Primary Human Bronchial Epithelial Cells During Tuberculosis Infection

Primary human bronchial epithelial cells

during tuberculosis infection

Ann-Kathrin Barbara Reuschl

Tuberculosis Research Centre National Heart and Lung Institute Imperial College London

Submitted for the degree of Doctor of Philosophy

Abstract

1 Abstract

Infection with Mycobacterium tuberculosis (Mtb) is acquired through the lungs after inhalation of aerosolised bacteria. Epidemiological studies have shown that infection can only be detected in 30- 50% of individuals after exposure, suggesting that the immune system can mediate clearance of or resistance to infection. Early responses to infection in an Mtb-naïve host are thought to be championed by the innate immune cells in the lungs, such as alveolar macrophages. However, the majority of cells exposed to inhaled air are epithelial, which line the entirety of the respiratory tract. Their function is not well understood in tuberculosis and almost no studies of primary airway epithelial cells have been undertaken. To identify their contribution to the lung immune responses to Mtb infection, human primary bronchial epithelial cells were interrogated in vitro and ex vivo.

Primary bronchial epithelial cells (PBEC) were poor responders to low doses of Mtb in vitro and were markedly less susceptible to infection than macrophages. Large bacterial burden triggered cell death and IL8 release in an NADPH-oxidase dependent manner. Additionally, PBECs were potent responders to myeloid-mediated Mtb-driven inflammation. Myeloid-epithelial cross-talk was, in part, dependent on interleukin 1β and type I interferon-signalling and enhanced the antimicrobial host immune response and neutrophil influx in vitro. Through the assessment of the whole transcriptome and mediator profile of the human airway epithelial lining ex vivo, the in vitro inflammatory epithelial signature could be partially confirmed in patients with suspected pulmonary tuberculosis and Mtb-exposed individuals. Additionally, healthy recently infected Mtb-exposed individuals, showed signs of ongoing low-level immune activation in their nasal and bronchial epithelial mucosa. Taken together, this is the first comprehensive analysis of the human primary airway epithelial response to Mtb-infection and offers new insights into their emerging role in human tuberculosis.

2 Acknowledgements

First and foremost, I want to thank Ajit Lalvani for the opportunity to undertake my PhD under his supervision. Thank you for your unparalleled support and faith in me and my work. I’m also grateful for the invaluable guidance from my second supervisor Robin Shattock. Your feedback was always helpful. Thanks also go to Michael Edwards for training and advice, which made this project viable, and Peter Beverly for his help throughout the write-up of this thesis.

This project would not have been possible without our clinical team who have done an amazing job at recruiting volunteers, especially Samuel Bremang, Lisa Grass, Helen Piotrowski and Hiromi Uzu. I’m grateful for the help of Onn-Min Kon, David Connell and Hannah Jarvis and their profound clinical expertise. Noteworthy is also the support from Amarjit Badhan and Melanie Rees-Roberts who kept the oversight when things seemed chaotic and unsurmountable. I would like to acknowledge our collaborations with Heinke Kunst, Robert Davison and Howard Branley which were imperative for the recruitment of our study volunteers. Most importantly, I would like extend my gratitude to all volunteers and patients who donated samples for this work.

Thanks to Mike Lovett for his encouragement and support of my RNASeq endeavours and Paul Golby as well as Umar Niazi for their discussions and help with the ensuing analysis. Thanks to Sandra Newton, for being a great CL3 lab manager. It was a joy to work with you! I’m grateful for our departmental support Seema Vekaria, Dan Solanki, Rebecca Pearson and Denise Gardner, who were incredibly resourceful and thank you to Sasha Ashbourne-Lewis and Susana Soler for keeping our lab in shape. I would also like to acknowledge the NHLI Foundation for granting me a PhD studentship.

I’m grateful for the support of our brilliant postdocs Robert Parker, Long Hoang, Alice Halliday and Luis Berrocal Almanza. Thanks to all the extraordinary members of the Tuberculosis Research Centre, it has been a tremendous pleasure to work with you. Special mentions go to Banx and Hilary for Tim Tams, adventures and explorations; Naz and Saranya for their patience and the cake-breaks; Matt for (involuntarily) providing chocolates; Dave for being an endless source of wisdom; Helen for all the cultural nights out and Rob for seriously improving my tea-making-skills.

I thank my Mum, Dad and all of my family, who supported me in all pursuits throughout my life. To my Mum: Danke, für deine bedingungslose Liebe und dass du immer für mich da warst!

I dedicate this work to my granddad, who taught me about science as far back as I can remember and who was my inspiration to embark onto the exciting adventure that is research. I wish you could have seen this. You’ll always be in my heart!

3 Declaration of originality

I hereby declare that the work presented in this thesis is my own and that no material has been previously submitted and approved for the award of a degree by this or any other University.

All materials in this thesis, which are not my own work, have been acknowledged or referenced.

4 Copyright declaration

The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution Non-Commercial No Derivatives licence. Researchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the licence terms of this work.

5 Table of Contents

1 Abstract ...... 2 2 Acknowledgements ...... 3 3 Declaration of originality ...... 4 4 Copyright declaration...... 5 5 Table of Contents ...... 6 6 List of Figures ...... 8 7 List of Tables ...... 10 8 Abbreviations ...... 11 9 Introduction ...... 13 9.1 Tuberculosis – the plague that will not perish ...... 13 9.2 The natural history and heterogeneity of tuberculosis ...... 13 9.3 Obstacles and strategies in the fight against tuberculosis ...... 15 9.4 Intervention after exposure: cracking down on the iceberg ...... 16 9.5 The immune responses to tuberculosis – an overview of pathology and mechanisms ...... 18 9.6 Mechanisms that may mediate resistance to or early clearance of infection...... 20 9.7 The airway epithelium: structure and barrier functions against invading agents ...... 25 9.8 The airway epithelium as part of the respiratory immune system ...... 27 9.9 Airway epithelial responses during chronic disorders and infections ...... 27 9.10 Rationale for studying the lung immune response to Mtb including the epithelium ...... 29 9.11 Rationale for studying human primary epithelial cells in tuberculosis ...... 33 10 Hypothesis ...... 34 10.1 Aims...... 34 11 Materials ...... 35 12 Methods ...... 39 12.1 Recruitment and ethics statement ...... 39 12.2 Sampling of the human respiratory tract...... 41 12.3 Cell culture ...... 43 12.4 Cell counting ...... 47 12.5 Bacterial cultures ...... 47 12.6 Cell stimulation and infections...... 49 12.7 Protein detection ...... 52 12.8 Microscopy ...... 59 12.9 Gene expression analysis ...... 60 12.10 Data analysis ...... 66

6 Table of Contents

13 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis ...... 68 13.1 Introduction ...... 68 13.2 Hypothesis ...... 69 13.3 Aims...... 69 13.4 Results ...... 70 13.5 Discussion ...... 84 14 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection ...... 89 14.1 Introduction ...... 89 14.2 Hypothesis ...... 90 14.3 Aims...... 90 14.4 Results ...... 91 14.5 Discussion ...... 122 15 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection ...... 128 15.1 Introduction ...... 128 15.2 Hypothesis ...... 130 15.3 Aims...... 130 15.4 Results ...... 131 15.5 Discussion ...... 157 16 Concluding remarks ...... 162 16.1 A brief summary of the work presented ...... 162 16.2 Perspectives ...... 166 16.3 Limitations of the present study ...... 168 16.4 Future directions ...... 170 17 References ...... 172 18 Appendices ...... 205 18.1 Appendix 1: Data ...... 205 18.2 Appendix 2: Presentations at conferences and meetings ...... 242

7 List of Figures

6 List of Figures

Figure 9.1: The natural history of tuberculosis infection...... 17 Figure 9.2: Structure of the human lungs and the airway epithelium...... 26 Figure 9.3: The epithelial contribution to the early stages of the natural history of tuberculosis infection...... 32 Figure 12.1: Sampling of the bronchial lining through bronchosoprtion and brushings...... 43 Figure 12.2: Expansion of primary bronchial epithelial cells in vitro...... 45 Figure 12.3: Optimisation and final protocol of SAM-strip processing...... 54 Figure 12.4: Optimisation of pre-processing of ex vivo bronchial samples for RNA Sequencing...... 64 Figure 12.5: Library preparation for RNA Sequencing...... 66 Figure 13.1: PBECs do not respond to mycobacterial PAMPs...... 71 Figure 13.2: Mtb infects PBECs less efficiently than macrophages...... 73 Figure 13.3: Sustained infection of PBECs with virulent Mtb induces cytokine release...... 75 Figure 13.4: Gene expression of selected targets in PBECs exposed to Mtb...... 76 Figure 13.5: Whole transcriptome analysis of the PBEC response to Mtb...... 78 Figure 13.6: Mtb-induced IL8 release is independent of TLR2 or Dectin-1 activation...... 79 Figure 13.7: Mycobacterial virulence induces IL8 and cytotoxicity in PBECs...... 81 Figure 13.8: Diphenyleneiodonium (DPI) inhibits LDH and IL8 release during Mtb exposure of PBECs...... 83 Figure 14.1: Macrophages are the major immune subset in the lung lining and release pro- inflammatory cytokines in response to Mtb infection...... 92 Figure 14.2: PBECs release IL8 in response to stimulation with pro-inflammatory cytokines...... 93 Figure 14.3: Mtb-induced IL1β levels are augmented in a co-culture model of myeloid-epithelial interactions...... 95 Figure 14.4: Mtb-infected THP-1 cells induce global transcriptomic changes in PBECs...... 97 Figure 14.5: PBEC gene expression in co-culture is strongly dependent on direct contact between Mtb and THP-1 cells...... 99 Figure 14.6: Mtb-infection of alveolar macrophages drives gene expression in PBECs similar to THP-1 cells...... 102 Figure 14.7: Mtb-induced IL1β drives a proportion of the PBEC response to myeloid infection...... 104 Figure 14.8: TNF promotes IL1β-driven gene induction in a THP-1-autocrine manner...... 105 Figure 14.9: Myeloid cells upregulate IFNβ during Mtb-infection and induce STAT1-activation in PBECs...... 107 Figure 14.10: IFNAR-signalling drives the IL1β-independent epithelial expression signature in response to myeloid Mtb-infection...... 109 Figure 14.11: Epithelial CXCL10 expression in response to Mtb-infected THP-1 cells is independent of IL27 and IFNγ...... 110

8 List of Figures

Figure 14.12: IL1β enhances interferon-induced CXCL10 release by PBECs...... 110 Figure 14.13: PBECs do not improve Mtb-control of THP-1 cells...... 111 Figure 14.14: DEFB4 and S100A7A are not expressed strongly in myeloid cells...... 113 Figure 14.15: IL1β and IFNβ do not improve PBEC control of Mtb...... 113 Figure 14.16: hBD2 efficiently prevents Mtb-growth...... 114 Figure 14.17: A commercial preparation of koebnerisin does not affect Mtb growth...... 115 Figure 14.18: Recombinant psoriasin prevents Mtb-growth...... 116 Figure 14.19: Mediator release during Mtb-infection of THP-1 cells in the presence and absence of PBECs...... 119 Figure 14.20: Flowcytometric phenotyping PBLs...... 120 Figure 14.21: PBECs enhance PMN influx during myeloid Mtb-infection...... 121 Figure 15.1: Diagram of potential mucosal signatures in the TB exposed human respiratory tract. . 129 Figure 15.2: Study outline for the ex vivo analysis for the natural history of tuberculosis of the human airways...... 132 Figure 15.3: Soluble mediators in nasal lining fluid (NLF) during latent and active tuberculosis...... 135 Figure 15.4: Presence of symptoms is associated with differences in nasal mediators in Mtb-infected subjects...... 137 Figure 15.5: Mediator levels in nasal and bronchial lining in the Exposure cohort...... 141 Figure 15.6: Differences in MLF mediator levels between infected and uninfected TB exposed healthy subjects...... 143 Figure 15.7: Differences in MLF mediator levels between all healthy subjects stratified by smoking status...... 144 Figure 15.8: Contact time and contact scores of infected and uninfected TB exposed healthy subjects...... 145 Figure 15.9: CCL4, IL2 and MMP3 are affected by the extent of TB exposure...... 146 Figure 15.10: Cellular composition and RNA-quality of ex vivo bronchial brushings...... 149 Figure 15.11: Bronchial epithelial expression signature of TB exposure...... 151 Figure 15.12: Bronchial epithelial expression signature of suspected TB...... 153 Figure 15.13: Pathway enrichment analysis of the suspected TB expression signature...... 154 Figure 15.14: Comparison of in vitro and ex vivo bronchial epithelial expression signatures...... 155 Figure 16.1: Primary human bronchial epithelial cells during tuberculosis infection...... 164 Figure 16.2: Schematic of the airway epithelial contribution to the host response against Mtb infection across the natural history of TB...... 165

9 List of Tables

7 List of Tables

Table 11.1: Antibodies...... 35 Table 11.2: Mycobacterial and synthetic ligands...... 36 Table 11.3: Gene expression assays...... 36 Table 11.4: Chemical stimuli and inhibitors...... 37 Table 11.5: Recombinant human cytokines...... 37 Table 11.6: Buffers...... 37 Table 11.7: Human and bacterial cell culture media...... 38 Table 12.1: Demographic characteristics of all recruited volunteers and patients...... 40 Table 12.2: ELISA kits and detection ranges...... 55 Table 12.3: MSD assay detection ranges...... 57 Table 14.1: Fold change IQR of target genes in PBECs exposed to uninfected and infected THP-1 cells...... 100 Table 14.2: Chemotactic mediators induced during THP-1-PBEC co-culture during Mtb-infection: . 119 Table 14.3: PBL subset phenotypes according to FSC/SSC gating...... 120 Table 15.1: Demographic and clinical characteristics of the NLF cohort...... 134 Table 15.2: Correlation of TNFβ, CXCL10 and CCL13 with treatment, smoking and symptoms...... 136 Table 15.3: Demographic characteristics of the Exposure cohort (Aim 2)...... 140 Table 15.4: Demographic characteristics of TB exposed healthy subjects...... 142 Table 15.5: Exposure quality of TB exposed healthy subjects...... 145 Table 15.6: Demographic characteristics of bronchial samples for RNA Sequencing (Exposure cohort - Aim 3)...... 150 Table 15.7: The most significantly differentially expressed genes in TB exposed healthy subjects and their involvement in smoking...... 152 Table 15.8: Differentially expressed genes in TB exposed subjects and suspected TB patients...... 156

10 Abbreviations

8 Abbreviations

°C Degree Celsius AMΦ Alveolar macrophage ATB Active tuberculosis BCG Mycobacterium bovis Bacillus Calmette-Guérin BEBM Bronchial epithelial basal medium BLF Bronchial lining fluid bp Base pairs BSA Bovine serum albumin CCL C-C motif ligand CD Cluster of differentiation CRP C-reactive protein CWF Cell wall fraction CXCL C-X-C motif ligand CytoFr Cytosolic fraction DC Dendritic cell dH2O Distilled water DMSO Dimethylsulfoxid DNA Desoxyribonucleic acid DPI Diphenyleneiodonium EDTA Ethylenediaminetetraacetic acid FACS Fluorescence-activated cell sorting FBS Foetal bovine serum h Hour hBD Human beta-defensin HBSS Hank’s balanced salt solution HRP Horseradish peroxidate IFN Interferon IFNAR Interferon α/β receptor IGRA IFNγ-release assay IL Interleukin LB Luria broth LDH Lactate dehydrogenase LM-MS Lipomannan from Mycobacterium smegmatis LTBI Latent tuberculosis infection LYM Lymphocytes min Minute ml Millilitre MLF Mucosal lining fluid

11 Abbreviations

MOI Multiplicity of infection mRNA Messenger RNA MSD Meso Scale discovery Mtb Mycobacterium tuberculosis NADPH Nicotinamide adenine dinucleotide phosphate NFκB nuclear factor kappa-light-chain-enhancer of activated B cells NLF Nasal lining fluid nm nanometre NΦ Neutrophil OADC Oleic acid albumin dextrose catalase OD Optical density Pam2 Pam2CSK4 Pam3 Pam3CSK4 PBEC Primary bronchial epithelial cells PBL Peripheral blood leukocytes PBMC Peripheral mononuclear cells PBS Phosphate-buffered saline PMA Phorbol 12-myristate 13-acetate PMN Polymorphonuclear cell Poly:IC Polyinosine-polycytidylic acid RBC Red blood cells RNA Ribonucleic acid Rot Rotenone RPMI Roswell Park Memorial Institute medium RT-PCR Reverse transcription polymerase chain reaction s Second STAT Signal transducer and activator of transcription TLR Toll-like receptor TNF Tumor necrosis factor WCL Whole cell lysate WHO World health organisation xg Times gravity

12 Introduction

9 Introduction

9.1 Tuberculosis – the plague that will not perish

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb). It has been part of the history of Homo sapiens for at least 70000 years (1). Accompanying humans throughout their migration across all continents (2), TB has taken its toll on mankind. Historically known as the “white plague” or “consumption”, it was the cause of death of more than 100 million people in the last century (3). While its incidence has drastically declined and it is a curable disease these days, TB remains one of the largest public health problems caused by a single infectious agent. In 2014, 9.6 million people were diagnosed with tuberculosis disease and 1.5 million people died as a consequence (4).

In 1882, Robert Koch proved tuberculosis to be an infectious disease by identifying the rod shaped tubercle bacillus, Mycobacterium tuberculosis (5). Mtb is part of the family of Mycobacteriaceae, which are characteristically acid-fast bacilli with a thick and robust cell wall. Being hydrophobic and high in lipid content, the cell wall contributes to the sturdiness and persistence of the organisms (6). While Mtb and its relative M. leprae, the causative agent of leprosy, are highly pathogenic, most mycobacterial strains are environmental and do not cause disease in immunocompetent human hosts (7). Mtb has co-evolved with and is adapted to humans. It has a closely related counterpart Mycobacterium bovis that causes tuberculous disease in cattle and sometimes even humans through the ingestion of non-pasteurised milk (8). Since Koch’s discovery, a lot of effort and resources have been directed towards a better understanding of the disease and the pathogen as well as its eradication – with some, but limited, success (9). While animal models helped to elucidate immunological pathways at play during tuberculosis disease, the complex host-pathogen interactions in the human host are not fully mimicked by the most accessible animal model, the mouse (9), which leaves many questions about human TB unanswered.

9.2 The natural history and heterogeneity of tuberculosis

The natural history of tuberculosis begins with the inhalation of aerosolised Mtb into the lungs. After establishing infection, adults run a 2-3% risk in the first following years of direct progression to active tuberculosis (ATB) (10, 11), also termed primary TB (12). However, if the infection can be controlled by the host, reactivation, termed postprimary TB, may occur much later with a lifetime risk of approximately 10 % (13). TB can affect virtually any organ in the human body (12) and the largest

13 Introduction public health threat is posed by the transmissible form, pulmonary TB (14, 15), during which viable bacteria can be shed from the host and infect individuals who are breathing the same air.

Even though the annual global ATB incidence is high, infection with Mtb does not automatically result in productive disease. The largest proportion of infected individuals host the bacterium in an asymptomatic state termed latent tuberculosis infection (LTBI). It is generally assumed that latency is a state of infection control, in which Mtb and the immune system are in equilibrium (16). These infected individuals remain at risk of developing ATB throughout this time, which may be decades (13). In fact, a third of the global population is latently infected with Mtb, with the main burden occurring in Southeast Asia, Western Pacific regions and Africa (4, 15). Recent work in non-human primates (17) and large human transcriptomic studies (18) have identified LTBI as a complex spectrum of infection. The host may be able to fully control the pathogen asymptomatically or, alternatively, may be in a state of sub-clinical disease in which bacteria are replicating yet the fight against the infection is localised (19). This phenomenon of “percolating” sub-clinical disease during infection-control was first described in the macaque model of tuberculosis by Lin et al (17). These studies have made it increasingly clear, that even during latency, immune responses at the site of infection may be ongoing to facilitate local containment of the infection (20).

Latent infection is identified by the peripheral immune sensitisation against mycobacterial antigens in the host. Immune sensitisation has long been measured by inoculating skin with purified protein derivate (PPD), a glycerol extract of Mtb, in the tuberculin skin test (TST) (21, 22). The read-out is a localised delayed-type hypersensitivity reaction which can be quantified after 48 to 72 hours (23). The TST has been standardised and used in clinical practice to determine Mtb infection since the 1940s, but lacks specificity and sensitivity (24). This is partly because of the crude antigenic mixture, which shares common antigens with environmental mycobacteria and BCG (25), which can confound the test result. Recently, an alternative has been developed in which peripheral blood cells are stimulated with Mtb-specific antigens absent in non-pathogenic mycobacteria and release of interferon (IFN) γ is measured as an indicator for infection (26, 27). Two of these IFNγ release assays (IGRAs) are commercially available: Quantiferon-TB Gold and Tspot.TB (28). While IGRAs show improved specificity and sensitivity over skin testing, they are costly and require appropriate laboratory facilities and thus are mainly used in high-income countries (29).

The lack of direct detection (as this would require necropsy of the host), has led to an ongoing debate whether all individuals designated “latently infected” truly harbour viable Mtb. Persistence of bacteria in subjects with LTBI has been confirmed in humans and it was shown that Mtb can be detected in macroscopically normal healthy tissue of individuals that died of other causes than

14 Introduction tuberculosis (30–32). The exact time of infection is often difficult to determine, however an epidemiological study in Denmark showed through strain-typing, that Mtb persisted for several decades in the human host before disease occurred (33). While the events leading to reactivation are not fully understood, long-term containment is often lost in the context of immune suppression. The best understood factors driving reactivation are co-infection with human immunodeficiency virus (HIV) and anti-rheumatic treatment (34, 35). Other factors that are associated with impaired control of the pathogen are age (36, 37), host genetics (38, 39) and states in which immune homeostasis is shifted, such as type 2 diabetes (40). The mycobacterial genotype additionally contributes to reactivation and some of the Southeast Asian strains of Mtb have been associated with higher progression rates to active disease (41).

9.3 Obstacles and strategies in the fight against tuberculosis

The World Health Organisation currently aims to eradicate tuberculosis by 2050 (4). With less than 35 years to achieve this ambitious goal, an obstacle in the battle against TB is the difficulty of diagnosing patients with disease as well as infection. Active TB can present in fashions that clinically mimic other diseases, such as other bacterial infections, cancer or the granulomatous disease sarcoidosis (12). A diagnosis of ATB can only be made when the bacterium is identified at the site of infection. If a large amount of Mtb is shed and can be sampled, the identification can occur quickly by microscopy (42). However, since this methodology lacks sensitivity, infection needs to be confirmed by culture, which can take up to six weeks. Confirmation of Mtb infection by these methods can require highly invasive procedures dependent on the site of disease, including lymph node biopsies or sampling of the cerebrospinal fluid. Once diagnosed, or suspected, ATB can be cured by an intense long-term course of antibiotics that requires strict adherence (43). This strategy is effective against disease caused by drug sensitive Mtb strains, however, the increased occurrence of multi- or extensively drug resistant Mtb, is making control of the bacilli progressively difficult (44). It is thus pressing to find alternative intervention strategies that are effective before progression to ATB occurs.

For many infections, disease can be prevented by priming the immune system through vaccination. Long term laboratory culture of M. bovis rendered the strain M. bovis Bacillus Calmette-Guérin (BCG) non-pathogenic (45). It has since been used as a live vaccine against TB in humans. BCG vaccination has highly variable efficacy in prevention of disease (46), but no viable alternative has been found to be an improvement over BCG in the last century (47). The protective efficacy can only be assessed by large clinical trials, partly because no biomarkers have been found to correlate with prevention of

15 Introduction disease or protection against infection (48). Thus, BCG remains the only licensed, and still widely used, vaccination available against tuberculosis (49).

9.4 Intervention after exposure: cracking down on the iceberg

Despite all shortcomings of available vaccines, diagnostics and treatment approaches, the human host has a remarkable capacity to control Mtb infection. Successful control of Mtb by the healthy immune system has long been reported. In 1930, 252 newborns were accidentally inoculated with M. tuberculosis instead of the vaccine strain BCG. As a result, 75 children died within a couple of months after vaccination. While all received the same mycobacterial isolate, a third of the infected children did not develop any signs of disease and remained well (50). It is also known that, while mortality due to active TB increases after 50 years of age, 30% of otherwise immunocompetent hosts can self-heal ATB (51). This evidence suggests that host-intrinsic immune mechanisms exists which are able to successfully control tuberculosis at various stages in its natural history. If identified, the optimal host immune responses to Mtb infection can be targeted to advance new intervention in the battle against TB.

An improved strategy could be to diminish the global tuberculosis burden by preventing the initial acquisition of infection. This would abrogate the replenishment of the LTBI reservoir, which is at risk of progression to ATB. Even though the reservoir of Mtb in humans is very large, exposure to aerosolised bacteria does not always lead to infection. Close contacts of ATB index cases can remain uninfected, as measured by the absence of a peripheral immune sensitisation against mycobacterial antigens. Meta-analyses revealed that approximately 50-70% of close contacts of pulmonary TB cases remain uninfected in endemic and non-endemic settings (52, 53). There are several environmental and host-dependent risk factors that contribute to the acquisition of infection. A crucial environmental factor that affects the outcome of exposure is the quality of the exposure, composed of the proximity and duration of the contact as well as the index case’s infectivity (54–56). However, some individuals in close contact with ATB patients remain persistently uninfected, even though the exposure is the same as that of their infected counterparts (57–59). This is evidence for a direct host-mediated resistance to infection. Host specific factors which have been associated with the outcome of infection and may influence the host immune response, are age (60, 61), ethnicity (62), malnutrition (63), smoking (64) and peripheral neutrophil counts (65) at the time of exposure.

While clearance of infection can occur and is indicated by reversion of IGRA positivity to negativity (66), it does not necessarily need to be mediated by the adaptive response. In fact, onset of the adaptive response is delayed during Mtb-infection (67), indicating that the innate immune system

16 Introduction may initially contain the infection. This is supported by the identification of a genetic locus that is strongly associated with persistent TST-negativity, inferring innate Mtb-resistance, in a tuberculosis- endemic setting (68).

Since the site of Mtb-entry is the human airways, resistance to infection must be mediated by the immune system residing in the lungs. It is therefore conceivable that the induction of the appropriate immune response at the site of Mtb-exposure may prevent Mtb-infection and reduce the global tuberculosis burden (Figure 9.1).

Figure 9.1: The natural history of tuberculosis infection. After the exposure of a naïve human host to an active pulmonary TB case, inhalation of Mtb can result in acquisition of (orange) or resistance to (green) infection. When resistance to or clearance of Mtb occurs, the bacteria are successfully eliminated by the host immune response through various possible pathways. If the infection cannot be cleared, latency or active disease occurs.

17 Introduction

9.5 The immune responses to tuberculosis – an overview of pathology and mechanisms

Prior to the discussion of possible immune mechanisms that may mediate innate resistance to infection; this section will give a brief overview of the immunopathology of TB. After inhalation of aerosolised Mtb, the bacterium is taken up by airway-resident macrophages which are thought to be the infection-niche for Mtb. Macrophages are professional antigen-presenting phagocytes and crucial in the detection and clearance of pathogenic and other invading agents. Within macrophages Mtb is contained in vesicles called phagosomes (69, 70). To dispose of internalised bacteria, phagosomes fuse with lysosomes, acidic hydrolase-containing compartments which can break down a wide range of biological molecules, to form the phagolysosome (71). The resulting bacilli- containing compartment leads to the killing and disposal of internalised pathogens. Interestingly, Mtb has developed mechanisms that prevent phagolysosomal fusion and by extension the antimicrobial environment created, allowing Mtb to inhabit the phagosome as a survival niche (72, 73). While this makes it more difficult to eradicate the bacteria, the host can override this fusion blockade by release of IFNγ to promote the acidification process and support macrophage control of infection (70, 74). Recent work has shown that virulent mycobacteria, once they have been sequestered into the phagolysosome, may however still survive within this hostile environment through a membrane serine protease which allows mycobacterial acid tolerance (75). This complex interaction between macrophages and Mtb requires the contribution of further immune subsets to the host response.

In addition to direct pathogen control, macrophages can initiate the inflammatory response against Mtb through the release of cytokines, soluble small proteins that allow auto- and paracrine cell signalling. These can initiate recruitment of further macrophages and other phagocytic immune subsets, including neutrophils and dendritic cells (DCs) to support local Mtb-control. Additionally, DCs transport Mtb to the draining lymph nodes, to initiate the adaptive immune response (76). Curiously, the onset of antigen-specific responses to Mtb is delayed in comparison to other infections. In humans and non-human primates, TST conversion after exposure to Mtb takes several weeks (77–79) and it is known from murine studies, that presentation of Mtb in the lymph nodes only occurs after 8-10 days (76, 80), while pathogen associated molecular patterns (PAMPs) and viruses can be shuttled to the lymph nodes by DCs within 24 hours of challenge (81–83). Studies in TB resistant and susceptible mouse strains, suggest that earlier dissemination to the lymphatics is associated with improved control of infection and diminished pathology (76). The influx of the adaptive immune system, even though it may not mediate the eradication of Mtb, is crucial for long

18 Introduction term containment of the bacteria. Since the emergence of the human immunodeficiency virus (HIV), it has been apparent that functional T cells are essential to achieve this. Depletion of Mtb-specific cluster of differentiation (CD) 4 T helper 1 (Th1) cells puts Mtb/HIV co-infected individuals at high risk of progression to active TB (84–86). Additionally, functional mutations in IFNγ- and IL12- signalling pathways, which form the axis of Th1 cell activation and function, can lead to severe disease caused by non-pathogenic mycobacteria, known as Mendelian susceptibility to mycobacterial disease (MSMD) (87). While most of the protective capacity of T cells is ascribed to the CD4+ cells (88), Carranza et al have proposed that autologous CD8+ T cells can also improve human alveolar macrophage control of intracellular Mtb infection (89).

Ultimately, infection with Mtb and the induced host immune response lead to structural changes in the infected tissues. Through the accumulation of immune cells around the infection foci, granulomas are formed to contain invading agents (90). Tuberculous granulomas are heterogeneous and of variable sizes (17, 43, 91), but broadly speaking spherical structures that consist of a centre with infected phagocytes (macrophages and neutrophils), epitheloid cells and foamy macrophages. This centre is surrounded by a layer of lymphocytes and fibroblasts (92, 93). The exact immunological composition of granulomas in humans can vary drastically. Lesions can be calcified, fibrotic, and free from bacteria, or necrotic, and carry a large mycobacterial burden (91, 94). Within the same host, these structures develop and control infection independently and with different antimicrobial activities (95). To date, it is not entirely clear whether granulomas are more beneficial for the host or the pathogen. They contain the infection as well as attract immune cell influx, providing new infection niches for mycobacteria or even allow Mtb to disseminate from the granuloma (96–98). During long-term containment, the maintenance of the immunological integrity of granulomas is required to prevent reactivation of tuberculosis, as has been evident from high reactivation rates in immunosuppressed individuals (34, 99–101). Specifically, neutralisation of tumor necrosis factor (TNF) during anti-rheumatic treatment can result in reactivation of disease in latently infected humans (35) and in experimentally infected non-human primates (102). Overall, this suggests that granulomas may have different functions during early and late infection, helping Mtb to establish infection, yet allowing host control of the bacteria in an immune equilibrium.

As stated before, the host cannot always control Mtb-infection and during active TB, overwhelming immune responses against replicating bacteria can lead to severe tissue destruction (12, 103). Within the lungs, various matrix metalloproteinases (MMPs) drive extracellular matrix degradation and disease severity (104). Most prominently, MMP1 and MMP9 are found to be elevated in tuberculous lesions during active infection (103, 105). Due to their profound effects on host tissue,

19 Introduction their inhibition has been suggested as a therapeutic target to mitigate disease severity (106). Through the use of global “omics”-approaches, an additional pathway has recently been associated with severe pathology. In a large whole-blood transcriptomic study in endemic and non-endemic settings, Berry and colleagues identified an IFN inducible signature that included IFNγ as well as type I IFN signalling induced components and linked it to increased disease severity in patients (18). Together with other studies, this shifted the spotlight to the underappreciated role of type I IFNs during human tuberculosis (107–109). Type I IFNs and their downstream signalling targets are mostly known for their anti-viral functions (110, 111), but can be detrimental during bacterial infections. Due to the increased recruitment of tissue-destructive neutrophils to the site of infection, type I IFN signalling has been shown to accelerate inflammation and severe outcome in Mtb- susceptible mice (112). The host response in tuberculosis remains a delicate immunological balancing act and can mediate bacterial containment as well as severe pathology and disease.

9.6 Mechanisms that may mediate resistance to or early clearance of infection

As stated above, exposure to Mtb does not necessarily lead to established Mtb-infection. It is unclear which events are decisive after inhalation of the pathogen. A complete understanding of the earliest antimycobacterial mechanisms in the human lungs could provide a blueprint for new intervention strategies. If exposure is sufficient to cause infection, Mtb may be cleared by the mucosal barrier, a local adaptive immune response or the respiratory innate immune system (Figure 9.1). Several pathways and mechanisms have been identified that may contribute to resistance or clearance of infection, some of which are discussed below.

9.6.1 Myeloid cells

Myeloid cells are the main component of the innate immune system. Two important myeloid subsets during Mtb-infection are macrophages and neutrophils. Both show considerable inter- individual variability with regards to their antimycobacterial capacities (65, 113). The dominant immune subset in non-inflamed healthy airways are macrophages (89, 91, 114). While they are found in all organs, they have markedly different phenotypes and functions pertaining to their respective environments (115). Residing in the terminal airways, alveolar macrophages (AMΦ) are the first professional phagocyte and primary infection target encountered by Mtb (89, 116). AMΦs are a complex cell subset that shows high plasticity within and between hosts. They are required to control respiratory infections but are also thought to maintain an anti-inflammatory state during

20 Introduction homeostasis to prevent unnecessary and potentially destructive pro-inflammatory response (117, 118). The activation state of the macrophages during the initial encounter may thus determine whether the scales tip towards resistance to infection in the context of exposure to Mtb.

Detection of Mtb by macrophages is mediated by pattern recognition receptors (PRRs) detecting conserved mycobacterial PAMPs. Since Mtb harbours a variety of PAMPs, macrophage activation can occur through several receptors, including Toll-like (TLR), mannose and scavenger receptors (119). Dependent on the respectively activated receptor, mycobacterial ligands can skew macrophages towards pro- or anti-inflammatory responses. Activation of TLRs results in pro-inflammatory activation and release of TNF and IL1β, which are key effectors during Mtb-infection and improve innate control of Mtb (114, 120). On the other hand, activation of the mannose receptor, while inducing phagocytosis, can induce an anti-inflammatory response, in part through the release of IL10 (121, 122). While activation of macrophage receptors is closely associated with the antigens presented on the mycobacterial cell wall and can differ depending on the infecting strain (123), priming of macrophages towards a certain receptor repertoire could allow therapeutic induction of a distinct homeostatic “Mtb-resistant” state. Feasibility of inducing long-lasting changes in resident lung macrophages is evident from studies on smokers. A subset of their AMΦs show impaired migratory capacities due to lysosomal storage dysfunctions, which may increase host susceptibility (124). Additionally, AMΦs recovered from smokers fail to mount an appropriate pro-inflammatory response to Mtb-infection which is associated with a lack of Mtb growth control (125). These diminished pro-inflammatory responses to Mtb persist in ex-smokers, suggesting that AMΦs maintain a specific phenotype over long periods (125). In fact, AMΦs have a remarkable capacity for self-renewal and the annual turnover in the lungs of approximately 40% is slow compared to other myeloid subsets (126, 127). Absence of infection after Mtb-exposure has also been attributed to previous BCG vaccination (61), which has been suggested to induce an Mtb-resistant innate immune phenotype. BCG may induce long-lasting pro-inflammatory activation of the innate immune system, rendering myeloid cells more antimicrobial. A study by Kleinnijenhuis and colleagues reported that exposure of monocytes to BCG resulted in NOD2-mediated epigenetic changes, increasing the release of pro-inflammatory mediators, including TNF, in a subsequent bacterial challenge. They observed similar phenotypes in circulating primary human monocytes three months after BCG- vaccination of healthy volunteers (128). However, whether this phenomenon truly occurs in vivo and throughout the course of a human’s life, even after BCG is cleared from the body, remains to be verified. Interestingly, though, BCG has long been known to have non-specific beneficial effects against various non-tuberculous infections and diseases in children (129, 130).

21 Introduction

Besides the macrophage activation state, the events occurring after the cell has been infected may shape the outcome of infection. To overcome the inhibition of phagosomal maturation, macrophages can undergo controlled cell death, called apoptosis. This allows disposal of intracellular Mtb, since bacteria-containing apoptotic bodies can be engulfed by neighbouring phagocytes and circumvent the Mtb-induced maturation block (131, 132). A form of cell death favouring Mtb- survival is necrosis, which is less well controlled and promotes tissue inflammation. This has been suggested to allow the mycobacteria to escape the host immune response and has been shown to facilitate pathogen escape and intercellular spread in an epithelial cell line (132–134). On the other hand, escape of Mtb from the host cells through necrosis and its accumulation in the extracellular space may also prevent further uptake by phagocytes, as it has been observed for other mycobacterial species. When the fast growing Mycobacterium abscessus forms extracellular cords after escaping macrophages, the bacterial aggregates are too large to be taken up by incoming phagocytes and thus can freely drive tissue damage and pathology (135). The balance between apoptosis and necrosis of infected cells thus favours containment or bacterial spread, respectively. Along these lines, eicosanoid pathways could play an important role and the balance of prostaglandin (PG) E2, favouring an apoptotic, and lipoxin (LX) A4, favouring a necrotic environment, could mediate resistance (136). Interestingly, various genetic polymorphisms involved in eicosanoid synthesis from arachidonic acid are associated with tuberculosis susceptibility (137, 138). The availability of PGE2 may be affected by intra-macrophage cytokine activation. Induction of type I IFNs by Mtb is associated with increased mycobacterial virulence (139). Type I IFN β, has been shown to be directly induced by Mtb through release of genomic DNA via its ESX-1 secretory system into the host cytosol (140), which supports its pro-mycobacterial role. It has been suggested recently, that type I IFNs and IL1β have opposing roles during Mtb-infection. IFNβ can impair pro- inflammatory IL1β induction (139), while, in turn, IL1β-induced PGE2 may diminish type I IFN levels during infection (141). Whether the balance of these two factors impacts the outcome of exposure to Mtb, remains to be verified.

The second myeloid subset that may shape the outcome of infection is neutrophils. Neutrophils are found at the site of disease in humans and are associated with disease severity (18, 142). While they are thought to be detrimental during active disease, they may have a protective role during the early stages of Mtb-infection. Neutrophils help to control the bacterial burden early during systemic murine Mtb-infection (143). In zebrafish, while neutrophils do not interact with mycobacteria at the site of infection, these cells improve mycobacterial control within granulomas (144). A study by Martineau et al, found a correlation between low peripheral neutrophil counts and positive IGRA

22 Introduction responses in tuberculosis contacts, suggesting that neutrophils might be mediators in the resistance against Mtb-infection (65), however this finding has not been replicated, yet

Infection results in the recruitment of more phagocytes. This recruitment can, in part, be manipulated by pathogenic mycobacteria to attract less microbicidal myeloid populations in a C-C motif chemokine receptor (CCR) 2-dependent manner (124). Even though this provides Mtb with further infection niches (98, 145), phagocytes can, to a certain extent, provide a source of antimicrobial peptides (AMPs) to control Mtb growth. These include macrophage derived cathelicidin and neutrophil α-defensins (65, 146). Availability of AMPs during infection, such as cathelicidin, can be modified by metabolic mediators such as vitamin D. The vitamin D pro-form 25- hydroxyvitamin D3 and the activated metabolite 1,25-dihydroxyvitamin D3, have been shown to improve innate control of Mtb through induction of cathelicidin in infected macrophages (146, 147). Controlling the myeloid phenotype or the antimicrobial environment encountered by Mtb upon arrival in the human lungs may critically contribute to human resistance to infection.

9.6.2 Lymphocytes

While myeloid cells are the major subsets in the airways and lung parenchyma, lymphocytes are also found in the local mucosa (91). Innate-like lymphocytes are potential early mediators of immunity, before classical adaptive T cells are recruited to the site of infection. They are resident in mucosal tissues and provide cell-mediated immunity similar to adaptive T cells, but are activated through germ-line encoded receptors that lack the specificity of the adaptive response (148). Amongst them are gamma-delta (γδ) T cells, natural killer (NK), Invariant natural killer T (iNKT) and mucosa- associated invariant T (MAIT) cells. These cells have been described to recognise conserved Mtb- antigens and their initial activation is likely induced by infected macrophages through antigen- presentation and local release of cytokines (149–152). In turn, activated tissue resident innate lymphocytes promote macrophage function. Release of IFNγ by lymphocyte subsets, can promote macrophage control of Mtb infection by enhancing their antimicrobial capacity and facilitating phagosomal acidification (70, 153).

The contribution of innate-like lymphocytes is not well described in tuberculosis infection, specifically with regards to early events after exposure. However, these cell subsets harbour several mechanisms that may support the initial control of Mtb after its inhalation. iNKT and NK cells can detect Mtb-infected myeloid cells and enhance their Mtb growth control in vitro via the release of cytokines such as IL22 and GM-CSF (149, 154). Curiously, the role of NK cells during tuberculosis in vivo is still undefined, while they are detectable in the human airways (155), they have found to

23 Introduction have a redundant role in mouse models (156). MAIT cells detect Mtb-infected cells via antigen- presentation through the conserved MR1-receptor (150). These cells are required in a mouse model of BCG infection for pulmonary bacterial control and are found enriched in the lung tissue compared to peripheral blood (150, 157). Another lymphocyte subset which may be important during early infection in the airways are γδ T cells. They are present in human BAL (155) and detect Mtb derived phosphoantigens (158). Similarly to CD8 T cells, activated γδ T cells can kill infected macrophages (159). The exact contribution of the above subsets in the human airway immunity against Mtb remains to be defined.

While in an Mtb-naïve host, the first response to Mtb is likely driven by the innate immune compartment of the lungs, individuals with previous exposure could harbour tissue-resident Mtb- specific T cells that contribute to early control of Mtb. Since antigenic challenge is required for the development of these responses, this scenario is most likely in tuberculosis endemic settings. Alternatively, local memory responses, not detectable in the periphery, may be a mechanism through which the “innate resistance” associated with BCG vaccination occurs. This is, however, speculative. It has been shown that recruitment of adaptive T cells to the airspaces can occur quickly given the right circumstances. A human bronchial challenge-model revealed that in TST+ individuals, PPD-specific lymphocytes are recruited to the airways within 48 hours of antigenic instillation (155, 160). Recruited PPD-specific CD4 T cells were the dominant source of IFNγ in this study. On the other hand, adoptive transfer of transgenic Mtb-specific T cells in mice, showed that activated CD4 T cells only affect the lung bacterial burden one week after infection, even when transferred before aerosol exposure (67). The failure of the adaptive response to promote control of Mtb might be due to the inherently small antigenic burden during exposure to the pathogen. While T cells are indisputably important during human tuberculosis, infection with Mtb after exposure is likely to only require few bacilli. Studies with the cattle-model of tuberculosis revealed that infection with M. bovis and development of pathology can occur after exposure to less than ten bacilli, even though, as in humans, not all exposed animals acquired infection in the first place (161). Experiments with guinea pigs exposed to air exhaled by tuberculosis patients, revealed distinct lesions likely to be caused by individual bacilli. This finding was based on the observation that the number of infection foci in the lungs closely correlated with number of infectious droplets inhaled (162). The small bacterial burden sufficient for infection in combination with the mycobacterial inhibition of intracellular macrophage trafficking may not provide enough stimulation to activate resident adaptive T cells. This suggests that the innate immune system may be able to clear these amounts of bacteria directly.

24 Introduction

It is unclear which, if any, of the above myeloid and lymphoid subsets might mediate early host responses leading to resistance or clearance of infection. Whichever immune cells may be involved, their local environment must be key as the interplay between invading pathogens and the immune system is orchestrated by their stromal environment. Non-haematopoietic cells express surface receptors and secrete soluble mediators that shape immune function. In the human lungs, this role is assumed by the lining of the airways, the epithelium. However, epithelial mediators in the airway lining fluid and direct interactions of epithelial cells with Mtb and immune cells have largely been overlooked during the investigation of tuberculosis.

9.7 The airway epithelium: structure and barrier functions against invading agents

The human airways are a complex organ required to simultaneously release toxic carbon dioxide

(CO2) from the body while taking up oxygen (O2) from the atmosphere and thus provide fuel for all biological processes. Structurally, the airways are organised into the upper (or large) airways and the lower (or small) airways. The large airways consist of the trachea, the bronchi and the upper bronchioles branching off into the small airways, formed by the terminal and respiratory bronchioles and the alveoli. Functionally, the respiratory tract leading up to the terminal airways is known as the conducting zone which is required to warm, moisten and filter the inhaled air before it reaches the respiration zone, the alveoli. In the alveoli, the place of gas exchange, blood is oxygenated and CO2 released back into the atmosphere (163, 164) (Figure 9.2 A).

In an adult, the surface of the airways exposed to the environment covers approximately 70m2 (165), the size equivalent of a badminton court, which is completely lined by epithelial cells. The respiratory epithelium contains several cell types which differ between the conducting and the terminal airways (Figure 9.2 A). The conducting airways are lined by pseudostratified epithelium, comprised of beating ciliated cells, secretory goblet and club cells, which facilitate mucus and glycosaminoglycan (GAG) production respectively, and neuroendocrine cells (164). Basal cells, their progenitors, give rise to these populations and replenish the cell layer in case of injury (166). Towards the terminal airways, in the lower bronchioles, the number of ciliated cells decreases while more secretory club cells are present. The alveoli themselves differ structurally from the rest of the respiratory tract. Two major epithelial cell types are found here: type I alveolar epithelial cells, which facilitate gas exchange, and surfactant-producing type II alveolar epithelial cells, which also act as progenitors for both cell types (166) (Figure 9.2 B). Every day, the human lung is exposed to 11 m3 of air (167), which is thought to contain over 100 bacteria per m3 (168, 169). As the first line of defence,

25 Introduction the airway epithelium needs to act as a barrier to repel invading agents and pathogens that might compromise the functionality of the lungs. Foremost, the epithelium provides a physical barrier against pathogens. This is achieved by the formation of tight adhesions between epithelial cells themselves, but also between epithelial and other stromal cells (170). Additionally contributing to the epithelial barrier function is the mucociliary elevator. The beating of ciliated epithelial cells transports invading agents up and out of the airways when they are trapped in the gel-like mucus that is layering the epithelium (171). The mucus layer is mainly maintained by the secretory cells in the epithelial lining and consists of various cross-linked macromolecules, amongst them the glycoproteins mucins. Mucin-production can be enhanced during infections to allow increased trapping of pathogens and their clearance from the respiratory tract (172). While the barrier function has long been appreciated as an important epithelial contribution to lung health, their direct involvement in airway immunity has only emerged recently.

Figure 9.2: Structure of the human lungs and the airway epithelium. (A) The human lung is structurally divided into conducting airways, reaching from the trachea to the bronchioles, and the respiratory zone in the alveoli. (B) Epithelial cells line the lung surface. Various cell types can be found. The actual composition of the airway lining varies between the conducting and the respiratory zone. The conducting airways are dominated by ciliated cells in the trachea leading to the upper bronchioles (1), followed by a section of increased secretory club cell presence leading to the alveoli (2). In the alveoli, type I and type II alveolar epithelial cells constitute the epithelial lining (3).

26 Introduction

9.8 The airway epithelium as part of the respiratory immune system

Being the first point of interaction for most agents entering the airways, epithelial cells require immune-sensing function which helps to decide whether invading agents need to be accommodated or eradicated. Much like classical immune cells, airway epithelial cells express a range of structurally different PRR molecules. These include TLRs (173), C-type lectin receptors (CLR) (174), retinoic acid inducible gene-I-like receptors (RLR) (175) and Nod-like receptors (NLR) (173). TLRs recognise a range of intra- and extracellular pathogen derived patterns, but can also sense host danger signals (176). CLRs, on the cell surface, bind carbohydrates and are associated with the response to fungal infections (177). NLR and RLRs are intracellular receptor families. RLR helicases are activated by nucleic acids and crucial in the host response to viruses and can induce the required type I IFN response (178). NLRs are a cytosolic family of receptors that recognises peptidoglycans and have shifted into focus due to their involvement in inflammasome-formation (179). While the receptor repertoire on each epithelial cell type can differ with their anatomical location in the airways (176), their wide variety allows epithelial responses to a broad range of invading agents and a prompt release of immunomodulatory mediators.

The airway epithelium is very much an active part of the respiratory immune system. Especially studies on chronic airway diseases and viral infections have revealed the contribution of epithelial cells to lung inflammation (180). They act as direct responders to invading agents as well as shaping their immunological environment by recruiting distant or regulating neighbouring immune cells. A selection of the epithelial contributions to the respiratory immune response is outlined in the next section.

9.9 Airway epithelial responses during chronic disorders and infections

Airway epithelial cells are the primary target for several pathogens, including viruses, such as influenza virus A (IVA), rhinovirus and respiratory syncytial virus (RSV), and bacteria, such as Klebsiella pneumoniae, Streptococcus pneumoniae and Pseudomonas aeruginosa (181–186). Epithelial defences against these agents include the release of antimicrobial peptides (AMPs) for direct pathogen-control, and the release of cytokines for immune activation. AMPs are small peptides with broad-spectrum inhibitory or killing-activity against pathogens (187). They can be directly gene encoded or cleaved off larger proteins to become active (188). Epithelial cells secrete AMPs, including lysozyme, lactoferrin, cathelicidin and defensins, into the airway lining fluid. While α-defensins are myeloid-derived, human β-defensins (hBD) are expressed by most epithelial cell types. Some family members, such as hBD1, are constitutively expressed, while others, namely

27 Introduction hBD2, require induction and are released during infection and inflammation (187). AMPs can be further regulated through the local cytokine environment. While anti-inflammatory cytokines can suppress their induction and impair bacterial control (189), activation of epithelial cells by pro- inflammatory mediators increases AMP release (187, 190, 191). The antimicrobial activity of epithelial cells contributes to the “immunological barrier” function of the epithelium.

In response to infection, epithelial cells can release cytokines to shape the inflammatory response in an auto- and paracrine manner. In the healthy lungs, the epithelium tightly regulates the activation state of tissue resident immune cells to prevent unnecessary inflammation through cell-cell-contact and soluble mediators. Especially, alveolar macrophage function is tightly regulated to prevent unwanted inflammatory responses to host cell debris or non-pathogenic antigens. As part of this regulation, epithelial cells can restrict myeloid pro-inflammatory function though direct interaction or release of anti-inflammatory mediators (117). These control mechanisms can be overridden in the presence of pathogens and cross-talk between epithelial and immune cells enhances their respective pro-inflammatory functions (118, 192). Additionally, chemokines released by infected epithelial cells can recruit further immune cells. IL8 and CXCL10, released after viral infection of epithelial cells (193), can recruit neutrophils and lymphocytes (194, 195). Epithelial cells also receive signals released by immune cells. During viral infections, only a limited number of host cells are actively infected and the relay of the inflammatory message by the epithelium is important to mount an appropriate immune response (196).

Inter-individual differences in epithelial responses during inflammation can tip the balances between beneficial and detrimental immune responses. The epithelial response can be substantially influenced by chronic diseases or environmental factors, especially tobacco smoke (197, 198). Chronic airway disease can be caused by inherited mutations, the best known example being cystic fibrosis (199), or by excessive inflammatory responses to environmental agents, as is the case for asthma and chronic obstructive pulmonary disease (COPD) (180). While these disorders can impair lung function through increased mucus formation, they also affect the local inflammatory response. Asthma and COPD have both been shown to persistently change the human epithelial response to viral infections, by altering the basal cell responsiveness to immunological challenge (182, 200). Chronic airway diseases impair the antimicrobial function of the epithelium which may increase the risk for opportunistic infections in these individuals (199, 201). The airway epithelium thus actively and directly shapes the immune response during chronic and acute airway disease. However, while the role of airway epithelium in the immune response against most respiratory infections is well appreciated, surprisingly little is known about their contribution to tuberculosis infection.

28 Introduction

9.10 Rationale for studying the lung immune response to Mtb including the epithelium

Studying the host responses to Mtb infection in the human lungs is a difficult undertaking. Knowledge accumulated about human immune responses in TB is mainly derived from cell lines or primary peripheral leukocytes. These cells are easily accessible and findings are commonly extrapolated to the airways. While studies of peripheral blood have great value for the identification of biomarkers, they cannot fully reflect the events at the site of disease in animal models and humans (91) and do not address the responses of the non-haematopoietic compartment. Especially during the earliest stages of tuberculosis infection, when the Mtb is thought to infect lung resident alveolar macrophages, the pathogen-host interaction is not confined to one cell type. Macrophages are the dominant myeloid subset, but the majority of cells exposed to the environment and inhaled droplets are epithelial cells. While it is only rarely the main focus of scientific investigations, the following sections collate findings, mainly derived from animal models and cell lines, supporting the epithelial contribution to the early stages of the natural history of tuberculosis infection (Figure 9.3).

9.10.1 Evidence for direct epithelial interactions with Mtb in humans

The observation that the airway epithelium is, at the very least, a responder during active pulmonary TB, has long been made. Immuno-histochemical staining of tissue sections or biopsies derived from patients with ATB have identified epithelial cells as a source of cytokines, for example CXCL10 (202) and IL18 (203), and proteolytic factors, amongst them matrix metalloproteinases (105, 204). Additionally, several mediators released into the airways during mycobacterial infections can be derived from immune and epithelial cells alike. IL8, which can be secreted by epithelial cells during inflammation (205), is enriched in bronchoalveolar lavage (BAL) from ATB patients (206–208). Given their vast numbers lining the lung surface, it has been suggested that airway epithelial cells may be a direct target of Mtb infection in vivo. Mtb is aerosolised into droplets of variable sizes. Large droplets are less likely to travel to the small airways and mucociliary clearance might remove these mycobacteria as part of the mucosal barrier, preventing infection. Aerosols less than 5 µm in size, however, travel into the lower airways and are more likely to directly interact with and infect cells. Hernandez-Pando and colleagues have identified Mtb-DNA in the alveolar epithelium of latently infected individuals in the absence of active disease (30, 31), suggesting that entering airway epithelial cells provides a niche for the pathogen either during latency or early after infection.

29 Introduction

In vitro studies on human airway epithelium mainly used the lung adenocarcinoma-derived cell line A549 to mimic alveolar epithelial cells (209). It was found that Mtb enters and replicates in A549 cells and that these cells may control intracellular growth of Mtb. While epithelial cells are not professional phagocytes, they can internalise particles (210) which may provide an entry mechanisms for Mtb into these cells. Uptake of the bacilli has been suggested to be facilitated by macropinocytosis (211) and receptor-dependent mechanisms, partially mediated by the integrins cluster of differentiation (CD) 29 and CD51 (212). The initial adherence of mycobacteria to epithelial cells can be mediated by antigens that bind to surface GAGs, including hyaluronic acid. Two of these antigens are mycobacterial DNA-binding protein (MDP) 1 (213) and heparin-binding hemagglutinin (HBHA) (214), the latter of which is also important for mycobacterial dissemination in mice and might be a marker of human latency (215). It is noteworthy that HBHA is conserved across pathogenic and non-pathogenic mycobacterial species and can be found on M. leprae and M. bovis BCG (214, 216), suggesting that adhesion to or infection of airway epithelial cells is a conserved mycobacterial strategy to establish a “home” in the host.

Infection of epithelial cells triggers various responses to the pathogen. A549 cells have been described to release IL8, CCL2 and even TNF after Mtb infection (205, 217–219). Along the same lines, infection with M. avium, which can cause pathology similar to Mtb, induces IL32 expression in the bronchial epithelial cell line Beas2B (220). The induction of mediator release by mycobacteria, specifically IL8, has been suggested to be mediated by TLR2 (218, 221, 222), TLR4 (221) and Dectin-1 (223). Epithelial infection has also been associated with direct induction of AMPs, most prominently hBD2. hBD2 is increased in A549 cells after Mtb-infection (224) and associates with intracellular Mtb in airway epithelium in mice in vivo (225). Interestingly, even though macrophages are readily infected with Mtb, their capacity to induce β-defensins is limited (191, 226, 227). The airway epithelium may thus act as important contributor to Mtb-infection by supporting the pro- inflammatory and antimycobacterial environment, in a way that is complementary to macrophages. While recognition of mycobacterial strains by airway epithelial cells seems to be conserved, virulent Mtb can be cytotoxic for epithelial cells as opposed to the non-pathogenic M. bovis BCG (228). Through lysis of infected epithelial cells in vitro Mtb can spread further to neighbouring cells (134). This mycobacterial cytotoxicity could be a strategy for establishing infection in the lungs by causing local tissue inflammation and provoking immune cell influx.

While the above findings support the importance of epithelial cells as an interactive interface in humans, they do not shed light on whether Mtb enters epithelial cells after exposure. In a mouse model, Mtb was detected in the epithelium of the upper and lower airways (229, 230). Two days

30 Introduction after intra tracheal infection, the majority of bacilli are found in macrophages and only approximately 10% of intracellular Mtb can be detected in epithelial cells (230). In fact, it has been observed in vitro that the uptake of Mtb by human dendritic cells is 5-fold higher than the uptake by primary tracheal epithelial cells (231), so it needs to be kept in mind, that intracellular infection of epithelial cells may not be required for their contribution to direct Mtb control.

9.10.2 Evidence for epithelial-leukocyte cross talk during Mtb-infection

Epithelial cells have been described to release cytokines and AMPs in response to Mtb-infection. These factors can also be induced by the pro-inflammatory environment created by infected myeloid cells. Uninfected epithelium can be activated in response to paracrine stimuli released by Mtb- infected immune cells. Studies in which supernatants from Mtb-infected myeloid cells were transferred onto primary human airway epithelial cells or A549 cells, showed that IL8, MMPs and hBD2 were induced (105, 191, 204, 205). In turn, mediators released by epithelial cells can affect macrophage control of Mtb. Surfactant proteins (SP), generally released by type II alveolar epithelial cells to reduce the surface tension in the alveoli, can improve macrophage control of Mtb. SP-A and SP-D, while not affecting the outcome of low-dose infection in mouse models (232), act as opsonising agents and facilitate Mtb-adhesion to and uptake by host cells (233, 234). Additionally, epithelial derived hydrolases are secreted into the human airway lining fluid, which can modify cell wall components of mycobacteria to make it easier for macrophages and neutrophils to process and kill intracellular Mtb (235, 236). While SPs and hydrolases are constitutively released into the airways by the epithelium, infection of macrophages can induce paracrine cross-talk with epithelial cells. Using A549 cells or primary human small airway epithelial cells (SAEC), it has been observed that cross-talk can promote a feedback loop that improves macrophage control of Mtb in vitro via the release of GM-CSF or IL1β, respectively (191, 230). Pro-inflammatory mediators in combination with Mtb-antigens released from infected macrophages also drive MMP release from epithelial cells (105). While MMPs are associated with tissue destruction during active tuberculosis, early epithelial MMP9 expression, driven by TNF and ESAT6, increases myeloid recruitment to the site of mycobacterial infection in zebrafish, driving granuloma formation (98). Recruitment of other myeloid subsets such as neutrophils, which are not found enriched in the healthy lung, to the site of infection can be driven directly by Mtb-infected A549 cells in vitro (222). It remains unclear whether this scenario can be driven by primary cells or whether it occurs in vivo. In a mouse model of infection, epithelial expression of CXCL5 was associated with increased neutrophil influx into the lungs (237). The same study showed that CXCL5 was induced directly in a murine alveolar epithelial cell line by Mtb through TLR2, but this mechanism was not verified specifically in the in vivo model.

31 Introduction

Cross-talk between the epithelium and immune cells is not limited to macrophages. Especially during established infection, when the adaptive response has set in, lymphocytes provide a rich source of epithelial-activating cytokines. When non-haematopoietic cells, which include epithelial cells, are unable to respond to IFNγ-stimulation, levels of the lymphotactic CXCL10 are diminished in the lungs of infected mice (238). Non-responsiveness to IFNγ leads to increased neutrophil influx and loss of infection control. Interestingly, airway epithelial cells can also induce IFNγ release from lymphocytes. After infection, epithelial cells have been shown to activate splenocytes from immunized mice as well as human MAIT cells through antigen-presentation (150, 239). This suggests that airway epithelium, to some extent, bridges the innate and adaptive immune response. In summary, based on studies in cell lines and animal models, the airway epithelium has been suggested to be involved in the immunological cross-talk that pertains to the local control of infection, while also orchestrating the influx of further immune subsets which may critically shape the outcome of infection.

Figure 9.3: The epithelial contribution to the early stages of the natural history of tuberculosis infection. Shown is a graphical summary of the experimental evidence of respiratory epithelial involvement during Mtb-infection, derived from work with human and murine cells. Ag, antigen; AMP,

32 Introduction antimicrobial peptide; MMP, matrix metalloproteinase; Mtb, Mycobacterium tuberculosis; PRR, pattern recognition receptor.

9.11 Rationale for studying human primary epithelial cells in tuberculosis

Immunological events in the human lungs during tuberculosis infection are not very well understood, especially during the very early stages of infection, after inhalation of Mtb into the human lungs. At this point there is ample opportunity for the epithelium to contribute to Mtb- control or shape the immunological environment. The mechanisms described in the previous sections have largely been investigated with the use of human cell lines or animal models. Very few attempts have been made to interrogate primary human respiratory epithelium in TB. In fact, no in depth study has been undertaken to study the human primary airway epithelial responses to direct infection and infection-mediated immune activation. To fill this knowledge gap, primary airway epithelial cells from several donors, to reflect biological variation, were sampled and interrogated in vitro and ex vivo.

An improved insight into the role of the airway epithelium during tuberculosis is necessary to better understand the interaction of Mtb with the human lungs, which in turn is pivotal in determining the outcomes of Mtb exposure, i.e. establishing of infection or elimination.

33 Hypothesis

10 Hypothesis

Primary human airway epithelial cells respond to Mtb-infection directly and indirectly via innate immune cross-talk and shape the immune response during tuberculosis infection.

10.1 Aims

To address this hypothesis, the following aims were pursued in the three results chapters presented in this thesis:

1. Aim: To interrogate primary bronchial epithelial cells (PBECs) as direct responders to Mtb- infection in vitro.

2. Aim: To assess whether PBECs participate in immune cross-talk with infected myeloid cells in vitro and investigate the mechanisms.

3. Aim: To interrogate protein and transcriptomic signatures of the human mucosal epithelial lining across different stages of the natural history of tuberculosis infection ex vivo.

34 Materials

11 Materials

11.1.1 Reagents Table 11.1: Antibodies. Source Target Isotype tag Clone Manufacturer organism polyclonal R&D Systems, IL27 goat n/a IgG Abingdon, UK Dectin- IgG mouse 259931 R&D Systems 1/CLEC7A 2B Miltenyi Biotec, TLR2 IgG mouse REA109 1 Surrey, UK IFNα/βR2

IgG mouse MMHAR-2 R&D Systems (IFNAR2) 2A

IFNγ IgG2A mouse K3.53 R&D Systems

IL1β IgG1 mouse 2805 R&D Systems

TNF IgG1 mouse 1825 R&D Systems Isotype IgG mouse 11711 R&D Systems control 1

Blocking and neutralisation Isotype IgG mouse 20102 R&D Systems control 2A Isotype IgG mouse 20116 R&D Systems control 2B Isotype IgG mouse REA293 Miltenyi Biotec control 1 Isotype polyclonal goat n/a R&D Systems control IgG New England β-actin IgG rabbit D6A8 Biolabs, Hitchin, UK Phospho- New England STAT1 IgG rabbit D4A7 Biolabs (Tyr701) polyclonal New England STAT1 rabbit n/a Western Blot IgG Biolabs HRP-linked polyclonal New England goat HRP n/a IgG IgG Biolabs

Brilliant Biolegend, San CD14 IgG2a mouse M5E2

- Violet 421 Diego, USA

sorting Brilliant CD15 IgM mouse SSEA-1 Biolegend Violet 605 Becton Dickinson CD3 IgG mouse PE-CF594 UCHT1 1 (BD), Oxford, UK Fluorescence PerCP/

activated cell CD66b IgM mouse G10F5 Biolegend Cy5.5 n/a, not applicable

35 Materials

Table 11.2: Mycobacterial and synthetic ligands. Ligand Manufacturer CFP Mycobacterium tuberculosis, Strain H37Rv, Biodefense and Emerging Infection (BEI) Culture Filtrate Proteins NR-14825 Resources, NIAID, NIH, Manassas, USA CWF Mycobacterium tuberculosis, Strain H37Rv, BEI Resources Cell Wall Fraction NR-14828 CytoFr Mycobacterium tuberculosis, Strain H37Rv, BEI Resources Cytosol Fraction NR-14834 LM-MS Lipomannan from Mycobacterium smegmatis InvivoGen, Toulouse, France

Pam2 Pam2CSK4 InvivoGen

Pam3 Pam3CSK4 InvivoGen

PolyIC Polyinosine-polycytidylic acid Sigma-Aldrich, Poole, UK rESAT-6 ESAT-6 Recombinant Protein Reference Standard BEI Resources NR- 14868 WCL Mycobacterium tuberculosis, Strain H37Rv, BEI Resources (H37Rv) Whole Cell Lysate (NR-14822) WCL Mycobacterium tuberculosis, Strain HN878, BEI Resources (HN878) Whole Cell Lysate NR-14824

Table 11.3: Gene expression assays. Target gene Gene expression assay Assay type

ACTB AX-003451-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) CAMP AX-019790-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) CXCL10 AX-007871-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) DEF4B AX- 012997-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) GAPDH AX-004253-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) HPRT1 AX-008735-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) IFI44 AX-016368-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) IFIT1 AX-019616-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) IFNB1 AX-019656-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) IL36G AX-007959-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) IL6 AX-007993-01 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) IL8 AX-004756-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) MMP9 AX-005970-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) PGK1 AX-006767-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) S100A7 Hs01923188_u1 TaqMan® Gene Expression Assays (ThermoFisher) S100A7A AX-027145-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher) TLR2 AX-005120-00 Solaris Human qPCR Gene Expresion Assay (ThermoFisher)

36 Materials

Table 11.4: Chemical stimuli and inhibitors. Chemical Manufacturer DPI Diphenyleneiodonium Sigma Rotenone Sigma DMSO Dimethyl sulfoxide Sigma PMA Phorbol 12-Myristate 13-Acetate Sigma

Table 11.5: Recombinant human cytokines. Cytokine Manufacturer IFNγ Interferon γ R&D Systems TNF Tumor necrosis factor R&D Systems IL1β Interleukin 1 β Millipore IFNβ Interferon β Miltenyi Biotec

11.1.2 Buffers and culture media Table 11.6: Buffers.

Buffer Ingredients

Phosphate buffered saline (PBS) PBS tablets (Sigma) were dissolved in dH2O and autoclaved for sterility.

ELISA wash buffer PBS supplemented with 0.05% Tween20 (Sigma)

1.37 M NaCl (Sigma) and 200mM Tris base (VWR, Lutterworth, UK) were 10x Tris-Buffer Saline (TBS) dissolved in dH2O and the pH adjusted to 7.6.

TBS with Tween20 (TBST) 10x TBS was diluted to 1x with dH2O and 0.1% Tween20 added.

PBS was supplemented with 0.5% BSA (Sigma) and 2 mM EDTA FACS buffer (ThermoFisher Scientific, Epsom, UK) and 0.2μm sterile filtered before use.

Red blood cell (RBC) lysis buffer 10x RBC lysis buffer (BioLegend) was diluted to 1x in dH2O

PBS was supplemented with 0.05% Tween80 (Sigma) and placed in a PBS/Tween80 waterbath at 36°C to fully dissolve. The buffer was then 0.2μm sterile filtered before use.

37 Materials

Table 11.7: Human and bacterial cell culture media. Medium Ingredients

Bronchial Epithelial Cell Bronchial Epithelial Cell Basal Medium (BEBM) (Lonza, Walkersville, USA)

Growth Medium (BEGM) supplemented with BEGM SingleQuot Kit Suppl. & Growth Factors (Lonza)

Alveolar macrophage RPMI 1640 (RPMI) (Sigma) supplemented with 10% heat-inactivated (AMΦ) culture medium human serum and 50μg/ml gentamycin (Sigma)

AMΦ and THP-1 infection RPMI supplemented with 5% heat-inactivated human serum (Sigma) medium

RPMI supplemented with 10% heat-inactivated fetal bovine serum (FBS)

Human culture cell medium THP-1 culture medium (Sigma), 50000U penicillin, 50mg streptomycin (Sigma) and 5μM β-

mercaptoethanol (Sigma)

4.7g Middlebrook 7H9 broth base (Sigma) were dissolved in 900 ml dH2O. The medium was then supplemented with 10 % Middlebrook Oleic Acid Albumin Dextrose Catalase (OADC) (BD), 0.5% glycerol (VWR) and 0.05% 7H9 broth Tween80. The broth was 0.22μm sterile filtered through vacuum filtration units (Rapid-Flow™ filters MF 75, Nalgene, ThermoFisher) and 10μg/ml amphotericin (Sigma) added.

19.47g Middlebrook 7H10 agar base (Sigma) were dissolved in 900ml dH2O and supplemented with 0.5 % glycerol and 0.05 % Tween80. The agar base was then autoclaved at 121°C for 15 min and allowed to cool 7H10 agar down to 50°C before 10 % OADC was added. Agar was poured into Ø 90 mm petri dishes and allowed to solidify overnight. Sterility was confirmed for each batch. Plates were stored at 4°C until used. Bacterial culture medium

37g LB powder (Merck, Darmstadt, Germany) were dissolved in 1000ml dH O. LB agar was autoclaved, poured into petri dishes and allowed to Luria-Bertani (LB) agar 2 solidify overnight. Sterility was confirmed for each batch. Plates were stored at 4°C until used.

38 Methods

12 Methods

12.1 Recruitment and ethics statement

12.1.1 Ethics statement

All human samples were collected in accordance with the Human Tissue Act 2004 and written informed consent was obtained from all participants (National Research Ethics Service approval reference 07/H0712/85+5).

12.1.2 Recruitment and exclusion criteria

Healthy volunteers recruited for this study were aged between 18-65 years and had no past history of diabetes, renal failure, cardiovascular or immunosuppression or current respiratory conditions. TB exposed healthy individuals were recruited within 16 weeks of identification of the ATB index case, irrespective of immunological TB test results. Chest X-rays of all exposed individuals were normal and no volunteer had developed ATB at the time of recruitment. The level of Mtb-exposure was determined with a detailed questionnaire as previously described (55). All suspected active and confirmed active tuberculosis (ATB) patients were HIV-negative and co-morbidities were recorded. For bronchial sampling, suspected ATB patients were recruited at the point of diagnostic bronchoscopy for suspected pulmonary TB and the final diagnosis was recorded when available. Amongst the demographic information collected were BCG vaccination status, age, smoking, ethnicity and previous medical history. TB exposed individuals and infected or suspected infected patients were recruited from Contact and TB clinics at Imperial College NHS Trust (St. Mary’s Hospital), London North West Healthcare NHS Trust (Ealing Hospital, Northwick Park Hospital) and Barts Health NHS Trust (Newham Chest Clinic). Healthy Mtb-naïve volunteers were recruited through local advertisements at Imperial College London or through word-of-mouth. Peripheral blood samples were obtained from healthy volunteers within the Respiratory Infections Section at the National Heart and Lung Institute, Imperial College London.

12.1.3 Demographic overview of healthy volunteers and patients

For Results Chapter 1 and 2, primary bronchial epithelial cells (PBEC) were recovered from healthy volunteers and expanded in vitro (see 12.2.5). For Results Chapter 3, the mucosal lining of the upper and lower airways was sampled for detection of soluble mediators by Meso Scale Discovery immune assays and the global transcriptome by RNA Sequencing. Volunteers and patients were recruited and

39 Methods assigned to three groups. For the NLF cohort, nasal samples were collected from patients with LTBI and ATB. For the Exposure cohort, nasal and bronchial samples were collected from healthy Mtb- unexposed volunteers, healthy volunteers with recent exposure to a culture confirmed pulmonary TB patient and patients undergoing diagnostic bronchoscopy for suspected pulmonary TB. Samples for RNA Sequencing were collected from the bronchial tree of the same groups and there was overlap between the volunteers and patients of the Exposure cohort recruited for mucosal lining fluid sampling and for RNA Sequencing. The demographic overview of all volunteers recruited for this work is shown below:

Table 12.1: Demographic characteristics of all recruited volunteers and patients. Exposure Volunteers Exposure NLF cohort sampled for cohort cohort (Aim 3, RNA PBECs (Aim 2, MLF) Sequencing) n 27 47 42 30

Sex - female 13 24 16 11

Age - median, IQR 24, 23-27 40, 29.75-55.25 24, 23-44.25 26, 23-40

Ethnicity White 20 9 23 16 Hispanic 0 1 1 0 Black 4 11 8 6 Middle Eastern 0 4 0 0 Asian 2 7 7 5 Indian Sub-continent 1 14 3 3 Mixed 0 1 0 0 NLF, nasal lignin fluid; MLF, mucosal lining fluid; IQR, interquartile range

12.1.4 Determination of the contacts score of TB exposed healthy volunteers

To quantify the levels Mtb-exposure, contact scores were calculated for each TB exposed healthy subject. The contact score has previously been developed by Shams and colleagues (55). In brief, based on a questionnaire, the following factors were determined:

Relationship: relationship of the exposed subject with the pulmonary ATB index case (household sexual contact, household non-sexual contact or non-household contact)

40 Methods

Infectivity: infectivity of the pulmonary ATB index case (sputum smear positive or negative)

Extent: extent of exposure, incorporating the time spent with the pulmonary ATB index case in a shared space

퐶표푛푡푎푐푡 푠푐표푟푒 = 푅푒푙푎푡𝑖표푛푠ℎ𝑖푝 ∗ 퐼푛푓푒푐푡𝑖푣𝑖푡푦 ∗ 퐸푥푡푒푛푡

12.1.5 Determination of the infection status of TB exposed healthy volunteers

To determine whether TB exposed healthy subjects were infected after sustained contact with pulmonary ATB index cases, ELISPOT-based IGRAs (T-SPOT.TB) were performed and defined as positive, indeterminate or negative as described in section 12.6.6. Additionally, the majority of TB exposed subjects underwent skin testing (TST) in clinic. TST outcomes were interpreted by a clinician as positive when the induration was > 14 mm (subject with previous BCG vaccination) or > 4 mm (subject without previous BCG vaccination).

12.2 Sampling of the human respiratory tract

12.2.1 Nasosorption

Nasosorption (Hunt Developments Ltd, Midhurst, UK) is a non-invasive technique to collect the nasal lining fluid (NLF) from the nasal mucosa. For this, a small filter paper sized 7mm x 35mm made from synthetic adsorptive matrix (SAM) based on fibrous polyester is touched upon the mucosal surface to adsorb any secreted fluid. For NLF sampling, nasosorption strips were inserted into the anterior region of each nasal inferior turbinate (240) for 2 min. Strips were placed into the insert buckets of Costar® Spin-X® centrifuge tube filters with a cellulose acetate membrane (pore size 0.22μm) (Corning Incorporates, New York, USA). The tubes were kept on ice and transported to the lab for processing within 30 min (see 12.7.3).

12.2.2 Bronchoscopy

Bronchoscopies were performed by Dr. David Connell, Dr. Hannah Jarvis and Dr. Onn Min Kon with the support of Mr. Samuel Bremang, Ms. Lisa Grass, Miss Helen Piotrowski and Miss Hiromi Uzu at the Endoscopy Unit, St. Mary’s Hospital, London. In brief: Subjects were sedated locally through intra venous midazolam and occasional fentanyl. The Olympus IT 260 bronchoscope was then passed

41 Methods through the mouth and visually guided into the right middle and lower lobe of the airways. Samples were taken as described below. After the procedure, the volunteers were recovered in St. Mary’s Hospital until they were considered as fit for discharge by the clinical team (in accordance with the Imperial College Healthcare guidelines).

12.2.3 Bronchosorption

Bronchosorption (Hunt Develpoments) samples the bronchial lining fluid (BLF) similar to nasosorption (see 12.2.1). BLF recovered by bronchosoprtion allows the recovery of mediators at significantly less diluted concentrations (Figure 12.3 D). SAM strips of bronchosoprtion devices are sized 1.8 x 30mm and attached to the end of an 81.5cm catheter-sheathed wire which allows insertion through the bronchoscope into the lower airways to sample BLF. Once in the right middle lobe, the sheathed SAM strip was extended and gently touched against the bronchial wall for 20s (Figure 12.1). The strip was then retracted and the bronchosoprtion device removed from the airways. The strips were cut off and placed into the insert buckets of centrifuge spin filters on ice and transported to the lab for processing within 30 min. Two bronchosoprtion devices were used per volunteer or patient.

12.2.4 Bronchial brushings for ex vivo transcriptomics

For ex vivo transcriptomics, three sequential brushes with the dimensions of 5mm x 10mm (BC- 202D-5010, Olympus Keymed, Southend-on-Sea, UK) were used to collect airway epithelial cells from the right lower lobe of healthy volunteers or patients undergoing diagnostic bronchoscopy for suspected active pulmonary TB (Figure 12.1). Importantly, to recover cells, brushings were gently pressed against the bronchial walls to prevent bleeding and subsequent blood cell contamination of the samples. All samples collected in this manner were macroscopically free of red blood cells. Of the three brushings, two brushes were immediately immersed in 750μl Trizol (ThermoFisher). Cells were dislodged through shearing of the brushes through a 1000μl pipette tip. Samples were placed on ice and transferred to a -80°C freezer for storage within 30 min. To obtain representative differential cell counts for the transcriptomic data, one brush (the second sequential brush taken) was sheared through the opening of a 5ml syringe barrel into 10ml PBS and transported to the Cytopathology unit St. Mary’s Hospital for a differential cell count (Dr. Corrina Wright).

42 Methods

12.2.5 Bronchial brushings for in vitro expansion of primary cells

To expand primary bronchial epithelial cells (PBECs) in vitro, basal epithelial cells were recovered from the right lower lobe through vigorous brushing of up to three brushes against the bronchial wall. To recover cells, brushes were sheared against the opening of a 30ml syringe-barrel into 10ml warm BEGM (Lonza). Cells were kept at room temperature and transported to the lab immediately and processed for culture within 30 min (see 12.3.1).

Figure 12.1: Sampling of the bronchial lining through bronchosoprtion and brushings. To sample the bronchial mucosal lining, bronchial lining fluid (BLF) was collected by bronchosoprtion from the right middle lobe of the lungs. Bronchial epithelial cells were recovered through bronchial brushes from the right lower lobe. Samples were collected from the 4th-5th bifurcation of the lungs.

12.2.6 Bronchoalveolar lavage

Bronchoalveolar lavage (BAL) was performed during bronchoscopy through instillation of 150-180ml 0.8 % saline into the right middle lobe for a 100ml return. Unfiltered BAL was sent for mycobacterial cultures (for healthy TB exposed volunteers) or transported to the laboratory on ice for further processing.

12.3 Cell culture

12.3.1 Primary bronchial epithelial cells

After recovery from the bronchial tree (see 12.2.5), the cell suspension was immediately transported to the lab and processed for in vitro culture. The suspension was transferred into a 15ml conical centrifuge tube (VWR) and centrifuged for 6 min at 300xg at 24°C. The supernatant was removed completely and the cell pellet resuspended and dispersed in 1ml warm BEGM until a single cell

43 Methods suspension was obtained. 10μl of each sample were used to count total cells and beating ciliated epithelial cells via trypan blue exclusion. The remaining cells were transferred into a 25 cm2 cell culture flask (VWR) in 7-10ml BEGM and placed into a 37°C humified CO₂ incubator (Binder, Tuttlingen, Germany). Processing was completed within 30 min of the recovery of the cells from the bronchial lining. All tissue culture vessels were coated with 100μg/ml collagen I (Cambridge bioscience, Cambridge, UK), 100μg/ml fibronectin (Roche, Welwyn Garden City, UK) and 100μg/ml BSA (Sigma) in BEGM overnight before use.

Two days after the start of culture, non-adherent cells were removed through careful rinsing of the tissue culture flask with warm medium. Fresh BEGM was added afterwards. Subsequently, medium was replaced every two to three days with fresh warm BEGM. Cells were passaged when 90% confluent. For subculture, culture medium was removed from flasks and the cell layers washed twice with warm HBSS (Lonza). Trypsin EDTA (TE) (Lonza) was added and cells were placed back into the incubator. After 3 min of incubation, culture flasks were gently tapped to dislodge cells from the surface and incubated a further 2-3 min. The cells in suspension were then removed and added to warm BEGM and Trypsin Neutralisation Solution (TNS) (Lonza) at volume ratios of 1:1:2. To detach the residual cells, TE treatment was repeated. After 2 min, TNS was added at 2x the TE volume into the flask and the cell suspension transferred into a conical centrifuge tube with warm BEGM. Cells were centrifuged and resuspended as a single cell suspension in fresh medium. PBECs were then seeded into coated tissue culture flasks at 1:3. PBEC phenotype (cobblestone appearance) was confirmed for all cultures by lightmicroscopy (VWR) (Figure 12.2 A). One representative culture was stained for cytokeratin-19 (Figure 12.2 B) (see 12.8.2).

All in vitro cultures were maintained for two passages, before PBECs were seeded for experiments at 0.08x106 cells/ml. In the experimental passage, when cells were 80-90% confluent, BEGM was changed to BEBM and PBECs were rested over night before use. Immediately before experimentation, the medium was replaced with fresh warm BEBM.

44 Methods

Figure 12.2: Expansion of primary bronchial epithelial cells in vitro. Primary bronchial epithelial cells (PBECs) were grown from bronchial brushings. (A) In culture, primary basal cells adhered to collagen-fibronectin coated tissue culture plastic within 2 days of culture and formed clusters, which resulted in a confluent monolayer after 7-9 days of culture. PBECs displayed the classical ‘cobblestone’ morphology. Shown are representative cultures from three donors at the indicated time points at 10x magnification (Eclipse TS100 and Digital Sight camera system, Nikon, Surrey). (B) The epithelial phenotype was further confirmed by fluorescence microscopy staining for cytokeratin-19 in one representative donor. (20x, CCD camera microscope, Zeiss). Ab, antibody.

12.3.2 Alveolar macrophages

To isolate alveolar macrophages (AMΦ) out of bronchoalveolar lavage fluid (BALF), BALF was passed through 70μm mesh strainers (Miltenyi Biotec) to remove mucus and obtain a single cell suspension. Strained BALF was then centrifuged for 5 min at 600xg and 4°C. Some of the cell-free BALF supernatant was recovered and filtered as described in (see 12.7.1) and stored at -20°C until further

45 Methods use. All the residual supernatant was discarded and the cell pellet resuspended in 2ml RBC lysis buffer and incubated for 10 min at 4°C to remove residual red blood cells. After lysis, cells were washed with RPMI, centrifuged and resuspended in AMΦ culture medium (RPMI, 10% human serum, 50μg/ml gentamycin). AMΦ numbers were determined by trypan blue exclusion and seeded at 1x106/ml. AMΦs were enriched through overnight adherence to tissue culture plastic. The next day, all non-adherent cells were washed off with warm medium, leaving adherent alveolar macrophages behind. For experiments, AMΦ were cultured in infection medium with 5% human serum or BEBM as required.

12.3.3 Peripheral blood leukocytes

5-10ml of peripheral whole blood was collected into Lithium-Heparin coated tubes (BD vacutainer). Peripheral blood leukocytes (PBL) were isolated through the removal of red blood cells (RBC). For this, whole blood was mixed well with RBC lysis buffer at a ratio of 1:10 and incubated for 10 min at room temperature with regular mixing. After the incubation period and RBC lysis, cells were centrifuged at 600xg for 10 min at 4°C to pellet PBLs. Supernatant was discarded completely and residual RBC buffer removed by pipetting. PBLs were washed once with RPMI and resuspended in BEBM for cell number determination.

12.3.4 Peripheral blood mononuclear cells

Peripheral blood mononuclear cells (PBMCs) were isolated from heparinised whole blood through Ficoll-Paque density gradients. Whole blood was diluted to equal volume with warm RPMI (Sigma) and up to 30ml of diluted blood was carefully layered onto 15 ml Ficoll-PaquePLUS (GE Healthcare, Amersham, UK). PBMCs were then separated by centrifugation at 900xg for 20 min at room temperature with the centrifuge deceleration set to 1. After separation, PBMCs were collected from the plasma/Ficoll interphase and washed twice with RPMI by centrifugation at 600xg for 5min. Cell were kept in RPMI in the incubator until used in T-Spots (see 12.6.6).

12.3.5 THP-1 monocytic cells

The human monocytic cell line THP-1 was obtained from the American Type Culture Collection ATCC (TIB-202, LGC Standards). Cells were maintained in THP-1 culture medium and passaged at approximately 1x106 cells/ml. For passaging, cells were washed by centrifugation for 7 min at 600xg at room temperature and resuspended in THP-1 culture medium at 0.2x106 cells/ml. For experiments, THP-1 cells were seeded at 1x106/ml in infection medium or BEBM as required.

46 Methods

To generate macrophages, THP-1 monocytes were differentiated phorbol 12-myristate 13-acetate (PMA). 15x106 cells were incubated with 50nM PMA in 75 cm2 tissue culture flasks. After 24h, the medium was removed and the adherent monolayer carefully washed with warm PBS. Cells were then detached with 0.05% Trypsin/0.02 % EDTA (Sigma) in PBS for 5 min and washed by centrifugation in culture medium. Cells were resuspended in fresh warm culture medium and counted. Macrophages were seeded at 1x106 cells/ml and allowed to adhere and rest overnight. The medium was changed to infection medium before use in experiments.

12.4 Cell counting

12.4.1 Trypan blue exclusion

PBECs and bronchoalveolar lavage cells were counted manually by trypan blue exclusion. 0.4% trypan blue solution (Sigma) was syringe filtered to remove crystals and aggregates. Cells were diluted 1:2 or 1:10 in trypan blue. 10μl cell suspension were added to the counting chamber of a FastRead counting slide (Immune systems, UK) and cells were counted under a light microscope (VWR). The cell count/ml was calculated as described below:

퐶푒푙푙푠⁄푚푙 = (푎푣푒푟푎푔푒 푐표푢푛푡⁄푠푞푢푎푟푒) ∗ 10000 ∗ 푡푟푦푝푎푛 푏푙푢푒 푑𝑖푙푢푡𝑖표푛 푓푎푐푡표푟

12.4.2 Automated counting by Countess Automated Cell Counter

PBLs, PBMCs and THP-1 cells were enumerated by Countess Automated Cell Counter (ThermoFisher). Cells were diluted 1:2 in 0.4% trypan blue (ThermoFisher) and 10μl of the suspension added to Countess® Cell Counting Chamber Slides (ThermoFisher). Live cell counts were used to determine cell numbers.

12.5 Bacterial cultures

12.5.1 Mycobacteria

Mycobacterium tuberculosis (Mtb) H37Rv or Mycobacterium bovis Bacillus Calmette- Guérin (BCG) (Statens Serum Institut, Copenhagen, Denmark) was cultured in 7H9 broth. Growth was monitored by measuring the optical density (OD) at 600nm (Ultrospec 10, GE Healthcare). Cultures were harvested in log phase (OD600nm=1) and frozen down in 15% glycerol in 0.5-1ml aliquots. Stocks were stored at - 80°C. To standardise infection doses, cells were infected from frozen stocks and multiplicity of infections (MOI) determined based on the mycobacterial counts (colony forming units (CFU)) of the

47 Methods stocks (H37Rv: 2.5x108/ml, BCG: 5x108/ml). For some experiments, the clinical Mtb isolates CH (241), Gurung 333 or NPH4216 (241) were used, which were a kind gift from Dr. Sandra Newton (Department of Medicine, Imperial College London). 12.5.2 Enumeration of mycobacteria via colony forming units

Mycobacteria were enumerated via colony forming units (CFU) on 7H10 agar. For this, mycobacterial cultures were 10-fold serially diluted in 500μl PBS/Tween80. 50μl of neat stocks and all prepared dilutions were spread out onto agar plates at least in duplicates with 10μl inoculation loops (VWR). To control for contaminations, the dilutions were also plated on LB agar. Agar plates were air dried and incubated at 37°C for 3-4 weeks. CFU were counted manually after this period if LB controls were clean.

12.5.3 Antimycobacterial activity assays

Effects of antimicrobial peptides (AMPs) hBD2 (Peprotech, London, UK), koebnerisin (S100A7A/S100A15) (Fitzgerald, Acton, USA) and psoriasin (242) were tested by monitoring growth inhibition of Mtb in liquid culture. Assays were performed in clear flat bottom 96 well plates. AMPs and controls were diluted in fresh 7H9 to the desired concentration. Antibiotics gentamycin (Sigma) and amikacin (Sigma) were used as positive controls for mycobacterial killing at 100 μg/ml and 200

μg/ml, respectively. Mtb was added for a final OD600nm of 0.15-0.2 and a total volume of 200 μl/well. Plates were sealed with plateseals (Greiner Bio-One, Stonehouse, UK) and parafilm (VWR) and incubated shaking for up to 7 days at 36°C. Culture growth was monitored by measuring optical density at 595nm with the iMark Microplate Absorbance Reader (Biorad, Life Science, Hertfordshire, UK). On day 7, cultures were plated on 7H10 for CFU enumeration.

12.5.4 Streptococcus pneumoniae

Streptococcus pneumoniae serotype 9V (strain 10692) was a kind gift from Dr. Michael Edwards. S. pneumoniae was grown in Todd Hewitt broth (Sigma) supplemented with yeast agar (Sigma). Bacteria were harvested in the logarithmic growth phase. Frozen stocks contained 5x108 CFU/ml.

48 Methods

12.6 Cell stimulation and infections

12.6.1 Stimulation of PBECs

For stimulation of PBECs with microbial or synthetic PRR-ligands or cytokines (Table 11.2), stimuli were diluted to 10x of the final concentration and diluted to 1x in the culture plate. After 24h, supernatants or RNA were harvested.

12.6.2 Infection and stimulation of human cells with mycobacteria

For infections, Mtb was thawed and well-resuspended by pipetting. To prevent non-specific stimulation through residual 7H9 broth, the appropriate MOI was then washed in cell culture medium through centrifugation at 15000xg for 5 min. Mtb was then resuspended in the appropriate cell culture medium and sonicated for 40 s in an ultrasonic waterbath (XUBA Analogue Ultrasonic Bath, Grant Instruments, Cambridgeshire, UK) to disperse clumps. Mtb was then immediately added onto cells for infection.

To measure Mtb-uptake and adherence to THP-1 macrophages or PBECs, Mtb was added onto cells for 24h. The cell monolayer was then carefully washed 2-3 times with warm medium to remove free Mtb. Infection was then determined by cell lysis with 0.1% Triton-X/PBS-Tween80 for 5 min at 37°C. Lysates were serially diluted in PBS/Tween80 and plated on 7H10 agar. For some experiments, 200g/ml amikacin (Sigma) was added for 2h before cell lysis to kill extracellular bacteria.

To measure mediator release or gene expression, myeloid cells or PBECs were infected with Mtb at the indicated MOI and culture supernatants or RNA harvested at the indicated time as descibed.

For transwell experiments, PBECs were seeded into 24- or 12-well tissue culture plates and 0.4m cell culture inserts (Millicell® Cell Culture Inserts, Millipore, Darmstadt, Germany) were placed on top. 0.25x106 THP-1 cells (or AMΦ) in BEBM were then added into the inserts. Mtb was added to the epithelial or myeloid compartment as desired at an MOI of 5 over THP-1 cells. For cytokine measurements, culture supernatants were harvested from the tissue culture wells after inserts were removed and processed as described in (see 12.7.1).

To study the effect of signalling inhibition, blocking antibodies or chemical inhibitors were used to interrogate signalling cascades. For all inhibition experiments, target cells were pre-incubated with relevant inhibitors for 30-45 min before infection with Mtb. As control, the appropriate isotype or vehicle controls were used. When signalling was interrogated in the transwell system, blocking

49 Methods antibodies were added to the bottom well 30-45 min before transwell inserts and THP-1 cells were added.

12.6.3 PBEC stimulation with conditioned medium from alveolar macrophages

To generate conditioned medium from AMΦs, macrophages were infected with Mtb H37Rv at MOI 5 in infection medium (RPMI with 5 % human serum). As control, uninfected AMΦs as well as cell-free infection medium with or without Mtb were prepared. After 24h, the cell culture supernatants were removed and filtered as described in (see 12.7.1). Conditioned media were stored at -80°C until used.

To stimulate PBECs with AMΦ-conditioned medium and the appropriate controls, conditioned media were diluted 1:10 or 1:100 in fresh BEBM and added to PBECs. After 24h of stimulation, culture medium was removed and the cells lysed in Trizol for RNA extraction.

12.6.4 Mtb growth-control by THP-1 monocytes and macrophages in the presence of PBECs

For THP-1 macrophage growth control experiments, macrophages were generated and infected in infection medium as described above. After 3h, culture medium was removed and cells were thoroughly washed to remove extracellular Mtb. At this point, Mtb-uptake was assessed by enumeration of CFUs in selected wells. Fresh infection medium was then added and transwell inserts with or without PBECs placed on top of the infected macrophages for up to 72h. In preparation for this, 0.5x105 PBECs were seeded in collagen-fibronectin coated transwell inserts and cultured for 48h. 24h before use in experiments, BEGM was changed to RPMI with 5% human serum. At the indicated time points, the Mtb-burden in the macrophage monolayer or in the whole culture well was determined.

For determination of CFUs in the macrophage monolayer, the transwell insert and the culture medium were carefully removed and monolayer lysed for Mtb-plating. For determination of CFU in the whole culture well, TritonX-100 was added directly to the culture medium at a final concentration of 0.1%. The transwell inserts were then removed and rinsed into the bottom well for plating of the lysates.

For THP-1 monocyte growth control experiments under direct contact with PBECs, 1.25x105 THP-1 cells were seeded into tissue culture plates with or without PBECs in BEBM. Mtb was directly added

50 Methods at an MOI of 5 over THP-1 cells. After 24 and 72h, TritonX-100 was added directly to the culture medium at a final concentration of 0.1% and lysates were plated to determine Mtb CFUs.

12.6.5 Transwell chemotaxis of peripheral blood leukocytes

Chemotaxis of peripheral blood leukocytes (PBLs) towards conditioned cell-free medium of infected THP-1 and PBECs was measured in a transwell system. Conditioned medium was generated through infection of 0.5x106 THP-1 monocytes with Mtb H37Rv (MOI5) in a 12 well format in the presence or absence of PBECs in BEBM. After 48h, supernatants were harvested and 0.2μm sterile filtered twice to remove all cells and Mtb. Cell free supernatant was stored at -80°C until used in experiments.

Chemotaxis assays were performed in transwell plates with 5m polycarbonate membrane cell culture inserts (Corning). Transwell inserts were removed and 600μl conditioned medium or BEBM (as medium control) was added to the bottom culture well. The plate was allowed to equilibrate in a humidified CO2 incubator for 30 min before transwell inserts were are added back into the culture wells. 20μl BEBM was added into the transwell to wet the membrane. PBLs were isolated as described above and 0.25x106 cells added to the insert. The culture plates were then placed back into the incubator to allow chemotaxis. After 3h, 2mM EDTA was added to the bottom well, left for 5 min. During this time, the plate was regularly gently tapped to dislodge cells from the transwell membrane. All inserts were then removed immediately and cells harvested from both compartments. Cells were pelleted by centrifugation at 900xg for 5 min at 4°C, resuspended in 50μl Cytofix Fixation buffer (BD) and fixed for 10 min at 4°C. Cells were washed with FACS buffer once and resuspended in exactly 100μl FACS buffer, sealed airtight and placed in the cold room overnight. The next day, 100μl FACS buffer was added to the fixed cells and each sample was enumerated through acquisition for 120s using a BD LSR II flowcytometer. Migration of different cell types was determined according to size and granularity through forward (FSC) and side scatter (SSC), respectively, using FlowJo v10 (FlowJo Data analysis software, Ashland, USA).

12.6.6 Enzyme-Linked Immunospot for IFNγ

T-SPOT.TB (Oxford Immunotech, Oxford, UK) is an Enzyme-Linked ImmunoSpot (ELISPOT)-based assay to detect Mtb-specific IFNγ-release by PBMCs. The test was used to confirm Mtb-infection in healthy volunteers recruited for this study as per the manufacturer’s instructions. 2.5x105 PBMCs/well were seeded in 100μl Aim V medium (ThermoFisher) in precoated T-Spot plates. PBMCs were stimulated with AIM V (negative control), phytohemagglutinin (PHA, positive control) or Mtb-antigens (ESAT-6 or CFP-10). The plates were placed in a humidified 36°C CO2 incubator for

51 Methods

18h. To develop T-Spots, cells and culture supernatants were carefully removed without touching the bottom of the well. Wells were washed 3 times with PBS and HRP-tagged detection antibody was added for 1h at 4°C. After the incubation, the detection antibody was washed off with PBS and BCIP/NBTplus substrate solution was added to the wells for 7 min at room temperature in the dark.

After development, the substrate was removed, the wells washed with dH2O and left to airdry. IFNγ- release was measured through enumeration of spot forming cells (SFC) with an automated ELISpot reader (AID-GmbH, Straβberg, Germany). The T-Spot result passed quality control if the negative control wells contained <11 SFC and the positive control >19 SFC. To determine the T-Spot result, SFC counts were scored as described below:

T-Spot positive: either ΔSFC (ESAT-6-negative) or ΔSFC (CFP-10-negative) > 7

T-Spot indeterminate: highest of ΔSFC (ESAT-6-negative) or ΔSFC (CFP-10-negative) is 5-7

T-Spot negative: both ΔSFC (ESAT-6-negative) and ΔSFC (CFP-10-negative) < 5

12.7 Protein detection

12.7.1 Processing of cell culture supernatants and bronchoalveolar lavage fluid

To measure soluble mediators in cell culture supernatants and bronchoalveolar lavage fluid (BALF), both were sterile filtered through 0.22μm membranes to remove any Mtb. Up to 600μl liquid was placed into the insert bucket of centrifuge tube filters (Costar) and centrifuged at 5000xg for 5 min at 4°C. To assure complete removal of Mtb, the flowthrough was transferred into a fresh centrifuge filter and filtered a second time. Supernatants were stored at -80°C until use.

12.7.2 Optimisation of SAM strip processing

To recover mucosal lining fluid (MLF) from nasal and bronchial SAM strips, the MLF extraction was optimised before sampling of the human respiratory tract commenced.

IL8 (eBioscience) and IL6 (eBioscience) was added together and used as spiking buffer. 20μl of spiking buffer was added onto Nasosorption SAM strips, which were placed into the insert buckets of centrifuge spin filters. 300μl of Milliplex Assay Buffer (LA-B, Milliplex) was then added to the insert containing the spiked SAM strip and incubated at 4°C for 5 or 10 min. The fluid was then recovered by centrifugation at 5000 or 15000xg for 5 min at 4°C. As a control, 20μl spiking buffer was directly

52 Methods added to 300μl of Milliplex Assay Buffer. The concentration of recovered IL8 and IL6 was then determined by ELISA (see 12.7.4) and compared amongst the several conditions (Figure 12.3 A and B). IL6 was recovered more easily than IL8. IL8 recovery was improved by prolonged incubation of the strip in Assay Buffer. No non-specific binding of IL8 or IL6 to the spin filter membrane was observed, as the cytokines were recovered at the same concentration as the direct spiking of 20μl spiking buffer in 300μl. Based on these findings, a protocol for elution of soluble mediators from SAM strips was used, including an extended incubation period.

12.7.3 Recovery of mucosal lining fluid from SAM-strips

To recover MLF from SAM strips, 300μl Milliplex Assay Buffer (LA-B) was added to the centrifuge filter insert containing the SAM strip. SAMs were incubated in the buffer for 30 min at 4°C. To recover the eluted MLF, the filter tubes were then centrifuged at 5000xg for 5 min at 4°C. To assure complete removal of Mtb, the flowthrough was transferred into a fresh centrifuge filter and filtered a second time (Figure 12.3 C). The eluates of both strips taken per volunteer or patient were pooled together and stored at -80°C until use.

53 Methods

Figure 12.3: Optimisation and final protocol of SAM-strip processing. (A) Optimisation of mediator recovery from SAM strips. Buffer containing IL8 and IL6 was either used neatly or added onto SAM strips and centrifuged using the indicated conditions. (B) Concentrations of recovered IL8 and IL6 were then measured by ELISA. Means ±SD are shown. (C) shows the final protocol to recover MLF from SAM strips. (D) shows IL8 concentrations in paired BLF and BALF, recovered during bronchoscopy from 11 healthy volunteers. Samples were compared by Wilcoxon signed rank test. **, p<0.01.

54 Methods

12.7.4 Enzyme Linked Immunosorbent Assay

Cytokines in cell culture supernatants were measured by Enzyme Linked Immunosorbent Assay (ELISA). ELISA kits were used according to the manufacturer’s instructions with the following changes: All ELISAs, which did not include pre-coated plates, were used with MICROLON 600 half- area 96-well microplates (Greiner) and half volumes of all reagents. For IL6 and IL8 ELISAs, samples and standards were incubated on the ELISA plate overnight at 4°C. ELISA plates were washed with 0.05% PBS/Tween20 3-6 times between incubation steps. After the addition of HRP-substrates, reactions were stopped by adding 1M H3PO4 or 2N H2SO4 where appropriate. Absorbance was then measured within 30 min at 450nm with an ELx800 Absorbance Reader (BioTek, Winooski, USA) with Gen5 Data Analysis Software. Standard curves were calculated using a best-fit-curve in Microsoft Excel and used to determine sample concentrations. The standard ranges are given in (Table 12.2). Any wells below the lowest detectable standard concentration were considered to have a concentration of 0pg/ml.

Table 12.2: ELISA kits and detection ranges.

Target ELISA kit Standard range

IL6 Human IL-6 ELISA Ready-SET-Go!® (eBioscience,) 3.1-200 pg/ml

IL8 Human IL-8 ELISA Ready-SET-Go! ® (2nd Generation) (eBioscience) 3.9-250 pg/ml

IL1β Human IL1β DuoSet (R&D Systems) 3.9-250 pg/ml

MCP-1 ELISA - Human MCP-1 Mini ELISA Development Kit (PeproTech, CCL2/MCP1 31.3-1000 pg/ml London, UK)

CXCL10 Human CXCL10 DuoSet (R&D Systems) 31.3-2000 pg/ml

VeriKine Human IFN Beta ELISA kit (pbl interferon source, Piscataway, IFNβ 25-2000 pg/ml USA)

TNF Human TNFα DuoSet (R&D Systems) 15.6-1000 ml

12.7.5 Lactate dehydrogenase release from PBECs

Lactate dehydrogenase (LDH) was measured in cell culture supernatants of Mtb-stimulated PBECs to determine cell death with the Cytotoxicity Detection Kit (Roche). Cell culture supernatants were harvested as described above (see 12.7.1). If time courses were performed, supernatants from all stimulations were kept at 4°C in sealed 96-well-plates until the experiment was completed, so that all samples in one experiment could be measured together. LDH release of PBECs upon stimulation

55 Methods with Mtb was expressed as relative release of LDH compared to unstimulated PBECs in BEBM medium (minimum LDH release) and PBECs lysed with 1% TritonX-100 (maximum LDH release) for 5 min.

The lyophilised catalyst (diaphorase/NAD+) was reconstituted with dH2O. Immediately before use, the reaction mixture was prepared by dilution of the catalyst at 1:46 in iodotetrazolium (INT). 75μl of reaction mixture were added to 75μl cell-free cell culture supernatant and incubated in the dark at room temperature for up to 10 min. The absorption of the supernatants was then measured at

OD490nm.with the iMark™ Microplate Absorbance Reader. The relative LDH release was then calculated as described below:

(푂퐷푠푎푚푝푙푒 − 푂퐷푚𝑖푛) % 퐿퐷퐻 푟푒푙푒푎푠푒 = ⁄ ∗ 100 [ (푂퐷푚푎푥 − 푂퐷푚𝑖푛)]

12.7.6 Meso Scale Discovery immunoassays

Meso Scale discovery (MSD) immuoassays (Meso Scale Diagnostics, Rockville, USA) are highly sensitive assays to detect low-concentration analytes. The following assays were used according to the manufacturer’s instructions: Human MMP 3-Plex Ultra-Sensitive Kit, V-PLEX Human Vascular Injury Panel 2 Kit and V-PLEX Human Cytokine Kit (Proinflammatory, Cytokine and Chemokine Panel). Plates were read using the MESO QuickPlex SQ 120 imager (Meso Scale Diagnostics). For each experiment, all samples were randomised and measured on the same plate in singlicate. Analyte concentrations were calculated using Discovery Workbench 4.0.12 (Meso Scale Diagnostics). To display the data and its spread, the results were log2-transformed for some graphs. To allow transformation, samples which were dermined as 0 pg/ml, 0.001 was added. The standard detection ranges are shown below:

56 Methods

Table 12.3: MSD assay detection ranges. NLF cohort Exposure cohort Assay Detection range [pg/ml] Detection range [pg/ml] CCL11 4.48 - 1510 3.04 - 1470 CCL13 2.91 - 645 n/a CCL17 0.32 - 1470 0.09 - 1430 CCL2 0.10 - 488 0.05 - 494 CCL22 8.52 - 10100 n/a CCL26 3.89 - 5020 n/a CCL3 3.27 - 1040 n/a CCL4 2.27 - 1050 0.52 - 1080 CRP 1.67 - 182500 3.20 - 195000 CXCL10 0.15 - 2650 0.12 - 2650 GM-CSF 0.13 - 963 n/a IFNγ 0.37 - 1360 0.31 - 1270 IL10 0.03 - 330 0.02 - 307 IL12p40 0.47 - 2840 0.22 - 3070 IL12p70 0.10 - 411 n/a IL13 1.89 - 509 0.79 - 512 IL15 0.20 - 654 0.08 - 683 IL16 11.37 - 2320 1.49 - 2810 IL17 0.69 - 5500 n/a IL1α 0.20 - 350 0.53 - 358 IL1β 0.06 - 620 0.02 - 488 IL2 0.10 - 1320 0.08 - 1220 IL4 0.03 - 208 n/a IL5 0.17 - 892 n/a IL6 0.32 - 789 0.08 - 621 IL7 0.28 - 650 0.06 - 628 IL8 71.43 - 93700 102.01 - 75200 IL8 0.10 - 519 0.05 - 504 MMP1 4.91 - 100000 5.07 - 100000 MMP3 2.50 - 100000 9.42 - 100000 MMP9 59.05 - 500000 97.57 - 500000 SAA 21.74 - 207500 13.32 - 218000 sICAM-1 1.96 - 45950 1.55 - 61400 sVCAM-1 18.23 - 49150 11.15 - 51700 TNFα 0.13 - 315 0.05 - 313 TNFβ 0.05 - 580 0.04 - 581 VEGF 1.70 - 941 0.75 - 993 n/a, not applicable.

57 Methods

12.7.7 Luminex assays

Cell culture supernatants were used to measure soluble mediators by bead-based Luminex assays using the xMAP platform (Thermo). Assays for CCL2, CCL20, CCL4, CCL5, CCL8, CXCL10, CXCL12, G- CSF, GM-CSF, IFNβ, IL1α, IL1β, IL6, IL8, SLP1, TNF and Trappin-2 were performed by Dr. Julia Makinde. The assays were read with Bio-Plex (BioRad).

12.7.8 Western Blotting

For protein lysates PBECs were treated with RIPA buffer (ThermoFisher) supplemented with 2x Halt Protease and Phosphatase Inhibitor Cocktail (ThermoFisher) and 250 U Benzonase (Sigma) for 15 min on ice. The lysates were vigorously resuspended every 5 min during this incubation. Lysates were centrifuged at 25000xg for 15 min at 4°C. Total protein concentration was measured by bicinchoninic acid assay (BCA) protein assay (ThermoFisher). 12g of protein lysates were mixed with Laemmli buffer (BioRad) and 25mM dithiothreitol (DTT) and boiled for 7 min. Proteins separated on 4%-20% Mini PROTEAN gels (BioRad) for 30 min at 200 V and transferred onto nitrocellulose membranes by iBlot (Invitrogen) using programme 0 for 8 min. After the transfer, the membrane was washed in TBST, blocked in 5% milk/TBST for 1h and probed with primary antibodies at 1:1000 in 5% BSA/TBST over night at 4°C. The membrane was then washed three times with TBST and HRP-tagged secondary detection antibody (1:2000) in 5% BSA/TBST was added for 1h at room temperature. Membranes were developed with Enhanced chemiluminescence (ECL) Western blotting substrate (ThermoFisher) and imaged with FUSION FX7 SPECTRA (Vilber, Eberhardzell, Germany). After developing, the membrane was thoroughly washed with TBST and probed with anti- β-actin as a loading control. Membranes were incubated with anti-β-actin (1:1000 in 5% BSA/TBST) for 1h at room temperature, washed and subsequently probed with 1:2000 HRP-tagged secondary detection antibody. Target protein levels were quantified using Fusion Software (Vilber) and signal intensity was normalised to the respective as β-actin signal.

12.7.9 PBL phenotyping by fluorescence-activated cell sorting

To identify the proportions of cell subsets in PBLs, cells were stained with surface markers of monocytes (CD14 (243)), lymphocytes (CD3 (244)) and neutrophils (CD15/CD66b (245, 246)) and quantified by fluorescence-activated cell sorting (FACS). Cells were prepared for FACS in V-bottom 96-well plates. PBLs were washed in FACS buffer by centrifugation at 900xg for 5 min at 4°C. After centrifugation, supernatants were discarded by quickly flicking the plate. Before staining, PBLs were treated with 10% human serum in FACS buffer for 20 min to block non-specific binding of antibodies

58 Methods to Fc receptors. Cells were washed once in FACS buffer and resuspended in 30μl antibody mix (1:100 CD14, 1:100 CD15, 1:20 CD3 and 1:20 CD66b in FACS buffer) and incubated for 20 min at 4°C in the dark. As unstained control, some cells were resuspended in FACS buffer instead of antibody mix. After incubation, cells were washed thoroughly with FACS buffer three times and resuspended in Cytofix Fixation buffer (BD) for 20 min. Cells were centrifuged, residual Cytofix removed and resuspended in FACS buffer. Stained cells were kept at 4°C overnight before flowcytometric acquisition using a BD LSR Fortessa. Compensation was performed using CompBeads α-mouse Ig, κ/negative control compensation beads (BD) were used to determine compensation parameters. Flowcytometry data was analysed with FlowJo v10 (FlowJo Data analysis software, Ashland, USA).

12.8 Microscopy

12.8.1 Kinyoun stain for mycobacteria

PBECs were infected with Mtb in Lab-Tek Permanox chamberslides (ThermoFisher). When desired, free Mtb was thoroughly washed off with warm BEBM. The washing step was repeated twice and all residual liquid removed afterwards. Chamberslides were then placed in a sealable plastic containers with tissues soaked in 37 % formaldehyde (Sigma) for 1h to allow fixation of PBECs and killing of Mtb. The chamberslide was then left to air-dry overnight to evaporate residual formaldehyde. The Tb-color kit (Merck) was used for Kinyoun staining (a modified Ziehl-Neelsen stain) of Mtb at room temperature. First, cells were covered in carbol-fuchsin. After 10 min, it was poured off and the cells briefly immersed in acid-EtHO, which was poured off after 5 s. After a thorough washing step with dH2O, the slides were covered for 2 min with malachite green (oxalate) solution. After removal of the solution, the slides were thoroughly washed with dH2O and left to air dry overnight. Images were acquired with an Axio Scope.A1 microscope (Zeiss).

12.8.2 Cytokeratin-19 staining of PBECs

For this, PBECs were seeded in chamberslides (Lab-Tek Permanox, ThermoFisher). When cells were confluent, monolayers were washed with PBS and fixed with 4 % paraformaldehyde for 7 min at room temperature. Cells were washed again with PBS and permealised with 0.2 % Triton-X 100/PBS for 5 min at room temperature. After a further PBS washing step, PBS with 1% BSA and 10% FBS was added as a blocking reagent over night at 4°C. The next day, 1:50 monoclonal mouse-α-human cytokeratin-19 (clone RCK108, Dako, Cambridgeshire, UK) was added as primary antibody for 2h at room temperature. Unbound antibody was washed off by 3 sequential washes with PBS. For

59 Methods detection, fluorochrome-tagged secondary antibody (rabbit-α-mouse Alexa-Fluor 546) was added 1:200 for 1.5h at room temperature. As a control for non-specific binding, some cells were treated with only the secondary antibody at 1:50. The cells were then washed 3 times with PBS and thoroughly washed with dH2O afterwards to remove any residual PBS. After a brief drying period, the slide was mounted with Mowiol (Sigma). Images of cells were acquired with a CCD camera microscope (Zeiss, Rugby, UK).

12.9 Gene expression analysis

12.9.1 RNA extraction

For cell lysis and subsequent RNA extraction, Trizol (ThermoFisher) was used since it effectively kills Mtb and thus decontaminates infected samples. Samples were stored in Trizol at -80°C until RNA extraction. Total RNA was extracted with the column-based Trizol Plus RNA Purification Kits (ThermoFisher). Trizol lysates were thawed and once at room temperature, 0.2ml chloroform (Sigma) per 1ml of Trizol added. Samples were mixed well by vigorous manual shaking for 15s and then centrifuged for phase separation at 14000xg at 4°C for 15 min. The aqueous phase (upper layer) was then carefully collected and an equal volume of 70% Ethanol added. The RNA was then purified with PureLink® RNA columns (ThermoFisher) according to the manufacutrer’s instructions. To recover RNA in the final elution step, 30μl RNAse free water was added to the column membrane and incubated for 1 min at room temperature. The water, containing the total RNA, was then collected through centrifugation at 14000xg for 3 min at 10°C. This elution step was repeated with the flowthorugh to elute any residual RNA. To remove contaminating genomic DNA, all RNA samples were treated with 1U DNAse I (ThermoFisher) for 30 min at 36°C. To stop the reaction, 5μl 50mM EDTA was added to the sample and heated to 65°C for 10 min. For each experiment, all stimulations were extracted as a batch to prevent the introduction of technical bias. RNA quality was assessed via nanodrop. For microarray and RNA sequencing, RNA quality was assessed with Bioanalyzer and quantified with Qubit.

12.9.2 NanoDrop quantification and quality assessment of total RNA

RNA was quantified with NanoDrop 8000 (ThermoFisher). Before each use, the nanodrop pedestals were carefully cleaned with RNAse free water to remove contaminants. The nanodrop was then blanked against water. 2μl of sample were added and the absorbance measured at 260 and 280nm. The sample quality was determined through the absorbance ratio 260/280.

60 Methods

12.9.3 Qubit fluorometric quantitation of total RNA

For microarrays and RNA Sequencing, the sample concentration was measured with Qubit RNA HS Assays (ThermoFisher). 1μl total RNA was added to 199μl Qubit Working Solution into the appropriate assay tubes, vortexed and incubated for 2 min at room temperature. Sample absorbance was then measured and the concentration determined with the Qubit 2.0 Fluorometer (ThermoFisher).

12.9.4 Quality assessment of total RNA by Bioanalyzer

The RNA quality was assessed through the RNA integrity number (RIN) measured by 2100 Bioanalyzer (Agilent, Stockport, UK). Dependent on the RNA yield of the respective samples, Agilent RNA 6000 Nano or Pico kits (Agilent) were used as per the manufacuter’s instructions. 1μl of total RNA was used per sample. Chips were analysed with the 2100 Expert Agilent Software and RINs determined. Before and after each chip, the Bioanalyzer electrodes were washed sequentially with

RNAZap and dH2O for 2 min each.

12.9.5 Reverse transcription of RNA to complementary DNA

For each experiment, 200-800ng of total RNA were reverse transcribed into complementary DNA (cDNA). Per reaction, 400U Maxima reverse transcriptase (RT) (ThermoFisher), 0.2μg random hexamers (ThermoFisher), 2μl 10mM dNTP Mix, 40U RiboLock RNase Inhibitor (ThermoFisher) and

1x RT buffer (50mM Tris-HCl, 75mM KCl, 3mM MgCl2, 10mM DTT) was used in a total reaction volume of 40μl. For each run of cDNA amplification, a no-template H2O-control was used, in which RNase-free water was added instead of RNA, to exclude non-specific amplification. If enough RNA was available, one sample was selected as a minus-RT control, in which the reaction was prepared without Maxima RT. This control was included to determine whether there was contamination genomic DNA present. The reactions were performed in RNase and DNase-free 0.2ml PCR tubes with a thermal cycler (TC-512, Techne, Bibby Scientific, Staffordshire, UK) using the following settings:

10 min, 25°C – 30 min, 50°C – 5 min, 85°C – hold, 4°C

After reverse transcription, cDNA samples were were diluted to 2.5ng/μl in nuclease-free water and stored at -20°C.

61 Methods

12.9.6 Real-time polymerase chain reaction

Expression of selected genes was measured by real-time polymerase chain reaction (RT-PCR). For reverse transcription, Solaris RT-PCR (GE Healthcare) or TaqMan (ThermoFisher) products were used. 12.5ng of cDNA were used in each reaction, and samples were run in duplicates. For Solaris products, reactions were performed in a total volume of 25μl. 12.5μl 2x Solaris Master Mix with LOW ROX and 1.25μl of 20x Solaris Human qPCR Gene Expression Assays were used. When TaqMan products were used, reactions were performed in a total volume of 20μl. 10μl 2x TaqMan Universal Master Mix II with 2.5μl 20x TaqMan Expression Assays were used. Reactions were performed in 0.1ml MicroAmp Fast 96-Well Reaction Plates (ThermoFisher), which were sealed with MicroAmp Optical Adhesive Film and ran on 7500 Fast Real-Time PCR instruments (ThermoFisher) using the following programmes:

Solaris: 1 cycle (95°C, 15 min) – 40 cycles (95°C, 15 s – 60°C, 1 min)

TaqMan: 1 cycle (50°C, 2 min) – 1 cycle (95°C, 10 min) – 40 cycles (95°C, 15 s – 60°C, 1 min))

Ct (threshold cycles) were exported using 7500 Software (v2.0.6) and analysed using qbase+ version 3.0 (Biogazelle, Gent, Belgien) (247). Target gene expression was normalised to the geometric mean of stably expressed reference genes (248). For PBECs, ACTB (β-actin) and PGK1 (phosphoglycerate kinase 1) were selected as reference genes, also known as housekeeping genes, and gene expression in myeloid cells was normalised to GAPDH (glyceraldehyde-3-phosphate dehydrogenase) and HPRT1 (Hypoxanthine Phosphoribosyltransferase 1).

12.9.7 Whole transcriptome analysis by microarray

50-100ng total RNA with RIN > 9.5 were used for GeneChip Human Transcriptome Array 2.0 (Affymetrix, High Wycombe, UK) and labelled with GeneChip WT PLUS Reagent Kit (Affymetrix) according to the manufacturer’s instructions (User Manual GeneChip® WT PLUS Reagent Kit, P/N 703174 Rev. 2). In brief: 3μl of total RNA were spiked with 2μl PolyA controls and first and second strand cDNA was synthesised. cDNA was then transcribed into complementary RNA (cRNA) overnight and purified after the reaction was finished. Purification step was performed on a Magnetic Stand 96 (ThermoFisher). 1.5μl of purified cRNA was measured by Nanodrop (ThermoFisher) and the yield determined. 15μg cRNA were again transcribed into ss cDNA and residual cRNA digested with RNAse H. cDNA was stored overnight at -20C. The protocol was continued by purifying ss cDNA and quanitified by Nanodrop and the size distribution of cDNA molecules was measured by Bioanalyzer RNA 6000 Nano kit (Agilent). 5.5μg cDNA were taken

62 Methods forward for fragementation and labelling. Fragementation was confirmed by Bioanalyzer. The labelled samples were then stored at -20°C before hybridisation. Samples were transferred to the MRC Genomics Laboratory (Hammersmith Campus, Imperial College London) and processed by Ivan Andrews. Samples were hybridised to GeneChip Human Transcriptome Array (HTA) 2.0 (Affymetrix) chips with the GeneChip Hybridisation oven (Affymetrix). Arrays were then washed and stained using the GeneChip Fluidics Stations F450 (Affymetrix) and scanned with a GeneChip Scanner 3000 7G (Affymetrix). The intensity files were processed and analysed with Partek Genomics Suite (PGS) 6.6 (Partek Incorporated, St. Louis, USA). Successful hybridisation and probeset distribution of HTA 2.0 arrays was confirmed before normalisation with Robust Multi-array Average (RMA). Statistical analysis of gene expression was performed on all 26831 probesets annotated by the NCBI Reference Sequence Database (RefSeq) with PGS for Analysis of variance (ANOVA) or MultiExperiment Viewer version (MeV) 4.9.0 (Saeed et al., 2003) for Significance Analysis of Microarrays (SAM).

12.9.8 Optimisation of sample pre-processing for RNA Sequencing

To allow recovery of RNA with best possible quality, pre-RNA extraction sample processing of ex vivo bronchial samples was optimised. Two approaches of pre-processing were compared. The first approach (Method 1: Processed) included the collection of bronchial samples in warm or cold BEGM and their resuspension of the cells in Trizol in the lab, the second method (Method 2: Direct) limited the handling of the samples drastically by directly shearing brochial cells off the brushes into Trizol.

Method 1 (Processed): Bronchial cells recovered through brushings were sheared into 10ml warm or cold BEGM through the barrel of a 50ml syringe  processing of samples as in 12.3.1  after counting, cells were centrifuged again and resuspended in 750μl Trizol  stored at -80°C. Method 2 (Direct): Bronchial cells recovered through brushings were sheared into cold Trizol through a modified 1000μl pipette tip and frozen at -80°C within 30 min.

Samples collected according to the described methods were extracted and the RNA quality assessed by RIN-determination (Figure 12.4). Processing of the samples, regardless of the sample temperature, yielded poor quality RNA, while direct lysis of bronchial cells in Trizol resulted in a significant increase of RIN. Thus, the direct method was applied to all samples which were taken forward for RNA Sequencing.

63 Methods

Figure 12.4: Optimisation of pre-processing of ex vivo bronchial samples for RNA Sequencing. Cells recovered from bronchial brushings were processed according to Method 1 (Processed, cold BEGM (grey circles), warm BEGM (open circles)) or Method 2 (Direct). Groups were compared by Mann-Whitney test. *, p<0.5. Representative RINs for Processed (B) and Direct (C) samples are shown.

12.9.9 Whole transcriptome analysis by RNA Sequencing

For RNA extraction from brushes for RNA Sequencing (RNASeq), samples were randomised into blocks of five, which were later combined into pools for sequencing (Figure 12.5 A). Blocks were extracted in pairs and samples yielded a median RIN of 6.45 with a range of 4-8.8. 130-350ng total RNA was used for RNASeq library preparations. Libraries were prepared with TruSeq Stranded Total RNA kit (Illumina, Chesterford, UK) according to the TruSeq Stranded Total RNA Sample Preparation Guide following the Low Sample (LS) Protocol (Ref: RS-122-9007DOC Part # 15031048 Rev. E Oct 2013). In brief: Total RNA was depleted of ribosomal RNA with RiboZero beads and fragmented for library preparation. RNA was then reverse transcribed into first strand cDNA with SuperScript II reverse transcriptase (ThermoFisher) and second strand cDNA was synthesised subsequently. After the completion of the cDNA synthesis, samples were frozen down at -20°C overnight and library preparation was continued the next day. After thawing of the samples, the 3’ ends of the cDNA were ligated with adapters 2, 4, 7, 13 or 16 as detailed in (Figure 12.5 A) and subsequently amplified by PCR. As part of the protocol, when appropriate, DNA and RNA was purified using Agencourt AMPure XP (Beckman Coulter, High Wycombe, UK) or Agencourt RNAClean XP (Beckman Coulter) magnetic beads, respectively, with a magnetic stand. To validate the fragmentation and

64 Methods adapter ligation, RNA Seq libraries were run on Agilent Bioanalyzer DNA 1000 chips, yielding fragments sized 254-272 bp. The overlay of all library traces is shown in (Figure 12.5 B). For library quantification, the fragment size (in base pairs (bp)) was determined through the Bioanalyzer size distribution. The dsDNA concentration was measured with the Quant-iT TM dsDNA assay kit (Life Technologies). 1μl of RNASeq libraries was use in duplicate for quantification.

The molarity of the libraries was calculated through the following formula:

23 푑푠퐷푁퐴 푚표푙푒푐푢푙푒푠 = 푐 ∗ 6.0233 ∗ 10 ⁄ ⁄휇푙 656.6 ∗ 109 ∗ 푙

푑푠퐷푁퐴 푚표푙푒푐푢푙푒푠 6 [( ⁄휇푙) ∗ 10 ] Molarity [M] = ⁄ 6.0233 ∗ 1023 c = concentration in ng/μl f = fragment length in bp

Libraries were diluted in Illumina Resuspension Buffer for a calculated final concentration of 30nM. 10μl of each library within a block was then added together to obtain the library pools for sequencing (Figure 12.5 C). The exact molarity was calculated via Bioanalyzer and Quant-IT and ranged from 25.87 to 28.45nM final concentration. Pools were shipped to Centro Nacional de Análisis Genómico (CNAG, Barcelona, Spain) for sequencing with the HiSeq 2000 System (Illumina) yielding 75 bp paired-end reads.

Quality control for RNASeq data was performed using FastQC v0.11.4 (Babraham Institute, Babraham, UK). All files passed quality control and were taken forward for analysis. Sequence reads were aligned by Dr. Paul Golby. In brief: The stranded paired-end reads were aligned against the human reference genome hg38 with the TopHat software package v 2.1.0 using the library parameter ‘fr-firststrand’. Aligned reads that overlapped with NCBI Reference Sequence Database (RefSeq) annotated genes (249) were counted through the summarizeOverlaps function of the Genomic Alignments software package v 3.2 using the counting mode parameter set to ‘union’ (https://bioconductor.org/packages/release/bioc/html/GenomicAlignments.html). Gene counts for all samples were collated into a single file. Counts were normalised and differential expression determined through the DESeq2 v 3.2 software package (https://bioconductor.org/packages/release/bioc/html/DESeq2.html) in Bioconductor. Genes were defined as significantly differentially expressed at a Benjamini Hochberg adjusted p-value < 0.05. Genes were annotated using Entrez Gene IDs (250). Two samples were removed from the final

65 Methods analysis: The sample from TB unexposed healthy subject #11 was removed as the subject reported to have mild asthma and TB exposed healthy subject #2 was removed as the subject reported coughing and fever.

Figure 12.5: Library preparation for RNA Sequencing. (A) Samples for RNASeq were randomly assigned into 6 blocks and assigned adapter 2, 4, 7, 13 or 16. 30 samples were prepared, of which 13 were from TB unexposed healthy volunteers (green), 10 TB exposed healthy volunteers (yellow) and 7 lung disease patients (red). After completion of the library preparation protocol, the sample quality was assessed by Bioanalyser DNA 1000 assay. The overlay of all libraries (B) and of the five pools is shown (C).

12.10 Data analysis

12.10.1 Statistical analysis

Statistical analysis of experimental data (if not indicated differently) was performed and plotted with GraphPad Prism 6 (GraphPad Software, La Jolla, USA). Demographic and MSD data was analysed with SPSS v22 (IBM, Portsmouth, UK).

12.10.2 Biological interpretation of transcriptomic data with InnateDB

Pathway and gene ontology enrichment analysis was performed with the online database InnateDB (251). NCBI Reference Sequence Database (RefSeq) (249) or Entrez Gene (250) identifiers were used

66 Methods and over-represenation analysis (ORA) performed by hypergeometric distribution test. Benjamini Hochberg correction was used to adjust p-values for multiple testing. Significant output of pathway and gene ontology ORA was reported when > 9 identified genes were associated with the Reactome (252) or gene ontology term (253, 254), respectively.

12.10.3 Transcription factor binding site analysis with oPOSSUM

Over representation of single transcription factor binding site (TFBS) was determined with oPOSSUM 3.0 (255). For the gene set analysis, the default settings were applied with a 0.4 cutoff and an 85% matrix score threshold. The search region was limited to 2,000/2,000 bp upstream/downstream of the target genes. Hits were selected as significant at a z-score of 10 with > 5 target gene hits.

67 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis 13 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis

13.1 Introduction

The first interactions between M. tuberculosis (Mtb) and its human host occur in the lungs after inhalation of aerosolised bacteria. It is assumed, that the primary target of Mtb, an intracellular pathogen (256), is the alveolar macrophage in the lower airways (114, 257). However, the majority of the cells in the airway lining are epithelial and make up a surface of approximately 70 m2 (165). A major function of the epithelium is the warming and filtering of inhaled air throughout the airways as well as the gas exchange in the terminal alveoli, however it also contributes to the immune responses in the lungs (164). Given the large interface formed by airway epithelial cells, they are frequently in contact with inhaled pathogens. Epithelial cells can sense intra- and extracellular pathogens, such as viruses and bacteria, via a wide range of pattern recognition receptors (PRR) (180, 258). This allows the release of cytokines and antimicrobial factors which contribute to the inflammatory milieu in the airways. It is, thus, likely that these cells also directly interact with Mtb after its inhalation. In fact, studies on lung tissue from latently infected individuals that died of causes other than tuberculosis (TB), revealed that Mtb DNA is detectable in epithelial cells of histologically healthy lung tissue (31). In the murine model of Mtb infection, mycobacteria were detected in bronchial (229) and alveolar epithelial cells (230). Additionally, mycobacteria express antigens that allow interaction with the epithelial layer. Most notably, mycobacterial DNA-binding protein 1 (MDP-1) (213) and heparin-binding hemagglutinin (HBHA) (214) have been shown to allow adherence of mycobacteria to epithelial glycosaminoglycans. Taken together, these studies support a role for epithelial cells as a target of Mtb infection in vivo.

To dissect responses and mechanisms involved in epithelial infection by Mtb, previously published work focussed on human airway epithelial cell lines. Alveolar as well as bronchial epithelial cell lines are susceptible to intracellular infection (212, 259). The majority of these studies employed alveolar A549 cells, which are derived from lung adenocarcinoma (209). A549 cells have been described to release a multitude of soluble mediators upon mycobacterial challenge. These include cytokines such as interleukin (IL) 8 and even tumor necrosis factor (TNF) (205, 219, 223), as well as antimicrobial peptides (AMP) including cathelicidin and human beta-defensin 2 (hBD2) (224, 260). The induction of these mediators is thought to be facilitated by the ligation of conserved mycobacterial pathogen associated molecular patterns (PAMP) to epithelial receptors. Mycobacteria

68 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis express a large variety of these patterns which can activate PRRs, such as C-type lectin or Toll-like receptors (TLR) (119). While various TLR-family members recognise mycobacterial antigens, TLR2 is a major receptor for lipomannans and lipoproteins found in the mycobacterial cell wall (261, 262). Even though its contribution to the outcome of Mtb infection in mice remains controversial (263, 264), TLR2 has been identified to be important for the initial recognition of the pathogen by macrophages in vitro. Importantly, TLRs, including TLR2, are found to be expressed throughout the airway epithelium (265–267). Similar to immune cells, airway epithelial cells can be activated by mycobacteria via TLR2, leading to the release of pro-inflammatory mediators (218, 222). These in vitro findings were corroborated in a mouse model of pulmonary TB, in which activation of epithelial TLR2 has been suggested to drive chemokine release and influence pathology and survival during Mtb infection (237).

Based on these findings, epithelial infection or recognition of Mtb in the human airways may shape early host responses to the bacilli. However, data on the response of primary human airway epithelial cells to Mtb infection is very limited. Whether primary human epithelial cells are in fact responders to Mtb infection has not been addressed in depth. In the present study, healthy volunteers were recruited to undergo bronchoscopic procedure to recover primary bronchial epithelial cells which were expanded in vitro and exposed to live virulent Mtb.

13.2 Hypothesis

Primary bronchial epithelial cells (PBECs) are a target for mycobacterial infection and respond to the pathogen with release of pro-inflammatory mediators induced via pattern recognition receptors in vitro.

13.3 Aims

Aim 1: To assess whether PBECs can be infected with Mtb.

Aim 2: To assess the whole transcriptomic response and mediator release of PBECs after exposure to Mtb.

Aim 3: To identify Mtb-sensing mechanisms of PBECs.

69 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis 13.4 Results

13.4.1 PBECs do not respond to mycobacterial ligands

In order to assess whether PBECs are responders to mycobacterial PAMPs, it was first investigated whether stimulation with crude mixtures of mycobacterial ligands could elicit cytokine release from these cells. In response to PRR stimulation, including TLR2, epithelial cells release IL8 and IL6 (182, 267, 268). Both cytokines support the immune response through their chemotactic and immune- modulatory properties (269, 270) and are secreted into the lining fluid of the upper and lower airways (see Results Chapter 3). Since TLR2 has been identified to mediate epithelial recognition of Mtb, the mycobacterial TLR2-agonist lipomannan from M. smegmatis (LM-MS) was added to PBECs alongside crude whole cell lysate (WCL) and cell wall fraction (CWF) derived from the virulent Mtb- strain H37Rv. Both preparations contain ligands recognised by TLR2 (271–273). Synthetic agonists for TLR2 (Pam2, Pam3) and TLR3 (Poly:IC) were chosen as positive controls for the activation of TLR signalling. While PBECs released IL8 and IL6 in response to the synthetic TLR agonists in a dose- dependent manner, this was not observed for the mycobacterial ligands (Figure 13.1 A). Surprisingly, even at the highest concentration of 10 µg/ml mycobacterial ligands did not significantly increase the release of IL8 or IL6 by PBECs. In comparison, IL8 and IL6 were significantly increased after stimulation with Pam2, Pam3 and Poly:IC at the same concentration (Figure 13.1 B). Since PBECs might require a longer exposure to mycobacterial agonists to mount a cytokine response similar to that observed in response to synthetic TLR ligands, the stimulation time was extended to 72h. Neither longer incubation, nor the addition of further ligands, such as Mtb H37Rv culture filtrate protein (CFP), cytosolic fraction (CytFr) and WCL of Mtb HN878, did significantly increase the release of IL8 or IL6 compared to the medium control (BEBM) (Figure 13.1 C).

70 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis

Figure 13.1: PBECs do not respond to mycobacterial PAMPs. (A) PBECs were stimulated with TLR agonists (Pam2, Pam3 and Poly:IC), mycobacterial ligands (M smegmatis lipomannan (LM-MS), Mtb H37Rv whole cell lysate (WCL) or cell wall fraction (CWF)) at the indicated concentrations. The release of IL8 (n=9) and IL6 (n=11) was measured in culture supernatants after 24h by ELISA and is expressed as mean±SEM. (B) shows the release of both cytokines after 24h of stimulation at 10 µg/ml with the indicated agonists in comparison to unstimulated medium controls (BEBM). (C) The stimulation of PBECs with 10 µg/ml mycobacterial ligands was extended up to 72h and additionally included WCL of Mtb HN878, culture filtrate protein (CFP) and cytosolic fraction (CytFr) of Mtb H37Rv. Cytokine release was measured at the indicated time points (n=5). No significant differences were detected between stimulus and BEBM at the respective time points. (B) and (C), Friedman test and Dunn’s post-test were used to compare groups with BEBM. Horizontal lines indicate the median. **, p<0.01; ***, p<0.001; ****, p<0.0001.

71 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis 13.4.2 PBECs are much less permissive to Mtb infection than macrophages

While isolated mycobacterial ligands did not elicit a cytokine response from PBECs, this may not mimic the interaction between virulent Mtb and these cells. As an intracellular pathogen, Mtb invades host cells and might thus be internalised by PBECs. Mtb-DNA can be detected in epithelial cells of infected human lung tissue (31) and enter A549 alveolar epithelial cells in vitro (274, 275), it was thus assessed next, whether PBECs were permissive to Mtb H37Rv. Since macrophages are a principal target for intracellular Mtb infection, the Mtb burden of PBECs was compared to that of PMA-differentiated THP-1 macrophages (Figure 13.2 A). After 24h, Mtb could be recovered from PBECs but the bacterial burden was two orders of magnitudes less than observed after infection of macrophages, even though the same concentration of Mtb was used. To identify the proportion of Mtb located intracellular as opposed to adherent to the cell surface, PBECs and macrophages were treated with the antibiotic amikacin to remove extracellular bacteria. The comparison of total cell- associated, i.e. extracellular and intracellular, Mtb with the number of internalised bacteria after amikacin-treatment, revealed that the proportion of internalised Mtb was similar. Macrophages and PBECs internalised 29.5±5.9 % and 27.9±10.9% (mean±SD) of the total associated Mtb burden, respectively, suggesting a lack of mycobacterial adherence to PBECs in comparison to macrophages. Epithelial cells are much larger than macrophages and the actual cell numbers per tissue culture well between these cell types differed by approximately 4-5 fold. However, even if this is taken into consideration, macrophages remain the more permissive target for Mtb infection. The association of Mtb with PBECs was further confirmed by microscopy. Even though PBECs were infected at a multiplicity of infection (MOI) of 50, Mtb was infrequently associated with epithelial cells (Figure 13.2 B).

72 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis

Figure 13.2: Mtb infects PBECs less efficiently than macrophages. (A) PBECs (n=4, median shown) and THP-1 macrophages (THP MΦ, mean±SD of 2 independent experiments in duplicate) were infected with 6.25x105 Mtb H37Rv for 24h. To remove extracellular bacteria, 200 µg/ml amikacin was added for an additional 2h where indicated. Mtb was enumerated via colony forming units (CFU). (B) The association of Mtb with PBECs was confirmed microscopically via Kinyoun stain after 24h of infection at MOI 50. Shown are representative images from 2 donors at a 200x magnification. Arrowheads indicate Mtb.

73 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis 13.4.3 PBECs respond to high Mtb burden

Even though the bacterial burden directly associated with PBECs after infection was low in comparison to macrophages, exposure to live Mtb may be sufficient to trigger an inflammatory response in PBECs. Airway epithelial cells respond to invading pathogens via release of cytokines which contribute to the host response against infection. While mycobacterial ligands did not trigger increased cytokine release from PBECs under the given experimental conditions, live virulent Mtb may have stronger effect on epithelial cells. PBECs were exposed to Mtb H37Rv for up to 72h at a MOI of 10 or 50. Interestingly, significant increases in the release of IL8 and IL6 were only observed at the high MOI. While IL8 was already significantly increased after 24h, IL6 levels were only elevated at the 72h time point (Figure 13.3 A). IL8 release in response to the Mtb outbreak strains CH (241), Gurung 333 (Gurung) or NPH4216 (NPH) (241) at low MOIs was comparable to the levels observed during Mtb H37Rv exposure(Figure 13.3 B). This indicated that a lack of responsiveness was not due to an attenuation of the laboratory strain H37Rv. The previously reported findings that Mtb infection of A549 cells results in the release of CCL2 (219) and TNF (218), could not be confirmed after exposure of PBECs to Mtb H37Rv (data not shown).

The low responsiveness of PBECs to mycobacterial infection within 24h raised the question, whether PBECs were inherently non-responsive to live bacteria in vitro. Activation of primary human airway epithelial cells by other respiratory bacteria has previously been described, but had not been verified in the present study up to this point. To address this, PBECs were exposed to the extracellular pathogen Streptococcus pneumoniae in parallel with Mtb H37Rv. Indeed, S. pneumoniae did have a more pronounced effect on the IL8 release by PBECs than Mtb, confirming that PBECs have the capacity to respond to live bacteria already at 24h (Figure 13.3 C).

74 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis

Figure 13.3: Sustained infection of PBECs with virulent Mtb induces cytokine release. (A) PBECs were exposed to Mtb H37Rv for up to 72h at the indicated MOI. IL8 and IL6 release into culture was measured by ELISA (n=19). (B) Additionally, levels of IL8 were measured up to 72h after PBECs were exposed to Mtb H37Rv (MOI10) or the clinical Mtb strains CH, Gurung 333 (Gurung), NPH4216 (NPH) at an MOI of 3, 3 and 20 respectively. No significant differences were detected in comparison to unstimulated medium controls (BEBM) at the respective time points (n=3). (C) shows the IL8 levels after exposure to S. pneumoniae at the indicated inoculums alongside Mtb H37Rv after 24h (shown are 2 donors with 2 technical replicates). (A) and (B), Friedman test with Dunn’s post- test was used to compare groups with BEBM. Horizontal lines indicate the median. * p<0.05; **, p<0.01; ***, p<0.001.

75 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis 13.4.4 Analysis of Mtb-inducible epithelial genes in PBECs

While IL8 and IL6 are important mediators of the epithelial response to infection and have been shown to be released from Mtb-infected A549 cells (205, 218), they might not be the primary response elicited by Mtb from PBECs at low bacterial burden or during short exposure. Several other factors have been described to be either found during in vitro infection of cell lines or in epithelial cells in histological sections of Mtb infected lung tissue. A549 cells have been shown to express antimicrobials cathelicidin antimicrobial peptide (CAMP) and beta-defensin 2 (DEFB4) during Mtb- infection in vitro and can upregulated the surface expression of TLR2 in response to mycobacteria (222, 224, 260). Furthermore, analysis of lung biopsies from TB patients have identified upregulation of matrix metalloproteinase (MMP) 9 and C-X-C motif chemokine (CXCL) 10 in epithelial cells of lung biopsies from TB patients (105, 202). To identify, whether any of these responses are induced in PBECs during direct exposure to live Mtb, reverse transcription polymerase chain reaction (RT-PCR) was used to measure the expression of the target genes (Figure 13.4). CAMP, DEFB4 and MMP9 were not significantly increased compared to unstimulated cells. A moderate increase in the expression of CXCL10 and TLR2 was observed. This was however only significant for one of the MOI conditions used. Interestingly, the only genes consistently and significantly upregulated were IL6 and IL8. While IL8 and IL6 protein required up to 72h to be significantly increased in cell culture supernatant of Mtb exposed PBECs, expression of the respective genes already occurred within 24h.

Figure 13.4: Gene expression of selected targets in PBECs exposed to Mtb. PBECs were exposed to Mtb H37Rv at the indicated MOI for 24h. Gene expression was measured via RT-PCR (n=7). Results are shown as fold change over unstimulated controls. Wilcoxon signed rank test against a fold change of 1 was used. Horizontal lines indicate the median. Dotted line intersects at fold change=1. ϕ, target not detected in 1 donor. *, p<0.05.

76 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis 13.4.5 Whole transcriptome analysis of the PBEC response to Mtb

The consistently increased expression of IL8 and IL6 indicated that Mtb already induces PBEC responses within 24h and is only manifested on the protein level later. However, mediators which had previously been described to be expressed by epithelial cells in situ or in vitro could not be confirmed in PBECs. Based on this observation, a global gene expression microarray approach was chosen to identify PBEC responses to Mtb. High quality RNA samples extracted from PBECs of four donors, which were infected with Mtb H37Rv (MOI10 and 50) or left unstimulated for 24h, were used for Affymetrix GeneChip Human Transcriptome Array (HTA) 2.0 chips (see Methods section 12.9.7). The array data was normalised by Robust Multi-array Average (RMA). All samples passed quality control (QC) and were used for downstream analysis. To identify differentially expressed (DE) transcripts between conditions, only transcripts that were annotated by the NCBI Reference Sequence Database (RefSeq) were selected. DE genes were identified by one-way analysis of variance (ANOVA). Initially, DE transcripts were defined to have a log2 fold change of > |1.5| fold over unstimulated cells and a multiple testing corrected p-value of < 0.05. However, no transcripts survived statistical adjustment for multiple comparisons. This was likely due to the small sample size, including the inherent inter-individual differences, and the limited expression changes induced by Mtb. As a result, a less stringent cut-off for DE transcripts with an unadjusted p-value < 0.005 and log2 fold change of > |1.5| over unstimulated cells were chosen. Only when PBECs were exposed to Mtb at MOI50, DE genes passed the selection criteria (Figure 13.5 A and B). Three transcripts were differentially expressed: IL8, IL36G and MMP1. The target gene induction by Mtb in PBECs was confirmed by RT-PCR in five independent donors and followed up to 72h (Figure 13.5 C). While IL36G was only increased at 24h, MMP1 an IL8 were found to remain upregulated until 72h.

77 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis

Figure 13.5: Whole transcriptome analysis of the PBEC response to Mtb. Affymetrix HTA2.0 arrays were performed on PBECs (uninfected, MOI10 or MOI50, 24h) from

4 donors and analysed with Partek Genomic Suite. (A) The log2 fold change compared to unstimulated PBECs and the associated unadjusted p-values (One way ANOVA) of all RefSeq annotated transcripts are shown in volcano plots for MOI10 (left) and MOI50 (right). The solid black lines intersect at fold change of ± 1.5 or a p-value of 0.005. DE genes with log2 fold change > |1.5| and p < 0.005 in either condition are highlighted. The details of the highlighted transcripts are displayed (B). (C) The expression of IL8, IL36G and MMP1 was validated by RT-PCR in independent experiments (n=5). Friedman test with Dunn’s post-test was used to compare gene expression to unstimulated cells at the respective time point. Horizontal lines indicate the median. N/C, no change; * p<0.05; **, p<0.01; ***, p<0.001.

78 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis 13.4.6 Mtb-induced IL8 release is independent of TLR2 and Dectin-1 activation

Whole transcriptome analysis of PBECs revealed that overall gene expression changes induced by Mtb were modest. Amongst the identified genes, IL8 had also been found to be increased at the protein level. The strongest induction of IL8 was detected after prolonged exposure to a high burden of Mtb. It has been suggested that mycobacteria are sensed by A549 cells through TLR2 (221, 222, 276) and the C-type lectin receptor Dectin-1 (223). The absence of an early response to Mtb by PBECs observed in this study, even though TLR2 signalling was functional, might be due to insufficient receptor levels or compartmentalisation of the receptors in epithelial cells (277). In fact, mycobacteria have been shown to upregulate TLR2 in A549 cells after 3 days of infection (222). Here, upregulation of TLR2 expression in PBECs was, even though modest, observed in PBECs after 24h at MOI50. This suggests that PRR-sensing of Mtb, while not sufficient early after exposure to Mtb, might facilitate cytokine release by PBECs after prolonged interaction. To see whether TLR2 or Dectin-1 could in fact mediate IL8 release, receptor-activation was inhibited by blocking antibodies. Neither inhibition of TLR2 (Figure 13.6 A) nor Dectin-1 (Figure 13.6 B) impaired Mtb-induced IL8 release after 72h.

Figure 13.6: Mtb-induced IL8 release is independent of TLR2 or Dectin-1 activation. PBECs were exposed to Mtb H37Rv (MOI50) in the presence of 20μg/ml αTLR2 (A, n=7) or αDectin-1 (B, n=4) antibody or the corresponding isotype control. IL8 release into cell culture was measured after 72h. IL8 levels were compared between blocking antibody and isotype control for each stimulation by Friedman test with Dunn’s post-test. Horizontal lines indicate the median. BEBM indicates the uninfected medium control. n.s., not significant.

79 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis 13.4.7 Mycobacterial virulence drives epithelial IL8 release and cytotoxicity

Since the inhibition of TLR2 and Dectin-1 signalling did not affect IL8 release, the activation of PBECs by Mtb likely occurred through mechanisms independent of PRRs which had previously been associated with mycobacterial sensing in epithelial cell lines. While there are mycobacterial PAMPs which are conserved and found commonly across several mycobacterial species, M. tuberculosis contains specific virulence factors that can drive inflammation and are absent in non-pathogenic stains (278, 279). To determine whether virulence may contribute to the interaction between PBECs and Mtb, IL8 release in response to the attenuated non-pathogenic mycobacterial strain BCG was measured. Unlike Mtb H37Rv, BCG did not induce significant release of IL8 by PBECs after 72h, even though MOI100 was used (Figure 13.7 A). A major difference between BCG and Mtb is the loss of the genomic region of difference 1 (RD1) (279, 280). RD1 encodes secreted virulence factors such as the 6-kDa early secreted antigenic target (ESAT-6) (281, 282). While ESAT-6 is an important diagnostic target due to its immune-dominance (283), it also has various other functions. It has been described to induce cytokine secretion in adenocarcinoma-derived NCI-H441 epithelial-like cells (284) and macrophages (285). Based on these findings, recombinant ESAT-6 was used to stimulate PBECs to assess its effect on epithelial cytokine release. ESAT-6 directly induced significant levels of IL8 already after 6h, with an even more pronounced effect after 24h (Figure 13.7 B). Interestingly, after 24h, ESAT-6 mediated significant release of LDH from PBECs, which is an indirect measurement for cytotoxicity and can reflect cell death through necrosis (286–288) (Figure 13.7 C). Mycobacterial virulence is associated with cytotoxicity in A549 cells (228, 289), and these data suggest that ESAT-6 might partially mediate similar effects in PBECs. To assess, whether cell death was observed after infection with live Mtb, LDH release by PBECs was measured after up to 72h of exposure (Figure 13.7 D). LDH release was highest when PBECs were exposed to Mtb for 72h at MOI50, which was the same condition that resulted in the highest IL8 release. In fact, the relative release of LDH after Mtb- exposure over unstimulated levels correlated significantly with the relative IL8 release (Figure 13.7 E). This suggested an association between Mtb-induced cytotoxicity and cytokine release. Increased LDH release from PBECs was also observed in the presence of clinical Mtb strains (Figure 13.7 F) but not in the presence of BCG (Figure 13.7 G).

80 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis

Figure 13.7: Mycobacterial virulence induces IL8 and cytotoxicity in PBECs. (see next page)

81 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis

Figure caption for Figure 13.7: (A) PBECs were infected with Mtb H37Rv and M. bovis BCG for 72h at the indicated MOI. The release of IL8 was measured by ELISA (A, n=4). (B) IL8 release was also measured after PBECs were stimulated with live Mtb H37Rv (MOI10) or increasing concentrations of recombinant ESAT-6 (rESAT-6) for 6h (left, n=3) or 24h (right, n=5). (C) rESAT-6 induced cytotoxicity was measured via calculation of the proportional LDH release in cell-free culture supernatant (n=5). (D) displays the LDH release induced by Mtb H37Rv infection at the indicated time and MOI (n=19). (E) LDH and IL8 release in response to Mtb H37Rv (MOI50) at 72h were correlated by calculating the relative mediator release as the ratio of stimulated/unstimulated measurements (n=15). (F) LDH levels after infection with Mtb H37Rv (MOI10) or the clinical Mtb strains CH, Gurung 333 (Gurung) and NPH4216 (NPH), MOI of 3, 3 and 20 respectively, was measured at 24h and 72h (n=3). (G) LDH release after BCG infection alongside Mtb H37Rv at 72h is shown at the indicated MOIs (n=4) For all graphs, LDH release is shown as % compared to the maximum LDH release (calculated as in the Methods section 12.7.5). For (A), (B), (D), (F) and (G), groups were compared via Friedman test with Dunn’s post-test (compared to unstimulated medium (BEBM) control). (C) Conditions were compared via one-tailed Wilcoxon signed rank test. (D) Spearman correlation was used to determine significance p and correlation coefficient r. Horizontal lines indicate the median. * p<0.05; **, p<0.01; ***, p<0.001; ****, p<0.0001.

82 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis 13.4.8 Mtb-induced cytotoxicity and IL8 release are NADPH oxidase- dependent

Exposure of PBECs to virulent Mtb and the secreted mycobacterial virulence factor ESAT-6 resulted in increased cell death in PBECs. ESAT-6 induced IL8 release from epithelial-like cells has been described to be mediated via induction of reactive oxygen species (ROS) (284). While it is known that reactive oxygen species (ROS) are required for cellular homeostasis, intracellular ROS accumulation can lead to cell death (290). Since cytotoxicity correlated well with IL8 release by PBECs in response to Mtb, it was tested next, whether inhibition of ROS production would affect both, LDH and IL8 release. To prevent ROS formation, the NADPH-oxidase inhibitor diphenyleneiodonium (DPI) and mitochondrial complex I inhibitor Rotenone were used. While Rotenone did not have an effect on Mtb-driven LDH or IL8 release, DPI significantly reduced cytotoxicity (Figure 13.8 A) and IL8 release (Figure 13.8 B).

Figure 13.8: Diphenyleneiodonium (DPI) inhibits LDH and IL8 release during Mtb exposure of PBECs. PBECs were exposed to Mtb H37Rv (MOI50) for 72h. NADPH-oxidase inhibitor diphenyleneiodonium (DPI) or mitochondrial complex I inhibitor Rotenone (Rot) were added at 10 µM. Medium (BEBM) or DMSO (vehicle) were used as controls. (A) LDH release was measured in cell-free culture supernatant and is shown as % compared to the maximum LDH release (n=4). (B) IL8 was measured by ELISA (n=4). Friedman test and Dunn’s post-test were used to compare groups as indicated. Horizontal lines indicate the median. n.s., not significant; *, p<0.05.

83 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis 13.5 Discussion

The airway epithelium has been proposed to serve as an infection-niche for Mtb to evade internalisation by macrophages (212). This posed the question whether primary airway epithelial cells could provide such a niche after inhalation of Mtb to allow establishment of infection. To address this, human PBECs were expanded in vitro to mimic the responses in the human lungs, as opposed to using respiratory epithelial cell lines or mouse models. While PBECs did internalise Mtb, the overall association of the pathogen with epithelial cells was poor in comparison to macrophages. These findings are consistent with a study of Harriff et al, in which primary human tracheal cells showed 5-fold less mycobacterial burden compared to monocyte-derived dendritic cells (DCs) (231). In fact, in lung sections of Mtb infected mice, only 10% of the observed mycobacteria were within epithelial cells while the majority of the bacterial burden was associated with macrophages two days post infection (230). Epithelial Mtb-uptake has been suggested to be mediated by macropinocytosis (211) and receptor-dependent mechanisms (212). It is known that epithelial cells possess a lesser capacity for endocytosis compared to professional phagocytes (211, 291), which might explain the limited intracellular bacterial burden observed. As only few bacilli are needed to establish pulmonary infection with Mtb (161) it is more likely that macrophages rather than epithelial cells are the first cells to be infected after inhalation of Mtb. These data are consistent with the idea that epithelial cells are a target for the pathogen during established or productive infection, when the bacterial burden is increased. Interaction of mycobacteria with the epithelium may then aid the development of latency or dissemination into other tissues, as previously described in animal models (214).

Even though internalisation of Mtb was limited, exposure to the bacteria was sufficient to increase epithelial cytokine release. Expression and release of IL8 and IL6 by PBECs were observed, while the previously reported upregulation of CCL2 and TNF by A549 cells (218) or induction of AMPs (224, 260) could not be confirmed in primary cell cultures. To identify novel pathways induced during epithelial Mtb-infection, the global transcriptomic response of PBECs to Mtb-exposure was measured for the first time. The analysis revealed that gene expression in response to neither low (MOI10) nor high (MOI50) Mtb burden was induced strongly enough to survive stringent statistical analysis. This was in part due to the small samples size and the small overall changes in expression. When less stringent criteria were applied and unadjusted p-values used for selection, IL8, IL36G and MMP1 were identified as targets of PBEC exposure to Mtb. IL8 and MMP1 showed increased induction over time, suggesting that the epithelium is a direct responder to Mtb when bacterial burden is high, rather than early after inhalation. The absence of MMP1 expression by primary human airway epithelial cells during low-dose Mtb infection has previously been described (204).

84 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis

Interestingly, the increased expression of MMP1 in the presence of a high Mtb-burden might be a way of directly driving lung pathology during active TB by the pathogen. The expression of IL36G was only significantly increased at 24h and had returned to baseline by 72h. IL36G is a IL1-family member that has mainly been studied in the context of skin inflammatory disorders and is thought to be a pro-inflammatory mediator (292). Interestingly, IL36G expression has recently been described to be upregulated in Mtb-infected macrophages (293). How IL36G or MMP1 contribute to the epithelial response to Mtb remains to be investigated in more detail in the future.

Across all investigated mediators, the expression and release of IL8 was most pronounced. However, the expression patterns in PBECs were contradicting observations previously reported with epithelial cell lines. IL8 was thus taken further for a more in depth investigation. PBECs did not upregulate IL8 strongly in response to low MOIs of Mtb, in contrast to the human primary epithelial response during infection with respiratory viruses (294) and other bacterial pathogens (267). In the present study, the extracellular bacterium S. pneumoniae induced IL8 release in PBECs within 24h of infection which was far more pronounced than the response induced by Mtb. Similar responses to S. pneumoniae have been shown in an infected bronchial epithelial cell line (295). While a lack of rapid IL8 release from primary human airway epithelial cells has been observed before (205), studies on A549 cells report inconsistent results. Wickremasinghe et al have shown IL8 release within 24 h of infection (205), while two other studies report significant IL8 induction only after three days (219, 276). Additionally, the release of CCL2 in response to mycobacteria is not consistently reported in A549 cells (218, 219, 222, 230). While it is difficult to account for the differences between the independent studies using the same cell lines, the lack of responses in primary cells opposed to established cell lines could be due to methodological differences or be associated with the source of the respective epithelial cells. Epithelial responses are partially conserved across bronchial and alveolar epithelium (237), but have also been reported to diverge in response to pro-inflammatory cytokines (296). Regarding methodology, culture of primary cells requires serum-free conditions during stimulation as presence of serum induces squamous terminal differentiation (297) and spontaneous mediator release (data not shown). In contrast to this, A549 cell lines are traditionally kept in medium supplemented with bovine or human serum. It is known that serum- supplementation affects the outcome of macrophage infection (114) and epithelial responses to Mtb might be affected in a similar manner. However, it can be argued that airway epithelium is not naturally immersed in serum, as would be peripheral blood mononuclear cells (PBMCs), and thus supplementation would artificially skew responses in vitro.

85 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis

IL8 induction was highest after 72h of Mtb exposure and independent of TLR2 activation, even though TLR2 responses were intact in PBECs. This was an interesting finding, as TLR2 has been previously described to drive Mtb-induced responses in A549 and TLR2-transfected Human Embryonic Kidney 293 (HEK293) cells (218, 298). While the C-type lectin receptor Dectin-1 has also been reported to mediate Mtb-detection in A549 cells (223), blocking of Dectin-1 activation did not impair the IL8 release from PBECs during Mtb-exposure either. These data suggest that increased release of IL8 is mediated by a mycobacterial-epithelial interaction which has not been previously shown. IL8 release correlated with Mtb-induced cytotoxicity and was not observed after infection with the non-pathogenic mycobacterium M. bovis BCG. Additionally, IL8 and increased cell death could both be rapidly induced in PBECs by direct stimulation with ESAT-6. Together, this suggests involvement of the RD1 locus and needs to be confirmed through Mtb deletion mutants in the future. The late response of PBECs may thus have occurred as accumulation of virulence factors secreted by live Mtb was required. IL8 release was abrogated by the NADPH oxidase inhibitor diphenyleneiodonium (DPI). ROS-generation through NADPH-oxidases as an immune response was originally thought to be a function of professional phagocytes as part of the oxidative burst (299). Their role during infections has been supported by the increased susceptibility of people with chronic granulomatous diseases, caused by NADPH-oxidase deficiencies, to persistent or recurring bacterial infections (300, 301). Now, it is known that NADPH-oxidases are expressed in most cell types, including epithelial cells (302). ROS were not measured directly in the present study, however, the effects of DPI on the epithelial response during Mtb infection strongly suggests their involvement. Even though Mtb affects the mitochondrial mass of epithelial cells (303), mitochondrial-derived ROS species were not found to contribute to the observed response to infection since Rotenone, an inhibitor of the mitochondrial electron transport chain (304), could neither inhibit cell death nor IL8 release in the present study. The effect of DPI revealed that both were driven by the NADPH oxidase pathway, a source for cellular ROS.

TLR2 as well as Dectin-1 have been shown to induce ROS in A549 cells during Mtb infection and to mediate IL8 release (218, 223). Neither receptor had an effect on IL8 secretion after Mtb-exposure of PBECs. Interestingly, Lee et al described early epithelial infection-induced IL8 induction to be dependent on TLR2-induced ROS which could be inhibited by DPI as well as Rotenone (218). The inhibitory effect of both compounds suggests involvement of mitochondrial ROS (305). Here, the same concentrations of ROS-inhibitors and increased concentration of anti-TLR2-antibody were used, but neither Rotenone, nor αTLR2 had an effect on IL8 levels. The absence of inhibition by Rotenone, and by extension the involvement of mitochondrial ROS, could be a function of the limited uptake of Mtb by PBECs.

86 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis

It has long been known that Mtb has cytotoxic effects on epithelial cells. After several days of culture, Mtb-infected A549 as well as HeLa cells undergo cell death (289, 306) which has been associated with the spread of infection in cultured A549 cells (134). This is the first time that Mtb- driven cell death has been shown to be dependent on NADPH-oxidases and thus potentially ROS production. While ROS are mediators of intracellular signalling, their accumulation can be cytotoxic. DPI did not completely inhibit Mtb-induced cell death. Direct perforation of the cell membrane by ESAT-6 may additionally contribute to the observed Mtb-induced cytotoxicity (307). Other pathogens have been described to induce NADPH oxidase dependent epithelial necrosis via secreted virulence factors. For example, Clostridium difficile toxin B induces ROS-mediated necrosis in intestinal epithelium which can be inhibited by DPI, resulting in reduced tissue pathology (308). Whether Mtb can drive tissue pathology in a similar manner through direct induction of epithelial cell death remains to be confirmed. Reactive oxygen species are part of the antimicrobial host response to several pathogens, yet physiological concentrations of ROS cannot efficiently kill intracellular or free Mtb (309–311). This suggests that the induction of ROS may be a mycobacterial survival strategy and the resulting tissue damage induced by epithelial necrosis in combination with chemokine release attract more professional phagocytes and provide new infection niches for Mtb.

The present study showed that high dose Mtb exposure of primary airway epithelial cells resulted in epithelial cell death and release of IL8, which can also be directly driven by secreted mycobacterial virulence factors. Both were dependent on NADPH and TLR2-independent, suggesting a novel mechanism for the interaction of epithelial cells and Mtb. Even though IL8 transcription was strongly increased over time, it is unclear whether the increased release of IL8 during exposure to Mtb reflects a direct response of the epithelium or, in part, a bystander effect caused by increased cell death. ROS are involved in the activation of several signalling cascades, such as the activation of NFκB and MAP kinases. Primary airway cells as well as A549 cells can activate NFκB via NADPH oxidase induced ROS in response to viral infections (312). In macrophages, TLR2- and ESAT-6- induced ROS activate MAP kinases and NFκB which drives cytokine induction (285). In PBECs, other PRRs could potentially induce similar cascades, leading to NFκB activation and downstream IL8 expression. An exact mechanism remains to be identified, but based on the present data and relevant literature is proposed to be as follows: Mtb, likely through RD-1 dependent virulence factors, activates PRRs other than TLR2 or Dectin-1 resulting in NADPH-oxidase activation. Reactive oxygen species are generated and activate downstream signalling, such as NFκB, which in turn induces IL8 expression. Overactivation of this pathway or sustained exposure to mycobacterial virulence factors, additionally results in cell death, which together with the released chemokines may promote neutrophil influx to the site of infection. This would contribute to tissue damage and

87 Results Chapter 1: Primary bronchial epithelial cells as direct responders to Mycobacterium tuberculosis inflammation in the respiratory tract in vivo. Taken together, this chapter revealed that primary bronchial epithelial cells are inert to low dose Mtb infection, thus disproving the hypothesis that PBECs are a target for and potent responders to initial infection.

88 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection 14 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection

14.1 Introduction

After inhalation into the airways, Mtb is taken up by macrophages patrolling the epithelial surface lining. The proximity of macrophages and epithelial cells affects the activation state of both cell types during homeostasis and inflammation (191, 313, 314). While primary human bronchial epithelial cells (PBECs) were unresponsive to small doses of Mtb (see Results Chapter 1)(204, 205), which are likely encountered after inhalation of Mtb, alveolar macrophages have long been known to be potent responders to the pathogen (114, 207). Mtb may thus indirectly activate epithelial cells through macrophage-derived cytokines released during infection. Shaping the local immune response to Mtb, there are three ways in which this cross talk might impact the outcome of infection: Firstly, cross-talk between epithelium and infected macrophages might contribute to the activation state and subsequent improved intracellular control of Mtb by macrophages. Secondly, activated epithelial cells may provide a source of broad-range antimicrobial peptides (AMP) and thus contribute to the control of extracellular Mtb locally. And thirdly, activation of epithelial cells might result in the release of chemotactic factors, ultimately contributing to the recruitment of immune cells to the site of infection.

Previous evidence that human airway epithelial cells can improve macrophage function during Mtb- infection was derived from A549 cells and, more recently, from work with primary small airway epithelial cells (SAEC). Both cell types have been described to increase macrophage control of intracellular bacteria through cross-talk involving granulocyte-macrophage colony-stimulating factor (GM-CSF) and β-defensin 2 (hBD2), respectively (191, 230). This cross-talk is initiated through pro- inflammatory mediators released from infected macrophages. Amongst them interleukin (IL) 1β (139) and tumor necrosis factor (TNF) (315), which are both potent activators of airway epithelial cells (202). Thus it is likely, that Mtb infection of macrophages leads to pro-inflammatory activation of epithelial cells in a paracrine manner which shapes the host response to infection. This concept has been supported by the finding that human airway epithelial cells provide a rich source of matrix metalloproteinases (MMP) in response to TNF secreted from Mtb-infected macrophages (105, 204). In the zebrafish model of tuberculosis infection, the induction of epithelial MMP9 has been shown to be involved in the establishment of granulomas and recruitment of further immune cells to the site of infection (98). Similarly, IL1β may shape the local inflammatory environment. IL1β important for

89 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection tuberculosis resistance in mice (316, 317) and human innate control of infection (139). It is also known to introduce the release of AMPs from epithelial cells (187, 318, 319), which may be beneficial during the early stages of tuberculosis infection to control the pathogen locally. This is particularly interesting, since macrophages are thought to be a poor source of AMPs (191, 225, 226).

Additionally, airway epithelial cells can support and orchestrate the influx of immune subsets through the release of chemokines in animal models and in experiments with cell lines in vitro (222, 237, 238). Chemokines are a family of cytokines that induces the migration of cells across a concentration gradient of these mediators, also known as chemotaxis. Primary human airway epithelial cells as well as epithelial cell lines have previously been described to release the IL8 in response to myeloid Mtb infection in vitro (205) and the bronchial epithelium is a source for CXCL10 during human tuberculosis in vivo (202). Both factors are chemotactic for leukocyte subsets (194, 195), suggesting that the human airway epithelium is involved in the early immune cell recruitment to the site of infection in vivo.

Taken together, infection with Mtb only requires few mycobacteria (161, 162), and early responses must be shaped by uninfected as much as infected cells in the airways. Macrophages provide a rich source of inflammatory-mediators that activate surrounding epithelium, however to date the global response of primary human airway epithelial cells to infected macrophages has not been investigated in depth and their potential contribution to the defense against Mtb is not well understood.

14.2 Hypothesis

Primary bronchial epithelial cells are potent responders to myeloid Mtb-infection and this cross-talk supports immune mechanisms imperative for the host response to Mtb.

14.3 Aims

Aim 1: Establish a co-culture model of myeloid-epithelial interactions during Mtb-infection that allows the interrogation of PBEC responses.

Aim 2: Measure the global epithelial transcriptomic responses to myeloid infection with Mtb and identify the pathways involved in its activation.

Aim 3: Assess the contribution of the identified signatures to host response mechanisms during Mtb-infection with regards to bacterial control and recruitment of immune subsets.

90 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection 14.4 Results

14.4.1 Macrophages are the major immune subset in the lung lining and release epithelial-activating cytokines after Mtb infection

It is well known that the majority of immune cells recovered by bronchoalveolar lavage (BAL) from the airspaces of the non-inflamed lungs are macrophages (89, 116). However, lymphocyte subsets might be resident in the epithelial layer and not be recovered by superficial lung washings. To assess which cell subsets are most likely to contribute to early responses after arrival of Mtb in the human lungs, differential cell counts of bronchial brushings recovered during bronchoscopy were acquired (courtesy of Corrina Wright, Cytopathology, St. Mary's Hospital, Imperial College Healthcare NHS Trust) (Figure 14.1 A). Samples were collected from individuals with recent close sustained exposure to culture confirmed ATB index cases (Mtb exposed) and Mtb unexposed healthy volunteers. While the dominant cell type recovered from the airway lining were bronchial epithelial cells, the largest immune subset detected in all donors were macrophages followed by lymphocytes. Neutrophils were infrequent and could only be detected in eight samples. Interestingly, Mtb exposed individuals did not have significantly different cellular composition in comparison to unexposed volunteers. This finding suggests that in the Mtb-naïve lungs, as well as early after Mtb-exposure, cellular cross-talk will largely occur between the airway epithelium and resident macrophages.

To confirm that macrophages release pro-inflammatory mediators in response to Mtb, THP-1 cells were infected for 24h (Figure 14.1 B). THP-1 cells are a monocytic cell line, which can be differentiated into macrophages through treatment with phorbol-12-myristate 13-acetate (PMA) and are commonly used for in vitro studies of Mtb-macrophage interactions (191, 320). Both, differentiated and undifferentiated, THP-1 cells released considerable amounts of IL1β and TNF in response to infection. The release of these cytokines could also be confirmed when primary alveolar macrophages were used (Figure 14.1 C), suggesting that THP-1 cells reflect the pro-inflammatory responses of airway macrophages. Interestingly, IL1β and TNF are constitutively present at low levels in the epithelial lining fluid of the upper and lower healthy human airways (Figure 14.1 D). Pro- inflammatory mediators are thus released from infected myeloid cells during Mtb infection in vitro and present at the site of infection in vivo.

To determine whether PBECs responded to pro-inflammatory mediators, cells were stimulated with recombinant cytokines (Figure 14.2). In addition to IL1β and TNF, Interferon (IFN) γ was added to PBECs since it an important mediator secreted by lymphocytes during tuberculosis (321). All three

91 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection cytokines caused a dose dependent increase of IL8 release from PBECs. Taken together, these findings confirm that macrophages release pro-inflammatory cytokines during Mtb-infection which can stimulate cytokine release by PBECs.

Figure 14.1: Macrophages are the major immune subset in the lung lining and release pro- inflammatory cytokines in response to Mtb infection. (see next page)

92 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection

Figure caption for Figure 14.1: (A) Presence of total bronchial epithelial cells (BECs), macrophages (MΦ), lymphocytes (LYM) and neutrophils (NΦ) was measured by differential cell counts of bronchial brushings derived from the airway epithelial lining. Subsets are shown as % of total cells recovered from healthy Mtb unexposed (n=17) or exposed (n=9) individuals. (B) THP-1 cells were used as monocytes or PMA-differentiated into macrophages and infected with Mtb H37Rv at the indicated MOI for 24h. IL1β and TNF were measured by ELISA in two independent experiments and are shown as mean±SEM. (C) Human alveolar macrophages were recovered from bronchoalveolar lavage and infected with Mtb H37Rv (MOI5). The release of IL1β (n=7) and TNF (n=3) was measured after 24h. (C) shows the IL1β and TNF levels in the nasal and bronchial epithelial lining fluid collected from five healthy volunteers, measured by MSD immunoassays. Differences between immune subsets in (B) were compared by Friedman test with Dunn’s post-test. Horizontal lines indicate the median. *, p<0.05; ***, p<0.001; ****, p<0.0001.

Figure 14.2: PBECs release IL8 in response to stimulation with pro-inflammatory cytokines. PBECs were stimulated with recombinant human TNF, IL1β or IFNγ for 24h at the indicated concentrations (left panel, mean±SEM) or at 10ng/ml (right panel). IL8 release was measured by ELISA (n=11). IL8 release in response to 10ng/ml cytokine was compared to medium control (BEBM) by Friedman test with Dunn’s post-test. Horizontal lines indicate the median. **, p<0.01; ***, p<0.001; ****, p<0.0001.

93 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection 14.4.2 Epithelial cells contribute to the pro-inflammatory milieu during myeloid Mtb-infection in a co-culture transwell model

Macrophages were the largest immune cell subset present in the healthy airways. Since their pro- inflammatory responses to Mtb may activate surrounding airway epithelial cells, a co-culture model was developed to mimic this interaction in vitro (Figure 14.3 A). For this, PBECs were seeded into tissue culture plates and transwell inserts with a pore size of 0.4 µm added on top, to allow exchange of soluble mediators between the compartments. Myeloid cells were added into the transwell. Since cytokine responses during Mtb infection were comparable between differentiated and undifferentiated THP-1 cells, undifferentiated THP-1 cells were used to represent the myeloid immune subset in the airways. Mtb H37Rv was added to either compartment as desired.

To assess how the pro-inflammatory milieu created during myeloid Mtb infection was affected by the presence of PBECs, the levels of IL1β were measured in the bottom compartment of the transwell system. During Mtb infection of THP-1 cells, the release of IL1β was significantly increased, when PBECs were present in co-culture (Figure 14.3 B). The observed augmentation was sustained over time (Figure 14.3 C). IL1β release was dependent on direct interaction between myeloid cells and Mtb, while direct infection of PBECs did not elicit IL1β release (Figure 14.3 D).

94 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection

Figure 14.3: Mtb-induced IL1β levels are augmented in a co-culture model of myeloid-epithelial interactions. (A) To interrogate the effect of myeloid-epithelial cross-talk during Mtb infection, a transwell co- culture system was established. Separated by a 0.4 µm pore-sized transwell membrane, PBECs were seeded in the bottom well of a tissue culture plate and THP-1 cells were added into the transwell insert. Cells were infected as indicated. (B) In co-culture, IL1β release from THP-1 cells was measured in the presence or absence of PBECs via ELISA at 24h with or without Mtb H37Rv infection (MOI5) (n=5). (C) IL1β release during THP-1 cell infection was measured for up to 72h post infection (n=3). (D) shows IL1β levels measured after 24h of culture, the experimental set up was as depicted (n=6). For (B) and (C), groups were compared by 2-way analysis of variance and Sidak’s post-test. Means±SD are shown. For (D), Friedman test with Dunn’s post-test was used to compare IL1β levels with the baseline levels of unstimulated PBECs. Bars indicate the median. * p<0.05; **, p<0.01; ***, p<0.001; ****, p<0.0001.

95 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection 14.4.3 Exposure to infected THP-1 cells induces global transcriptomic changes in PBECs

The presence of PBECs during myeloid Mtb infection resulted in a more pro-inflammatory milieu in culture, which likely induces various changes in epithelial cells. Since, to date, the global response of airway epithelial cells to Mtb-infected immune cells has not been studied, whole transcriptome analysis was performed to assess PBEC responses in co-culture. Epithelial cells were cultured in the presence of uninfected (THP) or Mtb-infected THP-1 cells (THP+Mtb). Paired PBEC samples from eight donors were prepared for Affymetrix GeneChip Human Transcriptome Array (HTA) 2.0 chips (see Methods 12.9.7). After Robust Multi-array Average (RMA) normalisation, all NCBI Reference Sequence Database (RefSeq) annotated transcripts were included in the further analysis of differentially expressed (DE) genes. DE genes between (THP+Mtb) and (THP) stimulated PBECs were identified by Significance Analysis of Microarrays (SAM) analysis using 256 permutations. 428 probesets representing 375 genes were significantly differentially expressed at a q-value < 0.05. Of these, 70 were elevated by a fold change > 1.5 (Figure 14.4 A, Appendix Table 18.1). To identify functional patterns of the transcriptomic signature, all differentially expressed genes were analysed with InnateDB (251), for pathway and gene ontology (GO) enrichment analysis, and oPOSSUM (255), to detect over-represented transcription factor binding sites (TFBS). TFBS analysis indicated the involvement of the interferon regulatory factor (IRF) - and nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB)-family in the regulation of the transcriptomic signature (Figure 14.4 B). These findings are complemented by the results of the pathway over-representation analysis (ORA) (Figure 14.4, Appendix Table 18.2). DE genes were associated with pathways involved in immune response signalling, including interferon-driven pathways, which can be mediated by IRF transcription factors (322). Similarly, GO ORA was enriched for terms associated with cytokine and interferon (IFN) signalling (Figure 14.4 D, Appendix Table 18.3). In summary, this data suggests that PBEC responses to myeloid Mtb-infection are mainly of pro-inflammatory nature, as supported by the enrichment of NFkB-inducible targets, alongside an IFN-inducible signature.

96 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection

Figure 14.4: Mtb-infected THP-1 cells induce global transcriptomic changes in PBECs. In the transwell co-culture model, PBECs from eight donors were exposed to uninfected (THP, T) or Mtb-infected (THP+Mtb, TM) THP-1 cells for 24h. Whole transcriptome analysis was performed on PBECs with Affymetrix HTA2.0 arrays. After RMA normalisation, SAM analysis was performed on all RefSeq annotated genes. (A) Hierarchical clustering of all significantly differentially expressed genes at a fold change of > 1.5 and a q-value < 0.05 was performed using average linkage and Euclidean distance (expression range from low (green) to high (red)). All DE genes at a q-value < 0.05 were used for statistical over-representation analysis (ORA) by InnateDB and oPOSSUM. The most significant Transcription Factor Binding Sites (TFBS) (B), Pathways (C) and Gene ontology (D) terms are shown. For (C) to (D), the red dashed line indicates a z-score of 10 or a corrected p-value of 0.05. For (C), IRF- and NFκB-family members are indicated in blue and red respectively.

97 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection 14.4.4 Transcriptomic PBEC signatures are strongly dependent on direct contact between Mtb and THP-1 cells

To confirm the transcriptomic signature identified by microarray analysis, a subset of genes was selected for validation by RT-PCR in independent samples. In order to better understand the patterns of target gene induction, the co-culture model was extended and Mtb was directly added to PBECs in the presence or absence of THP-1 cells (Figure 14.5). The following seven targets with different biological functions were chosen for validation: DEFB4 encodes the known antimycobacterial peptide β-defensin 2 (hBD2) and can be induced by various pro-inflammatory mediators (190, 191, 323). S100A7A, also known as koebnerisin, is a S100 family member, which has been shown to have antimicrobial activity similar to its close homologue psoriasin (S100A7) (324). Expression of IL8 and IL36G were both detected after direct infection of PBECs with Mtb (see Results Chapter 1). While IL8 is a well-studied chemokine, IL36G is an IL1-family member which may be beneficial during tuberculosis infection (293), yet has not been studied in depth. Additionally, C-X-C motif ligand (CXCL) 10, a chemokine which overall showed the highest expression and has previously been detected in the bronchial epithelium of ATB patients (202), and two known type I IFN inducible targets interferon-induced protein with tetratricopeptide repeats (IFIT) 1 and interferon-induced protein (IFI) 44 were taken forward for validation. All targets were detected by RT-PCR in PBECs exposed to infected THP-1 cells, confirming the microarray findings. Strong gene induction was dependent on myeloid infection and could not be achieved by direct addition of Mtb to PBECs in the presence or absence of myeloid THP-1 cells. Interestingly, the presence of THP-1 cells alone was enough to induce DEFB4, S100A7A, IL8 and IL36G, while this trend was not observed for CXCL10, IFIT1 and IFI44 (Table 14.1). This suggested two different modes of induction for the respective sets of genes.

98 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection

Figure 14.5: PBEC gene expression in co-culture is strongly dependent on direct contact between Mtb and THP-1 cells. In the transwell model, PBECs were exposed to THP-1 cells or Mtb H37Rv (MOI5 over THP-1) for 24h as indicated. Gene expression in PBECs was measured by RT-PCR and is shown as fold change over unstimulated PBECs (DEFB4, n=6; IFIT1 and IFI44, n=7; IL8, S100A7A, IL36G and CXCL10, n=8). Friedman test with Dunn’s post-test was used to compare expression with unstimulated controls. Bars indicate the median. * p<0.05; **, p<0.01; ***, p<0.001; ****, p<0.0001.

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Table 14.1: Fold change IQR of target genes in PBECs exposed to uninfected and infected THP-1 cells.

Co-culture stimulation: Co-culture stimulation:

Transcript THP-1 THP-1 + Mtb

Fold change IQR Fold change IQR

DEFB4 7.24-44.10 31.62-246.8

S100A7A 15.05-77.67 71.76-309.2

IL8 1.62-3.36 6.30-12.60

IL36G 2.14-7.11 7.63-24.09

CXCL10 0.67-2.75 9.06-171.0

IFIT1 0.94-2.41 138.3-395.1

IFI44 0.89-1.56 16.01-57.94 IQR, inter quartile range.

100 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection 14.4.5 PBEC co-culture with THP-1 cells mimics the response to infected alveolar macrophages

Alveolar macrophages (AMΦs) are the main macrophage subset exposed to inhaled pathogens and the first target of Mtb-infection in the human lungs. To confirm that the detected gene expression profiles can be induced by THP-1 cells as well as the macrophage subset first encountered by Mtb, the co-culture was repeated with primary human AMΦs isolated via adherence from brochalveolar lavage from healthy volunteers. DEFB4, S100A7A, CXCL10 and IFIT1 were chosen as representative targets since they showed the strongest induction in response to infected THP-1 cells. All genes were expressed in PBEC co-culture with infected AMΦs (Figure 14.6 A). Due to the long-term culture of PBECs, it is challenging to obtain AMΦs in time for experiments. To overcome this obstacle, conditioned medium from infected and uninfected AMΦs was generated and used for stimulation of PBECs (Figure 14.6 B). DEFB4, S100A7A and CXCL10 were upregulated significantly by medium derived from infected AMΦs, while expression of IFIT1 showed a trend towards significance. This confirmed that the in vitro system can model cross-talk which may occur during Mtb-infection in vivo.

101 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection

Figure 14.6: Mtb-infection of alveolar macrophages drives gene expression in PBECs similar to THP-1 cells. (A) Alveolar macrophages (AMΦ) from two healthy donors were co-cultured in the transwell model with PBECs and infected with Mtb H37Rv (MOI5) as indicated. (B) Cell-free conditioned medium from Mtb-infected and uninfected AMΦs, alongside the appropriate culture medium controls were diluted 10- or 100-fold and added to PBECs. After 24h DEFB4, S100A7A (n=5) CXCL10 and IFIT1 (n=6) expression was measured by RT-PCR and is shown as fold change over unstimulated PBECs. Friedman test with Dunn’s post-test was used to compare stimulations. Bars indicate the median. * p<0.05; ***, p<0.001 or the exact p-value are given.

102 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection 14.4.6 IL1β drives parts of the epithelial transcriptomic response to myeloid Mtb-infection and is enhanced by TNF

THP-1 cells and primary AMΦs induced marked transcriptomic changes in PBECs. However, since myeloid cells release a multitude of soluble mediators in response to Mtb, it was unclear which factors induced the observed epithelial gene expression. Pathway enrichment analysis suggested that a proportion of the infection-induced changes may be dependent on cytokine mediated NFκB activation. Since IL1β was augmented in co-culture and is known to activate NFκB (325), it was investigated, whether IL1β can mediate the effects observed during co-culture. Neutralisation of IL1β in the transwell system during co-culture resulted in abrogation of DEFB4, S100A7A, IL8 and IL36G expression in PBECs exposed to Mtb-infected THP-1 cells (Figure 14.7 A). Additionally, gene induction in the presence of uninfected THP-1 cells could be prevented, suggesting that constitutive IL1β release by THP-1 cells drove the expression of these genes in the absence of Mtb. IL1β did not significantly alter expression of CXCL10, IFIT1 or IFI44 (Figure 14.7 A) and recombinant IL1β was not able to induce CXCL10 directly, while DEFB4 was strongly inducible (Figure 14.7 B).

To see whether IL1β was the sole inducer of the observed signature, and since TNF is released during Mtb-infection by macrophages, TNF was neutralised in co-culture. DEFB4 expression was measured representatively for the IL1β-regulated genes and was found to be diminished, but not abrogated during neutralisation of TNF (Figure 14.8 A), which also decreased IL1β levels during co-culture (Figure 14.8 B). Interestingly, Mtb-induced TNF could increase IL1β release from THP-1 macrophages in an autocrine manner (Figure 14.8 C).

103 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection

Figure 14.7: Mtb-induced IL1β drives a proportion of the PBEC response to myeloid infection. (see next page)

104 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection

Figure caption for Figure 14.7: (A) PBECs were co-cultured with infected or uninfected THP-1 cells in the presence of 20μg/ml αIL1β or IgG1 (isotype control) as indicated. After 24h, gene expression was measured by RT-PCR. Expression is shown as % of gene induction by isotype control [THP-

1+Mtb+IgG1]. DEFB4, n=5; S100A7A, n=6; CXCL10, IFI44, IFIT1, IL36G and IL8, n=7. (B) PBECs were stimulated with recombinant IL1β at the indicated concentration for 24h. Expression of CXCL10 and DEFB4 was measured and is shown as fold change over unstimulated PBECs (n=5). Friedman test with Dunn’s post-test was used to compare expression with the corresponding isotype (A) or unstimulated (B) controls. Bars and horizontal bars indicate the median. n.s., not significant; *, p<0.05; **, p<0.01. ϕ, not detected in one donor.

Figure 14.8: TNF promotes IL1β-driven gene induction in a THP-1-autocrine manner.

PBECs were co-cultured with Mtb-infected (MOI5) THP-1 cells with 20μg/ml αTNF or IgG1 (Isotype control) for 24h. (A) DEFB4 expression was measured by RT-PCR and is shown as % induction of isotype control (n=3). (B) IL1β release was measured during co-culture by ELISA (n=3). (C) PMA- differentiated THP-1 macrophages were infected with Mtb H37Rv (MOI5) for 24h. The left panel shows one representative experiment. The right panel displays IL1β release as % of isotype control (n=5). For (A) and (B), horizontal bars represent the median. Wilcoxon signed rank test was used to compare groups. For (C), mean±SD are shown and t-test was used to compare groups with isotype control in the right panel. * p<0.05; **, p<0.01 or the exact p-value are given.

105 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection 14.4.7 Type I interferon signalling is activated in epithelial-myeloid co- culture during Mtb infection

Pathway analysis suggested that besides the IL1β-dependent signature, type I interferons (IFN) may drive epithelial responses in co-culture. While type I IFNs are a family consisting of 13 IFNα and IFNβ, all of which signal through the common type I IFN α/β receptor (IFNAR) (326), IFNβ has shown the strongest induction by infection of primary human macrophages (139). Indeed, Mtb induced IFNβ expression in AMΦs (Figure 14.9 A) and expression and secretion was observed in THP-1 cells (Figure 14.9 B and C). While PBECs did not show significant upregulation of IFNB after direct infection or exposure to infected THP-1 cells (Figure 14.9 D), the latter induced significant Signal transducer and activator of transcription (STAT) 1-phosphorylation in PBECs (Figure 14.9 E). Since STAT1 is phosphorylated downstream of type I as well as type II and III IFN signalling (327, 328), the latter were measured in the culture supernatants of Mtb-infected THP-1 cells. However in contrast to IFNβ, neither IFNγ nor IFNλ were detected in culture supernatants of Mtb-infected THP-1 cells (data not shown).

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Figure 14.9: Myeloid cells upregulate IFNβ during Mtb-infection and induce STAT1-activation in PBECs. (A) AMΦs from three donors were infected with Mtb H37Rv (MOI5) for 24h. IFNB expression was measured by RT-PCR and is shown as relative expression (rE) over GAPDH and HPRT. (B) THP-1 cells were infected with Mtb (MOI5) or left unstimulated (BEBM medium control) for the indicated time. IFNB expression is shown as mean fold change over BEBM stimulation at 6h from two independent experiments. (C) IFNβ release by THP-1 cells after 24h of infection was measured by ELISA. Mean±SD are shown (n=3). (D) PBECs were stimulated in the transwell co-culture system as indicated and IFNB expression measured after 24h. Fold change was calculated over unstimulated cells. Bars indicate the median (n=5). (E) Protein levels of STAT1 and phosphorylated (phospho)-STAT1 were measured by Western blot. Signal intensity is shown normalised to β-Actin levels (n=3). (F) shows one representative Western blot on PBECs in transwell co-culture with uninfected (THP) or Mtb-infected (THP+Mtb) THP-1 cells or after stimulation with recombinant 10ng/ml IL1β or IFNβ for the indicated time. For (C) and (E), paired t-test was used to compare groups. For (D), Friedman test with Dunn’s post-test was used to compare expression with unstimulated PBECs. n.s., not significant; *, p<0.05; **, p<0.01. ϕ, not detected in one donor.

107 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection 14.4.8 Type I IFN signalling activates gene expression in PBECs during co- culture

Since IFNβ was released by infected THP-1 cells and STAT1 activation detected in PBECs exposed to infected myeloid cells, it was determined next whether type I IFNs were driving the expression of IL1β-independent genes. To allow the simultaneous abrogation of signalling of all 14 type I IFNs, IFNAR activation was inhibited through blocking antibodies against the IFNAR2 subunit of the receptor. CXCL10, IFIT1 and IFI44 expression by PBECs exposed to infected THP-1 cells could be inhibited by blocking IFNAR2 (Figure 14.10 A). IFNAR2 signalling had no effect on the IL1β release in co-culture (Figure 14.10 B) or the IL1β-dependent expression signature (Figure 14.10 C).

While the expression of CXCL10 was dependent on IFNAR signalling, epithelial CXCL10 has previously been described to be inducible by IL27 and IFNγ (329). To show that CXCL10 induction in PBECs during co-culture was independent of these cytokines, they were neutralised. Neutralisation of neither cytokine did significantly diminish CXCL10 expression (Figure 14.11). This supports the role of type I IFNs in the activation of epithelial cells by myeloid Mtb-infection. Interestingly, while IL1β enhanced interferon-induced CXCL10 in primary airway epithelial cells (Figure 14.12 and (202)), IL1β neutralisation did not result in consistent downregulation of CXCL10 transcription.

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Figure 14.10: IFNAR-signalling drives the IL1β-independent epithelial expression signature in response to myeloid Mtb-infection. PBECs were exposed to Mtb-infected THP-1 cells (MOI5) in the presence of increasing concentrations of αIFNAR2 (5, 10 and 20 µg/ml) or IgG2 (isotype control) as indicated. After 24h, gene expression was measured by RT-PCR and is shown as % of isotype control in (A) and (C). (B) shows IL1β release in co-culture measured by ELISA. Friedman test with Dunn’s post-test was used to compare groups against isotype control. Bars indicate the median. *, p<0.05.

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Figure 14.11: Epithelial CXCL10 expression in response to Mtb-infected THP-1 cells is independent of IL27 and IFNγ. PBECs were exposed to Mtb-infected THP-1 cells (MOI5) in co-culture in the presence of 20μg/ml

αIFNγ, αIL27 or the respective isotype controls IgG2a or goat-IgG (Iso) as indicated. After 24h, CXCL10 expression was measured by RT-PCR and is shown as % of induction of isotype control. Friedman test with Dunn’s post-test was used to compare groups against isotype control. Bars indicate the median. n.s. not significant.

Figure 14.12: IL1β enhances interferon-induced CXCL10 release by PBECs. PBECs were stimulated with recombinant IFNβ or IFNγ in combination with IL1β (all at 10 ng/ml) or left unstimulated (BEBM) for 24h. CXCL10 release was measured by ELISA. Mean±SD from one of two independent experiments is shown.

110 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection 14.4.9 Myeloid-PBEC cross talk does not improve the myeloid control of Mtb

Since PBECs were potent responders to Mtb-infected myeloid cells, as measured by their transcriptomic activation, it was investigated how they may contribute to the early control of the invading bacteria in the airways. Airway epithelial cell lines and primary small airway epithelial cells have previously been reported to improve macrophage control of Mtb through cytokine-driven cross-talk (191, 230). To assess whether PBECs support macrophage function to a similar extent, PMA-differentiated THP-1 macrophages were infected with Mtb. After 4h, extracellular Mtb was washed off and epithelial cells added in transwell inserts on top of the infected monolayer to allow contact-independent cross-talk as previously described (191). The Mtb burden was assessed in the macrophage monolayer as well as in the whole well, to include extracellular Mtb. After 72h, PBECs did not affect macrophage control of Mtb (Figure 14.13 A). To see whether PBECs would improve Mtb-control through direct contact with THP-1 cells during infection, undifferentiated THP-1 cells were added onto PBECs and the cell culture was infected with Mtb for up to 72h. Similar to contact independent culture, direct contact between PBECs and THP-1 cells did not consistently improve control of Mtb (Figure 14.13 B).

Figure 14.13: PBECs do not improve Mtb-control of THP-1 cells. (A) PMA-differentiated THP-1 macrophages were infected with Mtb H37Rv (MOI 5) for 4h. Extracellular Mtb was washed off and transwell inserts containing PBECs added on top. After 72h, inserts and culture medium were removed to enumerate colony forming units (CFU) after lysis of the macrophage monolayer (Monolayer) (n=4). Alternatively, the lysing agent was added directly to the culture medium in the well to enumerate total Mtb present (Whole well) (n=3). (B) Mtb H37Rv (MOI5) was added directly to undifferentiated THP-1 cell in the presence or absence of PBECs for up to 72h. Mtb burden in the whole culture well was enumerated. Groups were compared by Wilcoxon matched-pairs signed rank test. n.s., not significant.

111 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection 14.4.10 Epithelial-derived antimicrobial peptides are active against Mtb

Even though PBECs did not directly improve THP-1 control of Mtb infection, the transwell co-culture revealed the expression of several AMPs in response to infected myeloid cells. Thus, PBECs might contribute to the local antimicrobial environment as a source of antimycobacterial effectors. Strikingly, the expression of AMPs S100A7A, encoding koebnerisin, and DEFB4, encoding hBD2, were not detected in THP-1 cells (Figure 14.14 A). Similarly, AMΦs did not express S100A7A during Mtb- infection and DEFB4 could only be measured at very low levels (Figure 14.13 B). To see whether the epithelial expression of AMPs in response to Mtb-driven inflammation could create an antimicrobial milieu locally, PBECs were infected with Mtb and recombinant IL1β was added to induce AMP expression. Since type I IFNs were also potent activators of PBECs, recombinant IFNβ was additionally added. Bacterial enumeration of the epithelial monolayer showed that neither cytokine improved control of Mtb over BEBM medium alone in the time period measured (Figure 14.15).

Since the concentrations of human AMPs required for antimycobacterial activity against Mtb are generally in the micro-gram range (65, 323, 330), in vitro stimulation of PBECs with IL1β may not have resulted in sufficient release of AMPs. Thus, the antimycobacterial activity of recombinant human AMPs was directly tested on growing liquid Mtb-cultures. Exposure of PBECs to infected myeloid cells, revealed the expression of AMPs such as β-defensins (DEFB4 and DEFB103) and S100 family members (S100A7, S100A7A and S100A12). Amongst these, hBD2 has previously been described to have direct antimycobacterial activity against Mtb (323). To confirm these effects, its activity against several Mtb strains was tested. Recombinant hBD2 was a potent antimicrobial agent against Mtb H37Rv (Figure 14.16 A and B) and three clinical Mtb isolates (Figure 14.16 C and D). Reduction in Mtb growth could already be observed after five days at a concentration of 2.5 µg/ml, which is a lower than the previously reported minimum inhibitory concentration (MIC) of 12 µg/ml (323). The second AMP shown to be dependent in IL1β, here, was koebnerisin (S100A7A). Since it has been reported to have direct antimicrobial effects against Eschicheria coli (E. coli) (324), recombinant protein was obtained commercially to test the activity of koebnerisin against Mtb. The obtained protein was not effective at reducing Mtb growth, however, the solvent in which the peptide was immersed strongly inhibited bacterial growth on its own (Figure 14.17 A and B), suggesting that the protein may not have been biologically active. However, a biologically active preparation of the close koebnerisin-homologue psoriasin (S100A7) could be obtained as a kind gift from Prof. Joachim Grötzinger (242). To confirm that S100A7 followed the same induction patterns as S100A7A, its expression was measured in PBECs in transwell co-culture. Indeed, the expression of S100A7 was induced in PBECs by infected THP-1 cells (Figure 14.18 A) and dependent on IL1β (Figure

112 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection

14.18 B). Similar to S100A7A, S100A7 was not induced in THP-1 cells or AMΦs after Mtb infection (data not shown). Recombinant psoriasin significantly reduced Mtb growth in liquid culture (Figure 14.18 C) and halved the bacterial load after seven days of incubation (Figure 14.18 D). Recombinant psoriasin has been shown to have cytokine-like activity and induce intracellular signalling cascades in microglia (242). To interrogate next whether exogenous psoriasin may support macrophage control of intracellular Mtb, psoriasin was added to infected cells. After 72h, no enhanced control of Mtb by infected PMA-differentiated THP-1 macrophages was observed at the used concentration of psoriasin (Figure 14.18 E).

Figure 14.14: DEFB4 and S100A7A are not expressed strongly in myeloid cells. THP-1 cells (A, n=2) and AMΦs from 3 donors (B) were infected with Mtb H37Rv (MOI5) for 24h. Gene expression was measured by RT-PCR and is shown as fold change over uninfected controls. n.d., not detected in any sample.

Figure 14.15: IL1β and IFNβ do not improve PBEC control of Mtb. PBECs were infected with Mtb H37Rv (MOI10) for 6h. Cells were washed and 10ng/ml IL1β or IFNβ added. BEBM is the medium control. At the respective time points, cells were washed, monolayers lysed and plated for Mtb enumeration by CFU. Experiments were performed at least in duplicate. Means are shown.

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Figure 14.16: hBD2 efficiently prevents Mtb-growth. (A) Mtb H37Rv was grown in the presence of the indicated concentrations of recombinant hBD2 or vehicle control (veh). Amikacin and gentamycin were used as positive controls at 200µg/ml and 100µg/ml respectively (n=5 from two independently grown H37Rv cultures). (B) At day 7, mycobacteria were plated to measure the bacterial burden by CFU (n=3 representative for two independent H37Rv cultures). (C) 5µg/ml hBD2 or vehicle control were added to cultures of the clinical Mtb strains CH, Gurung 333 (Gurung) or NPH4216 (NPH). (D) At day 7, bacterial burden was measured as CFU counts (n=3). Mtb growth was measured by optical density at 595nm (OD595nm) over time. Groups were compared against vehicle control at each time point by one-way ANOVA (results for (A) shown in table). Mean or mean±SD are shown. n.s., not significant; **, p<0.01; ***, p<0.001; ****, p<0.0001.

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Figure 14.17: A commercial preparation of koebnerisin does not affect Mtb growth. Mtb H37Rv was grown in the presence 125µg/ml koebnerisin, vehicle control (veh) and medium control (7H9) (n=2). (A) Mtb growth was measured by optical density at 595nm (OD595nm) over time. Amikacin and gentamycin were used as positive controls at 200µg/ml and 100µg/ml respectively. (B) At day 7, Mtb was enumerated by CFU. Means are shown.

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Figure 14.18: Recombinant psoriasin prevents Mtb-growth. (A) In the transwell model, PBECs were exposed to THP-1 cells or Mtb H37Rv (MOI5 over THP-1) for 24h as indicated. S100A7 expression in PBECs was measured by RT-PCR and is shown as fold change over unstimulated PBECs (n=5). (B) PBECs were co-cultured with infected or uninfected THP-1 cells in the presence of 20μg/ml αL1β or IgG1 (isotype control) as indicated. After 24h, S100A7 expression was measured by RT-PCR. Expression is shown as % of gene induction by isotype control [THP-

1+Mtb+IgG1] (n=5). Mtb H37Rv was grown in the presence of psoriasin or vehicle control (veh) at the indicated concentrations. (C) Mtb growth was measured by optical density at 595nm (OD595nm) over time. Amikacin and gentamycin were used as positive controls at 200µg/ml and 100µg/ml respectively (n=7 from 3 independently grown H37Rv cultures). (D) Psoriasin treated Mtb cultures were plated after 7 days for Mtb enumeration by CFU (n=3 representative for three independent H37Rv cultures). (see next page)

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Figure caption for Figure 14.18 continued: (E) PMA-differentiated THP-1 macrophages were infected with Mtb H37Rv (MOI5). After 2h, extracellular bacteria were washed off and psoriasin or vehicle control added. Mtb burden was enumerated by CFU after 72h (one representative experiment shown). For (A) and (B), Friedman test with Dunn’s post-test was used to compare expression with unstimulated controls or isotype control, respectively. Bars indicate the median. For (C), (D) and (E), groups were compared with vehicle control at each time point by one-way ANOVA (results for (C) shown in table). Mean±SD are shown. n.s., not significant; * p<0.05; **, p<0.01; ***, p<0.001.

117 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection 14.4.11 Presence of PBECs enhances neutrophil recruitment during Mtb infection

While PBECs exposed to Mtb-infected myeloid cells expressed AMPs with direct antimycobacterial activity, they might also secrete mediators which facilitate immune cell recruitment to the site of infection. To determine, whether presence of PBECs increased the concentrations of chemotactic mediators during Mtb-infection of THP-1 cells, soluble mediators were measured in culture- supernatants after 24 and 72h. Supernatants from infected THP-1 cell monocultures were compared to supernatants derived from infected epithelial-myeloid co-cultures. Presence of PBECs increased overall pro-inflammatory mediator levels during infection of THP-1 cells (Figure 14.19). Amongst those, various chemokines were directly expressed in PBECs, as measured in the transwell co-culture model (Table 14.2). Influx of immune cells is important to ensure control of Mtb (67) but can also drive pathophysiology (112). To see whether epithelial cells contribute to cell recruitment during early infection, migration of peripheral blood leukocytes (PBLs) towards cell-free culture supernatants generated from Mtb-infected THP-1 cells in the presence or absence of PBECs was measured (Figure 14.21 A). In brief, conditioned culture-supernatant was added to the bottom well of a tissue culture plate. Freshly isolated human PBLs were added into a transwell insert with a pore size of 5 µm, to allow cell migration, and placed on top of the conditioned medium. After 3 h, the migrated cells were collected from the bottom well and counted on a flow cytometer. To discern migrated subsets, cells were gated according to size (forward scatter) and granularity (side scatter) (Figure 14.21 B). The dominant immune subsets within PBLs are polymorphonuclear cells (PMNs), monocytes and lymphocytes. The phenotype of the cells was confirmed in three independent donors. Cells in the PMN-gate, largely consisted of neutrophils, as measured by the neutrophil markers CD15 and CD66b (245, 246) and cells in the monocyte and lymphocyte gates were positive for CD14 and CD3 respectively (Figure 14.20 and Table 14.3). PMNs were the largest migratory subset and PBECs enhanced their influx significantly (Figure 14.21 C). Few monocytes and lymphocytes migrated towards the culture supernatant (Figure 14.21 D and E), however the numbers were increased compared to background control (Figure 14.21 F). This data suggests that PBECs induce an increased chemotactic environment during myeloid Mtb-infection, which accelerates PMN migration towards the site of infection.

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Figure 14.19: Mediator release during Mtb-infection of THP-1 cells in the presence and absence of PBECs. THP-1 cells were directly cultured Mtb H37Rv (MOI5) in the presence or absence of PBECs for up to 72h. Mediators in cell-free culture supernatant were measured by luminex bead-based immunoassays. The bars show the mean mediator levels released by infected THP-1 cells in co- culture with PBECs, measured in two independent experiments. Arrows indicate absolute concentration changes compared to THP-1 cells infected with Mtb in monoculture (Appendix Table 18.4).

Table 14.2: Chemotactic mediators induced during THP-1-PBEC co-culture during Mtb-infection:

Cell subset Chemotactic factor

CCL2 (331), CCL4 (332), CCL8 (331), CCL20 (333) Lymphocytes CXCL10 (195, 333), CXCL11 (195, 334), IL6 (335), IL8 (336),S100A7 (337)

CCL2 (331), CCL8 (338), CXCL10 (339), DEFB4 (340), IL1β (341), S100A7 (337), S100A12 Monocytes (342), S100A15 (337), Trappin-2(343)

CCL20 (344), CSF2/GM-CSF (345), DEFB4 (340), IL8 (194, 346), S100A7 (337), S100A15 Neutrophils (337), Trappin-2 (343), SLP-I (347), IL1α (341)

Mediators are shown that were upregulated in PBECs (fold change>1.5, q-value < 0.05; Fig.4 A) (red), showed a mean increase in infected THP-1-PBEC co-culture over infected mono-culture at 24 or 72h in the Luminex assay (Figure 14.19) (blue) or were upregulated in both (black).

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Figure 14.20: Flowcytometric phenotyping PBLs. PBLs were isolated from whole blood and stained for CD3, CD14, CD15 and CD66b. Shown are representative plots for the gating strategy from one of three donors. After gating for singlets, forward (FSC) and side (SSC) scatter were used to define PBL subsets. Marker expression for each subset is shown in (Table 14.3). PMN, polymorphonuclear cells.

Table 14.3: PBL subset phenotypes according to FSC/SSC gating.

Marker expression in FSC/SSC gated Cell subset % of total PBLs - mean±SD subset in % - mean±SD

CD15+ (87.03±2.18) PMNs 55.63±9.01 CD66b+ (71.73±11.22)

Lymphocytes 27.20±5.51 CD3+ (71.73±11.22)

Monocytes 3.52±1.06 CD14+ (87.03±2.18)

FSC, Forward scatter; SSC, Side scatter; PBL, peripheral blood leukocytes; PMN, polymorphonuclear cells.

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Figure 14.21: PBECs enhance PMN influx during myeloid Mtb-infection. (A) PBLs were added into a transwell insert on top of a culture well containing conditioned medium from Mtb-infected THP-1 cells ± PBECs or medium control (BEBM). Supernatants were generated from five different PBEC donors (SN1-5). After 3 hours cells from the insert and the bottom well were collected and enumerated by flowcytometry. (B) shows representative plots of the gating strategy to define migrated subsets by forward scatter (FSC) and side scatter (SSC). Migration across the transwell membrane is shown as total number of recovered PMNs (C, left), lymphocytes (D) and monocytes (E) or as % of total cells (subset in transwell insert and bottom well) (C, right). (F) shows migration towards the BEBM medium control. Groups were compared by Wilcoxon signed rank test (n=12). Horizontal bars indicate the median. *, p<0.05; **, p<0.01; ***, p<0.001.

121 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection 14.5 Discussion

After entering the human airways, Mtb is thought to infect local immune cells: tissue-resident macrophages. The understanding of the interaction between leukocytes and the pathogen in the human lungs is largely based on in vitro studies using cellular monocultures. However, the infection of immune cells does not occur in isolation. The surface of the healthy human lungs is constantly exposed to invading agents and mainly consists of an epithelial layer which harbours resident leukocytes. Together, these cells form the first line of defense against respiratory pathogens. Even though lymphocytes and neutrophils are present, myeloid cells are the dominant immune subset in the bronchial lining and the bronchoalveolar space of the healthy lungs (210). This suggests that the earliest immune interaction after Mtb inhalation occurs between macrophages and epithelial cells. While it has been observed that Mtb can invade epithelial cells (142, 230), primary airway epithelial cells were weak responders to infection (see Results Chapter 1). The majority of bacterial burden is associated with macrophages early after exposure to Mtb (230) and during active disease, myeloid cells are the predominant cell subsets harbouring intracellular Mtb in sputum and bronchoalveolar lavage (142). As macrophages mount a potent pro-inflammatory response against the pathogen, epithelial cells are likely activated by the inflammatory milieu created by neighbouring infected macrophages in the human lungs.

To identify the contribution of human airway epithelial cells to the early innate immune response against Mtb, an in vitro co-culture model was established which allowed contact-independent communication between PBECs and infected myeloid cells in real-time. Interestingly, PBECs significantly enhanced the pro-inflammatory response of THP-1 cells to Mtb. This finding is similar to the observation that, even though airway epithelial cells are thought to regulate macrophage function to prevent excessive inflammatory responses during homeostasis, their immune-regulatory properties can be lost during viral infections driving a more inflammatory environment (118, 348). While previous studies on airway epithelial activation by myeloid-derived soluble mediators focussed on isolated pathways (105, 204, 205), the global transcriptomic response of primary airway epithelial cells in response to myeloid Mtb-infection was studied here for the first time. Striking expression changes were observed when PBECs were exposed to infected THP-1 cells in comparison to uninfected cells. The expression signature was strongly dependent on direct contact between THP-1 cells and Mtb and could not be induced by direct infection of PBECs. This suggests that these cells can act as amplifiers of infection induced signals, rather than direct targets for infection. The array of induced targets ranged from pro-inflammatory and chemotactic mediators to antimicrobial responses. The epithelial contribution to the outcome of infection could thus include supporting

122 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection macrophage function during infection, directly reducing extracellular Mtb-burden and attracting immune cells to the site of infection.

Here, PBECs did not improve macrophage control of Mtb in co-culture. This contradicts that A549 cells and, notably, primary SAECs enhanced macrophage control of intracellular Mtb in comparable culture conditions (191, 230). While there are differences in responses between bronchial and small airway epithelial cells to pro-inflammatory cytokines (349), the reported enhanced Mtb-control of macrophages mediated by SAECs was dependent on IL1β-induced DEFB4, which was conserved in PBECs. To avoid technical errors introduced by the handling of the transwell inserts, THP-1 cells and Mtb were added directly to PBECs. Over 72h, no improved control of Mtb by the addition of epithelial cells was observed. The concentration of secreted hBD2 in co-culture was not measured in either study. It thus is feasible that activation of PBECs by infected THP-1 cells was not as strong as activation of SAECs. While not observed in co-culture with THP-1 cells, mediators released by PBECs may still directly affect macrophage function. The in depth investigation of individual factors on the host control of Mtb will elucidate this further.

Based on pathway enrichment analysis of the transcriptomic response as well as the neutralisation of the cross-talk in vitro, activation of PBECs by myeloid Mtb-infection was largely driven by type I IFN signalling and IL1β. Both are known to be induced in myeloid cells through the Mtb ESX1 secretion system (139, 140, 350). Infection-induced IFNβ and IL1β have opposing roles in macrophages and can cross-regulate each other (141). Interestingly, PBEC gene expression occurred discretely and no cross-regulation between two pathways was observed. These two distinct modes of induction were reflected in the transcriptomic signature, which was dominated by genes associated with IRF- and NFκB-activation and the observation that IL1β- but not IFN-dependent genes showed heightened baseline induction in the presence of uninfected THP-1 cells.

Besides driving IL8 expression as previously described (205), IL1β enhanced transcription of IL1- family member IL36G. While IL8 has been studied in depth during Mtb infection, the role of IL1- family members, other than IL1β and IL1α (351), is not well understood. IL36G is not able to induce defensins in keratinocytes (352) and thus is unlikely to further the antimicrobial response of the airway epithelial cells. Whether it can directly increase the pro-inflammatory properties of macrophages and Mtb-control remains to be investigated.

Notably, induction of the antimicrobial targets DEFB4 and S100A7A in PBECs required myeloid IL1β. This response was enhanced through TNF-mediated autocrine augmentation of Mtb-induced IL1β release from THP-1 cells. Macrophage-induced epithelial AMPs may enhance the local antimicrobial

123 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection milieu during early infection in the airways. Overall, the detection of epithelial AMP-expression is an important finding since THP-1 cells did not express any of the selected AMPs during Mtb-infection and DEFB4 was only expressed at low levels in alveolar macrophages (224). Originally identified in the skin (353), hBD2 was later found to be expressed in various tissues, amongst them lung epithelium (187). Other than hBD1, which is constitutively expressed in epithelial cells, hBD2 requires induction by cytokines or pathogens (354). hBD2 is found in bronchoalveolar lavage during inflammatory lung disorders and is active against E. coli and respiratory pathogens such as P. aeruginosa (187). Evidence that airway epithelium is the source of β-defensins during tuberculosis infection in vivo is derived from a mouse models of latent Mtb infection, in which the murine homologue of hBD2, mouse beta-defensin 3 (mBD3) (355), co-localised strongly with Mtb in bronchial epithelial cells. Only little co-localisation was observed in infected macrophages (225). The antimycobacterial properties of hBD2 against Mtb H37Rv and multi-drug resistant (MDR) strains have been described before. However this has only been done via the Resazurin colorimetric assay, which does not quantify the actual bacterial burden (323). The present data shows that DEFB4 is induced in human PBECs during Mtb-driven inflammation and confirms its potent antimycobacterial activity against various Mtb strains.

PBECs also upregulated the close homologues S100A7 and S100A7A in response to infected myeloid cells, which have been shown to act as antimicrobial peptides (324, 356). They are part of the S100- family which has been emerging in tuberculosis research. The best studied family members in tuberculosis are S100A8/A9, which are induced during various inflammatory disorders. In ATB patients, these molecules have been found to correlate with pulmonary disease severity and peripheral neutrophil count (357). S100A7 and S100A7A have not been studied in depth in TB, but they are known to be overexpressed in skin during injury and inflammation (358). In this tissue, psoriasin (S100A7) is derived from epidermal rather than skin-infiltrating haematopoietic cells (359). In human lung biopsies, psoriasin was detected in epithelium as well as alveolar macrophages (360) and diminished Mtb-growth in vitro, in the present study. While S100A7 is not differentially induced during chronic respiratory disorders, such as COPD, infection with S. aureus correlates with increased psoriasin levels in BAL cells (360). Its antibacterial function is broad, with very potent effects against E. coli, but is ineffective against C. albicans (356, 359). Psoriasin showed activity against Mtb in culture, to a similar extent as against P. aeruginosa and S. aureus (356), which required high concentrations of protein to reduce bacterial growth. Even though koebnerisin (S100A7A) did not impair Mtb growth in this study, it is uncertain whether the obtained peptide was bioactive. It thus remains likely, that koebnerisin can, similar to psoriasin, target Mtb, which warrants further investigation in future. Clinical Mtb strains can induce varying levels of IL1β in

124 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection macrophages after infection (241, 361). Diminished induction of IL1β by Mtb may have evolved, in part, as a mechanism to evade epithelial antimicrobial defences. Whether this might also be associated with increased host susceptibility to these particular strains should be investigated further.

After the initial activation by the innate immune compartment through IL1β, mediators such as IL17 and IL22, known to induce defensins and S100 proteins in epithelial cells (362), may maintain or amplify the antimicrobial epithelial response after onset of the adaptive immune response. A caveat to these findings is that defensins and psoriasin were not directly measured on the protein level and that direct stimulation of PBECs with IL1β did not diminish Mtb-burden after infection. The latter may suggest that the induced concentrations in vitro are not enough to kill Mtb. This finding is similar to a previous report that found that infected macrophages, the source of IL1β during infection, did not improved Mtb control by infected A549 cells (230). The release of AMPs by epithelial cells during infection is an interesting and appropriate concept for epithelial defences against Mtb, since they are not as frequently targeted for intracellular infection as macrophages. Taken together, IL1β released during tuberculosis infection can induce expression of pro- inflammatory mediators as well as AMPs in epithelial cells which can reduce Mtb-burden.

Besides IL1β, type I IFN-signalling induced gene expression in PBECs exposed to Mtb-infected THP-1 cells. Type I IFNs have been emerging as important mediators during tuberculosis infection over the last couple of years. They are crucial for the host control of viral infections (110), but can have detrimental effects during bacterial infections. IFNAR deficient mice are more susceptible to viruses, however IFNAR signalling impairs the protective pro-inflammatory response during infection with the intracellular bacterium L. monocytogenes (363). In humans, viral infections predispose patients to severe secondary respiratory bacterial infections which have been attributed to the strong induction of type I IFNs (364, 365). Mice infected with Mtb after exposure to influenza virus, have a more severe long-term outcome. These animals showed moderate increases in bacterial burden at 120 days post infection and succumbed to infection at around 160 days, while the Mtb-only infected controls survived at least 240 days (366). Dependent on the mouse strain, type I IFN increases mortality during Mtb-infection (112). Rather than excessive bacterial burden, this is associated with exacerbation of tissue pathology and increased neutrophil influx (112, 367). In humans, during active TB, type I IFN driven signatures correlate with more severe disease and inflammation. In a pilot study, Subbian et al observed increased IFN-associated pathways in granulomas with high bacterial burden (91). Furthermore, peripheral upregulation of IFN-inducible genes correlated with disease severity in ATB patients (18). Despite the association with disease severity, the effect of type I IFNs

125 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection on the outcome of Mtb-infection after exposure is not well understood. Based on a mouse model, Desvignes et al. suggested that type I IFN and IFNγ are required for optimal immune cell recruitment during the pre-adaptive phase of Mtb-infection (368).

Induction of a chemotactic environment through epithelial-myeloid cross-talk may shape the host response against Mtb through the recruitment of immune cells to the site of infection. The influx of cells is required for control of the infection, but can also provide new infection niches for mycobacteria (98, 369). Cross-talk of PBECs and myeloid cells during infection resulted in increased induction of mediators with chemotactic function. PBECs significantly enhanced leukocyte migration towards mediators released during Mtb-infection of THP-1 cells. The largest leukocyte subset attracted by cell-free co-culture supernatants was polymorphonuclear cells (PMNs), the majority of which were neutrophils. Lymphocyte migration was also significantly increased, but the absolute number of cells detected was small. This is not surprising since lymphocytes need pre-activation to allow upregulation of chemokine receptors for migration (370). The total number of migrated monocytes was negligible and likely due to spill over by PMNs into the monocyte gate. It is unclear whether the increased migration of leukocytes was mediated by the enhanced response of THP-1 cells or due to mediators released from PBECs. THP-1 cells released cytokines that are not readily produced by PBECs, such as IL1β, while in turn epithelial cells contributed factors that were not induced in myeloid cells this setting, such as Trappin-2 or AMPs. The exact contribution of either cell type to the chemotactic milieu remains to be determined in future experiments, but it is likely to be a combination of both factors. While macrophages are the main subset of immune cells in the healthy lungs, Mtb-infection quickly recruited substantial amounts of neutrophils in vitro. Similar to the presented findings, Fujii et al. cultured primary bronchial epithelial cells together with alveolar macrophages resected from human lung tissue (210). Air pollution particles resulted in significant upregulation of cytokines released compared to challenged mono-cultures. Bronchial instillation of rabbits with these particle-challenged co-culture supernatants resulted in PMN influx into the airways.

Neutrophils are important early antimicrobial effectors with poor specificity. While they can cause substantial tissue damage and inflammation, their antimicrobial properties are crucial to control and prevent recurrent infections in humans (371). As professional phagocytes, they can internalise and kill pathogens. Alternatively, they release neutrophil extracellular traps (NETs). NETs consist of chromatin and granule-derived proteins and can directly kill gram-positive and gram-negative bacteria, through antimicrobial components deposited in the released chromatin structures (372).

126 Results Chapter 2: Primary bronchial epithelial cells as part of the immune-network during Mtb infection

While neutrophilia is associated with tissue destruction and inflammation during active TB (18), neutrophils reduced the bacterial burden in mice and zebrafish early after infection (143, 144). Neutrophils significantly contribute to the mycobacterial control of whole blood in vitro, likely through AMPs(65). NET release, on the other hand, has been reported to trap, but fail to kill, Mtb (373). However, killing assays were only performed for up to six hours, which might not have been enough time to kill slow-growing mycobacteria. The effect of neutrophil attraction towards the human lungs early during infection could thus have beneficial antimicrobial effects. Influx of neutrophils may result in AMP as well as NET release, of which the latter could allow the additional accumulation of locally secreted epithelial AMPs to concentrations that are sufficient to kill Mtb.

The limitations of this study are the use of undifferentiated THP-1 cells to represent the myeloid compartment in the respiratory tract. While these cells are phenotypically closer to monocytes than macrophages (374), cytokine release by THP-1 monocytes infected with Mtb (MOI5) resembled the response of PMA-differentiated THP-1 macrophages. THP-1 cells were also used in co-culture in a serum-free environment, to prevent squamous terminal differentiation of PBECs (297). This may affect the interaction between Mtb and the myeloid target cells, however pro-inflammatory mediators were still sufficiently released during infection and serum-free conditions may more accurately reflect interactions in the human airways. Additionally, the transcriptomic epithelial signature observed during co-culture with THP-1 cells resembled that induced by AMΦ for all interrogated genes. While Mtb is thought to infect macrophages in the alveoli, the airway epithelial cells used in this study were from the 4th bifurcation of the human airways and are phenotypically different from human alveolar epithelial cells, which are generally only found in preparations for small airway epithelial cells (SAECs). However, epithelial activation by infected myeloid cells presented here was contact independent and thus does not rely on anatomical proximity of the cell types. Even though responses to cytokines can diverge across different sections of the airways (237, 349), antimycobacterial responses were conserved across the upper and lower airway epithelium.

This study set out to identify the contribution of primary airway epithelial cells to host response against Mtb, initiated by the innate immune system. PBECs responded to type I IFN and pro- inflammatory mediators released by myeloid cells during Mtb-infection. This activation turned the epithelial cells into a rich source of antimicrobials locally, which are not induced in myeloid cells, and improved neutrophil recruitment towards the site of infection. Taken together, the presented data supports the hypothesis that primary human airway epithelial cells are potent responders to myeloid Mtb-infection and revealed a novel role for airway epithelial cells as contributors to the innate immune response to Mtb-infection.

127 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection 15 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

15.1 Introduction

It has become evident, that human infection with Mtb presents itself as a wide spectrum of different stages (17, 18). Especially latent TB (LTBI), a clinically asymptomatic state of infection, has been shown to be increasingly complex and varied. While it is thought that a third of the global population is latently infected with Mtb, the presence of bacteria and ongoing immune responses may range from non-existent to subclinical. LTBI is determined by the detection of peripheral immune priming to Mtb-antigens which may falsely classify patients who have cleared bacteria successfully, as infected. Truly infected individuals, however, are at a life-long risk of progression to active disease. Curiously, at the first stage of the natural history of tuberculosis, the acquisition of infection in the lungs, only 30-50% of individuals exposed to aerosolised Mtb become infected (52, 53). Strategies that aim at intercepting the spread of TB at this stage of the natural history could diminish the latently infected reservoir. Ultimately, this would result in a decreased number of people developing active TB disease. Transmission of Mtb has mainly been studied epidemiologically and revealed several environmental risk factors that contribute to the acquisition of infection in immune- competent individuals, including duration of exposure and smoking (52, 64). It has become increasingly evident that there are host-innate factors which may additionally influence the outcome of exposure. Persistently exposed individuals as well as close contacts to active pulmonary TB patients may never show signs of Mtb infection (57–59). This resistance to or clearance of Mtb, despite sustained exposure, has been suggested to be associated with host genetics and peripheral neutrophil counts (65, 68), but replication of these findings is still awaited.

The main portal for human Mtb-infection after inhalation of aerosolised bacteria is the respiratory tract. Resistance to or early clearance of infection is likely mediated by the local mucosal immune system and the epithelial lining. However, it is unclear which immune responses are beneficial immediately after exposure, which is in part due to the lack of knowledge about immune responses to Mtb in the human lungs. A lot of effort has been directed towards deciphering the spectrum of TB through interrogation of the peripheral immune compartments, especially through global transcriptomics (18, 375, 376). While these approaches have yielded new insights into the biology of human TB, the peripheral immune signatures cannot truly reflect responses at the site of infection or disease. During active pulmonary TB, even within the lungs of a single individual, gene expression

128 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection and cellular activation patterns of granulomatous lesions are very heterogeneous (17, 91, 93, 94) and poorly reflected in peripheral blood (18, 91). The understanding of lung-specific immune responses to Mtb-infection is mainly derived from investigations of tuberculous lesions or bronchoalveolar lavage samples from patients with active pulmonary TB (91, 377, 378). However, it has been reported that even in non-granulomatous tissue in healthy individuals, Mtb can be found, suggesting that even during latent infection, immunological activation may occur constantly on a small scale (31, 32). In fact, it has been confirmed, that even in the absence of ATB, Mtb-specific ongoing immune responses are detectable in pulmonary granulomas resected from latently infected individuals (20). The identification of immune pathways activated after recent exposure to Mtb in the human respiratory tract, would provide valuable insights into the host-pathogen interactions during the first stages of the natural history of tuberculosis. The comparison of the mucosal epithelial lining of infected and uninfected TB exposed contacts may identify markers of early infection and, all other variables being balanced, the comparison of TB exposed subjects with matched unexposed uninfected healthy controls may even reveal correlates of exposure, resistance or clearance of Mtb (Figure 15.1).

Figure 15.1: Diagram of potential mucosal signatures in the TB exposed human respiratory tract. The diagram depicts the characteristics of markers or signatures of resistance to or clearance of Mtb-infection, exposure or early infection and their presence in TB exposed infected and uninfected subjects.

129 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

While bronchoalveolar lavage is frequently used to sample the lung mucosal surface to assess soluble mediators ex vivo, this technique highly dilutes the sample and lavage returns can be variable between individuals (379). To overcome these problems, a novel technique has been developed recently to recover concentrated mucosal lining fluid (MLF) using synthetic absorptive matrixes (SAM) (240). SAMs are directly touched upon the mucosal surface to absorb MLF and allow the measurement of mediators at significantly less diluted levels (see Methods section 12.7.3). While the released mediators provide information about the inflammatory state of the extracellular space, the investigation of expression patterns of the lung epithelial lining can inform about cellular activation and inflammation. Cytological bronchial brushings can be used to study the airway epithelial lining of smokers or patients with chronic airway diseases ex vivo (380, 381), but this approach has to date not been used to study host responses to Mtb infection. In combination with the novel application of SAMs, which allow the sampling of lining fluid from defined anatomical locations, these techniques may provide a new platform to investigate respiratory mucosal surfaces in response to Mtb-infection and dissect the natural history of tuberculosis in the human lungs. Taken together, since the human airway epithelial lining is an immunologically active surface, SAM- based sampling of mucosal lining fluid and recovery of the epithelial lining through brushings was used to sample and interrogate the upper and lower respiratory tract of TB exposed individuals to yield new insights into early host responses to Mtb-exposure.

15.2 Hypothesis

Secreted soluble mediators and transcriptomic signatures of the airway epithelial lining reflect different stages of the natural history of tuberculosis infection.

15.3 Aims

Aim 1: To identify markers of active TB compared to latent TB infection in the nasal lining fluid.

Aim 2: To identify correlates of exposure and correlates on infection through SAM-based sampling of the nasal and bronchial lining of healthy TB exposed volunteers.

Aim 3: To identify ex vivo bronchial epithelial transcriptomic signatures correlating with exposure to tuberculosis in healthy TB exposed volunteers.

130 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

15.4 Results

15.4.1 Study outline

To address the delineated aims, patients and healthy volunteers were recruited and samples recovered as depicted in the flowchart in Figure 15.2. Based on the one-airway hypothesis, which suggests that the upper and lower airways are immunologically linked (382, 383),mucosal lining fluid (MLF) was collected from the nasal mucosa from subjects with latent infection (LTBI) or active tuberculosis (ATB) as part of the nasal lining fluid (NLF) cohort (Table 15.1). Patients were classified as LTBI or ATB according to Dosanjh et al. (384): ATB patients comprised confirmed and highly probable ATB (Dosanjh category 1 and 2, respectively) and included pulmonary and extra-pulmonary disease. Latent infection was confirmed by positive IFNγ-release assay (IGRA) or tuberculin skin test (TST). Some patients had already commenced anti-TB treatment by the time they were recruited for this study. NLF was collected through SAM-based nasosorption from the anterior inferior turbinate (see Methods section 12.2.1) and Mesoscale discovery (MSD) immunoassays were used to measure selected soluble mediators. After confirmation of the feasibility, healthy TB-unexposed and TB exposed volunteers were recruited to undergo bronchoscopy for lower airway sampling as part of the Exposure cohort. Healthy TB exposed volunteers in sustained close contacts of patients with active culture-confirmed pulmonary TB were recruited within three months of the initial identification of the index case. Importantly, TB exposed healthy volunteers did not show any signs suggestive of active disease and had normal chest radiography. As a third group, patients undergoing diagnostic bronchoscopic procedures for suspected active pulmonary TB were recruited. NLF, BLF or bronchial brushings were collected for mediator or transcriptomic analysis, respectively.

131 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Figure 15.2: Study outline for the ex vivo analysis for the natural history of tuberculosis of the human airways. Flowchart depicting the recruitment, sampling and subsequent molecular measurements to address the delineated aims of this Results Chapter.

132 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection 15.4.2 Comparison of nasal mediator profiles in latent and active tuberculosis infection

Mucosal lining fluid (MLF) can easily be collected through synthetic absorptive matrix (SAM) strips in the nasal and bronchial airways. 36 mediators were measured in NLF samples collected as part of the NLF cohort (Figure 15.3 A). The standard V-plex cytokine panels were used to account for pro- inflammatory cytokines and chemoattractants known to be involved in immune responses to Mtb. The Vascular injury panel was selected to detect local levels of intercellular adhesion molecule 1 (ICAM1), vascular cell adhesion molecule 1 (VCAM1), C-reactive protein (CRP) and serum amyloid A (SAA), which are associated with tissue injury or inflammation (385–388). A matrix metalloproteinase (MMP) panel was included, since several MMPs have been shown to be activated in epithelial cells surrounding ATB lesions and may be critically involved in establishing Mtb infection (98, 103, 105).

When mediator concentrations were compared between LTBI and ATB subjects, significant differences were detected in C-C motif ligand (CCL)13, C-X-C motif ligand (CXCL) 10 and tumor necrosis factor (TNF) β (also known as lymphotoxin α) (Figure 15.3 B). IL2, which is important for lymphocyte function (389), showed a trend towards significance between LTBI and ATB. Since anti- TB treatment in both groups may have affected the mediator milieu of the mucosal lining, all patients on current treatment were removed from the analysis (Appendix Table 18.6). Levels of CCL13 (p = 0.024) and TNFβ (p = 0.018) remained significantly different between LTBI (n=18) and ATB (n=12) in this comparison. There were no differences between these mediators when untreated patients with active extrapulmonary TB (n = 9) were compared to patients with pulmonary involvement (n = 4) (Appendix Table 18.7). This finding suggested that these mediators may not reflect a nasal response specific to Mtb-driven disease in the respiratory tract. The nasal mucosa responds to general inflammation elicited by infections or chronic diseases and is constantly exposed to environmental factors, including tobacco smoke or air pollutants, which may determine mediator levels in the mucosa. Smoking status did not correlate with the mediator levels of TNFβ, CCL13 or CXCL10. To address, whether the observed mediator differences reflected a general inflammatory state or well-being of the patient, rather than active TB infection, all three mediators were correlated with the presence of symptoms, comprising cough, fever, night sweats and weight loss (Table 15.2). Interestingly, IL2 did not correlate with any of the confounders (data not shown). To assess whether well-being, measured by the presence of symptoms, was associated with mediator concentrations in the nasal lining, recruited patients were stratified according to the presence or absence of cough, fever, night sweats and/or weight loss. Nine mediators were

133 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection significantly increased in the presence of symptoms: CCL3, CCL13, CCL22, CXCL10, IFNγ, IL15, TNFβ, sICAM1 and sVCAM1 (Figure 15.4, Appendix Table 18.8).

This data has shown that detection of differences in soluble mediators in the respiratory mucosa at various stages of the natural history of TB is feasible, however may reflect the overall well-being of the patient rather than a specific signature of active TB. The comparison of nasal soluble mediators between patients with latent and active Mtb-infection confirmed that sampling of the mucosal lining fluid of the airways through SAM was an appropriate strategy to detect mediator signatures and a valid approach to address the overall goal of this study: the identification of correlates of exposure and correlates of infection.

Table 15.1: Demographic and clinical characteristics of the NLF cohort. ATB LTBI p-value n=27 n=20 Sex - female 12 12 0.292 Age - median, IQR 43, 34-51 34, 26-55.75 0.241 Ethnicity 0.502 White 3 6 Hispanic 1 0 Black 8 3 Middle Eastern 2 2 Asian 5 2 Indian Sub-continent 7 7 Mixed 1 0 Mtb-infection IGRA available / positive 22 / 21 20 / 19 TST available / positive 11 / 10 16 / 11 Pulmonary involvement 12 n/a Symptoms 3 23 <0.001 Cough/fever/nightsweats/weightloss (2/0/0/1) (16/9/12/17) On treatment 15 2 0.002 duration range in months 0-9 0-6 BCG - Y/N/unsure 18 / 6 / 3 9 / 4 / 7 0.132 Smoking - Y/N/Ex 6 / 19 / 2 2 / 18 / 0 0.217 Groups were compared by Kruskal-Wallis, Chi-squared or Fisher’s exact test as appropriate. ATB, active tuberculosis; LTBI, latent tuberculosis infection; IQR, interquartile range; IGRA, IFNγ-release assay (T-Spot used); TST, tuberculin skin test; BCG, BCG-vaccination; Y, Yes; N, No; n/a, not applicable. Significant differences at p<0.05 are highlighted bold.

134 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Figure 15.3: Soluble mediators in nasal lining fluid (NLF) during latent and active tuberculosis. (A) Soluble mediators were measured in NLF of individuals with LTBI (n=20) and ATB (n=27) by MSD immunoassays. For each mediator, median and interquartile range is shown after log2- transformation (see Methods section 12.7.6). (B) CCL13, CXCL10, IL2 and TNFβ are shown. Horizontal bars indicate the median. Lower (LD) and upper (UD) detection limits are indicated. Groups were compared by Mann-Whitney test. ϕ, three values are 0 and not shown; *, p<0.05; or exact p-value is given.

135 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Table 15.2: Correlation of TNFβ, CXCL10 and CCL13 with treatment, smoking and symptoms. TNFβ CXCL10 CCL13 Treatment duration (months) rho 0.048 0.201 0.411 p 0.751 0.176 0.004 Smoking status rho 0.069 0.082 0.121 p 0.645 0.586 0.417 Symptoms rho 0.347 0.442 0.366 p 0.017 0.002 0.011  Fever rho 0.187 0.195 0.34 p 0.207 0.188 0.019  Cough rho 0.315 0.449 0.403 p 0.031 0.002 0.005  Nightsweats rho 0.196 0.101 0.28 p 0.187 0.501 0.057  Weightloss rho 0.211 0.226 0.353 p 0.154 0.127 0.015 Mediator concentrations of all samples (n=47) were correlated by Spearman rank. rho, correlation coefficient; p, p-value. Significant correlations at p<0.05 are highlighted bold.

136 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Figure 15.4: Presence of symptoms is associated with differences in nasal mediators in Mtb- infected subjects. The NLF cohort was stratified according to the presence of symptoms in all recruited subjects. Mediator levels were compared between subjects with (Yes, n=26) and without (No, n=21) symptoms (cough OR fever OR night sweats OR weight loss) by MSD immunoassays. Horizontal bars indicate the median. Mann-Whitney test was used to compare groups. Lower (LD) and upper (UD) detection limits are indicated as additional ticks. LTBI, open circles; ATB, closed circles; ϕ, two values are 0 and not shown; *, p<0.05; **, p<0.01

137 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection 15.4.3 Studying the airway mucosal lining in TB exposed individuals

The first interaction with Mtb after inhalation occurs at the mucosal epithelial lining of the human respiratory tract. To identify potential markers of TB exposure or early Mtb-infection, soluble mediators were measured in NLF and BLF collected as part of the Exposure cohort. As described above, this cohort included TB unexposed and exposed healthy volunteers, termed unexposed healthy and TB exposed healthy, respectively. Additionally, samples from patients with suspected pulmonary ATB, termed suspected TB, were collected, to assess the effect of broader immune activation on the mucosal lining fluid. Recent infection with or clearance of Mtb may not be accompanied by symptomatic manifestation, which correlated strongly with cytokine levels identified in the NLF feasibility study and thus may not be detectable in the nasal mucosa. To overcome this limitation, BLF was additionally sampled through bronchosorption, when possible. The three groups of the Exposure cohort were demographically significantly different, especially with regards to ethnicity and age (Table 15.3), which can substantially affect the human immune system and epithelial function (62, 390, 391). Notably, patients who underwent diagnostic bronchoscopy for suspected active pulmonary TB were diagnosed with culture confirmed pulmonary TB as well as other inflammatory conditions. Based on detectability and significant differences in the NLF cohort, 27 soluble mediators were selected and measured in MLF sampled in the Exposure cohort (Figure 15.5 A). To identify correlates of exposure, the mediator profiles of the respective groups were compared. No significant differences were detected in NLF between the groups (Appendix Table 18.9). In BLF rather than NLF, significant differences were identified for six mediators, CCL11, CXCL10, IFNγ, IL6, IL15 and MMP1 (Figure 15.5 B and C, Appendix Table 18.10). These differences mainly manifested between unexposed healthy subjects and patients with suspected TB. No cytokine was found to be significantly different between all three groups or between unexposed and exposed healthy subjects.

As described earlier, exposure to aerosolised Mtb does not inevitably result in acquisition of infection. To interrogate this phenomenon immunologically, the healthy TB exposed group was studied more in depth. In fact, half of the exposed population did develop LTBI, measured by IGRA and/or TST, while the other half remained uninfected (Table 15.5). The distribution of age, gender and ethnicity was well balanced between infected and uninfected subjects, overcoming the limitations of the earlier comparison of healthy unexposed and exposed subjects. Within the TB exposed group, differences in MLF between infected and uninfected exposed subjects may serve as correlates of early infection, in the absence of hallmarks of active disease. When stratified by infection status, five mediators were differentially detected in either the nasal or the bronchial lining

138 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

(Figure 15.6 A). CCL4, serum amyloid A (SAA) and soluble vascular cell adhesion protein (sVCAM) 1 were increased in NLF and IL2 as well as MMP3 were increased in BLF of latently infected TB exposed subjects. Amongst these, CCL4 correlated well between the upper and lower airways (Figure 15.6 B, Appendix Table 18.11, Appendix Table 18.12).

More current smokers were present amongst the uninfected TB exposed subjects. To address, whether smoking confounded the results, all healthy TB exposed and unexposed subjects were stratified according to whether they never or currently smoked. Ex-smokers were excluded from the analysis. Current smokers did not have significantly different levels of any of the identified mediators (Figure 15.7 A). However, SAA and sVCAM1 concentrations in NLF correlated negatively with smoking pack/years, suggesting that increased exposure to tobacco may have a dampening effect on these mediators in the mucosal lining (Figure 15.7 B). These trends were not observed for CCL4, IL2 and MMP3, suggesting that these mediators reflect recent infection after exposure to Mtb rather than differences in smoking status.

The likelihood of infection with Mtb increases with the inhaled bacterial dose (161). As such, probably the most important factor influencing the outcome of infection after inhalation of Mtb in humans, is the intensity of the exposure. The intensity of exposure is dependent on the time and proximity to and the infectivity of the pulmonary ATB index case. In the infected TB exposed group, the ATB index case was more frequently a household or an intimate contact (Table 15.5), both of which increase the time and proximity spend with the index case. Additionally, there was a trend to increased hours spent with the index case per week in infected TB exposed subjects (Figure 15.8 A). To combine these variations in exposure into a single quantitative variable, a contact score was calculated which has previously been described by Shams and colleagues (see Methods section 12.1.4 and (55)). The contact score incorporates and weights, amongst other factors, the relationship between the exposed subject and the index case, the duration of the contact and the smear-positivity of the index case. Infected exposed individuals showed a trend towards increased contact scores (Figure 15.8 B). To identify, whether exposure and mediator concentrations showed similar trends, the contact scores were correlated with CCL4, IL2 and MMP3 levels in NLF and BLF. CCL4 and MMP3 correlated well with contact scores in NLF and BLF, respectively, while IL2 showed a trend to correlate with contact score in BLF (Figure 15.9 A and B). Interestingly, all three mediators correlated well with each other in BLF in all TB exposed healthy volunteers (Figure 15.9 C and D). Taken together, these findings suggest that CCL4, IL2 and MMP3 may in fact be correlates of infection in the human airways after sustained exposure to Mtb.

139 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Table 15.3: Demographic characteristics of the Exposure cohort (Aim 2). Unexposed TB exposed Suspected TB healthy healthy p-value (n=17ϕϕ) (n=12ϕ) (n=8) BLF available 10 9 4* Sex - female 5 5 4 0.681 Age – median, (IQR) 23, 23-24 27.5, 20.75-47 47.5, 26-57.75 0.041

Ethnicity 0.001 White 12 6 1 Hispanic 0 1 0 Black 0 5 2 Asian 3 0 4 Indian Sub-continent 2 0 1

Smoking - Y/N/Ex 3/14/0 6/4/2 3/5/0 0.046

TST tested / positive Not tested 12/7 5/3

IGRA tested 10 12 n/a (positive/negative/indeterminate) (0/10/0) (5/6/1)

Recent contact with a pulmonary ATB 0 12 n/a index case

BCG (Y/N/unsure) 15/1/1 10/1/1 5/1/2 0.563

Symptoms 0 1‡ 6 <0.001

Cough/fever/nightsweats/weightloss 0/0/0/0 0/0/0/1 6/1/3/3

Final diagnosis of suspected TB NLF only: patients:  Culture confirmed pulmonary ATB (2x)  Lung dominant connective tissue disease with a fibrosing organising pneumonia pattern  Pneumonia (past TB) NLF and BLF:  Culture confirmed pulmonary ATB (2x)  Choroidal lesions (past TB) BLF only:  no final diagnosis (past TB) Groups were compared by Kruskal-Wallis, Chi-squared or Fisher’s exact test as appropriate. BLF, bronchial lining fluid; IQR, interquartile range; TST, Tuberculin skin test; IGRA, Interferon-gamma release assay (T-Spot used); BCG, BCG-vaccination; Y, Yes; N, No; n/a, not applicable. Significant differences at p<0.05 are highlighted bold. ‡, individuals reported hayfever or mild childhood asthma; *, no NLF was available for one patient.

140 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Figure 15.5: Mediator levels in nasal and bronchial lining in the Exposure cohort. (A) Soluble mediators were measured in BLF of unexposed healthy (n=10), TB exposed healthy (n=9) and patients with suspected TB (n= 4). For each mediator, median and interquartile range is shown after log2-transformation (see Methods section 12.7.6). (B) and (C) CCL11, CXCL10, IFNγ, IL15, IL6 and MMP1 concentrations in NLF and BLF are shown. Horizontal bars indicate the median. Lower (LD) and upper (UD) detection limits are indicated as additional ticks. Groups were compared by Kruskal Wallis test. For (B), Dunn’s post-test was used to adjust for multiple comparisons. ϕ, one value is 0 and not shown. *, p<0.05; **, p<0.01

141 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Table 15.4: Demographic characteristics of TB exposed healthy subjects. Uninfected LTBI (infected) p-value n=6 n=6ϕ BLF available 5 4 Sex - female 3 2 0.5 Age - median, IQR 33.5, 24.25-45.75 25.5, 19.5-50.75 0.818 Ethnicity 1 White 3 3 Hispanic 0 1 Black 3 2 Smoking - Y/N/Ex 5/0/1 1/4/1 0.028 TST - positive/negative 2/4 5/1 0.121 Induration range in mm 0-15 0-66 IGRA - Positive/negative/indeterminate 0/5/1 5/1/0 0.015 BCG - Y/N/unsure 5/0/1 5/1/0 1 Symptoms 1 0 1 Cough/fever/nightsweats/weightloss 0/0/0/1 0/0/0/0

Mtb culture positive 0 0 CHX available / suggestive of TB 5/0 6/0 LTBI was defined according to the TST and IGRA results as described in Materials section 12.1.5. Groups were compared by Kruskal-Wallis, Chi-squared or Fisher’s exact test as appropriate. BLF, bronchial lining fluid; TST, Tuberculin skin test; IGRA, Interferon-gamma release assay (T-Spot used); IQR, interquartile range; BCG, BCG- vaccination; CHX, chest radiography; Y, Yes; N, No.. ϕ, one individual reported hayfever or mild childhood asthma.

142 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Figure 15.6: Differences in MLF mediator levels between infected and uninfected TB exposed healthy subjects. (A) CCL4, IL2, MMP3, SAA and sVCAM1 concentrations are shown in NLF and BLF of infected (LTBI +) or uninfected (LTBI -) TB exposed healthy subjects. (B) shows the correlation of each cytokine between NLF and BLF. Groups were compared by Mann-Whitney test. Spearman correlation was used to determine significance p and correlation coefficient rho. Lower detection (LD) limits are indicated as additional ticks. Horizontal bars indicate the median. *, p<0.05; **, p<0.01 or exact p- value are given.

143 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Figure 15.7: Differences in MLF mediator levels between all healthy subjects stratified by smoking status. (A) NLF levels of CCL4, SAA and sVCAM1 or BLF levels of IL2 and MMP3 of all healthy exposed and unexposed subjects are shown stratified by smoking status. Included were individuals which were reported current (NLF: n=9, BLF: n=6) or never (NLF: n=18, BLF: n=12) smokers. (B) Where available, mediator concentrations were correlated with tobacco pack/years amongst current smokers. Groups were compared by Mann-Whitney test. Spearman correlation was used to determine significance p and correlation coefficient rho. Lower detection (LD) limits are indicated as additional ticks. Horizontal bars indicate the median. *, p<0.05; or exact p-value are shown.

144 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Table 15.5: Exposure quality of TB exposed healthy subjects. Uninfected LTBI (infected) p-value (n=6) (n=6ϕ) BLF available 5 4 Time in months since index south help 2.5, 1-3 2, 1-2 0.394 - median, IQR Household contact 2 5 0.121 Intimate contact 0 2 0.227 Exposure time in hours/week – median, IQR 34.5, 12-36.25 42.5, 32.5-57.25 0.065 Contact score - median (IQR) 556, 417.25-1213 1529, 1013-2185 0.065 LTBI was defined according to the TST and IGRA results as described in Methods section 12.1.5. Groups were compared by Kruskal-Wallis, Chi-squared or Fisher’s exact test as appropriate. BLF, bronchial lining fluid; IQR, interquartile range; contact score was calculated as described in (55); ϕ, one individual reported hayfever or mild childhood asthma.

Figure 15.8: Contact time and contact scores of infected and uninfected TB exposed healthy subjects. (A) Contact time of infected (LTBI +) and uninfected (LTBI -) exposed subjects spent with the pulmonary ATB index case is shown in hours per week. (B) shows the contact scores calculated of infected and uninfected exposed subjects. Groups were compared by Mann-Whitney test. Exact p- values are given.

145 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Figure 15.9: CCL4, IL2 and MMP3 are affected by the extent of TB exposure. (A) Concentrations of CCL4, IL2 and MMP3 were correlated with contact scores of infected (closed circles) and uninfected (open circles) TB exposed subjects in NLF (A) and BLF (B). (C) and (D) show correlation coefficients rho (blue squares) and p-values (green squares) of all three mediators in NLF or BLF respectively. Spearman correlation was used to determine significance p and correlation coefficient rho. Horizontal bars indicate the median.

146 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection 15.4.4 Ex vivo inflammatory signatures in bronchial epithelial cells can be detected by RNA sequencing

Besides soluble mediators in the mucosal lining, the epithelial transcriptome may be altered by exposure to or early infection with Mtb. Bronchial brushings were collected from the right lower lobe of subjects recruited as part of the Exposure cohort to identify ex vivo bronchial epithelial transcriptomic signatures correlating with exposure to Mtb in healthy subjects. Where possible, an additional cytological brush was taken to assess the extent of immune cell contamination in the recovered epithelium. In all groups, bronchial epithelial cells dominated the samples with a median ≥ 90%. The largest contaminating subset was macrophages. Overall, there were no significant differences in the recovered cell types between groups (Figure 15.10). The transcriptome of the epithelial lining was interrogated through RNA Sequencing (RNASeq). After optimisations of RNA extraction and RNASeq library preparation (see Methods section 12.9.8 and 12.9.9), samples were sequenced, yielding 29.2 million reads on average. Alignment of sequence reads, quantification and normalisation were performed as described in Methods section 12.9.9 by Dr. Umar Niazi and Dr. Paul Golby. While the quality of the extracted RNA was not affected by TB exposure or suspected TB, the dataset was skewed demographically with regards to ethnicity and smoking status (Table 15.6). To identify transcriptomic correlates of exposure, i.e. genes which are differentially expressed between TB exposed and unexposed healthy subjects, these groups were compared. 68 genes were differentially expressed as part of this ‘exposure signature’ at an adjusted p-value<0.05 and separated the two groups in unsupervised hierarchical clustering (Figure 15.11). Pathway over- representation analysis (ORA) with InnateDB yielded no significantly enriched pathways which contained more than 5 identified genes, however gene ontology (GO) ORA revealed enrichment for the GO term oxidation-reduction process (GO: 0055114, adjusted p-value = 3.70E-04). Oxidoreductase activity has previously been associated with ex vivo gene expression signatures of airway epithelial cells derived from smokers (392). In the Exposure cohort, significantly more current smokers were present amongst the TB exposed subjects compared to unexposed healthy subjects. In fact, 26 genes (38%) of the ‘exposure signature’ have previously been reported to be differentially regulated in the airway epithelium of healthy smokers (Appendix Table 18.13). Even though a substantial proportion of these signatures overlapped, six of the ten most significantly differentially expressed genes associated with exposure, have not been reported to be de-regulated in smokers within the transcriptomic studies used for comparison (380, 381, 392–394): MIR6723, CCNJL, FAM177B, BPIFB2, SUCNR1 and ENTPD8 (Table 15.7). This suggested that, at least in part, the gene signature reflected exposure to Mtb.

147 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Inhalation of Mtb by TB exposed subjects, regardless of the infection outcome, likely results in local immune activation in the airways. Identification of genes associated with epithelial immune activation during exposure is possible through their comparison of the ‘exposure signature’ with the epithelial expression pattern during TB disease and other inflammatory conditions. To accomplish this, the transcriptome of suspected TB (including patients with final diagnoses of pulmonary ATB and pneumonia) in comparison to healthy unexposed volunteers was determined. 1485 genes were differentially expressed in the epithelial lining of patients with suspected TB (Figure 15.12, Appendix Table 18.14). The signature was enriched for pathways and GO terms associated with activation of the immune system, including interferon signalling (Figure 15.13), similar to the biological interpretation of the expression signature detected in PBECs cultured with Mtb-infected monocytes in vitro (see Results Chapter 2). Genes expressed in response to TB-exposure which are also expressed in response to immune-driven inflammation in vitro (PBEC responses to Mtb-infected monocytes) or ex vivo as part of the signature of ‘suspected TB’, may reflect a localised ongoing immune response to Mtb-exposure. To compare these three signatures, a Venn diagram between all was created (Figure 15.14 A). 16 common genes were identified between ‘exposure’ and ‘suspected TB’ and all but CEACAM5 and CEACAM6 were up- or down-regulated in the same direction as compared to healthy unexposed subjects (Table 15.8). While there was no overlap between the in vitro signature and the ‘exposure signature’, 95 genes were commonly expressed in PBECs in vitro as well as in suspected TB ex vivo, including CXCL10, IFIT1, IFI44 and IL8 (Appendix Table 18.15). Amongst these genes, enrichment of IFN signalling and immune activation was detected (Figure 15.14 B and C), suggesting that epithelial responses in vivo are in fact reflected in primary cell cultures in vitro.

148 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Figure 15.10: Cellular composition and RNA-quality of ex vivo bronchial brushings. Differential cell counts of brushings recovered from unexposed and TB exposed healthy individuals as well as patients with suspected TB. 5/12, 5/9 and 6/7 sequenced samples had available cell counts respectively. Groups were compared by Kruskal-Wallis and Dunn’s post-test. Horizontal lines indicate the median. BEC, bronchial epithelial cells; MΦ, macrophages; LYM, lymphocytes; NΦ, neutrophils; n.s., not significant.

149 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Table 15.6: Demographic characteristics of bronchial samples for RNA Sequencing (Exposure cohort - Aim 3). Unexposed TB exposed Suspected TB healthy healthy p-value (n=12ϕ) n=9 (n=7ϕ) RIN – median, IQR 7.1, 6.25-7.6 5.9, 5.05-7.3 6.2, 5.7-7.3 0.328 Sex - female 4 4 1 0.451 Age – median, IQR 24, 22.25-26 40, 23.5-49 28, 23-89 0.105

Ethnicity 0.021

White 10 3 2 Black 0 4 1 Asian 1 2 2 Indian Sub-continent 1 0 2 Smoking - Y/N/Ex 2/10/0 7/1/1 2/5/0 0.004

TST tested / positive Not tested 7/3 3/1

IGRA available 12 8 n/a Positive / negative / indeterminate 0/12/0 1/7/0 LTBI - Y/N/Unknown 0/12/0 2/6/1 n/a Recent contact with a pulmonary 0 9 n/a ATB patient BCG - Y/N/unsure 11/1/0 8/0/1 5/0/2 0.244 Symptoms 0 0 6 <0.001 Cough/fever/nightsweats/weightloss 0/0/0/0 0/0/0/0 6/4/2/3

Final diagnosis of suspected TB  Bronchiectasis patients:  Culture confirmed pulmonary ATB

 No final diagnosis (past TB)  Pneumonia (± past TB) (4x) Groups were compared by Kruskal-Wallis, Chi-squared or Fisher’s exact test as appropriate. RIN, RNA integrity number; IQR, interquartile range; TST, Tuberculin skin test; IGRA, Interferon-gamma release assay (T-Spot used); LTBI, latent tuberculosis infection; BCG, BCG-vaccination; Y, Yes; N, No; n/a, not applicable. Significant differences at p<0.05 are highlighted bold. ϕ, individuals reported hayfever or mild childhood asthma.

150 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Figure 15.11: Bronchial epithelial expression signature of TB exposure. Hierarchical clustering of all 68 differentially expressed genes in TB exposed healthy compared to unexposed subjects at a fold change of > │2│ and an adjusted p-value < 0.001 was performed using average linkage and Euclidean distance (expression range from low (green) to high (red)).

151 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Table 15.7: The most significantly differentially expressed genes in TB exposed healthy subjects and their involvement in smoking. Expression Gene Entrez Fold adjusted Gene name affected by symbol gene ID change p-value smoking

MIR6723 102465432 25.65 9.37E-08 microRNA 6723 n/r

CCNJL 79616 6.33 8.65E-06 cyclin J-like n/r

family with sequence similarity 177 member FAM177B 400823 18.24 8.65E-06 n/r B

BPIFB2 80341 19.77 1.38E-05 BPI fold containing family B member 2 n/r

SUCNR1 56670 0.15 3.01E-04 succinate receptor 1 n/r

calcium binding tyrosine-(Y)- (380, 381, CABYR 26256 9.20 5.36E-04 phosphorylation regulated 394)

CNGB1 1258 13.66 5.36E-04 cyclic nucleotide gated channel beta 1 (381, 394)

ELMOD1 55531 9.00 1.09E-03 ELMO/CED-12 domain containing 1 (394)

aldo-keto reductase family 1, member B10 (380, 381, AKR1B10 57016 11.94 1.31E-03 (aldose reductase) 392, 394) ectonucleoside triphosphate ENTPD8 377841 5.17 1.57E-03 n/r diphosphohydrolase 8 ‘Expression affected by smoking’ indicates if genes were associated with smoking in any of the referenced studies; n/r, not reported; Benjamini Hochberg-adjusted p-values of differentially expressed genes are shown.

152 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Figure 15.12: Bronchial epithelial expression signature of suspected TB. Hierarchical clustering of all 186 differentially expressed genes in suspected TB patients compared to healthy unexposed subjects at a fold change of > │2│ and adjusted p-value < 0.001 was performed using average linkage and Euclidean distance (expression range from low (green) to high (red)).

153 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Figure 15.13: Pathway enrichment analysis of the suspected TB expression signature. (A) Pathway and (B) gene ontology over-representation analysis was performed with InnateDB. The suspected TB expression signature comprised all significantly differentially expressed genes in suspected TB compared to unexposed healthy individuals at an adjusted p-value < 0.05.

154 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Figure 15.14: Comparison of in vitro and ex vivo bronchial epithelial expression signatures. (A) The Venn diagram shows the overlap between the in vitro PBEC expression signature (see section 14.4.3), the exposure signature (TB exposed vs unexposed healthy) and the suspected TB signature (Suspected TB vs unexposed healthy). The total gene number is shown. The overlap between the expression signatures are shown in Table 15.8 and Appendix Table 18.15. Pathway (B) and gene ontology (C) ORA was performed on the 95 common genes between the in vitro and ex vivo signatures with InnateDB.

155 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

Table 15.8: Differentially expressed genes in TB exposed subjects and suspected TB patients. TB exposed vs suspected TB vs unexposed unexposed Gene Entrez Gene name healthy healthy symbol gene ID Fold adjusted Fold adjusted change p-value change p-value

AHRR 57491 aryl-hydrocarbon receptor repressor 7.32 5.25E-03 2.64 1.40E-03

CA12 771 carbonic anhydrase XII 5.39 2.15E-02 2.19 3.01E-02

CCNJL 79616 cyclin J-like 6.33 8.65E-06 1.75 1.64E-02 carcinoembryonic antigen-related cell CEACAM5 1048 6.92 3.36E-02 0.76 4.50E-02 adhesion molecule 5 carcinoembryonic antigen-related cell CEACAM6 4680 adhesion molecule 6 (non-specific 3.44 4.85E-02 0.53 3.74E-02 cross reacting antigen) DnaJ heat shock protein family DNAJC12 56521 6.46 2.32E-02 2.55 3.60E-03 (Hsp40) member C12 ELMOD1 55531 ELMO/CED-12 domain containing 1 9.00 1.09E-03 2.23 1.16E-02 ectonucleoside triphosphate ENTPD4 9583 1.60 2.98E-02 1.23 2.42E-02 diphosphohydrolase 4 family with sequence similarity 177 FAM177B 400823 18.24 8.65E-06 2.43 8.85E-03 member B lung cancer associated transcript 1 LUCAT1 100505994 6.54 2.84E-02 2.26 1.75E-02 (non-protein coding) neural proliferation, differentiation NPDC1 56654 2.49 9.60E-03 1.43 2.80E-02 and control, 1 PGM3 5238 phosphoglucomutase 3 1.99 1.16E-02 1.40 5.56E-03

PIP 5304 prolactin-induced protein 0.26 2.15E-02 0.35 5.14E-06

PTGER4 5734 prostaglandin E receptor 4 0.50 2.15E-02 0.77 4.45E-02

PYCR1 5831 pyrroline-5-carboxylate reductase 1 4.13 3.90E-02 1.77 4.45E-02 solute carrier family 7 (anionic amino SLC7A11 23657 acid transporter light chain, xc- 10.04 3.92E-03 2.22 2.63E-02 system), member 11 Shown are all genes which are differentially expressed in the ‘exposure signature’ and signature of suspected TB. Benjamini Hochberg-adjusted p-values of differentially expressed genes are shown.

156 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection 15.5 Discussion

Interrogations of the human immune responses at the surface of the respiratory tract during the natural history of TB will improve the understanding of host-pathogen interactions at the site of infection. In this pilot study, it was investigated whether differences in the mucosal epithelial lining of the upper and lower airways, detected through the application of novel sampling strategies, reflected the stages of Mtb-infection. The main aim of this study was to identify immune activation of the respiratory mucosal lining in the context of exposure to Mtb.

Since the human nasal mucosa has not been studied in TB before, it was first addressed whether soluble mediator profiles in the nasal lining fluid distinguished LTBI from ATB, two clinically well- defined groups. Differences between LTBI and ATB correlated strongly with the presence of symptoms, including coughing, which has been reported to increase sputum levels of pro- inflammatory mediators (395). Coughing and the resulting mucosal irritation likely increased release of mediators involved in endothelial activation and tissue injury, sICAM1 and sVCAM1, which have been shown to increase pro-inflammatory AMΦ-responses in vitro or are elevated during acute lung injury in vivo, respectively (396, 397). CXCL10 and other chemokines were increased, which are inducible by pro-inflammatory mediators, including IFNγ. This data demonstrates for the first time, that TB-mediated inflammation can activate the epithelial lining and induce measurable changes in the nasal mucosa. A caveat to this finding is that these differences represent the general well-being of the patient rather than Mtb-specific responses and whether these differences are driven by inflammation in the lower airways or by increased direct stimulation of the nasal mucosa will need to be investigated in future. It is of interest, that no differences in MMP1 or MMP9 were observed in the nose, both of which are known to be upregulated in human granulomas and have been reported to be released by human epithelial cells during Mtb-infection (103, 105). This may be a reflection of the disparity between the upper and lower airways, since both MMPs were elevated in the bronchi of patients with suspected TB. Regardless of whether they reflect infection-induced signals or underlying tissue injury, the presence of discernable responses, make the nasal mucosa a potential interface for the study of human immune responses to Mtb-antigens. Bronchial-segmental challenges have previously been used to mimic airway responses during Mtb-infection and interrogate cellular influx and phenotype. These studies are costly, though, and difficult to perform in large cohorts (160, 398). Nasal challenge models are already in use to study innate immune responses in the human respiratory tract (399) and it is feasible that local challenge with either PPD or Mtb-specific antigens may elicit immune responses similar to those occurring in the lower airways. This could yield new insights into Mtb-driven lung inflammation.

157 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection

To address the question of whether exposure to active pulmonary TB is discernable in the respiratory mucosal lining, which has not previously been attempted, the Exposure cohort was recruited. This cohort included individuals with close sustained exposure to ATB index cases, healthy TB unexposed subjects and patients with suspected pulmonary ATB. To facilitate the detection of immune activation at the site of infection in the lower airways, bronchial lining fluid was collected in addition to NLF during bronchoscopies. When the three subject groups were compared, differences were only detectable between patients with suspected TB and healthy unexposed or TB exposed subjects and no detectable differences were observed between unexposed healthy and TB exposed healthy subjects in nasal or bronchial lining fluid. The lack of differences may have, in part, been due to the imbalanced demographic characteristics of the unexposed and exposed groups. To identify correlates of exposure, this question will need to be addressed as part of a more balanced cohort in the future.

When the TB exposed subjects were stratified by Mtb-infection, LTBI was associated with elevated nasal levels of CCL4, SAA and sVCAM1 and elevated bronchial levels of IL2 and MMP3, suggesting these cytokines may act as markers of early Mtb-infection. Smoking strongly affects the airway mucosa and its immune responses. As such, tobacco smoke can have a dampening effect on the responses of lung-resident immune cells and epithelia ex vivo and in vitro (400–402). Even though none of the five identified markers were significantly affected by smoking status of the healthy subjects, SAA and sVCAM1, correlated negatively with pack/years, suggesting that increased tobacco smoke exposure dampened the release of these mediators. CCL4, IL2 and MMP3, on the other hand, did not correlate with pack/years. Additionally, it has previously been shown that CCL4-levels in bronchoalveolar lavage (BAL) are not affected by smoking (403). Similarly, sputum IL2 and CCL4 levels in asthmatics are not significantly different between smokers and non-smokers (404). These findings suggest that CCL4, IL2 and MMP3 may serve as correlates of early infection, in the absence of clinically manifested disease after exposure to Mtb. All three mediators correlated significantly with each other and may reflect an infection-induced network of immune activation. While there are no reported interactions between MMP3 (also known as stromelysin-1) and CCL4 or IL2, it can be induced by a pro-inflammatory environment through mediators such as TNF and IL1β (405). Additionally, MMP3 has proteolytic activity which can activate MMP1 and MMP9 (406, 407) and may help to establish Mtb infection in the human host. CCL4 can be secreted by Mtb-infected AMΦs (408) and is found to be elevated in BAL recovered from active pulmonary TB and chronic bronchitis patients compared to healthy volunteers (403, 409). It is also expressed by primary human airway epithelial cells in response to dsRNA stimulation or infection with influenza virus A (410, 411). Notably, CCL4 interacts with the cell surface receptor CCR5 found on T cells and macrophages (412)

158 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection and can be released during inflammation to attract T cells from the draining lymph nodes (413, 414). CCR5 has been described to act as a lung-homing marker and shown to be increased on BAL-derived T cells (415, 416). CCL4 may thus help to mediate attraction of lymphocyte subsets, which in turn would explain the elevated levels of IL2 in BLF. IL2 is secreted by activated T cells and innate lymphocytes (417, 418) and is involved in the maintenance of protective immune responses as well as immune tolerance (419). In the non-human primate model of tuberculosis, IL2 expressing T cells are found during latent and active infection in granulomatous lesions (95). The absence of detectable levels of IL2 in BLF of all but one uninfected TB exposed subjects, suggests that IL2 may be associated with an ongoing mucosal adaptive response during Mtb-infection in the absence of signs of disease and aid the local innate control of Mtb. CD8 T cells have been reported to support Mtb-control by AMΦs of TB exposed household contacts as opposed to community controls in vitro (89). A similar finding has been described for CD4 T cells. Silver et al found, that CD4 T cells from TST- positive subjects improved monocyte growth control of Mtb in vitro (88). IL2 levels are elevated in BAL during acute pneumonia and Mycoplasma pneumonia infection (420, 421), but have not been reported to be elevated in BAL during pulmonary ATB disease in comparison to healthy controls (378, 422). Whether this implies that IL2 is involved predominantly in early immune activation, after acquisition of infection, rather than during clinical disease, remains to be confirmed. While IL2, CCL4 and MMP3 are potential markers of early infection, CCL4 and MMP3 additionally correlated well with the contact score of TB exposed healthy subjects and may serve as quantitative markers of exposure. Even though the UK is a non-endemic country with regards to TB, it cannot be excluded that the infected TB exposed subjects may have been infected before the recent exposure occurred. Future studies, comparing recently and remotely acquired latent Mtb infection, will confirm whether the identified mediators are markers of early infection.

Besides sampling of the mucosal lining fluid, recovery and processing of bronchial epithelial cells for ex vivo analysis by RNASeq was optimised for this study. This methodology was then applied to samples collected as part of the Exposure cohort. The transcriptome of the epithelial lining was interrogated with RNASeq, a next generation sequencing technique which allows in depth interrogation of the global transcriptome at a larger dynamic range than microarrays and without the limitation by transcript-specific probesets (423). Through the comparison of healthy TB exposed and unexposed subjects, a transcriptomic signature of exposure was determined. This expression signature did not overlap with the gene set identified to be differentially expressed in PBECs in vitro during exposure to Mtb-infected monocytes. However, since the majority of TB exposed subjects within the transcriptomic dataset remained uninfected, no conventional immune activation may have occurred at the mucosal surface. Even though a third of the detected ‘exposure signature’ has

159 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection been previously described to be affected by smoking, it is conceivable, that the remaining signature in fact reflected responses of the airway lining to TB exposure. Amongst the most significantly differentially expressed genes was the bactericidal/permeability-increasing protein (BPI)-family member BPIFB2. First identified to be expressed in hypertrophic tonsils (424), it is a homologue of BPI, which is an antimicrobial effector (425). The function of BPIFB2 is currently not known. Based on its structure, it has been suggested to be involved in the innate immune response as a binding protein for small inflammatory host- or pathogen-derived molecules (424). This makes it an interesting candidate gene for further investigations.

As only two TB exposed subjects of the transcriptomic cohort were Mtb-infected, a subgroup analysis comparable to the MLF-analysis was not possible. As a more pronounced mediator signature was detected in MLF of infected subjects, transcriptomic analysis of a larger cohort of infected TB exposed subjects may yield similar insights as the MLF-interrogation. Comparison of suspected TB patients with healthy unexposed subjects revealed that immune activation is reflected in the airway epithelial lining during inflammatory conditions, including active TB and pneumonia, confirming the feasibility of this sampling approach. Gene expression in patients with suspected TB was enriched for inflammatory pathways and interferon signalling. The enrichment for IFN- associated genes in epithelial lining of suspected TB patients reflected the primary bronchial epithelial responses observed in vitro as well as expression signatures observed in resected tuberculous granulomas (91).

Future studies will aim to recruit a larger cohort of matched TB exposed and unexposed healthy subjects. This would overcome the limitations of the current study, which was insufficiently demographically balanced. Additionally, recruitment of TB exposed subjects and their respiratory sampling before IGRA and TST-conversion, could inform about immune mechanisms which are independent of adaptive immune priming. This could elucidate innate immune responses as well as and inform intervention strategies which may be mediated through appropriate immune priming after exposure to Mtb.

Taken together, the study presents the first approach to better define the immunological events occurring early after exposure to and infection with Mtb in the human respiratory tract ex vivo. The data support that different stages of the natural history of tuberculosis infection are reflected at mucosal lining of the airway mucosa. Furthermore, this study showed that sampling of the epithelial lining through SAM and cytological brushings allow the interrogation of the earliest interactions between Mtb and the human host, which occur in the respiratory tract after inhalation of the bacteria, ex vivo. The combination of SAM strips with highly sensitive immunoassays allowed the

160 Results Chapter 3: Airway mucosal responses across different stages in the natural history of tuberculosis infection detection of a broad range of cytokines and future studies will include non-protein mediators such as prostaglandins and vitamin D metabolites, which are thought to beneficial for the host response against Mtb (141, 147). This work furthermore confirms that epithelial responses during Mtb- infection and inflammatory diseases are detectable at the transcriptomic level in the bronchial lining, which can be exploited in the future.

Despite the limitations of the study cohort, this is the first report of immune activation in the lower respiratory tract following Mtb-exposure in the absence of underlying TB disease, supporting the hypothesis that secreted soluble mediators and transcriptomic signatures of the airway epithelial lining can reflect different stages of the natural history of tuberculosis infection. This provides the platform and rationale to study a larger cohort of matched individuals with different stages of Mtb- infection and would ultimately overcome the shortcomings of animal studies of the natural history of tuberculosis, especially with regards to exposure to Mtb.

161 Concluding remarks

16 Concluding remarks

16.1 A brief summary of the work presented

This thesis set out to interrogate the involvement of primary human airway epithelial cells in lung immune responses to Mycobacterium tuberculosis (Mtb) infection. To address this, primary bronchial epithelial cells (PBECs) and the human airway epithelial lining were investigated in vitro and ex vivo, respectively. The airway epithelium is the largest interface between the environment and the human body and even though leukocytes are found in the airway lining, epithelial cells respond directly to invading agents and infections (164).

PBECs were a poor target of direct infection with small doses of Mtb. However, in response to high bacterial burden, they released cytokines in an NADPH-oxidase dependent manner, likely induced by mycobacterial virulence factors. This mediator release coincided with increased cell death in the epithelial monolayer. In contrast, PBECs were potent responders to Mtb-driven inflammation initiated by macrophages and monocytes. Type I IFN signalling and IL1β were crucially involved in the epithelial activation, which enhanced the inflammatory environment through provision of antimicrobial factors as well as increased cellular influx to the site of infection.

Through a novel strategy, the human airway mucosal epithelial lining was successfully sampled ex vivo for interrogation of transcriptomic profiles and soluble mediators. The mucosal lining was confirmed to be a rich source for chemotactic and inflammatory factors and reflected the disease state of the host. Interestingly, the study of recently infected TB exposed individuals suggested ongoing immune activation in the human respiratory tract in the absence of clinical signs of disease. Additionally, during suspected pulmonary tuberculosis, several genes, which had been found to be expressed in a type I IFN and IL1β-dependent manner in vitro, were significantly increased (Figure 16.1).

Based on these findings, airway epithelial cells may contribute to the host response against Mtb- infection during several stages of the natural history of tuberculosis infection. Early after Mtb- inhalation and infection of alveolar macrophages in the lower airways, macrophage-derived cytokines may activate surrounding epithelial cells. Resulting in the release of antimicrobial peptides, acting against free Mtb, and chemotactic mediators, recruiting further leukocyte subsets, this may support the local immune response to infection (Figure 16.2 A). During active pulmonary TB, when the host cannot contain Mtb growth in granulomas, leukocytes and pro-inflammatory cytokines alongside replicating Mtb enter the airspaces. Host mediators activate epithelial cells in a similar

162 Concluding remarks manner as after early Mtb-infection, i.e. inducing AMP-release against free Mtb as well as recruiting further leukocytes, foremost neutrophils. The accumulation of large numbers of free Mtb may also directly induce epithelial damage and accelerated neutrophil recruitment, which results in tissue destruction and increased pathology (Figure 16.2 B). Overall, the presented findings confirmed the initial hypothesis that the human airway epithelium responds to Mtb and Mtb-driven inflammation and has provided novel insights into the role of the respiratory epithelial lining during Mtb infection.

163 Concluding remarks

Figure 16.1: Primary human bronchial epithelial cells during tuberculosis infection. In vitro, PBECs are only scarcely permissive to Mtb infection, however when exposed to high bacterial burden, they release cytokines in an NADPH-oxidase (NOX) dependent manner, which coincides with cell death. During Mtb-driven myeloid inflammation, PBECs are activated by type I IFN signalling and IL1β. This enhances the inflammatory environment through AMPs and increased leukocyte influx. Ex vivo, the respiratory mucosal lining and the epithelial transcriptome can reflect the disease state of the host and shows ongoing low level immune activation in recently infected TB exposed individuals.

164 Concluding remarks

Figure 16.2: Schematic of the airway epithelial contribution to the host response against Mtb infection across the natural history of TB. (A) After inhalation of Mtb, alveolar macrophages are infected in the lower airways and secrete cytokines which activate surrounding epithelial cells to release antimicrobial peptides (AMP) and chemokines. This helps to control free Mtb and orchestrate leukocyte influx to the site of infection, respectively. (B) During active TB, when the host cannot contain Mtb infection inside granulomas, free Mtb as well as infiltrating leukocytes create a pro-inflammatory environment in the airways. While cytokines may still induce epithelial AMPs against free replicating Mtb, the influx of neutrophils towards the pro-inflammatory environment and epithelial cell death induced by the large burden of Mtb may further increase tissue damage.

165 Concluding remarks

16.2 Perspectives

An important finding of this study was the low permissiveness of epithelial cells to mycobacteria. This may be desired by the pathogen as it is known that mycobacteria strategically “cloak” certain PAMPs in their cell wall, which has been shown to facilitate the recruitment of permissive myeloid cells (123). The limited susceptibility of PBECs to infection may also reflect an absence of responsiveness to non-pathogenic environmental mycobacteria to prevent excessive immune responses in the lungs, as they display common surface antigens to pathogenic strains. While the limited interaction and invasion of epithelium may allow Mtb to ensure uptake by surface-patrolling macrophages, the identification of mycobacterial DNA in alveolar epithelial cells previously led to the hypothesis that mycobacteria persist within epithelial cells during latent infection to evade immune detection (31). In contrast to intestinal epithelial lining, with a quick turnover, respiratory epithelium has been shown to have a half-life of up to 1.5 years in mice (426). Infiltration of epithelial cells by Mtb in small numbers, which are not cytotoxic for the host cell, may provide a shielded niche for the pathogen in which bacteria are not detected by macrophages and can lie dormant.

Amongst the main findings of this study were inflammation induced activation of antimicrobial responses and increased neutrophil recruitment in Mtb infection. Both may shape the outcome of exposure to Mtb and could be targeted therapeutically in future. With regards to the antimicrobial environment in the airways, the epithelium complements the innate immune response to invading pathogens through the release of distinct antimicrobial peptides (AMPs), which are not released by local leukocytes. Generally, AMPs have a broad range activity against microbial pathogens, independent of any acquired antibiotic resistance. Especially in the context of Mtb-infection, for which the treatment is already strenuous for the patient, drug-resistance complicates the control of active disease. By extension, this may lead to increased dissemination of infection. In the present study, PBECs were identified to express several AMP-encoding genes in response to pro- inflammatory cytokines released during myeloid Mtb-infection. Clinical Mtb-strains vary with regard to the pro-inflammatory cytokine profiles they induce, which may be part of an evasion strategy to avoid the antimicrobial environment (241, 361). While hBD2 has been shown to be antimycobacterial (323), this study revealed that there are epithelial AMPs with previously unknown antimycobacterial activity. These included psoriasin, which is part of the S100A-family of proteins. These AMPs were not measured at the protein level in the human airways and they were not detected to be differentially expressed as part of the’exposure signature’ or the signature of suspected TB. Thus, their presence remains to be verified in Mtb-exposed individuals as well as in a cohort of well-defined pulmonary TB patients. However, hBD2 protein is detectable in BAL fluid from

166 Concluding remarks patients with cystic fibrosis (187) as well as in children with pulmonary TB (427) and psoriasin can be detected in nasal lavage in healthy volunteers which is increased in inflammation (428) and is expressed in bronchial epithelial biopsies (360). Interestingly, several defensins, including hBD2, are encoded in a cluster on chromosome 8 and can show variations in their copy numbers, which have been associated with their expression levels (429). Increased genomic copy numbers of β-defensins are associated with psoriasis, and inflammatory skin conditions (430), while lower copy numbers of the DEFB4 gene are associated with Crohn’s disease and diminished DEFB4 expression in inflamed mucosal tissue (431). These studies suggest that hBD2 can influence the inflammatory response and the association of AMP copy numbers with susceptibility to other infections has been suggested previously (432), however no studies have investigated their association with susceptibility to tuberculosis in humans.

Psoriasin and koebnerisin were originally identified to be part of the antimicrobial skin response. To identify and interrogate further potential AMPs, a skin-based model of mycobacterial inflammation may be an interesting approach to study epithelial responses. Other pathogenic mycobacterial strains, including M. leprae and M. marinum cause granulomatous lesions in the skin, which are easily accessible. These lesions may be a viable source of ex vivo samples to interrogate epithelial cells. Additionally, a more controllable approach has been applied recently to study tissue-based responses to mycobacterial stimulation. A TST-based model has been used to identify TB immune signatures. Tomlinson and colleagues identified Th1- and macrophage-associated immune signatures in tuberculin skin test (TST) biopsies derived from Mtb-infected individuals (433). Both approaches may be useful to identify epithelial contributions, as well as leukocyte activation, to human immune responses in tuberculosis.

Interestingly, during Mtb-driven inflammation in vitro as well as suspected TB ex vivo, a type I IFN signature was detected in airway epithelium. This expression pattern coincided with increased neutrophil attraction in vitro. The role of neutrophils and type I IFNs is closely linked during active tuberculosis in mouse models and humans. Abrogation of type I IFN signalling in mice reduces the influx of neutrophils to the site of infection and the peripheral blood IFN-inducible expression signature that is found in severe TB disease is associated with neutrophils (18, 112). Even though expression patterns, in the airways and periphery show overlap, there may be differences between the modes of induction at each tissue site. While the in vitro data suggests that PBECs may be activated by interferons released during myeloid infection with Mtb, the peripheral signature may be a damage-associated response. For example, during autoimmune diseases such as systemic lupus erythematosus (SLE) and arthritis, NETs released from activated neutrophils can drive interferon

167 Concluding remarks stimulated gene (ISG) expression through the activation of dsDNA sensors (305). Whether this scenario occurs in tuberculosis, remains to be verified. The activation of similar pathways through discrete mechanisms may also reflect different roles of these pathways at the various stages of the natural history of tuberculosis.

Interferon-driven signatures, similar to those observed in vitro, were detected in the airway lining of patients with suspected TB, which included final diagnoses of active tuberculosis and pneumonia. Type I IFNs are indispensable in the immune response against viral infections, and it would be interesting to investigate, whether the increased expression of antiviral components may prevent viral infections during Mtb-driven inflammation in the lungs. In a report published during the 1918 influenza pandemic, the suggestion was made, that pulmonary tuberculosis may have protective effects against influenza infection (434). However, this observation may simply have been due to the improved hygiene and care provided for pulmonary TB patients. Other studies have associate coinfection with influenza during active tuberculosis with increased mortality (435) and in mice, influenza infection can exacerbate TB disease (366).

16.3 Limitations of the present study

To model inflammatory responses in the human body, cell lines are frequently used as proxies for primary cells. While they are available for most cell types and tissues, they are often derived from a single donor and have been cultured in vitro for decades in the laboratory environment. Hence, they may not reflect the responsiveness of their primary counterparts (202). Recovery of primary cells from tissues allows the interrogation of cellular responses ex vivo which more likely reflect the responses within an organism. Due to recent advances in cell culture technology it has become easier to isolate and propagate primary cells derived from human organs, including the lungs, in vitro.

Here, primary bronchial epithelial cells were expanded and interrogated. Through the use of multiple donors, the presented data reflects true biological variations occurring in the population. One limitation of this study is the use of submerged epithelial cultures. In this state, cells retain an undifferentiated phenotype. The responses measured in this setting may thus differ from fully differentiated airway epithelium. To obtain stratified epithelial layers in vitro, airway epithelial cells can be differentiated at an air-liquid interface (ALI). Since only limited literature was available on the interaction of Mtb with primary human airway epithelial cells, the present work focussed on submerged undifferentiated cells. However, future studies should consider the application of fully stratified polarised epithelial layers.

168 Concluding remarks

The absence of a pronounced response of PBECs to direct exposure to Mtb may have been a consequence of their undifferentiated state and ALI-cultures may have shown different activation patterns. The transcriptional profiles of submerged and differentiated PBECs revealed differences in immune-responses associated pathways (436). However, it has previously been reported that infection with human rhinovirus (HRV) or exposure to air pollution particles induced stronger responses in submerged epithelial compared to well-differentiated cultures (437, 438). Additionally, the limited infectivity of PBECs in vitro mimicked observations from murine studies in vivo, where only few lung epithelial cells were infected after intra tracheal instillation of Mtb (230). Taken together, this suggests that the non-responsiveness of PBECs to Mtb was not an artefact of submerged culture.

The main focus of the present study was the bronchial epithelium. However, anatomical locations of epithelial cells in the airways may affect their role in the lung immune response Trachea, bronchi and bronchioles are lined by ciliated cells and several secretory cell subsets, allowing the removal of particles as well as release of host defense mediators and mucus, while alveolar epithelial cells regulate gas exchange in the alveoli. Differences in the upper and lower airways can result in divergent responses to pro-inflammatory mediators (202, 349). It is assumed that infection with Mtb occurs in the alveoli and thus in the context of alveolar epithelial cells rather than ciliated bronchial epithelium. To garner information about the lower airways of recruited volunteers, healthy, infected or diseased, cells and lining fluid may be collected through improved sampling strategies based on the present study. The use of thinner endoscopes in combination with 2mm cytological brushes allows the recovery of cells from the 12th order bronchi (439). In combination with new bronchosorption devices, developed with smaller tube diameters (Hunt Developments), this would allow mediator and cellular sampling of the lower airways. However, this strategy would still fail to recover epithelium of the terminal airways. The alveolar epithelium is lined with alveolar epithelial type I and type II cells (ATI and ATII, respectively). While ATI cells cover 95% of the alveolar surface area and are crucial for gas exchange, ATII cells are required to lower the surface tension in the alveoli through the release of surfactant proteins (SP). SPs can also opsonise pathogens and SP-A and D allow adhesion of Mtb to airway epithelium under shear conditions in vitro (233). The direct interactions of primary human ATII cells may thus yield different results than the interaction of Mtb with PBECs. Small airway epithelial cells are available commercially from the 1mm terminal bronchioles and contain alveolar epithelial cells. To recover pure cultures of alveolar epithelial cells, however, these need to be recovered from lung resections or organ donations and are phenotypically difficult to maintain in culture (440, 441).

169 Concluding remarks

Despite the anatomical limitations of PBECs, they remain a proxy for the small airway response to Mtb infection. Additionally, they provide insights into the bronchial involvement during TB. Especially during active pulmonary disease, free Mtb as well as an abundance of cytokines are present in the airways (5, 142, 378). This suggests that both, direct interaction with mycobacteria or their virulence factors and activation by ongoing inflammation, impact on the bronchial epithelium. This idea was further supported by the detectable inflammation in patients with suspected TB in the bronchi as well as low level immune activation after exposure to Mtb. Bronchial epithelial cells may even be in contact with cough droplets generated by pulmonary TB patients. It is generally assumed that infectious particles containing Mtb need to be of a diameter less than 5μm, as larger droplets may not access the alveoli and remain in the upper airways or bronchi. However, Mtb can be found in aerosols > 7μm and thus may initiate a bronchial response (442).

Besides the anatomical location of the sampling site, the ex vivo study of the human respiratory tract only allowed limited insights into the epithelial responses to Mtb-infection. Due to the unbalanced design of the presented pilot study, it is difficult to draw definite conclusions from the data. However overall, this study has shown that comprehensive sampling of the human respiratory tract is feasible and that biologically meaningful pathways can be identified. To discern true differences at non-pathological stages of TB infection, a larger cohort of well-defined volunteers will be required. Dysfunctional innate immune responses of the airway epithelium are detectable in vitro in epithelial cells from asthma (182) and COPD patients (443). Similarly, future studies of inherent differences in airway epithelium may also reveal underlying genetic or epigenetic differences favouring Mtb- infection. The development of advanced patient-derived epithelial culture systems will be a valuable tool to study pathogenesis and therapeutic approaches for TB. Even though exposure (and transmission) are best studied in humans, it has become increasingly clear that the non-human primate model of TB recapitulates the spectrum of human disease well (17) and thus may allow the generation of similar insights into the early events of Mtb-infection as sampling of the human airways.

16.4 Future directions

This thesis work has shown that there is a role for the bronchial epithelium in the human lung immune response to Mtb-infection. Future work should focus on interrogating the identified pathways further. While the primary focus with regards to cellular cross-talk was contact independent interactions through soluble mediators, direct interactions between cell types are an important aspect of mucosal immune responses. Epithelial cells can regulate alveolar macrophage

170 Concluding remarks activation through cell surface receptor interactions, such as CD200-CD200R (117) and have not been interrogated in the context of Mtb-infection. These further studies should also include the investigation of interactions between primary epithelial cells and dendritic cells (DC). Similar to the macrophage-epithelial cross-talk, DCs may contribute to epithelial activation. They are located beneath the epithelial layer and sample antigens in the airway lining (444). Thus, DCs may interact with Mtb which is not internalised by epithelial cells of the the bronchial lining.

Further work should also include more comprehensive approaches to interrogate lung immune responses in vitro. A recently emerging alternative to mouse models and tissue resections to study the organ-level microenvironment in vitro has been the “lung-on-a-chip”-model (445, 446). Through microfluidic chambers, the structure, functions and immunological properties of the alveolar and bronchial lung lining can be mimicked in real-time. This model may provide more complex insights into the interactions between host cells and Mtb and should be considered for investigations in future.

In summary, the findings presented in this thesis showed that bronchial epithelial cells may contribute to the immunological environment as sentinels of inflammation with the ability to modulate leukocyte influx and local control of bacterial replication. Harnessing epithelial activation during early host-pathogen interactions may thus be a viable strategy to support early protective immune responses to Mtb in the human lungs.

171 References

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204 Appendices

18 Appendices

18.1 Appendix 1: Data

Appendix Table 18.1: Mtb-induced significantly differentially expressed genes in PBEC-myeloid co-culture. Gene Symbol RefSeq Affymetrix Probe ID Fold q-value Gene Name change (%) ABCA12 NM_173076 TC02002746.hg.1 1.289 2.69 ATP-binding cassette, sub-family A (ABC1), member 12 ACE2 NM_021804 TC0X000878.hg.1 1.087 3.15 angiotensin I converting enzyme (peptidyl-dipeptidase A) 2 ADAM19 NM_033274 TC05001986.hg.1 1.181 1.91 ADAM metallopeptidase domain 19 (meltrin beta) ADAM28 NM_014265 TC08000190.hg.1 1.402 0.00 ADAM metallopeptidase domain 28 ADAM8 NM_001109 TC10001783.hg.1 1.171 0.78 ADAM metallopeptidase domain 8 AKAP12 NM_005100 TC06001100.hg.1 1.116 3.55 A kinase (PRKA) anchor protein 12 ALAS1 NM_000688 TC03000329.hg.1 1.231 0.00 aminolevulinate, delta-, synthase 1 ALDH1A3 NM_000693 TC15000971.hg.1 1.204 0.00 aldehyde dehydrogenase 1 family, member A3 ALOX12B NM_001139 TC17001100.hg.1 1.218 3.35 arachidonate 12-lipoxygenase, 12R type AMPD3 NM_001172431 TC11000184.hg.1 1.107 4.10 adenosine monophosphate deaminase 3 ANKRD22 NM_144590 TC10001497.hg.1 1.216 3.23 ankyrin repeat domain 22 ANO1 NM_018043 TC11000721.hg.1 1.121 4.50 anoctamin 1, calcium activated chloride channel ANTXR2 NM_001145794 TC04001328.hg.1 1.265 0.00 anthrax toxin receptor 2 APOBEC3A NM_145699 TC22001424.hg.1 1.438 0.00 apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3A APOBEC3B NM_004900 TC22001425.hg.1 1.209 1.13 apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3B APOL6 NM_030641 TC22000262.hg.1 1.277 0.52 apolipoprotein L, 6 ARHGAP31 NM_020754 TC03000607.hg.1 1.100 3.73 Cdc42 GTPase-activating protein ARNTL2 NM_001248002 TC12000264.hg.1 1.186 0.50 aryl hydrocarbon receptor nuclear translocator like 2 ATP1B1 NM_001677 TC01001473.hg.1 1.202 0.00 ATPase, Na+/K+ transporting, beta 1 polypeptide BCL2A1 NM_001114735 TC15001719.hg.1 1.188 0.81 BCL2-related protein A1 BCL3 NM_005178 TC19000627.hg.1 1.136 2.15 B-cell CLL/lymphoma 3

205 Appendices

BID NM_001196 TC22000476.hg.1 1.131 0.00 BH3 interacting domain death agonist BIRC3 NM_001165 TC11000956.hg.1 1.138 4.46 baculoviral IAP repeat-containing 3 BMP2 NM_001200 TC20000067.hg.1 1.184 1.08 bone morphogenetic protein 2 BPGM NM_001724 TC07000836.hg.1 1.149 2.89 2,3-bisphosphoglycerate mutase BST2 NM_004335 TC19001275.hg.1 1.460 0.44 NPC-A-7; bone marrow stromal cell antigen 2 BTG1 NM_001731 TC12001807.hg.1 1.103 2.89 B-cell translocation gene 1, anti-proliferative C19orf66 NM_018381 TC19000168.hg.1 1.127 2.66 chromosome 19 open reading frame 66 C1orf74 NM_152485 TC01003786.hg.1 1.193 0.79 chromosome 1 open reading frame 74 C3 NM_000064 TC19001103.hg.1 1.171 0.50 complement component 3 C5orf4 NM_032385 TC05001973.hg.1 1.125 3.72 chromosome 5 open reading frame 4 CAB39 NM_001130849 TC02001379.hg.1 1.146 2.92 calcium binding protein 39 CARHSP1 NM_014316 TC16000851.hg.1 1.150 0.52 calcium regulated heat stable protein 1, 24kDa CASP10 NM_032976 TC02001176.hg.1 1.127 1.38 caspase 10 CASP4 NM_001225 TC11002246.hg.1 1.164 3.31 caspase 4, apoptosis-related cysteine peptidase CCL20 NM_001130046 TC02001364.hg.1 2.264 0.00 chemokine (C-C motif) ligand 20 CD274 NM_014143 TC09000037.hg.1 1.183 4.69 CD274 molecule CD68 NM_001040059 TC17000103.hg.1 1.213 1.41 CD68 molecule CDCP1 NM_022842 TC03001345.hg.1 1.153 0.81 CUB domain containing protein 1 CDSN NM_001264 TC6_qbl_hap6000140.hg.1 1.244 4.46 corneodesmosin CDSN NM_001264 TC6_dbb_hap3000139.hg.1 1.282 3.92 corneodesmosin CDSN NM_001264 TC6_mcf_hap5000127.hg.1 1.289 3.55 corneodesmosin CEACAM1 NM_001712 TC19001575.hg.1 1.337 0.00 carcinoembryonic antigen-related cell adhesion molecule 1 (biliary glycoprotein) CFB NM_001710 TC6_mann_hap4000196.hg.1 1.284 0.00 complement factor B CFB NM_001710 TC06004077.hg.1 1.309 0.00 complement factor B CFB NM_001710 TC6_cox_hap2000245.hg.1 1.309 0.00 complement factor B CFB NM_001710 TC6_dbb_hap3000222.hg.1 1.308 0.00 complement factor B CFB NM_001710 TC6_qbl_hap6000225.hg.1 1.306 0.00 complement factor B CFB NM_001710 TC6_ssto_hap7000199.hg.1 1.309 0.00 complement factor B CFB NM_001710 TC6_mcf_hap5000213.hg.1 1.309 0.00 complement factor B

206 Appendices

CLDN7 NM_001185022 TC17001083.hg.1 1.187 0.00 claudin 7 CMPK2 NM_207315 TC02005020.hg.1 1.466 0.00 cytidine monophosphate (UMP-CMP) kinase 2, mitochondrial CNFN NM_032488 TC19001572.hg.1 1.456 0.43 cornifelin CRCT1 NM_019060 TC01001227.hg.1 1.407 1.14 cysteine-rich C-terminal 1 CSF2 NM_000758 TC05000629.hg.1 1.502 0.00 colony stimulating factor 2 (granulocyte-macrophage) CTSS NM_004079 TC01003210.hg.1 1.219 1.89 cathepsin S CXCL1 NM_001511 TC04000411.hg.1 1.608 0.00 chemokine (C-X-C motif) ligand 1 (melanoma growth stimulating activity, alpha) CXCL10 NM_001565 TC04001305.hg.1 12.804 0.00 chemokine (C-X-C motif) ligand 10 CXCL11 NM_005409 TC04001306.hg.1 3.346 0.43 chemokine (C-X-C motif) ligand 11 CXCL16 NM_022059 TC17001029.hg.1 1.153 0.00 chemokine (C-X-C motif) ligand 16 CXCL2 NM_002089 TC04001286.hg.1 1.357 0.00 chemokine (C-X-C motif) ligand 2 CYB5R2 NM_016229 TC11001372.hg.1 1.119 2.69 cytochrome b5 reductase 2 CYP27B1 NM_000785 TC12001634.hg.1 1.133 0.00 cytochrome P450, family 27, subfamily B, polypeptide 1 DAB2 NM_001244871 TC05003425.hg.1 1.118 3.92 Dab, mitogen-responsive phosphoprotein, homolog 2 DAPP1 NM_014395 TC04000517.hg.1 1.205 1.33 dual adaptor of phosphotyrosine and 3-phosphoinositides DCUN1D3 NM_173475 TC16002041.hg.1 1.110 0.52 DCN1, defective in cullin neddylation 1, domain containing 3 (S. cerevisiae) DDX58 NM_014314 TC09000999.hg.1 3.334 0.00 DEAD (Asp-Glu-Ala-Asp) box polypeptide 58 DDX60 NM_017631 TC04001718.hg.1 3.240 0.00 DEAD (Asp-Glu-Ala-Asp) box polypeptide 60 DDX60L NM_001012967 TC04001719.hg.1 2.792 0.00 DEAD (Asp-Glu-Ala-Asp) box polypeptide 60-like DEFB103A NM_001081551 TC08000920.hg.1 2.400 1.91 defensin, beta 103B; defensin, beta 103A DEFB103A NM_001081551 TC08000050.hg.1 2.362 0.80 defensin, beta 103B; defensin, beta 103A DEFB4A NM_004942 TC08000051.hg.1 2.889 0.00 defensin, beta 4 DEFB4B NM_001205266 TC08000919.hg.1 2.625 0.00 defensin beta 4B DHRS9 NM_005771 TC02001000.hg.1 1.485 0.00 dehydrogenase/reductase (SDR family) member 9 DNAJB6 NM_058246 TC07001055.hg.1 1.095 4.10 DnaJ (Hsp40) homolog, subfamily B, member 6 DSCAM NM_001389 TC21000465.hg.1 1.172 0.54 Down syndrome cell adhesion molecule DTX3L NM_138287 TC03000632.hg.1 1.533 0.00 deltex 3-like (Drosophila) EDN1 NM_001168319 TC06000087.hg.1 1.201 0.42 endothelin 1 EFNA1 NM_004428 TC01001288.hg.1 1.156 0.44 ephrin-A1

207 Appendices

EHD4 NM_139265 TC15001257.hg.1 1.193 0.78 EH-domain containing 4 EIF2AK2 NM_001135651 TC02001739.hg.1 1.786 0.00 eukaryotic translation initiation factor 2-alpha kinase 2 ELK3 NM_005230 TC12000747.hg.1 1.157 1.11 ELK3, ETS-domain protein (SRF accessory protein 2) EMP1 NM_001423 TC12000189.hg.1 1.182 1.32 epithelial membrane protein 1 EMR2 NM_013447 TC19001242.hg.1 1.100 1.13 egf-like module containing, mucin-like, hormone receptor-like 2 ENKUR NM_145010 TC10001111.hg.1 1.546 0.00 enkurin, TRPC channel interacting protein EPHA2 NM_004431 TC01002258.hg.1 1.109 3.16 EPH receptor A2 EPSTI1 NM_001002264 TC13000612.hg.1 2.133 0.00 epithelial stromal interaction 1 (breast) FERMT1 NM_017671 TC20000603.hg.1 1.343 0.00 fermitin family homolog 1 (Drosophila) FEZ1 NM_005103 TC11002420.hg.1 1.141 0.82 fasciculation and elongation protein zeta 1 (zygin I) FUT2 NM_000511 TC19000709.hg.1 1.131 1.61 fucosyltransferase 2 FUT8 NM_178155 TC14000397.hg.1 1.138 0.80 fucosyltransferase 8 (alpha (1,6) fucosyltransferase) G0S2 NM_015714 TC01001749.hg.1 1.300 0.00 G0/G1switch 2 GBP1 NM_002053 TC01002847.hg.1 1.351 1.33 guanylate binding protein 1, interferon-inducible, 67kDa GBP4 NM_052941 TC01002849.hg.1 1.388 1.33 guanylate binding protein 4 GBP5 NM_001134486 TC01002850.hg.1 1.442 0.00 guanylate binding protein 5 GCH1 NM_000161 TC14001152.hg.1 1.241 0.00 GTP cyclohydrolase 1 GJB4 NM_153212 TC01000449.hg.1 1.197 1.90 gap junction protein, beta 4, 30.3kDa GK NM_000167 TC0X000141.hg.1 1.139 4.31 glycerol kinase GLRX NM_001118890 TC05001608.hg.1 1.165 0.00 glutaredoxin (thioltransferase) GPR110 NM_025048 TC06001776.hg.1 1.297 1.14 G protein-coupled receptor 110 GRK5 NM_005308 TC10000865.hg.1 1.115 4.37 G protein-coupled receptor kinase 5 GSDMA NM_178171 TC17000484.hg.1 1.256 0.82 gasdermin A HBEGF NM_001945 TC05001854.hg.1 1.430 0.00 heparin-binding EGF-like growth factor HCAR2 NM_177551 TC12002078.hg.1 1.245 0.00 niacin receptor 2; niacin receptor 1 HCAR3 NM_006018 TC12002079.hg.1 1.301 0.00 niacin receptor 2; niacin receptor 1 HEPHL1 NM_001098672 TC11000915.hg.1 1.948 0.00 hephaestin-like 1 HERC5 NM_016323 TC04000485.hg.1 2.359 0.42 hect domain and RLD 5 HERC6 NM_001165136 TC04000484.hg.1 2.307 0.00 hect domain and RLD 6 HLA-A BC003069 TC6_mcf_hap5000206.hg.1 1.110 0.45 major histocompatibility complex, class I, A

208 Appendices

HLA-B NM_005514 TC6_ssto_hap7000191.hg.1 1.205 0.51 major histocompatibility complex, class I, C; major histocompatibility complex, class I, B HLA-B NM_005514 TC6_mann_hap4000188.hg.1 1.202 0.56 major histocompatibility complex, class I, C; major histocompatibility complex, class I, B HLA-B NM_005514 TC06004060.hg.1 1.204 0.57 major histocompatibility complex, class I, C; major histocompatibility complex, class I, B HLA-B NM_005514 TC6_cox_hap2000237.hg.1 1.212 0.00 major histocompatibility complex, class I, C; major histocompatibility complex, class I, B HLA-B NM_005514 TC6_mcf_hap5000195.hg.1 1.217 0.00 major histocompatibility complex, class I, C; major histocompatibility complex, class I, B HLA-B NM_005514 TC6_qbl_hap6000147.hg.1 1.219 0.00 major histocompatibility complex, class I, C; major histocompatibility complex, class I, B HLA-C NM_001243042 TC6_cox_hap2000236.hg.1 1.109 4.37 major histocompatibility complex, class I, C HLA-C NM_001243042 TC6_dbb_hap3000145.hg.1 1.117 4.31 major histocompatibility complex, class I, C HLA-C NM_001243042 TC6_mann_hap4000187.hg.1 1.127 3.32 major histocompatibility complex, class I, C HLA-C NM_001243042 TC6_qbl_hap6000146.hg.1 1.126 2.65 major histocompatibility complex, class I, C HLA-C NM_001243042 TC6_ssto_hap7000190.hg.1 1.129 2.69 major histocompatibility complex, class I, C HLA-C NM_001243042 TC6_mcf_hap5000194.hg.1 1.135 1.32 major histocompatibility complex, class I, C HLA-E NM_005516 TC06000338.hg.1 1.102 1.38 major histocompatibility complex, class I, E HLA-E NM_005516 TC6_mann_hap4000031.hg.1 1.102 1.38 major histocompatibility complex, class I, E HLA-E NM_005516 TC6_mcf_hap5000023.hg.1 1.102 1.38 major histocompatibility complex, class I, E HLA-E NM_005516 TC6_qbl_hap6000029.hg.1 1.103 1.09 major histocompatibility complex, class I, E HLA-E NM_005516 TC6_dbb_hap3000029.hg.1 1.103 1.09 major histocompatibility complex, class I, E HLA-E NM_005516 TC6_ssto_hap7000029.hg.1 1.103 1.09 major histocompatibility complex, class I, E HLA-E NM_005516 TC6_cox_hap2000036.hg.1 1.103 1.09 major histocompatibility complex, class I, E HLA-G NM_002127 TC06004065.hg.1 1.100 4.10 major histocompatibility complex, class I, G HS3ST1 NM_005114 TC04001037.hg.1 1.143 0.78 heparan sulfate (glucosamine) 3-O-sulfotransferase 1 HSD11B1 NM_001206741 TC01001750.hg.1 1.345 0.56 hydroxysteroid (11-beta) dehydrogenase 1 HSD17B2 NM_002153 TC16000645.hg.1 1.406 0.00 hydroxysteroid (17-beta) dehydrogenase 2 ICAM1 NM_000201 TC19000174.hg.1 1.427 0.00 intercellular adhesion molecule 1 IDH3A NM_005530 TC15000724.hg.1 1.169 3.73 isocitrate dehydrogenase 3 (NAD+) alpha IFI16 NM_001206567 TC01001348.hg.1 1.255 3.23 interferon, gamma-inducible protein 16 IFI27 NM_001130080 TC14000584.hg.1 2.322 0.00 interferon, alpha-inducible protein 27

209 Appendices

IFI35 NM_005533 TC17000545.hg.1 1.343 0.45 interferon-induced protein 35 IFI44 NM_006417 TC01000795.hg.1 6.259 0.00 interferon-induced protein 44 IFI44L NM_006820 TC01000794.hg.1 11.316 0.00 interferon-induced protein 44-like IFI6 NM_002038 TC01002412.hg.1 8.359 0.00 interferon, alpha-inducible protein 6 IFIH1 NM_022168 TC02002481.hg.1 3.214 0.00 interferon induced with helicase C domain 1 IFIT1 NM_001548 TC10000639.hg.1 6.866 0.00 interferon-induced protein with tetratricopeptide repeats 1 IFIT1B NM_001010987 TC10000638.hg.1 1.338 0.00 interferon-induced protein with tetratricopeptide repeats 1-like IFIT2 NM_001547 TC10000636.hg.1 3.322 0.00 interferon-induced protein with tetratricopeptide repeats 2 IFIT3 NM_001031683 TC10000637.hg.1 5.777 0.00 interferon-induced protein with tetratricopeptide repeats 3 IFIT5 NM_012420 TC10000640.hg.1 1.472 0.52 interferon-induced protein with tetratricopeptide repeats 5 IFITM1 NM_003641 TC11000011.hg.1 1.262 0.44 interferon induced transmembrane protein 1 (9-27) IFNA2 NM_000605 TC09000960.hg.1 1.169 4.28 interferon, alpha 2 IFNGR1 NM_000416 TC06002152.hg.1 1.225 1.85 interferon gamma receptor 1 IFNGR2 NM_005534 TC21000129.hg.1 1.128 0.44 interferon gamma receptor 2 (interferon gamma transducer 1) IL1A NM_000575 TC02002218.hg.1 1.309 0.00 interleukin 1, alpha IL1B NM_000576 TC02002219.hg.1 1.329 0.00 interleukin 1, beta IL1R2 NM_004633 TC02000619.hg.1 1.467 0.00 interleukin 1 receptor, type II IL1RL1 NM_003856 TC02004994.hg.1 1.607 0.56 interleukin 1 receptor-like 1 IL1RN NM_173843 TC02000720.hg.1 1.310 0.00 interleukin 1 receptor antagonist IL23A NM_016584 TC12000512.hg.1 1.370 0.83 interleukin 23, alpha subunit p19 IL24 NM_001185156 TC01001730.hg.1 1.293 0.00 interleukin 24 IL36A BC107043 TC02000716.hg.1 1.416 0.00 interleukin 1 family, member 6 (epsilon) IL36B NM_014438 TC02002220.hg.1 1.438 0.00 interleukin 1 family, member 8 (eta) IL36G NM_019618 TC02000715.hg.1 2.504 0.00 interleukin 1 family, member 9 IL36RN NM_012275 TC02000717.hg.1 1.521 0.00 interleukin 1 family, member 5 (delta) IL6 NM_000600 TC07000137.hg.1 1.450 0.57 interleukin 6 (interferon, beta 2) IL7R NM_002185 TC05000159.hg.1 1.238 0.55 interleukin 7 receptor IL8 NM_000584 TC04000408.hg.1 2.462 0.00 interleukin 8 INHBA NM_002192 TC07001318.hg.1 1.357 0.00 inhibin, beta A IRAK2 NM_001570 TC03000056.hg.1 1.344 0.00 interleukin-1 receptor-associated kinase 2

210 Appendices

IRF1 NM_002198 TC05001767.hg.1 1.147 1.60 interferon regulatory factor 1 IRF2 NM_002199 TC04001805.hg.1 1.136 1.85 interferon regulatory factor 2 IRF7 NM_004031 TC11001241.hg.1 1.147 3.73 interferon regulatory factor 7 IRF9 NM_006084 TC14000161.hg.1 1.089 0.83 interferon regulatory factor 9 ISG15 NM_005101 TC01000023.hg.1 1.214 2.92 ISG15 ubiquitin-like modifier ITGA2 NM_002203 TC05000218.hg.1 1.183 0.56 integrin, alpha 2 (CD49B, alpha 2 subunit of VLA-2 receptor) ITGA5 NM_002205 TC12001571.hg.1 1.117 4.46 integrin, alpha 5 (fibronectin receptor, alpha polypeptide) ITPKC NM_025194 TC19000566.hg.1 1.131 0.45 inositol 1,4,5-trisphosphate 3-kinase C JHDM1D NM_030647 TC07001917.hg.1 1.202 4.69 jumonji C domain containing histone demethylase 1 homolog D (S. cerevisiae) JUNB BC009465 TC19000228.hg.1 1.107 4.50 jun B proto-oncogene KCNK1 NM_002245 TC01001928.hg.1 1.101 0.79 potassium channel, subfamily K, member 1 KIAA0247 NM_014734 TC14000417.hg.1 1.100 4.50 KIAA0247 KIAA0754 NM_015038 TC01000494.hg.1 1.157 2.89 hypothetical LOC643314 KLK6 NM_001012964 TC19001764.hg.1 1.402 0.50 kallikrein-related peptidase 6 KPNA7 NM_001145715 TC07001640.hg.1 1.166 0.45 karyopherin alpha 7 (importin alpha 8) KYNU NM_001032998 TC02000902.hg.1 1.346 0.00 kynureninase (L-kynurenine hydrolase) LAMC2 NM_005562 TC01001585.hg.1 1.094 1.12 laminin, gamma 2 LAMP3 NM_014398 TC03002054.hg.1 1.529 0.50 lysosomal-associated membrane protein 3 LAP3 NM_015907 TC04000151.hg.1 1.286 2.69 leucine aminopeptidase 3 LCE3A NM_178431 TC01003250.hg.1 1.260 4.31 late cornified envelope 3A LCE3C ENST00000333881 TC01001228.hg.1 1.195 2.92 late cornified envelope 3C LCE3D NM_032563 TC01003249.hg.1 1.803 0.00 late cornified envelope 3D LCE3E NM_178435 TC01003248.hg.1 1.821 0.00 late cornified envelope 3E LCMT1 NM_001032391 TC16000283.hg.1 1.143 1.12 leucine carboxyl methyltransferase 1 LCN2 NM_005564 TC09000677.hg.1 1.259 0.00 lipocalin 2 LOC100134229 NR_024451 TC07000878.hg.1 1.200 4.46 JHDM1D antisense RNA 1 (head to head) (JHDM1D-AS1), long non-coding RNA LOC100506377 ENST00000473756 TC03000498.hg.1 1.247 1.85 hypothetical LOC100506377 LOC152225 NR_026934 TC03000526.hg.1 1.214 3.23 uncharacterized LOC152225, long non-coding RNALOC152225 LOC541472 ENST00000325042 TC07001189.hg.1 1.175 3.73 hypothetical LOC541472 LY6E NM_001127213 TC08000814.hg.1 1.193 1.07 lymphocyte antigen 6 complex, locus E

211 Appendices

LYN NM_001111097 TC08000383.hg.1 1.252 0.47 v-yes-1 Yamaguchi sarcoma viral related oncogene homolog MAOA NM_000240 TC0X000207.hg.1 1.291 0.00 monoamine oxidase A MIR147B NR_030599 TC15000357.hg.1 1.941 0.00 microRNA 147b MIR3145 NR_036099 TC06002160.hg.1 1.120 1.37 microRNA 3145 MIR3660 NR_037433 TC05001581.hg.1 1.185 0.00 microRNA 3660 MIR513A1 ENST00000385138 TC0X001461.hg.1 1.238 3.73 microRNA 513a-1 MLKL NM_001142497 TC16001270.hg.1 1.363 0.00 mixed lineage kinase domain-like MMP1 NM_001145938 TC11002234.hg.1 2.681 0.00 matrix metallopeptidase 1 (interstitial collagenase) MMP10 NM_002425 TC11002233.hg.1 2.142 0.00 matrix metallopeptidase 10 (stromelysin 2) MMP12 NM_002426 TC11002237.hg.1 1.211 3.92 matrix metallopeptidase 12 (macrophage elastase) MMP13 NM_002427 TC11002239.hg.1 1.472 0.83 matrix metallopeptidase 13 (collagenase 3) MMP3 NM_002422 TC11002235.hg.1 1.194 0.43 matrix metallopeptidase 3 (stromelysin 1, progelatinase) MMP9 NM_004994 TC20000363.hg.1 1.463 0.00 matrix metallopeptidase 9 (gelatinase B, 92kDa gelatinase, 92kDa type IV collagenase) MUC21 NM_001010909 TC6_mann_hap4000046.hg.1 1.332 1.14 mucin 21, cell surface associated MUC21 NM_001010909 TC6_mcf_hap5000038.hg.1 1.326 0.42 mucin 21, cell surface associated MUC21 NM_001010909 TC06000353.hg.1 1.275 0.44 mucin 21, cell surface associated MUC21 NM_001010909 TC6_qbl_hap6000044.hg.1 1.328 0.45 mucin 21, cell surface associated MUC21 NM_001010909 TC6_cox_hap2000051.hg.1 1.359 0.47 mucin 21, cell surface associated MUC21 NM_001010909 TC6_apd_hap1000031.hg.1 1.329 0.48 mucin 21, cell surface associated MUC21 NM_001010909 TC6_dbb_hap3000044.hg.1 1.329 0.48 mucin 21, cell surface associated MX1 NM_001144925 TC21000189.hg.1 2.483 0.00 myxovirus (influenza virus) resistance 1, interferon-inducible protein p78 (mouse) MX2 NM_002463 TC21000188.hg.1 1.880 0.00 myxovirus (influenza virus) resistance 2 (mouse) MXD1 NM_001202513 TC02004970.hg.1 1.156 3.73 MAX dimerization protein 1 MYD88 NM_001172566 TC03000187.hg.1 1.160 0.48 myeloid differentiation primary response 88 MYH16 NR_002147 TC07000591.hg.1 1.202 0.00 myosin, heavy chain 16 pseudogene MYO1E NM_004998 TC15001492.hg.1 1.135 3.92 myosin IE N4BP1 NM_153029 TC16001098.hg.1 1.159 4.50 NEDD4 binding protein 1 NAGK NM_017567 TC02000427.hg.1 1.074 4.46 N-acetylglucosamine kinase NAV3 NM_014903 TC12000656.hg.1 1.296 0.00 neuron navigator 3; similar to neuron navigator 3

212 Appendices

NEDD4L NM_001144968 TC18000202.hg.1 1.114 3.23 neural precursor cell expressed, developmentally down-regulated 4-like NFE2L3 NM_004289 TC07000159.hg.1 1.228 1.64 nuclear factor (erythroid-derived 2)-like 3 NFKB2 NM_001077493 TC10000753.hg.1 1.133 0.43 nuclear factor of kappa light polypeptide gene enhancer in B-cells 2 (p49/p100) NFKBIA NM_020529 TC14001036.hg.1 1.379 0.00 nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha NFKBIZ NM_001005474 TC03003320.hg.1 1.324 0.00 nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, zeta NIPAL4 NM_001099287 TC05000868.hg.1 1.099 0.78 NIPA-like domain containing 4 NMI NM_004688 TC02002425.hg.1 1.299 1.85 N-myc (and STAT) interactor NPC1 NM_000271 TC18000413.hg.1 1.147 4.31 Niemann-Pick disease, type C1 NT5C3 NM_001002010 TC07001264.hg.1 1.411 2.42 5'-nucleotidase, cytosolic III NT5E NM_001204813 TC06000779.hg.1 1.133 3.73 5'-nucleotidase ecto OAS1 NM_001032409 TC12000884.hg.1 2.444 0.00 2',5'-oligoadenylate synthetase 1, 40/46kDa OAS2 NM_001032731 TC12000886.hg.1 4.158 0.00 2'-5'-oligoadenylate synthetase 2, 69/71kDa OAS3 NM_006187 TC12000885.hg.1 1.808 0.00 2'-5'-oligoadenylate synthetase 3, 100kDa OASL NM_003733 TC12002059.hg.1 1.758 0.00 2'-5'-oligoadenylate synthetase-like OR56B1 NM_001005180 TC11000117.hg.1 1.461 1.14 olfactory receptor, family 56, subfamily B, member 1 OR6M1 NM_001005325 TC11002399.hg.1 1.176 2.69 olfactory receptor, family 6, subfamily M, member 1 OSMR NM_003999 TC05000179.hg.1 1.156 0.80 oncostatin M receptor PAPL NM_001004318 TC19000536.hg.1 1.312 1.07 iron/zinc purple acid phosphatase-like protein PARP12 NM_022750 TC07001916.hg.1 1.668 0.00 poly (ADP-ribose) polymerase family, member 12 PARP14 NM_017554 TC03000634.hg.1 2.116 0.00 poly (ADP-ribose) polymerase family, member 14 PARP9 NM_001146102 TC03001705.hg.1 1.990 0.00 poly (ADP-ribose) polymerase family, member 9 PDZD2 NM_178140 TC05000135.hg.1 1.146 2.66 PDZ domain containing 2 PDZK1IP1 NM_005764 TC01002627.hg.1 1.327 0.00 PDZK1 interacting protein 1 PGLYRP4 NM_020393 TC01003259.hg.1 1.271 0.00 peptidoglycan recognition protein 4 PHF11 NM_001040444 TC13000199.hg.1 1.269 0.80 PHD finger protein 11 PHLDA1 NM_007350 TC12001751.hg.1 1.149 0.48 pleckstrin homology-like domain, family A, member 1 PI3 NM_002638 TC20000341.hg.1 1.318 0.45 peptidase inhibitor 3, skin-derived PLA2G4E NM_001206670 TC15001258.hg.1 1.295 0.00 phospholipase A2 group IVE

213 Appendices

PLAT NM_000930 TC08001175.hg.1 1.356 0.00 plasminogen activator, tissue PLAU NM_001145031 TC10000475.hg.1 1.208 0.00 plasminogen activator, urokinase PLAUR NM_001005376 TC19001593.hg.1 1.360 0.00 plasminogen activator, urokinase receptor PLEK2 NM_016445 TC14001238.hg.1 1.099 4.46 pleckstrin 2 PLOD2 NM_000935 TC03001866.hg.1 1.120 4.92 procollagen-lysine, 2-oxoglutarate 5-dioxygenase 2 PLSCR1 NM_021105 TC03001869.hg.1 1.923 0.00 phospholipid scramblase 1 PMAIP1 NM_021127 TC18000213.hg.1 1.211 3.32 phorbol-12-myristate-13-acetate-induced protein 1 PML NM_002675 TC15000671.hg.1 1.247 0.50 promyelocytic leukemia; similar to promyelocytic leukemia protein isoform 1 PNP NM_000270 TC14000056.hg.1 1.163 0.47 purine nucleoside phosphorylase PNPT1 NM_033109 TC02001866.hg.1 1.620 0.52 polyribonucleotide nucleotidyltransferase 1 POLB NM_002690 TC08000326.hg.1 1.204 4.50 polymerase (DNA directed), beta PPIF NM_005729 TC10000566.hg.1 1.282 0.00 peptidylprolyl isomerase F PPP2R2C NM_181876 TC04001001.hg.1 1.116 4.28 protein phosphatase 2 (formerly 2A), regulatory subunit B, gamma isoform PRDM1 NM_001198 TC06000844.hg.1 1.277 0.00 PR domain containing 1, with ZNF domain PRIC285 NM_001037335 TC20001035.hg.1 1.206 0.52 peroxisomal proliferator-activated receptor A interacting complex 285 PRSS22 NM_022119 TC16000795.hg.1 1.996 0.00 protease, serine, 22 PTAFR NM_001164721 TC01002421.hg.1 1.215 0.00 platelet-activating factor receptor PTPN12 NM_001131008 TC07000495.hg.1 1.148 1.63 protein tyrosine phosphatase, non-receptor type 12 PTPRK NM_002844 TC06002092.hg.1 1.127 4.37 protein tyrosine phosphatase, receptor type, K QPCT NM_012413 TC02000237.hg.1 1.119 0.47 glutaminyl-peptide cyclotransferase RAB31 NM_006868 TC18000047.hg.1 1.120 4.28 RAB31, member RAS oncogene family RAC2 NM_002872 TC22000725.hg.1 1.110 1.85 ras-related C3 botulinum toxin substrate 2 (rho family, small GTP binding protein Rac2) RASGEF1B NM_152545 TC04002922.hg.1 1.230 1.89 RasGEF domain family, member 1B RASSF10 NM_001080521 TC11000205.hg.1 1.117 1.32 Ras association (RalGDS/AF-6) domain family (N-terminal) member 10 REP15 NM_001029874 TC12000268.hg.1 1.200 4.69 RAB15 effector protein RHCG NM_016321 TC15001829.hg.1 1.246 2.66 Rh family, C glycoprotein RIPK3 NM_006871 TC14002317.hg.1 1.163 3.73 receptor-interacting serine-threonine kinase 3 RN5S173 ENST00000364857 TC04000879.hg.1 1.176 1.38 RNA, 5S ribosomal pseudogene 173 RN5S195 ENST00000362675 TC05000710.hg.1 1.156 0.00 RNA, 5S ribosomal pseudogene 195

214 Appendices

RN5S517 ENST00000364724 TC0X001457.hg.1 1.169 0.49 RNA, 5S ribosomal pseudogene 517 RNASE7 NM_032572 TC14000080.hg.1 1.445 0.00 ribonuclease, RNase A family, 7 RND1 NM_014470 TC12001459.hg.1 1.243 1.33 Rho family GTPase 1 RNF19B NM_001127361 TC01002478.hg.1 1.244 0.00 ring finger protein 19B RNU7-15P ENST00000516343 TC05001774.hg.1 1.176 4.37 RNA, U7 small nuclear 15 pseudogene RNU7-32P ENST00000516281 TC03000913.hg.1 1.116 4.10 RNA, U7 small nuclear 32 pseudogene RNU7-54P ENST00000459236 TC07001847.hg.1 1.168 1.33 RNA, U7 small nuclear 54 pseudogene RPS6KA5 NM_004755 TC14001434.hg.1 1.145 4.50 ribosomal protein S6 kinase, 90kDa, polypeptide 5 RSAD2 NM_080657 TC02000034.hg.1 10.509 0.00 radical S-adenosyl methionine domain containing 2 RTP4 NM_022147 TC03001031.hg.1 1.299 0.00 receptor (chemosensory) transporter protein 4 S100A12 NM_005621 TC01003260.hg.1 1.782 0.00 S100 calcium binding protein A12 S100A7 NM_002963 TC01003263.hg.1 1.734 0.00 S100 calcium binding protein A7 S100A7A NM_176823 TC01001255.hg.1 1.913 0.00 S100 calcium binding protein A7A S100A8 NM_002964 TC01003261.hg.1 1.232 0.52 S100 calcium binding protein A8 S100A9 NM_002965 TC01001254.hg.1 1.244 0.45 S100 calcium binding protein A9 SAA1 NM_000331 TC11000238.hg.1 1.324 0.00 serum amyloid A1 SAA2 NM_001127380 TC11003478.hg.1 1.379 0.00 serum amyloid A2 SAA4 NM_006512 TC11003477.hg.1 1.149 0.00 serum amyloid A4, constitutive SAMD9 NM_001193307 TC07001605.hg.1 1.937 0.00 sterile alpha motif domain containing 9 SAMD9L NM_152703 TC07001606.hg.1 3.504 0.00 sterile alpha motif domain containing 9-like SAMHD1 NM_015474 TC20000821.hg.1 2.927 0.00 SAM domain and HD domain 1 SAT1 NM_002970 TC0X000112.hg.1 1.150 1.38 spermidine/spermine N1-acetyltransferase 1 SCARNA23 NR_003007 TC0X000121.hg.1 1.180 0.00 small Cajal body-specific RNA 23 SCG5 NM_001144757 TC15000224.hg.1 1.125 0.43 secretogranin V (7B2 protein) SDC4 NM_002999 TC20000878.hg.1 1.121 1.12 syndecan 4 SDCBP2 NM_001199784 TC20001740.hg.1 1.124 0.00 syndecan binding protein 2 SDR16C5 NM_138969 TC08001232.hg.1 1.224 0.00 short chain dehydrogenase/reductase family 16C, member 5 SEMA7A NM_001146029 TC15001643.hg.1 1.305 0.00 semaphorin 7A, GPI membrane anchor (John Milton Hagen blood group) SERPINA3 NM_001085 TC14002309.hg.1 1.261 1.07 serpin peptidase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 3

215 Appendices

SERPINB1 NM_030666 TC06001217.hg.1 1.305 0.00 serpin peptidase inhibitor, clade B (ovalbumin), member 1 SERPINB10 BC096218 TC18000231.hg.1 1.165 0.45 serpin peptidase inhibitor, clade B (ovalbumin), member 10 SERPINB3 NM_006919 TC18001005.hg.1 1.334 1.61 serpin peptidase inhibitor, clade B (ovalbumin), member 3 SERPINB4 NM_002974 TC18001004.hg.1 1.539 0.48 serpin peptidase inhibitor, clade B (ovalbumin), member 4 SERPINB9 NM_004155 TC06001220.hg.1 1.205 2.13 serpin peptidase inhibitor, clade B (ovalbumin), member 9 SGK1 NM_001143676 TC06002126.hg.1 1.182 0.00 serum/glucocorticoid regulated kinase 1 SGPP2 NM_152386 TC02001347.hg.1 1.257 0.00 sphingosine-1-phosphate phosphotase 2 SH3KBP1 NM_001024666 TC0X000903.hg.1 1.139 0.79 SH3-domain kinase binding protein 1 SLC11A2 NM_001174125 TC12001499.hg.1 1.146 0.82 solute carrier family 11 (proton-coupled divalent metal ion transporter), member 2 SLC18B1 NM_052831 TC06002122.hg.1 1.139 3.92 chromosome 6 open reading frame 192 SLC25A28 NM_031212 TC10001582.hg.1 1.095 3.16 solute carrier family 25, member 28 SLC26A9 NM_052934 TC01003756.hg.1 1.217 0.00 solute carrier family 26, member 9 SLC28A3 NM_001199633 TC09001286.hg.1 1.404 0.00 solute carrier family 28 (concentrative nucleoside transporter), member 3 SLC43A3 NM_014096 TC11003482.hg.1 1.126 1.63 solute carrier family 43, member 3 SLC44A4 NM_001178044 TC6_dbb_hap3000165.hg.1 1.160 0.50 solute carrier family 44 member 4 (SLC44A4) SLC44A4 NM_001178044 TC6_qbl_hap6000166.hg.1 1.164 0.52 solute carrier family 44 member 4 (SLC44A4) SLC44A4 NM_001178044 TC6_cox_hap2000176.hg.1 1.160 0.54 solute carrier family 44 member 4 (SLC44A4) SLC44A4 NM_001178044 TC06001549.hg.1 1.160 0.54 solute carrier family 44 member 4 (SLC44A4) SLC44A4 NM_001178044 TC6_mcf_hap5000151.hg.1 1.171 0.00 solute carrier family 44 member 4 (SLC44A4) SLC44A4 NM_001178044 TC6_apd_hap1000090.hg.1 1.169 0.00 solute carrier family 44 member 4 (SLC44A4) SLC44A4 NM_001178044 TC6_ssto_hap7000145.hg.1 1.169 0.00 solute carrier family 44 member 4 (SLC44A4) SLC46A3 NM_001135919 TC13000518.hg.1 1.161 4.46 solute carrier family 46, member 3 SLC5A1 NM_000343 TC22000237.hg.1 1.290 0.00 solute carrier family 5 (sodium/glucose cotransporter), member 1 SLC6A14 NM_007231 TC0X000571.hg.1 1.711 0.00 solute carrier family 6 (amino acid transporter), member 14 SLC9A7 NM_032591 TC0X000992.hg.1 1.194 1.14 solute carrier family 9 (sodium/hydrogen exchanger), member 7 SLFN5 NM_144975 TC17000396.hg.1 1.315 0.00 schlafen family member 5 SNORD113-6 NR_003234 TC14000671.hg.1 1.343 4.69 small nucleolar RNA, C/D box 113-6 SNORD114-21 NR_003214 TC14000701.hg.1 1.393 1.33 small nucleolar RNA, C/D box 114-21 SNORD114-4 NR_003196 TC14000679.hg.1 1.270 0.00 small nucleolar RNA, C/D box 114-4

216 Appendices

SNORD114-9 NR_003201 TC14000686.hg.1 1.179 0.00 small nucleolar RNA, C/D box 114-9 SNORD115-2 NR_003294 TC15000076.hg.1 1.169 3.32 small nucleolar RNA, C/D box 115-2 SNX9 NM_016224 TC06001126.hg.1 1.162 1.08 sorting nexin 9 SOD2 NM_000636 TC06004141.hg.1 1.556 0.00 superoxide dismutase 2, mitochondrial SOX9 NM_000346 TC17000819.hg.1 1.142 3.31 SRY (sex determining region Y)-box 9 SP100 NM_001080391 TC02001377.hg.1 1.317 4.50 SP100 nuclear antigen SP110 NM_001185015 TC02002853.hg.1 1.469 1.14 SP110 nuclear body protein SPRR2A NM_005988 TC01006377.hg.1 1.339 0.55 small proline-rich protein 2A SPRR2B NM_001017418 TC01006375.hg.1 1.417 0.00 small proline-rich protein 2B SPRR2C NR_003062 TC01006378.hg.1 1.536 0.00 small proline rich protein 2C (pseudogene) SPRR2D NM_006945 TC01006374.hg.1 1.429 0.00 small proline-rich protein 2D SPRR2E NM_001024209 TC01003255.hg.1 1.455 0.00 small proline-rich protein 2E SPRR2F NM_001014450 TC01006376.hg.1 1.946 0.00 small proline-rich protein 2F SPRR2G NM_001014291 TC01003256.hg.1 2.641 0.00 small proline-rich protein 2C (pseudogene); small proline-rich protein 2G SPRR4 NM_173080 TC01001245.hg.1 1.181 1.62 small proline-rich protein 4 SQRDL NM_021199 TC15000364.hg.1 1.171 0.58 sulfide quinone reductase-like (yeast) ST3GAL1 NM_003033 TC08001660.hg.1 1.144 0.00 ST3 beta-galactoside alpha-2,3-sialyltransferase 1 STAT1 NM_007315 TC02002624.hg.1 1.856 0.00 signal transducer and activator of transcription 1, 91kDa STAT2 NM_005419 TC12001602.hg.1 1.257 2.65 signal transducer and activator of transcription 2, 113kDa STC1 NM_003155 TC08001062.hg.1 1.716 0.00 stanniocalcin 1 STEAP4 NM_001205315 TC07001582.hg.1 1.287 4.10 STEAP4 metalloreductase TAP1 NM_000593 TC6_qbl_hap6000187.hg.1 1.492 0.00 transporter 1, ATP-binding cassette, sub-family B (MDR/TAP) TAP1 NM_000593 TC6_mann_hap4000167.hg.1 1.492 0.00 transporter 1, ATP-binding cassette, sub-family B (MDR/TAP) TAP1 NM_000593 TC6_ssto_hap7000169.hg.1 1.498 0.00 transporter 1, ATP-binding cassette, sub-family B (MDR/TAP) TAP1 NM_000593 TC6_dbb_hap3000185.hg.1 1.492 0.00 transporter 1, ATP-binding cassette, sub-family B (MDR/TAP) TAP1 NM_000593 TC6_mcf_hap5000174.hg.1 1.492 0.00 transporter 1, ATP-binding cassette, sub-family B (MDR/TAP) TAP1 NM_000593 TC6_apd_hap1000105.hg.1 1.492 0.00 transporter 1, ATP-binding cassette, sub-family B (MDR/TAP) TAP1 NM_000593 TC06001574.hg.1 1.497 0.00 transporter 1, ATP-binding cassette, sub-family B (MDR/TAP) TAP1 NM_000593 TC6_cox_hap2000199.hg.1 1.497 0.00 transporter 1, ATP-binding cassette, sub-family B (MDR/TAP) TAP2 NM_000544 TC6_mann_hap4000165.hg.1 1.118 4.50 transporter 2, ATP-binding cassette, sub-family B (MDR/TAP)

217 Appendices

TAP2 NM_000544 TC6_qbl_hap6000185.hg.1 1.118 4.37 transporter 2, ATP-binding cassette, sub-family B (MDR/TAP) TAP2 NM_000544 TC6_mcf_hap5000225.hg.1 1.120 3.90 transporter 2, ATP-binding cassette, sub-family B (MDR/TAP) TAP2 NM_000544 TC6_cox_hap2000257.hg.1 1.116 3.92 transporter 2, ATP-binding cassette, sub-family B (MDR/TAP) TAP2 NM_000544 TC06004126.hg.1 1.117 3.73 transporter 2, ATP-binding cassette, sub-family B (MDR/TAP) TAP2 NM_000544 TC6_apd_hap1000130.hg.1 1.129 3.13 transporter 2, ATP-binding cassette, sub-family B (MDR/TAP) TAP2 NM_000544 TC6_dbb_hap3000242.hg.1 1.129 3.13 transporter 2, ATP-binding cassette, sub-family B (MDR/TAP) TAP2 NM_000544 TC6_ssto_hap7000213.hg.1 1.129 3.13 transporter 2, ATP-binding cassette, sub-family B (MDR/TAP) TDRD7 NM_014290 TC09000490.hg.1 1.543 0.00 tudor domain containing 7 TGFA NM_003236 TC02001963.hg.1 1.216 0.00 transforming growth factor, alpha TGM1 NM_000359 TC14000971.hg.1 1.217 1.85 transglutaminase 1 (K polypeptide epidermal type I, protein-glutamine- gamma-glutamyltransferase) TGM2 NM_004613 TC20000833.hg.1 1.255 0.00 transglutaminase 2 (C polypeptide, protein-glutamine-gamma- glutamyltransferase) TINF2 NM_001099274 TC14000970.hg.1 1.144 1.33 TERF1 (TRF1)-interacting nuclear factor 2 TLR2 NM_003264 TC04000775.hg.1 1.210 0.56 toll-like receptor 2 TM4SF1 NM_014220 TC03001888.hg.1 1.151 0.00 transmembrane 4 L six family member 1 TMC5 NM_001105248 TC16000214.hg.1 1.181 1.33 transmembrane channel-like 5 TMEM140 NM_018295 TC07000840.hg.1 1.236 0.55 transmembrane protein 140 TMEM171 NM_001161342 TC05000345.hg.1 1.351 0.00 transmembrane protein 171 TMEM173 NM_198282 TC05001845.hg.1 1.088 3.90 transmembrane protein 173 TMEM62 NM_024956 TC15000324.hg.1 1.193 4.50 transmembrane protein 62 TMPRSS11D NM_004262 TC04001252.hg.1 1.294 0.52 transmembrane protease, serine 11D TMPRSS11E NM_014058 TC04000369.hg.1 1.224 3.92 transmembrane protease, serine 11E TMPRSS11E NM_014058 TC4_ctg9_hap1000001.hg.1 1.228 3.55 transmembrane protease, serine 11E TMPRSS11F NM_207407 TC04001255.hg.1 1.379 0.50 transmembrane protease, serine 11F TMPRSS11GP NR_033737 TC04001254.hg.1 1.304 0.82 transmembrane protease, serine 11G, pseudogene TNFAIP3 NM_006290 TC06001027.hg.1 1.397 0.00 tumor necrosis factor, alpha-induced protein 3 TNFRSF10A NM_003844 TC08001052.hg.1 1.121 1.62 tumor necrosis factor receptor superfamily, member 10a TNIP1 NM_001252385 TC05001946.hg.1 1.234 0.00 TNFAIP3 interacting protein 1 TRANK1 NM_014831 TC03001283.hg.1 1.565 0.43 lupus brain antigen 1 TRIB1 NM_025195 TC08000733.hg.1 1.133 1.41 tribbles homolog 1 (Drosophila)

218 Appendices

TRIM14 NM_033220 TC09001403.hg.1 1.228 1.09 tripartite motif-containing 14 TRIM21 NM_003141 TC11001309.hg.1 1.407 0.00 tripartite motif-containing 21 TRIM25 NM_005082 TC17001716.hg.1 1.471 0.00 tripartite motif-containing 25 TTC9 NM_015351 TC14000426.hg.1 1.200 0.43 tetratricopeptide repeat domain 9 TTTY4 NR_001525 TC0Y000091.hg.1 1.106 4.37 testis-specific transcript, Y-linked 4 TTTY4C ENST00000436568 TC0Y000081.hg.1 1.106 4.37 testis-specific transcript, Y-linked 4 (non-protein coding) TTTY4C ENST00000456123 TC0Y000212.hg.1 1.106 4.37 testis-specific transcript, Y-linked 4C (non-protein coding) UBE2L6 NM_004223 TC11001795.hg.1 1.291 1.33 ubiquitin-conjugating enzyme E2L 6 UBTD2 NM_152277 TC05002060.hg.1 1.089 4.91 ubiquitin domain containing 2 UGCG NM_003358 TC09000560.hg.1 1.121 3.35 UDP-glucose ceramide glucosyltransferase UNC93B1 NM_030930 TC11001999.hg.1 1.106 4.50 unc-93 homolog B1 (C. elegans) UPP1 NM_003364 TC07000307.hg.1 1.099 1.90 uridine phosphorylase 1 USP18 NM_017414 TC22000029.hg.1 2.006 0.00 ubiquitin specific peptidase 18 USP41 ENST00000454608 TC22000519.hg.1 1.543 0.00 ubiquitin specific peptidase 41 VEGFC NM_005429 TC04001765.hg.1 1.286 0.47 vascular endothelial growth factor C VNN1 NM_004666 TC06002119.hg.1 1.544 0.00 vanin 1 VNN3 NR_028290 TC06002120.hg.1 1.237 0.00 vanin 3 VPS37B NM_024667 TC12002080.hg.1 1.102 2.15 vacuolar protein sorting 37 homolog B (S. cerevisiae) WFDC12 NM_080869 TC20000875.hg.1 1.455 0.00 WAP four-disulfide core domain 12 WFDC5 NM_145652 TC20000874.hg.1 1.326 1.41 WAP four-disulfide core domain 5 WWC1 NM_001161661 TC05000917.hg.1 1.112 2.43 WW and C2 domain containing 1 XAF1 NM_017523 TC17000077.hg.1 1.831 0.00 XIAP associated factor 1 XDH NM_000379 TC02001714.hg.1 1.367 0.00 xanthine dehydrogenase YOD1 NM_018566 TC01003773.hg.1 1.155 2.13 YOD1 OTU deubiquinating enzyme 1 homolog (S. cerevisiae) ZC3H12A NM_025079 TC01000474.hg.1 1.237 0.00 zinc finger CCCH-type containing 12A ZC3H12C NM_033390 TC11000985.hg.1 1.274 0.48 zinc finger CCCH-type containing 12C ZC3HAV1 NM_024625 TC07001910.hg.1 1.260 1.07 zinc finger CCCH-type, antiviral 1 ZNFX1 NM_021035 TC20000924.hg.1 1.217 0.47 zinc finger, NFX1-type containing 1 ZPLD1 NM_175056 TC03000528.hg.1 1.206 1.62 zona pellucida-like domain containing 1 Significantly differentially expressed genes at a fold change > 1.5 are highlighted bold.

219 Appendices

Appendix Table 18.2: InnateDB pathway over-representation analysis of differentially expressed genes during PBEC-myeloid co-culture. Uploaded gene Database count adjusted Pathway Name (ID) p-value Gene Symbols source (Total genes p-value for this entity) CSF2; DDX58; EIF2AK2; GBP1; GBP4; GBP5; HERC5; HLA-B; HLA-G; ICAM1; IFI35; Cytokine Signalling in IFI6; IFIT1; IFIT2; IFIT3; IFITM1; IFNA2; IFNGR1; IFNGR2; IL1A; IL1B; IL1R2; IL1RN; Immune system REACTOME 49 (267) 1.92E-30 9.22E-28 IL6; IL7R; IRAK2; IRF1; IRF2; IRF7; IRF9; ISG15; KPNA7; LYN; MX1; MX2; MYD88; (17418) OAS1; OAS2; OAS3; OASL; PML; PTAFR; SP100; STAT1; STAT2; TRIM25; UBE2L6; USP18; XAF1

DDX58; EIF2AK2; GBP1; GBP4; GBP5; HERC5; HLA-B; HLA-G; ICAM1; IFI35; IFI6; Interferon Signalling IFIT1; IFIT2; IFIT3; IFITM1; IFNA2; IFNGR1; IFNGR2; IRF1; IRF2; IRF7; IRF9; ISG15; REACTOME 39 (158) 2.17E-29 5.23E-27 (18059) KPNA7; MX1; MX2; OAS1; OAS2; OAS3; OASL; PML; PTAFR; SP100; STAT1; STAT2; TRIM25; UBE2L6; USP18; XAF1

Interferon α/β Signalling HLA-B; HLA-G; IFI35; IFI6; IFIT1; IFIT2; IFIT3; IFITM1; IFNA2; IRF1; IRF2; IRF7; IRF9; REACTOME 23 (59) 9.07E-23 1.45E-20 ISG15; MX1; MX2; OAS1; OAS2; OAS3; OASL; STAT2; USP18; XAF1 (13074)

BIRC3; C3; CASP10; CASP4; CD274; CFB; CSF2; CTSS; DAPP1; DDX58; DEFB103A; DEFB4A; DEFB4B; DTX3L; EIF2AK2; GBP1; GBP4; GBP5; HBEGF; HERC5; HLA-B; HLA-G; ICAM1; IFI16; IFI35; IFI6; IFIH1; IFIT1; IFIT2; IFIT3; IFITM1; IFNA2; IFNGR1; Immune System IFNGR2; IL1A; IL1B; IL1R2; IL1RN; IL6; IL7R; IRAK2; IRF1; IRF2; IRF7; IRF9; ISG15; REACTOME 79 (1127) 3.06E-20 3.68E-18 (18444) KPNA7; LYN; MX1; MX2; MYD88; NEDD4L; NFKBIA; OAS1; OAS2; OAS3; OASL; PML; PTAFR; RIPK3; RNF19B; RPS6KA5; S100A12; SAA1; SH3KBP1; SP100; STAT1; STAT2; TAP1; TAP2; TLR2; TMEM173; TNFAIP3; TRIM21; TRIM25; UBE2L6; UNC93B1; USP18; XAF1

Interferon γ Signalling GBP1; GBP4; GBP5; HLA-B; HLA-G; ICAM1; IFNGR1; IFNGR2; IRF1; IRF2; IRF7; IRF9; REACTOME 19 (63) 1.49E-16 1.43E-14 OAS1; OAS2; OAS3; OASL; PML; PTAFR; SP100 (13077) Benjamini Hochberg-adjusted p-values are shown.

Appendix Table 18.3: InnateDB Gene ontology over-representation analysis of differentially expressed genes during PBEC-myeloid co-culture.

220 Appendices

Uploaded gene count adjusted Pathway Name (ID) p-value Gene Symbols (Total genes for p-value this entity) ACE2; APOBEC3A; APOBEC3B; BCL2A1; BCL3; BID; BIRC3; BST2; C3; CASP10; CASP4; CD274; CEACAM1; CFB; CTSS; CXCL10; CXCL11; CXCL2; DDX58; DDX60; DEFB103A; DEFB4A; DEFB4B; EDN1; EIF2AK2; GLRX; GRK5; GSDMA; HBEGF; HERC5; HLA-B; ICAM1; IFI16; IFI6; IFIH1; IFIT1; IFIT2; IFIT3; IFIT5; IFITM1; IFNA2; innate immune response IFNGR1; IFNGR2; IL1A; IL1B; IL1R2; IL1RL1; IL23A; IL6; IL8; IRAK2; IRF1; IRF2; IRF7; IRF9; ISG15; LCN2; 103 (1359) 1.09E-38 2.75E-35 (GO:0045087) LYN; MMP9; MX1; MX2; MYD88; NFKBIA; NFKBIZ; OAS1; OAS2; OAS3; PGLYRP4; PLAUR; PLSCR1; PMAIP1; PML; PTAFR; RAC2; RASGEF1B; RIPK3; RNASE7; RPS6KA5; RSAD2; S100A12; S100A7; S100A8; S100A9; SAA1; SAMHD1; SDC4; SERPINB9; STAT1; STAT2; TLR2; TMEM173; TNFAIP3; TNIP1; TRIM21; TRIM25; UBE2L6; UNC93B1; VEGFC; VNN1; WFDC12; XDH; ZC3H12A; ZC3HAV1 defense response to APOBEC3A; APOBEC3B; BST2; CXCL10; DDX60; EIF2AK2; GBP1; HERC5; IFI16; IFI44L; IFIT1; IFIT2; IFIT3; virus 38 (146) 9.28E-34 1.17E-30 IFIT5; IFITM1; IFNA2; IL23A; IL6; IRF1; IRF9; ISG15; MX1; MX2; OAS1; OAS2; OAS3; OASL; PLSCR1; PMAIP1; PML; RSAD2; SAMHD1; STAT1; STAT2; TMEM173; TRIM25; UNC93B1; ZC3HAV1 (GO:0051607) type I interferon HLA-B; HLA-G; IFI35; IFI6; IFIT1; IFIT2; IFIT3; IFITM1; IFNA2; IRF1; IRF2; IRF7; IRF9; ISG15; MX1; MX2; signaling pathway 25 (63) 8.21E-28 5.18E-25 OAS1; OAS2; OAS3; OASL; SP100; STAT1; STAT2; USP18; XAF1 (GO:0060337) cytokine-mediated GBP1; HERC5; HLA-B; HLA-G; ICAM1; IFI35; IFI6; IFIT1; IFIT2; IFIT3; IFITM1; IFNA2; IFNGR1; IFNGR2; signaling pathway 41 (249) 7.30E-28 6.14E-25 IL1A; IL1B; IL1R2; IL1RL1; IL6; IL7R; IRF1; IRF2; IRF7; IRF9; ISG15; KPNA7; MX1; MX2; MYD88; OAS1; OAS2; OAS3; OASL; PML; PTAFR; SP100; STAT1; STAT2; UBE2L6; USP18; XAF1 (GO:0019221) response to virus ACE2; BCL3; BST2; CXCL10; DDX58; DDX60; EIF2AK2; ICAM1; IFI44; IFIH1; IFIT1; IFIT2; IFIT3; IFITM1; 29 (140) 6.49E-23 3.27E-20 IFNGR1; IFNGR2; IRF7; ITGA2; LCN2; MX1; MX2; MYD88; OAS1; OAS2; OAS3; OASL; RSAD2; SERPINB3; (GO:0009615) ZC3HAV1 Benjamini Hochberg-adjusted p-values are shown.

221 Appendices

Appendix Table 18.4: Mediators in culture supernatants measured by Luminex immunoassays. 24h 72h

(A) (B) (C) (D) (E) (F) (G) (H) - - THP THP - - THP THP

Culture - Mtb Mtb Mtb - Mtb Mtb Mtb conditions Mean Mean PBEC PBEC - PBEC (D)-(C) PBEC PBEC - PBEC (H)-(G) CCL2 0.01 0.01 2.29 2.17 -0.12 0.01 0.02 1.91 1.55 -0.36 CCL20 0.15 0.11 0.21 1.46 1.26 0.31 0.18 0.35 1.69 1.34 CCL4 0.00 0.00 1.31 1.79 0.49 0.00 0.00 1.13 1.52 0.39 CCL5 0.00 0.00 1.05 0.72 -0.33 0.00 0.09 1.82 1.25 -0.57 CCL8 0.00 0.00 1.45 1.24 -0.22 0.00 0.00 4.18 4.78 0.60 CXCL10 0.12 0.15 12.73 13.18 0.46 0.48 7.46 14.80 19.90 5.11 CXCL12 0.01 0.00 1.63 1.96 0.33 0.04 0.03 2.38 1.97 -0.42 G-CSF 0.07 0.03 0.11 0.21 0.11 0.03 0.03 0.11 0.31 0.21 GM-CSF 0.05 0.08 0.08 0.37 0.30 0.11 0.25 0.15 0.86 0.71 IFNβ 0.00 0.01 0.19 0.19 0.00 0.01 0.02 0.36 0.36 0.00 IL1α 0.08 0.08 0.01 0.10 0.09 0.10 0.13 0.01 0.19 0.18 IL1β 0.02 0.02 1.23 4.02 2.80 0.03 0.04 1.59 19.42 17.83 IL6 0.02 0.04 0.02 0.14 0.12 0.04 0.09 0.03 0.64 0.61 IL8 1.54 1.63 3.16 3.82 0.66 2.05 3.79 3.51 1.78 -1.74 SLP1 36.52 23.36 0.48 24.88 24.40 46.16 49.87 0.36 38.25 37.90 TNF 0.00 0.00 0.06 0.05 -0.01 0.00 0.00 0.08 0.10 0.02 Trappin-2 54.67 40.92 0.58 105.14 104.56 190.75 255.43 0.41 531.18 530.77 Mediator levels are shown as mean of two independent experiments in ng/ml.

222 Appendices

Appendix Table 18.5: NLF mediator concentrations in LTBI and ATB patients. LTBI ATB (n=20) (n=27) Median [IQR] Median [IQR] p-value

CCL11 20.37 [14.02 - 29.63] 31.68 [21.87 - 49.90] 0.066 CCL13 0 [0 - 3.77] 6.19 [3.43 - 8.08] <0.001 CCL17 4.48 [2.37 - 9.37] 7.58 [4.23 - 14.12] 0.060 CCL2 67.30 [49.75 - 140.97] 80.03 [44.15 - 121.11] 0.715 CCL22 6.88 [0 - 24.37] 23.26 [11.47 - 44.46] 0.070 CCL26 16.25 [9.48 - 24.11] 18.32 [11.51 - 37.48] 0.159 CCL3 10.26 [0 - 19.57] 7.23 [0.67 - 21.36] 0.862 CCL4 17.66 [10.33 - 39.36] 17.14 [9.60 - 45.98] 0.931 CRP 5635.13 [3398.97 - 18818.06] 15487.12 [3719.39 - 35709.66] 0.098 CXCL10 272.49 [151.50 - 628.10] 879.10 [269.75 - 2519.14] 0.030 GM-CSF 0.19 [0.10 - 0.50] 0.28 [0.21 - 0.70] 0.138 IFNγ 1.57 [0.47 - 2.40] 1.66 [1.02 - 6.72] 0.189 IL10 0.37 [0.05 - 1.16] 0.41 [0.07 - 2.28] 0.674 IL12p40 2.18 [1.40 - 4.45] 3.23 [1.94 - 9.83] 0.098 IL12p70 0.21 [0.13 - 0.39] 0.19 [0.10 - 0.35] 0.974 IL13 6.62 [4.48 - 15.38] 6.09 [4.00 - 15.79] 0.747 IL15 1.96 [1.52 - 2.63] 2.80 [1.82 - 4.32] 0.107 IL16 411.99 [136.52 - 1177.23] 100.18 [50.32 - 815.03] 0.168 IL17 1.61 [0.19 - 2.24] 0.76 [0.31 - 2.40] 0.667 IL1α 93.03 [56.01 - 176.51] 77.80 [46.79 - 151.61] 0.533 IL1β 25.18 [4.62 - 43.89] 9.36 [3.13 - 23.18] 0.162 IL2 0.29 [0.08 - 0.92] 0.85 [0.23 - 2.62] 0.050 IL4 0.06 [0.04 - 0.09] 0.08 [0.06 - 0.13] 0.064 IL5 0.24 [0.17 - 1.38] 0.26 [0.16 - 1.32] 0.755 IL6 4.41 [1.77 - 8.78] 4.33 [1.75 - 10.74] 0.966 IL7 23.60 [15.02 - 34.66] 31.89 [20.68 - 52.75] 0.182 IL8 3146.89 [1529.32 - 9004.78] 1683.93 [881.96 - 5351.68] 0.245 MMP1 3000.08 [1277.84 - 6027.74] 2626.68 [1166.82 - 8912.27] 0.966 MMP3 2424.70 [1165.57 - 3211.79] 1811.40 [779.59 - 3329.79] 0.731 MMP9 1112340.24 [58978.62 - 2164928.67] 100786.84 [23241.72 - 792335.07] 0.111 SAA 1491.90 [855.95 - 2679.13] 1927.86 [1364.65 - 3290.83] 0.277 sICAM1 2454.79 [1373.94 - 3538.09] 3588.95 [1776.34 - 6549.22] 0.091 sVCAM1 1972.13 [1217.76 - 2815.75] 2298.28 [1670.00 - 5309.81] 0.189 TNFα 0.56 [0.22 - 2.49] 0.73 [0.32 - 3.40] 0.378 TNFβ 0.06 [0.03 - 0.11] 0.12 [0.05 - 0.18] 0.043 VEGF 700.40 [445.45 - 972.83] 557.19 [470.99 - 858.70] 0.533 LTBI, Latent tuberculosis infection; ATB, Activ tuberculosis infection; IQR, interquartile range; Mediator concentrations between LTBI and ATB were compared by Mann-Whitney test

223 Appendices

Appendix Table 18.6: NLF mediator concentrations in untreated LTBI and ATB patients. LTBI ATB (n=18) (n=12) Median [IQR] Median [IQR] p-value

CCL11 20.52 [13.02 - 34.54] 28.82 [22.36 - 45.99] 0.185 CCL13 0 [0 - 4.59] 3.89 [3.02 - 6.02] 0.028 CCL17 4.33 [2.27 - 10.47] 7.84 [3.66 - 17.57] 0.172 CCL2 67.30 [47.04 - 116.91] 58.40 [45.05 - 114.57] 0.573 CCL22 4.21 [0 - 19.78] 18.48 [11.73 - 37.49] 0.079 CCL26 16.88 [8.64 - 25.10] 17.87 [11.51 - 24.32] 0.518 CCL3 10.26 [0 - 22.13] 10.72 [6.20 - 20.85] 0.491 CCL4 17.66 [11.90 - 43.65] 29.26 [11.42 - 45.81] 0.518 CRP 5635.13 [2837.85 - 21837.55] 6742.48 [1499.85 - 17035.23] 0.755 CXCL10 272.49 [134.67 - 674.47] 910.60 [305.82 - 1607.94] 0.113 GM-CSF 0.15 [0.10 - 0.50] 0.44 [0.25 - 0.68] 0.053 IFNγ 1.44 [0.39 - 3.23] 1.83 [1.16 - 8.01] 0.134 IL10 0.25 [0.04 - 1.29] 0.30 [0.11 - 1.84] 0.545 IL12p40 2.18 [1.59 - 4.23] 3.38 [2.27 - 5.87] 0.113 IL12p70 0.18 [0.10 - 0.30] 0.15 [0.07 - 0.31] 0.755 IL13 6.32 [4.12 - 14.74] 6.57 [4.06 - 16.00] 1.000 IL15 1.81 [1.46 - 2.78] 2.44 [1.45 - 3.78] 0.391 IL16 384.78 [112.44 - 1334.64] 139.97 [77.93 - 778.02] 0.545 IL17 1.61 [0.21 - 2.57] 1.12 [0.40 - 2.68] 0.787 IL1α 85.67 [53.98 - 170.32] 125.37 [43.05 - 180.93] 0.787 IL1β 16.11 [4.36 - 45.36] 12.74 [7.49 - 44.32] 0.884 IL2 0.26 [0.06 - 0.60] 0.65 [0.15 - 2.43] 0.158 IL4 0.05 [0.04 - 0.09] 0.07 [0.05 - 0.12] 0.200 IL5 0.22 [0.15 - 1.45] 0.26 [0.07 - 1.00] 0.884 IL6 3.55 [1.70 - 9.53] 4.67 [3.07 - 10.57] 0.391 IL7 26.92 [14.76 - 35.03] 23.56 [16.04 - 48.95] 0.983 IL8 2328.11 [1426.16 - 8353.57] 2517.11 [1388.00 - 5141.58] 0.950 MMP1 3000.08 [1218.06 - 5758.52] 2748.04 [1322.92 - 8930.23] 0.819 MMP3 2424.70 [1225.45 - 3132.35] 3065.81 [1559.32 - 4661.18] 0.325 MMP9 649362.30 [52921.54 - 1821403.82] 160686.17 [39246.29 - 2182092.11] 0.632 SAA 1523.46 [889.70 - 2868.59] 2019.42 [1804.64 - 3233.02] 0.391 sICAM1 2557.00 [1325.48 - 3746.74] 4184.40 [2797.54 - 6234.92] 0.035 sVCAM1 1972.13 [1151.16 - 2863.61] 2435.10 [1812.37 - 4024.45] 0.249 TNFα 0.56 [0.19 - 2.08] 0.97 [0.34 - 1.75] 0.391 TNFβ 0.05 [0.03 - 0.11] 0.13 [0.10 - 0.19] 0.017 VEGF 680.00 [431.11 - 1017.71] 573.25 [454.00 - 801.23] 0.465 LTBI, Latent tuberculosis infection; ATB, Activ tuberculosis infection; IQR, interquartile range; Mediator concentrations between LTBI and ATB were compared by Mann-Whitney test

224 Appendices

Appendix Table 18.7: NLF mediator concentrations in untreated ATB patients with and without pulmonary involvemet. ATB with pulmonary involvement ATB without pulmonary involvement

(n=4) (n=8) Median [IQR] Median [IQR] p-value

CCL11 30.59 [17.75 - 54.03] 28.82 [22.36 - 44.69] 0.933 CCL13 4.07 [0.78 - 9.27] 3.89 [3.02 - 6.02] 0.933 CCL17 6.26 [2.55 - 26.62] 7.84 [5.42 - 17.57] 0.808 CCL2 69.89 [50.01 - 111.21] 56.11 [28.61 - 114.94] 0.808 CCL22 32.38 [13.68 - 61.43] 15.31 [9.13 - 30.00] 0.283 CCL26 18.59 [11.51 - 52.53] 17.87 [11.17 - 20.01] 0.683 CCL3 19.25 [5.67 - 101.11] 8.72 [6.20 - 17.29] 0.368 CCL4 45.63 [17.28 - 166.06] 17.26 [11.42 - 41.46] 0.368 CRP 4391.55 [1373.83 - 175098.09] 9620.84 [2178.06 - 17035.23] 0.808 CXCL10 644.65 [168.94 - 3176.02] 1005.36 [310.78 - 1607.94] 0.683 GM-CSF 0.52 [0.27 -4.91] 0.44 [0.15 - 0.61] 0.461 IFNγ 4.81 [1.05 - 12.78] 1.83 [1.47 - 5.49] 1.000 IL10 2.59 [0.60 - 3.25] 0.17 [0.11 - 0.42] 0.154 IL12p40 7.24 [2.62 - 21.73] 3.16 [ 2.27 - 4.14] 0.214 IL12p70 0.38 [0.05 - 0.71] 0.15 [0.09 - 0.26] 0.808 IL13 12.24 [5.35 - 24.91] 5.17 [3.74 - 11.38] 0.214 IL15 1.90 [1.18 - 4.16] 2.91 [1.45 - 3.78] 0.683 IL16 1535.06 [286.33 - 3311.44] 119.57 [74.73 - 185.70] 0.073 IL17 11.13 [0.89 - 27.61] 0.81 [0.40 - 1.90] 0.154 IL1α 125.37 [60.49 - 184.05] 104.75 [32.98 - 180.93] 0.933 IL1β 70.27 [22.34 - 104.64] 10.92 [6.61 - 15.68] 0.048 IL2 2.62 [0.47 - 19.06] 0.38 [0.15 - 1.60] 0.214 IL4 0.08 [0.04 - 0.14] 0.07 [ 0.06 - 0.12] 0.808 IL5 0.55 [0.19 - 1.00] 0.26 [0.02 - 1.06] 0.808 IL6 13.05 [3.67 - 17.77] 4.42 [3.07 - 8.40] 0.214 IL7 20.92 [11.08 - 29.21] 29.82 [16.04 - 56.20] 0.368 IL8 10940.67 [2368.70 - 26191.12] 1548.84 [1002.51 - 4464.93] 0.109 MMP1 4738.71 [1174.86 - 9949.94] 2540.23 [ 1322.92 - 8514.30] 0.933 MMP3 2763.14 [766.00 - 9477.46] 3065.81 [ 2086.09 - 4469.51] 0.808 MMP9 2773202.38 [680675.04 - 2932021.98] 110888.51 [39246.29 - 224701.13] 0.154 SAA 1866.25 [451.16 - 11478.23] 2527.07 [1804.64 - 3233.02] 0.683 sICAM1 4449.98 [1592.74 - 6549.22] 4184.40 [ 3221.42 - 5523.61] 0.808 sVCAM1 3260.18 [1714.75 - 5251.35] 2417.74 [1812.37 - 3407.18] 0.808 TNFα 2.47 [0.69 - 8.71] 0.59 [0.31 - 1.46] 0.154 TNFβ 0.18 [0.11 - 0.21] 0.11 [0.10 - 0.15] 0.368 VEGF 721.94 [449.13 - 1001.12] 564.51 [454.00 - 665.67] 0.283 ATB, Activ tuberculosis infection; IQR, interquartile range; Mediator concentrations between LTBI and ATB were compared by Mann-Whitney test

225 Appendices

Appendix Table 18.8: NLF mediator concentrations in all patients with or without symptoms. No symptoms Symptoms

(n=21) (n=26) Median [IQR] Median [IQR] p-value

CCL11 23.22 [14.05 - 36.36] 30.54 [20.62 - 49.48] 0.123 CCL13 0 [0 - 6.33] 5.12 [3.09 - 8.17] 0.013 CCL17 4.38 [2.35 - 9.04] 7.29 [4.49 - 14.66] 0.089 CCL2 59.71 [41.09 - 98.17] 81.67 [49.51 - 126.11] 0.416 CCL22 5.13 [0 - 23.39] 23.61 [12.25 - 50.12] 0.020 CCL26 16.34 [8.68 - 25.40] 18.23 [11.46 - 33.54] 0.314 CCL3 2.93 [0 - 12.00] 11.35 [5.28 - 27.59] 0.023 CCL4 13.38 [7.60 - 33.53] 23.54 [11.77 - 59.93] 0.074 CRP 6174.46 [3184.47 - 21884.18] 10557.37 [4081.57 - 35380.23] 0.304 CXCL10 266.77 [158.81 - 488.63] 1005.36 [353.38 - 2953.23] 0.003 GM-CSF 0.22 [0.11 - 0.43] 0.38 [0.19 - 0.75] 0.155 IFNγ 1.43 [0.61 - 1.96] 2.29 [1.06 - 7.20] 0.020 IL10 0.23 [0.05 - 0.72] 0.41 [0.06 - 2.40] 0.404 IL12p40 2.09 [1.48 - 4.68] 3.38 [1.99 - 9.83] 0.072 IL12p70 0.19 [0.11 - 0.30] 0.21 [0.13 - 0.38] 0.542 IL13 6.30 [4.09 - 14.81] 7.67 [4.18 - 16.20] 0.684 IL15 1.94 [1.54 - 2.27] 2.91 [1.78 - 4.96] 0.032 IL16 361.72 [77.75 - 684.96] 139.97 [53.63 - 1148.90] 0.716 IL17 0.76 [0.16 - 2.11] 0.96 [0.35 - 2.48] 0.480 IL1α 92.54 [48.72 - 176.13] 79.11 [52.54 - 153.88] 0.898 IL1β 8.70 [4.36 - 42.51] 12.74 [3.79 - 33.10] 0.864 IL2 0.31 [0.13 - 1.43] 0.48 [0.19 - 2.04] 0.374 IL4 0.06 [0.04 - 0.09] 0.09 [0.06 - 0.13] 0.072 IL5 0.26 [0.17 - 1.34] 0.26 [0.14 - 1.38] 0.957 IL6 3.11 [1.69 - 5.64] 4.67 [1.77 - 14.25] 0.171 IL7 24.81 [14.69 - 32.02] 33.54 [20.16 - 53.07] 0.063 IL8 2038.51 [1121.05 - 8762.00] 2517.11 [955.74 - 7046.64] 0.932 MMP1 2405.99 [1337.62 - 5317.62] 2748.04 [1145.47 - 9917.07] 0.549 MMP3 1659.27 [636.38 - 3068.55] 2409.06 [1260.08 - 4284.71] 0.178 MMP9 251572.22 [50286.57 - 1492078.10] 160686.17 [23534.24 - 2389037.62] 0.563 SAA 1491.90 [839.08 - 2471.36] 2019.42 [1266.85 - 3785.44] 0.113 sICAM1 2070.55 [1378.09 - 2777.63] 4102.64 [2350.66 - 7452.88] 0.004 sVCAM1 1787.02 [1249.83 - 2685.64] 2435.10 [1689.58 - 5383.86] 0.042 TNFα 0.54 [0.21 - 1.69 0.97 [0.39 - 3.40] 0.118 TNFβ 0.05 [0.03 - 0.10] 0.12 [0.08 - 0.19] 0.019 VEGF 595.17 [449.89 - 939.88] 579.93 [465.33 - 998.88] 0.765 Symptoms represent cough OR fever OR night sweats OR weight loss, IQR, interquartile range; Mediator concentrations between LTBI and ATB were compared by Mann-Whitney test

226 Appendices

Appendix Table 18.9: NLF mediator concentrations in unexposed healthy subject, TB exposed healthy subjects and suspected TB patients. Unexposed healthy (n=17) TB exposed healthy (n=12) Suspected TB (n=7)

Median [IQR] Median [IQR] Median [IQR] p-value

CCL11 24.21 [13.89 - 40.61] 21.96 [16.33 - 41.21] 19.25 [6.67 - 28.91] 0.568 CCL17 5.19 [2.73 - 22.86] 5.05 [2.46 - 9.03] 1.35 [0.65 - 40.91] 0.767 CCL2 53.25 [36.09 - 157.80] 68.36 [50.91 - 190.87] 54.89 [21.48 - 179.69] 0.399 CCL4 42.66 [12.15 - 114.35] 15.02 [9.84 - 57.56] 11.91 [4.12 - 51.65] 0.231 CRP 4371.77 [1195.29 - 7127.86] 3439.33 [781.04 - 10943.53] 2288.90 [766.18 - 150822.27] 0.916 CXCL10 431.02 [107.52 - 1750.59] 412.21 [132.79 - 1596.90] 115.00 [43.70 - 1659.63] 0.804 IFNγ 1.56 [0.03 - 2.97] 0.91 [0 - 3.36] 1.75 [0.04 - 3.83] 0.861 IL10 0.86 [0.23 - 2.88] 0.25 [0.11 - 0.41] 0.15 [0.11 - 0.63] 0.168 IL12p40 3.22 [1.77 - 7.02] 2.47 [0.94 - 4.23] 1.55 [0.99 - 3.41] 0.364 IL13 4.09 [1.81 - 7.18] 3.65 [1.31 - 4.07] 3.37 [1.92 - 5.16] 0.424 IL15 1.87 [1.19 - 2.83] 1.91 [0.92 - 3.56] 0.69 [0.36 - 5.19] 0.903 IL16 471.16 [213.85 - 2449.62] 488.29 [130.70 - 980.38] 201.74 [114.28 - 628.29] 0.319 IL1α 51.03 [42.41 - 101.73] 75.61 [45.04 - 110.67] 69.09 [15.90 - 170.57] 0.831 IL1β 21.43 [7.03 - 48.26] 14.58 [5.01 - 31.62] 17.86 [6.10 - 31.17] 0.480 IL2 0.14 [0 - 1.06] 0.33 [0.00 - 1.78] 0.16 [0 - 10.25] 0.688 IL6 3.52 [2.04 - 6.91] 1.96 [1.65 - 3.51] 2.87 [0.55 - 8.62] 0.420 IL7 21.50 [8.88 - 49.29] 23.33 [13.46 - 38.11] 9.00 [5.38 - 60.55] 0.916 IL8 1789.00 [560.34 - 3076.38] 1318.28 [457.47 - 2341.78] 1274.30 [449.17 - 3128.31] 0.838 IL8 3571.39 [1398.24 - 8649.41] 3979.52 [1502.02 - 5782.83] 2843.43 [1381.35 - 6505.83] 0.855 MMP1 2590.10 [903.54 - 6685.31] 2174.69 [1487.57 - 2429.05] 962.38 [686.11 - 5106.10] 0.698 MMP3 2870.89 [1302.70 - 4226.03] 2225.31 [1155.64 - 2769.69] 1422.18 [393.84 - 4435.92] 0.400 MMP9 362501.30 [128971.82 - 2860715.26] 205169.49 [108980.70 - 1084284.38] 203294.21 [171112.15 - 875685.38] 0.524 SAA 2750.74 [1034.73 - 13593.27] 1826.72 [1153.72 - 5405.18] 586.03 [387.81 - 24048.92] 0.514 sICAM1 2598.60 [1548.08 - 5234.80] 1689.54 [1065.27 - 2941.13] 1191.18 [476.69 - 4589.51] 0.306

227 Appendices

sVCAM1 1932.18 [1063.58 - 5012.61] 1287.76 [767.90 - 1818.83] 922.97 [429.05 - 3091.60] 0.139 TNFα 1.32 [0.50 - 3.56] 1.20 [0.24 - 1.52] 0.90 [0.16 - 2.09] 0.507 TNFβ 0.05 [0.03 - 0.14] 0.01 [0 - 0.07] 0.06 [0 - 0.12] 0.085 VEGF 812.01 [355.44 - 1392.00] 807.41 [383.19 - 1240.11] 471.14 [175.57 - 1217.96] 0.685 TB, tuberculosis; IQR, interquartile range; Mediator concentrations between all three groups were compared by Kruskal-Wallis test

Appendix Table 18.10: BLF mediator concentrations in unexposed healthy subject, TB exposed healthy subjects and suspected TB patients. Unexposed healthy (n=10) TB exposed healthy (n=9) Suspected TB (n=4)

Median [IQR] Median [IQR] Median [IQR] p-value

CCL11 7.58 [6.40 - 10.81] 9.44 [8.16 - 9.64] 12.84 [11.07 - 17.47] 0.029 CCL17 2.84 [1.88 - 3.70] 2.48 [1.67 - 2.85] 3.71 [1.59 - 5.13] 0.370 CCL2 13.34 [7.31 - 23.98] 21.54 [13.67 - 24.90] 33.01 [14.87 - 69.67] 0.230 CCL4 12.88 [7.79 - 19.88] 21.58 [4.65 - 50.25] 26.50 [5.21 - 114.48] 0.967 CRP 151.23 [59.11 - 287.16] 252.01 [85.69 - 659.44] 460.87 [198.87 - 21931.92] 0.142 CXCL10 50.55 [40.82 - 151.07] 120.03 [79.65 - 205.80] 313.37 [137.50 - 676.48] 0.028 IFNγ 0.11 [0 - 0.97] 0 [0 - 5.23] 2.66 [1.96 - 484.10] 0.041 IL10 0 [0 - 0.07] 0 [0 - 0.16] 0.06 [0.01 - 0.31] 0.384 IL12p40 0.75 [0.30 - 1.55] 0.89 [0.67 -1.83] 2.01 [0.87 - 7.66] 0.260 IL13 0.22 [0 - 0.50] 0.16 [0 - 0.87] 1.33 [0.48 - 2.72] 0.106 IL15 0.20 [0.12 - 0.26] 0.24 [0.16 - 0.30] 0.51 [0.41 - 0.53] 0.019 IL16 68.42 [50.66 - 163.90] 125.10 [64.43 - 166.92] 209.65 [61.02 - 398.24] 0.364 IL1α 8.60 [4.62 - 11.89] 4.43 [3.33 - 6.12] 8.52 [1.92 - 21.31] 0.280 IL1β 2.22 [1.02 - 3.15] 1.18 [0.95 - 2.11] 4.20 [0.95 - 87.60] 0.427 IL2 0.06 [0.02 - 0.19] 0.04 [0 - 0.09] 0.29 [0.04 - 1.80] 0.228 IL6 1.23 [0.94 - 3.18] 1.98 [0.98 - 2.79] 4.95 [3.18 - 11.47] 0.038 IL7 3.82 [3.18 - 5.55] 3.34 [2.77 - 5.41] 6.53 [3.77 - 9.77] 0.261 IL8 181.81 [131.08 - 216.94] 170.20 [136.36 - 199.54] 630.81 [158.32 - 1086.27] 0.189

228 Appendices

IL8 465.90 [287.66 - 579.59] 366.26 [277.28 - 385.60] 920.91 [445.33 - 1775.12] 0.062 MMP1 104.52 [84.10 - 118.60] 121.80 [108.48 - 130.15] 393.88 [299.01 - 31960.52] 0.007 MMP3 59.55 [48.58 - 76.88] 70.17 [50.71 - 98.80] 99.50 [67.69 - 1664.22] 0.143 MMP9 10843.38 [7739.69 - 18730.62] 17021.01 [8316.58 - 22027.85] 46018.91 [6729.92 - 279731.57] 0.596 SAA 430.37 [237.99 - 614.24] 472.94 [430.41 - 628.34] 754.75 [571.91 - 1749.79] 0.093 sICAM1 1423.11 [615.88 - 2229.41] 1832.61 [1288.24 - 3874.85] 2969.93 [2485.21 -3614.78] 0.133 sVCAM1 334.72 [98.29 - 640.74] 358.56 [198.05 - 635.08] 541.64 [173.45 - 938.57] 0.568 TNFα 0.03 [0.01 - 0.09] 0.03 [0.01 - 0.11] 1.58 [0.05 - 3.93] 0.322 TNFβ 0.00 [0 - 0.03] 0.01 [0.00 - 0.05] 0.03 [0.01 - 0.65] 0.132 VEGF 137.64 [110.30 - 185.60] 147.30 [103.61 - 247.26] 243.67 [169.11 - 326.31] 0.198 TB, tuberculosis; IQR, interquartile range; Mediator concentrations between all three groups were compared by Kruskal-Wallis test

229 Appendices

Appendix Table 18.11: NLF mediator concentrations in uninfected and infected TB exposed subjects. Uninfected LTBI (infected) (n=6) (n=6) Median [IQR] Median [IQR] p-value

CCL11 20.77 [12.39 - 52.13] 21.96 [18.58 - 44.42] 0.818 CCL17 5.05 [1.68 - 7.09] 5.20 [2.60 - 17.54] 0.485 CCL2 86.17 [35.90 - 193.16] 68.36 [60.16 - 216.30] 0.937 CCL4 12.38 [6.40 - 16.43] 53.84 [14.64 - 103.73] 0.041 CRP 1083.39 [298.67 - 13237.23] 4357.48 [2801.35 - 15386.10] 0.240 CXCL10 480.91 [214.54 - 991.23] 300.12 [97.66 - 40835.20] 0.937 IFNγ 0.75 [0 - 1.84] 2.07 [0 - 4.36] 0.589 IL10 0.25 [0.09 - 1.60] 0.28 [0.08 - 9.22] 0.818 IL12p40 1.75 [0.53 - 3.81] 3.41 [1.37 - 6.10] 0.310 IL13 2.82 [1.64 - 4.21] 3.70 [1.02 - 5.23] 0.937 IL15 1.91 [0.63 - 2.95] 2.08 [1.09 - 4.49] 0.589 IL16 283.52 [45.96 - 642.93 604.42 [393.91 - 1241.85] 0.240 IL1α 64.19 [33.19 - 132.43] 93.13 [58.88 - 114.85] 0.589 IL1β 9.22 [3.70 - 19.29] 27.40 [6.50 - 38.95] 0.180 IL2 0.33 [0 - 9.94] 0.24 [0.00 - 11.42] 0.818 IL6 1.94 [1.12 - 3.17] 2.75 [1.67 - 6.56] 0.310 IL7 23.22 [9.08 - 29.82] 26.74 [15.05 - 44.79] 0.485 IL8 1104.24 [325.26 - 2554.17] 1628.05 [591.51 - 2517.74] 0.699 IL8 3494.52 [982.96 - 6317.93] 3979.52 [2653.46 - 7166.07] 0.818 MMP1 1666.02 [283.27 - 2766.02] 2272.89 2071.48 - 3045.86] 0.093 MMP3 1730.87 [399.58 - 2643.19] 2690.87 [1406.21 - 4384.35] 0.240 MMP9 178933.87 [42186.30 - 856285.79] 535459.98 [109265.32 - 1300607.09] 0.485 SAA 1230.33 [458.07 - 2241.54] 5303.32 [1446.06 - 13187.64] 0.041 sICAM1 1668.16 [721.89 - 1940.30] 2383.07 [1315.34 - 5369.30] 0.310 sVCAM1 855.76 [408.30 - 1090.54] 1725.92 [1419.77 - 3233.26] 0.002 TNFα 1.25 [0.16 - 1.88] 1.20 [0.31 - 1.63] 0.937 TNFβ 0.01 [0 - 0.10] 0.03 [0 - 0.06] 0.699 VEGF 740.46 204.58 - 1232.02] 915.18 [402.89 - 1312.13] 0.485 LTBI, latent tuberculosis infection; IQR, interquartile range; Mediator concentrations between uninfected and LTBI (infected) TB exposed subjects were compared by Mann-Whitney test.

230 Appendices

Appendix Table 18.12: BLF mediator concentrations in uninfected and infected TB exposed subjects. Uninfected LTBI (infected) (n=5) (n=4) Median [IQR] Median [IQR] p-value

CCL11 9.59 [9.26 - 12.33] 8.30 [6.52 - 9.47] 0.111 CCL17 1.78 [1.05 - 2.72] 2.69 [2.35 - 3.36] 0.190 CCL2 23.38 [14.97 - 25.74] 17.44 [11.80 - 22.73] 0.413 CCL4 7.07 [2.12 - 27.01] 44.19 [24.51 - 66.09] 0.063 CRP 106.13 [48.47 - 750.50] 290.75 [152.90 - 776.60] 0.556 CXCL10 83.40 [74.57 - 120.73] 205.80 [123.98 - 268.70] 0.063 IFNγ 0 [0 - 0] 5.23 [0.07 - 19.97] 0.063 IL10 0 [0 - 0.20] 0 [0 - 0.22] 0.730 IL12p40 0.72 [0.67 - 1.07] 1.83 [0.76 - 3.03] 0.286 IL13 0.43 [0 - 0.87] 0.08 [0 - 0.90] 0.905 IL15 0.23 [0.16 - 0.26] 0.29 [0.15 - 0.37] 0.556 IL16 119.68 [64.33 - 126.95] 166.92 [81.10 - 226.07] 0.190 IL1α 4.43 [2.57 - 6.04] 4.55 [3.79 - 7.48] 0.556 IL1β 1.08 [0.618699 -1.66] 1.73 [1.20 - 3.10] 0.190 IL2 0 [0 - 0.02] 0.09 [0.04 - 0.13] 0.032 IL6 2.29 [1.32 - 3.69] 1.33 [0.92 - 2.69] 0.556 IL7 3.34 [2.63 - 7.28] 3.78 [2.64 - 4.57] 0.905 IL8 170.20 [155.74 - 213.79] 150.40 [108.81 - 194.67] 0.556 IL8 366.26 [267.50 - 511.42] 338.85 [265.82 -386.20] 1.000 MMP1 112.93 [53.00 - 123.76] 130.15 [115.38 -765.45] 0.111 MMP3 51.06 [43.62 - 68.04] 98.80 [76.53 -127.40] 0.032 MMP9 17021.01 [4753.56 - 19486.71] 16969.23 [8326.03 -46508.53] 0.556 SAA 472.94 [344.88 - 557.75] 557.68 [430.40 - 1479.18] 0.413 sICAM1 2624.90 [1868.61 - 5266.00] 1446.15 [953.35 - 1756.14] 0.111 sVCAM1 405.68 [221.89 - 767.76] 334.72 [141.63 - 582.85] 0.556 TNFα 0.03 [0.01 - 0.05] 0.09 [0.00 - 0.50] 0.730 TNFβ 0.03 [0 - 0.05] 0.01 [0.00 - 0.04] 1.000 VEGF 245.13 [106.72 - 299.69] 129.94 [88.11 - 170.88] 0.286 LTBI, latent tuberculosis infection; IQR, interquartile range; Mediator concentrations between uninfected and LTBI (infected) TB exposed subjects were compared by Mann-Whitney test.

231 Appendices

Appendix Table 18.13: Genes differentially expressed between TB exposed healthy subjects and unexposed healthy subjects (‘Exposure signature’). Expression Fold adjusted Gene symbol Entrez ID Gene name affected by change p-value smoking ACPP 55 2.51 3.28E-02 acid phosphatase, prostate n/r AHRR 57491 7.32 5.25E-03 aryl-hydrocarbon receptor repressor n/r aldo-keto reductase family 1, member B10 (aldose (380, 381, AKR1B10 57016 11.94 1.31E-03 reductase) 392, 394) AKR1B15 441282 10.90 3.32E-03 aldo-keto reductase family 1, member B15 n/r aldo-keto reductase family 1, member C1 (380, 381, AKR1C1 1645 4.36 3.86E-02 [Source:HGNC Symbol;Acc:HGNC:384] 392–394) (380, 381, AKR1C2 1646 7.52 1.38E-02 aldo-keto reductase family 1, member C2 392–394) ankyrin repeat domain 20 family member A9, ANKRD20A9P 284232 4.71 2.15E-02 n/r pseudogene (380, 392, AZGP1 563 6.72 2.15E-02 alpha-2-glycoprotein 1, zinc-binding 394) UDP-GlcNAc:betaGal beta-1,3-N- B3GNT6 192134 7.51 2.57E-02 (394) acetylglucosaminyltransferase 6 BPIFB2 80341 19.77 1.38E-05 BPI fold containing family B member 2 n/r (380, 393, CA12 771 5.39 2.15E-02 carbonic anhydrase XII 394) calcium binding tyrosine-(Y)-phosphorylation (380, 381, CABYR 26256 9.20 5.36E-04 regulated 394) calcium channel, voltage-dependent, gamma CACNG4 27092 6.14 2.15E-02 (394) subunit 4 (380, 381, CBR1 873 4.01 3.86E-02 carbonyl reductase 1 393, 394) CCNJL 79616 6.33 8.65E-06 cyclin J-like n/r CDR1 1038 6.73 2.32E-02 cerebellar degeneration related protein 1 n/r carcinoembryonic antigen-related cell adhesion CEACAM5 1048 6.92 3.36E-02 (380, 394) molecule 5 carcinoembryonic antigen-related cell adhesion (380, 393, CEACAM6 4680 3.44 4.85E-02 molecule 6 (non-specific cross reacting antigen) 394) cell growth regulator with EF-hand domain 1 CGREF1 10669 9.91 5.39E-03 n/r [Source:HGNC Symbol;Acc:HGNC:16962] CHAD 1101 3.07 2.32E-02 chondroadherin (394) (380, 381, CLDN10 9071 4.13 2.32E-02 claudin 10 393, 394) CNGB1 1258 13.66 5.36E-04 cyclic nucleotide gated channel beta 1 (381, 394) (380, 381, CYP1B1 1545 8.13 2.15E-02 cytochrome P450 family 1 subfamily B member 1 394, 447) DnaJ heat shock protein family (Hsp40) member DNAJC10 54431 1.91 4.32E-02 n/r C10 DnaJ heat shock protein family (Hsp40) member DNAJC12 56521 6.46 2.32E-02 (394) C12 ELMOD1 55531 9.00 1.09E-03 ELMO/CED-12 domain containing 1 (394) ectonucleoside triphosphate diphosphohydrolase ENTPD4 9583 1.60 2.98E-02 n/r 4 ectonucleoside triphosphate diphosphohydrolase ENTPD8 377841 5.17 1.57E-03 n/r 8 EPHX3 79852 0.38 2.15E-02 epoxide hydrolase 3 n/r FABP5 2171 0.23 3.91E-02 fatty acid binding protein 5 (psoriasis-associated) n/r FAM177B 400823 18.24 8.65E-06 family with sequence similarity 177 member B n/r FBXO16 157574 3.54 2.32E-02 F-box protein 16 n/r

232 Appendices

FCRL6 343413 0.20 2.15E-02 Fc receptor-like 6 n/r GNLY 10578 0.17 2.11E-02 granulysin n/r GRB10 2887 3.37 7.98E-03 growth factor receptor bound protein 10 n/r HID1 283987 2.23 4.32E-02 HID1 domain containing n/r LINC00942 100292680 7.86 7.85E-03 long intergenic non-protein coding RNA 942 n/r LOC101927136 101927136 9.33 7.91E-03 uncharacterized LOC101927136 n/r LOC344887 344887 9.66 3.89E-03 NmrA-like family domain containing 1 pseudogene n/r LOXHD1 125336 7.36 2.57E-02 lipoxygenase homology domains 1 n/r lung cancer associated transcript 1 (non-protein LUCAT1 100505994 6.54 2.84E-02 n/r coding) (380, 381, ME1 4199 4.68 4.85E-02 malic enzyme 1, NADP(+)-dependent, cytosolic 394, 447) MEP1A 4224 6.53 3.28E-02 meprin A subunit alpha n/r MIA3 375056 2.17 2.34E-02 melanoma inhibitory activity family member 3 n/r MIR6723 102465432 25.65 9.37E-08 microRNA 6723 n/r MUCL1 118430 8.64 3.92E-03 mucin-like 1 (394) NOS3 4846 4.62 2.39E-02 nitric oxide synthase 3 n/r NPDC1 56654 2.49 9.60E-03 neural proliferation, differentiation and control, 1 (392) NPTX2 4885 0.26 4.99E-02 neuronal pentraxin II n/r NTN4 59277 1.91 2.15E-02 netrin 4 [Source:HGNC Symbol;Acc:HGNC:13658] n/r OR10G2 26534 7.00 3.63E-02 olfactory receptor family 10 subfamily G member 2 n/r OSGIN1 29948 5.24 5.25E-03 oxidative stress induced growth inhibitor 1 n/r PANX2 56666 3.37 4.32E-02 pannexin 2 (394) PDGFRL 5157 3.97 2.95E-02 platelet-derived growth factor receptor-like n/r PGM3 5238 1.99 1.16E-02 phosphoglucomutase 3 n/r PIP 5304 0.26 2.15E-02 prolactin-induced protein n/r PLPP5 84513 1.67 3.63E-02 phospholipid phosphatase 5 n/r PTGER4 5734 0.50 2.15E-02 prostaglandin E receptor 4 (394) PYCR1 5831 4.13 3.90E-02 pyrroline-5-carboxylate reductase 1 n/r RRBP1 6238 2.02 2.95E-02 ribosome binding protein 1 n/r solute carrier family 7 (anionic amino acid (380, 381, SLC7A11 23657 10.04 3.92E-03 transporter light chain, xc- system), member 11 394) SRXN1 140809 3.28 2.15E-02 sulfiredoxin 1 (394) ST3GAL4-AS1 399972 4.58 4.93E-02 ST3GAL4 antisense RNA 1 (head to head) n/r SUCNR1 56670 0.15 3.01E-04 succinate receptor 1 n/r TEPP 374739 5.91 3.89E-03 testis, prostate and placenta expressed n/r TFF1 7031 7.91 2.15E-02 trefoil factor 1 (394) TMCO5A 145942 4.80 3.28E-02 transmembrane and coiled-coil domains 5A n/r TRIM16L 147166 3.46 4.93E-02 tripartite motif containing 16-like (392) ‘Expression affected by smoking’ indicates if genes were associated with smoking in any of the referenced studies; n/r, not reported; Benjamini Hochberg-adjusted p-values of differentially expressed genes are shown.

233 Appendices

Appendix Table 18.14: The most significantly differentially expressed genes between suspected TB patients and unexposed healthy subjects (‘Suspected TB signature’). Gene Entrez Fold adjusted Gene name symbol ID change p-value ADAM8 101 2.72 3.57E-04 ADAM metallopeptidase domain 8 ADAMTS2 9509 3.33 2.63E-04 ADAM metallopeptidase with thrombospondin type 1 motif 2 ADGRE2 30817 2.73 1.07E-04 adhesion G protein-coupled receptor E2 ADGRG3 222487 3.02 9.77E-04 adhesion G protein-coupled receptor G3 ADM 133 3.26 2.82E-04 adrenomedullin AFF2 2334 3.83 5.89E-06 AF4/FMR2 family member 2 AIM2 9447 3.06 7.40E-04 absent in melanoma 2 ALAS2 212 5.55 7.92E-08 5'-aminolevulinate synthase 2 ANKRD22 118932 3.04 3.77E-04 ankyrin repeat domain 22 ANKRD33B 651746 3.05 5.35E-04 ankyrin repeat domain 33B apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like APOBEC3A 200315 3.68 7.02E-05 3A apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like APOBEC3A 100913187 3.62 8.85E-05 3A apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like APOBEC3B 9582 3.15 3.97E-05 3B APOBR 55911 2.43 9.87E-04 apolipoprotein B receptor AQP9 366 3.01 9.70E-04 aquaporin 9 ARID3A 1820 2.84 4.22E-04 AT-rich interaction domain 3A BCL2A1 597 3.16 5.57E-04 BCL2-related protein A1 C10orf55 414236 5.64 7.92E-08 chromosome 10 open reading frame 55 C15orf48 84419 3.10 7.34E-04 chromosome 15 open reading frame 48 C5orf58 133874 3.84 2.18E-05 chromosome 5 open reading frame 58 CARD16 114769 2.86 2.38E-04 caspase recruitment domain family member 16 CARD17 440068 3.96 1.79E-05 caspase recruitment domain family member 17 CASP1 834 2.63 1.44E-04 caspase 1 CASS4 57091 3.05 1.71E-04 Cas scaffolding protein family member 4 CATSPERB 79820 2.35 8.23E-04 catsper channel auxiliary subunit beta CCL2 6347 3.35 2.62E-04 chemokine (C-C motif) ligand 2 CCR1 1230 3.25 3.80E-04 chemokine (C-C motif) receptor 1 CCRL2 9034 3.57 1.07E-04 chemokine (C-C motif) receptor-like 2 CD177 57126 3.28 3.06E-04 CD177 molecule CD22 933 4.17 9.46E-06 CD22 molecule CEACAM3 1084 3.25 3.51E-04 carcinoembryonic antigen-related cell adhesion molecule 3 CHGB 1114 0.39 7.04E-04 chromogranin B CHRM4 1132 3.21 3.87E-04 cholinergic receptor, muscarinic 4 CLEC4D 338339 3.74 3.95E-05 C-type lectin domain family 4 member D CLEC4E 26253 3.57 8.85E-05 C-type lectin domain family 4 member E CMKLR1 1240 3.09 9.53E-05 chemerin chemokine-like receptor 1 CRTAC1 55118 3.04 9.85E-04 cartilage acidic protein 1 colony stimulating factor 2 receptor, beta, low-affinity CSF2RB 1439 3.17 4.62E-04 (granulocyte-macrophage)

234 Appendices

CSF3R 1441 3.43 1.84E-04 colony stimulating factor 3 receptor CSRNP1 64651 2.65 6.71E-04 cysteine-serine-rich nuclear protein 1 CXCL8 3576 3.22 3.83E-04 chemokine (C-X-C motif) ligand 8 CXCR1 3577 3.10 7.48E-04 chemokine (C-X-C motif) receptor 1 CXCR2 3579 3.28 2.83E-04 chemokine (C-X-C motif) receptor 2 CXorf21 80231 2.94 3.67E-04 chromosome X open reading frame 21 DDX60L 91351 2.97 2.16E-05 DEAD (Asp-Glu-Ala-Asp) box polypeptide 60-like DENND5A 23258 2.70 5.06E-04 DENN/MADD domain containing 5A DEPTOR 64798 0.44 1.64E-04 DEP domain containing MTOR-interacting protein DYSF 8291 4.08 1.41E-05 dysferlin E2F3 1871 2.40 4.36E-04 E2F transcription factor 3 EDN1 1906 3.18 2.42E-04 endothelin 1 EFHD1 80303 0.37 2.97E-04 EF-hand domain family member D1 EVI2B 2124 2.47 3.79E-04 ecotropic viral integration site 2B FAM111B 374393 3.94 1.95E-05 family with sequence similarity 111 member B FBN3 84467 2.86 9.02E-04 fibrillin 3 FCAR 2204 3.73 3.75E-05 Fc fragment of IgA receptor FCGR2A 2212 2.99 7.61E-04 Fc fragment of IgG, low affinity IIa, receptor (CD32) FCGR2A 9103 2.40 5.35E-04 Fc fragment of IgG, low affinity IIa, receptor (CD32) FCGR3B 2215 4.13 1.23E-05 Fc fragment of IgG, low affinity IIIb, receptor (CD16b) FFAR2 2867 3.77 4.11E-05 free fatty acid receptor 2 FLT1 2321 4.04 8.55E-06 fms-related tyrosine kinase 1 FPR2 2358 3.03 9.77E-04 formyl peptide receptor 2 G0S2 50486 3.94 2.18E-05 G0/G1 switch 2 GBP5 115362 3.11 1.07E-04 guanylate binding protein 5 GLT1D1 144423 4.10 1.37E-05 glycosyltransferase 1 domain containing 1 GNG2 54331 3.51 1.66E-05 guanine nucleotide binding protein (G protein), gamma 2 GPR65 8477 3.13 1.64E-04 G protein-coupled receptor 65 GRK5 2869 2.62 5.89E-06 G protein-coupled receptor kinase 5 HAL 3034 3.09 1.64E-04 histidine ammonia-lyase HBA1 3039 4.42 5.14E-06 hemoglobin subunit alpha 1 HBA2 3040 4.39 5.14E-06 hemoglobin subunit alpha 2 HCAR3 8843 3.88 2.95E-05 hydroxycarboxylic acid receptor 3 HERC5 51191 2.61 4.52E-04 HECT and RLD domain containing E3 ubiquitin protein ligase 5 HIF1A-AS2 100750247 3.53 3.37E-05 HIF1A antisense RNA 2 HSPA6 3310 4.73 5.14E-07 heat shock protein family A (Hsp70) member 6 ICAM1 3383 3.65 2.95E-05 intercellular adhesion molecule 1 IFI44 10561 2.12 5.89E-04 interferon induced protein 44 IFIT2 3433 4.06 1.44E-06 interferon induced protein with tetratricopeptide repeats 2 IFIT3 3437 2.98 2.32E-04 interferon induced protein with tetratricopeptide repeats 3 IFITM2 10581 3.75 1.51E-05 interferon induced transmembrane protein 2 IGSF6 10261 3.39 2.18E-05 immunoglobulin superfamily member 6 IL18R1 8809 2.60 3.97E-05 interleukin 18 receptor 1

235 Appendices

IL1B 3553 3.65 7.64E-05 interleukin 1 beta IL1R2 7850 3.10 7.55E-04 interleukin 1 receptor, type II IL1RN 3557 3.49 1.56E-04 interleukin 1 receptor antagonist INSRR 3645 0.34 8.22E-04 insulin receptor-related receptor IRAK2 3656 3.91 1.66E-05 interleukin 1 receptor associated kinase 2 ITPRIP 85450 2.98 7.02E-05 inositol 1,4,5-trisphosphate receptor interacting protein KCNJ15 3772 3.02 1.50E-04 potassium channel, inwardly rectifying subfamily J, member 15 LAT2 7462 2.63 2.69E-04 linker for activation of T-cells family member 2 LCP2 3937 4.18 5.23E-06 lymphocyte cytosolic protein 2 leukocyte immunoglobulin-like receptor, subfamily A (with TM LILRA2 11027 2.91 9.84E-04 domain), member 2 leukocyte immunoglobulin-like receptor, subfamily B (with TM LILRB2 10288 2.77 9.85E-04 and ITIM domains), member 2 leukocyte immunoglobulin-like receptor, subfamily B (with TM LILRB3 10288 2.77 9.85E-04 and ITIM domains), member 3 LINC00877 285286 3.32 2.97E-04 long intergenic non-protein coding RNA 877 LOC100499194 100499194 3.11 2.73E-04 uncharacterized LOC100499194 LPCAT1 79888 4.31 3.45E-06 lysophosphatidylcholine acyltransferase 1 LRRK2 120892 2.44 5.83E-04 leucine-rich repeat kinase 2 LUM 4060 3.28 3.13E-04 lumican v-maf avian musculoaponeurotic fibrosarcoma oncogene MAFF 23764 3.85 1.09E-05 homolog F MCM10 55388 3.12 2.50E-04 minichromosome maintenance 10 replication initiation factor MEFV 4210 3.53 1.07E-04 Mediterranean fever MICB 4277 2.69 4.57E-04 MHC class I polypeptide-related sequence B MIR449C 100313923 3.31 1.17E-04 microRNA 449c MLKL 197259 2.54 4.15E-04 mixed lineage kinase domain-like MMP25 64386 3.46 3.44E-05 matrix metallopeptidase 25 MMP9 4318 3.17 5.06E-04 matrix metallopeptidase 9 MNDA 4332 3.27 1.92E-04 myeloid cell nuclear differentiation antigen MUC6 4588 2.44 8.96E-04 mucin 6, oligomeric mucus/gel-forming MX2 4600 2.88 7.72E-04 MX dynamin-like GTPase 2 MXD1 4084 4.05 6.10E-06 MAX dimerization protein 1 NAMPT 10135 3.18 1.71E-04 nicotinamide phosphoribosyltransferase NCF1 653361 3.68 1.26E-05 neutrophil cytosolic factor 1 NCF1B 654816 3.96 5.14E-06 neutrophil cytosolic factor 1B pseudogene NCF1C 654817 3.81 7.81E-06 neutrophil cytosolic factor 1C pseudogene NCF4 4689 3.26 6.73E-05 neutrophil cytosolic factor 4 NEIL3 55247 3.69 1.66E-05 nei-like DNA glycosylase 3 NETO2 81831 2.89 3.86E-04 neuropilin and tolloid like 2 NFE2 4778 3.07 8.07E-04 nuclear factor, erythroid 2 nuclear factor of kappa light polypeptide gene enhancer in B-cells NFKB2 4791 2.67 8.27E-04 2 (p49/p100) NLRP3 114548 2.79 8.23E-04 NLR family, pyrin domain containing 3 NOD2 64127 2.66 1.72E-04 nucleotide binding oligomerization domain containing 2 NTNG2 84628 3.36 2.53E-04 netrin G2

236 Appendices

OSM 5008 3.54 8.40E-05 oncostatin M P2RY14 9934 3.10 1.64E-04 purinergic receptor P2Y, G-protein coupled, 14 PDE4B 5142 3.63 4.89E-05 phosphodiesterase 4B PER3 8863 0.49 3.30E-04 period circadian clock 3 PHACTR1 221692 3.63 4.11E-05 phosphatase and actin regulator 1 PI3 5266 3.07 7.62E-04 peptidase inhibitor 3 PIK3AP1 118788 3.17 1.92E-04 phosphoinositide-3-kinase adaptor protein 1 PIK3R5 23533 2.99 5.94E-04 phosphoinositide-3-kinase regulatory subunit 5 PIM1 5292 2.16 1.19E-04 Pim-1 proto-oncogene, serine/threonine kinase PIP 5304 0.35 5.14E-06 prolactin-induced protein PLAUR 5329 3.17 5.57E-04 plasminogen activator, urokinase receptor PLEK 5341 4.38 5.14E-06 pleckstrin PLEKHG2 64857 2.93 1.64E-04 pleckstrin homology and RhoGEF domain containing G2 PLXNC1 10154 2.29 5.89E-04 plexin C1 PPBP 5473 3.04 1.64E-04 pro-platelet basic protein PPIF 10105 2.52 5.62E-04 peptidylprolyl isomerase F PPP1R18 170954 2.53 7.72E-04 protein phosphatase 1 regulatory subunit 18 PSTPIP2 9050 2.77 1.73E-04 proline-serine-threonine phosphatase interacting protein 2 PTAFR 5724 2.72 2.39E-05 platelet-activating factor receptor prostaglandin-endoperoxide synthase 2 (prostaglandin G/H PTGS2 5743 3.40 2.17E-04 synthase and cyclooxygenase) PTPRE 5791 2.50 2.37E-04 protein tyrosine phosphatase, receptor type, E RASGRP4 115727 2.80 2.21E-04 RAS guanyl releasing protein 4 RASSF2 9770 3.92 5.14E-06 Ras association (RalGDS/AF-6) domain family member 2 RGS2 5997 3.00 4.26E-04 regulator of G-protein signaling 2 RHOH 399 2.25 7.04E-04 ras homolog family member H RNASE1 6035 3.33 7.02E-05 ribonuclease, RNase A family, 1 (pancreatic) RSAD2 91543 3.17 6.27E-05 radical S-adenosyl methionine domain containing 2 S100A12 6283 3.17 3.67E-04 S100 calcium binding protein A12 SAMSN1 64092 3.29 1.07E-04 SAM domain, SH3 domain and nuclear localization signals 1 SCARF1 8578 3.29 4.11E-05 scavenger receptor class F member 1 SELL 6402 4.14 1.23E-05 selectin L SERPINB9 5272 3.06 1.56E-04 serpin peptidase inhibitor, clade B (ovalbumin), member 9 serpin peptidase inhibitor, clade E (nexin, plasminogen activator SERPINE1 5054 3.58 1.94E-05 inhibitor type 1), member 1 small glutamine-rich tetratricopeptide repeat (TPR)-containing, SGTB 54557 3.29 1.12E-04 beta SHROOM1 134549 2.23 8.23E-04 shroom family member 1 SIGLEC10 89790 2.29 4.15E-04 sialic acid binding Ig-like lectin 10 solute carrier family 24 (sodium/potassium/calcium exchanger), SLC24A3 57419 2.29 2.36E-04 member 3 solute carrier family 25 (mitochondrial iron transporter), member SLC25A37 51312 2.44 2.63E-04 37 solute carrier family 2 (facilitated glucose transporter), member SLC2A14 144195 3.18 5.35E-04 14 SLC2A3 6515 3.57 9.53E-05 solute carrier family 2 (facilitated glucose transporter), member 3 SLC43A3 29015 2.67 5.92E-04 solute carrier family 43 member 3

237 Appendices

solute carrier family 4 (anion exchanger), member 1 (Diego blood SLC4A1 6521 4.50 1.57E-06 group) solute carrier family 5 (sodium/monocarboxylate cotransporter), SLC5A12 159963 3.17 5.56E-04 member 12 solute carrier family 7 (amino acid transporter light chain, L SLC7A5 8140 2.98 3.35E-04 system), member 5 SOD2 6648 3.04 3.77E-04 superoxide dismutase 2, mitochondrial SP140 11262 2.64 2.63E-04 SP140 nuclear body protein SPHK1 8877 2.61 3.19E-04 sphingosine kinase 1 SSTR3 6753 2.77 6.17E-04 somatostatin receptor 3 TACC3 10460 2.40 2.50E-04 transforming, acidic coiled-coil containing protein 3 TAGAP 117289 4.92 5.14E-07 T-cell activation RhoGTPase activating protein TEF 7008 0.50 1.64E-04 thyrotrophic embryonic factor TESC 54997 2.76 8.27E-04 tescalcin TMEM140 55281 2.40 9.58E-04 transmembrane protein 140 TNFAIP6 7130 3.12 3.27E-04 TNF alpha induced protein 6 TNFRSF1B 7133 3.91 2.02E-05 tumor necrosis factor receptor superfamily member 1B TNFSF13B 10673 2.89 4.19E-04 tumor necrosis factor superfamily member 13b TNFSF14 8740 3.93 1.66E-05 tumor necrosis factor superfamily member 14 TREML2 79865 3.72 5.77E-05 triggering receptor expressed on myeloid cells like 2 TREML3P 340206 3.00 8.25E-04 triggering receptor expressed on myeloid cells like 3, pseudogene TRIM58 25893 3.43 1.92E-04 tripartite motif containing 58 WDR62 284403 2.76 1.64E-04 WD repeat domain 62 ZDHHC18 84243 2.43 5.92E-04 zinc finger, DHHC-type containing 18 ZEB1 6935 2.31 7.72E-04 zinc finger E-box binding homeobox 1 ZNF438 220929 2.49 9.01E-04 zinc finger protein 438 All differentially expressed genes at a fold change > 2 and adjusted p-value < 0.001 are shown; Benjamini Hochberg-adjusted p-values of differentially expressed genes are shown.

238 Appendices

Appendix Table 18.15: Differentially expressed genes in suspected TB patients ex vivo and PBECs co-cultured with Mtb-infected monocytes in vitro. adjusted Fold change p-value Gene Entrez (suspected TB (suspected TB Gene name symbol ID vs unexposed vs unexposed healthy) healthy) ADAM8 101 2.72 3.57E-04 ADAM metallopeptidase domain 8 ADGRE2 30817 2.73 1.07E-04 adhesion G protein-coupled receptor E2 ANKRD22 118932 3.04 3.77E-04 ankyrin repeat domain 22 apolipoprotein B mRNA editing enzyme, catalytic APOBEC3A 200315 3.68 7.02E-05 polypeptide-like 3A apolipoprotein B mRNA editing enzyme, catalytic APOBEC3B 9582 3.15 3.97E-05 polypeptide-like 3B BCL2A1 597 3.16 5.57E-04 BCL2-related protein A1 BID 637 2.02 2.41E-03 BH3 interacting domain death agonist CASP4 837 1.59 1.63E-03 caspase 4 CD274 29126 2.57 1.49E-03 CD274 molecule CXCL10 3627 2.14 3.70E-02 chemokine (C-X-C motif) ligand 10 CXCL11 6373 2.08 4.74E-02 chemokine (C-X-C motif) ligand 11 CXCL8 3576 3.22 3.83E-04 chemokine (C-X-C motif) ligand 8 DCN1, defective in cullin neddylation 1, domain containing DCUN1D3 123879 1.61 7.17E-03 3 DDX58 23586 1.81 2.51E-03 DEAD (Asp-Glu-Ala-Asp) box polypeptide 58 DDX60L 91351 2.97 2.16E-05 DEAD (Asp-Glu-Ala-Asp) box polypeptide 60-like EDN1 1906 3.18 2.42E-04 endothelin 1 EMP1 2012 1.92 3.96E-02 epithelial membrane protein 1 EPSTI1 94240 2.17 1.44E-02 epithelial stromal interaction 1 (breast) G0S2 50486 3.94 2.18E-05 G0/G1 switch 2 GBP1 2633 2.07 3.47E-03 guanylate binding protein 1, interferon-inducible GBP5 115362 3.11 1.07E-04 guanylate binding protein 5 GCH1 2643 1.90 7.31E-03 GTP cyclohydrolase 1 GK 2710 1.55 3.02E-02 glycerol kinase GRK5 2869 2.62 5.89E-06 G protein-coupled receptor kinase 5 HBEGF 1839 2.07 9.46E-03 heparin-binding EGF-like growth factor HCAR2 338442 2.58 1.74E-03 hydroxycarboxylic acid receptor 2 HCAR3 8843 3.88 2.95E-05 hydroxycarboxylic acid receptor 3 HELZ2 85441 1.56 2.96E-02 helicase with zinc finger 2, transcriptional coactivator HECT and RLD domain containing E3 ubiquitin protein HERC5 51191 2.61 4.52E-04 ligase 5 ICAM1 3383 3.65 2.95E-05 intercellular adhesion molecule 1 IFI35 3430 1.54 4.57E-02 interferon induced protein 35 IFI44 10561 2.12 5.89E-04 interferon induced protein 44 IFI44L 10964 2.49 6.56E-03 interferon induced protein 44 like IFIH1 64135 1.86 3.42E-03 interferon induced, with helicase C domain 1

239 Appendices

IFIT1 3434 1.94 3.19E-02 interferon induced protein with tetratricopeptide repeats 1 IFIT2 3433 4.06 1.44E-06 interferon induced protein with tetratricopeptide repeats 2 IFIT3 3437 2.98 2.32E-04 interferon induced protein with tetratricopeptide repeats 3 IFITM1 8519 2.10 2.29E-02 interferon induced transmembrane protein 1 interferon gamma receptor 2 (interferon gamma IFNGR2 3460 1.75 1.16E-02 transducer 1) IL1B 3553 3.65 7.64E-05 interleukin 1 beta IL1R2 7850 3.10 7.55E-04 interleukin 1 receptor, type II IL1RL1 9173 2.17 2.63E-02 interleukin 1 receptor-like 1 IL1RN 3557 3.49 1.56E-04 interleukin 1 receptor antagonist IRAK2 3656 3.91 1.66E-05 interleukin 1 receptor associated kinase 2 IRF7 3665 2.14 2.01E-03 interferon regulatory factor 7 ISG15 9636 2.43 8.18E-03 ISG15 ubiquitin-like modifier ITGA2 3673 0.69 1.48E-02 integrin subunit alpha 2 ITGA5 3678 2.36 8.58E-03 integrin subunit alpha 5 LYN 4067 1.80 1.81E-02 LYN proto-oncogene, Src family tyrosine kinase MLKL 197259 2.54 4.15E-04 mixed lineage kinase domain-like MMP1 4312 2.24 2.59E-02 matrix metallopeptidase 1 MMP12 4321 2.58 5.74E-03 matrix metallopeptidase 12 MMP9 4318 3.17 5.06E-04 matrix metallopeptidase 9 MX1 4599 2.28 1.15E-03 MX dynamin-like GTPase 1 MX2 4600 2.88 7.72E-04 MX dynamin-like GTPase 2 N4BP1 9683 1.67 4.39E-03 NEDD4 binding protein 1 NAGK 55577 1.47 1.88E-02 N-acetylglucosamine kinase nuclear factor of kappa light polypeptide gene enhancer in NFKB2 4791 2.67 8.27E-04 B-cells 2 (p49/p100) nuclear factor of kappa light polypeptide gene enhancer in NFKBIA 4792 2.53 3.28E-03 B-cells inhibitor, alpha nuclear factor of kappa light polypeptide gene enhancer in NFKBIZ 64332 1.81 2.63E-02 B-cells inhibitor, zeta NIPAL4 348938 2.31 2.00E-02 NIPA-like domain containing 4 NMI 9111 1.49 8.58E-03 N-myc and STAT interactor OAS3 4940 2.29 2.15E-03 2'-5'-oligoadenylate synthetase 3 PARP14 54625 1.56 2.74E-02 poly(ADP-ribose) polymerase family member 14 PARP9 83666 1.61 4.33E-02 poly(ADP-ribose) polymerase family member 9 PHF11 51131 1.44 1.01E-03 PHD finger protein 11 PI3 5266 3.07 7.62E-04 peptidase inhibitor 3 PLAT 5327 2.04 1.02E-02 plasminogen activator, tissue PLAU 5328 2.73 2.31E-03 plasminogen activator, urokinase PLAUR 5329 3.17 5.57E-04 plasminogen activator, urokinase receptor PLSCR1 5359 1.80 9.57E-03 phospholipid scramblase 1 PNP 4860 1.73 7.60E-03 purine nucleoside phosphorylase PPIF 10105 2.52 5.62E-04 peptidylprolyl isomerase F

240 Appendices

PTAFR 5724 2.72 2.39E-05 platelet-activating factor receptor QPCT 25797 2.30 4.51E-03 glutaminyl-peptide cyclotransferase ras-related C3 botulinum toxin substrate 2 (rho family, RAC2 5880 2.18 9.74E-03 small GTP binding protein Rac2) RNF19B 127544 1.63 3.69E-03 ring finger protein 19B RSAD2 91543 3.17 6.27E-05 radical S-adenosyl methionine domain containing 2 S100A12 6283 3.17 3.67E-04 S100 calcium binding protein A12 S100A8 6279 2.42 1.23E-02 S100 calcium binding protein A8 S100A9 6280 2.27 2.24E-02 S100 calcium binding protein A9 SAMD9L 219285 1.86 4.30E-03 sterile alpha motif domain containing 9-like SAT1 6303 1.79 6.34E-03 spermidine/spermine N1-acetyltransferase 1 semaphorin 7A, GPI membrane anchor (John Milton Hagen SEMA7A 8482 1.94 3.50E-02 blood group) SERPINB9 5272 3.06 1.56E-04 serpin peptidase inhibitor, clade B (ovalbumin), member 9 SLC43A3 29015 2.67 5.92E-04 solute carrier family 43 member 3 SOD2 6648 3.04 3.77E-04 superoxide dismutase 2, mitochondrial STAT2 6773 1.38 1.98E-02 signal transducer and activator of transcription 2 transporter 1, ATP-binding cassette, sub-family B TAP1 6890 1.89 2.63E-02 (MDR/TAP) transporter 2, ATP-binding cassette, sub-family B TAP2 6891 1.76 9.87E-03 (MDR/TAP) TLR2 7097 2.39 1.98E-03 toll-like receptor 2 TMEM140 55281 2.40 9.58E-04 transmembrane protein 140 TRIM25 7706 1.54 2.03E-03 tripartite motif containing 25 VPS37B 79720 1.49 8.73E-03 vacuolar protein sorting 37 homolog B (S. cerevisiae) XAF1 54739 2.40 1.69E-03 XIAP associated factor 1 Benjamini Hochberg-adjusted p-values of differentially expressed genes are shown.

241 Appendices

18.2 Appendix 2: Presentations at conferences and meetings

Data from Results Chapter 1 and 2 was previously presented at the below meetings. Title and author lists are shown as printed in the respective abstract books:

 09. January 2015, Acid Fast Club Winter Meeting, London, United Kingom (Oral presentation): Ann-Kathrin Reuschl, M Edwards, D Connell, N Siddiqui, H Lambie, S Bremang, OM Kon, R Shattock & A Lalvani;Primary human airway epithelial cells are early responders to tuberculosis infection. Tuberculosis Research Centre, NHLI, Imperial College London

 22.-27. January 2015, Keystone symposium “Host Response in Tuberculosis”, Santa Fe, USA (Poster presentation): AK Reuschl, M Edwards, D Connel, N Siddiqui, H Lambie, S Bremang, OM Kon, R Shattock and A Lalvani; Primary human airway epithelial cells are early responders to tuberculosis infection

 06-09. September 2015, 4th European Congress of Immunology, Vienna, Austria (Poster presentation): Primary human airway epithelial cells are early responders to tuberculosis infection; A. Reuschl, M. Edwards, D. Connell, S. Bremang, O. Kon, R. Shattock, A. Lalvani.

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