokine:chemokine receptor signals, which DCs require to move through and remain in LNs after antigen exposure. The following will describe DC activation, migration and activation of T cells.

1.3.2.1 Activation of DCs In the steady state, cDCs are described as immature or ‘resting.’ This is characterized by low expression of co-stimulatory molecules (CD80, CD86, and CD40) and MHCII. At this stage, cDCs have an increased propensity to probe for antigens and increased phagocytic capacity (255). During an inflammatory response, cDCs mature, increasing surface expression of co-stimulatory molecules, their phagocytic capacity diminishes and they express antigen- loaded MHCII. Activated cDCs also acquire expression of CCR7 that facilitates their entry into SLOs where they may encounter and activate naïve T cells, stimulating their expansion and differentiation, through provision of appropriate cytokine cues (171). TLRs are among the most widely studied PRRs. They vary in their distribution in different DC subsets, which allows for specialization of DCs in response to different stimuli. DC subsets will be defined in this section as CD8+ cDCs (Irf8+ cDCs), CD11b+ cDCs (Irf4+ cDCs), pDCs and moDCs. Given the roles of different DC subsets in regulating responses to different pathogens, it is not surprising that different TLRs are expressed by each DC subset. CD8+ cDCs express TLR3 and pDCs express TLR7 and TLR9 (256), which are found in the

28 endosomes and are important for responses to intracellular bacteria and viruses, as they sense nucleic acids (257). Interestingly, it was shown that murine CD8+ cDCs express very low levels of TLR4 (258). On the other hand, CD11b+ cDCs and moDCs, that respond to extracellular infections, express TLRs important for the recognition of bacterial cell wall components: TLR 1, 2, 4, 5 and 6 (256).

Figure 1.4 TLR signaling cascades. Pathways invoked by different TLRs and the associated adaptor molecules are indicated

TLR signaling pathways are outlined in Figure 1.4. All TLRs activate MAPK and NFκB pathways, and select TLRs also activate IRFs. Activation of the MAPK and NFκB pathways is critical for inducion of pro-inflammatory cytokines, and the IRFs are associated with type I IFN production. TLR4 is activated by the bacterial cell wall component, lipopolysaccharide (LPS). Ligation of TLR4 leads to dimerization of the receptor and recruitment of adaptor molecules myeloid differentiation primary-response protein-88 (MyD88) and MyD88 adapter-like (MAL), through their Toll-IL-1-resistance (TIR) domains. These proteins then recruit IL-1R associated kinases (IRAKs) and TGF-β activated kinase-1 (TAK1) which activates both NFκB and MAPK signaling cascades (259). Additionally, TAK1 has been shown to be important for regulating DC lineage and subsequent T cell activation, as its DC-specific deletion leads to a reduction in CD8+ cDCs and deficiency in Tregs (260). Endocytosis of TLR4 leads to activation of TIR domain-containing adaptor protein inducing IFN-β (TRIF), rather than MyD88, and another adaptor protein, TRIF-related adaptor molecule (TRAM), that leads to IFN-β production (261). TRIF activates tank binding kinase (TBK1) and IκB kinase ε (IKKε) (262), which leads to IRF3 activation and the production of type I IFN. The ability to induce IFN production is limited to TLR4 and TLRs 3, 7, and 9, as they are the only TLRs that utilize TRIF. The integration of TLR and type I IFN signaling may, therefore, also be important for DC production of IL-12 and polarization of Th1 cells (263). Activation of the MAPK pathway in DCs appears necessary to promote Th17 responses, as deletion of the p38α kinase in DCs was shown to completely dampen DC-mediated Th17 polarization, mediated by lack of IL-6 production and an increase in IL-27 production (264). Steady state activation may occur in a small portion of cDCs, through indirect activation of the DCs by inflammatory mediators rather than direct PRR stimulation (265). Steady state DC activation is thought to induce tolerogenic cDCs. DCs treated with TNF-α protect mice from induction of EAE and this was shown to be due to induction of IL-10 producing Tregs, whereas DCs treated with LPS could not protect from disease (266). In another study, DCs activated by inflammatory mediators in a co-culture system failed to induce Th1 and Th2 responses (267). Additionally, regulatory components of the NFκB pathway may contribute to steady-state maturation, as their deletion yields DCs that are, instead, immunostimulatory (268-270). This

31 form of DC activation may therefore function to reduce the population of peripheral T cells that are self-reactive by inducing anergic T cell responses or inducing Tregs.

1.3.2.2 Migration of DCs Guidance of DCs into lymphoid tissues is similar to that of T cells described above. Table 1.2 provides an overview of the different receptors expressed by DC subsets that trigger activation and their migration. In the steady state, peripheral DCs utilize CCR7 to migrate through the afferent lymphatics into LNs, utilized by skin- (271) and gut-resident DCs (272). Peripheral DCs that migrate into the LNs during the steady state have a ‘semi-mature’ phenotype and may be important for the induction of tolerance. The lymphatic vessels in non- lymphoid organs produce CCL21, promoting CCR7+ DC migration into draining LNs. Unlike T cell migration from HEVs into LNs, the migration of DCs from lymphatics into the LN is not necessarily dependent on DC arrest by integrins, as integrin-deficient DCs are able to migrate into draining LNs (273). On the other hand, migration of DCs from the lamina propria to the draining mesenteric LNs requires CCR7, as CCR7 null mice lack lamina propria DCs in the draining LNs (274). CCL21 and CCL19 guide DCs from the sub-capsular sinus of LNs into the T cell areas, where the DCs can interact with and activate naïve T cells. DCs also express S1P receptors 1-5 and can respond to gradients of S1P to migrate into and out of LNs (275). During homeostatic conditions, S1P blockade does not appear to affect DC migration into draining LNs or in the spleen, but may affect the distribution of immature CD11b+ cDCs in the splenic marginal zone (276).

Table 1.2 Chemokine receptor, TLR and S1P receptor expression on DC subsets DC subset Chemokine TLRs S1P receptors receptors CD8+ cDC XCR1, CCR7, TLR3 S1P1-4 (immature) CCR2, CXCR3, S1P1,3 upregulated on activation CXCR4 S1P2 (inactivation of migration) CD11b+ cDC CCR7, CCR2, TLR1, 2, 4, 5, 6 S1P1 required for LN positioning CCR6, CXCR4, S1P1,3 upregulated on activation CCR9 S1P2 (inactivation of migration) pDC CCR7, CCR2, TLR7, 9 S1P1, 2, 4, 5 CCR5, CCR6, S1P2 (inactivation of migration) CCR9, CXCR3, CXCR4 moDC CCR2, CX3CR1 TLR 1, 2, 4, 5, 6 S1P1,4,5 S1P2 (inactivation of migration)

Activated, mature DCs express CCR7, which enables their response to CCL21 released into the periphery by the lymphatic endothelium (277). DCs are drawn to the lymphatic vessels through CCR7:CCL21 interactions and enter into the lymphatics through gaps in the lymphatic endothelial basement membrane (278). In the lymphatic vessel lumen, DCs crawl along the endothelial layer, following the flow of the lymph and are able to enter into the LNs through the collecting lymphatics (279). DCs can also enter into the LNs via the bloodstream and HEVs. Inflammatory chemokines released into the interstitial fluid flow into the LNs where blood DCs and monocytes can migrate through the HEV and into the LNs (175). In the case of monocytes, this process is CCR2-dependent. These mature DCs and monocyte-derived DCs can then produce cytokines and chemokines that stimulate T cell proliferation and differentiation (280). In the absence of CCR7, responses to autoantigen are largely in the spleen, but not the LNs, indicating the importance for CCR7 in DC (and T cell) trafficking to the LNs to induce an immune response (281). The migration of mature DCs is also modulated by S1P. The upregulation of CCR7 and response to CCL19 by mature DCs triggers the downregulation of S1PR2 (282). S1PR2 blocks DC migration by activation of the small GTPase, RHO, and also prevents S1pr1 transcription (283). The maturation of DCs and CCL19:CCR7 interactions promote activation of the small GTPase, RAC, which activates S1pr1 transcription and responsiveness to S1P through S1PR1, triggering DC migration.

1.3.3 IFN-β effects on DCs

Type I IFN treatment of immature DCs promotes their activation by increasing surface expression of co-stimulatory molecules and MHCII. In humans, this can also trigger IL-12 production by DCs, which stimulates CD4+ Th1 cells. Additionally, type I IFNs increase the ability of cDCs to cross-present antigen to CD8+ T cells (17). In a murine tumor model, IFNAR signaling was required in CD8+ cDCs to mediate tumor rejection through cross-presentation of tumor antigen to CD8+ T cells (284). Activation of murine DCs with IFN-β alone leads to increased expression of CD80, CD86 and MHCII, although TLR stimulation has a more potent effect on the co-stimulatory molecules (285). The effect of IFNs on DC cytokine production may be regulated by the amount of IFN present, as low levels of IFNs promote production of IL- 12 and high levels of IFNs may suppress inflammatory cytokine production (263, 286).

However, cytokine production may also be affected by the presence of TLR agonists. IFN-β treatment of murine bone marrow derived DCs stimulated with LPS inhibits production of IL-12 and IL-23, and increases the regulatory cytokine IL-10, by activating STAT2 (287). In addition to modulating cytokine production and T cell activation capacity, IFNs can affect DC migration. In humans, in vitro generated monocyte-derived DCs matured in the presence of IFN-α have increased expression of CCR7. These DCs have an increased capacity for migration toward CCL19 and migrate upon adoptive transfer into SCID mice (288). On the other hand, treatment of murine bone marrow derived DCs with IFN-β triggers a decrease in CCR7 expression and limits their migratory capacity (289). IFN-β treatment during influenza infection increases CD69 expression on murine pDCs, which leads to downregulation of S1P receptors and accumulation of pDCs in the LNs (290). Given these data, it appears that the effects of type I IFNs on modulating the phenotype and function of DCs is affected by the presence or absence of TLR stimuli. Since type I IFNs and TLRs both stimulate the MAPK pathway and IRFs, it is possible that they may have combinatorial or co-operative effects and the interplay between these pathways should be further investigated in different immunological contexts.

1.4 Multiple Sclerosis and Experimental Autoimmune Encephalomyelitis Multiple Sclerosis (MS) is a chronic, progressive autoimmune disorder characterized by central nervous system (CNS) damage (291). The onset of disease is typically seen between 20 and 50 years of age and MS affects approximately 2.5 million people worldwide. Approximately 85% of patients suffer from the relapsing-remitting (RR) form of MS, while the remaining suffer from primary-progressive (PP) and secondary-progressive (SP) MS (292). Patients with RRMS experience unpredictable, self-limiting bouts of CNS dysfunction, which can be heterogeneous in their severity, duration and frequency. PPMS is characterized by an insidious onset, followed by a gradual worsening of neurological symptoms. Many patients with RRMS progress to SPMS, when disease remission no longer occurs. The mechanisms involved in the different courses of the disease are not clearly understood. Additionally, there is heterogeneity in morphological alterations in the brains of MS patients as well as in their clinical presentation, indicating that MS is a complex disease with an equally complex pathophysiology (293, 294).

The causes of MS are not fully understood. However, like other autoimmune diseases, it has been shown that certain genes can confer risk related to the development of MS. Recent genome-wide association studies (GWAS) have identified a number of genes that contribute differently to the risk associated with developing MS (295). While the most significant risk was found to be associated with the MHC class II genes, it was shown that MHC class I alleles might actually be protective in MS. Furthermore, a number of genes that were found to confer risk are associated with the differentiation of T cells into the different T helper lineages. Not only were genes involved in T cell polarization represented, but also genes involved in co- stimulation and downstream signaling pathways in APCs, suggesting roles for both T cells and APCs in the pathogenesis of MS.

1.4.1 MS pathogenesis

Clinical manifestations of MS include sensory and visual impairment and irregularities, chronic pain, fatigue, cognitive deficits and motor dysfunction (296). The symptoms of MS are caused by pathological lesions in the CNS, which are attributed to immune cell infiltration that causes inflammation, demyelination and axonal damage. The infiltration of peripheral inflammatory T cells is critical to the development of MS and mice deficient in CD4 or CD8 T cells exhibit a reduced incidence of EAE (297). A graphical schematic of MS pathogenesis is shown in Figure 1.5. Activated T cells are activated in the periphery and migrate to the CNS. After CNS entry, T cells can be re-activated by resident APCs such as DCs and microglia, leading to pathogenic cytokine production, which promotes recruitment of other cells, leading to inflammation. Subsequently, the inflammatory milieu and cell recruitment lead to myelin sheath damage and formation of lesions. As the CNS is an immunologically specialized compartment, cells must cross the blood brain barrier (BBB) to gain access to the parenchyma. Breakdown of the BBB is one of the initial steps in the development of MS (298). Expression of chemokines and their receptors dictate the timing at which cells can gain entry into the CNS. To that end, specific chemokines and their receptors have been implicated in leukocyte recruitment to the CNS. The chemokine receptors CCR1 and CCR2 are critical for leukocyte trafficking in EAE in mice (299). CCR2 is also required for EAE induction (300, 301). Notably, development of EAE is unaffected in

CCR5 null mice (302). An apparent contradiction is that CCL5 levels are elevated in MS lesions in patients (303) and the expression of CCR5, a cognate receptor for CCL5, is increased on circulating T cells in MS patients (304, 305). Additionally, there is evidence for increased CXCR3 expression on circulating T cells derived from MS patients (305). T cells derived from MS patients expressing CCR5 and CXCR3 are characterized by a signature cytokine profile of elevated IFN-γ and TNF-α (306), suggestive of a Th1 phenotype. CCL20, the ligand for CCR6 is expressed by the blood-cerebrospinal fluid (CSF) barrier endothelium, which lines the choroid plexus. The choroid plexus is where CSF is produced and may serve as a port of entry for T cells into the CNS (307). CCR6-expressing CD4+ T cells are also present in MS patient tissues and express both IL-17 and IFN-γ (308). CCR6 is required for CCL20-mediated Th17 cell entry into the choroid plexus (309), however, CCR6 null mice are not protected from EAE (310). The implications from these studies are that CCR6 may also allow entry of CCR6-expressing Tregs into the CNS where they can exert protective functions.

Figure 1.5 Overview of MS pathogenesis CD4+ T cells become activated and primed to a myelin-like antigen in the periphery. The T cells migrate to and penetrate the blood brain barrier. Once in the CNS, resident APCs can re-activate the T cells to myelin antigens. Release of cytokines by the T cells and resident microglia amplify the immune response against myelin, leading to demyelination and axonal damage.

1.4.2 The EAE model of MS

The primary animal model used to study MS pathogenesis is EAE. There is also a viral model of MS in mice, where Theiler’s murine encephalitis virus (TMEV) is used to induce damage to the CNS and study neuroinflammation, demyelination, and axonal damage (311), however, this section will focus on the EAE models induced against myelin antigens. A number of different murine EAE models exist and have been developed to mimic different disease phenotypes and clinical features of MS (312). In general, the induction of active EAE in mice involves a subcutaneous injection of myelin components emulsified in complete Freund’s adjuvant (CFA) to induce an autoimmune response. Depending on the strain of mouse used, the antigen varies, as does the use of pertussis toxin (PTX). This results in an MS-like, CD4+ T cell mediated disease. Early studies in SJL mice employed myelin basic protein (MBP) for immunization (313), but proteolipid protein (PLP) 139-151 is a more immunodominant antigen that also induces disease in SJL mice (314, 315). PLP plus CFA immunization induces a relapsing-remitting form of disease and has long been considered the closer of the two main active EAE models to MS. C57BL/6 mice immunized with myelin oligodendrocyte glycoprotein (MOG) 35-55 (316) leads to a chronic disease with no relapses, and is generally used to study the induction phase of disease. This model also requires injection of PTX, which aids in the breakdown of the BBB and allows entry of T cells into the CNS (317). In addition to BBB breakdown, PTX activates TLR4 and other TLRs, contributing to cell activation and disease induction (318, 319). One of the main transgenic mouse models of EAE employs C57BL/6 mice with a MOG 35-55 restricted TCR (also known as 2D2 mice) (320). These mice have a higher incidence of induced disease than C57Bl/6 mice and also can develop spontaneous disease. While active EAE requires injection of myelin components to induce pathology, the disease can also be adoptively transferred to naïve animals by the injection of encephalogenic autoreactive CD4+T cells from 2D2 mice (321), but cannot be transferred by antibodies, and only in rare circumstances has been transferred by injection of encephalogenic CD8+T cells (322, 323). Even with these differences, the different EAE mouse models exhibit a prominent CD4+ T cell infiltrate into the CNS, containing both Th1 and Th17 cells. These models have been extensively used to gain an understanding of the contribution of autoreactive T helper cells to

39 disease, as well as a tool to study the mechanisms of action and effects of candidate therapies (324).

1.4.3 T cells in MS and EAE

MS was originally considered to be a CD4+ Th1-mediated autoimmune disease. The majority of evidence in support of a Th1-mediated autoimmune response derives from studies examining the cellular influx of cells into the brain and CSF in EAE. Additional evidence for a role for CD4+ T cells in MS derives from association of specific HLA class II molecules with MS, accounting for a significant portion of the genetic risk linked to MS (295). The importance of Th1 cells has been highlighted in MS and EAE: elevated IFN-γ has been reported in the CSF of MS patients and in the spinal cords of mice with EAE (325); mice deficient in the Th1 transcription factor, T-bet, are resistant to EAE development (326); adoptive transfer of myelin- specific Th1 cells will induce EAE (327, 328). Moreover, administration of IFN-γ to MS patients exacerbates the disease (329), yet IFN-γ-/- and IFN-γR-/- mice are more susceptible to EAE (107, 330). Several lines of evidence suggest that Th1 cells likely are not the exclusive, or most significant, critical effectors in MS and EAE. IL-12 is important for the differentiation of Th1 CD4+ lymphocytes, however, EAE is also exacerbated in IL-12-/-mice (106, 331). The disease is blocked in mice that lack the IL-12 family member, IL-23 (108), which promotes the expansion and survival of CD4+ Th17 cells. Expression of the IL-1 receptor (IL-1R) is implicated in the development of EAE, and IL-1RI-/- mice have significantly reduced EAE. Notably, the addition of IL-1β to in vitro cultures of Th17 cells promotes IL-17 production (332). IL-1β is present in MS lesions and high IL-1β/IL1R antagonist ratios are associated with a greater risk of relapse onset in MS (333). Additionally, IL-23 drives the pathogenic Th17 population to induce CNS autoimmunity (334). MS patients exhibit increased levels of IL-17 and IL-12 in peripheral blood, CSF and brain lesions (335, 336). Enhanced expression of IL-23 is present in CD11b+ macrophages and microglial cells in active MS lesions (337), suggesting that the CNS microenvironment may sustain the Th17 population in MS. Interestingly, use of an IL-23 blocking antibody in MS did not show therapeutic benefit in terms of relapse reduction and MRI lesions (338). This lack of efficacy was attributed (i) to the high disease scores of patients

40 enrolled in the study, where active Th17 cells were likely already present in the CNS, causing disease, and (ii) the antibody may not have crossed the BBB to block re-activation of Th17 cells (339). On the other hand, blockade of IL-17A in MS is the subject of ongoing study and has been shown to have some potential benefit in reducing new lesions as identified by magnetic resonance imaging (MRI) (340).

1.4.4 DCs in MS and EAE

Given the role of DCs to induce immune responses by activating T cells and generating immunological memory, it is not surprising that they have a role in the generation of autoimmunity. Presentation of self-antigens by DCs to autoreactive T cells represents a breakdown in tolerance and initiates subsequent immune attack on tissues and organs. The specific roles of DCs in MS and EAE are complex and the subject of considerable investigation. Monocytes represent an important subset of circulating cells that can develop into DCs and macrophages (341). Monocytes express a variety of scavenger receptors, chemokine receptors and adhesion molecules, allowing them to respond to inflammatory stimuli and migrate from the blood into affected tissues (342). Monocyte-derived or myeloid DCs (moDCs) are short-lived migratory DCs that differentiate in response to inflammation (343) and may be responsible for re-activation of T cells in the CNS during MS and EAE (344, 345). There is increasing evidence that moDCs are critical APCs in EAE, driving the Th17 lineage (346) and exerting a pathogenic role in disease (345). Studies have identified abundant DCs, both cDCs and pDCs, in inflamed CNS lesions and CSF of patients with MS. During relapse, the levels of pDCs in the CSF increase compared with levels observed during remission (347). In addition to increased DC numbers, the DC phenotype varies with the clinical course of MS. For patients with RRMS, circulating cDCs exhibit an activated phenotype, with CSF-derived cDCs exhibiting a more pronounced activation and increased production of pro-inflammatory cytokines (348, 349). For pDCs, there is emerging evidence of a subset of pDCs that promote Th17 differentiation and exhibit a pro- inflammatory phenotype in RRMS (350). In MOG-induced EAE, pDCs apparently exhibit dual functions: promoting induction of EAE, yet reducing severity of disease during the acute phase (351).

Conditional depletion of DCs around the time of MOG immunization of mice does not affect the frequency of activated splenic Th1 and Th17 cells, or the incidence of EAE, but affects severity of disease (352). pDC depletion in PLP-immunized SJL/J mice, either during the acute phase or during EAE relapse, results in increased Th1 and Th17 cells in the CNS and exacerbated disease (353). In this case it appears that once disease is initiated, pDCs exert a tolerogenic role. Indeed, other studies have indicated an anti-inflammatory function of pDCs during EAE (354, 355). The data suggest that, after EAE induction, pDCs are recruited to LNs and interact with CD4+ T cells to promote the selective expansion of Tregs that would dampen the autoimmune response. A recent study also showed that pDCs transferred into mice with established EAE reduced clinical scores and led to recruitment of host pDCs to the CNS and induction of PD-1 on CD4+ T cells (356). Indeed, pDCs express MHC class II and co- stimulatory molecules, enabling their effector function as APCs. pDCs secrete cytokines and chemokines that influence the recruitment and function of T cells, and pDCs express IDO, ICOSL and granzyme B, which promote Treg activation (357). In addition to the apparently pathogenic roles for DCs in MS and EAE, tolerogenic DCs have been identified to have beneficial effects in both settings. Myelin peptide-loaded tolerogenic DCs induce hyporesponsiveness in myelin-reactive T cells from RRMS patients (358), and tolerogenic DCs transferred into EAE-induced mice reduced severity of disease and induced IL-10 producing- Tregs (359). DCs can also produce regulatory cytokines, including IL-27, that suppresses Th17 differentiation, possibly through antagonism of IL-6 (360).

1.4.5 Therapies for MS

Several different immunomodulatory therapies for MS are in use in the clinic. While there is no cure for MS, these drugs have many different immunomodulatory functions and benefit relapse rate and clinical presentation for MS patients. In addition to IFN-β, which was the first approved therapy for MS, other immunomodulatory drugs that have therapeutic benefit in MS are glatiramer acetate (361), dimethyl fumarate (362, 363), and teriflunomide (364). IFN- β is the first line treatment for patients with RRMS. It was originally proposed to have benefits in MS due to its antiviral activity, as MS was initially suspected to be induced by viral infections and relapses a result of viral re-activation (365). IFN treatment reduces the rate of relapses and

42 exacerbations in RRMS patients. IFN-β also reduces the number of new lesions detected by magnetic resonance imaging (MRI) after starting therapy (366). Treatment of EAE mice with IFN-β reduces relapse rates and overall, clinical scores are lower (367, 368). In agreement with those studies, IFN-β-/- mice studied in relapse-remitting EAE show evidence of increased frequency of relapses (369). In MS, IFN-β treatment modulates adhesion molecule expression (366), inhibits matrix metalloproteinase activity (370) and regulates leukocyte trafficking (370, 371). Although IFN-β therapy is effective in many MS patients, approximately one-third of MS patients are considered non-responders (372), demonstrating how clinically heterogeneous the population of MS patients truly is, and highlighting the importance of defining the specifics of the mechanism(s) of action of IFN-β in MS. Targeting of T cell migration also provides therapeutic benefit in MS. Blockade of the integrin α4 (also known as very late antigen 4 – VLA-4) by the monoclonal antibody natalizumab inhibits T cell migration across the BBB and reduces severity of disease and relapse rates in MS patients (373). However the blockade of all VLA-4-mediated entry into the CNS comes with risk, as susceptibility to fatal opportunistic CNS viral infection by the JC virus leading to progressive multifocal leukoencephalopathy, is greatly increased with natalizumab therapy (374). Another blockade of leukocyte trafficking in MS is the S1P receptor agonist, FTY720. The modulation of S1P receptors blocks lymphocyte egress from LNs, leading to decreased autoreactive T cells in the periphery and decreased disease symptoms in patients (375). Recently, the use of monoclonal antibodies that target specific cell types in MS patients has been used in clinical trials and some have gained approval for use in RRMS. Alemtuzumab is an anti-CD52 antibody, targeting CD52 on monocytes and lymphocytes, leading to their depletion. This leads to a reduction in relapse rates and new lesions identified by MRI (376). Ocrelizumab is a humanized anti-CD20 antibody that targets and depletes B cells, leading to decreases in brain lesions and relapses (377). Ocrelizumab is a promising therapy and may be approved for clinical use in the near future (378). Finally, a humanized anti-CD25 antibody, daclizumab, modulates IL-2R signaling, but also appears to increase regulatory NK cells in RRMS. Daclizumab reduced relapse rates and new lesions as detected by MRI in RRMS patients (379). Daclizumab recently received FDA approval (May 2016) for use in RRMS patients that have failed 2 other therapies (380).

1.4.5.1 IFN-β effects on T cells in MS and EAE The effects of IFN-β in MS are pleiotropic and include differential effects on the different subsets of immune cells. Broadly, the effects of IFN-β on T cells in MS and EAE can be either direct or indirect and modulate their proliferation, differentiation and cytokine production. IFN-β may also modulate the migration of T cells into the CNS by downregulating VLA-4 on T cells, thereby reducing their capacity to migrate across the BBB (381), and this may be indicative of a positive response to IFN-β therapy (382). IFN-β treatment appears to have confounding effects on Th1 cells. In one study, treatment of purified human CD4+ T cells with IFN-β led to increased IFN-γ+ cells (328), yet in another study IFN-β treatment of CD4+ T cells isolated from healthy control peripheral blood led to a decrease in IFN-γ production (383). Additional confounding data were reported using Ifnar-/- mice and the EAE model; one study revealed increased IFN-γ production from Ifnar-/- MOG re-stimulated splenocytes (202), while another did not find a difference in IFN-γ production between Ifnar-/- and wildtype splenocytes (27). In Ifnb-/- mice, re-stimulated LN T cells from EAE mice produced the same amount of IFN-γ compared to wildtype mice (369). In a more recent study, regulatory effects of IFN-β on Th1 cells (suppression of proliferation, IFN-γ and IL-2 production) were dependent on a lack of APCs present in the system (196). From these data, the implications are that IFN-β is inhibitory to Th1 CD4+ T cells in the absence of APCs, yet may have differing effects on other cell types present in a heterogeneous population. IFN-β treatment also regulates the expression of the Th1 cell-associated chemokine receptors CCR5 and CXCR3, as treatment with IFN-β reduces the numbers of CD4+ T cells positive for these receptors in the CNS of mice with EAE (384). In MS patient samples, while some reports have indicated an unclear role for IFN-β effects on Th1 cells, others have reported decreased gene expression of IFN-γ and T-bet from IFN-β treated patient PBMCs (385). Additionally, this study provided evidence for decreased Th17 cytokine gene expression and an increase in expression of IL-10, IL-27 and Foxp3 in the PBMCs from MS patients on IFN-β therapy, though the IL-10 and IL-27 were attributed to expression by monocytes from these samples. GM-CSF, which can be produced by pathogenic Th1 cells and Th17 cells, is present in MS brain lesions and IFN-β treatment reduces GM-CSF production by peripheral CD4+ T cells in MS patients (386).

The exact mechanism of type I IFN regulation of Th17 cell lineage commitment has not been elucidated. Accumulating evidence reveals that the Th17 lineage is affected by IFN-β. Treatment of proliferating murine CD4+ T cells with IFN-β decreases IL-17 gene and protein expression and IFN-β treatment prior to induction of EAE limits expression of IL-17 mRNA in cells from the CNS draining lymph node (387). In MS patient CD4+ T cells, silencing of IRF7 leads to increased production of IL-17A and IL-17F, highlighting the importance of endogenous IFN-β for regulating the Th17 lineage (388). Additionally, Ifnar-/- mice have elevated levels of Th17 cells during EAE (202, 389); however, another study with Ifnar-/- mice did not show any differences in Th17 cell numbers compared with wildtype mice (27). Although IFN-β inhibits Th17 polarization in vitro, on adoptive transfer of Th17 cells into recipient mice, IFN-β treatment exacerbated EAE. In the same study, evidence was also provided that IFN-γ signaling must be intact for IFN-β to exert its effects on Th17 cells in vitro, and for IFN-β to limit the induction of MOG-induced EAE (328). IFN-β treatment of SJL mice with EAE leads to increased production of the Th2 cytokine, IL-4, and a decrease in IL-17A expression, but does not appear to change IFN-γ expression (387). In MS patient CD4+ T cells, IFN-β treatment decreases Th17 cell differentiation by limiting RORc, IL23R and CCR6 expression (390, 391). The proportion of CD4+ IL-17A+ and CD4+ IL-17F+ cells are reduced upon ex vivo treatment of MS patient PBMCs with IFN-β. This study also showed that gene expression of IL-17C and IL- 23R were decreased in PBMCs from MS patients on IFN-β therapy (388). An important action for IFN-β on T cells in MS and EAE is the induction of Tregs and regulatory cytokines. In EAE, and possibly MS, IFN-β treatment increases proliferation of Tregs by upregulating GITRL on APCs and downregulating CTLA4 on CD4+ T cells (392). Additionally, an increased number of CD4+CD25+GITR+Foxp3+ cells were identified in SJL EAE mice treated with IFN-β. This was accompanied by an increase in Th2 cytokines and a decrease in Th17 cytokines (205). In MS patients, IFN-β treatment leads to increased Treg frequency and suppressive capacity (393, 394). A unique population of Tregs expressing the transcription factor, FoxA1, developed during EAE when mice were treated with IFN-β. These Tregs could also be induced by IFN-β treatment of PBMCs from healthy controls, and could also be identified from MS patients that were responsive to IFN-β therapy (395). Increased IL- 10 expression either at the mRNA or protein level has been shown upon IFN-β treatment of murine splenocytes or human PBMCs (328, 396). Tregs produce IL-10, however, studies

45 identifying IFN-β induced IL-10 production in EAE and MS have not indicated whether the IL- 10 does indeed originate from Tregs, although some studies have identified that IL-10 is produced by CD4+ T cells. In one study, treatment of differentiated murine Th17 cells with IFN- β inhibited IL-17 production, yet induced IL-10, even under Th17 conditions (397). In a study with MS patient PBMCs, IL-10 was increased in CD4+ T cells that were treated ex vivo with IFN-β (391).

1.4.5.2 IFN-β effects on DCs in MS and EAE The mechanisms by which IFN-β regulates the DC contributions to MS and EAE are unclear. Effects of IFN-β treatment also appear to be different in cDCs or mDCs and pDCs. MS patients on IFN-β therapy have altered chemokine expression levels in blood monocytes (398). Monocyte-derived DCs from MS patients produce less IL-12p70 and increased IL-10 in response to IFN-β treatment in vitro (399). In the EAE model, a role for type I IFNs in regulating myeloid cells was identified by specific deletion of IFNAR on myeloid cells, which led to exacerbated EAE (27). In another study, engagement of IFNAR on DCs was shown to de- repress IL-27 by inhibiting intracellular osteopontin (a pleiotropic cytokine shown to promote Th1 skewing in EAE), which led to decreased Th17 responses (389). This is in agreement with data that indicated that increased osteopontin production in DCs stimulates IL-17 production by CD4+ T cells in EAE (400). Administration of IFN-β to mice with EAE reduced the Th1 and Th17 populations in vivo and also reduced the expression of IL-12 and IL-23, while increasing IL-10 expression in splenic DCs (287). In MS patients, clinical response to IFN-β therapy has been linked to a low baseline level of mDCs in the blood, which did not change in response to therapy over a 12-month study (401). Notably, in that study the pDC numbers were not altered by IFN-β therapy, though the survival marker CD123 was upregulated on pDCs. IFN-β treatment also modulates co- stimulatory marker expression on MS patient monocytes/DCs compared to healthy controls (402, 403). In non-responders, the co-stimulatory marker CD86 is present prior to treatment, indicating that patients with DCs that are already in an activated state may be refractory to IFN- β therapy. Additionally, pDCs seem to acquire an anti-inflammatory phenotype, characterized by decreased CCR7 expression and decreased pro-inflammatory chemokine production when stimulated with IFN-β in vitro (404). As mentioned earlier, there are two subsets of pDCs have

46 been identified in MS patients – pDC1 are anti-inflammatory and produce IL-10 and IFN-α, while pDC2 are pro-inflammatory and drive Th17 responses by secretion of IL-6. In MS patients, there is a skewing toward more pDC2 versus pDC1. IFN-β therapy appears to alter the balance of these two subtypes, skewing toward the anti-inflammatory pDC1 subtype (350). In vitro studies of human monocyte-derived DCs have shown that IFN-β treatment can inhibit the secretion of IL-1β and IL-23, while promoting IL-27 production and this required functional TLR7 (405). In addition to regulating cytokine production, IFN-β treatment induces PD-L1 expression on pDCs, which could modulate T cell function by inducing Tregs. In vitro IFN-β treatment of human DCs and monocytes revealed increased PD-L1 expression and inhibition of CD4+ T cell activation. Additionally, in serial samples from MS patients before and after initiation of IFN-β therapy, there was evidence of increased PD-L1 expression on monocytes, 24h after induction of IFN-β therapy, and PD-L1 mRNA expression in PBMCs was increased over 6 months of treatment (406). Interestingly, a recent study showing that pDC transfer into mice with EAE significantly reduced disease, found that pDCs generated from IFN-β null mice and transferred into wildtype mice could also ameliorate disease, indicating that the protective action of pDCs in EAE was not via IFN-β secretion (356). From these data, it remains to be determined the specific effects of IFN-β in regulating DC activation and cytokine production in MS and in EAE.

1.5 Hypothesis and Objectives The preceding has outlined the pleiotropic effects of type I IFNs and specifically IFN-β, on T cell and DC activation and effector functions. Our working hypothesis is that IFN-β influences the immunophenotype of CD4+ T cells and CD11c+ DCs. To that end, this project had two main aims: 1) Investigate the regulatory roles of IFN-β in Th17 differentiation and function We utilized IFN-β-/- mice to determine effects of IFN-β on T cell activation, cytokine production, Th17-associated gene expression, and Th17 cell polarization in a murine MOG peptide-induced EAE model. 2) Investigate the effects of IFN-β in DCs during EAE Using IFN-β-/- mice and our EAE model, we interrogated the activation status of IFN-β-/- DCs, their ability to produce Th17-associated cytokines, and to drive CD4+ T cell proliferation and Th17 polarization. We also examined the role of IFN-β in regulating the migration of DCs during EAE.

Chapter 2

Materials & Methods

Chapter 2: Materials and Methods 2.1 Mice IFN-β+/+ and IFN-β-/- mice (407) were bred and maintained in a specific pathogen free colony in accordance with guidelines set by University Health Network’s Animal Care committee. Mice were genotyped by PCR as previously described (204). C57BL/6-Tg (Tcra2D2,Tcrb2D2) Kuch1/J (2D2) transgenic mice with TCR specificity for MOG 35-55 were purchased from the Jackson Laboratory (Bar Harbor, ME, USA) and bred with wild type C57BL/6 mice in our colony to obtain mice heterozygous for the 2D2 transgene. 2D2 mice were genotyped by flow cytometry.

2.2 Genotyping Briefly, mice were bled from a tail vein prick. Blood was collected in hematocrit tubes and expelled into 5mL polypropylene tubes containing phosphate buffered saline (PBS) plus heparin sulfate. Samples were stained for CD4-PE-Cy5 (eBioscience) and Vβ11 TCR (BD Biosciences) for 15 minutes at 4°C. Red blood cells (RBC)s were lysed using RBC lysis buffer

(150 mM NH4Cl, 10 mM KHCO3, 0.1 mM Na2EDTA) for 2 minutes at room temperature and samples washed twice in PBS with 2% FCS. Cells were acquired on a FACSCalibur cytometer and samples containing double positive CD4+Vβ11+ cells were determined to be derived from 2D2 transgenic mice.

2.3 EAE induction EAE was induced in IFN-β+/+ and IFN-β-/- mice as previously described (204). Briefly, a subcutaneous injection of 50µg of MOG peptide mixed with complete Freund’s adjuvant (CFA) (10 mg/mL M. tuberculosis, Sigma Aldrich) was administered in the hind flank of mice on day 0, and 400 ng of pertussis toxin was given by intraperitoneal injection on days 0 and +2 relative to MOG peptide plus CFA immunization. Disease progression was scored using a 5 point ascending scale: 0 = no signs of disease, 1 = limp tail, 2 = hind limb weakness, 3 = partial hind limb paralysis, 4 = full hind limb paralysis, 5 = moribund. At early (score of 1-2) and late (score of 3-4) stages of disease, mice were sacrificed and the brains and spinal cords (CNS) and draining inguinal lymph nodes (LN) were harvested and processed into single cell suspensions as previously described (204). Briefly, CNS tissue was digested with 1 µg/mL Collagenase A

(Roche) and 0.1 µg/mL DNase I (Roche) in PBS for 30 minutes at 37°C. The reaction was stopped by incubating with 1 mM EDTA for 10 minutes at room temperature. Cell suspensions were subsequently passed through a 70 µm filter, then the suspension centrifuged at 250 x g over a 37% Percoll (Sigma Aldrich) gradient in PBS, for 20 minutes with no brake. The fatty layer and PBS were aspirated, leaving the remaining cells, which were then washed and subjected to RBC lysis for 5 minutes at room temperature, then centrifuged and counted, before further analysis. For DC isolation and co-culture with 2D2 CD4+ T cells, DCs were isolated from mice on day 3 of EAE, from the injection site draining LN, and CD11c+ cells were positively selected as described below.

2.4 Magnetic Cell Separation (CD4+ T cells & CD11c+ DCs) Spleens were harvested from 6-12 week old female IFN-β+/+, IFN-β-/-, or 2D2 transgenic mice and single cell suspensions were obtained by passing the cells through a 70 µm filter. Contaminating red blood cells were lysed using RBC lysis buffer, for 5 minutes on ice. Cells were washed with PBS and CD4+ T cells were positively selected using a CD4+ magnetic bead selection kit (Miltenyi) as per the manufacturer’s instructions. The purity of CD4+ T cells isolated using this method was routinely >90%. For separation of CD11c+ dendritic cells, spleens of naïve IFN-β+/+ or IFN-β-/- mice or the injection site draining inguinal lymph nodes of 6-8 week old IFN-β+/+ and IFN-β-/- mice with EAE were harvested and digested with 1 µg/mL Collagenase A (Roche) and 0.1 µg/mL DNase I (Roche) in PBS for 30 minutes at 37°C. The reaction was stopped by incubating with 1 mM EDTA for 10 minutes at room temperature. Cell suspensions were subsequently passed through a 70 µm filter and contaminating red blood cells were lysed by incubating in RBC lysis buffer, for 5 minutes on ice. Cells were washed, resuspended in PBS and counted, then CD11c+ cells were isolated by magnetic separation (Miltenyi) as per manufacturer’s instructions.

2.5 Immunoblotting Splenocytes or CD4+ T cells were isolated from IFN-β+/+ or IFN-β-/- mice and serum starved for 1 hr at 37°C. Splenocytes (2 x 106 cells/mL) or CD4+ T cells (5 x 106 cells/mL) were stimulated with 10 µg/mL anti-CD3 and 2 µg/mL anti-CD28 antibodies. At the indicated times, cold PBS was added to quench further phosphorylation, the cells centrifuged for 5 minutes at

770 x g, then lysed using SDS sample buffer (62.5 mM Tris-HCl pH = 6.8, 2% w/v SDS, 10% glycerol, 50mM DTT, 0.01% bromophenol blue). Lysates were boiled for 5 minutes, and then incubated on ice for 15 minutes. Protein extracts were separated on a 7% SDS-polyacrylamide gel and transferred to nitrocellulose membranes using a wet electrophoretic transfer unit. Membranes were then blocked for 1 hour with 2% bovine serum albumin in Tris-buffered saline with 0.01% Tween-20 (TBS-T), then probed for phospho-ZAP70 (pY493 Cell Signaling Technologies), 1:1000 dilution in blocking buffer, overnight at 4°C. In order to re-probe membranes, they were stripped using a buffer containing 7 M guanidine-HCl, 50 mM glycine pH = 10.8, 0.1 M KCl, 50 mM EDTA and 20 mM β-mercaptoethanol for 30 minutes at room temperature, then rinsed using TBS-T and incubated with anti-total ZAP70 (Transduction Laboratories) at a 1:1000 dilution in blocking buffer. Membranes were washed 3 times with TBS-T and then incubated with the secondary anti-rabbit-horseradish peroxidase antibody (1:10000, GE Healthcare) for 1 hour. Signal was developed using the BioRad Clarity chemiluminescence kit. Band density was determined using BioRad QuantityOne software and phospho-ZAP70 levels were normalized to total ZAP70 levels for each sample.

2.6 Th17 cell generation and sorting Positively selected CD4+ T cells were resuspended at 2x106 cells/mL in RPMI 1640 medium supplemented with 100 U Penicillin and Streptomycin, 2 mM L-glutamine and 10% fetal calf serum (FCS). 2 x 105 cells were plated in each well of a 96 well round-bottom culture plate previously coated with 10 µg/mL anti-CD3e (BD Biosciences) and 2 µg/mL anti-CD28 antibodies (eBioscience). Cells were incubated in Th17 polarizing conditions: TGF-β (5 ng/ ml) (Peprotech), IL-6 (20 ng/ml) (Peprotech), IL-1β (10 ng/ml) (Peprotech), IL-23 (10 ng/ml) (R&D Systems), anti-IFN-γ antibody (10 mg/ml) (BD Biosciences) and anti-IL-4 antibody (10 mg/ml) (BD Biosciences) for 4 days at 37°C. In the final 4 hours of incubation, PMA (50 ng/ml) (Sigma), ionomycin (500 ng/ml) (Sigma) and Golgiplug (BD Biosciences) were added. Resultant Th17 cells were harvested, counted, and stained using anti-CD4-APC antibody (eBioscience) for 30 minutes at 4°C. Cells were then washed using FACS buffer (2% FCS in PBS), fixed and permeabilized using BD Cytofix/Cytoperm buffer as per the manufacturer’s specifications. The cells were then stained using anti-IL-17-PE antibody (BD Biosciences) for 1 hour at 4°C. Cells were washed and sorted on a MoFlo Cell sorter (Dako) for CD4+IL-17+ cells.

2.7 RNA extraction and gene expression analysis using PCR Arrays RNA was extracted from the fixed and sorted CD4+IL-17+ cells using the FFPE RNA extraction kit (SA Biosciences). Following this, cDNA was generated using the RT2 PreAMP cDNA synthesis kit, using the Th17 specific primer mix (SA Biosciences). RNA from positively selected CD4+ T cells not subjected to Th17 polarization was extracted using the RNeasy kit from Qiagen and cDNA was generated using the RT2 First Strand Kit (SA Biosciences). Gene expression in the Th17 cells was analyzed using the Th17 for Inflammation and Autoimmunity PCR array kit from SA Biosciences, where 84 genes related to the Th17 regulatory network are analyzed in a 96 well plate format. Surface molecules: CD28, CD34, CD3D, CD3E, CD3G, CD4, CD40L, CD8A, ICAM1, ICOS, ISG20. Chemokines: CCL1, CCL2, CCL20, CCL22, CCL7, CD247, CX3CL1, CXCL1, CXCL12, CXCL2, CXCL5, CXCL6, CXCL8 (IL-8), MMP13, MMP3, MMP9 Cytokines: CSF2, CSF3, IFNG, IL-10, IL-12, IL-13, IL-15, IL-17A, IL-17C, IL-17D, IL-17F, IL-18, IL-2, IL-21, IL-22, IL-23A, IL-25, IL-27, IL-3, IL-4, IL-5, IL-6, TGFB, TNFA. Cytokine receptors: IL-12RB1, IL-12RB2, IL-17RB, IL-17RC, IL-17RD, IL-17RE, IL-23R, IL- 6R, IL-7R Signaling pathway molecules and transcription factors: CACYBP, CEBPB, CLEC7A, SIPR1, FOXP3, GATA3, JAK1, JAK2, NFATC, NFKB, RORC, SOCS1, SOCS3, STAT3, STAT4, STAT5A, STAT6, SYK, TBX21, TIRAP, TLR4, TRAF6, YY1. This format also includes positive and negative PCR controls as well as housekeeping genes (Gusb, Hprt, Hsp90ab1, Gapdh, Actb). The array kit was purchased for use with an ABI 7900HT cycler and cycling conditions were as indicated in the manufacturer’s instructions for the SA Biosciences kits. Data were analyzed using the SA Biosciences RT2 Profiler Data Analysis software.

2.8 Real-Time PCR Probing for specific genes using real-time quantitative PCR (qRT-PCR) was conducted employing a Roche LightCycler. RNA for these experiments was isolated from positively selected CD4+ T cells or from sorted CD4+IL-17+ Th17 cells, in separate experiments. RNA was

53 extracted using either the RNeasy kit from Qiagen or the FFPE RNA extraction kit from SA Biosciences. cDNA was synthesized using 200 ng of RNA and MMLV Reverse Transcriptase (Invitrogen) in the presence of random primers. The LightCycler FastStart DNA Master SYBR GreenPlus I kit was used to perform RT-PCR and the corresponding software was used to analyze data. RT-PCR was performed in a volume of 20 µL, using 0.5 mM of each primer and 5 µL of diluted (1:5) cDNA template. Primer sets for each gene were as follows: S1PR1-Forward 5’-AACTTTGCGAGTGAGCTGGT-3’ and S1PR1-Reverse 5’- GGTATTTCTCCAGGCAAACG-3’, IRF4-Forward 5’-AGCCCAGCAGGTTCATAACT-3’ and IRF4-Reverse 5’-AGGTGGGGCACAAGCATAAA-3’ and HPRT-Forward 5’- TTGCAACCTTAACCATTTTGG -3’ and HPRT-Reverse 5’- ATCATGTCAACGGGGGACATA -3’. Standard curves were generated for each primer set and reference and target reactions were performed for each sample.

2.9 Intracellular Cytokine Staining for Fluoresence-Activated Cell Sorting (FACS) CD4+ T cells were isolated from spleens of IFN-β+/+ and IFN-β-/- mice. 2 x 105 cells were seeded into individual wells of a 96 well round-bottom culture plate, then either left untreated or stimulated with anti-CD3 (10 µg/mL) and anti-CD28 (2 µg/mL) antibodies for up to 72 hours. In the final 4 hours of incubation, PMA (50 ng/ml) (Sigma), ionomycin (500 ng/ml) (Sigma) and Golgiplug (BD Biosciences) were added. Cells (1 x 106 per sample) were washed 3 times in FACS buffer, non-specific binding was blocked using 10% mouse serum for 10 minutes at room temperature and surface epitopes were stained using anti-CD3-FITC (eBioscience), anti-CD4- eFluor650 (or APC) (eBioscience), anti-IL23R-PE (BD Biosciences), anti IL-6R-Biotin (BioLegend), anti-CCR6-PE/Cy7 (BioLegend), and anti-CXCR4-APC (BioLegend) antibodies for 30 minutes at 4°C. Cells were washed 3 times and PE-Cy5 Streptavidin (BD Biosciences) was added for 30 minutes at 4°C. The cells were washed 3 times, then fixed and permeabilized using BD Cytofix/Cytoperm for 20 minutes at 4°C. Cells were subsequently washed using BD Perm/Wash buffer and intracellular epitopes were stained using anti-IL-17A-AlexaFluor700 (or PE-Cy7) (BioLegend) antibodies for 60 minutes at 4°C. Cells were washed twice with Perm/Wash buffer and once with FACS buffer, then analyzed using a BD LSRII cytometer. Background staining was determined by isotype control staining for each antibody.

2.10 Surface staining for FACS DCs and DC-CD4+ T cell co-cultures that were stained for analysis by flow cytometry were washed after treatments, culture or isolation and resuspended in FACS buffer (PBS with 2% FCS). Non-specific antibody binding was blocked using 10% mouse serum in FACS buffer for 10 minutes at room temperature. The following antibodies were used (all antibodies were from BioLegend, San Diego, CA, USA, unless otherwise indicated): anti-CD4-BV650, anti- CD3-BV510, anti-MHCII (IA/IE)-FITC (eBioscience) or –BV650, anti-CCR7-PE (eBioscience), anti-CD80-PE-Cy5 or -PE (eBioscience), anti-CD86-FITC or –APC, anti-CD11c-AlexaFluor 700, anti-CD11b-BV421, anti-B220-BV711, and anti-CCR2-AlexaFluor 647. Cells were stained for 30 minutes at 4°C and then washed 3 times with FACS buffer. Cells were analyzed using a Beckton Dickinson LSRII flow cytometer and appropriate isotype controls and fluorescence minus one controls were used in each experiment to gauge non-specific staining and to determine gates. Flow cytometry files were analyzed using FlowJo software (FlowJo, Ashland, OR, USA).

2.11 Cell proliferation assays Spleens were harvested from 6-12 week old female 2D2 mice and CD4+ T cells were positively selected using a CD4+ selection kit (Miltenyi) as described above. Resulting CD4+ T cells were labeled with Cell Proliferation Dye (CPD, eBioscience), at a concentration of 1 µM, as per manufacturer’s instructions. Co-cultures of 1 x 105 CD4+ 2D2 T cells with 5 x 104 IFN- β+/+ or IFN-β-/- CD11c+ DCs, isolated as described above, were set up in 96-well round-bottom culture plates in complete RPMI medium. In experiments where naïve DCs were treated with LPS, cells were plated at 5 x 104/well and incubated with 1 µg/mL LPS overnight, before CD4+ 2D2 T cells were added the following day. When MOG peptide was included in the cultures, it was added at a concentration of 1 µg/mL. After 48 or 72h, cell supernatants were harvested for ELISAs, and cells were washed and stained for FACS analysis. Proliferation was quantified by gating on CD4+ MHCII- cells and CPD dilution was assessed. Histograms from the proliferating samples were compared with unstimulated, untreated and unlabeled controls to gate on dividing cells, and were quantified based on % dividing.

2.12 Enzyme-linked Immunosorbent Assay (ELISA) & FlowCytomix Cytokine Analysis Whole splenocytes or CD4+ T cells were isolated from spleens of IFN-β+/+ and IFN-β-/- mice and stimulated with anti-CD3 and anti-CD28 antibodies in a time course study from 24-96 hours. Supernatants from cell cultures were stored at -80°C until time of analysis with Ready- Set-Go ELISA kits (eBioscience) for IL-17A. Cytokine levels were measured in DC-CD4+ T cell co-culture supernatants using Ready-Set-Go ELISA kits from eBioscience (IL-6, IL-17A, IFN-γ, IL-12p40, and IL-23) were used as per manufacturers instructions. To measure LPS- induced cytokines in IFN-β+/+ or IFN-β-/- BMDCs, the FlowCytomix assay (flow-cytometry based multiplex cytokine detection, eBioscience) was used as per manufacturers instructions. Cytokines measured included IL-1α, IL-1β, IL-2, IL-4, IL-6, IL-10, IL-13, IL-15, IL-17, IL-21, IL-22, IL-23, IL-27, IFN-γ, and TNF-α.

2.13 Bone marrow derived dendritic cell generation Bone marrow derived dendritic cells (BMDCs) were generated as reported previously (408). Briefly, IFN-β+/+ and IFN-β-/- mice aged 6-12 weeks were euthanized, their femurs harvested then flushed and resulting cells were passed through a 70 µm filter. Progenitors were plated at 2 x 106 cells per plate in bacterial Petri dishes. Cells were cultured for 9 days in RPMI medium supplemented with 10% FCS, 100 U penicillin and streptomycin, 2 mM L-glutamine, 20 µM β-Mercaptoethanol (complete RPMI). Recombinant mouse GM-CSF (Peprotech) was added on days 0, 3, 6, and 8 at 40 ng/mL. On the 9th day, cells in suspension were aspirated, washed, counted and seeded at a density of 2 x 106 cells/well in 24-well tissue-culture plates. BMDCs were matured by adding 1 µg/mL of lipopolysaccharides (LPS) (E. coli, O55:B5, Sigma-Aldrich) for 16 h. When BMDCs were primed with MOG 35-55 peptide it was at a concentration of 1 µg/mL for 2-3h on day 10 of DC culture. LPS-activated (or LPS-activated, MOG-primed) BMDCs were then washed 3 times with complete RPMI before their use.

2.14 Gene expression analysis BMDCs were generated from female IFN-β+/+ (n = 3) and IFN-β-/- (n = 3) mice as described above and either left untreated or treated with LPS (1 µg/mL) for 6 hours. Pooled BMDCs were then washed and RNA was extracted using the RNeasy isolation kit according to the manufacturer’s instructions (Qiagen). RNA was then submitted to the UHN Microarray

Facility, where 200 ng/sample was hybridized to the Illumina mouse whole genome WG-6 v2 BeadChip, as per standard protocols. The WG-6 v2 BeadChip contains probes for >42,500 transcripts spanning the mouse genome, and includes probes identified from the NCBI RefSeq database, the mouse exonic evidence based oligonucleotide (MEEBO) probe set and protein coding sequences from the RIKEN FANTOM2 database. Data were analyzed using Illumina’s GenomeStudio software. Raw fluorescence intensities were background corrected and the resulting probe fluorescence intensities from LPS-stimulated samples were compared to the untreated control for each mouse genotype. Fold change was calculated from the log2 transformed data.

2.15 Adoptive transfer For adoptive transfer experiments, LPS-activated, MOG-primed IFN-β+/+ and IFN-β-/- BMDCs were generated as indicated above. DCs were washed and labeled with Cell Vue Maroon dye (eBioscience) at a concentration of 1 µM, as per the manufacturer’s instructions. 2 x 106 labeled DCs were injected into IFN-β+/+ and IFN-β-/- mice on day 3 of EAE via the tail vein. 24 h and 72 h following injection, mice were sacrificed, their spleens, spinal cords and brains were removed and fixed in 10% formalin. 24 h later, tissues were transferred into PBS, and imaged using a Xenogen IVIS. The excitation was set at 640 nm and the emission filter used was 680 nm.

Chapter 3

Immunoregulatory effects of Interferon-beta in suppression of Th17 cells

This chapter was published as:

Pennell LM, Fish EN. 2014. Immunoregulatory effects of interferon-β in suppression of Th17 cells. J Interferon Cytokine Res. 34(5):330–41.

LMP performed all experiments, analyzed data, and drafted the manuscript.

Chapter 3: Immunoregulatory effects of Interferon-beta in suppression of Th17 cells 3.1 Abstract To investigate the immunoregulatory effects of IFN-β on CD4+ T cells we examined the response of CD4+ T cells from IFN-β+/+ and IFN-β-/- mice to CD3/CD28 activation and to differentiation to Th17 lineage, analyzing expression of signaling effectors, cell surface receptors, production of IL-17, and gene expression profiles. We provide evidence of increased phosphorylation of the membrane proximal kinase associated with TCR activation, ZAP-70, in IFN-β-/- T cells compared with IFN-β+/+ T cells. Anti-CD3/anti-CD28 antibody stimulation of whole splenocytes or CD4+ T cells from IFN-β-/- mice results in secretion of IL-17A, in contrast to identical stimulation of cells from IFN-β+/+ mice, which fails to increase IL-17A production. Following CD3/CD28 activation, IFN-β-/- CD4+ T cells express higher levels of IRF-4, required for Th17 differentiation, and increased expression of CCR6, IL-23R, IL-6R and CXCR4, compared with activated IFN-β+/+ T cells. Notably, cell surface expression of IL-6R and IL-23R is significantly higher in the IFN-β-/- CD4+ T cells, with an increased number of double positive CCR6+IL-23R+ and IL-6R+IL-23R+ CD4+ T cells. On polarization to Th17 lineage, CD4+ T cells from IFN-β-/- mice exhibit a more Th17-primed transcriptome compared to CD4+ T cells from IFN-β+/+ mice. Indeed, when CD4+ T cells from IFN-β+/+ mice are polarized to Th17 lineage in the presence of IFN-β, many Th17-associated genes are downregulated. Employing a MOG-peptide induced experimental autoimmune encephalomyelitis (EAE) model of multiple sclerosis (MS), we identify a greater proportion of Th17 cells in the lymph nodes of IFN-β-/- mice compared with IFN-β+/+ mice, and increased numbers of CD4+ T cells in the central nervous system of IFN-β-/- mice, regardless of stage of disease. Taken together, our data indicate an immunoregulatory role for IFN-β in suppression of Th17 cells.

3.2 Introduction Interferons (IFN), originally identified for their ability to protect cells from viral infection (1, 2), are now recognized as pleiotropic cytokines with additional roles in cell growth regulation and as modulators of the innate and adaptive immune responses, most recently associated with bacterial infections and inflammatory disorders (reviewed in: (210, 409)). Notably, in vivo, whether an IFN response is associated with pathogen clearance, antitumor/anti-leukemic activity, or inflammatory diseases, there are accumulating data that the type I IFNs, IFNs-α/β, will shape the nature of the signature immune cell response (410). CD4+ T cells are critical effectors in an immune response. Their differentiation into effector (Th) or regulatory T (Treg) cells defines the appropriate immune response. Whereas the Th1, Th2, Th9, Th17 and Th22 subsets are associated with the production of distinct cytokines that mediate immune responses against different pathogens (82, 110, 411-413) an exaggerated Th17 response has been implicated as pro-inflammatory in different autoimmune disorders, including rheumatoid arthritis, psoriasis, multiple sclerosis and inflammatory bowel disorders (414). In recent years, IFNs-α/β have been implicated in the differentiation of CD4+ (and CD8+) T cells. There is evidence that IFNs-α/β promote Th1 lineage commitment, mediated in part by inducing the tyrosine phosphorylation of STAT4 (193) that is required for transcriptional activation of T-bet, that drives IFN-γ production and Th1 polarization. By contrast, IFNs-α/β reverse Th2 cell commitment. We and others describe a mechanism whereby IFNs-α/β suppression of GATA3 limits this Th2 commitment (198, 200). Valuable information relating to the contributions of IFNs-α/β to an immune response have been gleaned through studies involving receptor (IFNAR) knockout mice, regardless of which receptor subunit is knocked down (415-418). However, given that all the type I IFNs, including the IFN-αs and IFN-β, bind to and activate IFNAR, the use of receptor knockout mice precludes examination of the unique contributions of a given type I IFN subtype to a specific biological response. Accordingly, a number of years ago we undertook to examine the effects of specific knockdown of IFN-β on the mouse immunophenotype, on the background of intact other type I IFNs, including all the IFN-α subtypes. Our earlier immunophenotypic analysis of the IFN-β-/- mice revealed that activation of splenocytes from IFN-β-/- mice did not affect the consequent production of IFN-γ or IL-2, but did lead to a reduction in the levels of TNF-α, both in CD4+ and CD8+ cells (407). Moreover, we provided evidence that activation of lymph node

60 cells (407) or splenocytes (204) results in enhanced proliferation of IFN-β-/- T cells compared with IFN-β+/+ T cells. A number of studies have examined the effects of IFNs-α/β on Th17 polarization. Under Th17 polarizing conditions, using the appropriate cytokine cocktail and anti-IFN-γ and anti-IL-4 antibodies, IFN-α treatment of human peripheral blood mononuclear cells, or human or mouse CD4+ cells, will inhibit IL-17 production (203). In this study, the authors also demonstrate that IFN-α treatment of patients with ulcerative colitis led to diminished IL-17 expression in colonic tissue biopsies, which correlated with clinical improvement. Similarly, a number of studies have shown that IFN-β treatment of T cells under Th17 polarizing conditions reduces IL-17 production (204, 391, 397, 419, 420). In this report we provide further evidence for the direct role of IFN-β in suppression of Th17 lineage commitment. Specifically, using CD4+ T cells from mice that are null for IFN-β we provide evidence that anti-CD3/anti-CD28 antibody activation of the T cell receptor leads to enhanced ZAP70 activation and gene expression that supports Th17 polarization. In time course studies we demonstrate that the absence of IFN-β during CD4+ T cell activation drives commitment to a Th17 phenotype.

3.3 Results Given our earlier data that identified enhanced activation-induced proliferation of T cells from IFN-β-/- mice compared with IFN-β+/+ mice, we examined the kinetics of phosphorylation of ZAP-70 following antiCD3/antiCD28 antibody activation of CD4+ splenic T cells. Tyrosine phosphorylation of ZAP-70 is an early proximal event associated with T cell receptor activation (reviewed by Au-Yeung et al (421)). The data in Figure 3.1A reveal that anti-CD3/anti-CD28 activation of CD4+ T cells results in the rapid phosphorylation of ZAP-70 on tyrosine 493, with evidence of more pronounced ZAP-70 phosphorylation in the T cells derived from IFN-β-/- mice. These results are consistent with a greater sensitivity to activation and enhanced proliferation compared with CD4+ T cells derived from IFN-β+/+ mice. Next we examined the effects of anti-CD3/anti-CD28 antibody activation on IL-17 production by splenocytes from IFN-β+/+ and IFN-β-/- mice. Of note, any IL-17 secretion is in the absence of specific cytokine polarizing conditions. The data in Figure 3.1B show enhanced IL- 17 secretion by stimulated IFN-β-/- splenocytes compared with IFN-β+/+ splenocytes. Moreover, when sorted CD4+ cells are anti-CD3/anti-CD28 antibody activated, we observe the same trend, namely greater IL-17 production by the IFN-β-/- CD4+ T cells (Figure 3.1C). Notably, whether splenocytes or sorted CD4+ T cells are stimulated, the results show that there is no increase in IL-17 production in the IFN-β+/+ cells over the 96 hour time course, in contrast to the progressive increase in IL-17 produced by the IFN-β-/- cells. Scrutiny of the CD4+ cell population by FACS revealed that there is no difference in the percentage of CD4+ cells that are producing IL-17 when comparing IFN-β+/+ and IFN-β-/- CD4+ T cells, whether unstimulated or stimulated for 72 hours (Figure 3.1D). The implications are that constitutive basal levels of IFN-β directly affect IL-17 gene expression when T cells are activated.

Figure 3.1 IFN-β CD4+ T cells secrete IL-17A after anti-CD3/anti-CD28 stimulation. Spleens were harvested from IFN-β+/+ (n = 3/experiment) and IFN-β-/- (n = 3/experiment) mice and splenocytes or splenic CD4+ T cells isolated. (A) 5 x 106 CD4+ T cells (pooled) were cultured under stimulating conditions with anti-CD3/anti-CD28 antibodies, in a time course study, then proteins isolated and phospho-ZAP70 identified by Western immunoblot. Density values for phospho-ZAP70 were normalized to total ZAP70 for each sample and represented as a normalized ratio. (B) Splenocytes or (C) CD4+ T cells from IFN-β+/+ and IFN-β-/- mice were pooled and cultured in the presence of anti-CD3/anti-CD28 antibodies for up to 96h, in quadruplicate assays. Cell culture supernatants were analyzed by ELISA assay for IL-17A. (D) CD4+ T cells from 3 IFN-β+/+ and 3 IFN-β-/- mice (not pooled) were either left untreated, or stimulated with anti-CD3/anti-CD28 antibodies for up to 72h and the percentage of IL-17A+ CD4+ cells was analyzed by FACS. Open histograms represent data from IFN-β+/+ mice and filled histograms represent data from IFN-β-/- mice. Data are presented as the mean value +/- standard error and are representative of at least 2 independent experiments. Data were analyzed using a Student’s t test. * p<0.05, ** p<0.0001.

Accordingly, in subsequent studies we examined the effects of anti-CD3/anti-CD28 stimulation of CD4+ cells derived from IFN-β+/+ and IFN-β-/- mice on the expression of selected targets associated with a Th17 phenotype. At the outset we examined interferon regulatory 4 (IRF-4), given the requirement for IRF-4 for the differentiation of Th17 cells (422, 423) and also its protective role during activation-induced cell death of Th cells (424). Whereas basal gene expression levels remain indistinguishable between IFN-β+/+ and IFN-β-/- CD4+ T cells, anti-CD3/anti-CD28 antibody stimulation increases IRF-4 expression in CD4+ T cells in both wildtype and IFN-β null mice, with a modest increased expression in the IFN-β-/- CD4+ T cells (Figure 3.2A).

A B

Figure 3.2 IFN-β influences IRF4, but not S1PR1 expression in CD4+ T cells. Splenic CD4+ T cells were isolated from IFN-β+/+ and IFN-β-/- female mice (n = 3 mice per group, not pooled) and cultured at 2 x 106 cells/mL in the presence or absence of anti-CD3/ anti- CD28 antibodies for 24h. Cellular RNA was extracted and cDNA was synthesized for qRT-PCR of the indicated genes. For each test group (n = 3) the copy number of the reference gene (hprt) and the target gene were determined and target gene is normalized relative to hprt. Open histograms represent data from IFN-β+/+ mice and filled histograms represent data from IFN-β-/- mice. Data are representative of 2 independent experiments. Data were analyzed using Student’s T-test, * p<0.05.

Expression of the sphingosine-1-phosphate (S1P) receptor 1 (S1PR1) on T cells is associated with responsiveness to the ligand, S1P. S1P activation of S1PR1 leads to decreased responsiveness of T cells to chemokines, hence affecting retention time of T cells in lymph nodes and their egress into the circulation. TCR-dependent activation of T cells reduces S1PR1 expression, thereby releasing the suppression of chemokine responsiveness (425). Examination of gene expression for S1PR1 in CD4+ T cells derived from IFN-β-/- and IFN-β+/+ mice revealed the anticipated downregulation of gene expression upon stimulation, with no evidence for a differential effect between wildtype and IFN-β null T cells (Figure 3.2B). Moreover, cell surface expression levels for the chemokine receptor, CCR6, associated with trafficking of Th17 cells (187, 426) are upregulated in CD4+ T cells when stimulated with anti-CD3/anti-CD28 antibodies, again with no distinguishable difference in surface expression levels between IFN-β- /- and IFN-β+/+ CD4+ T cells (Figure 3.3A).

Figure 3.3 IFN-β regulates levels of Th17-associated cell surface receptors. Splenic CD4+ T cells from IFN-β+/+ (n = 3) and IFN-β-/- (n = 3) mice were cultured in the presence or absence of anti-CD3/anti-CD28 antibodies for the indicated times and cell surface expression levels of (A) CCR6, (B) IL-6R, and (C) IL-23R analyzed by FACS. (D) and (E) describe the cell surface expression levels of CD4+ T cells that are double positive for CCR6/IL- 23R and IL-6R/IL-23R, respectively. Data are presented as the mean value of triplicates +/- standard error and are representative of 2 independent experiments. Open histograms represent data from IFN-β+/+ mice and filled histograms represent data from IFN-β-/- mice. Data were analyzed using a Student’s t test: (B) *p = 0.004; **p = 0.002. (D) *p = 0.02; **p = 0.002. (E) *p = 0.04; **p = 0.01; ***p = 0.003; ****p = 0.007.

Once activated, CD4+ T cells will differentiate into effector or regulatory T cells dependent on the cytokine milieu and their cell surface receptor expression. Two other receptors that are associated with Th17 cell differentiation are the IL-6 receptor (IL-6R) (117, 427, 428) and the IL-23 receptor (IL-23R) (429, 430). The data in Figure 3.3B indicate that after 72 hours in culture, there is a significant difference in terms of increased IL-6R expression on the surface of CD4+ T cells derived from IFN-β-/- mice compared with CD4+ T cells derived from IFN-β+/+ cells. Moreover, at that time point, there is also a significant increase in IL-6R surface expression upon anti-CD3/anti-CD28 antibody stimulation that is most pronounced in the IFN- β-/- CD4+ T cells. Examination of IL-23R cell surface expression revealed increased expression in the IFN-β-/- CD4+ T cells compared with the IFN-β+/+ CD4+ T cells, in both unstimulated and anti-CD3/anti-CD28 antibody stimulated cells, at each of the time points examined, including basal levels at time 0 (Figure 3.3C). Perhaps most striking, is that when we consider CD4+ T cells that are double positive for CCR6 and IL-23R (Figure 3.3D) or double positive for IL-6R and IL-23R (Figure 3.3E), whether the cells are stimulated with anti-CD3/anti-CD28 antibodies or left untreated, there is evidence of a higher percentage of double positive cells derived from IFN-β-/- CD4+ T cells compared with IFN-β+/+ CD4+ T cells. Again, the implications are that in the absence of IFN-β cells are primed to differentiate into Th17 cells upon T cell activation. Given the preceding, we next considered the Th17 transcriptome of both IFN-β+/+ and IFN-β-/- CD4+ T cells. Specifically, CD4+ splenic T cells derived from IFN-β+/+ and IFN-β-/- mice were cultured under Th17 polarizing conditions for 96 hours (as described in Materials and Methods), then gene expression examined employing a PCR gene expression array where 84 genes related to the Th17 regulatory network are analyzed. We anticipated an enhanced Th17 profile in the IFN-β-/- derived cells. After 96 hours in Th17 polarizing conditions cells were sorted based on CD4+IL-17+ to collect Th17 cells. Approximately 20% of the CD4+ T cell population from the IFN-β-/- mice and 17% from the IFN-β+/+ CD4+ T cells expressed IL-17. The data in Figure 3.4 are presented as expression levels in the IFN-β-/- Th17 cells compared to expression levels in the IFN-β+/+ Th17 cells that have been normalized relative to a panel of 5 housekeeping genes. The results in panel A reveal that the expression levels of the majority of genes are elevated in the IFN-β-/- Th17 cells (66 genes) compared with the IFN-β+/+ Th17 cells, many of which are associated with a Th17 transcriptome. A minority of the genes are downregulated to any significant level in the IFN-β-/- Th17 cells (8 genes) compared to the IFN-

β+/+ Th17 cells gene profile, with the exception of IL-23r, IL-6ra and Rorc, perhaps indicative of a completed response to IL-23- and IL-6-induced polarization in the IFN-β-/- CD4+ T cells. Next we examined the effects of including IFN-β in the culture conditions during polarization of CD4+ T cells derived from IFN-β+/+ CD4+ T cells. Including IFN-β in the culture conditions resulted in fewer CD4+IL-17+ cells (8% of total CD4+ cells) compared with cultures with no IFN-β (18% of total CD4+ cells). The data in Figure 4.4B clearly indicate that addition of IFN-β affects polarization towards Th17, reducing gene expression in the majority of genes examined, with only 6 of the 84 genes exhibiting a modest increased expression (>1.5-fold) relative to their expression in cells not treated with IFN-β.

Figure 3.4 IFN-β influences the ‘Th17 transcriptome’. Splenic CD4+ T cells from (A) 3 IFN-β+/+ and 3 IFN-β-/- female mice or (B) 5 IFNβ+/+ mice were stimulated with a cocktail of antibodies and cytokines to generate Th17 cells (as described in Materials and Methods), and in (B), IFN-β was added to half of the cultures. After 96h of polarization, CD4+IL-17A+ cells were sorted by FACS, RNA extracted and cDNA synthesized for qRT-PCR PCR arrays. Data are expressed as (A) a fold up or down-regulation compared to the IFNβ+/+ Th17 gene expression profile and in (B) as a fold up or down-regulation compared to the Th17 cells that were not treated with IFN-β. The Figures combine data from two independent experiments.

In a final series of experiments we examined the contribution of IFN-β to Th17 polarization in vivo, specifically using an EAE model of multiple sclerosis, where Th17 cells have been implicated in disease pathogenesis (334). Groups of IFN-β+/+ and IFN-β-/- mice were immunized with MOG peptide to develop EAE and monitored daily for clinical signs of disease, scored 0-5 as described in Materials and Methods. Fifty percent of mice that scored 1-2 (early disease) were sacrificed and their inguinal LNs, spinal cords and brains were harvested for T cell subtype enumeration. The remaining mice with EAE were allowed to progress to late stage disease, scoring 3-4, at which time they were sacrificed and their LNs, spinal cords and brains also harvested. The data in Figure 5 identify both the absolute numbers of CD3+CD4+ and CD4+IL-17+ (Th17) cells in the different compartments, and the percentage of Th17 cells in the CD3+CD4+ population. The results indicate that in the early stages of EAE there are fewer T cells in the LNs of the IFN-β-/- mice (Figure 3.5A), but a greater proportion of these are Th17 cells (Figure 3.5B). Likewise, in late stage disease, there are fewer CD3+CD4+ T cells in the LNs of IFN-β-/- mice than in the LNs of IFN-β+/+ mice, yet a greater proportion of these are Th17 cells in the IFN-β-/- mice. (Figure 3.5 C, D). Examination of the CNS (brain + spinal cord) at early and late stage disease for CD3+CD4+ T cells revealed greater numbers in the brains and spinal cords of IFN-β-/- mice compared with IFN-β+/+ mice, as well as greater numbers of Th17 cells (Figure 3.5 E, G). These results are consistent with egress of T cells from the LNs and their accumulation in the CNS. Notably, in vitro we provide evidence for increased cell surface expression of CXCR4 on CD4+ T cells derived from both IFN-β+/+ and IFN-β-/- mice when activated by anti-CD3/anti-CD28 antibodies (Figure 3.5I), consistent with their potential to migrate across the blood brain barrier mediated by CXCL12, expressed in the CNS (431). Although absolute numbers of Th17 cells in the CNS are greater in the IFN-β-/- mice throughout the course of EAE, as a percentage of the total CNS CD3+CD4+ population we do not observe any notable differences between wildtype and IFN-β null mice (Figure 3.5 F, H). However, as reported in a previous publication, IFN-β-/- mice exhibit a more aggressive disease with earlier onset (data not shown) (204).

Figure 3.5 IFN-β influences Th17 polarization in vivo. EAE was induced in 10 IFN-β+/+ and 10 IFN-β-/- mice. Half of the mice (5 IFNβ+/+ mice and 5 IFN-β-/- mice) were sacrificed when they reached a score between 1 and 2 (early stage EAE) and the remaining half were sacrificed when they scored between 3 and 4 (late stage EAE). Brains and spinal cords (CNS) and draining inguinal LNs were harvested. CD3+CD4+ and CD3+CD4+IL-17A+ cells were enumerated by FACS. Data in A, C, E and G are presented as the mean value +/- standard error (n = 5). The Th17 cell numbers in B, D, F and H are presented as a percentage of the total CD3+CD4+ cell population (n = 5). (I) Splenic CD4+ cells from 3 IFN- β+/+ and 3 IFN-β-/- mice were stimulated with anti-CD3/anti-CD28 antibodies as per as Figure 3 and cell surface CXCR4 expression determined by FACS. Open histograms represent data from IFN-β+/+ mice and filled histograms represent data from IFN-β-/- mice. Data are representative of two independent experiments. Data were analyzed using a Student’s t test. *p = 0.03; **p = 0.002.

3.4 Discussion Accumulating evidence indicates that constitutive low expression of IFN-β in many tissues is required to maintain homeostasis of the immune system and also to prime cells to enable a rapid and robust response to any challenge (reviewed by Gough et al (40)). The loss of priming levels of IFNs compromises different facets of the immunophenotype. Studies in Ifnar1- /- mice have identified a critical role for type I IFNs in maintaining homeostasis of the hematopoietic stem cell compartment (19). Cells of myeloid lineage, including macrophages and dendritic cells, also require constitutive type I IFN expression, to elicit the appropriate response to pathogens and invoke activation of T cells (20-23). The cytotoxicity and abundance of natural killer (NK) cells are regulated by constitutive type I IFN expression: Studies in Ifnar-/- mice revealed fewer NK cells (432) and, in the absence of constitutive IFN, the altered STAT expression in NK cells affects NK targeted cytotoxicity (14, 433, 434). The effects of type I IFNs on T cells are complex. Our earlier studies revealed no significant effects of the lack of constitutive IFN-β expression on CD4 or CD8 T cell numbers (407), supported by later data in Ifnar-/- mice (435). In agreement with our earlier studies (204), the studies described herein demonstrate a regulatory role for IFN-β in activation-induced T cell proliferation, perhaps a consequence of altered STAT regulation, as suggested by studies in Ifnar1-/- mice (197). We identified greater TCR activation in the absence of IFN-β, evidenced by enhanced ZAP-70 phosphorylation. Given the activity of IFN-β as a potent suppressor of proliferation of most cell types, it is intriguing to speculate that the enhanced activation-induced proliferation we observe in the absence of IFN-β may reflect de-repression of specific IFN- inducible factors that are associated with constitutive IFN-mediated tonic signaling to regulate cell growth. IFN-β has been used as a therapy for relapsing-remitting MS for many years, yet its mechanism of action remains poorly defined. As indicated earlier, a number of studies have identified a role for IFN-β in suppressing Th17 lineage commitment and, certainly, Th17 cells are implicated in MS disease pathogenesis (436). By contrast, IFN-β treatment may be associated with IFN-β inducing the expansion of CD4+CD25+FoxP3+ regulatory T cells (392) that would limit the effector functions of Th17 cells. Th17-associated cytokines are also modulated during IFN-β therapy of MS patients. Studies that have analyzed serum IL-17 levels

73 in MS patients on IFN-β therapy have shown differing results. While two studies indicated that IFN-β therapy reduced IL-17 levels (437, 438), another reported that IFN-β therapy increases IL-17 levels (328). IL-23, important for maintenance of the Th17 lineage, is elevated in the serum of MS patients, but decreases once IFN-β therapy is initiated (437). Notably, the Esendagli group (438) identified a gradual increase in serum IL-23 levels over the course of IFN-β therapy. These apparently conflicting data may be attributed to the immunophenotype of responders versus non-responders to IFN-β; given that therapy is only effective in approximately 30% of MS patients, the variability seen in certain serum cytokine levels amongst MS patients may reflect either a failed or lack of sustained response to IFN-β. Our transcriptome analyses indicate that whereas IFN-β treatment apparently does not affect gene expression for IL-17A and IL-17F, under Th17 polarizing conditions, gene expression for IL-17C, IL-17D, IL- 17E (IL-25) and IL-23A is variably downregulated. In addition to affecting serum cytokine levels, cytokine receptor levels on myeloid cells and lymphocytes are subject to regulation by IFN-β. While circulating CD3+IL-17R+ cells decrease in number over the course of IFN-β therapy, circulating IL-23R+ CD4+ lymphocytes are barely detectable, perhaps due to their trafficking to the CNS (438). Ex vivo treatment of MS patient PBMCs with IFN-β results in downregulation of IL-23R and CCR6 expression (391). In addition to being a marker of central memory CD4+ T cells and Th17 cells, CCR6 is a homing receptor for the CNS responding to CCL20 (439). Notably, in our studies we provide evidence for a modest increase in CD4+IL-23R+ cells in response to anti-CD3 and anti-CD28 antibody stimulation, that is nominally amplified in the CD4+ cells derived from IFN-β-/- mice, and a more robust increase in the percentage of CCR6+ cells, with no difference whether the cells were derived from IFN-β+/+ or IFN-β-/- mice. The percentage of CD4+ cells expressing the IL-6R is greater when IFN-β-/- cells are activated by anti-CD3/anti-CD28 antibodies, compared with IFN-β+/+ cells, as are the percentage of double positive CCR6+IL-6R+ and CCR6+IL-23R+ CD4+ cells. We infer from these data that the lack of IFN-β primes CD4+ cells to become Th17 cells, further supported by our results showing increased IL-17A production by IFN-β-/- CD4+ T cells. The migration of Th17 cells into the CNS has been a target of MS therapies, with the development and clinical approval of FTY720 (fingolimod). FTY720 is a S1PR1 agonist that inhibits lymphocyte egress from secondary lymphoid organs. Naïve T cells express S1PR1. Activation leads to S1PR1 downregulation. Upon differentiation to effector T cells, S1PR1 is re-

74 expressed on the cell surface and will respond to the gradient of S1P, which is higher in the lymph. FTY720 acts as an agonist to S1PRs, rendering cells unresponsive to S1P, thereby inhibiting their egress from LNs (275). Importantly, FTY720 acts on central memory T cells as well as naïve T cells, but not on effector memory T cells. In MS patients, Th17 cells are constituents of the central memory compartment and FTY720 treatment in MS patients reduces blood Th17 cell levels (440). In our studies we provide evidence that S1PR1 transcript levels are downregulated upon TCR activation with anti-CD3/anti-CD28 antibodies, and that levels of S1PR1 transcript are indistinguishable between IFN-β+/+ and IFN-β-/- CD4 T cells. However, our transcriptome analysis reveals that in polarized IFN-β-/- Th17 cells the levels of S1PR1 transcript are greater after 96h in culture compared with polarized IFN-β+/+ Th17 cells. Increased expression of S1PR1 transcript may indicate that these IFN-β-/- polarized Th17 cells are primed and, in vivo, would be ready to exit the secondary lymphoid organs. In further support of an effect of IFN-β on SIPR1 expression, when IFN-β is included in the culture to polarize CD4+ T cells to Th17 cells, we identified decreased transcript levels of S1PR1 using our PCR array analysis. These results are consistent with findings that type I IFN decreases S1PR1 expression on CD4+ T cells (181). Again, consistent with these results, we provide evidence for an increased proportion of Th17 cells in the draining LNs of IFN-β-/- mice with EAE compared with IFN-β+/+ mice, with fewer CD3+CD4+ T cells in the LNs of IFN-β-/- mice at both early and late stages of EAE. Concomitantly, we show an increased number of Th17 cells in the CNS of IFN-β-/- mice at both early and late stages of EAE. These data suggest that the lack of IFN-β promotes Th17 lineage polarization and a rapid egress of these cells from the LNs into the circulation and trafficking to the CNS. Our gene expression analysis revealed a role for IFN-β in regulating IRF4 expression, a transcription factor required for Th17 development (422, 423). Th17-associated transcriptome analysis comparing ex vivo polarized IFN-β+/+ and IFN-β -/- Th17 cells, revealed higher expression levels for a number of genes in the IFN-β-/- Th17 cells; e.g. increased Csf2 (GM- CSF) expression (10-fold). GM-CSF has been implicated in influencing Th17 pathogenesis in EAE (113, 114). As mentioned, Il17a expression was also increased (3-fold) in the Th17 cells from IFN-β-/- mice, as was Stat3 (4-fold) expression, another key transcription factor for Th17 development (123). A population of IL-17/IFN-γ-secreting Th17 cells has been identified in

EAE and MS, that are preferentially recruited to the CNS during inflammatory events (308). We observed a 3-fold increase in Stat4 and a 14-fold increase in Ifng expression in the IFN-β-/- Th17 cells, potentially reflecting a greater proportion of IL-17/IFN-γ-secreting Th17 cells in the IFN- β-/- Th17 population. Interestingly, we found that expression levels for Il6ra, Il23r and Rorc were downregulated in IFN-β-/- Th17 cells (2.5-fold, 14-fold, and 2-fold, respectively), perhaps indicative of a completed response to IL-23- and IL-6-induced polarization in the IFN-β-/- CD4+ T cells. Viewed altogether, our data suggest that constitutive IFN-β expression in CD4+ T cells determines the proliferative capacity of the cells, their sensitivity to activation, and subsequent cytokine-inducible polarization to a Th17 phenotype. We have identified a number of molecular targets of IFN-β associated with T cell activation and differentiation that may account for these effects. Our ongoing studies are focused on defining their critical upstream effectors that are regulated by IFN-β.

Chapter 4

Interferon-β regulates dendritic cell activation and migration in experimental autoimmune encephalomyelitis

Pennell LM, Fish EN. Interferon-β regulates dendritic cell activation and migration in experimental autoimmune encephalomyelitis. 2017 (manuscript under review).

LMP performed all experiments, analyzed data, and drafted the manuscript.

Chapter 4: Interferon-β regulates dendritic cell activation and migration in experimental autoimmune encephalomyelitis 4.1 Abstract CD11c+ dendritic cells (DCs) exert a critical role as antigen-presenting cells in regulating pathogenic T cells in multiple sclerosis (MS). To determine whether the therapeutic benefit of interferon (IFN)-β treatment for MS is in part influenced by IFN regulation of DC function, we examined the immunophenotype of DCs derived from IFN-β+/+ and IFN-β-/- mice using a myelin oligodendrocyte glycoprotein (MOG) peptide-induced mouse model of MS, experimental autoimmune encephalomyelitis (EAE). Our earlier work identified that IFN-β-/- mice exhibit earlier onset and more rapid progression of neurologic impairment compared with IFN-β+/+ mice, and that DCs derived from IFN-β-/- mice induce greater proliferation of CD4+ T cells derived from either IFN-β+/+ or IFN-β-/- mice, compared with DCs derived from IFN-β+/+ mice. In this study we provide evidence that LPS/MOG peptide stimulation increases the percentage of DCs expressing CD80 and increases MHCII expression when the DCs are derived from IFN- β-/- mice compared with IFN-β+/+ mice, and that these IFN-β-/- DCs secrete cytokines associated with pathologic Th17 polarization compared with IFN-β+/+ DCs, that secrete cytokines associated with regulatory T cell (Treg) polarization. IFN-β-/- DCs from mice immunized to develop EAE induce greater proliferation of MOG-transgenic CD4+ T cells and promote IL-17 production by these T cells. Adoptive transfer of MOG peptide-primed IFN-β-/- DCs into IFN- β+/+ and IFN-β-/- mice immunized to develop EAE resulted in their rapid migration into the CNS of recipient mice, prior to onset of disease, visualized by fluorescence imaging. Taken together, our data support immunoregulatory roles for IFN-β in the activation and migration of DCs during EAE.

4.2 Introduction Multiple Sclerosis (MS) is an autoimmune disorder characterized by central nervous system (CNS) damage. Approximately 85% of MS patients suffer from a relapsing-remitting (RR) form of MS (292). RRMS is associated with unpredictable, self-limiting bouts of CNS dysfunction, which vary in their frequency and duration. MS is a complex disease with an equally complex pathophysiology, as indicated by the heterogeneity in the level of clinical presentations as well as morphological differences in brain lesions (293). MS is characterized by a profound inflammatory cell infiltrate into the CNS. The migration of inflammatory T cells to the CNS is critical to the development of MS and mice deficient in CD4 or CD8 T cells exhibit a reduced incidence of experimental autoimmune encephalomyelitis (EAE), an animal model of MS (297). Recruitment of inflammatory cells into the CNS requires cells to cross the blood-brain barrier, with its breakdown being one of the initial steps in the development of MS. Chemokine and chemokine receptor expression is critical for inflammatory cell migration, recruitment to the CNS and subsequent disease pathology (441). The chemokine receptors CCR2 and CCR7 are of particular importance in MS and EAE. CCR2-/- mice are resistant to EAE (300), CCR2 expression is observed on CNS infiltrating dendritic cells (DCs) (442) and elevated levels of CCR2 have been found in CNS tissue of MS patients (443). It is well established that CCR7 is required for lymphocyte retention in lymphoid tissues such as lymph nodes (LNs) and several reports suggest the importance of CCR7 expression on lymphocytes in EAE (444) and in MS (445) for CNS recruitment. Both Th1 and Th17 cells are posited to be pathogenic/pro-inflammatory CD4+ T cell subsets in MS (446). Dendritic cells (DCs) facilitate recruitment of T cells into the CNS (447), and are critical antigen presenting cells (APCs) in EAE, driving the Th17 lineage (346). DCs secrete IL-12, associated with Th1 lineage commitment, and TGF-β and IL-6, associated with Th17 polarization (446). In MS, DCs are abundant in brain lesions and, together with microglia function to reactivate CD4+T cells as they enter the CNS, driving myelin-specific Th17/Th1 polarization associated with neuroinflammation, demyelination and neuronal damage. A predominant role for DCs in the pathogenesis of MS is underscored by the association of specific HLA class II molecules with significant genetic risk linked to MS (448). DCs are sufficient to induce autoimmunity in the CNS (344); increasing their numbers exacerbates EAE (449), and their depletion ablates the induction of EAE (442). By contrast, some reports have

79 suggested a tolerogenic role for DCs in the context of T cell priming and activation in EAE (351, 450). Viewed together, these findings highlight the importance of DCs in CNS autoimmunity. IFN-β remains one of the first line treatments for patients with RRMS. IFN treatment has shown benefits in outcome measures related to relapses, progression of disability and magnetic resonance imaging (MRI). IFN-β exhibits pleiotropic effects in MS, including modulation of adhesion molecule expression, inhibition of matrix metalloproteinase activity and regulation of leukocyte trafficking (451). In EAE, IFN-β reduces relapse rates and leads to improvements in clinical scores (368). IFN-β-/- mice have been used in EAE studies to validate the importance of IFN-β treatment in limiting the pathogenesis of the disease (204, 369) and in relapsing-remitting EAE, where there was evidence of increased frequency of relapses (369). We and others have shown regulatory roles for IFN-β in Th17 cell polarization (452, 453). IFN- β treatment decreases IL-17 gene and protein expression in proliferating murine CD4+ cells and prevents the elevation of IL-17 mRNA in cells from the CNS draining lymph node (387). In this report we describe a role for IFN-β in regulating the DC immunophenotype, affecting DC effects on T cell activation, Th17 lineage polarization and DC migration in EAE.

4.3 Results Our earlier studies identified that IFN-β-/- mice are more susceptible to EAE than IFN- β+/+ mice (204). Given that in MS DCs drive the Th1/Th17 T cell polarization associated with neuroinflammation, we undertook a series of experiments to determine whether the absence of IFN-β might influence cytokine production by DCs, thereby affecting T cell polarization. Accordingly, we generated bone marrow derived DCs (BMDC) from IFN-β+/+ and IFN-β-/- mice in vitro and stimulated these DCs with the TLR4 agonist, LPS, for 16 hours. Culture supernatants from these activated BMDCs were analyzed for Th1/Th2/Th17/Th22 cytokines. Our data reveal increased IL-6 (Figure 4.1A) and decreased TNF-α, IL-27 and IL-10 production (Figure 4.1B-D) from activated IFN-β-/- BMDCs compared with activated IFN-β+/+ BMDCs, suggestive of a pro-Th17 environment generated by IFN-β-/- DCs and a pro-Treg environment generated by IFN-β+/+ DCs.

Figure 4.1 Activation of IFN-β+/+ and IFN-β-/- DCs leads to differential cytokine production. Bone marrow was isolated from the femurs of IFN-β+/+ (open bars) or IFN-β-/- (filled bars) mice and DCs were generated in vitro using GM-CSF (40 ng/mL). After 10 days in culture, DCs were harvested, stimulated with LPS (1 µg/mL) for 16h, and the culture supernatants were assessed for cytokines by multiplex cytokine analysis. Data for A) IL-6 B) TNF-α, C) IL-27 and D) IL- 10 are shown. Significant differences were determined by Student’s t test. *p <0.05, **p <0.01, ***p <0.001. Data are representative of 2 independent experiments with 3 mice per group.

In our earlier publication we also provided evidence that DCs derived from IFN-β-/- mice induce a greater MOG-specific CD4 T cell proliferation, regardless of whether the CD4 T cells originated from IFN-β+/+ or IFN-β-/- mice, compared with DCs isolated from IFN-β+/+ mice (204). To further investigate this effect of IFN-β on DC mediated T cell proliferation, we examined DC:T cell co-cultures using CD4+ T cells isolated from 2D2 transgenic mice. 2D2 CD4+ T cells are MOG-specific, eliminating the need to generate antigen-reactive T cells by inducing EAE. In Figure 4.2 we provide evidence for greater proliferation when the 2D2 CD4+ T cells are cultured with LPS-activated splenic CD11c+ DCs isolated from IFN-β-/- mice compared with CD11c+ DCs isolated from IFN-β+/+ mice. Notably, although co-culture of DCs and 2D2T cells with MOG peptide alone does increase proliferation of the T cells, TLR4 activation of the DCs by LPS enhances this proliferative response to a greater extent.

Figure 4.2 DCs from IFN-β-/- mice drive increased MOG-transgenic CD4+ T cell proliferation. CD11c+ DCs were isolated from the spleens of IFN-β+/+ and IFN-β-/- mice and either left untreated or treated with 1 µg/mL LPS for 16h. MOG-transgenic CD4+ T cells were isolated by positive selection and labeled with Cell Proliferation Dye (CPD). 1 x 105 CD4+ T cells were cultured with 5 x 104 CD11c+ DCs. A) Representative plots of CD4+ T cell dye dilution for each culture condition. 2D2 T cells were cultured with IFN-β+/+ (top row) or IFN-β-/- (bottom row) DCs. Culture conditions were as follows: (i) unstimulated DCs with 2D2 T cells, (ii) unstimulated DCs with 2D2 T cells in the presence of MOG peptide or (iii) LPS stimulated DCs with 2D2 T cells in the presence of MOG peptide for 48 hours. Following culture, cells were stained and CD4+ T cell proliferation was assessed. B) Quantification of replicate samples of CD4+ T cells are shown (n = 4 mice with 3 technical replicates per mouse). Significant differences were measured by Student’s t-test. *p = 0.004. Data are representative of 2 independent experiments.

As we have consistently observed a discriminating capacity for IFN-β-/- CD11c+ DCs to enhance T cell proliferation, we investigated whether this might be a direct consequence of MHCII and co-stimulatory molecule expression. At the outset we identified that a greater percentage of IFN-β-/- CD11c+ DCs constitutively express CD80 (5.5%) compared with naïve IFN-β+/+ CD11c+ DCs (3.3%) (Figure 4.3A). By contrast, we identified a modest, yet significant increase in the percentage of IFN-β+/+ CD11c+ DCs expressing CD86 constitutively (5.4%), compared with IFN-β-/- CD11c+ DCs (4.1%) (Figure 4.3B). As anticipated, LPS treatment led to DC activation, indicated by increased percentages of CD80+ and CD86+ expressing CD11c+ DCs, and increased MHCII expression (Figure 4.3C). Although LPS stimulation activated both IFN-β+/+ and IFN-β-/- DCs, the percentage of DCs expressing CD80, was significantly increased in IFN-β-/- DCs (16%) compared to IFN-β+/+ DCs (10.7%) (Figure 4.3A). We observed a modest, yet significant increase in the percentage of CD86 expressing DCs when derived from IFN-β+/+ (43.8%) compared with IFN-β-/-mice (35.5%), after LPS stimulation (Figure 4.3B). When considering MHCII expression, we observed that >95% of the DCs were positive for MHCII, whether this was constitutive expression or following LPS stimulation (data not shown). However, examination of MFI revealed that the level of MHCII expression was different between IFN-β+/+ versus IFN-β-/- splenic DCs. Specifically, in unstimulated DCs we found that MHCII expression was elevated on DCs from IFN-β-/- compared with IFN-β+/+ mice (Figure 4.3C). Furthermore, LPS stimulation significantly increased MHCII expression to a greater extent on the IFN-β-/- DCs compared with the IFN-β+/+ DCs (Figure 4.3C).

Figure 4.3 LPS stimulation modulates co-stimulatory molecule and MHCII expression on splenic DCs from IFN-β+/+ and IFN-β-/- mice. Splenocytes were isolated from naïve IFN-β+/+ (open bars) and IFN-β-/- (closed bars) mice and stimulated for 16h with LPS (1 µg/mL). Cells were stained with the relevant antibodies as described in Materials and Methods. DCs were gated as CD45+CD3-CD11c+. The percentage of cells expressing A) CD80 and B) CD86 and the mean fluorescence intensity of C) MHCII are shown. Significant differences were measured by the Mann-Whitney U test. *p<0.05, **p<0.01, ***p<0.001, and ****p<0.0001. Data are representative of at least 3 independent experiments with 3 mice per group and 3 technical replicates per mouse.

Activation of DCs using LPS may differ from activation of DCs in the context of EAE induction, since TLR agonists are known potent activators of DCs (454). When IFN-β-/- and IFN-β+/+ mice were induced to develop EAE, then their draining LNs harvested at 72 hours post induction and before symptom onset, we observed an increased percentage of CD80+ DCs and increased MHCII expression on DCs from IFN-β-/- mice compared with the DCs from IFN-β+/+ mice (Figure 4.4A). Additionally, when co-cultured with 2D2 T cells, these IFN-β-/- DCs induced a greater proliferation of the T cells than their IFN-β+/+ counterparts, yet this proliferative response by the 2D2 T cells required the presence of MOG peptide (Figure 4.4B). Examination of the culture supernatants from these experiments showed that for the IFN-β-/- DCs co-cultured with 2D2 CD4+ T cells in the presence of MOG peptide, there were increased levels of IL-6, IL-17A, IL-23, and IFN-γ compared to the co-cultures with IFN-β+/+ DCs (Figure 4.5). IL-12p40 levels detected were similar, regardless of whether IFN-β-/- or IFN-β+/+ DCs were present in the co-cultures (Figure 4.5).

Figure 4.4 DCs from IFN-β-/- mice with EAE have increased CD80 and MHCII expression and drive increased proliferation of MOG-transgenic CD4+ T cells. CD11c+ DCs were isolated from the draining lymph node of IFN-β+/+ mice and IFN-β-/- mice 72h after EAE induction. CD4+ T cells were collected by positive selection from the spleens of MOG-transgenic (2D2) mice and labeled with Cell Proliferation Dye (CPD). 1 x 105 CD4+ T cells were cultured with 5 x 104 CD11c+ DCs in the absence (EAE) or presence (EAE+MOG) of MOG peptide for 72h, when CD4+ T cell proliferation was assessed, as described in Materials and Methods. A) Cells were gated as MHCII+ CD11c+ and CD80+ (LHS), and the MFI of MHCII expression on CD11c+ cells (RHS) is shown. B) Representative plots of CD4+ T cell dye dilution for 2D2 T cells cultured with IFN-β+/+ or IFN-β-/- DCs (LHS) and quantification of replicate samples of CD4+ T cells (RHS). Significant differences were measured by Student’s t-test. *p < 0.05, *** p = 0.0002. Data are representative of 2 independent experiments with 5 technical replicates of 3 pooled mice per group.

Figure 4.5 Activated IFN-β-/- DCs produce pro-Th17 cytokines and drive Th17 polarization ex vivo. CD11c+ DCs were isolated from the draining LN of IFN-β+/+ (open bars) and IFN-β-/- (filled bars) mice 72h after EAE induction. CD4+ T cells were collected by positive selection from the spleens of MOG-transgenic (2D2) mice. 1 x 105 CD4+ T cells were cultured with 5 x 104 CD11c+ DCs (EAE) or in the presence of MOG peptide (1 µg/mL) (EAE+MOG) for 72h. Cytokines (IL-6, IL-12p40, IL-23, IL-17A and IFN-γ) in culture supernatants were measured by ELISA. Significant differences were measured by Student’s t-test. *p < 0.05, **p < 0 .01, and ***p < 0.001, ****p < 0.0001. UD = cytokine undetectable, ns = not significant. Data are representative of 2 independent experiments with 3 technical replicates from 3 pooled mice per group.

DCs that express CCR7 respond to gradients of CCL19 and CCL21, directing them to the T cell zones of lymphoid organs where they interact with and activate naïve T cells. Moreover, DCs in CNS lesions have been shown to express CCR7 (445). CCR2 expression has been extensively studied in EAE, with data indicating CCR2-/- mice having fewer CNS infiltrating T cells and macrophages (300). We analyzed the surface expression of CCR2 and CCR7 on BMDCs before and after 16 h of LPS treatment and found that basal CCR2 expression was similar between IFN-β+/+ and IFN-β-/- BMDCs, and while CCR2 expression was increased after LPS stimulation, there was no significant difference in expression on the IFN-β-/- compared with the IFN-β+/+ DCs (Figure 4.6A, LHS). By contrast, basal CCR7 expression was significantly elevated on IFN-β-/- BMDCs compared with IFN-β+/+ BMDCs and was also increased to a greater level after LPS stimulation (Figure 4.6A, RHS). One of the proposed mechanisms of action of IFN-β is to inhibit migration of DCs by modulation of CCR7 expression. This requires a functional STAT1, since studies have shown that CCR7 expression is not altered in response to IFN-β treatment in STAT1-deficient BMDCs (289). STAT1 activation is a key component of IFN-β signaling that leads to induction of IFN-inducible gene expression (51). Not surprisingly, IFN-β-/- macrophages have been shown to be deficient in their ability to activate STAT1 in response to LPS (21, 455). Cognizant that IFN-β influences CCR7 expression, mediated by STAT1, we examined whether the effects of LPS on CCR7 expression might reflect differences in STAT1 expression between IFN-β+/+ and IFN-β-/- DCs. While basal levels of STAT1 gene expression were comparable between IFN-β+/+ and IFN-β-/- BMDCs, we found that LPS stimulation increased STAT1 expression 3 fold in BMDCs from IFN-β+/+ mice, yet had no effect on STAT1 gene expression in BMDCs from IFN-β-/- mice (Figure 4.6B).

Figure 4.6 IFN-β affects CCR7 expression on DCs thereby contributing to their migratory capacity to the CNS. Cell surface expression of CCR2 and CCR7 on A) LPS-matured BMDC (gated on CD45+CD11c+CD11b+) from IFN-β+/+ (WT, n = 4) or IFN-β-/- (KO, n = 4) were analyzed . Statistical differences were calculated using the Mann-Whitney U test. *p<0.05. B) BMDCs were generated from IFN-β+/+ (n = 3) and IFN-β-/- (n = 3) mice, cultured for 9 days as described in the Materials and Methods, then treated for 6h with 1 µg/mL LPS. RNA was extracted, cDNA prepared and gene expression for STAT1 determined. C), Cultured BMDCs (9 days) from IFN-β+/+ (n = 3) and IFN-β-/- (n = 3) mice were LPS matured for 16h, pulsed with MOG peptide (3h) and labeled with CellVue Maroon. DCs were adoptively transferred into IFN-β-/- or IFN-β+/+ recipient mice on day 3 of EAE and DC migration to brains, spinal cords and spleens were assessed at 24 and 72h post DC infusion using a Xenogen IVIS fluorescence imager. Images are representative of 3 mice per group, per time point.

In a final series of experiments we examined the effects IFN-β on DC migration to the CNS in the context of EAE. In vitro generated BMDCs, derived from IFN-β+/+ and IFN-β-/- mice, were stimulated with LPS and MOG peptide, labeled with fluorescent CellVue Maroon, then introduced by intravenous injection into recipient mice, both IFN-β+/+ and IFN-β-/-, on day 3 post induction of EAE. As early as 24 and 72 hours post DC infusion, we detected the presence of the labeled DCs in the spleens, spinal cords and brains of all recipient mice, regardless of the source of the DCs (Figure 4.6C). Notably, at 24 and 72 hours post-infusion, none of these mice displayed any symptoms of EAE. At both 24 and 72 hours post-infusion we observed a greater accumulation of DCs in the brains of IFN-β-/- mice compared with the brains of IFN-β+/+ mice. Additionally, the greatest accumulation of DCs in the brain was exhibited in IFN-β-/- mice that were infused with IFN-β-/- DCs. Analysis of the spinal cords of the IFN-β+/+ and IFN-β-/- mice, at both 24 and 72 hours post-infusion, suggested little accumulation of DCs and no apparent difference whether the DCs were derived from IFN-β+/+ or IFN-β-/- mice, or whether they were infused into IFN-β+/+ or IFN-β-/- mice induced to develop EAE. Examination of spleens revealed that there was the greatest accumulation of DCs when IFN-β-/- DCs were infused into IFN-β-/- mice induced to develop EAE, at both time points.

4.4 Discussion DCs represent an important component of the immune system, bridging the innate and adaptive immune responses: detecting and presenting antigens to T cells to induce an appropriate immune response and generate subsequent immunological memory. DCs may also present self-antigens to T cells, effecting a breakdown in tolerance, leading to autoimmunity and detrimental immune responses against tissues and organs. As such, identifying the specific effects of disease modifying treatments in MS on DCs is important, since there is evidence that modifying DC function influences disease progression in EAE (344, 442, 447). As IFN-β therapy remains an important treatment for MS, the molecular mechanisms involved in its beneficial effects related to DCs were the subject of these studies. MS patients have higher levels of pro-inflammatory cytokines in their serum and blood (456, 457). IFN-β treatment alters cytokine profiles in EAE and in MS patients, increasing regulatory or anti-inflammatory cytokines (383), and decreasing pro-inflammatory cytokines (391). DCs secrete pro- and anti-inflammatory cytokines in MS and EAE, which guide T cell

91 differentiation. IL-27 has been implicated in regulating Th17 responses in murine EAE experiments and in human CD4+ T cells (360, 458). There is evidence that IFN-β treatment of both mouse and human DCs in vitro leads to IL-27 as well as IL-10 production (287, 383). Additionally, DCs generated from MS patients that respond to IFN-β therapy produce more IL- 27 in response to IFN-β treatment, compared to non-responders (383). In agreement, we identified that IFN-β-/- DCs stimulated with LPS produced less TNF-α, IL-10 and IL-27, associated with Tregs, yet produced more IL-6, compared with IFN-β+/+ DCs. The increase in production of IL-6 by IFN-β-/- DCs may contribute to polarization of CD4+ towards a Th17 cell lineage, as IL-6 is required for Th17 cell differentiation and inhibits Treg polarization (459). These data are supportive of a role for IFN-β regulating DC production of cytokines that affect CD4+ T cell polarization. These results align with our previous findings of increased CD4+ IL- 17A+ T cells in IFN-β-/- mice, associated with exacerbated EAE (383, 457). We infer that in the presence of IFN-β, activated DCs will limit CD4+ T cell polarization to pathogenic Th17 cells, thereby contributing to less severe EAE, or MS. While a number of reports have indicated a role for IFN-β in limiting IL-17 production in MS and EAE (387, 452, 453, 456) , recent work by Axtell and others indicated that IFN-β could exacerbate Th17-induced EAE (328). Herein we provide evidence that the absence of IFN-β in DCs led to induction of pro-inflammatory cytokines IL-6, IL-23, IL-17 and IFN-γ when cultured with 2D2 transgenic CD4+ T cells. IFN-β-/- DCs produced more of the Th17- polarizing cytokines IL-6 and IL-23 which may drive the increased IL-17 production in this 2D2 context. In earlier studies we showed that CD4+ T cells from IFN-β-/- mice polarized more readily to the Th17 lineage (204) and that IL-6R and IL-23R were both up-regulated on activated IFN-β-/- CD4+ T cells (452). This suggested a role for IFN-β in T cells, influencing polarization toward the Th17 lineage and our current study suggests that IFN-β may also regulate Th17-polarizing cytokine production by DCs. We identified equivalent production of the IL-12 and IL-23 common subunit, IL-12p40, in IFN-β+/+ and IFN-β-/- DC:T cell co-cultures, yet increased IFN-γ in the IFN-β-/- DC:T cell co-cultures. Given the cytokine data we present in Figure 4.5, we estimate that the ratio of Th1:Th17 cells would be ~6:1 in the IFN-β-/- DC co- culture with 2D2 T cells, and ~7:1 in the IFN-β+/+ DC co-culture with 2D2 T cells. This may be a consequence of the increased capacity of IFN-β-/- DCs to activate 2D2 CD4+ T cells and/or that these 2D2 T cells produce large quantities of IFN-γ in a recall response to MOG peptide

(320). The DCs cultured with the 2D2 T cells were harvested from mice 72h after disease induction, a time point when it is unlikely that early T cell activation produces sufficient cytokines to influence DC activation. Taken together with our data indicating a role for IFN-β in regulating expression of MHCII and CD80 on DCs, we postulate that IFN-β is required by DCs to limit interactions with CD4+ T cells that lead to their activation and polarization to the Th17 lineage. One of the proposed mechanisms of IFN-β action in MS is to regulate cell proliferation. In our earlier work, we provided evidence that IFN-β-/- splenocytes are hyper-proliferative in response to non-specific stimuli (407). IFN-β exerts antiproliferative effects when added to peripheral blood monocyte cultures from MS patients, inhibiting the proliferation of both CD4+ and CD8+ T cells (460). Given these inhibitory effects of IFN-β on T cell proliferation, we postulated that IFN-β may regulate the DC contribution to proliferation of T cells, herein supported by our data that DCs from IFN-β-/- mice induce a greater proliferation of CD4+ T cells than DCs derived from IFN-β+/+ mice (Figure 4.2). Circulating DCs in MS patients have elevated levels of co-stimulatory markers when compared to healthy controls (349), and MS patients have more activated cDCs in their CSF compared to their blood (348). APCs in the CNS have been implicated in re-activation of T cells during EAE. Teige et al provided evidence that IFN-β down-regulates the antigen presenting capacity of CNS glial cells, thereby potentially resulting in less efficient activation of autoreactive T cells in EAE (461). In the priming phase, in lymphoid tissues, we hypothesized that IFN-β may function to regulate both proliferation and T helper cell polarization/activation, mediated by IFN-β effects on DCs. In this study we found that treatment of splenic DCs with LPS led to their anticipated activation, detected as increased levels of MHCII, and an increase in the percentage of CD80+ and CD86+ DCs. Notably, we identified that LPS stimulation of IFN-β-/- DCs resulted in enhanced levels of MHCII compared with IFN-β+/+ DCs and increased the percentage of CD80+ DCs, in support of a heightened capacity for IFN-β-/- DCs to activate T cells. While MFI was not increased for CD80 or CD86 (data not shown), we infer that an increased percentage of cells expressing these activation markers would confer an increased capacity to induce T cell proliferation. In the EAE setting, we identified a greater percentage of DCs expressing CD80 and increased expression of MHCII on CD11c+ DCs from the LNs of IFN-β-/- mice compared to IFN-β+/+ mice, while the expression of CD86 did not differ with IFN-

β status of the DCs (Figure 4.4 and data not shown). Interestingly, pDCs from MS patients treated with IFN-β exhibit decreased expression of MHCII and CD86 (462). MS patients that do not respond to IFN-β treatment have increased expression of CD86 on their myeloid DCs, compared to MS patients that respond to IFN-β therapy (463). Given that IFN-β therapy is only effective in about 30% of MS patients, the variable response to IFN-β therapy may reflect the variable responsiveness of different DC populations to IFN-β, the subject of our ongoing investigations. Migration of DCs to the CNS, orchestrated by chemokines that interact with CCR2 and CCR7, is critical for re-activating T cells during EAE (344, 442, 449). While we did identify an increase in CCR2 expression on BMDCs in response to LPS treatment, this was IFN-β- independent. Studies have identified the importance of the CCR7 ligands CCL19 and CCL21 for maintaining an inflammatory state in the CNS during EAE (444, 464) and there is evidence for CCR7+ cells accumulating in the CNS during MS (445, 465). We previously showed that LPS stimulated IFN-β-/- bone marrow derived macrophages had lower gene expression of STAT1 and were deficient in their ability to phosphorylate STAT1 compared with their IFN-β+/+ counterparts (21). Additionally, it has been shown that treatment of IFN-β-/- macrophages with IFN-β will induce STAT1 phosphorylation and restore IFN-β-inducible gene expression (455). Another study identified that IFN-β treatment inhibited DC migration, through STAT1 transcriptional inhibition of CCR7 (289). We provide evidence that IFN-β-/- BMDCs are unable to induce STAT1 gene expression upon LPS stimulation. Given our earlier published observation that LPS stimulation of IFN-β-/- bone marrow-derived macrophages (BMMs) leads to blunted STAT1 phosphorylation compared with IFN-β+/+ BMMs, we infer that a similar blunted STAT1 phosphorylation would occur in the IFN-β-/- BMDCs. We also found that IFN- β-/- BMDCs have increased surface expression of CCR7 when compared to IFN-β+/+ BMDCs, whether naïve (unstimulated) or in response to LPS stimulation. At an early time point post EAE induction, we observed a trend toward increased CCR7 expression on DCs in the spleens and LNs of IFN-β-/- mice compared with CCR7 expression on DCs from IFN-β+/+ mice, albeit not significant (data not shown). These findings are in agreement with IFN-β inhibiton of CCR7 mediated by STAT1 reported by Yen et al, suggestive of a role for endogenous IFN-β in the regulation of CCR7. While CCR7-/- mice are not protected from EAE and appear to develop disease comparable to CCR7+/+ mice, T cell responses are restricted to the spleen, and absent in

LNs, indicative of aberrant T cell migration (281). However, this study did not address the migration of DCs or T cells to the CNS in the absence of CCR7. In the BMDC adoptive transfer experiment described herein, we provide evidence that BMDCs generated from IFN-β-/- mice rapidly migrate to the CNS of mice primed for EAE, in the absence of clinical scores. Our findings support the notion that one of the immunoregulatory roles of IFN-β during neuroinflammation is to limit DC migration, in part mediated through STAT1 transcriptional inhibition of CCR7. Taken together, our data highlight an important role for IFN-β in regulating the interactions of T cells and DCs in the context of EAE. We show that IFN-β is required to modulate the function of DCs in terms of antigen presentation and co-stimulation of T cells, and regulates DC cytokine production that determines T cell lineage commitment. We point to a role for IFN-β in regulating migration of DCs into lymphoid tissues and the CNS during EAE. Our findings of immunoregulatory properties of IFN-β in DCs in the context of EAE provide further support for consideration of DC-targeted therapies in MS.

Chapter 5

Discussion & Future Directions

Chapter 5: Discussion and Future Directions 5.1 Thesis Summary In this thesis, we aimed to determine the regulatory roles for IFN-β in T cells and DCs. IFN-β acts on different cell populations to exert diverse effects. We hypothesized that IFN-β may exert an influence on both T cells and DCs to control the Th17 population in a mouse model of MS, EAE. In previous publications using IFN-β-/- mice, our group showed that T cells were hyper-proliferative in response to TCR stimulation, and when co-cultured with DCs from mice with EAE (204, 407). In Chapter 3 of this thesis, we identified that purified CD4+ T cells isolated from IFN-β-/- mice responded to TCR stimulation with enhanced phosphorylation of ZAP-70, increased production of IL-17A in the absence of Th17-inducing cytokines, had increased expression of the transcription factor Irf4, and had increased surface expression of Th17-associated cytokine receptors, when compared to CD4+ T cells from IFN-β+/+ mice. We also identified that polarized CD4+ T cells from IFN-β-/- mice compared to CD4+ T cells from IFN-β+/+ mice had increased expression of Th17-associated genes, while treatment of IFN-β+/+ Th17 cells with IFN-β globally down-regulated the expression of many Th17-associated genes. Furthermore, we identified more Th17 cells in IFN-β-/- mice with EAE in their LNs and CNS during the course of disease. While Chapter 3 showed that the lack of IFN-β led to a dysregulation in the Th17 lineage, we undertook investigations to determine whether this was an effect on T cells alone, or whether IFN-β regulated the DC contribution to Th17 lineage polarization. In Chapter 4 we identified that IFN-β-/- BMDCs produce more IL-6 and less IL-10 and IL-27 in response to LPS stimulation. We also found that CD11c+ DCs isolated from naïve IFN-β-/- mice and stimulated with LPS could drive increased proliferation in IFN-β sufficient 2D2 transgenic CD4+ T cells. Furthermore, LPS stimulation increased CD80 and MHCII on IFN-β-/- CD11c+ DCs, suggesting a possible mechanism for the increase in 2D2 T cell proliferation observed. We also found that CD11c+ DCs isolated from IFN-β-/- mice with EAE could drive increased proliferation of 2D2 T cells compared to CD11c+ DCs from IFN-β+/+ mice, and this, again, we associated with increased expression of CD80 and MHCII on IFN-β-/- DCs. In co-culture, DCs from IFN-β-/- mice produced more pro-Th17 cytokines, and drove production of IL-17 by 2D2 T cells. Finally, we showed that BMDCs from IFN-β-/- mice had increased CCR7 expression on their

97 surface after LPS treatment, and that IFN-β-/- BMDCs migrated more readily to the CNS of mice primed to induce EAE. Taken together, these data identified that IFN-β plays a role in both T cells and DCs to regulate the Th17 lineage. Refer to Figure 5.1 for a graphical representation of these findings. In T cells, IFN-β limits the expression of Th17-associated genes and cytokine receptors and limits production of IL-17 in response to TCR stimulation. In DCs, IFN-β appears to prevent upregulation of CD80 and MHCII, as well as production of Th17-associated cytokines, which would then act on CD4+ T cells to drive their proliferation and differentiation into Th17 cells.

Figure 5.1 Immunoregulatory effects of IFN-β on DCs and CD4+ T cells. IFN-β acts on DCs and CD4+ T cells to regulate Th17 cell differentiation and effector function, by limiting cytokine production, cytokine receptor expression, and co-stimulatory molecule expression.

5.2 Discussion and areas of future study While our data have provided some insights into the regulatory functions of IFN-β in T cells and DCs, several important questions arise from these findings and should be addressed in future work. In a preliminary study, we set out to determine whether breeding IFN-β-/- mice onto a 2D2 TCR transgenic mouse background might increase disease incidence, given the potential protective roles for IFN-β in T cells and in DCs during EAE. In 2D2 mice, the incidence of spontaneous EAE is approximately 4% (320). In our preliminary studies, we identified an incidence of approximately 15% in the F2 population which were 2D2+ and IFN-β+/- or IFN-β-/-. Our preliminary immunophenotyping work revealed that an F2 mouse from this cross that developed signs of disease had a reduction in the NK1.1+ cell population that was not reflected in the 2D2+ healthy mouse (IFN-β sufficient). These cells may represent natural killer (NK) cells, which have been implicated in controlling both MS and EAE (466). Additionally, IFN-β therapy appears to increase the NK cell population in MS patients (467). Notably, we did not conduct an extensive characterization of the immune cells in the lymphoid organs and CNS tissue of mice showing signs of disease. It will be important to determine whether different T cell and DC subsets are perturbed in the IFN-β-/-.2D2 EAE model, as we would expect an increase in Th17 cells in the 2D2+ IFN-β-/- animals. Since we did not genetically characterize whether the sick vs. healthy F2 mice were homozygous or heterozygous, respectively, for the IFN-β gene deletion, subsequent studies need to address this. However, we suspect that F2 healthy animals were heterozygous for IFN-β, while sick animals were homozygous for the IFN-β deletion. In both settings (homozygous for IFN-β deletion and heterozygous for IFN-β deletion), it will be important to determine the effects of IFN- production by DCs in response to stimulation, as well as during disease. This model presents an interesting opportunity to study the effect of IFN-β on spontaneous disease induction, and may be more relevant to patients with MS, who may have low serum levels of IFN-β prior to starting therapy (388, 468), - should the IFN-β heterozygous mice present a similar phenotype. One interesting observation in this study was that one female F2 mouse developed signs of disease at over 52 weeks of age, while the mean age of onset was 15 weeks for the rest of the mice in the study. This older female mouse had been pregnant and gave birth before showing signs of disease. During a second pregnancy after disease onset, signs of disease appeared to improve, but returned after delivery. This was not unexpected, as hormonal fluctuations in the

100 menstrual cycle affect MS relapses. For female MS patients, symptoms may worsen in the pre- menstrual luteal phase, which may be accompanied by increased lesions identified by MRI. On the other hand, during pregnancy females experience fewer relapses, with relapses returning post-partum (469). It is possible that increased levels of immunosuppressive IL-10 in the third trimester and a Th2 skew in cytokine production and responses are responsible for the decrease in relapses during pregnancy, while post-partum relapses may be associated with increased IL-8 production (470). How IFN-β affects the cellular contributions to disease in these female 2D2+ IFN-β-/- mice should be examined, to determine whether IFN-β might exert protective effects during pregnancy given its known effect of inducing IL-10 in MS patients. The regulatory effects of IFN-β on T cells and DCs may be exerted by a number of different negative regulators. First, negative regulation by IFN-β in T cells and in DCs by SOCS proteins should be considered. The SOCS proteins are induced upon activation of type I and type II cytokine receptors, including IFN activation of IFNAR, and function as feedback inhibitors to inhibit activation of STAT-inducible genes (471, 472). This might include cytokine genes (and their products) that can induce Th17 cells. SOCS proteins can also be induced upon TLR ligation and function to fine-tune the inflammatory response associated with TLR signaling (473). SOCS1 knockout DCs were shown to have an aberrant activation phenotype, leading to the induction of autoimmunity (474). Taken together, SOCS proteins have roles in both innate and adaptive immunity and may be important regulators of T cells as well as DC activation and the phenotype we have observed in EAE. In some preliminary analysis of DCs from IFN-β-/- mice, we found that Socs1 gene expression was downregulated (6.5 fold) in DCs isolated from naïve IFN-β-/- mice compared to DCs isolated from IFN-β+/+ mice. In CD4+ T cells from IFN-β-/- mice, Socs1 was downregulated 2.2 fold when compared with CD4+ T cells from IFN-β+/+ mice. In both cases, only naïve DCs and T cells were analyzed, and it would be important to determine whether the same trend is observed when the cells were stimulated either with TLR agonists or TCR stimulation, respectively. Interestingly, SOCS1-/- T cells are impaired in their ability to become Th17 cells, while they can still effectively become Th1 cells (475). In these studies STAT1 expression appeared to be dysregulated and increased due to the lack of inhibition by SOCS1. This led to SOCS3 induction and suppression of STAT3, and the inhibition of Th17 cells, while the increased STAT1 allowed for polarization to the Th1 lineage. Therefore, investigation of the lack of induction, rather than lack altogether, of Socs1 in the absence of

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IFN-β should be undertaken to determine if IFN-β inducible Socs1 is necessary to limit Th17 cells. Certainly, Socs1 and Socs3 are upregulated by IFN-β in astrocytes (476). Additionally, there is some evidence for increases in Socs1 and Socs3 expression in IFN-β treated MS patients, though this information was gleaned from published meeting abstracts and not peer- reviewed publications. We propose investigating the induction of Socs1 and Socs3 gene expression, as well as measuring SOCS1 and SOCS3 protein levels, in T cells and DCs, from IFN-β+/+ and IFN-β-/- mice, during activation and in response to treatment with IFN-β. Furthermore, the negative regulation of T cells and DCs by IFN-β may be mediated through microRNAs (miRs). miRs are short (~22nt), non-coding, single-stranded RNAs that regulate protein expression, through activation or repression of mRNA translation (477-479). Dysregulated miR levels contribute to the development of different diseases, including neurological diseases, such as MS (480-483). In MS, miR dysregulation in the immune system has been identified in naive T cells, memory T cells, Th17 cells, Tregs and B cells. IFN-β may affect miR expression, thereby contributing to altered gene expression in immune cells. Certainly, miR changes have been identified during IFN-β treatment in MS (482, 484). miR-155 modulates Treg and Th17 cell differentiation (485) and has also been shown to regulate myeloid cell polarization in MS (486). miR-155 targets the negative regulators SH2-containing inositol phosphate 5’ phosphatase (Ship1) and Socs1, promoting T cell activation (487). In a preliminary study, we found that naïve splenic IFN-β-/- CD4+ T cells express higher levels of miR-155 compared with IFN-β+/+ T cells, and that following anti-CD3 and anti-CD28 activation this expression bias persists. It would be interesting to address the induction of miR-155 following treatment with IFN-β, in both IFN-β-/- and IFN-β+/+ T cells, to determine whether we can confirm our preliminary findings. Importantly, the inhibition of miR-155 by IFN-β may be part of the mechanism by which IFN-β regulates CD4+ T cell proliferation, and so we might expect to see induction of miR-155 during T cell proliferation and Th17 polarization in IFN-β-/- T cells, and to a lesser extent, if at all in IFN-β+/+ T cells. miR-155 overexpression in DCs reduced expression of Ship1, leading to a breakdown in tolerance and increased expression of IL-6 (488). If IFN-β is necessary to control miR-155 expression in DCs, then this miR may contribute to the regulation of inflammatory cytokine production by IFN-β. Investigating the expression of miR- 155 during IFN-β treatment and TLR-induced activation of IFN-β+/+ and IFN-β-/- DCs could reveal a regulatory role for IFN-β in this context. Profiling of other miRs by miRNA arrays, in

102 the presence or absence of IFN-β treatment and during activation of both IFN-β+/+ and IFN-β-/- T cells and in DCs, should also be conducted, to determine the effects of IFN-β on other miRs and possible involvement in the suppression of DC and T cell activation. In Chapter 3 we provided evidence that Irf4 expression increased in IFN-β-/- CD4+ T cells compared to IFN-β+/+ CD4+ T cells, upon TCR stimulation. Given this observation in IFN- β-/- T cells, it is of interest to determine whether Irf4+ DCs also increase in numbers compared to Irf8+ DCs in the IFN-β-/- mice. From the literature, it appears that CD11b+ Irf4+ DCs are implicated in Th17 responses. Previous work on CD11b+ DCs indicated their importance in driving Th17 responses and EAE (346). Therefore, in our IFN-β-/- mice, determining the proportion of Irf4+ DCs, both in naïve and in EAE mice, should be considered, with the hypothesis that Irf4+ DCs might indeed be overrepresented in IFN-β-/- mice. This could be accomplished by FACS analysis of the different DC populations in lymphoid tissues (CD8+Irf8+ and CD11b+Irf4+) in IFN-β+/+ compared to IFN-β-/- mice, in both the naïve and EAE settings. Importantly, a role for IFN-β in regulating the proportion of different DC lineages based on their current definitions has not yet been determined, and this may be a unique opportunity to identify a role for IFN-β in DC homeostasis and development. Another open question in regard to the IFN-β contribution to the DC phenotype is whether the effects are due to endogenous IFN-β providing negative regulatory signals in the DCs. To address this question, we will determine whether IFN-β is produced in response to TLR stimulation in IFN-β+/+ DCs, using IFN-β-/- DCs as negative controls. Concommitantly, we would study DC production of IFN-β during the course of EAE, at early and late time points/stages during disease. It would be important to discern the specific contribution of IFN-β to DCs, by generating a specific knockout of IFN-β in DCs, by generating floxed IFN-β mice and breeding these to a CD11c-Cre mouse. This would serve to isolate the effect of a lack of IFN-β to CD11c+ DCs alone, allowing the contributions of exogenous cytokines produced by other cell types (which, themselves, may be affected by a lack of IFN-β) to be excluded. Using the DC-IFN-β-/- mice, several studies should be conducted. First, induction of EAE, to determine whether a lack of IFN-β in DCs alone will exacerbate EAE as we have observed in the IFN-β-/- mice. Second, phenotyping of IFN-β-/- DCs to determine whether their response to TLR stimulation and their phenotype in EAE is similar or different to what we have observed in the studies described in this thesis. Finally, a set of co-culture experiments with CD4+ T cells from

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2D2 mice to determine whether the DC-specific IFN-β-/- affects their cytokine production, and subsequent lineage polarization of T cells.

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5.3 Summary Statement Taken together, the data presented in this thesis have provided some insights into the immunoregulatory roles of IFN-β in T cells and DCs. IFN-β is required in T cells to prevent excessive proliferation and upregulation of cytokine receptors and genes associated with the Th17 lineage. In DCs, IFN-β is required to maintain normal expression of co-stimulatory molecules and MHCII, and limit the production of cytokines associated with Th17 polarization. These findings provide the basis for further investigations into the mechanistic effects of IFN-β as a treatment for MS, and suggest that directly targeting the downstream T cell and DC effectors that mediate the effects of IFN-β in MS may have clinical utility.

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Chapter 6

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