The Glial Cell Line-Derived Neurotrophic Factor Family in Airway Infectious Disease

The glial cell line-derived neurotrophic factor family in airway infectious disease

A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the Faculty of Biology, Medicine and Health

2017

By Emma Connolly

School of Biological Sciences Division of Infection, Immunity and Respiratory Medicine Contents

List of Figures ...... 9 List of tables ...... 13 Abbreviations ...... 14 Abstract ...... 17 Declaration ...... 18 Copyright Statement ...... 18 Acknowledgement ...... 19 Chapter 1 : Introduction ...... 20

1.0 Introduction ...... 21

1.1 Airway host defence ...... 21

1.2 Tissue-resident lung macrophages ...... 22

1.3 The function of tissue-resident lung macrophages ...... 24

1.4 Regulation of alveolar macrophages by the airway epithelium ...... 24

1.5 The role of alveolar macrophages at homeostasis ...... 26

1.6 The role of alveolar macrophages in host defence ...... 27

1.7 Airway host defence to viral infection ...... 28

1.7.1 Pattern recognition receptors ...... 28

1.7.2 Toll-like receptors ...... 28

1.7.3 The Interferons ...... 31

1.8 Airway host defence to Influenza virus infection ...... 34

1.8.1 Interferon-stimulated genes important in influenza virus infection .... 35

1.8.2 Dysregulation of the type I IFN response ...... 36

1.9 The role of macrophages in airway disease ...... 36

1.9.1 The adaptation and plasticity of macrophages to their environment . 36

1.9.2 Classically activated and alternatively activated macrophages...... 37

1.10 Chronic airway disease ...... 38

1.11 Neuroimmune crosstalk ...... 40

1.12 Neurotrophic factors ...... 41

1.12.1 The glial cell line-derived neurotrophic factor family ...... 42

1.12.2 RET-dependent GDNF family signalling ...... 43

1.12.3 GDNF family signalling in lipid rafts ...... 44

1.12.4 RET-independent GDNF family signalling ...... 45

1.12.5 The functions of the GDNF family in the nervous system ...... 45

1.12.6 The GDNF family in neurological diseases ...... 46

1.13 The neuroimmune crosstalk in lymphatic tissue ...... 46

1.14 The neuroimmune crosstalk in mucosal tissue ...... 47

1.15 The functions of the GDNF family outside of the nervous system ...... 48

1.16 The role of the GDNF family in lymphatic tissue ...... 49

1.17 The role of the GDNF family in the Intestine ...... 49

1.18 The peripheral nervous system and neurotrophic factors in chronic airway disease ...... 50

1.19 Research hypothesis and aims ...... 53

Chapter 2 : Methods ...... 54

2.1 Mouse strains ...... 55

2.2 Mouse experimental models ...... 55

2.2.1 Influenza infection model ...... 55

2.2.2 House dust mite model ...... 55

2.3 Isolation of mouse tissue cells ...... 56

2.3.1 Isolation of murine bone marrow cells...... 56

2.3.2 Culture of murine bone marrow-derived macrophages ...... 56

2.3.3 Isolation of mouse bronchoalveolar lavage macrophages ...... 56

2.3.4 Digestion of mouse lung tissue ...... 57 2

2.3.5 Digestion of mouse ear and back skin tissue ...... 57

2.4 Isolation of human tissue cells ...... 58

2.4.1 Isolation of human peripheral blood monocytes...... 58

2.4.2 Culture of human monocyte-derived macrophages ...... 58

2.4.3 Isolation of human bronchoalveolar lavage macrophages ...... 59

2.4.4 Isolation and culture of airway macrophages from human lung resection samples ...... 59

2.4.5 Sputum sample collection and processing ...... 60

2.5 Cell line culture ...... 60

2.5.1 Beas-2b cells ...... 60

2.5.2 A549 cells ...... 61

2.5.3 THP-1 cells ...... 61

2.6 mRNA detection assays ...... 61

2.6.1 RT-qPCR ...... 61

2.6.2 RT2 Profiler PCR array for mouse neurotrophins and receptors ...... 62

2.7 Protein detection assays ...... 63

2.7.1 Concentrating protein in supernatants ...... 63

2.7.2 Cytokine Bead Array ...... 63

2.7.3 Human TNFα and IL-6 ELISAs ...... 64

2.7.4 Human and mouse Neurturin ELISAs ...... 64

2.7.5 Western Blotting ...... 65

2.7.6 Immunocytochemistry and immunofluorescence ...... 65

2.7.7 PathScan Antibody Array Kits (Fluorescent Readout) ...... 66

2.7.8 Flow cytometry ...... 66

2.8 Phagocytosis assay ...... 70

2.9 Cell death detection assays ...... 70

2.9.1 Annexin V flow staining ...... 70

2.9.2 LDH assay ...... 70

2.10 Statistics ...... 71

Chapter 3 : Characterisation of the GDNF family receptor, GFRα2, on airway macrophages in health and disease ...... 72

3.1 Introduction ...... 73

3.1.1 Neuronal factor function outside the nervous system ...... 73

3.1.2 Are neuronal factors expressed on airway immune cells? ...... 73

3.1.3 The GDNF family expression and signalling on airway cells ...... 74

3.1.4 The role of the GDNF family in disease ...... 75

3.1.5 Hypothesis ...... 76

3.1.6 Aims ...... 76

3.2 Results ...... 77

3.2.1 Screening mouse macrophages for neurotrophic factors...... 77

3.2.2 The expression of the GDNF family on mouse bone marrow-derived macrophages ...... 82

3.2.3 The cytokine IL-4 enhances the mRNA of the GFRα2 receptor on mouse bone marrow-derived macrophages...... 84

3.2.4 GFRα2 is expressed at the mRNA level on mouse alveolar macrophages at steady state and enhanced with the cytokine IL-4 ...... 85

3.2.5 GFRα2 is more highly expressed on CD11b+ mouse airway macrophages compared to CD11c+ mouse alveolar macrophages at steady state ...... 86

3.2.6 GFRα2 protein expression on mouse airway macrophages cannot be detected at steady state ...... 87

3.2.7 GFRα2 is expressed on human monocyte-derived macrophages .... 91

3.2.8 GFRα2 expression on human monocyte-derived macrophages is not affected by TLR3/TLR4 agonist or cytokine stimulation ...... 92

3.2.9 GFRα2 is highly expressed on healthy human airway macrophages 94

3.2.10 GFRα2 is expressed on healthy peripheral blood monocytes at the mRNA level ...... 95

3.2.11 Does GFRα2 bind to an alternative co-receptor to RET in healthy human airway macrophages? ...... 96

3.2.12 Is GFRα2 expressed on macrophages from other tissue sites? ..... 98

3.2.13 Is the expression of GFRα2 altered on airway macrophages from patients with chronic inflammatory airway diseases? ...... 103

3.3 Discussion ...... 107

3.3.1 GFRα2 is highly expressed on airway macrophages ...... 107

3.3.2 GFRα2 expression is not restricted to airway macrophages ...... 107

3.3.3 GFRα2 expression is enhanced on airway macrophages following IL- 4 stimulation ...... 108

3.3.4 Does GFRα2 and Nrtn signal independently of RET in human airway macrophages? ...... 109

3.3.5 The possible roles of other neuronal factors expressed on GM-CSF- and M-CSF- derived BMDMs ...... 110

3.3.6 Conclusion ...... 112

Chapter 4 : What is the effect of neurturin on macrophages? ...... 113

4.1 Introduction ...... 114

4.1.1 Do alveolar macrophages and airway epithelial cells communicate via neuronal factors? ...... 114

4.1.2 The roles of the GDNF family outside the nervous system ...... 114

4.1.3 The pleiotropic functions of airway macrophages ...... 115

4.1.4 The downstream intracellular signalling pathways activated by the GDNF family ...... 116

4.1.5 Hypothesis ...... 117

4.1.6 Aims ...... 117

4.2 Results ...... 118

4.2.1 The expression of the GDNF family on human bronchial and alveolar epithelial cell lines at the mRNA level ...... 118

4.2.2 Nrtn expression in human bronchial and alveolar epithelial cells is not altered by TLR4 agonist or cytokine stimulation ...... 120

4.2.3 Nrtn is not released from human bronchial epithelial cells following programmed cell death or necrosis ...... 122

4.2.4 Nrtn expression in mouse airway disease ...... 124

4.2.5 Do GFRα2 and Nrtn play a role in the inflammatory response?...... 126

4.2.6 Does Nrtn inhibit the activation of intracellular signalling pathways in LPS-treated human airway macrophages? ...... 132

4.2.7 Nrtn induces low level release of TNFα from human monocyte- derived macrophages ...... 135

4.2.8 Does Nrtn affect the polarisation of macrophages to an M1- or M2- like phenotype? ...... 136

4.2.9 Does Nrtn affect macrophage phagocytosis of bacteria?...... 140

4.2.10 Is RET phosphorylated in human airway macrophages by Nrtn stimulation alone? ...... 141

4.3 Discussion ...... 143

4.3.1 Nrtn is expressed by airway epithelial cells ...... 143

4.3.2 How is Nrtn released from human airway epithelial cells? ...... 143

4.3.3 Nrtn expression is altered in airway disease ...... 145

4.3.4 What effect does Nrtn have on airway macrophages? ...... 146

4.3.5 Nrtn does not induce RET phosphorylation in airway macrophages at steady state ...... 148

4.3.6 Conclusion ...... 148

Chapter 5 : Does the GDNF family have a role in airway viral infection? ...... 150

5.1 Introduction ...... 151

5.1.1 The response of type I interferons to invading microbial pathogens in the airways ...... 151

5.1.2 Dysregulation of the type I interferon response ...... 153

5.1.3 The alternatively spliced isoforms of GFRα2 and RET have differential functions ...... 154

5.1.4 Optimal RET signalling occurs within membrane lipid rafts ...... 155

5.1.5 Hypothesis ...... 156

5.1.6 Aims ...... 156

5.2 Results ...... 157

5.2.1 Nrtn expression is enhanced in human bronchial epithelial cells following TLR stimulation ...... 157

5.2.2 TLR stimulation does not alter the expression of GFRα2 on macrophages ...... 158

5.2.3 Stimulation of human bronchial epithelial cells with interferons does not affect Nrtn expression ...... 160

5.2.4 Stimulation of THP-1 differentiated macrophages with type I interferons enhances RET expression ...... 161

5.2.5 Stimulation of M-CSF-differentiated MDMs with type I interferons enhances RET expression ...... 169

5.2.6 Stimulation of human airway macrophages with type I interferons enhances RET expression ...... 177

5.2.7 Stimulation of mouse airway macrophages with type I interferons does not induce RET expression ...... 178

5.2.8 Stimulation of human airway macrophages with type I interferons induces the expression of different RET isoforms...... 179

5.3 Discussion ...... 181

5.3.1 TLR activation enhances the production of Nrtn in human bronchial epithelial cells ...... 181

5.3.2 RET as a novel interferon-stimulated gene ...... 182

5.3.3 Is the subcellular location of GFRα2 or RET in human airway macrophages affected by type I IFN stimulation? ...... 182

5.3.4 Do GFRα2 and RET splice variants expressed on human airway macrophages have distinct functions? ...... 184

5.3.5 Dysregulation of the type I IFN response ...... 185

5.3.6 Conclusion ...... 188

Chapter 6 : Final Discussion ...... 189

6.1 Discussion ...... 190

6.2 Does Nrtn affect the function of airway macrophages in allergic airway disease? ...... 191

6.3 Does Nrtn have an anti-inflammatory function on airway macrophages? ...... 192

6.4 Does Nrtn have an effect on airway macrophages in viral infection? .... 193

6.5 The implications of RET as an interferon-stimulated gene ...... 194

6.6 Future Directions ...... 195

6.7 Conclusion ...... 196

References...... 198

List of Figures

Figure 1.1: Location of alveolar and interstitial macrophages within the airways...... 23 Figure 1.2: Inhibitory regulation of alveolar macrophages by the airway epithelium ... 26 Figure 1.3: The production of type I IFNs by TLR receptor signalling ...... 31 Figure 1.4: The type I IFN signalling pathway...... 34 Figure 1.5: Neurotrophic factor receptors and ligands...... 42 Figure 1.6: RET-dependent GDNF family signalling ...... 44 Figure 1.7: Neurogenic inflammation in the airways...... 51 Figure 1.8: The roles of the GDNF family in the immune system...... 53 Figure 3.1: The expression of F4/80, CD11c and CD11b on M-CSF- and GM-CSF- bone marrow derived macrophages...... 78 Figure 3.2: Neurotrophic factors and related genes on murine bone marrow-derived macrophages...... 81 Figure 3.3: GM-CSF-differentiated bone marrow derived macrophages express GFRα2, but not RET or Nrtn...... 83 Figure 3.4: GFRα2 expression is enhanced on GM-CSF- and M-CSF- differentiated BMDMs following IL-4 stimulation...... 85 Figure 3.5: GFRα2 mRNA expression is enhanced on mouse alveolar macrophages following IL-4 stimulation...... 86 Figure 3.6: GFRα2 is more highly expressed at the mRNA level on CD11c intermediate/CD11b high mouse interstitial macrophages...... 87 Figure 3.7: Gating strategy used to identify macrophage subsets in naïve mouse lung 90 Figure 3.8: GFRα2 is not detected on naive mouse alveolar macrophages or interstitial macrophages at the protein level...... 90 Figure 3.9: The mRNA expression of GFRα2, Nrtn and RET on GM-CSF- and M-CSF- differentiated MDMs...... 92 Figure 3.10: The mRNA expression of GFRα2 is not altered on GM-CSF- or M-CSF- differentiated MDMs following TLR agonist or cytokine stimulations...... 93 Figure 3.11: GFRα2 is highly expressed on human airway macrophages at the mRNA level...... 95 Figure 3.12: GFRα2 is highly expressed on human peripheral blood monocytes...... 96

Figure 3.13: The alternative co-receptors to GFRα2; NCAM, syndecan 3 and Gas1 are expressed on human airway macrophages...... 97 Figure 3.14: The expressions of the alternative co-receptors for GFRα2 signalling are not altered by IL-4 stimulation of human airway macrophages...... 98 Figure 3.15: GFRα2 is expressed on mouse small intestine macrophages at the mRNA level...... 99 Figure 3.16: Gating strategy to identify dermal macrophages and Langerhan cells in mouse ear and back skin...... 101 Figure 3.17: GFRα2 is not detected on naïve dermal macrophages or Langerhans cells at the protein level...... 102 Figure 3.18: GFRα2 expression is not altered on sputum macrophages from asthmatic patients compared to healthy donors...... 104 Figure 3.19: GFRα2 expression increases in human macrophages from COPD patients compared to healthy non-smokers and healthy smokers...... 105 Figure 3.20: GFRα2 is slightly increased on human airway macrophages from COPD patients compared to healthy non-smokers...... 106 Figure 4.1: GFRα1, Nrtn and Artn are expressed on human bronchial and alveolar epithelial cell lines...... 119 Figure 4.2: Nrtn is expressed at the protein level in Beas-2b cells in the steady state...... 120 Figure 4.3: The mRNA level of Nrtn on human bronchial and alveolar epithelial cells is not altered by stimulation with cytokines, TLR ligands or Nrtn itself...... 121 Figure 4.4: The protein level of Nrtn in human bronchial epithelial cells is not altered by stimulation with cytokines, TLR ligands or Nrtn itself...... 122 Figure 4.5: Optimisation of cell death induction in Beas-2b cells by camptothecin. .. 123 Figure 4.6: Nrtn is enhanced in the lung in a mouse model of house dust mice...... 125 Figure 4.7: Nrtn is enhanced in BAL fluid at peak inflammation in a mouse model of influenza...... 126 Figure 4.8: Nrtn does not alter the mRNA expression of pro-inflammatory cytokines in M-CSF-differentiated BMDMs following LPS challenge...... 127 Figure 4.9: Nrtn does not affect the release of pro-inflammatory cytokines from M-CSF- differentiated BMDMs following LPS challenge...... 128

Figure 4.10: Nrtn does not alter the mRNA expression of pro-inflammatory cytokines in GM-CSF-differentiated BMDMs following LPS challenge...... 129 Figure 4.11: Nrtn inhibits the release of pro-inflammatory cytokines from GM-CSF- differentiated BMDMs following LPS challenge...... 130 Figure 4.12: Nrtn does not affect the release of pro-inflammatory cytokines from M- CSF- and GM-CSF- differentiated MDMs following LPS challenge...... 131 Figure 4.13: Nrtn does not affect the release of pro-inflammatory cytokines from human airway macrophages following LPS challenge...... 132 Figure 4.14: Nrtn does not affect the activation of intracellular signalling molecules in human airway macrophages following LPS challenge...... 135 Figure 4.15: Nrtn induces low level release of TNFα from M-CSF- and GM-CSF- differentiated MDMs...... 136 Figure 4.16: Nrtn does not alter the mRNA expression of M1 ‘like’ macrophage markers...... 137 Figure 4.17: Nrtn does not alter the protein expression of M1 ‘like’ macrophage markers...... 138 Figure 4.18: Nrtn does not alter the mRNA expression of M2 ‘like’ macrophage markers...... 139 Figure 4.19: Nrtn does not alter the protein expression of M2 ‘like’ macrophage markers...... 140 Figure 4.20: Nrtn does not alter the uptake of bacteria by M1 ‘like’ or M2 ‘like’ macrophages...... 141 Figure 4.21: Nrtn does not induce RET phosphorylation in human airway macrophages at steady state...... 142 Figure 5.1: The type I IFN signalling pathway...... 153 Figure 5.2: The production and release of Nrtn is enhanced by TLR agonist stimulation...... 158 Figure 5.3: RET is expressed on THP-1-differentiated macrophages at steady state .. 159 Figure 5.4: The mRNA expression of GFRα2 and RET is not altered on THP-1- differentiated macrophages following TLR agonist stimulation...... 160 Figure 5.5: Nrtn expression in human bronchial epithelial cells is not altered by interferon stimulation...... 161

Figure 5.6: Interferons enhance the expression of GFRα2 and RET on THP-1- differentiated macrophages...... 162 Figure 5.7: Type I Interferons enhance the protein expression of RET on THP-1- differentiated macrophages...... 163 Figure 5.8: Gating strategy used to identify live THP-1-differentiated macrophages. 164 Figure 5.9: GFRα2 surface, cytoplasmic and nuclear protein expression in THP— differentiated macrophages...... 166 Figure 5.10: RET surface, cytoplasmic and nuclear protein expression in THP-1 – differentiated macrophages...... 168 Figure 5.11: Type I interferons enhance the mRNA expression of RET on human M-CSF- differentiated MDMs...... 170 Figure 5.12: Type I interferons enhance the protein expression of RET on human M- CSF-differentiated MDMs...... 171 Figure 5.13Figure 5.12: Gating strategy used to identify live M-CSF-differentiated MDMs...... 172 Figure 5.14: GFRα2 surface, cytoplasmic and nuclear protein expression in M-CSF- differentiated MDMs...... 174 Figure 5.15: RET surface, cytoplasmic and nuclear protein expression in M-CSF- differentiated MDMs...... 176 Figure 5.16: The expression of RET is enhanced on human airway macrophages following stimulation with type I interferons...... 178 Figure 5.17: Type I interferons do not enhance the expression of RET in mouse airway macrophages...... 179 Figure 5.18: Type I interferons induce the expression of the RET51 and RET9 isoforms in human airway macrophages...... 180 Figure 6.1: The regulation of the GDNF family in airway viral infection. Airway epithelial cells recognise an invading virus and release neurturin...... 194

List of tables

Table 1.1: World health organisations (WHOs) estimates for the global 20 leading causes of death in 2015...... 39 Table 2.1: Flow Cytometry primary antibody cocktail for M-CSF and GM-CSF- differentiated BMDMs ...... 67 Table 2.2: Flow Cytometry primary antibody cocktail for mouse lung digest cells ...... 68 Table 2.3: Flow Cytometry primary antibody cocktail for mouse skin digest cells ...... 68 Table 2.4: Flow Cytometry primary antibody cocktail for GM-CSF- and M-CSF- differentiated MDMs ...... 69 Table 3.1: The genes expressed on murine bone marrow-derived macrophages differentiated with M-CSF and GM-CSF...... 82

Abbreviations

Artn Artemin BAL Bronchoalveolar lavage BDNF Brain-derived neurotrophic factor BMDM Bone-marrow derived macrophage BMP2 Bone morphogenic protein 2 BSA Bovine serum albumin Cbln1 Cerebellin 1 cDCs Conventional dendritic cells CDNF Cerebral dopamine neurotrophic factor CGRP Calcitonin-gene related peptide CLC Cardiotrophin-like cytokine CNTF Ciliary neurotrophic factor CNTFR Ciliary neurotrophic factor receptor COPD Chronic obstructive pulmonary disease COX-2 Cyclooxygenase-2 CREB cAMP response element binding protein CT-1 Cardiotrophin-1 CXCL C-X-C motif chemokine d.p.i Days post-infection DAMP Damage-associated molecular patterns Dendritic cell DC DMEM Dulbecco’s Modified Eagle Medium dsRNA Double-stranded RNA ECM Extracellular matrix EDTA Ethylenediaminetetraacetic acid EIF2α Eukaryotic translation initiation factor 2 alpha FCS Fetal calf serum FGF Fibroblast growth factor GABA-ergic Gamma-aminobutyric acid-ergic GATA6 GATA binding protein 6 GDNF Glial cell-line derived neurotrophic factor GFL GDNF family ligand GFRα GDNF family receptor alpha GM-CSF Granulocyte macrophage colony-stimulating factor gMFI Geometric mean fluorescent intensity HA Haemagglutinin HBEC Human bronchial epithelial cell HBSS Hank’s balanced salt solution HCV Hepatitis C HDM House dust mite 14

HIV Human immunodeficiency virus HNS Healthy non-smoker HRP Horseradish peroxidase HS Healthy smoker HSC Haemoatopoietic stem cell IFITM Interferon-induced transmembrane IFN Interferon IFNAR Interferon-alpha/beta receptor IFNGR Interferon-gamma receptor IFNLR Interferon-lambda receptor IL interleukin IL-1R IL-1 receptor ILC Innate lymphoid cell IRAK Interleukin-1 receptor-associated kinase 1 IRF Interferon regulatory factor ISG Interferon-stimulated gene ISGF3 Interferon-stimulated gene factor 3 ISRE Interferon-stimulated response element JAK Janus kinase LIF Leukemia inhibitory factor LIFR Leukemia inhibitory factor receptor LPS Lipopolysaccharide LRR Leucine-rich repeats LTA Lipoteichoic acid MANF Mesencephalic astrocyte-derived neurotrophic factor MAPK Mitogen activated protein kinase MAVS Mitochondrial antiviral-signalling protein M-CSF Macrophage colony-stimulating factor MDM Monocyte-derived macrophage MEN2 Multiple neoplasia type 2 MHC Major histocompatibility complex MMP Matrix metalloproteinase MT3 Metallothionein-3 MX Myxoma resistance protein NA Neuraminidase NGF Nerve growth factor NK Natural killer NLR NOD-like receptor NPY Neuropeptide Y NPY2R Neuropeptide Y receptor Y2 Nrg1 Neuregulin 1 Nrtn Neurturin

NT3 Neurotrophin 3 NT4 Neurotrophin 4 OAS 2’-5’-oligoadenylate synthase OSM Oncostatin M OVA Ovalbumin p75NTR p75 neurotrophin receptor PAMP Pathogen-associated molecular pathogens PBMC Peripheral blood mononuclear cell PBS Phosphate-buffered saline pDCs Plasmacytoid dendritic cells PFA Paraformaldehyde PI3K Phosphatidylinositol-4,5-biphosphate 3-kinase PKR Protein kinase R PLCγ Phospholipase C gamma PMA Phorbol 12-myristate 13-acetate PPARγ Peroxisome proliferator-activated receptor-gamma PRR Pattern recognition receptor Pspn Persephin RLR RIG-I-like receptor RNaseL Ribonuclease L RSV Respiratory syncytial virus SD Standard deviation SDS Sodium dodecyl sulfate SLE Systemic lupus erythematosus SOCS Supressor of cytokine signalling SP Surfactant protein ssRNA Single-stranded RNA STAT Signal transducers and activators of transcription TBK1 TANK binding kinase 1 TBS Tris-buffered saline TGFβ Transforming growth factor beta Th T helper TIR Toll/IL-1 receptor TLR Toll-like receptor TRAF6 TNF receptor-associated factor 6 TREM1 Triggering receptor expressed on myeloid cells 1 TRIF TIR-domain-containing adapter-inducing interferon-β Trk Tropomyosin receptor kinase TRPA1 Transient receptor potential cation channel A1 USP18 Ubiquitin-specific protease 18 VEGF Vascular endothelial growth factor α7nAChR Alpha 7 nicotinic acetylcholine receptor

Abstract

Alveolar macrophages reside in the healthy airspaces and are continuously exposed to environmental challenges. As such, mechanisms are in place to restrict their activity, including negative regulation by epithelial cells. Upon encountering a harmful pathogen, this inhibition is lost and pattern recognition receptors, such as toll-like receptors (TLRs), are activated. This stimulates the release of type I interferons, which exert anti-microbial actions on airway cells. The importance of neurotrophic factors in the immune response is becoming well established. However, research into their role in airway homeostasis and infectious disease is lacking. Therefore, in this thesis I aimed to determine which neurotrophic factors were highly expressed on airway macrophages and elucidate their potential role in homeostasis, as well as microbial clearance, of the airway.

In this thesis, I have found that the glial cell line-derived neurotrophic factor (GDNF) family receptor, GFRα2, is highly expressed on mouse and human airway macrophages at steady state. However, the expression of the signalling partner for the GFRα receptors, the tyrosine kinase RET, is specifically induced in airway macrophages by type I interferons. Furthermore, TLR activation enhances the production and release of the GFRα2 ligand, neurturin, from airway epithelial cells. Therefore, I propose a novel role for the GDNF family in infectious disease, through modulation of airway macrophage anti-microbial activity.

Declaration

No portion of the work referred to in the thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning. Copyright Statement

i. The author of this thesis (including any appendices and/or schedules to this thesis) owns certain copyright or related rights in it (the “Copyright”) and s/he has given The University of Manchester certain rights to use such Copyright, including for administrative purposes. ii. Copies of this thesis, either in full or in extracts and whether in hard or electronic copy, may be made only in accordance with the Copyright, Designs and Patents Act 1988 (as amended) and regulations issued under it or, where appropriate, in accordance with licensing agreements which the University has from time to time. This page must form part of any such copies made. iii. The ownership of certain Copyright, patents, designs, trademarks and other intellectual property (the “Intellectual Property”) and any reproductions of copyright works in the thesis, for example graphs and tables (“Reproductions”), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual Property and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the relevant Intellectual Property and/or Reproductions. iv. Further information on the conditions under which disclosure, publication and commercialisation of this thesis, the Copyright and any Intellectual Property and/or Reproductions described in it may take place is available in the University IP Policy (see http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=2442), in any relevant Thesis restriction declarations deposited in the University Library, The University Library’s regulations (see http://www.library.manchester.ac.uk/about/regulations/) and in The University’s policy on Presentation of Theses 18

Acknowledgement

Firstly, I would like to thank Professor Tracy ‘the Goddess of Science’ Hussell who has been an amazing supervisor to me over the last three and a half years. It was a rocky start but through her support I have completed a PhD I am proud of. She has instilled in me a passion for my research and improved my confidence immensely, which I can’t thank her enough for.

I would also like to thank past and present members of the Hussell lab, in particular Alek Grabiec for all his input and expertise to get this project off the ground, and Mark ‘Danger’ Fife, Amy Chandler and David Morgan for listening to all my moaning, their amazing support and friendship. I would also like to thank other members of the MCCIR, including Jonathan Worboys, Pablo Palazon, Holly Linley, James Crooks, Stephanie Houston, Joshua Casulli and Tamsin Zangerle Murray. The countless Friday nights spent in the Grafton, the hours spent on Xpert 11 and the MLs have helped me through and kept me going. I’m looking forward to many more during my post-doc!

I would also like to thank my parents for their support and understanding especially towards the final few months of this project. And, most importantly, for always knowing when to have a bottle of Prosecco ready for me!

Chapter 1 : Introduction

1.0 Introduction

Research into the interaction between the nervous system and immune system is gaining traction. Indeed, factors initially thought to be restricted to one system are now known to be expressed on the other. Furthermore, inflammation is now associated with enhanced severity of several nervous system diseases, such as stroke, multiple sclerosis and Alzheimer’s disease (Weissert 2013; Lynch 2014; Allan et al. 2005). The nervous and immune systems have similar response mechanisms to environmental and host challenges, for example through their expression of pattern recognition receptors (PRRs) (Chiu et al. 2012). However, the impact of neuronal factors on diseases in peripheral tissues, such as the airways, is less well known. This thesis focuses on the role of receptors and ligands, previously deemed to be restricted in function to the nervous system, on macrophage regulation.

1.1 Airway host defence

The lungs are designed to allow optimal gaseous exchange (Lambrecht 2006). Inhaled air comprises a multitude of microbes and particulates, which if not dealt with appropriately, compromise this vital function. The diversity of cell types that make up the airways creates a range of host defence mechanisms that allow safe removal of harmful pathogens. The respiratory system can be divided into two distinct regions; the upper and lower respiratory tracts. The upper respiratory tract contains the nasal cavity, pharynx and larynx, while the lower respiratory tract consists of the trachea, bronchi, bronchioles and alveoli (Iwasaki et al. 2016). The conducting airways of the lower respiratory tract are lined with a pseudostratified epithelium and include ciliated and secretory cells (Leiva-Juárez et al. 2017). Basal cells situated beneath the epithelial cell layer are progenitors for both of these cell types and are essential for repair of the epithelial barrier after injury (Rock et al. 2010). The secretory cells include serous, club, neuroendocrine and goblet cells, which are all found in the healthy airways, albeit at lower frequencies compared to ciliated cells (Whitsett & Alenghat 2015). Goblet cells secrete mucins, which are critical factors in the mucociliary clearance of inhaled microbes (Roy et al. 2014; Voynow & Rubin 2009). Mucins tethered to the

21 airway epithelium bind to pathogens and are shed by proteases allowing them to be transported out of the airways by the movement of ciliated cells (Fahy & Dickey 2010).

In contrast, the alveoli are comprised of only two epithelial cell types, the most abundant being the type I alveolar epithelial cells which facilitate gas exchange (Franks et al. 2008). The alveolar epithelial cells are in very close proximity to the capillary endothelial cells, allowing for efficient delivery of oxygen to the bloodstream (Leiva- Juárez et al. 2017). Type II alveolar epithelial cells secrete pulmonary surfactant, which contains SP-A and SP-D (Whitsett & Alenghat 2015). This serves to prevent collapse of the lungs during inhalation and exhalation and also contributes to host defence against infection through their binding to pathogens (Hartshorn 2010; Ariki et al. 2012).

1.2 Tissue-resident lung macrophages

Innate immune cells, such as macrophages, play a major role in airway host defence. The airways are home to two distinct macrophage subsets in rodents and humans; alveolar macrophages and interstitial macrophages (Figure 1.1). Alveolar macrophages reside in the alveolar lumen and are one of the few cell populations recovered by bronchoalveolar lavage (BAL), comprising 90-95% of the cells, in addition to a small number of lymphocytes (Ely et al. 2006; Snelgrove et al. 2011). Alveolar macrophages are long-lived and self-renewing and therefore do not require continuous replenishment from bone marrow-derived precursors (Murphy et al. 2008; Janssen et al. 2011; Hashimoto et al. 2013), unlike intestinal tissue resident macrophages (Bogunovic et al. 2009; Varol et al. 2009; Tamoutounour et al. 2012). In contrast, interstitial macrophages have a higher turnover rate and are shorter lived in the steady state compared to alveolar macrophages (Cai et al. 2014). Interstitial macrophages are located in the interstitial space between the alveoli and capillaries and are much less abundant than alveolar macrophages, and along with the difficulty in isolating these cells, explains why fewer studies have been carried out on this cell type in comparison to alveolar macrophages (Duan et al. 2017).

Figure 1.1: Location of alveolar and interstitial macrophages within the airways. Alveolar macrophages are situated in the alveolar lumen and are separated from the interstitial space by an epithelial cell layer. Interstitial macrophages are located in the interstitial space in between the airway epithelial cells and blood capillaries.

Alveolar macrophages are initially derived from fetal monocytes and their development is completely reliant on granulocyte macrophage colony-stimulating factor (GM-CSF), of which there is an abundance of in the airspaces shortly after birth (Yona et al. 2013; Guilliams et al. 2013). GM-CSF drives production of alveolar macrophages through induction of peroxisome proliferator-activated receptor-γ (PPARγ) expression (Schneider et al. 2014; Bonfield et al. 2003; Guilliams et al. 2013). Mice lacking GM-CSF or its receptor, and patients with defects in GM-CSF signalling, develop pulmonary alveolar proteinosis due to a build-up of surfactant in the airways because of a lack of clearance by macrophages (Trapnell & Whitsett 2002; Dranoff et al. 1994). On the other hand, interstitial macrophages originate from bone marrow derived-monocytes and are preferentially replenished by this population during inflammation (Landsman & Jung 2007).

1.3 The function of tissue-resident lung macrophages

Due to their location, the macrophage subsets within the airways have specialised functions. Alveolar macrophages reside in the alveolar lumen and are surrounded by surfactant, which contains proteins that dampen macrophage activity (Hussell & Bell 2014). This allows alveolar macrophages to be tolerant to cellular debris and innocuous antigens, thereby preventing excessive tissue damage, while setting an activation threshold that needs to be overcome to efficiently clear more pathogenic microorganisms (Snelgrove et al. 2011). On the other hand, interstitial macrophages are in close contact with the extracellular matrix (ECM) and, as such, have a more prominent role in modulating tissue fibrosis, as well as being better equipped for antigen presentation (Schneberger et al. 2011; Steinmüller et al. 2000). Moreover, alveolar macrophages have reduced phagocytic activity and respiratory burst in comparison to interstitial macrophages (Holt 1978; Hoidal et al. 1981). Both subsets of macrophages inhibit T cell activation and subsequent onset of adaptive immunity, via the suppression of dendritic cell (DC) activation; a process dependent on the anti- inflammatory cytokine interleukin-10 (IL-10), transforming growth factor-β (TGFβ) and prostaglandins (Bedoret et al. 2009; Roth & Golub 1993). Alveolar macrophages are poor at presenting antigen to T cells (Lipscomb et al. 1986), although they are capable of transporting antigens to the lung-draining lymph nodes (Kirby et al. 2009). Likewise, human alveolar macrophages induce T cell antigen-specific unresponsiveness as a result of poor antigen presentation and a lack of expression of co-stimulatory molecules, such as CD86 (Blumenthal et al. 2001); which in itself promotes tolerance to innocuous antigens.

1.4 Regulation of alveolar macrophages by the airway epithelium

Due to their direct exposure to environmental challenges in the alveolar lumen, strategies need to be in place for alveolar macrophages to discern a harmless antigen from a serious pathogenic threat. For this reason, alveolar macrophages are tightly regulated in order to prevent an inflammatory response against cellular debris and innocuous antigens, whilst still providing protection against harmful pathogens by

24 propelling an inflammatory response (Hussell & Bell 2014). For example, alveolar macrophages are hyporesponsive to low levels of endotoxins, which are present in ambient air (Snelgrove et al. 2011), thereby preventing an inappropriate innate immune response to innocuous antigens. A number of mechanisms are in place to suppress the activity of alveolar macrophages, including their interaction with the airway epithelium. The airway epithelium, through both direct contact and secreted products, negatively regulates alveolar macrophage activity (Figure 1.2). These factors include CD200, TGF-β, IL-10 and surfactant proteins (SP-A and SP-D), which act to suppress macrophage phagocytic ability and production of pro-inflammatory cytokines (Snelgrove et al. 2008; Munger et al. 1999; Bonfield et al. 1995). In addition, these mechanisms set a threshold of activation that needs to be overcome in order for an inflammatory response to be triggered. Activation of toll-like receptor (TLR) signalling, through recognition of an invading pathogen, elicits a strong enough immune response to exceed the inhibitory regulation of alveolar macrophages and causes up-regulation of TLR co-receptors including CD14 and triggering receptor expressed on myeloid cells 1 (TREM1) (Klesney-Tait et al. 2006). Furthermore, loss of epithelial integrity during inflammation reduces the level of regulatory factors releasing alveolar macrophages from epithelial-induced inhibition. This increases their phagocytic capabilities and initiates the production of pro-inflammatory cytokines (Lohmann-Matthes et al. 1994; Steinmüller et al. 2000). The inhibitory factors that are important in maintaining airway homeostasis are also crucial in resolving inflammation after elimination of the microbial pathogen. Both CD200 and TGF-β assist in the suppression of inflammation, promote resolution and restore homeostasis (Snelgrove et al. 2008).

Figure 1.2: Inhibitory regulation of alveolar macrophages by the airway epithelium. Airway epithelial cells produce IL-10, TGFβ, CD200 and surfactant proteins (SPA and SPD). Their receptors are expressed on alveolar macrophages and exert inhibitory effects to suppress macrophage activation. Adapted from (Hussell & Bell 2014).

1.5 The role of alveolar macrophages at homeostasis

At steady state, cellular turnover is a normal occurrence and generates debris and apoptotic cells. Alveolar macrophages play an important function in clearing apoptotic cells, a process known as efferocytosis. Efferocytosis is essential in maintaining airway homeostasis and in preventing excessive inflammation that would otherwise be elicited (Krysko et al. 2006). Inefficient clearance of apoptotic cells leads to secondary necrosis and the release of damage associated molecular patterns (DAMPs) that subsequently promote an inflammatory response (Lauber et al. 2004). Defects in apoptotic cell clearance by airway macrophages is observed in patients with cystic fibrosis, asthma and chronic obstructive pulmonary disease (COPD) and may play a role in disease pathogenesis (Vandivier et al. 2006). Efferocytosis is mediated by a plethora

26 of receptors that recognise externalised phosphatidyl serine on the cell surface of apoptotic cells. These include the TAM receptor family (Tyro3, Axl and Mertk receptors) that enhance the expression of suppressor of cytokine signalling (SOCS) 1 and SOCS3, thereby reducing TLR signalling pathways and inhibiting pro-inflammatory cytokine release (Rothlin et al. 2007; Lemke & Rothlin 2008; Sharif et al. 2006), while inducing the production of TGFβ, IL-10 and prostaglandins (Chung et al. 2007; Voll et al. 1997; Korns et al. 2011; Xiao et al. 2008). This anti-inflammatory alveolar macrophage state is important in promoting tolerance to host cells and preventing autoimmunity (Krysko et al. 2006).

1.6 The role of alveolar macrophages in host defence

The lungs are continuously exposed to environmental pathogens, with alveolar macrophages being at the forefront of combating an infection through their location in the alveolar lumen. In contrast to the clearance of dying cells under homeostatic conditions, engulfment of pathogens or infected cells requires an inflammatory response in order to remove the pathogenic threat. Efferocytosis of infected apoptotic cells leads to the production of pro-inflammatory cytokines and activation of the adaptive immune system by dendritic cell maturation and thus T cell activation (McCubbrey & Curtis 2013), which is necessary to control the invading pathogen. Later in the infection, should the pathogen be eliminated, macrophages switch their function towards tissue repair and contribute to the removal of recruited apoptotic immune cells by efferocytosis. Removal of recruited immune cells is crucial to prevent them from undergoing secondary necrosis that would extend the inflammatory period by the release of DAMPs (Akbar et al. 1994; Razvi et al. 1995; Chen et al. 2006). The anti-inflammatory mediators released by alveolar macrophages during efferocytosis promote and maintain airway homeostasis by enhancing tissue repair and suppressing inflammation (Korns et al. 2011).

1.7 Airway host defence to viral infection

1.7.1 Pattern recognition receptors

Airway cells are continuously exposed to inhaled microbes from the external environment, and therefore defence systems in the airways need to be in place to detect potentially harmful pathogens. The detection of microbial pathogens in the airways is orchestrated by sensor cells expressing a plethora of receptors that are adapted to detect a wide range of viral and bacterial components (Iwasaki et al. 2016). These receptors are known as PRRs and include TLRs, RIG-I-like receptors (RLRs), NOD- like receptors (NLRs) and c-type lectins (Leiva-Juárez et al. 2017; Yan & Chen 2012). Following initial pathogen recognition, activation of PRRs on airway epithelial cells, alveolar macrophages and DCs initiates the release of cytokines, chemokines, eicosanoids and type I interferons (IFNs) into the airspaces (Iwasaki & Pillai 2014; Iwasaki et al. 2016). Pro-inflammatory cytokines and eicosanoids promote local inflammation and initiate adaptive immune responses to combat the infection (Iwasaki & Pillai 2014). Chemokines initiate the recruitment of monocytes, neutrophils and natural killer (NK) cells to the site of infection, where NK cells target infected airway epithelial cells that have lost or reduced major histocompatibility complex (MHC) I (Gazit et al. 2006), and monocytes and neutrophils aid alveolar macrophages in removing infected dead cells (Hashimoto et al. 2007). Type I IFNs stimulate the production of hundreds of interferon-stimulated genes (ISGs), leading to cell-intrinsic and extrinsic antiviral activity (Chen et al. 2017).

1.7.2 Toll-like receptors

TLRs vary widely in the ligands that they bind to, allowing them to detect a substantial range of molecular patterns, known as pathogen-associated molecular pathogens (PAMPs) and DAMPs (Medzhitov 2001; Janeway 1989). The TLR receptors were originally identified in Drosophila with 10 functional TLR receptors to date having been described in humans (Sandor & Buc 2005). TLRs are characterised by the presence of leucine-rich repeats (LRRs) in their extracellular domains, which are responsible for recognising PAMPs (Parker et al. 2007; Botos et al. 2011). TLRs also contain a toll/IL-1 receptor (IL-1R) (TIR) cytoplasmic domain that recruits adapter proteins, including 28

Myeloid differentiation primary response 88 (MyD88), to initiate downstream signalling pathways and allows TLRs to tailor an appropriate immune response to a specific pathogen (Yan & Chen 2012; Gay et al. 2014).

Based on their cellular location, the TLR receptors can be subcategorised, with those TLRs expressed at the cellular surface (TLR1, TLR2, TLR4, TLR5, TLR6 and TLR10) more commonly involved in the detection of lipid and protein ligands, whereas those localised in endosomal compartments (TLR3, TLR7 TLR8 and TLR9) are known for their recognition of viral nucleic acids (Gay et al. 2014). The TLR receptors all have a variety of different ligands. TLR2 recognises lipoteichoic acid (LTA) from gram-positive bacteria, mycobacteria, whole bacteria, for example, heat killed Listeria monocytogenes, and zymosan, a cell wall component of yeast (Sandor & Buc 2005; Knapp et al. 2004). TLR2 forms heterodimers with TLR1 and TLR6 (Kirschning & Schumann 2002; Knapp et al. 2004), thereby allowing for a greater diversity in the immune response generated (Suzuki et al. 2008). TLR4 is the best characterised TLR receptor and lipopolysaccharide (LPS) is the most well-defined ligand for this receptor (Qureshi et al. 1999; Hoshino et al. 1999), but it is also capable of detecting viral proteins (Rassa et al. 2002). Interestingly, TLR4 also recognises endogenously-derived molecules including heat shock proteins and fibronectin, among others (Rallabhandi et al. 2006). In addition, the cofactors, CD14 and MD2, are required for TLR4 receptor signalling (Zanoni et al. 2011). The only known ligand for TLR5 is flagellin, a component of bacterial flagella (Hayashi et al. 2001). As mentioned above, the endosomal TLRs recognise viral nucleic acids, with TLR3 detecting double-stranded RNA (dsRNA) (Alexopoulou et al. 2001), TLR7 and TLR8 recognising single-stranded RNA (ssRNA) (Heil et al. 2003; Diebold et al. 2004; Tanji et al. 2013) and TLR9 being able to identify unmethylated CpG dinucleotides in viral and bacterial DNA (Latz et al. 2007)

MyD88 is an essential adapter protein for all TLRs, except for TLR3, which requires TIR- domain-containing adapter-inducing interferon-β (TRIF) (Yamamoto et al. 2003; Yamamoto et al. 2002; Gay et al. 2014). MyD88 recruits members of the interleukin-1 receptor-associated kinase 1 (IRAK) family, IRAK1, IRAK4 and TNF receptor-associated factor 6 (TRAF6), which activate IKKα and leads to the phosphorylation and degradation of the nuclear factor NF-κB inhibitor IκB (Skaug et al. 2009; Suzuki et al. 2008). Subsequently, NF-κB activates the mitogen-activated protein kinase (MAPK) 29 and Phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K) signalling pathways, allowing the transcription of diverse pro-inflammatory cytokine genes (Ropert et al. 2001; Yan & Chen 2012).

MyD88 and TRAF6 also recruit the transcription factor interferon regulatory factor 7 (IRF7), which is phosphorylated by IKKα and initiates type I IFN production, in particular IFNα (Colonna 2007). TLR3 activation leads to the recruitment of TRIF, which assembles with TRAF2 and TANK binding kinase 1 (TBK1) to activate IRF3 and IRF7, resulting in type I IFN production (Yamamoto et al. 2003; O’Neill & Bowie 2007). TLR4 activates MyD88-dependent and MyD88-independent pathways. The MyD88 pathway leads to the production of pro-inflammatory cytokines, whereas the MyD88- independent requires the TRAM and TRIF adaptor proteins to induce the production of type IFNs (Figure 1.3). Interestingly, while the MyD88-dependent pathway is activated at the plasma membrane, the subsequent activation of the MyD88-independent pathway occurs intracellularly within endosomes (Kagan et al. 2008).

Figure 1.3: The production of type I IFNs by TLR receptor signalling. TLR3 and TLR4 downstream signalling leads to the activation of the adapter protein, TRIF, whereas the TLRs expressed in endosomes utilise the adapter protein, MyD88. TLR4 also requires the TRAM adapter protein. TRIF recruits TRAF3, which leads to the activation of TBK1, IKKε and the transcription factor IRF3. MyD88 recruits IRAK1, IRAK4 and TRAF6, leading to the activation of IKKα and phosphorylation of the transcription factor IRF7. Activation of IRF3 and IRF7 lead to the production of the type I IFNs. Adapted from (Zhao et al. 2014).

1.7.3 The Interferons

The IFNs were originally discovered based on their ability to ‘interfere’ with viral replication in cells (Gessani et al. 2014; Yan & Chen 2012; McNab et al. 2015) and it is now well established that these proteins exert potent antimicrobial effector functions against intracellular pathogens (Sadler & Williams 2008; MacMicking 2009). High levels of IFNs are secreted in response to pathogen detection by PRRs (Paludan & Bowie 2013; Goubau et al. 2013; Durbin et al. 2000; Huber & Farrar 2011). The IFNs are divided into three classes (Ivashkiv & Donlin 2014). The type I IFN family comprise IFNα, which exists as 13 isoforms in humans, a single IFNβ member, and the less well

31 defined IFNε, IFNk, IFNω, and IFNδ members, all of which signal through the common heterodimeric receptor, the interferon-alpha/beta receptor (IFNAR) (de Weerd & Nguyen 2012; Pestka et al. 2004). The type II IFNs have one member, IFNγ, which is mainly produced by NK cells and T cells and signals through the interferon-gamma receptor (IFNGR) (Schoenborn & Wilson 2007). IFNλ1, 2 and 3 (also known as IL-29, IL- 28A and IL-28B, respectively) constitute the type III IFNs, and all signal through the interferon-lambda receptor (IFNLR) (Levy et al. 2011; Li et al. 2009). A fourth member, IFNλ4, has also recently been discovered (O’Brien et al. 2014; Prokunina-Olsson et al. 2013). Although type I and type III IFNs have comparable functions, the receptor for the type III IFN receptor is limited to epithelial cell surfaces, whereas IFNAR is much more widely expressed (Witte et al. 2010; Durbin et al. 2013).

The type I IFNs are most well known for their impact on cell-intrinsic antiviral functions in infected and surrounding cells, that results in control of the spread of viruses (Ivashkiv & Donlin 2014; Yan & Chen 2012). However, these cytokines also have profound effects on the innate and adaptive immune responses to infection (McNab et al. 2015). For example, type I IFNs promote NK cell functions and enhance the surface expression of MHC and co-stimulatory molecules on DCs, thereby facilitating T cell activation (Montoya et al. 2002; Ito et al. 2001).

1.7.3.1 Type I interferon production

Almost all cell types contain the signalling components associated with IFNβ production, and therefore are capable of mounting type I IFN responses, whereas haematopoietic cells, such as plasmacytoid DCs (pDCs), are the predominant producers of IFNα (Ivashkiv & Donlin 2014). The PRRs that are potent producers of the type I IFNs include the TLRs; TLR3, TLR4, TLR7 and TLR9, and the cytosolic RLR, RIG-I (McNab et al. 2015). The transcription factors; IRF3 and IRF7, are shared by all the downstream signalling pathways of these PRRs (Tamura et al. 2008; Honda & Taniguchi 2006). TLR3 and TLR4 mediate type I IFN production by signalling through TRIF, which activates TBK1 and subsequently phosphorylates IRF3 (Yamamoto et al. 2003). Conversely, TLR7 and TLR9 utilise the adapter protein MyD88 to stimulate type I IFN production (Häcker et al. 2006). In addition, RIG-I activates TBK1 and IRF3 through the mitochondrial

32 antiviral-signalling protein (MAVS) to initiate IFNα and IFNβ production (Sun et al. 2006).

1.7.3.2 Interferon-stimulated genes

Despite the diversity of members of the Type I IFN family, all bind to the heterodimeric receptor, IFNAR, which is composed of IFNAR1 and IFNAR2 subunits (Pestka et al. 2004; Gough et al. 2012). IFNAR ligation activates the janus kinases (JAK)- signal transducers and activators of transcription (STAT) pathway (Levy & Darnell 2002; Stark et al. 1998). Phosphorylation of STAT1 and STAT2 induces their dimerization and translocation to the nucleus, where they recruit IRF9 to form the interferon-stimulated gene factor 3 (ISGF3) complex (Levy & Darnell 2002; Stark & Darnell 2012). This complex binds to IFN-stimulated response elements (ISREs), which in turn initiates the transcription of ISGs (Levy & Darnell 2002) (Figure 1.4). The ISGs encode a wide range of proteins that restrict viral infection and spread, including inhibition of viral transcription, translation and replication, the degradation of viral nucleic acids and the alteration of cellular lipid metabolism (MacMicking 2012; Saka & Valdivia 2012). Approximately 2000 human and mouse ISGs have been identified and catalogued in the Interferome database (Hertzog et al. 2011). A large proportion of ISGs encode proteins with antiviral functions, however they also encode cytokines, chemokine and molecules involved in apoptosis (Wang et al. 2008). In addition, transcription factors involved in the production of type I IFNs, such as IRFs and STATs, are also ISGs (Der et al. 1998). This ensures a continuous feedback loop to amplify type I IFN production. It is clear that distinct subsets of ISGs are required for different viral infections (McNab et al. 2015). The best characterised ISGs in influenza a virus infection will be described below in order to give examples of the roles of these genes in viral infection.

Figure 1.4: The type I IFN signalling pathway. The type I IFNs (IFNα and IFNβ) bind to their receptor IFNAR. This leads to the recruitment of TYK2 and JAK1, which subsequently leads to the phosphorylation of STAT1 and STAT2. IRF9 is recruited to form the ISGF3 complex. This complex binds to IFN-simulated response elements (ISREs) and triggers the production of interferon-stimulated genes (ISGs). Adapted from (Platanias 2005).

1.8 Airway host defence to Influenza virus infection

The Influenza virus is a member of the orthomyxovirus family and is composed of haemagglutinin (HA) and neuraminidase (NA), which are used to identify the virus subtype (Iwasaki & Pillai 2014). Upon entering the respiratory tract, the influenza virus first encounters the mucus layer formed over the airway epithelium. The virus must evade this defence mechanism in order to successfully infect airway epithelial cells and subsequently airway immune cells, including alveolar macrophages and dendritic cells (Manicassamy et al. 2010; Perrone et al. 2008). The influenza virus invades cells by binding to cells with α-2,6 or α-2,3-linked sialy glycans on their surface (Shinya et al. 2006; Thompson et al. 2006).

Several families of PRRs detect the presence of the influenza virus, including the TLRs (TLR3, TLR7 and TLR8), the RLRs (RIG-I) and NLRs (NLRP3) (Le Goffic et al. 2007; Diebold et al. 2004; Demaria et al. 2010; Allen et al. 2009). The signalling components of the TLR3 and RIG-I signalling pathways are present in airway epithelial cells, alveolar macrophages and conventional dendritic cells (cDCs) (Le Goffic et al. 2007), whereas TLR7 is predominantly expressed in alveolar macrophages and pDCs (Diebold et al. 2004). Although pDCs are largely considered the main producers of type I IFNs, in influenza virus infection alveolar macrophages fulfil this role and secrete large amounts of IFNα and IFNβ (Kumagai et al. 2007; Goritzka et al. 2015).

1.8.1 Interferon-stimulated genes important in influenza virus infection

Several ISGs have important roles in host defence against all stages of the influenza virus life cycle, including entry and replication. The myxoma resistance protein (MX) family have potent antiviral activity against orthomyxoviruses, such as influenza (Haller & Kochs 2011). The mouse MX1 protein and the human MXA protein both restrict influenza virus entry into cells (Pavlovic et al. 1995; Haller & Kochs 2011; Mordstein et al. 2010). Mouse Mx1 and human MxA target viral ribonucleoproteins and block primary transcription of influenza virus genes (Pavlovic et al. 1992; Turan et al. 2004). In the case of MxA this is thought to occur by MxA proteins recognising and self- assembling MxA rings around viral ribonucleoproteins, preventing nuclear entry and therefore viral transcription (Gao et al. 2011; Daumke et al. 2010). In addition, interferon-induced transmembrane (IFITM) proteins restrict influenza virus replication (Brass et al. 2009) and specifically, mice deficient in IFITM3 are highly susceptible to influenza virus infection (Everitt et al. 2012). The influenza virus enters cells via the endocytic pathway (Yount et al. 2012). IFITM3 resides in late endosomal and lysosomal structures and thereby has a role in viral degradation (Perreira et al. 2013; Smith et al. 2014). The 2′-5′-oligoadenylate synthase (OAS) family and ribonuclease L (RNase L) work in concert to restrict viral replication through viral DNA degradation (Sadler & Williams 2008). Protein kinase R (PKR) is a serine/threonine kinase that binds to viral ssRNA and dsRNA to inhibit influenza virus replication. This is achieved through PKR phosphorylating eukaryotic translation initiation factor 2α (EIF2α), which results in the nonspecific inhibition of both host and viral protein (Elde et al. 2009).

Therefore, PKR activation leads to cell apoptosis and autophagy, effectively restricting viral spread (McCarroll et al. 2008). Similarly to IFITM3, PKR-deficient mice are also highly susceptible to influenza virus infection (Balachandran et al. 2000).

1.8.2 Dysregulation of the type I IFN response

Type I IFN production is tightly regulated in order to promote appropriate antiviral effector mechanisms, while simultaneously limiting the level of damage sustained by the host. One way type I IFN responses are controlled is by degradation of IFNAR on the surface of cells (de Weerd & Nguyen 2012). Viruses and tumour cells induce the degradation of IFNAR and consequently escape type I IFN-mediated responses (Liu et al. 2009). The SOCS proteins, SOCS1 and SOCS3, whose expression is induced by type I IFNs, and ubiquitin-specific protease 18 (USP18) exert negative feedback on type I IFN signalling and therefore suppress the extent and duration of the response (Yoshimura et al. 2007; Sarasin-Filipowicz et al. 2009).

Type I IFNs are firmly recognised as beneficial in acute viral infections. However, dysregulation of the type I IFN response is evident in a number of autoimmune diseases, including systemic lupus erythematosus (SLE) and rheumatoid arthritis (Hall & Rosen 2010). Furthermore, a distinct IFN signature is observed in chronic viral infections, such as hepatitis C (HCV) and human immunodeficiency virus (HIV) (Forster 2012). This further illustrates the importance of tightly regulating the type I IFN response in order to prevent the development of chronic disease.

1.9 The role of macrophages in airway disease

1.9.1 The adaptation and plasticity of macrophages to their environment

Alveolar macrophages express a unique repertoire of receptors that make them easily distinguishable from not only other lung myeloid cells but from other tissue-resident macrophages. Tissue-resident alveolar macrophages express high levels of CD11c and SiglecF, but low levels of CD11b; a common macrophage marker (Zaynagetdinov et al. 2013; Misharin et al. 2013). Nevertheless, macrophages display plasticity and as a result can respond and adapt to changes in their microenvironment. Lung and peritoneal macrophages differ greatly in the genes that they express, which is owed in 36 part to environmental cues in their tissue surroundings (Lavin et al. 2015). Evidence shows that peritoneal macrophages transferred into the lung up-regulate genes specific to lung macrophages, including PPARγ and CD11c, and concurrently down- regulate genes known to be specific to peritoneal macrophages, such as GATA binding protein 6 (GATA6) (Lavin et al. 2014). Although these peritoneal macrophages did retain some genes associated with their tissue of residence, for example, CD11b, this data substantiates the ability of macrophages to adapt to different tissue-derived signals and to maintain a level of plasticity even after terminal differentiation in other tissue microenvironments.

1.9.2 Classically activated and alternatively activated macrophages

Similar to the distinction of T cell subsets, attempts have been made to categorise macrophages. Originally the plasticity division of macrophages was through their role in distinct T helper (Th)1-type and Th2-type immune responses. Classically activated macrophages or M1 macrophages are produced by LPS or IFNγ stimulation in a STAT1 dependent manner (Hardison et al. 2012; Chinen et al. 1999). M1 macrophages mediate host defence against pathogens by microbicidal activity (Ding et al. 1988; Huang et al. 1993). In contrast, alternatively activated macrophages or M2 macrophages are polarised through activation with IL-4 and IL-13 in a STAT6 dependent manner (Takeda et al. 1996). M2 macrophages are further subdivided into M2a (induced by IL-4 or IL-13), M2b (induced by immune complexes or TLR/IL-1R ligands) and M2c (induced by IL-10 or glucocorticoids) categories (Mantovani et al. 2004). M2a macrophages are important in the allergic immune response, M2b macrophages play a role in immunoregulation and M2c macrophages promote matrix deposition and tissue remodelling (Martinez & Gordon 2014). Though we began with M1 and M2 polarisation, the reality is much more complex and classification is now reliant on specific macrophage functions. Macrophages can alter their phenotype depending on the cytokines they come into contact with. For example, macrophages previously polarised towards an M1 phenotype by activation with IFNγ can be polarised towards an M2 phenotype in the presence of IL-4, and vice versa (Stout et al. 2005; Davis et al. 2013). Furthermore, murine M1 and M2 macrophages are activated by stimulation with GM-CSF and macrophage colony-stimulating factor (M-CSF),

37 respectively (Verreck et al. 2004; Xu et al. 2007). However, what is clear is that the simplified categorisation of macrophages towards an M1 or M2 phenotype does not fully elucidate the complexity of the cytokine milieu in diseased tissue.

1.10 Chronic airway disease

Chronic airway diseases are characterised by airway obstruction and chronic inflammation (Holtzman et al. 2014; Pappas et al. 2013). The most common, COPD and asthma, cause a high level of morbidity and mortality throughout the world (Holtzman et al. 2014) and both are associated with exacerbations by respiratory pathogens (Table 1.1). COPD encompasses a range of diseases including chronic bronchitis, which manifests as inflammation of the larger airways, and emphysema, characterised by destruction of alveolar tissue and airspace enlargement (Hiemstra 2013). However, in all of these heterologous diseases, macrophages represent important contributors to disease development and progression (Lee 2012; Pappas et al. 2013).

Rank Cause Deaths % of Cumulative Crude Death (000s) total % of total Rate (CDR) deaths deaths (per 100 000 population) 0 All Causes 56,441 100.0 100.0 768.5 1 Ischaemic heart disease 8,756 15.5 15.5 119.2 2 Stroke 6,241 11.1 26.6 85.0 3 Lower respiratory infections 3,190 5.7 32.2 43.4 4 Chronic obstructive pulmonary disease 3,170 5.6 37.8 43.2 5 Trachea, bronchus, lung cancers 1,695 3.0 40.8 23.1 6 Diabetes mellitus 1,586 2.8 43.7 21.6 7 Alzheimer disease and other dementias 1,542 2.7 46.4 21.0 8 Diarrhoeal diseases 1,389 2.5 48.8 18.9 9 Tuberculosis 1,373 2.4 51.3 18.7 10 Road injury 1,342 2.4 53.7 18.3 11 Cirrhosis of the liver 1,162 2.1 55.7 15.8 12 Kidney diseases 1,129 2.0 57.7 15.4 13 HIV/AIDS 1,060 1.9 59.6 14.4 14 Preterm birth complications 1,058 1.9 61.5 14.4 15 Hypertensive heart disease 942 1.7 63.1 12.8 16 Liver cancer 788 1.4 64.5 10.7 17 Self-harm 788 1.4 65.9 10.7 18 Colon and rectum cancers 774 1.4 67.3 10.5 19 Stomach cancer 754 1.3 68.7 10.3 20 Birth asphyxia and birth trauma 691 1.2 69.9 9.4

Table 1.1: World health organisations (WHOs) estimates for the global 20 leading causes of death in 2015. Lower respiratory infections and chronic obstructive pulmonary disease are within the top 4 causes of mortality globally.

COPD and asthma are typically described as diseases containing Th1-associated neutrophilic airway inflammation and Th2-driven eosinophilic airway inflammation, respectively (Keatings et al. 1996). These polarised outcomes are likely dependent on the antigen inciting inflammation, but also the complexity of the underlying innate immune response. However, it is now recognised that these conditions are not as discrete as originally implied. Indeed, neutrophilic asthma is one of the most severe forms of this disease. Furthermore, airway macrophages from COPD patients exhibit characteristics of M2 macrophages and produce factors that are involved in airway remodelling, such as TGFβ and matrix metalloproteinases (MMPs) (Shaykhiev et al. 2009). Regardless of their activation state, however, what is apparent is that macrophages from asthmatic and COPD patients are functionally impaired. These macrophages display a reduced ability to phagocytose viruses or bacteria and

39 efferocytose infected or dying cells, which overall contributes to an enhanced susceptibility to bacterial and viral infections and a persistently heightened inflammatory response (Sethi et al. 2009; Hodge et al. 2003; Moreira & Hogaboam 2011).

1.11 Neuroimmune crosstalk

There is significant evidence for bi-directional crosstalk between the nervous and immune systems. Not only are neuronal receptors expressed on immune cells, but nerves can detect factors secreted by immune cells and directly respond to environmental challenges. Considering this, the immune system and nervous system have evolved similar mechanisms to detect and respond to danger signals (Chiu et al. 2012). The airways are densely innervated with sensory nociceptive neurons which are sensitive to mechanical, thermal and chemical stimuli (Canning & Mazzone 2006). Sensory neurons innervate the epithelial cell layer making their location within the airways ideal for rapid detection of pathogens and, importantly, their response to stimuli is much quicker than that of immune cells (Tracey 2009; Andersson & Tracey 2012). These sensory neurons express many of the same pattern recognition receptors that were characterised originally on immune cells. Peripheral sensory neurons are known to express TLR3, 4 7 and 9 receptors and therefore can directly sense invading pathogens and endogenous danger molecules (Liu et al. 2012). Bacteria, such as Staphylococcus aureus, directly activate sensory nociceptors (Chiu et al. 2013) and LPS directly binds TLR4 expressed on sensory neurons (Acosta & Davies 2008). Airway nociceptive neurons are then able to communicate the threat detected to innate immune cells through release of neuronal factors. These neuronal factors include neuropeptides such as CGRP and substance P, which recruit immune cells to the site of inflammation leading to their activation and increased pro-inflammatory cytokine release, thereby enhancing the inflammatory response (Talbot et al. 2015). Innate immune cells are reciprocally able to communicate with peripheral nerves as sensory nociceptive neurons express receptors for the pro-inflammatory cytokines TNF-α and IL-1β, which are released by airway macrophages (Binshtok et al. 2008; Zhang & Dougherty 2011).

1.12 Neurotrophic factors

Neurotrophic factors are defined by their ability to regulate neuronal differentiation, development and survival (Airaksinen & Saarma 2002). Four categories of neurotrophic factors have been described; the neurotrophins, the glial cell line-derived neurotrophic factor (GDNF) family, the neuropoietic cytokines and the cerebral dopamine neurotrophic factor (CDNF)/mesencephalic astrocyte-derived neurotrophic factor (MANF) family (Figure 1.5). These factors are classed as growth factors in much the same way as TGFβ, vascular endothelial growth factor (VEGF) and fibroblast growth factor (FGF) and more recent studies highlight their importance as trophic factors for non-neuronal cells (Sidorova & Saarma 2016). The neurotrophin family is made up of NGF, brain-derived neurotrophic factor (BDNF), neurotrophin 3 (NT3) and neurotrophin 4 (NT4), which signal through the Trk and p75NTR receptors (Bothwell 2016). The GDNF family ligands (GFLs) consist of GDNF, neurturin (Nrtn), artemin (Artn) and persephin (Pspn) and bind to their respective GDNF family receptor alpha (GFRα) and the canonical signalling tyrosine kinase receptor, RET (Airaksinen & Saarma 2002). The neuropoietic cytokines, ciliary neurotrophic factor (CNTF) and leukemia inhibitory factor (LIF) signal through the IL-6 receptor signal-transducing component gp130 and the LIF receptor (LIFR) and CNTF receptor (CNTFR), respectively (Ip et al. 1992). The receptors for CDNF and MANF remain to be described (Lindholm & Saarma 2010).

Figure 1.5: Neurotrophic factor receptors and ligands. The neurotrophin ligands, NGF, BDNF, NT3 and NT4 bind to the p75NTR receptor and their respective Trk receptors (TrkA, TrkB and TrkC). The GDNF family ligands GDNF, Nrtn, Artn and Pspn bind to their preferential GFRα receptors (GFRα1-4) and the canonical co-receptor, RET. The neuropoietic cytokines, LIF and CNTF, bind to gp130, the LIF receptor (LIFR) and the CNTF receptor (CNTFR). The receptor for CDNF and MANF is currently unknown. Adapted from (Bradshaw et al. 2015; Airaksinen &

Saarma 2002; Bauer et al. 2007; Lindholm & Saarma 2010).

1.12.1 The glial cell line-derived neurotrophic factor family

The GFLs belong to the wider TGFβ superfamily and include GDNF, Nrtn, Artn and Pspn. GDNF was first discovered as a trophic factor for embryonic midbrain dopamine neurons (Lin et al. 1993). Thereafter, Nrtn was identified as a survival factor for sympathetic neurons (Kotzbauer et al. 1996), with Artn and Pspn discovered on the basis of sequence homology (Baloh et al. 2000). The GFLs bind to their cognate GFRα receptors, GDNF to GFRα1, Nrtn to GFRα2, Artn to GFRα3 and Pspn to GFRα4 (Airaksinen et al. 1999). This binding is preferential; however, some crosstalk has been described. For example, Nrtn and Artn bind to GFRα1, with GFRα2 and GFRα3 also able to bind the GDNF ligand (Airaksinen & Saarma 2002). The GFRα receptors require 42 the receptor tyrosine kinase, RET, in order to signal (Takahashi 2001). RET was originally defined as a proto-oncogene, with activating mutations in the RET gene leading to the development of cancer, including human thyroid carcinomas (PTC and FMTC) and multiple neoplasia type 2 (MEN2) (Pasini et al. 1996; Edery et al. 1994). For this reason, RET is considered a therapeutic target in certain cancers (Mulligan 2014). Conversely, inactivating mutations of RET are found in Hirschsprung’s disease (Attié et al. 1995).

1.12.2 RET-dependent GDNF family signalling

The original principal of GDNF family signalling outlines the requirement of GFL binding to the membrane-bound GPI-anchored GFRα receptor, which subsequently activates RET, inducing its homodimerisation and phosphorylation. This stimulates multiple downstream signalling pathways, including Ras/ERK (Santoro et al. 1994; Worby et al. 1996), PI3k/Akt (van Weering & Bos 1997), PLCγ (Borrello et al. 1996) and JNK pathways (Chiariello et al. 1998; Xing et al. 1998) (Figure 1.6). Conversely, in the absence of GFLs, the GPI-anchored protein Gas1, which is a pro-apoptotic factor, can interact with RET and promote cell death (Cabrera et al. 2006). This is corroborated by evidence showing that when RET is overexpressed in certain cell lines, apoptosis is triggered if GFLs are not present (Bordeaux et al. 2000).

Several mechanisms exist which allow the GFLs to mediate a wide range of functions. Firstly, RET activation can trigger the recruitment of diverse adapter proteins, such as FRS2, Shc, DOK4/5, IRS1/2 and enigma (Schlessinger 2000). Secondly, in many cell types the GFRα receptors are expressed without RET and a number of alternative co- receptors have been proposed, which are described in more detail below. Thirdly, two predominant RET isoforms exist in mammals namely the long isoform (RET51) and the short isoform (RET9) (Tahira et al. 1990). These isoforms have distinct functions, for example, RET9-deficient mice have severe loss of gut and renal neuronal innervation, whereas RET51-deficient mice are unaffected (de Graaff et al. 2001).

As the GFRα receptors are more widely expressed compared to RET, this gave rise to the investigation of whether GFRαs are cleaved from the cell membrane and act on neighbouring RET-expressing cells. Studies report Schwann cells can produce soluble

GFRα1, which subsequently activates RET on peripheral sympathetic and sensory neurons and, in collaboration with GDNF, support nerve regeneration (Naveilhan et al. 1997; Trupp et al. 1997).

Figure 1.6: RET-dependent GDNF family signalling. The GDNF family ligands bind to their respective GFRα receptors, which leads to the recruitment and activation of the canonical co- receptor, RET. RET recruits the adapter proteins Enigma, FRS2, Shc, IRS1, c-Src, DOK4/5, Grb2 and PLCγ. This leads to the phosphorylation of JNK, ERK and Akt and subsequent activation of c-JUN, CREB and NF-κB. Adapted from (Takaki et al. 2014).

1.12.3 GDNF family signalling in lipid rafts

Cellular localisation of the RET receptor can affect activation of signalling cascades. The most effective RET signalling is believed to occur in membrane lipid rafts, which

44 are pockets of specialised microdomains that highly express shingolipids and cholesterol within the plasma membrane (Simons & Sampaio 2011). Lipid rafts bring signalling molecules into close proximity with receptors and therefore facilitate their interaction and downstream receptor signalling (Simons & Toomre 2000). GPI- anchored receptors have affinity for lipid rafts and therefore the GFRα receptors are located within these regions (Poteryaev et al. 1999). RET is recruited to lipid rafts following GFL binding to a GFRα receptor (Tansey et al. 2000). Once activated, RET is rapidly internalised into endosomes for lysosomal or proteosomal degradation or is recycled back to the cell surface (Crupi et al. 2015).

1.12.4 RET-independent GDNF family signalling

RET interaction with the GFRα receptors is the canonical pathway that mediates GFL signalling. However, some cell types expressing the GFRα receptors and can signal independently of RET (Poteryaev et al. 1999; Trupp et al. 1999). This led to the hypothesis that the GFLs can signal through alternative receptors. It is now well established that NCAM is a co-receptor for GDNF and promotes the migration of Schwann cells and axonal growth in hippocampal and cortical neurons (Paratcha et al. 2003). On the other hand, it was first thought that Nrtn was unable to signal without RET (Pezeshki et al. 2001). This has since been disproved following the discovery that the GFLs have high affinity for the ECM heparan sulfate proteoglycan, syndecan-3, and signalling through this receptor can promote the migration of gamma-aminobutyric acid-ergic (GABAergic) neurons (Bespalov et al. 2011). In support of this, the activity of several other growth factors, such as FGFs and BMPs, are also modulated by syndecans (Bernfield et al. 1999; Bishop et al. 2007).

1.12.5 The functions of the GDNF family in the nervous system

Studies describing the phenotype of GDNF family gene deletions in mice have alluded to the function of these neurotrophic factors in the development of specific neuronal subpopulations within the central and peripheral nervous systems. However, because of the severe defects these mice present with, it is difficult to utilise these mice in experiments that determine the role of the GFLs outside of development and the nervous system. GFRα1, GDNF and RET knockout mice are not viable and die soon

45 after birth. These mice all have kidney agenesis and a loss of parasympathetic and enteric neurons (Schuchardt et al. 1994; Enomoto et al. 1998; Sánchez et al. 1996). On the other hand, GFRα2 and Nrtn knockout mice have similar defects in enteric and parasympathetic neurons but to a lesser degree and are viable and fertile (Rossi et al. 1999; Heuckeroth et al. 1999). These mice display a similar phenotype to each other with a significant reduction in substance P producing myenteric nerves in the small intestine (Rossi et al. 1999; Heuckeroth et al. 1999) . The majority of studies have focussed on neuronal deficits that GDNF family knockout mice exhibit and therefore knowledge on their function is better characterised in the nervous system.

1.12.6 The GDNF family in neurological diseases

Due to their effective role in neuronal repair and survival, the GDNF family have proven promising targets in the treatment of neurological diseases, such as Parkinson’s disease and Alzheimer’s disease, and in the treatment of neuropathic pain and spinal cord injury (Ibáñez & Andressoo 2017). Specifically, GDNF and Nrtn are capable of protecting dopaminergic neurons in rodent and primate models of Parkinson’s disease (Gasmi et al. 2007; Biju et al. 2013; Kordower et al. 2000). Administration of GDNF and Nrtn to patients with Parkinson’s disease has also been tested in clinical trials. However, thus far the beneficial effects of these neurotrophic factors in patients have not been encouraging (Marks et al. 2010; Marks et al. 2016; Gill et al. 2003; Slevin et al. 2005). This is believed to be as a result of the GFLs inability to widely diffuse across tissue. The GFLs have high affinity to ECM proteins, including heparin sulphate proteoglycans (Bespalov et al. 2011), which heavily restricts their movement and limits the amount of tissue these factors can penetrate (Hamilton et al. 2001; Piltonen et al. 2009).

1.13 The neuroimmune crosstalk in lymphatic tissue

The region of the body where the crosstalk between immune cells and nerves has been most extensively studied is in the bone marrow, thymus, lymph nodes and spleen. This is because these areas have dense networks of neurons that modulate the activity of haematopoietic cells due to their close proximity (Chavan & Tracey 2017). The bone marrow microenvironment is innervated by sympathetic nerves which come

46 into close contact with haematopoietic stem cells (HSCs) (Yamazaki et al. 2011). In the bone marrow, norepinephrine produced by sympathetic neurons promotes the migration of HSCs into the bloodstream via regulation of C-X-C motif chemokine 12 (CXCL12) expression (Katayama et al. 2006; Méndez-Ferrer et al. 2010). Moreover, Schwann cells that surround bone marrow sympathetic neurons regulate HSC quiescence via activation of TGFβ (Yamazaki et al. 2011). In the spleen, vagus nerve- mediated signals inhibit pro-inflammatory cytokine release by red pulp and marginal zone macrophages, and shifts their phenotype towards a more anti-inflammatory and protective ‘M2-like’ macrophage (Rosas-Ballina et al. 2011). In this context, vagus nerve stimulation induces the release of acetycholine from T cells, which acts on macrophages expressing the α7 nicotinic acetylcholine receptor (α7nAChR) (Wang et al. 2003; Rosas-Ballina et al. 2011).

1.14 The neuroimmune crosstalk in mucosal tissue

Mucosal sites also constitute another region of the body where the critical functions of neuroimmune communication are becoming increasingly apparent. In the airways, this is most evident in allergic disease. For example, inhibition of sensory nociceptive neuron activation dramatically reduces both airway inflammation and hyperresponsiveness in a mouse model of allergic airway disease (Talbot et al. 2015). This is partially mediated by IL-5, a cytokine produced by CD4+ T cells and group 2 innate lymphoid cells (ILC2s) during allergic airway inflammation, which stimulates sensory nociceptors to produce the neuropeptide vasoactive intestinal peptide (VIP), which then acts in a feedback loop to activate CD4+ T cells and ILC2s (Talbot et al. 2015). In addition, a chemokine for eosinophils, eotaxin, is produced by airway nerves and promotes the clustering of eosinophils around nerves, which is evident in asthmatic patients and antigen-challenged animals (Costello et al. 1997; Fryer et al. 2006). Furthermore, the major basic protein, which is released by eosinophils, inhibits M2 muscarinic receptors expressed on airway nerves, resulting in increased release of acetylcholine and enhanced bronchoconstriction (Evans et al. 1997).

In the intestine, muscularis macrophages support enteric neurons by providing bone morphogenic protein 2 (BMP2), whereas neurons maintain macrophage homeostasis through production of M-CSF (Muller et al. 2014). Muscularis macrophages are further 47 regulated by the neurotransmitter norepinephrine, which is secreted from sympathetic neurons following a bacterial encounter and binds to the β2-adrenergic receptor on these macrophages, overall promoting a tissue repair phenotype (Gabanyi et al. 2016). Moreover, mast cells are often found in close proximity to sensory neurons in the intestine and skin and are able to respond to the neuropeptides, substance P and calcitonin-gene related peptide (CGRP) released by these sensory nerves (van Diest et al. 2012).

Another aspect to consider at barrier sites is the communication between epithelial cells and the surrounding neurons. In the airways, pulmonary neuroendocrine cells secrete neuropeptides, including CGRP, in response to a range of stimuli (Cutz et al. 2013). This leads to the activation of sensory nerves and immune cells, propagating the inflammatory response (Branchfield et al. 2016). In the skin, thymic stromal lymphopoietin (TSLP) released by epithelial cells activates the transient receptor potential cation channel A1 (TRPA1) expressed on sensory nociceptive nerves (Wilson et al. 2013).

1.15 The functions of the GDNF family outside of the nervous system

Further to their essential role in neuronal development, the GDNF family have now been implicated in a wide range of functions outside of the nervous system. GDNF is an essential growth factor in kidney development (Keefe-Davis et al. 2013) and spermatogenesis (Kubota et al. 2004). GFRα2 is a marker for cardiac progenitors and plays a crucial role in heart development, whereas GFRα1 is redundant (Ishida et al. 2016). The precise function of GFRα2 in heart development is still unknown as GFRα2 knockout mice have no reported heart defect,, however, it does appear to be independent of RET (Ishida et al. 2016). A role for Pspn on thyroid C cells has also been described with GFRα4 and RET activation regulating the production of calcitonin by these cells (Lindfors et al. 2006). Furthermore, Nrtn-deficient mice provide a murine model of dry eye disease (Song et al. 2003). This manifests as abnormal corneal epithelial cell function, reduced autonomic nerve innervation in the lacrimal gland and

48 enhanced production of inflammatory mediators, supporting a potential anti- inflammatory role for Nrtn (Song et al. 2003).

1.16 The role of the GDNF family in lymphatic tissue

The GDNF family are implicated in the neuroimmune crosstalk within the bone marrow as RET signalling promotes HSC survival (Fonseca-Pereira et al. 2014). Interestingly, the GFLs are secreted by bone marrow non-haematopoietic support cells, whereas the GFL receptor, RET, is expressed on HSCs (Fonseca-Pereira et al. 2014). Similarly to the bone marrow microenvironment, GFLs are secreted by thymic stromal cells and act on RET-expressing thymocytes to support their survival but not their development (Golden et al. 1999; Kondo et al. 2003; Almeida et al. 2012; Almeida et al. 2014). Furthermore, GFRα1, GFRα2 and RET are poorly expressed in naïve T cells, but are highly up-regulated in effector T cell subsets (Almeida et al. 2014). Stimulation of Th1 and Th2 cells with the GFLs, GDNF and Nrtn, results in the suppression of IL-10 production via the transcription factor, Maf (Almeida et al. 2014). Therefore, although the GDNF family is not essential for T cell development, these neurotrophic factors can regulate T cell effector functions.

1.17 The role of the GDNF family in the Intestine

RET is essential in the development of the enteric nervous system (Schuchardt et al. 1994) and, through the formation of a GFRα3/Artn/RET signalling complex, governs formation of the enteric haematopoietic organ, Peyer’s patches (Veiga-Fernandes et al. 2007). The GDNF family are also important modulators of gut homeostasis and host defence, of which the group 3 ILCs are known to be important mediators (Artis & Spits 2015). Enteric glial cells produce the GFLs, GDNF and Nrtn, following stimulation with TLR agonists or alarmins (Ibiza et al. 2016). This in turn leads to the activation of the RET receptor expressed on ILC3s and subsequent production of IL-22 in a STAT3- dependent manner (Ibiza et al. 2016). IL-22 acts on gut epithelial cells and drives antimicrobial responses (Ibiza et al. 2016). This accumulating data reveals the importance of considering peripheral sensory nerves, and the factors they express and release, when investigating the innate and adaptive immune response in host defence to infection. 49

1.18 The peripheral nervous system and neurotrophic factors in chronic airway disease

Peripheral sensory nerves innervating the lungs cause some of the pathological features of COPD and asthma, including dyspnea, cough and an increased sensitivity to environmental stimuli, known as airway hyperresponsiveness (Audrit et al. 2017). Therefore, studies have tried to elucidate the function of neuroimmune interactions in chronic respiratory disease, especially asthma. The neurotrophins are a family of neurotrophic factors that have been implicated in asthmatic disease. Research into this area began following the report that the levels of the neurotrophin, nerve growth factor (NGF) are enhanced in the serum of patients with allergic asthma compared to healthy subjects (Bonini et al. 1996). Since this discovery, studies have found that neurotrophin levels are increased in the BAL fluid obtained from asthmatic patients (Virchow et al. 1998; Kassel et al. 2001) and mouse models of allergic asthma (Braun et al. 1998; Braun et al. 1999). The neurotrophins are produced by a range of structural and immune cells within the airways following allergen challenge, including epithelial cells, fibroblasts, macrophages, eosinophils and lymphocytes (Braun et al. 1999; Nockher & Renz 2003; Freund & Frossard 2004). The secreted neurotrophins signal through the p75 neurtotrophin receptor (p75NTR) and tropomyosin receptor kinase (Trk) receptors expressed on sensory neurons and trigger the production and release of neuropeptides, including the tachykinin substance P (Pattarawarapan & Burgess 2003; Lindsay & Harmar 1989). Substance P can, in turn, activate a wide range of immune cells and is termed neurogenic inflammation (Barnes 1992) (Figure 1.7). This neurogenic inflammation can exacerbate both allergic airway inflammation and airway hyperresponsiveness. Therefore, the role of neurotrophins in allergic asthma represents a good example of how neuroimmune interactions are important in chronic airway diseases and could be potential therapeutic targets.

Figure 1.7: Neurogenic inflammation in the airways. Immune cells express a range of pattern recognition receptors (PRRs) that detect allergens. This induces an inflammatory response and the release of neurotrophin family ligands. The inflammation causes epithelial cell damage, which exposes sensory neurons to irritants. Epithelial cell and sensory neuron activation leads to the secretion of neuropeptides, which bind to their receptors on immune cells and amplify the inflammatory response.

Other families of neurotrophic factors, such as the glial cell line-derived neurotrophic factor (GDNF) family, have been less studied in chronic airway diseases. Nrtn is structurally similar to the anti-inflammatory cytokine TGFβ and because of this; studies suggest that this neurotrophic factor may also have anti-inflammatory properties. In an ovalbumin (OVA)-induced and house dust mite (HDM)-induced mouse model of allergic asthma, neurturin knockout mice displayed enhanced Th2 cytokine (IL-4, IL-5 or IL-13) expression in BAL fluid and lung tissue, enhanced airway reactivity to methacholine and an increased infiltration of eosinophils to the airways compared to

51 their wild-type counterparts (Michel et al. 2011; Mauffray et al. 2015). Interestingly, TGFβ knockout mice showed a similar worsening of the allergic inflammatory response in a murine asthma model (Scherf et al. 2005). Furthermore, re-introducing Nrtn to the airways before OVA challenge partially rescues this phenotype by decreasing Th2 cytokine production and reducing eosinophil numbers in the airways (Michel et al. 2011). In a chronic model of OVA-induced allergic asthma, neurturin knockout mice exhibited increased neutrophil infiltration, higher levels of the chemokine KC, MMP-9 and the pro-inflammatory cytokines TNF-α and IL-6 and enhanced collagen deposition compared to wild-type mice (Mauffray et al. 2015). Therefore, this data suggests that Nrtn may have a protective role in allergic airway disease by modulating the inflammatory response and the extent of airway remodelling. In this study, Nrtn was found to be expressed in lung tissue; however, the specific cell-types that produce Nrtn were not investigated (Michel et al. 2011). Having said this, the source of Nrtn may also be from outside of the airways in the form of immune cells recruited to the area of inflammation, as it has been shown that human peripheral blood mononuclear cells (PBMCs); monocytes, T cells and B cells, produce Nrtn at the protein level following their activation (Vargas-Leal et al. 2005). Therefore, unlike the neurotrophins, the GDNF family may have a protective role in allergic airway diseases. The role of neurotrophic factors in COPD has not yet been studied; therefore, further research is required to fully appreciate the impact of the neuroimmune crosstalk in chronic airway diseases. However, accumulating data demonstrates the important and diverse roles of the GDNF family in the immune response (Figure 1.8).

Figure 1.8: The roles of the GDNF family in the immune system. 1.19 Research hypothesis and aims

The hypothesis tested in this thesis is that neuropeptides and their receptors impact on macrophage regulation in the healthy and inflamed lung. As we discovered high expression of the GDNF family receptor, GFRα2, on lung macrophages our aims were to:

1) Characterise the expression of the GDNF family receptors, GFRα2 and RET, on mouse and human airway macrophages at homeostasis and airway disease. 2) Determine the source of the GDNF ligand, Nrtn, in the airways and elucidate its effect on airway macrophage functions. 3) Investigate the role of the GDNF family in airway host defence against viral infection.

Chapter 2 : Methods

2.1 Mouse strains

Experiments were performed in female mice aged 8 to 12 weeks of C57BL/6 or BALB/c background (Harlan Olac Ltd, Bicester, UK). Animals were kept in specific pathogen- free conditions at Bio Safety Level 2 with a controlled temperature (21oC ± 1oC), humidity (55% ± 10%) and a 12 h light/dark cycle, with food and water ad libitum. All animal procedures carried out conformed to the requirements of the European Council Directives (86/609/EEC) and the UK Animals (Scientific Procedures) Act, 1986.

2.2 Mouse experimental models

Mouse experimental procedures from 2.2.1 and 2.2.2 were performed by Dr Toshifumi Fujimori.

2.2.1 Influenza infection model

C57BL/6 mice were lightly anaesthetised with isofluorane and infected intranasally with 7.5 plaque forming units (p.f.u) of influenza A virus, Puerto Rico/8/34(PR8), H1N1 or control mice with phosphate buffered saline (PBS). Mice were euthanized by intraperitoneal injection of 3 mg pentobarbitone at specific time points post infection and BAL fluid harvested.

2.2.2 House dust mite model

BALB/c mice were lightly anaesthetised with isofluorane and inoculated intranasally with 15 μg of house dust mite (HDM) extract (Greer, Nebraska, USA, endotoxin: 31.25 EU/vial, Der p 1: 145.56 mcg/vial, protein: 2.78 mg/vial, batch id: XPB70D3A5.5) or PBS as a control 3 times a week for 3 weeks. Mice were euthanized at day 24 by intraperitoneal injection of 3 mg pentobarbitone and BAL fluid, lung lobes and serum harvested.

2.3 Isolation of mouse tissue cells

2.3.1 Isolation of murine bone marrow cells

The hind limbs were removed and the bone stripped of skin and muscle. The femur and tibia were washed with 70 % ethanol and 3 times with sterile phosphate-buffered saline (PBS). The tips of the femur and tibia were cut and bone marrow flushed out with sterile PBS. Cells were centrifuged at 500 x g for 5 minutes, supernatant discarded and the pellet resuspended in red blood cell lysis buffer (Sigma-Aldrich, Dorset, UK) for 3 minutes at room temperature. Cells were resuspended in complete RPMI media (RPMI 1640 containing 100 U/ml of penicillin, 100 µg/ml streptomycin and 20 mM Hepes (all from Sigma-Aldrich, Dorset, UK)) with 20 % fetal calf serum (FCS) (Gibco) and the suspension centrifuged at 500 x g for 5 minutes. The supernatant was discarded and cells resuspended in complete RPMI media containing 20 % FCS (Gibco).

2.3.2 Culture of murine bone marrow-derived macrophages

Cells from the bone marrow were seeded into T75 flasks and incubated with GM-CSF (20 ng/ml) (Peprotech, New Jersey, USA) or M-CSF (20 ng/ml) (Peprotech) in complete RPMI media containing 20 % FCS (Gibco) for 3 days at 37oC. Fresh complete RPMI media (RPMI 1640 containing 10 % FCS (Gibco), 100 U/ml of penicillin, 100 µg/ml streptomycin and 20 mM Hepes (all from Sigma-Aldrich) with GM-CSF or M-CSF was added and cells further cultured for 4-7 days until confluent. Cells were plated at 2.5 x 105 cells/ml in 24-well tissue culture plates and stimulated with lipopolysaccharide (LPS) (100 ng/ml), polyI:C (10 μg/ml) (both from Invivogen), IL-4 (100 ng/ml), IFNy (100 ng/ml), , IL-13 (100 ng/ml) or neurturin (100 ng/ml) (all from Peprotech) and incubated for 24 hours at 37 oC. Cell supernatants were collected and stored at -80 oC until cytokine bead array analysis. Cells were lysed in RLT buffer and stored at -80 oC until RNA extraction.

2.3.3 Isolation of mouse bronchoalveolar lavage macrophages

A 21 G needle was inserted into the mouse trachea and 1 ml of Hank’s balanced salt solution (HBSS) containing 0.05 M Ethylenediaminetetraacetic acid (EDTA) (Sigma- Aldrich) was flushed into the lungs 3 times. The BAL fluid was centrifuged at 300 x g 56 for 5 minutes and the cell pellet resuspended in complete RPMI media. Cells were plated at 2.5 x 104 cells/ml in 96-well tissue culture plates and incubated for 1 hour at 37 oC until cells adhered. Cells were stimulated with 100 ng/ml IL-4, or a combination of 20 ng/ml IFNα and 20 ng/ml IFNβ (all Peprotech). The adhered macrophages were lysed in RLT buffer and stored at -80 oC until RNA extraction.

2.3.4 Digestion of mouse lung tissue

Lung lobes were taken and placed in 1 ml of complete media and finely chopped. The tissue was digested by placing the tissue in complete RPMI media containing 0.13 mg/ml Liberase TM (Roche, Switzerland) and 50 μg/ml DNase I (Roche) and incubated for 30 minutes at 37 °C on a shaker. The lung tissue digest was passed through a 100 μM cell strainer (BD labware, New Jersey, USA) and centrifuged at 500 x g for 5 minutes. The supernatant was discarded and the pellet was resuspended in red cell lysis buffer (Sigma-Aldrich, Dorset, UK) and incubated for 3 minutes at room temperature. Cells were centrifuged at 500 x g for 5 minutes, supernatant discarded and cells resuspended in RPMI complete media and stained for flow cytometry.

2.3.5 Digestion of mouse ear and back skin tissue

Back and ear skin was removed and placed in PBS containing 3 % FCS and 2 mM EDTA. Excess fat was removed from the back skin and ear skin was separated. Skin samples were placed dermis side down on 0.8 % trypsin (Sigma-Aldrich) in complete RPMI media (Sigma-Aldrich) without FCS and incubated for 30 minutes at 37 °C. Samples were placed in FCS to inactivate trypsin and the epidermis peeled away from the dermis and placed in complete RPMI media. The dermis from the ear and back skin was finely chopped in collagenase (Liberase TM, 0.1 mg/ml, Roche, Basel, Switzerland) or dispase II (1 mg/ml, Roche), respectively, for further digestion and incubated for 1 hour at 37 °C on a shaker. Digested dermis and epidermis samples were passed through a 70 μM cell strainer and centrifuged at 400 x g for 4 minutes. Supernatant was discarded and cell pellet resuspended in complete RPMI media. Cells were stained for flow cytometry.

2.4 Isolation of human tissue cells

2.4.1 Isolation of human peripheral blood monocytes

Leukocyte apheresis cones were collected from healthy donors at the national blood transfusion service (Plymouth Grove, Manchester). Equal volumes of sterile PBS and blood were mixed and the diluted blood sample layered onto Ficoll-paque (GE healthcare, Amersham, UK) and centrifuged at 400 x g for 30 minutes at room temperature (acceleration: 1, Deceleration: 0). The peripheral blood mononuclear cell (PBMC) layer at the plasma-Ficoll interface was collected using a Pasteur pipette, washed in sterile PBS and cells counted. A maximum of 1 x 107 PBMCs were incubated with anti-human CD14 magnetic beads (Miltenyi Biotec, Surrey, UK) and MACS buffer (sterile PBS with 0.5 % bovine serum albumin (BSA) and 2 mM EDTA) and incubated at 4 oC for 15 minutes. Cells were centrifuged at 300 x g for 8 minutes, supernatant discarded and pellet resuspended in sterile MACS buffer. Cells were passed through an LS MACS separation column in a MidiMACS separator according to the manufacturer’s instructions (Miltenyi Biotec) to obtain CD14+ monocytes.

2.4.2 Culture of human monocyte-derived macrophages

CD14+ monocytes were plated at 5 x 105 cells/ml in 12-well tissue culture plates and cultured in 50 ng/ml M-CSF (Peprotech) or 50 ng/ml GM-CSF (Peprotech) in complete RPMI media and incubated for 6 days at 37 oC to induce their differentiation into macrophages. Monocyte-derived macrophages (MDMs) were stimulated with LPS (20 ng/ml), polyI:C (10 μg/ml) (both from Invivogen), IFNγ (20 ng/ml), IL-4 (20 ng/ml), IL- 13 (20 ng/ml), IL-10 (20 ng/ml), Nrtn (100 ng/ml), IFNα (20 ng/ml), IFNβ (20 ng/ml) or IFNλ (20 ng/ml) (All from Peprotech) and incubated for 4 or 24 hours at 37 oC. Cell supernatants were collected and stored at -80 oC until ELISA analysis. Cells were stained for flow cytometry or lysed in RLT buffer (Qiagen, Manchester, UK) or RIPA buffer (150mM NaCl, 50mM Tris-HCl, 1% Triton-X100, 0.1% SDS and 0.5% Sodium deoxycholate) with protease inhibitors (Protease Inhibitor Cocktail, Sigma-Aldrich) and phosphatase inhibitors (Phosphatase Inhibitor Cocktail 3, Sigma-Aldrich) and stored at -80 oC until RNA extraction or -20 oC until western blot analysis, respectively.

2.4.3 Isolation of human bronchoalveolar lavage macrophages

3 healthy non-smokers (HNS), 3 COPD patients and 3 healthy smokers (HS) with normal lung function were recruited to undergo bronchoscopy. The bronchoscope was wedged into the lung lobes and sterile 0.9 % NaCl solution was introduced and aspirated. The BAL fluid was centrifuged at 400 x g for 10 minutes and the cell pellet resuspended in complete RPMI media. Macrophages were incubated for 1 hour at 37 oC to allow adherence. Cells were stimulated with LPS (20 ng/ml) or polyI:C (10μg/ml) (both from invivogen) and incubated for 24 hours at 37 oC. Cells were lysed in RLT buffer and stored at -80 oC until RNA extraction.

2.4.4 Isolation and culture of airway macrophages from human lung resection samples

The noncancerous tissue margins of lung resection samples from patients undergoing surgery for suspected or confirmed cancer were collected from the Manchester Allergy, Respiratory and Thoracic Surgery Biobank at the University Hospital of South Manchester. In this study, 10 patients also had underlying COPD and healthy non- smokers were selected based on having no chronic inflammatory lung disease and normal lung function (FEV1/forced vital capacity ratio > 0.70). A 26 G needle and 20 ml syringe were used to perfuse sterile PBS through arteries in the human lung resection samples until the perfusate ran clear. The perfusate was centrifuged at 400 x g for 10 minutes, supernatant discarded and pellet resuspended in sterile PBS. Cells were layered onto Ficoll-paque and centrifuged at 400 x g for 30 minutes at room temperature (acceleration: 1, Deceleration: 0). The leukocyte cell layer at the plasma- Ficoll interface was collected using a Pasteur pipette, washed in sterile PBS and cells counted. Cells were plated at 5 x 105 cells/ml in 12-well tissue culture wells and stimulated with IL-4 (20 ng/ml), IFNα (20 ng/ml), IFNβ (20 ng/ml) IFNγ (20 ng/ml) or IFNλ (20 ng/ml) (all from Peprotech). Cells were lysed in RLT buffer and stored at -80 oC until RNA extraction.

2.4.5 Sputum sample collection and processing

Spontaneous or induced sputum samples were collected from fifteen healthy subjects and twenty eight patients diagnosed with moderate-to-severe asthma. The sputum samples were treated with dithiothreitol (DTT) (Sigma-Aldrich, Dorset, UK) diluted in PBS in a volume of 4 times the sample weight, vortexed for 15 seconds and pipetted up and down gently to mix thoroughly. Samples were placed on a rocker for 15 minutes and a further four times the volume PBS was added to the sample and placed on a rocker for 5 minutes. The samples were filtered through a 48 μm cell strainer (BD labware, New Jersey, USA) and the cell suspension centrifuged at 790 x g for 10 minutes. Supernatants were stored at -80 °C. Samples were thawed in batches and incubated with 50 μg/ml DNase (Roche, Sussex, UK) for 30 minutes at 37 °C. Samples were washed and plated in a 24-well plate in RPMI complete media for 1 hour to allow for macrophage adherence. Cells were washed with PBS to remove non-adherent cells and macrophages lysed in RLT buffer and stored at -80 °C until RNA extraction.

2.5 Cell line culture

2.5.1 Beas-2b cells

Beas-2b cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM) (Sigma- Aldrich) containing 10 % FCS (Gibco), 100 U/ml of penicillin, 100 µg/ml streptomycin and 20 mM Hepes (all from Sigma-Aldrich). Beas-2b cells were plated at 2.5 x 105 cells/ml in 24-well tissue culture plates and stimulated with IL-4 (20 ng/ml), IL-10 (20 ng/ml), Nrtn (100 ng/ml), IFNα (20 ng/ml), IFNβ (20 ng/ml) IFNγ (20 ng/ml), IFNλ (20 ng/ml) (all from Peprotech), camptothecin (3 μM, 10 μM or 30 μM, Sigma-Aldrich), lipoteichoic acid (LTA) (100 ng/ml), LPS (20 ng/ml or 100 ng/ml), PolyI:C (1 μg/ml) or R848 (1 μg/ml) (all from Invivogen) and incubated for 4, 24 or 48 hours at 37 oC . Cell supernatants were collected and stored at -80oC until ELISA analysis. Cells were stained for immunofluorescence or lysed in RLT buffer (Qiagen) or RIPA buffer with protease inhibitors (Protease Inhibitor Cocktail, Sigma-Aldrich) and phosphatase inhibitors (Phosphatase Inhibitor Cocktail 3, Sigma-Aldrich) and stored at -80 oC until RNA extraction or -20 oC until western blot analysis, respectively.

2.5.2 A549 cells

A549 cells were cultured in DMEM (Sigma-Aldrich) containing 10 % FCS (Gibco), 100 U/ml of penicillin, 100 µg/ml streptomycin and 20 mM Hepes (all from Sigma-Aldrich). A549 cells were plated at 2.5 x 105 cells/ml in 24-well tissue culture plates and stimulated with IL-4 (20 ng/ml), IL-10 (20 ng/ml), Nrtn (100 ng/ml) (all from Peprotech) or LPS (20 ng/ml) (Invivogen) and incubated for 4 or 24 hours at 37 oC. Cell supernatants were collected and stored at -80 oC until ELISA analysis. Cells were lysed in RLT buffer (Qiagen) and stored at -80 oC until RNA extraction.

2.5.3 THP-1 cells

THP-1 cells were cultured in complete RPMI media and plated at 5 x 105 cells/ml in 12- well tissue culture plates. THP-1 cells were treated with 0.5 μM phorbol 12-myristate 13-acetate (PMA) (Sigma-Aldrich) to induce differentiation into macrophages. After 3 hours, fresh complete RPMI media was added to the cells and the plate incubated at 37 oC overnight prior to stimulation. THP-1 cells were stimulated with the human TLR agonist kit according to the manufacturer’s instructions (Invivogen) or IFNα (20 ng/ml), IFNβ (20 ng/ml), IFNγ (20 ng/ml) or IFNλ (20 ng/ml) (all from Peprotech) and incubated for 4 or 24 hours at 37 oC. Cells were stained for flow cytometry or lysed in RLT buffer (Qiagen) or RIPA buffer with protease inhibitors (Protease Inhibitor Cocktail, Sigma- Aldrich) and phosphatase inhibitors (Phosphatase Inhibitor Cocktail 3, Sigma-Aldrich) and stored at -80 oC until RNA extraction or -20 oC until western blot analysis, respectively.

2.6 mRNA detection assays

2.6.1 RT-qPCR

RNA was isolated using the RNeasy micro kit according to the manufacturer’s instructions (Qiagen) and total RNA was quantified using a Nanodrop spectrophotometer (ThermoFisher Scientific, Waltham, MA, USA). Reverse transcription of equivalent amounts of RNA was carried out using the High-Capacity RNA-to-cDNA kit according to the manufacturer’s instructions (Applied Biosystems, California, USA). Briefly, samples were incubated at 37 oC for 1 hour and heat 61 inactivated at 95 oC for 5 minutes. qPCR reactions were performed using TaqMan Fast Universal PCR master mix and pre-designed Taqman expression assays (both from Life Technologies, Paisley, UK) or Sybr Green master mix (Applied Biosystems) on a Quantstudio 12k flex PCR system (Life Technologies). Relative mRNA expression was calculated based on the ΔΔCT method (Livak & Schmittgen 2001) using QuantStudio 12K Flex Software v1.1.1 (Life Technologies).

The average mRNA expressions of the house keeping genes RN18s (Mm03928990_g1) and Hprt (Mm01545399_m1) were used to calculate relative mRNA levels of GFRα2 (Mm00433584_m1), Nrtn (Mm03024002_m1), Ret (Mm00436304_m1), IL-6 (Mm00446190_m1), TNFα (Mm00443258_m1), IL-1β (Mm00434228_m1) in mouse bone marrow-derived macrophages (BMDMs) and mouse alveolar macrophages. The mRNA expression of RPLP0 (Hs00420895_gH) was used to calculate relative mRNA levels of GFRα1 (Hs00237133_m1), GFRα2 (Hs00176393_m1), GFRα3 (Hs00181751_m1), GFRα4 (Hs00942561_g1), RET (Hs01120030_m1), GDNF (Hs01931883_s1), NRTN (Hs00177922_m1), ARTN (Hs00754699_s1), PSPN (Hs03986122_s1), NCAM (Hs00941830_m1), GAS1 (Hs00266715_s1), SYNDECAN3 (Hs01568665_m1), CD80 (Hs01045161_m1), CD86 (Hs01567026_m1), SOCS3 (Hs02330328_s1), CD206 (Hs00267207_m1), TNFα (Hs00174128_m1), IL-6 (Hs00174131_m1), and IL-1β (Hs01555410_m1) in Human MDMs, Beas-2b cells, A549 cells, THP-1 cells and human airway macrophages. RET9 was detected using the following primer pair: Forward primer – 5’TCCCTTCCACATGGATTG-3’; Reverse primer – 5’-ATCACAGAGAGGAAGGATAGT-3’ and RET 51 was detected using the following primer pair: Forward primer – 5’-CTCCCTTCCACATGGATTG-3’; Reverse primer – 5’- TCAGCTCTCGTGAGTGGT-3’. Primer sequences were sequenced in Myers et al., 1995 and provided by Dr Lois Mulligan (Myers et al. 1995). Gene expression was normalised to the housekeeping gene GAPDH using the following primer pair: Forward Primer, 5’-GAAGGTGAAGGTCGGAGT-3’, Reverse Primer, 5’- CATGGGTGGAATCATATTGGAA-3’.

2.6.2 RT2 Profiler PCR array for mouse neurotrophins and receptors

RNA was isolated using the RNeasy micro kit according to the manufacturer’s instructions (Qiagen) and total RNA was quantified with a Nanodrop

62 spectrophotometer (ThermoFisher Scientific) and 1 μg of RNA from each sample was reverse transcribed using the RT2 First Strand Kit (Qiagen). Briefly, the genomic DNA elimination mixture was added to each sample and incubated for 5 minutes at 37 oC. Immediately after, samples were chilled on ice for 1 minute. The RT master mix was added to each sample and incubated at 42 oC for 15 minutes and heat inactivated at 95 oC for 5 minutes. qPCR reactions were performed using RT2 SybrGreen Rox qPCR Master Mix and the PCR array plate on a Quantstudio 12k flex PCR system (Life Technologies). Relative mRNA expression was calculated based on the ΔΔCT method using QuantStudio 12K Flex Software v1.1.1 (Life Technologies). Data was analysed using the SABiosciences RT2 Profiler PCR Array Data Analysis version 3.5.

2.7 Protein detection assays

2.7.1 Concentrating protein in supernatants

For some experiments, supernatants were concentrated using Amicon® Ultra-0.5 Centrifugal Filter Devices (Merck, Watford, UK). Briefly, 500 μl of supernatant was added to the filter device and centrifuged at 14 000 x g for 30 minutes. The concentrated solute was recovered by placing the filter device upside down in a microcentrifuge tube and centrifuged at 1000 x g for 2 minutes.

2.7.2 Cytokine Bead Array

Cell supernatants from M-CSF- and GM-CSF-differentiated BMDMs were collected and a cytometric bead array (BD biosciences, Oxford, UK) was used to measure the protein concentration of cytokines according to the manufacturer’s instructions. The array contained IL-6, IL-1β, TNFα, IL-10, IL-4, IL-13, IL-5 and IFNγ. Briefly, the lyophilised recombinant protein for each cytokine listed was combined, reconstituted and diluted to generate a standard curve. The capture bead master mix and PE detection reagent master mix were combined and added to each standard and sample in a 96-well plate. The plate was incubated for 2 hours at room temperature protected from light. At the end of the incubation, the plate was placed on a digital shaker for 5 minutes at 500 rpm. The plate was centrifuged at 500 x g for 5 minutes and washed twice with CBA wash buffer. Samples were resuspended in wash buffer and run through the BD

FACSVerse flow cytometer (BD biosciences) and data analysed using FCAP array software (BD biosciences).

2.7.3 Human TNFα and IL-6 ELISAs

Human TNFα and IL-6 cytokine levels in cell supernatants from LPS-stimulated GM-CSF- and M-CSF- differentiated MDMs and human alveolar macrophages, in the presence or absence of Nrtn, were analysed by ELISA according to the manufacturer’s instructions (ebioscience, Waltham, MA, USA). Briefly, a 96-well flat bottom plate was coated with capture antibodies for TNFα or IL-6 and incubated at 4 oC overnight. The plate was washed 3 times with PBS containing 0.05 % tween and blocked with ELISA buffer for 1 hour at room temperature. The TNFα or IL-6 standards, alongside the samples, were added to pre-designated wells and incubated for 2 hours at room temperature. The plate was washed 3 times and TNFα or IL-6 detection antibodies added to each well and incubated for 1 hour at room temperature. After washing the plate 3 times, avidin-HRP was added to each well and incubated for 30 minutes at room temperature. The plate was washed 5 times and TMB solution added to each well and incubated for 5 to 15 minutes at room temperature, protected from light. Stop solution was added to each well and absorbance read at 450nm using a spectrophotometer (ThermoFisher Scientific).

2.7.4 Human and mouse Neurturin ELISAs

Human Nrtn protein levels were measured in cell lysates and supernatants from Beas- 2b cells. For some experiments, supernatants were concentrated to detect low levels of protein. Mouse Nrtn protein levels were measured in mouse BAL fluid, serum and lung tissue homogenates. Both ELISAs were performed according to the manufacturer’s instructions (Cusabio, Maryland, USA). Briefly, standards and samples were added to the wells of a pre-coated plate and incubated for 2 hours at 37 oC. The liquid was removed and the detection biotin-antibody added to each well. The plate was incubated for 1 hour at 37 oC and wells washed 3 times with wash buffer and HRP- avidin was added to each well. The plate was incubated for 1 hour at 37 oC and washed 5 times with wash buffer. TMB substate was added to each well and incubated for 15 to 30 minutes at 37 oC, protected from light. Stop solution was added

64 to each well and and absorbance read at 450nm using a spectrophotometer (ThermoFisher Scientific).

2.7.5 Western Blotting

Protein concentrations from cell lysates of THP-1-differentiated macrophages and human M-CSF-differentiated MDMs were determined using a BCA Protein Assay Kit (ThermoFisher Scientific). Equivalent amounts of protein were loaded into the gel and resolved by electrophoresis on 4-15 % mini-Protean TGX precast gels (Biorad, Watford, UK) for 50 minutes at 120 volts. Proteins were transferred to nitrocellulose membranes (Biorad) using a semi-dry Trans-Blot turbo transfer system (Biorad). The transfer was run for 25 minutes at 15 volts. The membrane was blocked with 5 % milk in 0.1 % tris-buffered saline (TBS)-tween, to prevent non-specific binding, and incubated for 1 hour on an orbital shaker. The membrane was washed 3 times with 0.1% TBS-Tween. Human anti-GFRα2 (1:500, rabbit, R&D systems, Abingdon, UK), human anti-RET (1:200, rabbit, Cell Signalling Technology, The Netherlands) and anti-β- actin-Peroxidase (1:10000, horseradish peroxidase (HRP)-conjugated, Sigma-Aldrich) were diluted in 5 % milk in 0.1% TBS-Tween and added to the membrane. The membranes were incubated overnight at 4 oC and washed in 0.1 % TBS-Tween. Anti- rabbit HRP-conjugated secondary antibody (1:3000, Dako, Stockport, UK) diluted in 5 % milk in 0.1 % TBS-Tween was added to the membrane and incubated for 1 hour at room temperature on an orbital shaker. The membranes were developed using a Clarity Western ECL Substrate (Biorad) and visualised with a ChemiDoc MP Imaging System (Biorad).

2.7.6 Immunocytochemistry and immunofluorescence

Beas-2b cells were plated at 5 x 104 cells/well in Nunc Lab-Tek II Chamber slides (Sigma-Aldrich) and washed in PBS. Cell were fixed in 4 % paraformaldehyde and incubated for 20 minutes at room temperature. Cells were washed and blocked in 1 % BSA in TBS for 1 hour at room temperature. Cells were washed in PBS and neurturin antibody (1:400, rabbit, R&D systems) diluted in 1 % BSA in TBS added and incubated overnight at 4 oC. Cells were washed with PBS and incubated with Alexa Fluor 594 Anti-rabbit IgG (1:1000, Thermofisher Scientific) in 1 % BSA in TBS for 1 hour at room

65 temperature protected from light. Cells were washed with PBS, chamber removed and cover slip mounted onto the slide with ProLong Diamond antifade mountant with DAPI (Thermofisher Scientific). Cells were imaged on a Zeiss Axioimager.D2 upright microscope using a 20x objective and captured using a coolsnap HQ2 camera (photometrics) through Micromanager software v1.4.23. Specific band pass filter sets for DAPI and Texas red were used to prevent bleed through from one channel to the next. Images were then processed and analysed using ImageJ.

2.7.7 PathScan Antibody Array Kits (Fluorescent Readout)

Human M-CSF-differentiated MDMs were lysed in cell lysis buffer (Cell Signalling Technology) and protein concentrations from cell lysates were determined using a BCA Protein Assay Kit (ThermoFisher Scientific). The PathScan Intracellular Signalling Array kit and the PathScan RTK Signalling Antibody array kit were carried out according to the manufacturer’s instructions (Cell Signalling Technology). Briefly, blocking buffer was added to the array wells and incubated for 15 minutes at room temperature. Equivalent amounts of protein from each sample were added to the wells and incubated overnight at 4 oC. The wells were washed with PBS and the detection antibody cocktail was added to each well and incubated for 1 hour at room temperature on an orbital shaker. The wells were washed with PBS and the DyLightTM 680-linked Streptavidin was added to each well and incubated for 30 minutes at room temperataure on an orbital shaker, protected from light. Wells were washed with PBS and imaged using a ChemiDoc MP Imaging System (Biorad).

2.7.8 Flow cytometry

2.7.8.1 Extracellular surface staining of M-CSF and GM-CSF- differentiated BMDMs

Cells were stained with live/dead stain (Zombie UVTM Fixable Viability Kit (Biolegend, London, UK) and incubated for 20 minutes at 4 oC, protected from light. Cells were centrifuged at 500 x g for 5 minutes and resuspended in anti-CD16/32 antibody (eBioscience) for 20 minutes at 4 oC. Cells were centrifuged at 500 x g for 5 minutes and resuspended in the primary antibody cocktails listed in Table 2.1. Cells were incubated for 20 minutes at room temperature and centrifuged at 500 x g for 5 minutes. Cells were resuspended in 4 % paraformaldehyde (PFA) and incubated for 20 66 minutes at room temperature. Cells were centrifuged at 500 x g for 5 minutes before being resuspended in PBS and run through a BD LSRFortessaTM flow cytometer (BD biosciences) and data analysed using FlowJo software. Fluorescence minus one (FMO) staining was used as a negative control.

Name Conjugation Clone Isotype Concentration Company F4/80 BV605 BM8 Rat IgG2a 1:100 Biolegend CD11c BV785 N418 Hamster IgG 1:200 Biolegend CD11b APC-Cy7 M1/70 Rat IgG2b 1:200 Biolegend

Table 2.1: Flow Cytometry primary antibody cocktail for M-CSF and GM-CSF-differentiated BMDMs

2.7.7.2 Extracellular surface staining of digested mouse lung and skin cells

Cells were stained with live/dead stain (Zombie UVTM Fixable Viability Kit (Biolegend) or Live/DeadTM Fixable Near-IR Dead Cell Stain Kit (Invitrogen)) and incubated for 20 minutes at 4 oC, protected from light. Cells were centrifuged at 500 x g for 5 minutes and resuspended in anti-CD16/32 antibody (eBioscience) for 20 minutes at 4 oC. Cells were centrifuged at 500 x g for 5 minutes and resuspended in the primary antibody cocktails listed in Table 2.2 and Table 2.3, mouse GFRα2 antibody (1:200, polyclonal goat, R&D Systems) and mouse Mertk antibody (1:100, polyclonal goat, R&D Systems). Cells were incubated for 20 minutes at room temperature and centrifuged at 500 x g for 5 minutes. Cells were resuspended in Alexa Fluor 488 Anti-goat IgG (1:1000, Thermofisher Scientific) or Alexa Fluor 647 Anti-goat IgG (1:1000, Thermofisher Scientific) and incubated for 20 minutes at room temperature. Cells were centrifuged at 500 x g for 5 minutes and resuspended in 4 % PFA and incubated for 20 minutes at room temperature. Cells were centrifuged at 500 x g for 5 minutes and resuspended in PBS. Cells were run through a BD LSRFortessaTM flow cytometer (BD biosciences) and data analysed using FlowJo software. Fluorescence minus one (FMO) staining was used as a negative control.

Name Conjugation Clone Isotype Concentration Company CD45 BV510 30-F11 Rat IgG2b 1:200 Biolegend SiglecF FITC REA798 Human IgG1 1:200 Miltenyi CD3 APC-Cy7 17A2 Rat IgG2b 1:200 Biolegend CD19 APC-Cy7 6D5 Rat IgG2a 1:200 Biolegend CD11b BV711 M1/70 Rat IgG2b 1:200 Biolegend CD11c BV650 N418 Hamster IgG 1:200 Biolegend CD64 PE X54-5/7.1 Mouse IgG1 1:200 Biolegend Ly6G PerCP-efl710 1A8-Ly6G Rat IgG2a 1:200 eBioscience MHCII Alexa 700 M5/114.15.2 Rat IgG2b 1:200 eBioscience Ly6C PE-Cy7 HK1.4 Rat IgG2c 1:200 Biolegend

Table 2.2: Flow Cytometry primary antibody cocktail for mouse lung digest cells

Name Conjugation Clone Isotype Concentration Company CD45 BV510 30-F11 Rat IgG2b 1:200 Biolegend MHCII Alexa 700 M5/114.15.2 Rat IgG2b 1:200 eBioscience CD64 PE-Cy7 X54-5/7.1 Mouse IgG1 1:200 Biolegend CD11b Pacific Blue M1/70 Rat IgG2b 1:200 Biolegend CX3CR1 PerCP-efl710 2A9-1 Rat IgG2b 1:200 eBioscience

Table 2.3: Flow Cytometry primary antibody cocktail for mouse skin digest cells

2.7.8.3 Extracellular surface staining human GM-CSF- and M-CSF- differentiated MDMs

Human GM-CSF- and M-CSF-differentiated MDMs were removed from tissue culture wells using trypsin (Sigma-Aldrich) and a cell scraper. Cells were stained with live/dead stain (Zombie UVTM Fixable Viability Kit (Biolegend)) and incubated for 20 minutes at 4 oC, protected from light. Cells were centrifuged at 500 x g for 5 minutes and resuspended in Human TruStain FcXTM block (Biolegend) for 10 minutes at room temperature, respectively. Cells were centrifuged at 500 x g for 5 minutes and resuspended in the primary antibody cocktails listed in Table 2.4. Cells were incubated for 20 minutes at room temperature, centrifuged at 500 x g for 5 minutes and resuspended in PBS. Cells were run through a BD LSRFortessaTM flow cytometer (BD biosciences) and data analysed using FlowJo software. Fluorescence minus one (FMO) staining was used as a negative control.

Name Conjugation Clone Isotype Concentration Company CD80 APC 2D10 Mouse IgG1 1:200 Biolegend CD86 PE-Texas Red 2331 Mouse IgG1 1:200 BD CD206 APC-Cy7 15-2 Mouse IgG1 1:200 Biolegend

Table 2.4: Flow Cytometry primary antibody cocktail for GM-CSF- and M-CSF-differentiated MDMs

2.7.8.4 Antibody Conjugation kits

Human GFRα2 (R&D systems) and human RET (Cell Signalling Technologies) antibodies were conjugated using the Abcam APC or PE-Cy7 conjugation kits, respectively (Abcam). Briefly, the APC or PE-Cy7 modifier reagents were added to 10μg of antibody. The antibody sample was added to lyophilised material in the APC or PE-Cy7 Conjugation mix and incubated for 3 hours at room temperature, protected from light. The APC or PE-Cy7 Quencher reagent was added and incubated for 30 minutes at room temperature. The antibody was then ready for use.

2.7.8.5 Extracellular surface, cytoplasmic and nuclear staining of THP-1-differentiated macrophages and M-CSF-differentiated MDMs

THP-1-differentiated macrophages and M-CSF-differentiated MDMs were removed from tissue culture plates using cell dissociation buffer (Sigma-Aldrich). Buffer was pipetted up and down to ensure cell removal. Cells were stained with live/dead stain (Live/DeadTM Fixable Aqua Dead Cell Stain Kit (Invitrogen)) and incubated for 20 minutes at 4 oC, protected from light. Cells were centrifuged at 500 x g for 5 minutes and resuspended in Human TruStain FcXTM block (Biolegend) for 10 minutes at room temperature. Cells were centrifuged at 500 x g for 5 minutes and to stain for extracellular surface markers, cells were resuspended in APC-conjugated anti-GFRα2 (1:200, polyclonal goat, R&D systems) and PE-Cy7-conjugated anti-RET (1:400, monoclonal rabbit, Cell Signalling Technology) antibodies. For cytoplasmic staining, cells were fixed in IC fixation buffer (Invitrogen) and incubated for 20 minutes at room temperature. For nuclear staining, cells were fixed in FoxP3 fixation/permeabilisation solution (Invitrogen) and incubated at room temperature for 30 minutes and centrifuged at 500 x g for 5 minutes. Cells were then resuspended in permeabilisation buffer and again centrifuged at 500 x g for 5 minutes. Cells were resuspended in APC- 69 conjugated anti-GFRα2 (1:200, polyclonal goat, R&D systems) and PE-Cy7-conjugated anti-RET (1:400, monoclonal rabbit, Cell Signalling Technology) antibodies and centrifuged at 500 x g for 5 minutes. Cells were resuspended in PBS before being run through a BD Canto II flow cytometer (BD biosciences) and data analysed using FlowJo software. Fluorescence minus one (FMO) staining was used as a negative control.

2.8 Phagocytosis assay

Human GM-CSF and M-CSF-differentiated MDMs were removed from tissue culture wells using trypsin (Sigma-Aldrich) and a cell scraper. Cells were counted and plated at 1 x 105 cells/well in a 96-well tissue culture plate. pHrodoTM conjugated E.coli bioparticles (10 μg/ml, ThermoFisher Scientific) were added to the wells and incubated for 2 hours at 37 oC. Cytochalasin D (5 μg/ml Sigma-Aldrich) was added to the negative control wells to prevent phagocytosis of the pHrodoTM conjugated E.coli bioparticles. Cells were centrifuged at 2000 rpm for 2 minutes and resuspended in PBS. Cells were run through a BD Canto II flow cytometer (BD biosciences) and data analysed by FlowJo software.

2.9 Cell death detection assays

2.9.1 Annexin V flow staining

Beas-2b cells were removed from tissue culture wells using trypsin (Sigma-Aldrich) and a cell scraper. Annexin V staining was performed according to manufacturer’s instructions (Biolegend). Briefly, cells were washed with cell staining buffer (Biolegend) and resuspended in Annexin V Binding Buffer (Biolegend) at a concentration of 1 x 106 cells/ml. APC annexin V was added to 100 μl of cell suspension and incubated for 15 minutes at room temperature, protected from light. Annexin V Binding Buffer was added to each sample and cells were run through a BD Canto II flow cytometer (BD biosciences) and analysed by FlowJo software.

2.9.2 LDH assay

LDH release in Beas-2b cell supernatants was measured using CytoTox 96 non- radioactive Cytotoxicity Assay according to the manufacturer’s instructions (Promega, 70

Southampton, UK). Briefly, 50 μl of fresh cell supernatants was added to a 96-well flat- bottom plate and 50 μl of CytoTox 96 reagent added to each sample. The plate was incubated for 30 minutes at room temperature, protected from light. Stop solution was added to each well and absorbance read at 490 nm on a spectrophotometer.

2.10 Statistics

GraphPad Prism version 7 was used for all statistical analysis, unless otherwise previously stated. For multiple dataset analysis ANOVA with Bonferroni correction was applied. To compare two datasets a paired or unpaired t test was applied. Data are presented as the mean ± standard deviation (SD). P values < 0.05 were considered significant (*p<0.05, **p<0.01, ***p<0.001).

Chapter 3 : Characterisation of the GDNF family receptor, GFRα2, on airway macrophages in health and disease

3.1 Introduction

3.1.1 Neuronal factor function outside the nervous system

The study of neuronal factors has mainly focussed on the central and peripheral nervous systems. However, there is evidence that three families of neurotrophic factors; neurotrophins, GDNF family and neuropoietic cytokines, can be produced by immune cells and regulate immune function (Schwartz et al. 1999; Kerschensteiner et al. 2003). For example, the neurotrophin NGF, is important in the differentiation, maintenance and function of lymphocytes, monocytes and mast cells (Ehrhard et al. 1993; Ehrhard et al. 1993). The GDNF family have been investigated on human peripheral blood immune cells, with the GFRα2 receptor most highly expressed on these cells (Vargas-Leal et al. 2005). Moreover, co-receptors that mediate GFRα receptors signalling, for example, RET, are important in driving haematopoietic stem cell survival and function (Fonseca-Pereira et al. 2014). Furthermore, the neuropoietic cytokines, CNTF and LIF, are closely related to the IL-6 family of cytokines and function in a similar manner, as their signalling pathways both involve the IL-6 signal transducing receptor component gp130 (Ip et al. 1992). Overlap between the immune and nervous systems is therefore evident, but under-researched.

3.1.2 Are neuronal factors expressed on airway immune cells?

The neurotrophins are the most widely studied neuronal factors on airway immune cells. Mouse alveolar macrophages constitutively express neurotrophin 3 (NT3) and NT4 and produce nerve growth factor (NGF) and brain derived neurotrophic factor (BDNF) following allergen stimulation (Virchow et al. 1998; Hikawa et al. 2002). However human alveolar macrophages are reported to only express NGF (Ricci et al. 2004). Due to conflicting reports, it is unclear whether alveolar macrophages express neurotrophin receptors. Ricci et al., initially reported that the neurotrophin Trk receptors were expressed on alveolar macrophages (Ricci et al. 2000). However Hikawa et al., could not corroborate these findings, being unable to detect expression of Trk receptors on alveolar macrophages (Hikawa et al. 2002). Therefore, there remains a significant gap in our knowledge of which neuronal factors are expressed by

73 these cells and their likely function. In this chapter, the expression of the GDNF family receptor, GFRα2, is described for the first time on alveolar macrophages.

Macrophage classification has predominantly been based on their derivation in vitro using different cocktails of stimuli. Macrophages treated with IFN-γ (with or without LPS) results in an ‘M1-like’ macrophage, which has a more pro-inflammatory phenotype. Macrophages treated with IL-4, IL-13 or IL-10 yields an ‘M2-like’ macrophage, which displays an anti-inflammatory/repair phenotype. Both types of macrophage have distinct receptors that are important in an inflammatory response or in the resolution of inflammation, respectively (Ji et al. 2014). There is some evidence for further subsets, particularly with the M2 category, which have been further subcategorised into M2b and M2c cells, which are important in driving type 2 immune responses and tissue remodelling, respectively. The expression of the GDNF family of receptor has not previously been characterised on different macrophage subtypes and will be addressed here.

The lung environment is rich in GM-CSF that is absolutely required for determining the unique repertoire of receptors alveolar macrophages express, including CD11c, SiglecF and Axl (Hussell & Bell 2014). Peritoneal macrophages adoptively transferred to the lung upregulate lung-macrophage-specific genes, such as Chi3l3, Sftpc, Car4 and Pparg, while downregulating peritoneal macrophage-specific genes, including Alox15 and Gata6 (Lavin et al. 2014). It is not currently known whether the lung microenvironment shapes the expression of neuronal factors, including GFRα2, on macrophages or whether GFRα2 is expressed on other tissue resident macrophages.

3.1.3 The GDNF family expression and signalling on airway cells

In addition to the paucity of information on GFRα receptors and their respective ligand expression the co-receptor they adopt for signalling is unknown. GFRα receptors interact with the classical co-receptor RET to enable GDNF family signalling. However, there is debate over whether RET is absolutely required. For example, in schwann cells and many areas of the adult brain GFRα receptors are expressed without RET. This suggests that GFRα receptors interact with RET produced from another cellular source and GFRα receptors have been described in soluble form (Naveilhan et al. 1997; Trupp

74 et al. 1997). In addition, some studies suggest that GFRα receptors can co-opt alternative co-receptors such as NCAM (Paratcha et al. 2003), syndecan-3 (Bespalov et al. 2011) and Gas1 (Schueler-Furman et al. 2006). Whether the GDNF receptor family signal in a RET dependent or -independent manner in alveolar macrophages has not been previously addressed.

3.1.4 The role of the GDNF family in disease

The genetic deletion of members of the GDNF family has given insight into their roles in a range of tissues within the body. However, the majority of roles are most apparent in defective areas of the nervous system, as these neurotrophic factors are important in the development of specific subtypes of neurons. The genetic deletion of RET, GDNF or GFRα1 is lethal at birth. These mice have loss of enteric neurons and also display kidney agenesis (Schuchardt et al. 1994; Moore et al. 1996; Pichel et al. 1996; Sánchez et al. 1996; Cacalano et al. 1998; Enomoto et al. 1998). GFRα2 or Nrtn knockout mice are viable, but have deficits in the enteric and parasympathetic nervous systems (Heuckeroth et al. 1999; Rossi et al. 1999) and a similar eye phenotype as a result of defective parasympathetic innervation of the lacrimal glands (Song et al. 2003). Only Nrtn deficient mice have been studied with regards to airway disease. These mice exhibit increased Th2 cytokine secretion, eosinophilic airway inflammation and airway hyperresponsiveness in a mouse model of allergic airway disease (Michel et al. 2011). Though the GDNF family have not been studies in detail in the airways, the neurotrophins have been widely researched in allergic airway diseases. This area of research was propelled following the finding that the serum levels of NGF and BNDF were enhanced in patients with allergic airway diseases (Virchow et al. 1998). In asthma, the neurotrophins enhance airway inflammation, sensitise peripheral nerves and promote neurogenic inflammation (Nassenstein et al. 2006; Rochlitzer et al. 2006). Nevertheless, a more comprehensive approach to the role of the GDNF family in airway diseases is required. In this chapter, we focus on asthma and COPD.

3.1.5 Hypothesis

Neuronal factors are expressed independently of the nervous system on airway macrophages and play a role in the maintenance of airway homeostasis and/or disease.

3.1.6 Aims

1) Characterise the expression of the GDNF family on airway macrophages.

2) Determine if the expression of GFRα2 on airway macrophages is affected by their activation state.

3) Decipher the co-receptor that GFRα2 binds with to allow Nrtn signalling in airway macrophages.

4) Investigate the expression of GFRα2 on tissue resident macrophages in the skin and gut.

5) Compare the expression of GFRα2 and Nrtn in the healthy airways to that of acute and chronic airway diseases.

3.2 Results

3.2.1 Screening mouse macrophages for neurotrophic factors

Since the expression of neurotrophic factors have not been thoroughly investigated on immune cells, we took the unbiased approach of using a RT2 profiler PCR array on mouse bone marrow cells that had been differentiated using M-CSF or GM-CSF. M-CSF drives mouse bone marrow precursors to a ‘M2-like’ macrophage phenotype that is frequently used as a model of resident homeostatic tissue macrophages (Xu et al. 2007). GM-CSF-treated bone marrow cells give rise to a macrophage population that produces higher levels of pro-inflammatory cytokines, but lower levels of anti- inflammatory cytokines compared to M-CSF-treated cells (Verreck et al. 2004). The use of GM-CSF to derive macrophages is somewhat controversial as historically it has been used to derive dendritic cells from monocytes. However, such cells display macrophage markers and possess a basal transcriptome closer to macrophages than dendritic cells (Mabbott et al. 2010). Therefore, GM-CSF-treated bone marrow cells can still be used as a macrophage model as they have functional and phenotypic characteristics of an inflammatory macrophage (Fleetwood et al. 2007).

To determine whether the macrophages derived from the bone marrow were phenotypically like macrophages or dendritic cells, flow cytometry was performed. The expression of F4/80 and CD11b (macrophage markers) and CD11c (dendritic cell and alveolar macrophage marker) were assessed. Doublets were first removed and live cells gated. Two populations of cells could be detected by gating on F4/80 in the M-CSF derived cells; a higher proportion were F4/80+ and a lower proportion were F4/80- (Figure 3.1a). Both populations were CD11b+CD11c- (Figure 3.1b and figure 3.1c), suggesting a predominantly macrophage-like population of cells. Two populations of cells could also be detected by gating on F4/80 in the GM-CSF derived cells, with a similar proportion of F4/80+ and F4/80- cells present (Figure 3.1d). The majority of the F4/80+ population were CD11b+CD11c+ (Figure 3.1e). The F4/80- population were CD11b+CD11c+ and CD11b+ CD11c+ (Figure 3.1f). Therefore, M-CSF and GM-CSF produce different cell populations, with M-CSF producing more macrophage-like cell populations and GM-CSF producing cell populations similar phenotypically to macrophages and dendritic cells. 77

Figure 3.1: The expression of F4/80, CD11c and CD11b on M-CSF- and GM-CSF- bone marrow derived macrophages. The femurs of C57BL/6 female mice were flushed with PBS to derive bone marrow that was then cultured in 20 ng/ml M-CSF or GM-CSF. After 5 days in culture bone marrow derived macrophages were run through a BD fortessa flow cytometer. Doublets were removed and live cells were identified. The M-CSF-derived macrophages were identified as F4/80+ or F4/80- (a). Both populations were CD11b+CD11c-(b,c). The GM-CSF macrophages were distinguished as F4/80+ or F4/80- (d). The F4/80+ cells were CD11b+CD11c+ (e). The F4/80-population was CD11b+Cd11c+ and CD11b+ and CD11c- (f). Data are from one independent experiment with one mouse per group.

The RT2 profiler PCR array allows detection of genes associated with neuronal cell growth, differentiation, regeneration and survival, the transmission of nerve impulses, cytokines and receptors involved in neuronal signalling and genes involved in neuronal apoptosis. Our initial analysis was on the whole population of M-CSF- and GM-CSF- differentiated BMDMs (Figure 3.1a and Figure 3.1d). The relative mRNA expression of each factor was compared between M-CSF- and GM-CSF-differentiated BMDMs (Figure 3.2a and 3.2b). In general, the expression of all the genes tested was low on M-CSF- differentiated murine macrophages (Figure 3.2a), with the axis scale being 10x lower compared to GM-CSF-derived macrophages (Figure 3.2b). When comparing expression to housekeeper genes, those genes in the array not characterised specifically as neuronal receptors or ligands were excluded in order to not mask the expression of our genes of interest (Figure 3.2c and Figure 3.2d). Out of 84 genes in the RT2 profiler PCR array, 38 genes were increased greater than 2 fold on M-CSF-differentiated BMDMs, whereas only 15 genes were increased greater than 2 fold on GM-CSF- differentiated BMDMs (Figure 3.2a and Figure 3.2b). High relative expression of neuregulin 1 (Nrg1), metallothionein-3 (Mt3), interleukin-6 (IL-6), cerebellin 1 (Cbln1) and GFRα2 expression was detected on GM-CSF-differentiated macrophages (>250 fold for GFRα2) (Figure 3.2b). It is interesting to note that these genes highly expressed on GM-CSF-differentiated macrophages were low or absent on M-CSF- derived macrophages. In addition, GFRα2 is found to be highly expressed on GM-CSF- differentiated BMDMs and not on M-CSF-differentiated BMDMs when relative mRNA expression is analysed by comparing to housekeeping genes (Figure 3.2c and Figure 3.2d).

Figure 3.2: Neurotrophic factors and related genes on murine bone marrow-derived macrophages. The femurs of C57BL/6 female mice were flushed with PBS to derive bone marrow that was then cultured in 20 ng/ml M-CSF (a,c) or GM-CSF (b,d). After 5 days in culture macrophages were lysed, RNA extracted and assayed in an RT2 profiler PCR array for neurotrophins and their receptors. The values shown represent fold change of GM- CSF- compared to M-CSF-differentiated cells (a,b) or normalised to the average of the housekeeping genes Actb, B2m, Gapdh, Gusb and Hsp90ab1 and displayed as relative expression (c,d). Data are from one independent experiment with one mouse per group. The genes with >2-fold change are shown on the Y axis. 81

To enable comparison between M-CSF and GM-CSF- differentiated macrophages, the neurotrophins and receptors expressed on each from figures 3.2a and Figure 3.2b are displayed in table 3.1, with those expressed on both subsets in the right-hand column. The genes displayed have a fold change greater than 5. Of particular interest was GFRα2, which was >250 fold higher on GM-CSF-differentiated macrophages. Furthermore, GFRα2 was expressed at a relatively high level on GM-CSF-differentiated BMDMs compared to M-CSF-differentiated BMDMs when normalised to housekeeping genes (Figure 3.2c and 3.2d). This could reflect that GM-CSF directly or indirectly drives GFRα2 or that is it inhibited on M-CSF derived macrophages. The lung is particularly rich in GM-CSF that is critical for airway macrophage development at this site (Guilliams et al. 2013). Therefore, the GFRα2 receptor was studied in greater depth.

Genes exclusive to M-CSF- Genes exclusive to GM- Genes expressed on derived macrophages CSF-derived macrophages both ADCYAP1R1,CNTFR, CRHR2, BCL2, CBLN1, CRHBP, IL1B, LIF, MT3, MYC, CX3CR1, CXCR4, GALR2, FGFR1, GFRA1, GFRA2, NRG1 HCRT, IL10, NPY2R, NR1I2, IL1R1, IL6, NRG4 NTF4, TRO

Table 3.1: The genes expressed on murine bone marrow-derived macrophages differentiated with M-CSF and GM-CSF.

3.2.2 The expression of the GDNF family on mouse bone marrow-derived macrophages

GFRα2 is a member of the GDNF family and has been studied in relation to neurogenesis. Very few studies have examined the expression on immune cells, apart from one showing GFRα2 expression on human peripheral blood mononuclear cells (PBMCs) (Vargas-Leal et al. 2005). The observation of GFRα2 on macrophages was therefore novel. To validate the PCR array, the expression of GFRα2 was assessed by RT-qPCR. In accordance with the PCR array, high expression of GFRα2 was observed on GM-CSF-, but not M-CSF-differentiated BMDMS (Figure 3.3a). We have therefore determined for the first time that GFRα2 is expressed on a subset of murine macrophages in the steady state.

GFRα2 binds to Nrtn but needs a co-receptor to signal, commonly RET (Airaksinen & Saarma 2002). Nrtn was not detected on GM-CSF-differentiated BMDMs and was barely detectable on M-CSF-differentiated BMDMs (Figure 3.3b and 3.3c, respectively). Surprisingly, RET, which mediates Nrtn signalling via GFRα2 in neurons, was undetectable in both GM-CSF- and M-CSF-differentiated macrophages. This does not mean that RET is redundant for GFRα2 signalling in macrophages, but may involve other stimuli to enhance its expression or that macrophages use an alternative co- receptor.

Figure 3.3: GM-CSF-differentiated bone marrow derived macrophages express GFRα2, but not RET or Nrtn. The femurs of C57BL/6 female mice were flushed with PBS to derive bone marrow that was then cultured in 20 ng/ml of M-CSF or GM-CSF. After 5 days in culture macrophages were lysed, RNA extracted and the relative mRNA expression of GFRα2 was measured and compared between GM-CSF- and M-CSF-differentiated BMDMs (a). The relative mRNA expression of Nrtn and RET was measured on GM-CSF- or M-CSF- differentiated BMDMs (b, and c, respectively). RT-qPCR data are normalised to the housekeeping genes RN18s and Hprt and displayed as relative gene expression ± the standard deviation (SD) from the mean. Graphs combine data from six (a), five (b) or three (c) independent experiments. *P < 0.05, ***P < 0.001; unpaired t-test (a), one-way ANOVA (b, c). 83

3.2.3 The cytokine IL-4 enhances the mRNA of the GFRα2 receptor on mouse bone marrow-derived macrophages

The above results were performed at steady state. Next, we wanted to know if other signals affected the expression of GFRα2 or RET in GM-CSF- and M-CSF- differentiated BMDMs. The TLR3 and TLR4 ligands, PolyI:C and LPS, increased GFRα2 on GM-CSF- derived but not M-CSF-derived BMDMs, however this did not reach statistical significance compared to media alone (Figure 3.4a and 3.4b). Interestingly, IL-4 enhanced GFRα2 mRNA expression by approximately 150-fold in GM-CSF- differentiated BMDMs (Figure 3.4c) and 20-fold in M-CSF-differentiated BMDMs (Figure 3.4d). IL-4 was chosen as an additional stimulus as the lung environment is rich in this cytokine and the IL-4 receptor is expressed on airway macrophages (Hong et al. 2014). Though IL-13 had no effect on GM-CSF-differentiated macrophages, a partial upregulation was observed on M-CSF-differentiated macrophages. IFN-γ had no effect on either subset (Figure 3.4c and 3.4d). None of the additional stimuli tested induced the mRNA for RET (Data not shown).

Figure 3.4: GFRα2 expression is enhanced on GM-CSF- and M-CSF- differentiated BMDMs following IL-4 stimulation. The femurs of C57BL/6 female mice were flushed with PBS to derive bone marrow that was then cultured in 20 ng/ml of M-CSF or GM-CSF. After 5 days in culture macrophages were lysed, RNA extracted and the relative mRNA expression of GFRα2 was measured on GM-CSF- and M-CSF- differentiated BMDMs following stimulation with 100 ng/ml of LPS, 10μg/ml of polyI:C (a, b) or the cytokines IFNγ, IL-4 and IL-13 (c, d). RT-qPCR data are normalised to the housekeeping genes RN18s and Hprt and displayed as a fold change over the unstimulated control ± the standard deviation (SD) from the mean. Graphs combine data from three independent experiments. *P < 0.05, **P < 0.01; one-way ANOVA.

3.2.4 GFRα2 is expressed at the mRNA level on mouse alveolar macrophages at steady state and enhanced with the cytokine IL-4

Since the airways are rich in GM-CSF (Dranoff et al. 1994) and the development of alveolar macrophages depends on its expression (Guilliams et al. 2013), we hypothesised that mouse airway macrophages may also express GFRα2. This was confirmed by RT-qPCR and, similarly to bone marrow-derived macrophages, Nrtn and RET were absent (Figure 3.5a). Stimulation of mouse alveolar macrophages with IL-4

85 also significantly enhanced the mRNA for GFRα2 (Figure 3.5b). Therefore, GM-CSF drives the expression of GFRα2 that is further amplified by IL-4. Furthermore, the airspace microenvironment contains the necessary conditions for GFRα2 expression. At this point however, the co-receptor required for signalling and the source of the ligand, Nrtn, are unknown.

Figure 3.5: GFRα2 mRNA expression is enhanced on mouse alveolar macrophages following IL-4 stimulation. Adherent mouse alveolar macrophages, obtained from the bronchoalveolar lavage (BAL) fluid of naive C57BL/6 female mice, were lysed and RNA extracted. The mRNA expression of GFRα2, Nrtn and RET was measured in mouse alveolar macrophages at steady state (a), and for GFRα2 following stimulation with 100 ng/ml of IL-4 for 24 hours (b). RT-qPCR data are normalised to the housekeeping genes RN18s and Hprt and displayed as relative gene expression (a) or as fold change over the unstimulated control (b) ± the standard deviation (SD) from the mean. Graphs combine data from one independent experiment with three mice per group. *P < 0.05, **P < 0.01; one-way ANOVA (a), paired student t-test (b).

3.2.5 GFRα2 is more highly expressed on CD11b+ mouse airway macrophages compared to CD11c+ mouse alveolar macrophages at steady state

Digestion of lung tissue liberates both alveolar macrophages and interstitial macrophages that can be identified based on their expression of CD11c and CD11b (Fujimori et al. 2015). Alveolar macrophages are classed as CD11c+ CD11b- and lung monocyte-macrophages as CD11c intermediate and CD11b+. To determine if GFRα2 expression is restricted to alveolar macrophages or present on other lung resident macrophages, we measured the mRNA expression of GFRα2 on FACS sorted alveolar 86 macrophages and lung monocyte-macrophages. As before, GFRα2 was expressed on alveolar macrophages, classified as CD11chi, but even higher expression was observed on the CD11cint/CD11bhi interstitial macrophages (Figure 3.6). GFRα2 is therefore expressed on both alveolar and interstitial macrophages.

Figure 3.6: GFRα2 is more highly expressed at the mRNA level on CD11c intermediate/CD11b high mouse interstitial macrophages. Mouse airway and interstitial macrophages from the digested lungs of female C57/BL6 female mice were FACS sorted and the mRNA examined for GFRα2. RT-qPCR data are normalised to the housekeeping genes RN18s and Hprt and displayed as relative gene expression ± the standard deviation (SD) from the mean. Graphs combine data from one independent experiment with four mice per group. ***P < 0.001; unpaired student t-test.

3.2.6 GFRα2 protein expression on mouse airway macrophages cannot be detected at steady state

To assess whether the expression of GFRα2 at the mRNA level translated to expression of the protein at the cell surface of lung macrophages, flow cytometry was performed on enzymatically digested mouse lung tissue. Airway macrophages were distinguished based on the gating strategy used by Misharin and colleagues (Misharin et al. 2013). Live CD45+ cells were first gated to identify immune cells, followed by gating on CD3- CD19- to remove T cells and B cells. Doublets were removed and alveolar macrophages characterised by siglecF+CD11b-CD11c+CD64+ cells (Figure 3.7). Neurtrophils and eosinophils were gated out of the siglecFint/- fraction of cells using Ly6G and siglecF, respectively. The CD11b+MHCII- cells were classified as lung monocyte-macrophages (Figure 3.7). 87

Figure 3.7: Gating strategy used to identify macrophage subsets in naïve mouse lung. Cells were isolated from digested lungs of female C57BL/6 mice and run through a BD fortessa flow cytometer (a) and live CD45+ cells were identified (b). CD3+ and CD19+ cells were gated out to remove T cells and B cells (c). Doublets were excluded (d) and SiglecF+CD11b- cells gated on (e), followed by CD11c+ and CD64+ cells to identify alveolar macrophages (f). SiglecFint/- cells were gated on (g) and neutrophils excluded by gating out Ly6G+CD11b+ cells (h). Eosinophils were removed by excluding the siglecFint population of cells (i) and the remaining cells used to gate CD11b+ cells (j). The CD64+ cells were gated on (k) and MHCII+ cells were classified as interstitial macrophages (l). Data are representative of one independent experiment with three mice.

The gating strategy shown in figure 3.7 was used to assess the protein expression of GFRα2 on different mouse airway macrophage subsets. The surface expression of GFRα2 could not be detected at the protein level on alveolar macrophages (Figure 3.8a) or interstitial macrophages (Figure 3.8b) from the airways of naïve C57/Bl6 mice. Given that stimulation of alveolar and bone marrow-derived macrophages with IL-4 was required for optimal expression of GFRα2 at the mRNA level, it is possible the same could be required for surface expression of the GFRα2 protein.

Figure 3.8: GFRα2 is not detected on naive mouse alveolar macrophages or interstitial macrophages at the protein level. The surface protein expression of GFRα2 was assessed on cells digested from the lungs of female C57BL/6 mice by flow cytometry. Mouse alveolar macrophages were characterised as siglecF+CD11b-CD11c+CD64+ cells (a) and interstitial macrophages as CD11b+CD64+MHCII+ cells (b). Data are representative of one independent experiment with three mice. Specific GFRα2 staining (blue), FMO (red).

3.2.7 GFRα2 is expressed on human monocyte-derived macrophages

To translate our findings of GFRα2 mRNA expression in mouse macrophages to human macrophages, we differentiated healthy blood derived monocytes with GM-CSF or M- CSF. GFRα2 was expressed on both human GM-CSF- and M-CSF- differentiated monocyte-derived macrophages (MDMs) at the mRNA level (Figure 3.9a). Similarly to the mouse BMDMs, the expression of Nrtn was not detectable on either the GM-CSF- or M-CSF- differentiated MDMs (Figure 3.9b and 3.9c). RET was detected at the mRNA level on GM-CSF-differentiated MDMs (Figure 3.9b), however it was barely detectable on M-CSF-differentiated MDMs (Figure 3.9c). These data confirm that similar to mice, GFRα2 is expressed in human macrophages, but not the ligand. Whereas the signalling co-receptor RET is expressed at low levels on a subset of macrophages.

Figure 3.9: The mRNA expression of GFRα2, Nrtn and RET on GM-CSF- and M-CSF- differentiated MDMs. CD14+ monocytes were isolated from human peripheral blood of healthy donors and cultured in 20ng/ml of GM-CSF or M-CSF. After 6 days of culture, cells were lysed and RNA extracted. The relative mRNA expression of GFRα2 was compared between GM-CSF-and M-CSF- differentiated MDMs (a). The relative mRNA expressions of GFRα2, Nrtn and RET was measured in GM-CSF- and M-CSF-differentiated MDMs (b and c, respectively). RT-qPCR data are normalised to the housekeeping gene RPLP0 and displayed as relative gene expression ± the standard deviation (SD) from the mean. Graphs combine data from nine (a) or six (b and c) healthy donors. *P < 0.05, ***P < 0.001; unpaired t-test (a), one- way ANOVA (b, c).

3.2.8 GFRα2 expression on human monocyte-derived macrophages is not affected by TLR3/TLR4 agonist or cytokine stimulation

To determine whether the expression of GFRα2 is altered on human macrophages to additional stimuli in the same way as mouse macrophages, we stimulated GM-CSF- and M-CSF- differentiated MDMs with TLR ligands or cytokines (Figure 3.10). As with mouse BMDMs, TLR ligands did not induce expression of GFRα2 (Figure 3.10a and 92

3.10b). However, in contrast to mouse BMDMs and alveolar macrophages, IL-4 also did not increase the expression of GFRα2 on GM-CSF- or M-CSF-differentiated MDMs (Figure 3.10c and 3.10d). In addition, IFN-y, IL-13 and IL-10 had no effect on the expression of GFRα2 (Figure 3.10c and 3.10d). Human and mouse monocyte-derived macrophages therefore appear to differ slightly in their expression of GFRα2.

Figure 3.10: The mRNA expression of GFRα2 is not altered on GM-CSF- or M-CSF- differentiated MDMs following TLR agonist or cytokine stimulations. CD14+ monocytes were isolated from human peripheral blood of healthy donors and cultured in 20 ng/ml of GM-CSF or M-CSF. After 6 days of culture, cells were lysed and RNA extracted. The relative mRNA expression of GFRα2 was measured on GM-CSF- and M-CSF- differentiated MDMs following stimulation with 20 ng/ml of LPS and 10 μg/ml of polyI:C (a, b) and 20 ng/ml of the cytokines IFNγ, IL-4 and IL-13 (c, d) for 24 hours. RT-qPCR data are normalised to the housekeeping gene RPLP0 and displayed as a fold change over the unstimulated control ± the standard deviation (SD) from the mean. Graphs combine data from six healthy donors.

3.2.9 GFRα2 is highly expressed on healthy human airway macrophages

Monocyte-derived macrophages are a poor representation of tissue macrophages. Therefore, we next assessed whether GFRα2, or any of the GDNF family receptors or ligands, were expressed on human airway macrophages. These macrophages were derived from the healthy margin perfusate of human lungs resected for the presence of cancer. GFRα2 mRNA was highly expressed on these human airway macrophages (Figure 3.11a) and is therefore conserved between humans and mice. Like in the mouse, the other GDNF family receptors nor the co-receptor RET were detected (Figure 3.11a). Human airway macrophages were observed to express low levels of the GDNF receptor ligands (Figure 3.11b). Similarly to mouse BMDMs and airway macrophages, IL-4 stimulation increased GFRα2 mRNA, though the fold change was not as pronounced when compared to mouse BMDMs and mouse alveolar macrophages (Figure 3.11c). This less dramatic increase may reflect the high levels of GFRα2 already present on human airway macrophages. Like mouse macrophages, RET mRNA expression was not induced by IL-4 stimulation in human airway macrophages (Figure 3.11d). Thus, despite differences between monocyte-derived macrophages in mouse and humans, both species expressed GFRα2 on airway macrophages, but not Nrtn or RET.

Figure 3.11: GFRα2 is highly expressed on human airway macrophages at the mRNA level. Adherent human airway macrophages were perfused from the healthy margins of lung resection samples, cells lysed and RNA extracted. The relative mRNA expression of GDNF family receptors (GFRα1, GFRα2, GFRα3, GFRα4 and RET) (a) and ligands (GDNF, Nrtn, Artn and Pspn) (b) were measured on human airway macrophages. The mRNA expression of GFRα2 (c) and RET (d) were measured following stimulation with 20 ng/ml of IL-4 for 24 hours. RT-qPCR data are normalised to the housekeeping gene RPLP0 and displayed as relative gene expression (a,b) or as fold change over the unstimulated control (c,d) ± the standard deviation (SD) from the mean. Graphs combine data from three (a and b), seven (c) and five (d) donors. **P < 0.01, ***P < 0.001; one-way ANOVA of means of all groups (a), paired t-test (c).

3.2.10 GFRα2 is expressed on healthy peripheral blood monocytes at the mRNA level

Recent studies suggest that macrophages adapt to specific microenvironments. For example, peritoneal macrophages that have been adoptively transferred into the lung down-regulate the peritoneal macrophage specific gene, GATA6, and up-regulate the lung macrophage specific gene, PPARγ (Lavin et al. 2014). High expression of GFRα2

95 may be as a result of the human airspace environment. We therefore next assessed the expression of the GDNF family on healthy monocytes isolated from human peripheral blood before their terminal differentiation in tissues. One previous study shows that GFRα2, but not GFRα1 or GFRα3, is expressed on human CD14+ monocytes from peripheral blood (Vargas-Leal et al. 2005). We also observed GFRα2 but not GFRα1 expression at the mRNA level on human CD14+ monocytes isolated from peripheral blood (Figure 3.12a). Therefore, acquisition of GFRα2 is not dependent on a tissue specific microenvironment. Though RET and Nrtn are reportedly expressed on human monocytes at the mRNA and protein level (Vargas-Leal et al. 2005); we were unable to confirm this at the mRNA level in our experiments. (Figure 3.12a).

Figure 3.12: GFRα2 is highly expressed on human peripheral blood monocytes. CD14+ monocytes were isolated from human peripheral blood of healthy donors, cells lysed and RNA extracted. The relative mRNA expressions of GFRα1, GFRα2, RET, GDNF and Nrtn was measured. RT-qPCR data are normalised to the housekeeping gene RPLP0 and displayed as relative gene expression ± the standard deviation (SD) from the mean. Graphs combine data from three healthy donors. ***P < 0.001; one-way ANOVA of means from all groups.

3.2.11 Does GFRα2 bind to an alternative co-receptor to RET in healthy human airway macrophages?

Since GFRα2 cannot signal alone, it was surprising that airway macrophages in mice and humans did not express RET. We therefore investigated whether other potential co-receptors for the GDNF family were expressed on human airway macrophages. NCAM (Paratcha et al. 2003), syndecan-3 (Bespalov et al. 2011) and GAS1 (Cabrera et al. 2006) have all been implicated as alternative co-receptors for the GDNF family receptors. NCAM, syndecan-3 and GAS1 were all expressed in human airway 96 macrophages at the mRNA level (Figure 3.13a, 3.13b and 3.13c), with syndecan-3 having the highest expression (Figure 3.13b). Thus, human alveolar macrophages may use syndecan 3 as a co-receptor for GFRα2.

Figure 3.13: The alternative co-receptors to GFRα2; NCAM, syndecan 3 and Gas1 are expressed on human airway macrophages. Adherent human airway macrophages were perfused from the healthy margins of lung resection samples, cells lysed and RNA extracted. The relative mRNA expressions of NCAM (a), Syndecan 3 (b), Gas1 (c) and RET (a-c) were measured on human airway macrophages. RT-qPCR data are normalised to the housekeeping gene RPLP0 and displayed as relative gene expression ± the standard deviation (SD) from the mean. Graphs combine data from six healthy donors. **P < 0.01; unpaired t-test (b).

We showed previously that IL-4 enhanced the expression of GFRα2, but not the co- receptor RET. Similarly, IL-4 had no effect on mRNA levels of NCAM (Figure 3.14a), syndecan-3 (Figure 3.14b) or GAS1 (Figure 3.14c).

Figure 3.14: The expressions of the alternative co-receptors for GFRα2 signalling are not altered by IL-4 stimulation of human airway macrophages. Adherent human airway macrophages were perfused from the healthy tissue of lung resection samples, cells lysed and RNA extracted. The relative mRNA expressions of NCAM (a), Syndecan 3 (b), and Gas1 (c) were measured on human airway macrophages following stimulation with 20 ng/ml of IL-4 for 24 hours. RT-qPCR data are normalised to the housekeeping gene RPLP0 and displayed as a fold change over the unstimulated control ± the standard deviation (SD) from the mean. Graphs combine data from six healthy donors.

3.2.12 Is GFRα2 expressed on macrophages from other tissue sites?

This is the first time that GFRα2 has been characterised on airway macrophages and therefore it is unknown whether this expression is specific to airway macrophages or if GFRα2 is expressed on macrophages from other tissue sites. Mouse small intestine macrophages were FACs sorted and the mRNA expression of GFRα2 analysed on three subsets of resident macrophages characterised as CD4-Tim4+, CD4+Tim4- and CD4+Tim4+. At the mRNA level, GFRα2 was expressed on all three subsets of small intestine naïve macrophages (Figure 3.15).

Figure 3.15: GFRα2 is expressed on mouse small intestine macrophages at the mRNA level. Cells were isolated from digested small intestine from female C57BL/6 mice and macrophages sorted on a BD FACS Aria Fusion flow cytometer based on their expression of CD4 and Tim4 (CD4-Tim4+, CD4+Tim4-, CD4+Tim4+). The relative mRNA expression of GFRα2 was measured on small intestine macrophages (Mφ). RT-qPCR data are normalised to the housekeeping gene RPLP0 and displayed as relative gene expression. Data are from one independent experiment with one mouse.

Due to the high proportion of CD45- cells in mouse ear and back skin, sorting resident macrophages from these tissue sites was difficult. For that reason, the expression of GFRα2 was analysed on the surface of dermal macrophages and Langerhans cells. Skin resident macrophages and dendritic cells were distinguished based on their specific cell surface markers (Malissen et al. 2014). In both ear and back skin, live CD45+ cells were first gated to identify immune cells (Figure 3.16a and Figure 3.16b), followed by doublet removal (Figure 3.16c) and gating on MHCII+ (Figure 3.16d). In ear skin, dermal macrophages were identified by their expression of CD64 and Mertk (Figure 3.16e) and Langerhans cells were classified as CD64-Mertk-CX3CR1-CD11b+ (Figure 3.16f). Dermal macrophages in the back skin were also identified as CD64+Mertk+, however this was a smaller population than those present in the ear skin (Figure 3.16g). Langerhans cells were identified in the back skin also as CD64-Mertk-CX3CR1-CD11b+ (Figure3.16h).

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Figure 3.16: Gating strategy to identify dermal macrophages and Langerhan cells in mouse ear and back skin. Cells were isolated from digested ear and back skin from female C57BL/6 mice and run through a BD fortessa flow cytometer (a) and live CD45+ cells were identified (b). Doublets were removed (c) and MHCII+ cells gated on (d). In the ear skin, dermal macrophages were identified by their expression of CD64 and Mertk (e) and langerhan cells were classified as CD64-Mertk-CX3CR1-CD11b+ (f). Langerhan cells in the back skin were also identified as CD64-Mertk-CX3CR1-CD11b+ (g). Data are representative of one independent experiment with three mice.

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The gating strategy shown in figure 3.16 was used to assess the protein expression of GFRα2 on dermal macrophages and Langerhans cells in mouse ear and back skin. The surface expression of GFRα2 could not be detected at the protein level on dermal macrophages or Langerhans cells from ear skin (Figure 3.17a) or on dermal macrophages or Langerhans cells from back skin (Figure 3.17b) of naïve C57Bl/6 mice. Similarly to naïve mouse airway macrophages, which also do not express GFRα2 on their surface, skin resident cells may need to be stimulated in order to express GFRα2 at the protein level.

Figure 3.17: GFRα2 is not detected on naïve dermal macrophages or Langerhans cells at the protein level. The surface protein expression of GFRα2 was assessed on cells digested from the ear (a) and back (b) skin of female C57BL/6 mice by flow cytometry. Dermal macrophages were characterised as CD64+Mertk+ (a) and Langerhans cells were characterised as CD64-Mertk- CX3CR1-CD11b+ (b,c). Data are representative of one independent experiment with three mice. FMO (blue), GFRa2 staining on dermal macrophages (red), GFRα2 staining on Langerhans cells (orange).

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3.2.13 Is the expression of GFRα2 altered on airway macrophages from patients with chronic inflammatory airway diseases?

3.2.13.1 The expression of GFRα2 on airway macrophages from patients with asthma

As we have characterised the expression of the GFRα2 receptor on airway macrophages, we next wanted to investigate whether this receptor is altered on airway macrophages from patients with chronic airway disease. As we had found an increase in the expression of GFRα2 on mouse airway macrophages stimulated with IL- 4, we were interested to know whether this receptor has a role in a Th2-driven disease. GFRα2 expression was assessed on sputum human airway macrophages from patients with asthma compared to healthy donors. GFRα2 is already expressed on human airway macrophages and we found no increase in mRNA levels between healthy donors and asthmatic patients (Figure 3.18). In addition, the expression of the signalling partner for GFRα2, RET, could not be detected on healthy or asthmatic sputum human macrophages (Data not shown). This corroborates our finding that in humans the expression of GFRα2 is not altered following stimulation with IL-4. Unfortunately, we did not have a soluble sample within which to test for the presence of Nrtn and it has not been reported previously.

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Figure 3.18: GFRα2 expression is not altered on sputum macrophages from asthmatic patients compared to healthy donors. Adherent sputum macrophages were obtained from healthy donors and asthmatic patients, cells lysed and RNA extracted. The relative mRNA expression of GFRα2 was measured on human sputum macrophages. RT-qPCR data are normalised to the housekeeping gene RPLP0 and displayed as a fold change over the healthy donor controls ± the standard deviation (SD) from the mean. Graph combines data from twelve healthy donors and twenty eight asthmatic patients.

3.2.13.2 The expression of GFRα2 on airway macrophages in COPD

The role of the GDNF family in chronic airway disease has not been extensively studied. COPD is known to be associated with aberrant alveolar macrophage activity and we were interested to determine whether GFRα2 is altered in this disease. Macrophages in BAL fluid obtained from bronchoscopys showed an increase in GFRα2 mRNA expression in airway macrophages from COPD patients compared to healthy non-smokers and healthy smokers (Figure 3.19a). Stimulation of the same airway macrophages with the TLR agonists LPS and Poly:IC decreased GFRα2 mRNA levels in the macrophages from COPD patients (Figure 3.19b).

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Figure 3.19: GFRα2 expression increases in human macrophages from COPD patients compared to healthy non-smokers and healthy smokers. Adherent human airway macrophages were collected from BAL fluid following bronchoscopy of the upper lung lobes, cells lysed and RNA extracted. The relative mRNA expression of GFRα2 was measured on human airway macrophages unstimulated for 4 or 24 hours (a) or following stimulation with 20 ng/ml of LPS and PolyI:C for 24 hours. RT-qPCR data are normalised to the housekeeping gene RPLP0 and displayed as a fold change over the healthy non-smoker controls ± the standard deviation (SD) from the mean. Graphs combine data from three donors per group.

The laboratory also receives the healthy margins of human lung tissue resected for cancer. These patients display prior co-morbidities, the most prominent one being COPD. We therefore assessed GFRα2 mRNA on macrophages perfused from this tissue and found it elevated in those with a history of COPD compared to patients with no known co-morbidities (Figure 3.20).

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Figure 3.20: GFRα2 is slightly increased on human airway macrophages from COPD patients compared to healthy non-smokers. Adherent human airway macrophages were perfused from the healthy tissue of lung resection samples, cells lysed and RNA extracted. The relative mRNA expression of GFRα2 was measured on human airway macrophages. RT-qPCR data are normalised to the housekeeping gene RPLP0 and displayed as a fold change over the healthy non-smoker controls ± the standard deviation (SD) from the mean. Graph combines data from six healthy non-smoker donors and ten COPD patient donors. *P < 0.05; unpaired t-test.

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3.3 Discussion

3.3.1 GFRα2 is highly expressed on airway macrophages

The discovery of GFRα2 on macrophages is a novel finding though its role is unclear and will be examined in the next chapter. We report GFRα2 on mouse and human macrophages, but different processes induce its expression between species. In mice, GFRα2 expression on GM-CSF-differentiated BMDMs is significantly higher compared to M-CSF-differentiated BMDMs, whereas no difference was observed between human MDMs differentiated with GM-CSF or M-CSF. In addition, the Th2 cytokine IL-4 significantly enhanced the expression of GFRα2 on GM-CSF- and M-CSF- differentiated BMDMs and mouse airway macrophages, but had little effect on human MDMs and a substantially lower up-regulation of GFRα2 mRNA was observed in human airway macrophages. Therefore, although GFRα2 is conserved across species, the parameters driving the expression of this receptor may be different.

In many circumstances, the airspace microenvironment drives a very different airway macrophage phenotype. For example, TAM receptor Axl is exclusively expressed on airway macrophages, but not interstitial macrophages at the steady state (Fujimori et al. 2015). Furthermore, airway macrophages express higher levels of CD200R than interstitial counterparts (Snelgrove et al. 2008). In contrast, GFRα2 expression was detected in both mouse alveolar and interstitial macrophages at the mRNA level, but we could not detect their protein expression on the surface of either macrophage population in the steady state. In support of this, GFRα2 was also not detectable on the cell surface of mouse dermal macrophages or Langerhans cells isolated from the ear and back skin of naïve mice. This implies that macrophages need to be stimulated in order to induce GFRα2 protein expression or receptor translocation to the cell surface.

3.3.2 GFRα2 expression is not restricted to airway macrophages

We originally thought that GFRα2 expression would be restricted to macrophages in sites rich in GM-CSF as bone marrow-derived macrophages differentiated in GM-CSF conditions expressed significantly higher levels of GFRα2 than those derived in M-CSF.

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Airway macrophages did indeed express GFRα2 in mice and humans. However, we also observed high mRNA expression in monocytes isolated from human peripheral blood and macrophages from the mouse small intestine. The data suggests that macrophage GFRα2 expression is not shaped by the airway microenvironment nor is it a specific marker for airway macrophages. GFRα2 is therefore likely to play a more fundamental role in macrophage biology. It would be interesting to know whether GFRα2 is expressed on resident macrophages from other tissue sites or whether its expression is altered once monocytes differentiate to dendritic cells or macrophages in inflamed tissue.

3.3.3 GFRα2 expression is enhanced on airway macrophages following IL- 4 stimulation

A significant increase in the mRNA levels of GFRα2 were detected in mouse airway macrophages treated with IL-4 and to some extent in human airway macrophages. We were surprised to find that the TLR3 and TLR4 agonists, PolyI:C and LPS, as well as the cytokine IFN-γ had no effect on GFRα2 expression. Therefore, only selective stimuli up-regulate GFRα2. IL-4 is associated with both the resolution phase of inflammation and Th2-driven diseases. Interestingly, Michel et al., found that Nrtn-deficient mice exhibit enhanced Th2 cytokine levels, eosinophil recruitment and heightened sensitivity in a murine model of allergic airway inflammation (Michel et al. 2011), suggesting that GFRα2 may limit inflammation. Though the mRNA level of GFRα2 in sputum macrophages was comparable between asthmatic patients and healthy donors we cannot rule out heightened activity due to enhanced Nrtn or GFRα2 post- translational modifications. We did define that airway macrophages obtained from the BAL fluid, or from the healthy margins of lung resection samples of COPD patients displayed a trend towards higher mRNA expression of GFRα2 compared to healthy non-smokers and healthy smokers. At present, this data is pointing towards a role in repair. It remains to be investigated whether Nrtn levels are also increased in chronic respiratory disease and the impact of altered neurotrophic factor expression on disease severity.

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3.3.4 Does GFRα2 and Nrtn signal independently of RET in human airway macrophages?

The canonical GDNF family receptor, RET, is undetectable on mouse and human airway macrophages at steady state. In addition, the expression of this co-receptor was not induced by any of the stimuli tested. GFRα2 may signal independently of RET in airway macrophages similar to that described in schwann cells (Paratcha et al. 2003). However, there are conflicting reports as to whether this is possible (Pezeshki et al. 2001; Ishida et al. 2016). Nevertheless, alternative co-receptors for the GFRα receptors have been reported. GDNF is known to interact with NCAM and activate the fyn and FAK family of kinases. This promotes schwann cell migration and axonal growth in hippocampal and cortical neurons in a RET-independent manner (Paratcha et al. 2003). Extracellular matrix proteins, for example, heparan sulfate proteoglycans, have profound effects on growth factor signalling (Bernfield et al. 1999; Bishop et al. 2007). Syndecan-3 is a member of this family and is capable of binding to immobilised GDNF, Nrtn and artemin. The binding of GDNF to syndecan-3 leads to the phosphorylation of Src family kinases and functionally results in hippocampal neurite outgrowth and neuronal migration (Bespalov et al. 2011). Gas 1 is a known mediator of cell death and unlike the above receptors interferes with RET-dependent signalling. Gas1 recruits RET to lipid rafts and mediates its signalling by blocking Akt phosphorylation and inhibiting the survival effects of GDNF on neurons (Cabrera et al. 2006). We did observe the expression of the potential signalling partners for GFRα2; syndecan-3, and to a lesser extent NCAM and Gas1, in human airway macrophages. Whether all or one of these is the dominant co-receptor for airway macrophages is currently unclear. However, this could possibly be elucidated by the different downstream signalling pathways each receptor activates following binding to the GFLs. The GFRα receptors are also produced from cells in a soluble form (Naveilhan et al. 1997; Trupp et al. 1997). Therefore, GFRα2 could be cleaved from airway macrophages and interact with RET on other cell types. This is something we have not studied in detail.

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3.3.5 The possible roles of other neuronal factors expressed on GM-CSF- and M-CSF- derived BMDMs

Though this thesis focuses on GFRα2, a number of other interesting neuronal associated proteins were also detected on GM-CSF-differentiated macrophages including neuregulin 1 (Nrg1), metallothionein-3 (Mt-3) and cerebellin 1 (Cbln1). Our research tends to focus on GM-CSF differentiated macrophages since these resemble airway macrophages better than other subsets. However, Neuropeptide Y receptor Y2 (NPY2R), Ciliary neurotrophic Factor receptor (CNTFR) and Leukemia Inhibitory Factor (LIF) are expressed at significant levels on M-CSF derived macrophages.

3.3.5.1 Neuregulin-1

Nrg1 is a member of the epidermal growth factor family and is an important factor in neutrophil adhesion to endothelial cells (Wu et al. 2015). Nrg1 is implicated in several disorders including breast cancer, multiple sclerosis, schizophrenia and atherosclerosis (Marballi et al. 2010). Interestingly, the receptors for Nrg1 are expressed on human monocytes and are believed to perform an anti-inflammatory function. Nrg1 inhibits LPS-induced TNF-α production from non-classical human monocytes (CD14low/CD16+) (Ryzhov et al. 2017). Nrg1 expression is also observed on human monocyte-derived dendritic cells differentiated using GM-CSF and IL-4 (Lapteva et al. 2001). Furthermore, studies allude to a function of Nrg1 in chronic respiratory diseases. The bronchoalveolar lavage fluid of patients with sarcoidosis, a granulomatous disease primarily affecting the lungs, shows significantly higher levels of Nrg1 compared to healthy controls (Qazi et al. 2010). In addition, neuregulin-1 has been identified as a novel regulator of goblet cell formation in primary cultures of human bronchial epithelial cells (HBECs) and increases the expression of the mucins, MUC5A and MUC5B, known to be elevated in chronic airway diseases (Kettle et al. 2010). Therefore, nrg1 has a plethora of functions outside the nervous system.

3.3.5.2 Metallothionein-3

Metallothionein-3 (Mt-3) is a copper and zinc metal chelator originally believed to be exclusively expressed in the central nervous system (Masters et al. 1994). However, more recent studies describe expression of Mt-3 in the pancreas (Clifford & 110

MacDonald 2000), prostate, testis and tongue (Hozumi et al. 2008). The role of Mt-3 has been extensively researched in neurodegenerative disorders with dysregulated metal metabolism, such as Alzheimer’s disease (Vašák & Meloni 2017). Zinc represents an environmental oxidative challenge to the human lung (Wu et al. 2013). At high levels, zinc can lead to cellular apoptosis (Bozym et al. 2010) and increased expression of pro-inflammatory genes including IL-8 (Kim et al. 2006) and cyclooxygenase-2 (COX- 2) (Wu et al. 2005) in human airway epithelial cells. Metallothioneins may be essential in removing excess zinc from the airways in order to prevent an inflammatory response. Mt-3 is hypoxia-inducible in cultured human astrocytes (Tanji et al. 2003) and adipocytes (Wang et al. 2008), and therefore potentially protects these cells from hypoxic damage. Within the healthy airways, hypoxia is a normal occurrence and induces the stimulation of breathing (König & Seller 1991). On the other hand, hypoxia also plays a role in the pathophysiology of lung diseases (Kumar & Choi 2015). Whether Mt-3 is involved in protecting macrophages from a hypoxic environment within the airways still remains to be defined.

3.3.5.3 Cerebellin-1

Cbln1 is highly expressed in the cerebellum and is best characterised in this region, however it is known to be expressed throughout the brain (Wei et al. 2012). The major role of Cbln1 is in synapse formation between pre-synaptic neurexin-expressing neurons and post-synaptic GluRδ2-expressing neurons (Ito-Ishida et al. 2012). Of note, Cbln1 contains a C1q domain characteristic of the C1q family of target recognition proteins of the classical complement pathway (Yuzaki 2008). Although research into the role of cbln1 in the immune system has not yet been conducted, it could be assumed that cbln1 plays a wider role in immunity to infection.

3.3.5.4 Neuropeptide Y

NPY2R is one of five G-protein-coupled receptors that bind to neuropeptide Y. Neuropeptide Y is well defined in the modulation of immune cell function. For example, NPY regulates immune cell recruitment (Woods et al. 2015), oxygen radical formation (De la Fuente et al. 1993), macrophage phagocytosis of pathogens (Phan & Taylor 2013) and the release of cytokines from macrophages (Bedoui et al. 2004; Ferreira et al. 2010; Wheway et al. 2007). Administration of exogenous NPY inhibits IL- 111

6 release from splenic macrophages via the Y1 receptor (Straub et al. 2000). Intraperitoneal NPY treatment suppresses the production of antibodies in rats (Friedman et al. 1995) and intravenous NPY treatment affects blood leukocyte populations (Bedoui et al. 2001). Therefore, NPY is a good example of how neuronal factors can have a range of important functions within the immune system.

3.3.5.5 CNTF and LIF

CNTF and LIF are part of the IL-6 family of cytokines, which also includes IL-11, IL-27, Oncostatin M (OSM), Cardiotrophin-1 (CT-1) and Cardiotrophin-like Cytokine (CLC). They share the same receptor; gp130, and are important factors in the inflammatory response (Silver & Hunter 2010). LIF has a variety of roles within the immune system. Not only does LIF promote the survival of haematopoietic stem cells (Escary et al. 1993), it also has a protective role in a mouse model of endotoxin shock. LIF enhances the expression of acute phase proteins and IL-10, which downregulates the release of the pro-inflammatory cytokine TNFα (Weber et al. 2005). The role of LIF in T cell regulation has also been well defined. LIF promotes the expression of the Treg transcription factor FOXP3, yet reduces the Th17 transcription factor RORγt (Gao et al. 2009). Conversely, IL-6 promotes expression of Th17 transcription factors and represses the expression of Treg transcription factors. Therefore, not only is this family important in immune cell regulation, but also can have opposing effects.

3.3.6 Conclusion

In conclusion, we have described for the first time the expression of the GDNF family receptor, GFRα2, on airway macrophages. However, we do not know which airway cells express the ligand, neurturin. In addition, whether GFRα2 and Nrtn signal through the co-receptor RET or another signalling receptor still needs to be confirmed. In the next chapter, we will characterise the expression of Nrtn in the airways in the steady state and airway disease. In addition, we will investigate the effect of Nrtn on airway macrophage function.

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Chapter 4 : What is the effect of neurturin on macrophages?

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4.1 Introduction

The previous chapter details, for the first time, the expression of GFRα2 on human and mouse macrophages under different physiological conditions. In this chapter, we examine the source of the ligand Nrtn and some of the potential pathways that the interaction of neurturin with its receptor may affect.

4.1.1 Do alveolar macrophages and airway epithelial cells communicate via neuronal factors?

When examining airway macrophage biology, the interaction with airway epithelial cells must be considered. In health, alveolar macrophages are negatively regulated through their interaction with airway epithelial cells in the form of soluble mediators or direct cell-cell contact. CD200, surfactant proteins and TGF-β expressed by the epithelium all restrict alveolar macrophage activation, to prevent continuous inflammatory responses (Hussell & Bell 2014). In airway disease, damage to the airway epithelium leads to a loss of this negative regulation, leading to a lower threshold of macrophage activation. It is possible therefore that epithelial cells are also the source of Nrtn. Members of the neurotrophin family and the GDNF family have been shown to be expressed constitutively by airway epithelial cells. For example, the neurotrophin, NGF, is produced by human airway epithelial cells (Fox et al. 2001; Ricci et al. 2004) and Nrtn is expressed at the mRNA level in adult mouse airway epithelium (Golden et al. 1999) and in human small airway epithelium (Hackett et al. 2012). However, it remains to be defined whether alveolar macrophages and epithelial cells can communicate via GFRα2 and Nrtn at steady state or in airway disease.

4.1.2 The roles of the GDNF family outside the nervous system

The GDNF family of neurotrophic factors are well characterised as important regulators of neuronal survival and growth both in development and adulthood. However, this family also has key roles outside of the nervous system. The function of GDNF is the most well studied and studies show it acts as a morphogen in kidney development (Vega et al. 1996) and regulates the differentiation of spermatogonia (Meng et al. 2000). The GFRα2 receptor has recently been described as a marker for

114 cardiomyocyte progenitors and is important for their differentiation (Ishida et al. 2016). Furthermore, the GFRα3 receptor, its signalling partner RET, and its ligand artemin, are crucial for lymphoid organ (Peyer’s patch) formation in the gut (Veiga- Fernandes et al. 2007). In addition, the GDNF family and RET play important roles in the immune system. RET signalling regulates haematopoiesis (Fonseca-Pereira et al. 2014), thymocyte survival and maturation (Kondo et al. 2003), Th2 cell production of IL-10 (Almeida et al. 2014), and ILC3 production of IL-22; a critical pathway in controlling gut homeostasis and defence (Ibiza et al. 2016). Nrtn also inhibits the secretion of the pro-inflammatory cytokines, IL-6 and TNFα , from stimulated human PBMCs and airway epithelial cells (Vargas-Leal et al. 2005) and mouse splenic T cells and BMDCs cocultured and stimulated with ovalbumin (Mauffray et al. 2015). In accordance with being members of the TGF-β superfamily, these data would suggest the GDNF family has an anti-inflammatory role in an immune response. In this chapter, we aim to determine whether Nrtn has an anti-inflammatory role on airway macrophages.

4.1.3 The pleiotropic functions of airway macrophages

When investigating airway macrophages, it is important to remember that their function likely changes in health and disease. All macrophages display plasticity that is driven by different environmental stimuli and depends on the need of the tissue at that time. Macrophage polarisation is often studied by differentiating them in alternate cytokine environments. Classically activated macrophages (M1 macrophages) protect against invading pathogens and induce inflammation through the production of the pro-inflammatory cytokines IL-6 and TNFα. Alternatively activated macrophages (M2 macrophages) produce allergic or anti-inflammatory cytokines, including IL-4 and IL-10, that are important in the allergic response, resolution of inflammation and tissue remodelling (Ginhoux & Guilliams 2016). It is unknown whether neurotrophic factors are important in the function of alveolar macrophages in an M1- or M2- inflammatory setting.

However, M1/M2 polarisation does not accommodate all macrophage varieties or functions. In the case of airway macrophages, they are required in health to clear cellular and matrix turnover products. The same macrophages though, in the presence 115 of damage, are required to initiate an inflammatory event. Equally in resolution of inflammation airway macrophages must repair the lung and clear apoptotic cells by a process known as efferocytosis. This process is vital in order to prevent an inflammatory response caused by the release of danger-associated molecular patterns (DAMPs) from the apoptotic cells (Arandjelovic & Ravichandran 2015). All of these processes require an airway macrophage with a very different attitude and one role may inhibit participation in another. The role of neurotrophic factors in macrophage activity has not been previously studied and may produce different effects depending on the stage of inflammation and the function assessed.

4.1.4 The downstream intracellular signalling pathways activated by the GDNF family

In addition to macrophage function, one way to determine the influence of Nrtn on macrophages is to examine common signalling pathways. The GDNF family are reported to induce the activation of a range of intracellular signalling molecules, with alternative GFL-GFRα pairings activating differential signalling pathways. RET interacts with the Src family kinases in membrane microdomains known as lipid rafts (Tansey et al. 2000). In neurons, this leads to the activation of phosphatidylinositol-3 kinase (PI- 3K) followed by Akt activation and consequently the promotion of cell survival (Encinas et al. 2001). The regulation of IL-22 production by ILC3s via RET is downstream of the p38 MAPK/ERK-Akt pathway and STAT3 activation (Ibiza et al. 2016). A signalling pathway divergent from ERK activation is described in NIH3T3 cells transfected with RET. RET activates JNKs via a signalling pathway requiring Rho/Rac-like small GTPases (Chiariello et al. 1998). The GFL-GFRα complex also signals independently of RET. The binding of GDNF to GFRα1, for example, initiates the activation of phospholipase Cγ (PLCγ), ERK1/2 and cAMP response element binding protein (CREB) in RET-deficient dorsal root ganglion neurons (Poteryaev et al. 1999). Nrtn regulation of pro- inflammatory cytokine production in microglia is also suggested to be downstream of the p38-MAPK pathway (Rickert et al. 2014). The intracellular signalling molecules activated or inhibited by Nrtn, in the presence or absence of RET, in airway macrophages is not currently known.

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4.1.5 Hypothesis

Airway macrophage function is altered following binding of Nrtn to GFRα2.

4.1.6 Aims

1) Characterise the expression of the GDNF family on human airway epithelial cells. 2) Determine if Nrtn affects macrophage function, including the release of pro- inflammatory cytokines, activation state and phagocytic activity. 3) Investigate the intracellular signalling pathways Nrtn activates in airway macrophages.

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4.2 Results

4.2.1 The expression of the GDNF family on human bronchial and alveolar epithelial cell lines at the mRNA level

In chapter 3 we found the expression of the GFRα2 receptor on airway macrophages. However, we do not yet know the cellular source of neurturin, except that it is not from macrophages. The source of Nrtn could be from peripheral nerves that innervate the airways. However, it has previously been reported that in the bone marrow and thymus stromal cells produce GDNF family ligands (Nakayama et al. 1999; Kondo et al. 2003). In addition, Nrtn mRNA has been described previously in mouse airway epithelial cells (Golden et al. 1999). We therefore examined non-immune cells for the presence of the GDNF family and their ligands.

Initial investigations revealed that the human bronchial epithelial cell line (Beas-2b) and the alveolar type II epithelial cell line (A549) both expressed GFRα1 but not GFRα2, 3 or 4 at steady state (Figure 4.1a and 4.1b). These epithelial cells lines also expressed the ligands GDNF, Nrtn, artemin and persephin (Figure 4.1c and 4.1d) with higher expression observed on Beas-2b cells at steady state. Therefore, human airway epithelial cells express specific neurotrophic factor receptors and their ligands, with bronchial epithelial cells expressing more than alveolar epithelial cells.

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Figure 4.1: GFRα1, Nrtn and Artn are expressed on human bronchial and alveolar epithelial cell lines. The relative mRNA expressions of the GDNF family receptors (GFRα1, GFRα2, GFRα3, GFRα4 and RET) and ligands (GDNF, Nrtn, Artn and Pspn) were measured on a human bronchial epithelial cell line (Beas-2b) (a and c, respectively) and a human alveolar type II like cell line (A549) (b and d, respectively). RT-qPCR data are normalised to the housekeeper gene RPLP0 and expressed as relative gene expression ± the standard deviation (SD) from the mean. Graphs combine data from three independent experiments. *P < 0.05, **P < 0.01; one-way ANOVA.

Nrtn has not previously been investigated at the protein level in airway epithelial cells and there are no suitable antibodies for analysing it by flow cytometry. Immunocytochemical staining of Nrtn in Beas-2b cells showed expression of Nrtn within human bronchial epithelial cells at the protein level (Figure 4.2a). Nrtn staining is localised in one spot within the cell. This may indicate that Nrtn is contained within specific organelles such as endosomes or vesicles in these cells. No staining is shown in the negative control (Figure 4.2b).

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Figure 4.2: Nrtn is expressed at the protein level in Beas-2b cells in the steady state. Beas2bs cells were plated in cell chambers and stained by immunofluorescence for Nrtn (texas red) and cell nuclei (DAPI) (a). The negative control for Nrtn is shown in (b). Scale bars = 50μm. Data are from one independent experiment.

4.2.2 Nrtn expression in human bronchial and alveolar epithelial cells is not altered by TLR4 agonist or cytokine stimulation

There is limited research on what induces the release of GDNF family ligands from cells or the mechanism by which this occurs. To begin to address this in airway epithelial cells, Beas2bs and A549 cells were stimulated with the cytokines IL-4 and IL-10, the TLR4 ligand LPS, and Nrtn itself to assess changes in Nrtn mRNA expression (Figure 4.3). No significant changes in the expression of Nrtn were detected in either Beas2bs or A549 cells following stimulation for 4 hours (Figure 4.3a and 4.3b, respectively) or 24 hours (Figure 4.3c and 4.3d, respectively).

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Figure 4.3: The mRNA level of Nrtn on human bronchial and alveolar epithelial cells is not altered by stimulation with cytokines, TLR ligands or Nrtn itself. The relative mRNA expression of Nrtn was measured at 4 and 24 hours on a human bronchial epithelial cell line (Beas-2b) (a and c, respectively) and a human alveolar type II like cell line (A549) (b and d, respectively) cells after stimulation with 20 ng/ml of IL-4, IL-10, IFNγ, LPS or 100 ng/ml of Nrtn. RT-qPCR data are normalised to the housekeeper gene RPLP0 and expressed as a fold change over the unstimulated control ± the standard deviation (SD) from the mean. Graphs combine data from one (a, b) or three (c, d) independent experiments.

While we were unable to detect changes in Nrtn mRNA expression following stimulation, it is possible these stimuli were having post-transcriptional effects on Nrtn expression. Nrtn was evident in Beas2bs cells at the protein level but was unaffected by additional stimuli as measured in cell lysates at 4 hours (Figure 4.4a) or 24 hours (Figure 4.4b). Supernatants were analysed to assess the release of Nrtn from Beas2bs cells at 4 hours (Figure 4.4c) and 24 hours (Figure 4.4d). However, the protein levels were low and around the detection limit of the ELISA used. Thus, Nrtn can be detected in epithelial cells but it is not released in the stimulation conditions tested so far.

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Figure 4.4: The protein level of Nrtn in human bronchial epithelial cells is not altered by stimulation with cytokines, TLR ligands or Nrtn itself. The protein level of Nrtn was measured by ELISA in human bronchial epithelial cell line (Beas2bs) lysate at 4 hours (a) or 24 hours (b) and in cell supernatants at 4 hours (c) or 24 hours (d) following stimulation with 20 ng/ml of IL- 4 IFNγ, LPS and 100 ng/ml of Nrtn. ELISA data are expressed as protein expression ± the standard deviation (SD) from the mean. Graphs combine data are from three independent experiments.

4.2.3 Nrtn is not released from human bronchial epithelial cells following programmed cell death or necrosis

Nrtn may be released upon cell death. Camptothecin is routinely used to induce apoptosis in Immortalised T cells (Jurkat cells). Therefore, we used this compound to induce apoptosis in our Beas2bs cell line. LDH release measurement acted as a positive control to determine cell death and annexin V staining was used to determine apoptosis. Camptothecin at 10μM concentration induced apoptosis after 4 hours (Figure 4.5a and 4.5b). Camptothecin at 3 μM, 10 μM and 30 μM concentrations also induced apoptosis at 24 hours (Figure 4.5c and 4.5d). By 48 hours camptothecin

122 induced necrosis at all concentrations (Figure 4.5e and 4.5f). In the same conditions no Nrtn release into the supernatant was observed (data not shown).

Figure 4.5: Optimisation of cell death induction in Beas-2b cells by camptothecin. A human bronchial epithelial cell line (Beas-2b) was treated with 3, 10 and 30μM camptothecin. LDH release and annexin V+ staining was measured at 4 hours (a and b, respectively), 24 hours (c and d, respectively) and 48 hours (e and f, respectively). Data are from one independent experiment.

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4.2.4 Nrtn expression in mouse airway disease

4.2.4.1 The expression of Nrtn in the airways of a mouse model of allergic asthma

Nrtn has previously been looked at in the context of airway disease, with its knock- down in mice leading to heightened inflammation and airway hyperresponsiveness in ovalbumin and house dust mite mouse models of allergic asthma (Michel et al. 2011). Although, the global knock-down of Nrtn in these mice worsened the airway inflammatory response to OVA, the expression levels of Nrtn in the lungs were not compared between the OVA sensitised and challenged mice and PBS controls. To determine whether Nrtn levels are altered in mouse models of allergic asthma, we measured the protein levels of Nrtn in the BAL, serum and lung. The house dust mite sensitised and challenged mice had decreased levels of Nrtn in the BAL (Figure 4.6a), comparable levels in the serum (Figure 4.6b) and increased levels in the lung (Figure 4.6c) compared to PBS controls. Nrtn levels are therefore altered in the airways in a mouse model of allergic asthma.

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Figure 4.6: Nrtn is enhanced in the lung in a mouse model of house dust mice. BAL fluid supernatant (a), serum (b) and homogenised lung tissue (c) were obtained from naïve and house dust mite (HDM) sensitised and challenged female C57BL/6 mice at day 24. The protein concentration of Nrtn was measured by ELISA. ELISA data are expressed as protein expression ± the standard deviation (SD) from the mean. Graphs combine data from one independent experiment with four naïve and six house dust mite sensitised and challenged mice. *P < 0.05, **P < 0.01; paired t-test.

4.2.4.2 The expression of Nrtn in the airways during airway viral infection

The GDNF family have previously been shown to play a role in viral infection, with GDNF and Nrtn important in the reactivation and replication of herpes simplex virus in specific populations of sensory neurons (Yanez et al. 2017). The plasma levels of the neurotrophins, NGF and BDNF, are higher in patients with H1N1 Influenza infection compared to controls (Chiaretti et al. 2013). Additionally, influenza virus results in neuroinflammation and a reduction of neurotrophin levels in the brain (Jurgens et al. 2012), overall suggesting neurotrophic factors could be important in this infection. The role of Nrtn in influenza infection is currently unknown, therefore the protein

125 levels of Nrtn were analysed in the BAL fluid of mice intranasally infected with influenza virus. Nrtn levels were significantly increased in the BAL fluid of mice at day 8 post-influenza infection compared to naïve animals (Figure 4.7). This time point represents peak inflammation in this infection model. Interestingly, the levels of Nrtn significantly decreased below naïve levels at day 21, when inflammation from the infection has been resolved (Figure 4.7).

Figure 4.7: Nrtn is enhanced in BAL fluid at peak inflammation in a mouse model of influenza. BAL fluid supernatant was obtained from naïve and influenza infected female C57BL/6 mice at 8, 11, 14, 21 and 42 days post-infection (d.p.i). The protein concentration of Nrtn was measured by ELISA. ELISA data are expressed as protein expression ± the standard deviation (SD) from the mean. Graph combine data from one independent experiment with four mice per group. *P < 0.05, ***P < 0.001; one-way ANOVA.

4.2.5 Do GFRα2 and Nrtn play a role in the inflammatory response?

The role of Nrtn in the nervous system has been well researched, whereas comparatively little is known about its role in the immune system. However, the GDNF family and RET are important in haematopoiesis (Fonseca-Pereira et al. 2014), thymocyte survival and maturation (Kondo et al. 2003), Th2 cell production of IL-10 (Almeida et al. 2014), and ILC3 production of IL-22, which is important in gut homeostasis and defence (Ibiza et al. 2016). In addition, Nrtn can inhibit the secretion of the pro-inflammatory cytokines, IL-6 and TNFα, from stimulated human PBMCs (Vargas-Leal et al. 2005) and mouse splenic T cells and BMDCs cocultured and stimulated with ovalbumin (Mauffray et al. 2015). To test the possible functional outcome of GFR2 activation in macrophages, M-CSF- and GM-CSF-differentiated 126

BMDMs were stimulated with LPS with and without Nrtn. The mRNA for IL-6 (Figure 4.8a), TNFα (Figure 4.8b) and IL-1β (Figure 4.8c) was not altered by the addition of Nrtn to LPS stimulated M-CSF-differentiated BMDMs.

Figure 4.8: Nrtn does not alter the mRNA expression of pro-inflammatory cytokines in M- CSF-differentiated BMDMs following LPS challenge. The femurs of C57BL/6 female mice were flushed with PBS to derive bone marrow that was then cultured in 20 ng/ml of M-CSF. After 5 days in culture macrophages were lysed, RNA extracted and the relative mRNA expressions of IL-6 (a), TNFα (b) and IL-1β (c) were measured in M-CSF-differentiated BMDMs following stimulation with 100 ng/ml of LPS and/or Nrtn. RT-qPCR data are normalised to the housekeeper gene RPLP0 and expressed as fold change over the unstimulated control ± the standard deviation (SD) from the mean. Graphs combine data from three independent experiments.

It has previously been reported that Nrtn does not significantly alter the mRNA expression of the pro-inflammatory cytokines IL-6 and TNFα , however does reduce the amount of these cytokines released from immune cells into the supernatant (Vargas- Leal et al. 2005). At the protein level, the secretion of IL-6 (Figure 4.9a), TNFα (Figure

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4.9b) and IL-1β (Figure 4.9c) was similar in both the LPS alone treated M-CSF- differentiated BMDMs and LPS and neuturin treated cells.

Figure 4.9: Nrtn does not affect the release of pro-inflammatory cytokines from M-CSF- differentiated BMDMs following LPS challenge. The femurs of C57BL/6 female mice were flushed with PBS to derive bone marrow that was then cultured in 20 ng/ml of M-CSF. After 5 days in culture supernatants were collected and protein expression of IL-6 (a), TNFα (b) and IL- 1β (c) were measured by ELISA in supernatants from M-CSF-differentiated BMDMs following stimulation with 100 ng/ml of LPS and/or Nrtn. Data are expressed as protein expression ± the standard deviation (SD) from the mean. Graphs combine data from three independent experiments.

This lack of an effect of neuturin on M-CSF differentiated macrophages was expected as in chapter 3 it was shown that in these conditions, only low levels of GFR2 are expressed. Therefore, we next examined GM-CSF differentiated macrophages. Similar to M-CSF derived macrophages, the transcript levels of IL-6 (Figure 4.10a), TNFα (Figure 4.10b) and IL-1β (Figure 4.10c) in LPS-treated GM-CSF-differentiated BMDMs did not alter in the presence of Nrtn.

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Figure 4.10: Nrtn does not alter the mRNA expression of pro-inflammatory cytokines in GM- CSF-differentiated BMDMs following LPS challenge. The femurs of C57BL/6 female mice were flushed with PBS to derive bone marrow that was then cultured in 20 ng/ml of GM-CSF. After 5 days in culture macrophages were lysed, RNA extracted and the relative mRNA expressions of IL-6 (a), TNFα (b) and IL-1β (c) were measured in GM-CSF-differentiated BMDMs following stimulation with 100 ng/ml of LPS and/or Nrtn. RT-qPCR data are normalised to the housekeeper gene RPLP0 and expressed as fold change over the unstimulated control ± the standard deviation (SD) from the mean. Graphs combine data from three independent experiments.

However, Nrtn significantly reduced the levels of IL-6 (Figure 4.11a) and TNFα (Figure 4.11b), with the same trend of IL-β (Figure 4.11c), released from LPS-stimulated GM- CSF-differentiated BMDMs.

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Figure 4.11: Nrtn inhibits the release of pro-inflammatory cytokines from GM-CSF- differentiated BMDMs following LPS challenge. The femurs of C57BL/6 female mice were flushed with PBS to derive bone marrow that was then cultured in 20 ng/ml of GM-CSF. After 5 days in culture, supernatants were collected and protein expression of IL-6 (a), TNFα (b) and IL-1β (c) were measured by ELISA following stimulation with 100 ng/ml of LPS and/or Nrtn. Data are expressed as protein expression ± the standard deviation (SD) from the mean. Graphs combine data from three independent experiments. *P < 0.05; one-way ANOVA.

Although only an inhibition in pro-inflammatory cytokine release from GM-CSF- differentiated BMDMs was observed (Figure 4.9a-b), we next determined if this inhibitory effect of Nrtn was also evident in human M-CSF- or GM-CSF- differentiated monocyte-derived macrophages. The optimal level of IL-6 and TNFα released from both M-CSF- and GM-CSF- differentiated MDMs was at 4 h, with the levels decreasing by 24 h (data not shown). Surprisingly, the release of IL-6 from M-CSF- (Figure 4.12a) or GM-CSF- (Figure 4.12b) differentiated MDMs stimulated with LPS was not altered in the presence of Nrtn at 2 or 4 hours. Moreover, the release of TNFα was also not inhibited by Nrtn in M-CSF- (Figure 4.12c) or GM-CSF- (Figure 4.12d) differentiated MDMs stimulated with LPS at 2 or 4 hours.

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Figure 4.12: Nrtn does not affect the release of pro-inflammatory cytokines from M-CSF- and GM-CSF- differentiated MDMs following LPS challenge. CD14+ monocytes were isolated from human peripheral blood of healthy donors and cultured in 20 ng/ml of M-CSF or GM-CSF. After 6 days of culture, supernatants were collected from M-CSF- (a,c) and GM-CSF- (b,d) differentiated MDMs and the protein expression of IL-6 (a,b) and TNFα (c,d) were measured by ELISA following stimulation with 20 ng/ml of LPS and/or 100 ng/ml of Nrtn. ELISA data are expressed as protein expression ± the standard deviation (SD) from the mean. Graphs combine data from six healthy donors.

To determine whether Nrtn may affect human airway macrophages differently to monocyte-derived macrophages and inhibit the release of pro-inflammatory cytokines from these cells similarly to the GM-CSF-differentiated mouse BMDMs, human airway macrophages were stimulated with LPS with or without Nrtn (Figure 4.13). The mRNA levels of IL-6 (Figure 4.13a) and TNFα (Figure 4.13b) were not altered in human airway macrophages treated with LPS in the presence of Nrtn. Similarly, the release of IL-6

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(Figure 4.13c) and TNFα (Figure 4.13d) from LPS-stimulated human airway macrophages was not altered with the addition of Nrtn.

Figure 4.13: Nrtn does not affect the release of pro-inflammatory cytokines from human airway macrophages following LPS challenge. Adherent human airway macrophages were perfused from the healthy margins of lung resection samples, cells lysed and RNA extracted. The relative mRNA expression of TNFα (a) and IL-6 (b) were measured and supernatants collected to measure the protein expression of and TNFα (c) and IL-6 (d) by ELISA following stimulation with 20ng/ml of the TLR agonist LPS and 100 ng/ml of Nrtn. RT-qPCR data are normalised to the housekeeper gene RPLP0 and expressed as fold change over the unstimulated control ± the standard deviation (SD) from the mean (a,b). ELISA data are expressed as protein expression ± the standard deviation (SD) from the mean (c,d). Graphs combine data from three healthy donors.

4.2.6 Does Nrtn inhibit the activation of intracellular signalling pathways in LPS-treated human airway macrophages?

Nrtn does not inhibit the release of pro-inflammmatory cytokines from human airway macrophages, although previous reports have shown that Nrtn can inhibit the

132 phosphorylation of several MAP kinases, including ERK and p-38 (Rickert et al. 2014). Therefore, the PathScan® Intracellular Signalling Array Kit was used to determine whether Nrtn inhibits the phosphorylation of molecules present in the signalling pathways activated by LPS stimulation in human airway macrophages (Figure 4.14a). Human airway macrophages were stimulated with LPS in the presence or absence of Nrtn for 5 (Figure 4.14b), 10 (Figure 4.14c), 15 (Figure 4.14d) 30 (Figure 4.14e), 45 (Figure 4.14f) and 60 (Figure 4.14g) minutes. Although differences in the activation of intracellular signalling molecules in LPS stimulated cells compared to baseline could be detected (data not shown), Nrtn did not alter the activation state of any signalling molecules compared to LPS alone (Figure 4.14).

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Figure 4.14: Nrtn does not affect the activation of intracellular signalling molecules in human airway macrophages following LPS challenge. Adherent human airway macrophages were perfused from the healthy margins of lung resection samples and cells lysed for protein extraction. The activation of signalling molecules was measured using the PathScan® Intracellular Signaling Array Kit on human airway macrophages stimulated with 20ng/ml of the TLR agonist LPS and/or 100 ng/ml of Nrtn (a). Fluorescence intensity was quantified using image J at 5 (b), 10 (c), 15 (d), 30 (e), 45 (f) and 60 (g) minutes. Graphs combine data from one independent experiment with one healthy donor in duplicate.

4.2.7 Nrtn induces low level release of TNFα from human monocyte- derived macrophages

Although Nrtn does not alter the release of pro-inflammatory cytokines or activation of intracellular signalling molecules in LPS treated human macrophages, Nrtn alone does influence the release of TNFα from human macrophages (Figure 4.15). The mRNA expression of TNFα was not altered on M-CSF- (Figure 4.15a) or GM-CSF- (Figure 4.15b) differentiated MDMs compared to media alone. However, at the protein level, the release of TNFα from M-CSF- (Figure 4.15c) and GM-CSF- (Figure 4.15d) differentiated MDMs was significantly increased compared to media alone. However, the level of TNFα released from human MDMs triggered by Nrtn are in the picogram range, 10- fold less than that induced by LPS (Figure 4.12) and therefore very low (Figure 4.15c-d).

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Figure 4.15: Nrtn induces low level release of TNFα from M-CSF- and GM-CSF- differentiated MDMs. CD14+ monocytes were isolated from human peripheral blood of healthy donors and cultured in 20 ng/ml of M-CSF (a,c) or GM-CSF (b,d). After 6 days of culture, cells were lysed and RNA extracted. The relative mRNA expression of TNFα (a,b) was measured and supernatants collected to measure the protein expression of TNFα (c,d) by ELISA following stimulation with 100 ng/ml of Nrtn for 24 hours. RT-qPCR data are normalised to the housekeeper gene RPLP0 and expressed as fold change over the unstimulated control ± the standard deviation (SD) from the mean (a,b). ELISA data are expressed as protein expression ± the standard deviation (SD) from the mean (c,d). Graphs combine data from three healthy donors. *P < 0.05, **P < 0.01; paired t-test

4.2.8 Does Nrtn affect the polarisation of macrophages to an M1- or M2- like phenotype?

It has not previously been investigated whether Nrtn has any effect on macrophage function. Stimulation of macrophages with LPS and IFNγ produces an M1-like phenotype, whereas stimulation with IL-4 produces an M2-like phenotype. To determine whether Nrtn has any influence on M1-like macrophage phenotypes, GM- 136

CSF-differentiated MDMs, which produce a more M1-like phenotype compared to M- CSF-differentiated cells, were stimulated with LPS and IFNγ or LPS, IFNγ and Nrtn or Nrtn alone (Figure 4.16). The effect of Nrtn on a range of M1 macrophage markers, CD80, CD86 and SOCS3 were examined at the mRNA and protein level. Nrtn did not change the mRNA expressions of CD80 (Figure 4.16a), CD86 (Figure 4.16b) and Socs3 (Figure 4.16c) on GM-CSF- differentiated MDMs stimulated with LPS and IFNγ.

Figure 4.16: Nrtn does not alter the mRNA expression of M1 ‘like’ macrophage markers. CD14+ monocytes were isolated from human peripheral blood of healthy donors and cultured in 20ng/ml of GM-CSF. After 6 days of culture, cells lysed and RNA extracted. The relative mRNA expressions of CD80 (a), CD86 (b) and Socs3(c) was measured in GM-CSF-differentiated MDMs following stimulation with 20 ng/ml of LPS and IFNγ and/or 100 ng/ml of Nrtn. RT-qPCR data are normalised to the housekeeper gene RPLP0 and expressed as fold change over the unstimulated control ± the standard deviation (SD) from the mean. Graphs combine data from four healthy donors.

To determine whether Nrtn affects the expression of M1 macrophage markers at the protein level, GM-CSF-differentiated MDMs were stimulated with LPS and IFNγ in the 137 presence or absence of Nrtn, and the levels of CD80 and CD86 measured by flow cytometry. Firstly, doublets were removed and live cells gated (Figure 4.17a-c). Neurtuin did not alter the percentage of CD80-expressing (Figure 4.17d) or CD86- expressing (Figure 4.17e) GM-CSF-differentiated MDMs following LPS treatment. Likewise, Nrtn did not affect the mean fluorescent intensity of CD80 (Figure 4.17f) or CD86 (Figure 4.16g) on GM-CSF-differentiated MDMs following LPS treatment.

Figure 4.17: Nrtn does not alter the protein expression of M1 ‘like’ macrophage markers. CD14+ monocytes were isolated from human peripheral blood of healthy donors and cultured in 20 ng/ml of GM-CSF. After 6 days of culture, cells were stimulated with 20 ng/ml of the TLR agonist LPS and the cytokine IFN-γ and/or 100 ng/ml of Nrtn. Cells were trypsinized and run through a BD foretessa flow cytometer (a). Doublets were removed (b) and live cells gated on (c). The percentage of CD80 (d) and CD86 (e) expressing MDMs, and the geometric mean 138 fluorescent intensity (gMFI) normalised to FMO for CD80 (f) and CD86 (g) on MDMs were measured. Graphs combine data from three healthy donors.

In regards to whether Nrtn has an influence on an M2-like macrophage phenotype, M- CSF-differentiated MDMs, which produce a more M2-like phenotype compared to GM- CSF-differentiated cells, were stimulated with either IL-4, Nrtn or a combination of both. Similarly, to the influence of Nrtn on M1 macrophage markers, Nrtn also did not alter the mRNA expression of the M2 macrophage marker CD206 (Figure 4.18).

Figure 4.18: Nrtn does not alter the mRNA expression of M2 ‘like’ macrophage markers. CD14+ monocytes were isolated from human peripheral blood of healthy donors and cultured in 20 ng/ml of M-CSF. After 6 days of culture, cells lysed and RNA extracted. The relative mRNA expression of CD206 was measured on M-CSF-differentiated MDMs following stimulation with 20 ng/ml of IL-4 and/or 100 ng/ml of Nrtn. RT-qPCR data are normalised to the housekeeper gene RPLP0 and expressed as fold change over the unstimulated control ± the standard deviation (SD) from the mean. Graph combines data from five healthy donors.

To determine whether Nrtn affects the expression of M2 macrophage markers at the protein level, M-CSF-differentiated MDMs were stimulated with IL-4 in the presence or absence of Nrtn, and the levels of CD206 measured by flow cytometry. Firstly, doublets were removed and live cells gated on (Figure 4.19a-c). Nrtn did not alter the percentage of CD206-expressing M-CSF-differentiated MDMs following IL-4 treatment (Figure 4.19d). Likewise, Nrtn did not affect the mean fluorescent intensity of CD206 following IL-4 treatment (Figure 4.19e).

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Figure 4.19: Nrtn does not alter the protein expression of M2 ‘like’ macrophage markers. CD14+ monocytes were isolated from human peripheral blood of healthy donors and cultured in 20 ng/ml of M-CSF. After 6 days of culture, cells were stimulated with 20 ng/ml of the cytokine IL-4 and/or 100 ng/ml of Nrtn. Cells were trypsinized and run through a BD foretessa flow cytometer (a). Doublets were removed (b) and live cells gated on (c). The percentage of CD206 expressing MDMs (d) and the geometric mean fluorescent intensity (gMFI) normalised to FMO for CD206 (e) were measured. Graph combines data from three healthy donors.

4.2.9 Does Nrtn affect macrophage phagocytosis of bacteria?

Another important function of macrophages is in the phagocytosis of bacteria, which is known to be impaired in chronic airway diseases such as COPD (Taylor et al. 2010) and asthma (Liang et al. 2014). To determine whether Nrtn affects the phagocytosis of bacteria, the percentage uptake of pHrodoTM conjugated S.aureus bioparticles by human macrophages was measured. Nrtn does not alter the phagocytosis of bacteria from MDMs with an M1-like phenotype (Figure 4.20a), or M2-like phenotype (Figure 4.20b).

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Figure 4.20: Nrtn does not alter the uptake of bacteria by M1 ‘like’ or M2 ‘like’ macrophages. CD14+ monocytes were isolated from human peripheral blood of healthy donors and cultured in 20 ng/ml of GM-CSF or M-CSF. After 6 days of culture, cells were trypsinized and run through a BD FACSCanto-II flow cytometer. The percentage uptake of pHrodoTM conjugated E.coli bioparticles were measured on GM-CSF-differentiated MDMs stimulated with 20 ng/ml of the TLR agonist LPS, the cytokine IFN-γ and/or 100 ng/ml of Nrtn (a) and M-CSF- differentiated MDMs stimulated with 20 ng/ml of IL-4 and/or 100 ng/ml of Nrtn (b). Graphs combine data from three healthy donors.

4.2.10 Is RET phosphorylated in human airway macrophages by Nrtn stimulation alone?

Due to the inability to detect RET at the protein level in human airway macrophages, the phosphorylation of RET could not be thoroughly analysed via western blotting. Therefore, the PathScan® RTK Signaling Array Kit was used to determine whether Nrtn phosphorylates any receptor tyrosine kinases, including RET, in human airway macrophages (Figure 4.21a). Human airway macrophages were stimulated with Nrtn for 5, 10, 15, 30 and 60 minutes. However, at none of the time points tested could RET phosphorylation be detected using this method (Figure 4.21b), nor the phosphorylation of any other tyrosine kinases (data not shown).

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Figure 4.21: Nrtn does not induce RET phosphorylation in human airway macrophages at steady state. Adherent human airway macrophages were perfused from the healthy margins of lung resection samples and cells lysed for protein extraction. The activation of receptor tyrosine kinases was measured using the PathScan® RTK Signaling Array Kit on human airway macrophages stimulated with 100 ng/ml of Nrtn for 5, 10, 15, 30 and 60 minutes (a). Fluorescence intensity was quantified using image J (b). Graph combines data from one independent experiment with one healthy donor in duplicate.

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4.3 Discussion

4.3.1 Nrtn is expressed by airway epithelial cells

We show that airway macrophages do not express Nrtn, which is perhaps not surprising based on previous studies that describe Nrtn production by support cells (Heuckeroth et al. 1999). This ligand-receptor pairing within tissues is evident in the intestine, salivary gland and whisker pad. Nrtn is expressed in the circular muscle layer in the intestine, gland parenchyma in the salivary gland and in and around the vibrissae in the whisker pad. The nerves innervating these tissues are in close proximity to the Nrtn-expressing structural cells and are positive for GFRα2. It is therefore interesting that we find GFRα2 on macrophages and Nrtn in epithelial cells. Studies from our lab and those of others investigating airway macrophage and epithelial cell interactions in the lung, led to the hypothesis that airway macrophages sense epithelial cell health through soluble and contact dependent factors from epithelial cells (Hussell & Bell 2014). It is therefore tempting to speculate that Nrtn also fulfils this role.

While airway macrophages express GFRα2, it was also interesting to note that airway epithelial cells express GFRα1 that preferentially binds to the ligand GDNF. GFRα1/GDNF signalling is evident in epithelial cells from other tissue sites, but we are the first to describe it in the lung. GFRα1 is expressed within the kidney epithelium and conditional deletion of this receptor prior to uteric bud branching leads to renal agenesis (Keefe-Davis et al. 2013). Moreover, GDNF and GFRα1 are expressed in the olfactory epithelium and olfactory bulb and are critical for its development and function (Marks et al. 2012). In addition, GDNF released from enteric glial cells has protective effects on the intestinal epithelium (Xiao et al. 2014). These reports corroborate our finding of GFRα1 expression in the airway epithelium and it would be interesting to determine the role of this neurotrophic factor receptor on these cells.

4.3.2 How is Nrtn released from human airway epithelial cells?

Paracrine regulation of airway macrophages by epithelial cells has been described before. Epithelial expressed CD200 regulates airway macrophages that express high levels of CD200R (Snelgrove et al. 2008) and also secrete IL-10 or activate TGF-β to

143 influence macrophage inflammatory tone (Hussell & Bell 2014). Whether Nrtn is stored within epithelial cells and released upon a specific stimulus is not currently known. It is also unclear whether it interacts with GFRα2 on macrophages as a soluble ligand or in a contact dependent manner. The GFLs are synthesised as preproGFL proteins that are processed to proGFLs in the endoplasmic reticulum and secreted into the extracellular space as mature GFLs or as proGFLs (Airaksinen & Saarma 2002). Quite what causes this cleavage is still debated, but it is likely mediated by proteolytic cleavage. Nrtn may also be cleaved after secretion from the cell and it is suggested that such forms are retained in the local area by binding to Heparan-sulphate side chains of extracellular matrix proteoglygans and may be biologically active (Hamilton et al. 2001). Serine protease plasmin and matrix metalloproteinases also extracellularly cleave proforms of the neurotrophins, NGF and BDNF (Airaksinen & Saarma 2002). It is thus possible that we did not observe Nrtn secretion because it was in its prepro form. In future, the addition of lung relevant metalloproteinases or serine protease plasmin should be included in the epithelial assays.

4.3.2.1 Nrtn is not released from epithelial cells upon cell death

Some proteins are secreted upon cell death or apoptosis and act as alarmins to signify a problem. IL-33 is one such alarmin that is released from epithelial cells during cell necrosis or necroptosis and can have both pro-inflammatory and protective effects on macrophages, depending upon the type of infection or inflammatory setting (Arshad et al. 2016). In a mouse model of allergic airway inflammation and cigarette smoke- induced lung inflammation, antagonising IL-33 deceases Th2 cytokine production (Ramaprakash et al. 2011) and macrophage infiltration (Qiu et al. 2013), respectively, and therefore down-regulates the airway inflammatory response. Other protein components released upon cell death incite inflammation through their recognition by pattern recognition receptors and include heat-shock proteins, HMGB1 and IL-1α (Oppenheim & Yang 2005). We could not detect the release of Nrtn following apoptotic or necrotic cell death from human airway epithelial cells; therefore, we can rule out the role of this neurotrophic factor as a danger signal.

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4.3.3 Nrtn expression is altered in airway disease

Neuronal factors have long been implicated in airway disease. Interest into the impact of neuronal factors in airway disease started after the discovery that neurotrophin NGF and BDNF levels are increased in the serum and BAL fluid of asthmatic patients compared to healthy controls (Bonini et al. 1996; Virchow et al. 1998). The neurotrophins are now known to regulate airway inflammation, hypperresponsiveness and remodelling in response to allergen challenge. The levels of Th2 cytokines in the airways decrease in mice treated with anti-NGF antibodies (Braun et al. 1998; Päth et al. 2002). In addition, NGF enhances the survival of eosinophils, which may explain the airway eosinophilia associated with allergen challenge (Nassenstein et al. 2003). The administration of NGF alone in mice is sufficient to cause airway hyperresponsiveness comparable to that observed in an asthma-induced mouse model (Braun et al. 2001). In support of this mice lacking the neurotrophin receptor, p75NTR, have a drastically reduced sensitivity to capsaicin following allergen challenge (Kerzel et al. 2003). Furthermore, NGF contributes to airway remodelling following allergen challenge. NGF initiates sensory nerve hyperinnervation, (Rochlitzer et al. 2006), type III collagen production (Kılıç et al. 2011)and the migration of human pulmonary fibroblasts and their differentiation into myofibroblasts (Huang et al. 2015).

The GDNF family are also implicated in having a protective role in mouse models of allergic airway disease. GDNF expression is induced in the trachea of OVA sensitised and challenged mice (Lieu et al. 2012). Furthermore, global knockout of Nrtn in mice increases Th2 cytokine levels, immune cell infiltration and airway hyperreactivity in the airways following OVA sensitisation and challenge. This phenotype is partially rescued by re-introducing Nrtn before allergen challenge (Michel et al. 2011). Nrtn deficient mice also exhibit enhanced airway remodelling in an OVA-induced chronic model of allergic asthma (Mauffray et al. 2015). However, it has not previously been determined whether the levels of Nrtn are altered in mouse models of allergic asthma. We show that Nrtn levels are decreased in the BAL and increased in the lung tissue of HDM sensitised and challenged mice compared to PBS controls. These results suggest that there is an increased production of Nrtn in asthmatic airways and a higher level of Nrtn is being taken up by airway cells. For Nrtn to be taken up by cells, GFRα2 needs

145 to be expressed at the cell surface. It remains to be confirmed whether the presence of Th2 cytokines in mouse asthmatic airways induces cell surface expression of GFRα2.

Reports linking neurotrophic factors to influenza virus infection are scarce. One study shows that the mRNA levels of NGF and BDNF are decreased in the hippocampus of influenza-infected mice compared to controls (Jurgens et al. 2012). In addition, the serum levels of NGF and BDNF are increased in children infected with H1N1 influenza virus compared to controls, whereas GDNF levels remained unchanged (Chiaretti et al. 2013). The protein levels of these neurotrophic factors in the lungs following influenza infection has not yet been determined. We found that in mice the level of Nrtn in the BAL is significantly increased at day 8 post-influenza infection compared to naïve mice. This suggests that Nrtn has a role in this airway viral infection, which is yet to be elucidated. Neurotrophic factors are implicated in a variety of other viral infections. Higher NGF mRNA and protein levels are observed in the lungs in respiratory syncytial virus (RSV)-infected rats compared to controls (Hu et al. 2002). Altered expression of neurotrophins are also observed in humans presenting with RSV infection. The levels of NGF and BDNF are increased in the BAL of RSV-infected children compared to controls (Tortorolo et al. 2005). Moreover, the NGF receptor, TrkA, is expressed in airway epithelial cells and macrophages of RSV-infected children yet virtually undetectable in these cells in children non-infected or infected with other viruses (Tortorolo et al. 2005). This data suggests a very prominent role for neurotrophins in airway viral infections. One study also implicates the GDNF family in viral infection. GDNF and Nrtn maintain herpes simplex virus latency in sensory and sympathetic neurons (Yanez et al. 2017). Evidence suggests that neurotrophic factors may play a role in anti-viral activity during an infection. However, more studies are needed to understand how these factors are involved in a viral response.

4.3.4 What effect does Nrtn have on airway macrophages?

4.3.4.1 Pro-inflammatory cytokine production

Nrtn is known to decrease the levels of the pro-inflammatory cytokines, TNFα and IL- 6, in the supernatants of stimulated human PBMCs (Vargas-Leal et al. 2005) and mouse splenic T cells and BMDCs cocultured and stimulated with ovalbumin (Mauffray et al.

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2015). However, in these studies, Nrtn did not affect cytokine mRNA levels. In concurrence, we also found that Nrtn does not affect the mRNA levels of TNFα or IL-6 in LPS-stimulated mouse BMDMs, human MDMs or human airway macrophages. Surprisingly, only in the GM-CSF-differentiated BMDMs did we observe a decrease in the protein levels of TNFα and IL-6 in the supernatant. The reduction of TNFα in the supernatants of stimulated PBMCs by Nrtn was also observed with the addition of exogenous TNFα (Vargas-Leal et al. 2005). Whether this reduced level of pro- inflammatory cytokines is due to decreased production or impaired release of cytokines from the cells or due to uptake of TNFα and IL-6 by the cells is unknown. One way to answer this question would be to measure the intracellular cytokine levels. It is interesting that this same affect was not observed in M-CSF-differentiated BMDMs or human macrophages. The mRNA levels of the GFRα2 receptor are low on M-CSF- differentiated BMDMs, which may explain why Nrtn does not affect pro-inflammatory cytokine levels in these cells. The fact we did not see a decrease in pro-inflammatory cytokines in human macrophages possibly suggests that Nrtn has other effects on these cells compared to mouse macrophages.

We may be using the wrong stimulant or analysing the wrong effect. GDNF, for example, inhibits the production of TNFα and IL-6 in IL-17A-stimulated in primary human limbal epithelial cells via the NF-kB pathway (Bian et al. 2010). Therefore, it would be interesting to examine other stimuli and readouts in a more hypothesis free approach, for example, through RNA sequencing or proteomics.

Though Nrtn doesn’t inhibit TNFα release, it may have the opposite effect. Nrtn stimulation increases the level of TNFα, but not IL-6, in the supernatants of M-CSF- and GM-CSF- differentiated human MDMs. However, compared to the level of TNFα produced by LPS stimulation the concentration is only in the picogram range with Nrtn stimulation. Whether TNFα at this level is biologically relevant is not known.

4.3.4.2 Macrophage polarisation

Macrophages are plastic in nature and can adapt to their environment. One such way they do this is by polarising their phenotype and function. This polarisation is most apparent when activating macrophages towards a more pro-inflammatory or anti- inflammatory/repair phenotype in vitro by IFN-γ and IL-4, respectively. We 147 demonstrate that Nrtn does not affect macrophage polarisation at the mRNA or post- transcriptional level.

4.3.4.3 Macrophage phagocytic activity

Another important role of macrophages is to phagocytose invading pathogens to limit damage from an inflammatory response. Nrtn did not affect the phagocytosis of pHrodoTM conjugated S.aureus bioparticles by human MDMs. This may be because human MDMs need to be stimulated in order to express GFRα2 and RET at the cell surface. During homeostasis and resolution, macrophages are also required to clear apoptotic cells. It would be interesting to investigate whether Nrtn affects the uptake of apoptotic cells by human macrophages.

4.3.5 Nrtn does not induce RET phosphorylation in airway macrophages at steady state

Although GFRα2 is expressed at the mRNA level in airway macrophages, the canonical signalling partner, RET, is undetectable. Nrtn does not induce RET phosphorylation in airway macrophages at steady state. In addition, Nrtn does not affect the intracellular signalling pathways activated by LPS in airway macrophages. This may be due to the absence of RET on these cells and an inappropriate stimulus applied to airway macrophages to detect the signalling pathways downstream of Nrtn.

4.3.6 Conclusion

In conclusion, Nrtn is expressed by airway epithelial cells; however, the stimulus that induces the release of this neurotrophic factor is still unknown. Having said that, Nrtn production is enhanced in the lung tissue of mice following HDM-sensitisation and challenge and in the BAL of mice infected with influenza during peak inflammation. Although we found that Nrtn is produced by human airway structural cells, we were unable to determine the effect of Nrtn on airway macrophage function. In human macrophages, Nrtn did not affect macrophage production of pro-inflammatory cytokines, activation state or phagocytic activity. We hypothesise that this lack of an effect is due to the absence of GFRα2 and RET at the cell surface of macrophages.

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In the next chapter, we address this to show that TLR7/8 agonists stimulate the release of Nrtn from airway epithelial cells and that type I interferons up-regulate the expression of RET on airway macrophages. We therefore propose a role for the GDNF family in the immune response to viral infection.

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Chapter 5 : Does the GDNF family have a role in airway viral infection?

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5.1 Introduction

In the last chapter, the precise signals regulating GDNF family members were not identified. Nor are there any prior reports of GDNF family receptor up-regulation on innate immune cells. Upon infection of the respiratory tract, airway epithelial cells and airway macrophages are the predominant first responders, often producing type 1 interferons and chemokines.

5.1.1 The response of type I interferons to invading microbial pathogens in the airways

5.1.1.1 Airway epithelial cells in the detection of microbial pathogens

Viruses entering the airways must first bypass entrapment in the mucous and the mucociliary escalator. If a virus manages to reach the distal airways the preferred cell type for infection are airway epithelial cells (Iwasaki & Pillai 2014). Airway epithelial cells are not just a physical barrier to prevent the entry of pathogens into the body but also perform critical roles in immunity (Weitnauer et al. 2016). Airway epithelial cells express a range of PRRs that respond to the presence of microbial products (McNab et al. 2015). Evidence has confirmed these cells express all known human TLRs (Ioannidis et al. 2013). TLR activation on airway epithelial cells leads to the production of type I IFNs, cytokines and chemokines, stimulating an antiviral response, contributing to inflammation and mediating the recruitment of innate immune cells to the airways, respectively (Sha et al. 2004). The cells recruited to the airways to help clear infection include monocytes, neutrophils and NK cells. NK cells target infected epithelial cells that have reduced MHC class I expression and produce inflammatory cytokines necessary to facilitate adaptive immune cells. Monocytes (in addition to differentiating into macrophages and dendritic cells) and neutrophils aid alveolar macrophages in the phagocytosis of infected dead cells and apoptotic immune cells (Gazit et al. 2006; Hashimoto et al. 2007). Usually, innate immunity is sufficient to clear invading microorganisms. However, should they not be sufficient, adaptive immunity tackles the remaining pathogen load (Braciale et al. 2012). There are many parameters that determine whether pathogen clearance is successful or not. Equally, there are many instances where the induced immune response does more harm than good by causing 151 bystander tissue damage and occluding the airways that reduce lung function. Over the last few decades, many studies have attempted to limit bystander tissue damage by applying therapeutic or immune suppressants to limit damaging inflammation. To the best of our knowledge, the release of neuronal factors from airway epithelial cells in response to a pathogen and their subsequent role in viral clearance and/or the inflammatory response has so far not been elucidated.

5.1.1.2 Type I Interferon production and function

Almost all cells within the body have the capacity to produce type I IFNs (McNab et al. 2015). PRRs known to induce type I IFN production include RIG-1, MDA5, the NLRs and the TLRs; TLR3, TLR4, TLR7, TLR8 and TLR9 (Gay et al. 2014). During an airway viral infection, alveolar macrophages are one of the major producers of type I IFNs (Goritzka et al. 2015). Once released, type I IFNs can act in an autocrine or paracrine manner. They bind to their heterodimeric IFNAR, composed of IFNAR1 and IFNAR2 subunits, expressed on a variety of immune cells, including alveolar macrophages (Divangahi et al. 2015). This leads to activation of the JAK/STAT pathway, the activation of IRF9 and subsequent formation of the ISG factor 3 (ISGF3) complex (Ivashkiv & Donlin 2014). This complex binds to IFN-stimulated response elements (ISREs) in interferon- stimulated gene (ISG) promoters, triggering ISG transcription (Stark & Darnell 2012). Type I IFNs stimulate the production of several hundred ISGs that encode for cytokines, chemokines, antimicrobial proteins and pro- and anti-apoptotic molecules (Rusinova et al. 2013; Rauch et al. 2013). A major role for ISGs is to inhibit viral replication and promote viral clearance (Yan & Chen 2012). However, ISGs also effect the function of innate and adaptive immune cells during an infection (Ivashkiv & Donlin 2014). The influence of interferons on the expression of the GDNF family on airway macrophages has not been previously studied (Figure 5.1).

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Figure 5.1: The type I IFN signalling pathway. The type I IFNs (IFNα and IFNβ) bind to their receptor IFNAR. This leads to the recruitment of TYK2 and JAK1, which subsequently leads to the phosphorylation of STAT1 and STAT2. IRF9 is recruited to form the ISGF3 complex. This complex binds to IFN-simulated response elements (ISREs) and triggers the production of interferon-stimulated genes. It is not currently known if type I IFNs stimulate the production of neurotrophic factors. Adapted from (Platanias, 2005) and reproduction of Figure 1.4.

5.1.2 Dysregulation of the type I interferon response

Type I IFN-mediated signalling needs to be tightly regulated in order to successfully clear an invading pathogen, while limiting excessive damage to the host. Dysregulation of the type I IFN pathway can lead to chronic infections, autoimmune diseases and cancer (Di Domizio & Cao 2013). Furthermore, dysregulation of the IFN response is observed in COPD and asthma patients who experience exacerbations with subsequent infections (Matsumoto & Inoue 2014). The negative regulation of the type I IFN response is achieved through down-regulation of IFNAR expression, induction of negative regulators such as SOCS and USP18 and the induction of miRNAs (Nazarov et al. 2013). Viruses and tumour cells have evolved mechanisms to evade type I IFN- 153 mediated responses through manipulation of these negative regulatory pathways. For example, some viruses and tumour cells encode genes that degrade IFNAR (Liu et al. 2009) or produce agonist mimics of the negative regulators SOCS1, SOCS3 and USP18, which limit the extent and duration of type I IFN signalling, to escape from type I IFN- mediated anti-microbial actions (Yoshimura et al. 2007; Sarasin-Filipowicz et al. 2009). Whether the GDNF family play a role in type I IFN responses and/or are affected by dysregulation of this pathway is not yet known.

5.1.3 The alternatively spliced isoforms of GFRα2 and RET have differential functions

RET alternative splicing leads primarily to the production of two isoforms; namely RET9 and RET51 due to their unique 9 or 51 amino acid C-terminal tails, respectively (Tahira et al. 1990). However, other isoforms have been reported in humans, including RET43 (Carter et al. 2001). Evidence has shown these isoforms can activate differential signalling pathways. RET has multiple phosphorylation sites and therefore different proteins can bind to activate alternative signalling pathways (Liu et al. 1996). Moreover, adaptor proteins differentially bind to the alternate isoforms. For example, the Enigma (Borrello et al. 2002) and Shank3 (Schuetz et al. 2004) adaptor proteins bind to RET9 but not RET51. Differences in the cellular location and trafficking of the RET isoforms have also been proposed, which leads to variation in the downstream signalling cascades activated (Richardson et al. 2012). The short and long RET isoforms also have diverse functions. RET9, but not RET51, is essential for kidney 154 morphogenesis and enteric nervous system development. Transgenic expression of RET9, but not RET1, rescues the kidney agenesis and loss of enteric ganglia presented in RET-deficient mice (de Graaff et al. 2001). Conversely, only RET51 promotes the survival and tubulogenesis of mouse inner medullary collecting duct cells within the kidney (Lee et al. 2002). The relative expressions of the GFRα2 and RET isoforms on airway macrophages has not been previously defined. Furthermore, activation of the GFRα2 and RET receptors may lead to isoform-specific effects on airway macrophage function.

5.1.4 Optimal RET signalling occurs within membrane lipid rafts

Membrane lipid rafts are microdomains within the lipid bilayer that are enriched in cholesterol and sphingolipids signalling (Aureli et al. 2016; Patra 2008; Simons & Sampaio 2011). These microdomains enhance signalling transduction by enabling receptor complexes and signalling proteins to be in close proximity (Simons & Toomre 2000). Lipid rafts are enriched in GPI-anchored proteins; therefore, the GFRα receptors are highly expressed in these membrane microdomains. On the other hand, the signalling partner for the GFRα receptors, RET, is located outside of lipid rafts in the absence of a GFL (Tansey et al. 2000; Paratcha et al. 2001). RET translocates to lipid rafts following GFL stimulation and forms an active signalling complex with the GFR receptors, which enables optimal signal transduction (Baloh et al. 2000; Encinas et al. 2001; Paratcha et al. 2001; Pierchala et al. 2006). The generation of a knock-in mouse containing GFRα1 with a transmembrane domain instead of a GPI-anchor leads to GFRα1 expression in the plasma membrane outside of lipid rafts (Tsui et al. 2015). These mice display similar deficits to GFRα1 deficient mice, including loss of enteric neurons and renal agenesis (Enomoto et al. 1998; Tsui et al. 2015). In addition, the loss of the GPI-anchor attenuates the translocation of RET to lipid rafts following GDNF activation and diminishes the activation of downstream signalling pathways (Tansey et al. 2000; Tsui et al. 2015). Therefore, this data highlights the importance of GDNF receptor expression at the cell surface, specifically in membrane lipid rafts, to allow effective GDNF family signalling.

So far, the location of GFRα2 and RET within macrophages has not been investigated. In addition, it is not known whether the activation of macrophages induces the 155 expression and translocation of GFRα2 and RET to the cell surface membrane. Furthermore, it would be interesting to know if GFRα2 and RET expression at the cell surface is critical for effective downstream signalling in airway macrophages.

5.1.5 Hypothesis

The GDNF family have an important role in airway infectious diseases.

5.1.6 Aims

1) Investigate whether TLR activation or type I IFN stimulation affects the expression of the GDNF family on airway epithelial cells and/or airway macrophages. 2) Examine the cellular localisation of the GFRα2 and RET receptors in untreated and type I IFN treated macrophages, to determine whether effective GDNF family signalling can be elicited. 3) Determine the expression of the alternatively spliced RET isoforms in human airway macrophages.

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5.2 Results

5.2.1 Nrtn expression is enhanced in human bronchial epithelial cells following TLR stimulation

In the previous chapter, we found that Nrtn expression was increased in the BAL fluid of mice infected with influenza virus compared to naive controls. Airway epithelial cells express pattern recognition receptors, including TLRs, and are the first line of defence against infection (Greene & McElvaney 2005). Therefore, because we discovered the expression of Nrtn in the human bronchial epithelial cell line (Beas-2b), we wanted to determine whether Nrtn was released from epithelial cells in response to a viral or bacterial infection (or by using protein mimics). Beas-2b cells were stimulated with the TLR agonists lipoteichoic acid (LTA) (TLR2), polyI:C (TLR3), LPS (TLR4) and R848 (TLR7/8). Beas-2b cells express these TLR receptors at the mRNA and protein level (Sha et al. 2004; Ioannidis et al. 2013). Though TLR activation did not alter Nrtn mRNA levels in Beas-2b cells (Figure 5.2a) they did significantly increase the Nrtn protein content of cell lysates (Figure 5.12). Interestingly, though Nrtn protein content of cells was elevated by all TLR agonists, the release of Nrtn from Beas-2b cells was specific for agonism of the TLR7/8 receptors by R848 (Figure 5.2c).

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Figure 5.2: The production and release of Nrtn is enhanced by TLR agonist stimulation. A human bronchial epithelial cell line (Beas-2b) was stimulated for 24 hours with 100 ng/ml of the TLR2 and TLR4 agonists, LTA and LPS, respectively, and 1 μg/ml of the TLR3 and TLR7/8 agonists, polyI:C and R848, respectively (a,b,c). Cells were lysed and supernatants collected. Supernatants were concentrated using a centrifugal filter. The relative mRNA expression of Nrtn was measured (a). RT-qPCR data are normalised to the housekeeping gene RPLP0 and expressed as a fold change over the unstimulated control ± the standard deviation (SD) from the mean (a). The protein concentration of Nrtn in the cell lysates (b) and supernatants (c) was measured by ELISA. ELISA data are expressed as protein expression ± standard deviation (SD) from the mean. Graphs combine data from three independent experiments (a,b) or four independent experiments (c). *P < 0.05, **P < 0.01, ***P < 0.001; unpaired t-test.

5.2.2 TLR stimulation does not alter the expression of GFRα2 on macrophages

The THP-1 human monocytic cell line can be differentiated to macrophages using phorbol 12-myristate 13-acetate (PMA) (Auwerx 1991). THP-1 cells differentiated to macrophages express GFRα2 and surprisingly RET at the mRNA level at steady state (Figure 5.3). Therefore, we used these cells as a positive control for RET expression.

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Figure 5.3: RET is expressed on THP-1-differentiated macrophages at steady state. The THP-1 monocytic cell line was differentiated to macrophages by incubating cells with PMA for 4 hours. Cells were lysed and the relative mRNA expressions of GFRa2 and RET were measured. RT-qPCR data are normalised to the housekeeping gene RPLP0 and expressed relative gene expression ± the standard deviation (SD) from the mean. Graph combines data from four independent experiments.

As TLR7/8 activation enhances the production, and initiates the release of, Nrtn from human bronchial epithelial cells, we next determined whether TLR7/8 activation on macrophages increased the expression of the Nrtn receptor, GFRα2, or it’s signalling partner, RET, at the mRNA level. The stimulation of THP-1 differentiated macrophages with the TLR7/8 agonist R848 did not increase the mRNA expression of GFRα2 (Figure 5.43a) or RET (Figure 5.4b) above homeostatic levels. Nor was there any increase of GFRα2 (Figure 5.4c) or RET (Figure 5.4d) mRNA using additional TLR agonists (though in some cases expression was reduced).

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Figure 5.4: The mRNA expression of GFRα2 and RET is not altered on THP-1-differentiated macrophages following TLR agonist stimulation. The THP-1 monocytic cell line was differentiated to macrophages by incubating cells with PMA for 4 hours. THP-1 cells were stimulated for 24 hours with 1 μg/ml of R848 (a,b) or TLR1-9 agonists from the invivogen human TLR1-9 agonist kit according to the manufacturer’s instructions (c,d). Cells were lysed and the relative mRNA expressions of GFRa2 (a,c) and RET (b,d) were measured . RT-qPCR data are normalised to the housekeeping gene RPLP0 and expressed as a fold change over the unstimulated control. Data are from one independent experiment.

5.2.3 Stimulation of human bronchial epithelial cells with interferons does not affect Nrtn expression

Recognition of an invading pathogen induces the release of factors with antimicrobial properties. These factors include interferons, specifically type I interferons, which are important in host defence (McNab et al. 2015). To determine whether interferons released in response to a bacterial or viral pathogen affect the production and/or release of Nrtn, the human bronchial epithelial cell line (Beas-2b) were stimulated with type I interferons (IFNα and IFNβ), a type II interferon (IFNγ) and a type III interferon 160

(IFNλ). Interferon stimulation did not affect Nrtn mRNA levels or protein production in Beas-2b cells (Figure 5.5a and Figure 5.5b, respectively). In addition, stimulation of Beas-2b cells with interferons did not induce the release of Nrtn (data not shown).

Figure 5.5: Nrtn expression in human bronchial epithelial cells is not altered by interferon stimulation. A human bronchial epithelial cell line (Beas-2b) was stimulated with 20 ng/ml of IFNα, IFNβ, IFNγ or IFNλ (a,b). Cells were lysed and the relative mRNA expression of Nrtn was measured (a). RT-qPCR data are normalised to the housekeeping gene RPLP0 and expressed as a fold change over the unstimulated control ± the standard deviation (SD) from the mean. The protein concentration of Nrtn in the cell lysates was measured by ELISA (b). ELISA data are expressed as protein expression ± the standard deviation (SD) from the mean. Graphs combine data from three independent experiments.

5.2.4 Stimulation of THP-1 differentiated macrophages with type I interferons enhances RET expression

TLR activation did not affect the expression of GFRα2 or RET on macrophages (Figure 5.4). To investigate whether GFRα2 and RET expression is altered by interferons; cytokines predominantly released following TLR activation by a viral or bacterial pathogen, THP-1 differentiated macrophages were stimulated with IFNα, IFNβ, IFNγ and IFNλ. Stimulation of THP-1 differentiated macrophages with interferons for 4 hours did not alter the mRNA expression of GFRα2 or RET (Figure 5.6a and Figure 5.6b, respectively). However, stimulation for 24 hours with IFN-λ enhanced the mRNA expression of GFRα2 (Figure 5.6c) and stimulation for 24 hours with the type I interferons (IFNα, IFNβ) increased the mRNA expression of RET (Figure 5.6d) in THP-1 differentiated macrophages. Combining IFNγ and IFNλ or all interferons enhanced

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GFRα2 mRNA (Figure 5.6e) and RET mRNA (Figure 5.6f) in THP-1 differentiated macrophages. Therefore, because RET expression is induced on macrophages by type I interferons, RET may contribute to the anti-microbial activity of interferons.

Figure 5.6: Interferons enhance the expression of GFRα2 and RET on THP-1-differentiated macrophages. The THP-1 monocytic cell line was differentiated to macrophages by incubating cells with PMA for 4 hours. THP-1 cells were stimulated with 20 ng/ml of IFNα, IFNβ, IFNγ or IFNλ for 4 (a,b) or 24 hours (c-f). The relative mRNA expressions of GFRα2 (a,c,e) and RET (b,d,f) were measured. RT-qPCR data are normalised to the housekeeping gene RPLP0 and expressed as a fold change over the unstimulated control ± the standard deviation (SD) from

162 the mean. Graphs combine data from one independent experiment (a,b) or three independent experiments (c-f). *P < 0.05, **P < 0.01, ***P < 0.001; one way ANOVA.

Type I interferons enhance the mRNA expression of RET on macrophages. Therefore, to determine whether this translates to the protein level, a time course of type I interferon stimulation was conducted on THP-1 differentiated macrophages. High GFRα2 protein expression could be detected in both unstimulated cells and cells stimulated with IFN-α and IFN-β (Figure 5.7). Although RET expression could be detected in unstimulated cells, protein levels were increased at 6, 12, 24 hours and 32 hours post-interferon stimulation (Figure 5.7). The highest expression of RET at the protein level in THP-1 differentiated macrophages stimulated with type I interferons was observed at 24 hours (Figure 5.7).

Figure 5.7: Type I Interferons enhance the protein expression of RET on THP-1-differentiated macrophages. The THP-1 monocytic cell line was differentiated to macrophages by incubating cells with PMA for 4 hours. THP-1 cells were stimulated with 20 ng/ml of IFN-α and IFN-β for 6, 12, 24, or 32 hours. Cells were lysed, run through an SDS page gel and analysed for GFRα2 and RET expression. Data are from one independent experiment.

To determine where within the cell GFRα2 and RET are expressed, THP-1 differentiated macrophages, unstimulated or stimulated with type I interferons for 24 hours, were analysed by flow cytometry. Before the expression of GFRα2 and RET protein levels were assessed, all THP-1-differentiated macrophages were identified (Figure 5.8a), doublets were removed (Figure 5.8b) and live cells gated (Figure 5.8c).

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Figure 5.8: Gating strategy used to identify live THP-1-differentiated macrophages. The THP-1 monocytic cell line was differentiated to macrophages by incubating cells with PMA for 4 hours. Cells were run through a BD fortessa flow cytometer. All cells were gated (a), doublets removed (b) and live cells gated on (c). Data are from one independent experiment.

Low expression of GFRα2 could be detected at the surface of unstimulated THP-1 differentiated macrophages (Figure 5.9a) that was increased upon stimulation with type I interferon as evidenced by an increase in the mean fluorescent intensity and the proportion of cells expressing GFRα2 (Figure 5.9b and Figure 5.9c, respectively). In the cytoplasm, only low levels of GFRα2 were detected (Figure 5.9d), which was not increased in intensity following type I interferon stimulation compared to unstimulated cells (Figure 5.9e). In addition, only a very low percentage of cells expressed GFRα2 in the cytoplasm (Figure 5.9f Note the small scale), which may be more representative of 164 a background signal than specific GFRα2 detection. In contrast, clear GFRα2 expression could be detected in the nucleus of both unstimulated and type I interferon stimulated THP-1 differentiated macrophages (Figure 5.9g). Type I interferon stimulation did not appreciably increase what was already a high mean fluorescent intensity (Figure 5.9h) of, and proportion of cells expressing, GFRα2 in the nucleus (Figure 5.9i). However, further experiments would be needed to confirm this.

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Figure 5.9: GFRα2 surface, cytoplasmic and nuclear protein expression in THP-1— differentiated macrophages. The THP-1 monocytic cell line was differentiated to macrophages by incubating cells with PMA for 4 hours. Cells were stimulated with 20 ng/ml of IFNα and IFNβ for 24 hours. The expression of GFRα2 on the cell surface (a-c), in the cytoplasm (d-f) and in the nucleus (g-i) of THP-1 cells was analysed by mean fluorescent intensity (MFI) (b,e,h) and percentage (%) of cells positive for GFRα2 (c,f,i). Data are from one independent experiment. Staining of GFRα2 on THP-1 cells in media alone (blue), staining of GFRα2 on THP-1 cells stimulated with IFN-α and IFN-β (orange), FMO (red) (a,d,g).

Similarly to GFRα2, RET is expressed at low levels on the cell surface of unstimulated THP-1-differentiated macrophages (Figure 5.10a). A clear upregulation of expression occurred following type I interferon stimulation, evidenced by an increase in mean fluorescent intensity (Figure 5.10b) and the percentage of cells expressing RET at the

166 surface (Figure 5.10c). Additionally, low expression of RET was observed in the cytoplasm of unstimulated cells (Figure 5.10d). Although a small shift in RET expression could be detected in type I interferon stimulated cells (Figure 5.10d), with increased mean fluorescent intensity (Figure 5.10e) and percentage of RET-expressing cells (Figure 5.10f), the levels were still very low. As observed for GFRα2, the highest expression of RET in THP-1-differentiated macrophages was found within the nucleus (Figure 5.10g). Type I interferon stimulation did not appreciably increase what was already a high mean fluorescent intensity (Figure 5.10h) and proportion of positive cells (Figure 5.10i). Therefore, THP-1-differentiated macrophages express GFRα2 and RET in the nucleus at steady state and increase the surface expression of both these receptors following type I interferon stimulation.

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Figure 5.10: RET surface, cytoplasmic and nuclear protein expression in THP-1 –differentiated macrophages. The THP-1 monocytic cell line was differentiated to macrophages by incubating cells with PMA for 4 hours. Cells were stimulated with 20 ng/ml of IFNα and IFNβ for 24 hours. The expression of RET on the cell surface (a-c), in the cytoplasm (d-f) and in the nucleus (g-i) of THP-1 cells was analysed by mean fluorescent intensity (MFI) (b,e,h) and percentage (%) of cells positive for RET (c,f,i). Data are from one independent experiment. Staining of RET on THP-1 cells in media alone (blue), staining of RET on THP-1 cells stimulated with IFN-α and IFN- β (orange), FMO (red) (a,d,g).

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5.2.5 Stimulation of M-CSF-differentiated MDMs with type I interferons enhances RET expression

To determine whether type I interferons enhance the expression of RET in a more biologically relevant macrophage model, human M-CSF-differentiated MDMs were stimulated with type I interferons (IFNα and IFNβ), a type II interferon (IFNγ) and a type III interferon (IFNλ). A significant increase in the mRNA expression of GFRα2 was observed in M-CSF-differentiated MDMs following IFNγ stimulation at 4 hours (Figure 5.11a). The type I interferon, IFNβ, significantly enhanced the mRNA expression of RET in M-CSF-differentiated MDMs at 4 hours, with a trend towards an increase in expression with IFN-α stimulation (Figure 5.11b). Interestingly, IFNα, IFNβ and IFNγ stimulation all significantly decreased the mRNA expression of GFRα2 in M-CSF- differentiated MDMs at 24 hours (Figure 5.11c). On the other hand, a significant increase in RET expression was still observed following IFN stimulation at 24 hours (Figure 5.11d).

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Figure 5.11: Type I interferons enhance the mRNA expression of RET on human M-CSF- differentiated MDMs. CD14+ monocytes were isolated from human peripheral blood of healthy donors and cultured in 20 ng/ml of M-CSF. After 6 days of culture, cells were lysed and RNA extracted. The relative mRNA expressions of GFRα2 and RET were measured on M-CSF- differentiated MDMs following stimulation with 20 ng/ml of IFNα, IFNβ, IFNγ or IFNλ for 4 (a,b) or 24 hours (c,d). RT-qPCR data are normalised to the housekeeping gene RPLP0 and expressed as fold change over the unstimulated control ± the standard deviation (SD) from the mean. Graphs combine data from three independent experiments. *P < 0.05, **P < 0.01; one- way ANOVA.

Similarly, to THP-1 macrophages, type I interferons significantly enhanced the mRNA expression of RET in M-CSF-differentiated macrophages. To investigate whether an increase was also observed at the protein level, M-CSF-differentiated macrophages were treated with the type I interferons, IFNα and IFNβ, at different concentrations for 24 hours. Protein expression was analysed by western blot, and RET expression was observed to be induced with type I interferon stimulation (Figure 5.12). The presence of two bands was interesting and may represent the detection of both the immature and mature forms of RET in these cells. In contrast, the levels of GFRα2 remained

170 relatively high and constant between unstimulated and type I interferon stimulated M- CSF-differentiated MDMs (Figure 5.12). Therefore, some conclusions made with the THP-1 macrophage cell line on GFR2 expression transferred to primary macrophages, whereas a positive influence for IFN did not.

Of interest, RET expression at the protein level in M-CSF-differentiated MDMs was difficult to detect compared to THP-1-differentiated macrophages. A higher percentage of sodium dodecyl sulfate (SDS) was required in the cell lysis buffer in order to observe RET by western blot. This suggests that RET may be concentrated in a specific cellular compartment upon stimulation. Further analysis may require fractionation of the nuclear and cytosolic regions of the cell to enhance the signal. Alternatively, RET may be expressed within an insoluble part of the cell. To corroborate this, RET is known to be recruited to lipid rafts, where it binds to the GFRα/GFL complex to activate downstream signalling cascades (Tansey et al. 2000). Therefore, type I interferon stimulation of M-CSF-differentiated MDMs may trigger the protein expression of RET and the subsequent recruitment of this receptor tyrosine kinase to membrane lipid rafts.

Figure 5.12: Type I interferons enhance the protein expression of RET on human M-CSF- differentiated MDMs. CD14+ monocytes were isolated from human peripheral blood of healthy donors and cultured in 20 ng/ml M-CSF. After 6 days of culture, cells were stimulated with 20 ng/ml or 100 ng/ml of IFN-α and IFN-β for 24 hours. Cells were lysed, run through an SDS page gel and analysed for GFRα2 and RET expression. Data are from one independent experiment with three healthy donors.

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To assess whether RET could be more easily identified using an alternative method at the protein level, the expression of GFRα2 and RET was analysed on unstimulated and type I interferon stimulated M-CSF-differentiated MDMs at 24 h by flow cytometry. All M-CSF-differentiated cells were gated on (Figure 5.13a), doublets removed (Figure 5.13b) and live cells identified (Figure 5.13c).

Figure 5.13: Gating strategy used to identify live M-CSF-differentiated MDMs. CD14+ monocytes were isolated from human peripheral blood of healthy donors and cultured in 20 ng/ml of M-CSF. After 6 days of culture, cells were run through a BD fortessa flow cytometer. All cells were gated (a), doublets removed (b) and live cells gated on (c). Data are representative of two independent experiments.

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GFRα2 could be detected at the surface of unstimulated and type I interferon stimulated MDMs (Figure 5.14a). Type I interferon stimulation did not really further enhance what was already very high expression (Figure 5.14b and figure 5.14c). GFRα2 expression could also be detected in the cytoplasm of M-CSF-differentiated MDMs (Figure 5.14d) with a partial increase upon interferon stimulation (Figure 5.14e and figure 5.14f). However, GFRα2 was found to be most highly expressed within the nucleus (Figure 5.14g). No difference in mean fluorescent intensity was observed in the nucleus between unstimulated and type I interferon stimulated MDMs (Figure 5.14h). In addition, the majority of cells expressed GFRα2 in the nucleus even at steady state (Figure 5.14i).

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Figure 5.14: GFRα2 surface, cytoplasmic and nuclear protein expression in M-CSF- differentiated MDMs. CD14+ monocytes were isolated from human peripheral blood of healthy donors and cultured in 20 ng/ml M-CSF. After 6 days of culture, cells were stimulated with 20 ng/ml of IFNα and IFNβ for 24 hours. The expression of GFRα2 on the cell surface (a- c), in the cytoplasm (d-f) and in the nucleus (g-i) of M-CSF- differentiated MDMs was analysed by mean fluorescent intensity (MFI) (b,e,h) and percentage (%) of cells positive for GFRα2 (c,f,i). Graphs combine data from two independent experiments. Staining of GFRα2 on M-CSF- differentiated MDMs in media alone (blue), staining of GFRα2 on M-CSF- differentiated MDMs stimulated with IFN-α and IFN-β (orange), FMO (red) (a,d,g).

As it was difficult to detect RET protein expression by western blot, it was surprising to observe RET expression on the cell surface of M-CSF-differentiated MDMs at steady state by flow cytometry (Figure 5.15a). Addition of type I IFNs had little effect on the 174 already significant expression (Figure 5.15b and figure 5.15c). In addition, RET was detected at the protein level within the cytoplasm of both unstimulated and type I interferon stimulated MDMs (Figure 5.15d-f). Similar to THP-1-differentiated macrophages, the highest expression of RET was detected within the nucleus of M- CSF-differentiated MDMs (Figure 5.15g) that type 1 IFNs did not increase further (Figure 5.15h-i).

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Figure 5.15: RET surface, cytoplasmic and nuclear protein expression in M-CSF-differentiated MDMs. CD14+ monocytes were isolated from human peripheral blood of healthy donors and cultured in 20 ng/ml of M-CSF. After 6 days of culture, cells were stimulated with 20 ng/ml of IFNα and IFNβ for 24 hours. The expression of RET on the cell surface (a-c), in the cytoplasm (d-f) and in the nucleus (g-i) of M-CSF- differentiated MDMs was analysed by mean fluorescent intensity (MFI) (b,e,h) and percentage (%) of cells positive for RET (c,f,i). Graphs combine data from two independent experiments. Staining of RET on M-CSF- differentiated MDMs in media alone (blue), staining of RET on M-CSF- differentiated MDMs stimulated with IFN-α and IFN-β (orange), FMO (red) (a,d,g).

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5.2.6 Stimulation of human airway macrophages with type I interferons enhances RET expression

The levels of neurotrophic factors, specifically the neurotrophins, are known to be enhanced in the airways during viral infection. The levels of NGF, BDNF and the neurotrophin receptor, TrkA, are enhanced in the BAL fluid of RSV-infected children compared to non-infected children and children infected with other viruses (Tortorolo et al. 2005). In addition, our data suggests that Nrtn levels are enhanced in a mouse model of influenza infection, with the source of this Nrtn possibly from airway epithelial cells. Therefore, to determine whether type I interferons also enhance the expression of the signalling receptor for the GDNF neurotrophic factor family, RET, on airway macrophages, human airway macrophages perfused from the healthy margins of resected lung tissue were stimulated with IFN-α, IFN-β, IFN-γ and IFN-λ. Though the mRNA expression of GFRα2 was not altered by interferon stimulation at 4 hours (Figure 5.16a) RET mRNA was significantly increased (Figure 5.16b). Furthermore, human airway macrophage GFRα2 mRNA expression was not affected by interferon stimulation at 24 hours (Figure 5.16c). However, RET mRNA expression in human airway macrophages was still enhanced 24 hours post type I interferon stimulation (Figure 5.16d).

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Figure 5.16: The expression of RET is enhanced on human airway macrophages following stimulation with type I interferons. Human airway macrophages were perfused from the healthy margins of lung resection samples and adhered cells lysed and RNA extracted. The relative mRNA expressions of GFRα2 and RET were measured on human airway macrophages following stimulation with 20 ng/ml of IFNα, IFNβ, IFNγ and IFNλ for 4 (a,b) or 24 hours (c,d). RT-qPCR data are normalised to the housekeeping gene RPLP0 and expressed as fold change over the unstimulated control ± the standard deviation (SD) from the mean. Graphs combine data from three independent experiments. *P < 0.05, **P < 0.01; one-way ANOVA.

5.2.7 Stimulation of mouse airway macrophages with type I interferons does not induce RET expression

To assess whether type I interferon stimulation alters the mRNA expression of RET in mouse cells, airway macrophages were isolated from the BAL fluid of naïve C57BL/6 mice and stimulated with the type I interferons, IFNα and IFNβ, for 24 hours. The mRNA expression of RET in mouse airway macrophages was not induced by type I interferon stimulation (Figure 5.17a). A reason for this may be that a higher concentration of IFNα and IFNβ may be required to enhance RET expression in these 178 cells. Furthermore, a mouse cell type expressing RET at the mRNA level should be run in parallel to confirm the primer used in this experiment can detect RET.

Figure 5.17: Type I interferons do not enhance the expression of RET in mouse airway macrophages. BAL fluid was obtained from female naive C57BL/6 mice and adhered mouse airway macrophages were lysed and RNA extracted. The relative mRNA expression of RET was measured on mouse airway macrophages following stimulation with 20 ng/ml of IFNα and IFNβ for 24 hours (b). RT-qPCR data are normalised to the housekeeping gene RPLP0 and expressed as relative gene expression ± the standard deviation (SD) from the mean. Graphs combine data from one independent experiment with three mice.

5.2.8 Stimulation of human airway macrophages with type I interferons induces the expression of different RET isoforms

RET is alternatively spliced to produce different isoforms (Richardson et al. 2012). To investigate which RET isoforms type I interferons induce in human airway macrophages, these cells were stimulated with type I interferons for 4 and 24 hours. The mRNA expression of the isoforms, RET51 and RET9, was identified. Both RET51 and RET9 were enhanced at the mRNA level in human airway macrophages following IFNα and IFNβ stimulation at 4h and 24 hours (Figure 5.18a and Figure 5.18b, respectively). Therefore, this suggests multiple isoforms of RET are produced in human airway macrophages following type I interferon stimulation. It is unknown whether these isoforms have different functions.

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Figure 5.18: Type I interferons induce the expression of the RET51 and RET9 isoforms in human airway macrophages. Human airway macrophages were perfused from the healthy margins of lung resection samples and adherent cells lysed and RNA extracted. The relative mRNA expressions of RET51 and RET9 were measured in human airway macrophages following stimulation with 20 ng/ml of IFNα and IFNβ for 4 (a) or 24 hours (b). RT-qPCR data are normalised to the housekeeping gene RPLP0 and expressed as fold change over the unstimulated control ± the standard deviation (SD) from the mean. Graphs combine data from three independent experiments.

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5.3 Discussion

5.3.1 TLR activation enhances the production of Nrtn in human bronchial epithelial cells

In the airways, epithelial cells are one of the first cells to encounter a potentially harmful microorganism (Weitnauer et al. 2016). As such, these cells are well-adapted in the recognition of a vast range of pathogens, through their expression of TLRs (Iwasaki et al. 2016). Activation of TLR signalling in airway epithelial cells leads to the production of pro-inflammatory cytokines, chemokines and antimicrobial peptides (Sha et al. 2004). This initiates an inflammatory response to help clear the infection and protect the host from further damage. We have described for the first time that TLR activation enhances the production and release of the neurotrophic factor, Nrtn, from human bronchial epithelial cells. Therefore, this suggests that Nrtn has a role in airway host defence against infections, or that epithelial cells contribute to neurogenesis in the inflamed lung. In support of the former, the GDNF family have previously been described to regulate gut host defence (Ibiza et al. 2016). mRNA levels of Nrtn are increased in enteric glial cells following TLR2 and TLR4 stimulation (Ibiza et al. 2016). We did not observe a significant difference in Nrtn at the mRNA level in Beas-2b cells. This discrepancy may reflect a lack of analysis of Nrtn protein expression in gut epithelium.

An antiviral role for Nrtn has also been described during herpes simplex virus in primary sympathetic neurons where it inhibits viral replication (Yanez et al. 2017). In our study, although increased Nrtn production is detected in the Beas-2B cell line stimulated with a range of TLR agonists, the release of Nrtn from these cells appears to be specific to TLR7/8 activation. Importantly, the influenza virus is detected by TLR7 and TLR8 (Pang & Iwasaki 2012) and we have shown that Nrtn release is enhanced in the airways of influenza-infected mice compared to controls. This increase in Nrtn, at least in part, could be from airway epithelial cells following recognition of the influenza virus by TLR7 and TLR8. This could be further tested by blocking TLR7/8 in in vitro experiments examining influenza virus replication in epithelial cells and then examining Nrtn release.

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5.3.2 RET as a novel interferon-stimulated gene

Type I IFNs are produced at high levels in the airways in response to viral infection (Ivashkiv & Donlin 2014). We have shown that type I IFNs induce the expression of the neurotrophic receptor, RET, in human airway macrophages. Therefore, we propose RET as a novel ISG. Furthermore, RET induction is specific to type I IFNs as stimulation with the type II IFN, IFN-γ, and the type III IFN, IFN-λ, have no effect. However, the cells affected by IFNλ are likely to be limited as the IFNλ receptor is thought to mainly be expressed by epithelial cells within the airways (Witte et al. 2010; Durbin et al. 2013). Interestingly, RET has not been characterised as an interferon- stimulated gene previously. This may be due to the cell types used in other studies to determine the genes upregulated by IFNs. Whether RET expression is up-regulated following type I IFN stimulation on other cell types remains to be established. At present, it would appear that the limitation of GFR2 activity is mediated by the expression of RET.

In contrast to the human studies, stimulation of mouse airway macrophages with type I IFNs did not induce the expression of RET at the mRNA level. However, to confirm this we would need to test the primers used in our experiments in a mouse cell type known to express RET at the mRNA level. It is interesting that TLR activation has no effect on RET expression in THP-1-differentiated macrophages, suggesting these cells do not produce a high enough level of type I IFNs. IFNβ is released constitutively in the airways and induces tonic IFNAR signalling (Gough et al. 2012). Therefore, this suggests a threshold of activation needs to be overcome in order for RET to be expressed in macrophages. It would make sense that RET needs to be tightly regulated if this neurotrophic factor receptor is involved in promoting potent antiviral activity.

5.3.3 Is the subcellular location of GFRα2 or RET in human airway macrophages affected by type I IFN stimulation?

In chapter 3, we demonstrated that the GFRα2 receptor was not expressed on the surface of naïve mouse airway macrophages. In this chapter, we have shown that type I IFNs induce RET expression at the mRNA and protein level. Therefore, we wanted to know where the GDNF family receptors were expressed within airway macrophages.

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The immature form of RET is produced within the endoplasmic reticulum, with the mature form expressed on the cell surface (Richardson et al. 2012). We found the highest expression of GFRα2 and RET in the nucleus of human macrophages by flow cytometry. Therefore, to counteract the weak signal observed by western blot of the RET protein in monocyte-derived macrophages, separating the nuclear and cytoplasmic fractions of cell lysates may allow for a clearer band detection. Currently, it is unclear why we can readily detect RET at the protein level in THP-1-differentiated macrophages and not in monocyte-derived macrophages by western blot. One reason for this could be that RET is much more highly expressed in the THP-1-differentiated macrophages.

In a previous study the overall levels of RET expressed at the plasma membrane were found to be relatively low (Richardson et al. 2012). We observed only minor differences in RET protein expression in type I IFN stimulated THP-1-differentiated and monocyte-derived macrophages compared to untreated macrophages by flow cytometry. This contradicts the relatively low levels of RET observed in untreated compared to type I IFN treated human macrophages by western blot. To overcome the discrepancies between the two techniques, immunofluorescence imaging of GFRα2 and RET in monocyte-derived macrophages following a time-course of type I IFN stimulation will need to be performed in order to confidently identify the cellular location of these GDNF family receptors. The reason flow cytometry was chosen over immunofluorescence in the first instance was to reproduce our findings in human airway macrophages. The autofluorescence of airway macrophages is more easily controlled for in flow cytometry than immunofluorescent imaging due to the greater range of fluorophores available. In addition, previous reports have shown that in the absence of a GNDF family ligand, RET is not found at the cellular surface. Activation of cells with GDNF induces the translocation of RET to membrane lipid rafts, which appears to be critical for effective signal transduction (Tansey et al. 2000; Paratcha et al. 2001). Therefore, we would also need to determine whether Nrtn is required to initiate RET cell surface expression.

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5.3.4 Do GFRα2 and RET splice variants expressed on human airway macrophages have distinct functions?

5.3.4.1 The RET9 and RET51 isoforms are expressed on human airway macrophages

Alternative splicing is a process by which structurally and functionally diverse mRNA and protein variants can be produced from a single gene (Blencowe 2006). Alternatively spliced isoforms of GFRα2 (Wong & Too 1998) and RET (Lorenzo et al. 1997; de Graaff et al. 2001; Lee et al. 2002) have been reported. Alternative splicing of the RET gene predominantly produces the short RET9 isoform and the long RET51 isoform (Tahira et al. 1990). Both isoforms are generally co-expressed, with RET9 frequently detected at higher levels (Ivanchuk et al. 1998; Le Hir et al. 2000; Lee et al. 2003). However, this does not necessarily correlate with enhanced RET9 protein levels at the cellular surface as RET51 has been found to be more efficiently trafficked to the cell surface (Richardson et al. 2012). Although we did not characterise the expression of the three GFRα2 splice variants in human airway macrophages, we did observe induction of both the RET9 and RET51 isoforms at the mRNA level in human airway macrophages stimulated with type I IFNs. Both isoforms were expressed at relatively similar levels. It would be interesting to further explore the expression of the RET isoforms at the protein level as differences in the regulation, signalling and function of these isoforms have been previously reported in other cell types and tissues.

In addition to the diversity in cellular localisation of the RET isoforms, the signalling pathways activated, and therefore their function, have also been reported to be distinct. RET9 and RET51 differ in their interaction with the adaptor proteins Grb2 (Alberti et al. 1998), Shank3 (Schuetz et al. 2004) and enigma (Borrello et al. 2002). Interestingly, another study found that the specific activation of GFRα2c and RET9 by Nrtn was required to trigger neurite outgrowth in a STAT3-dependent manner, which was not induced by other GFRα2 and RET isoform combinations (Zhou & Too 2013). Furthermore, RET9 was found to be essential for kidney and enteric nervous system development, whereas RET51 displayed redundancy in these roles (de Graaff et al. 2001; Lee et al. 2002). Whether the specific activation of distinct GFRα2 or RET isoforms on airway macrophages are important determinants in the functions elicited by these cells remains unknown. 184

5.3.4.2 Which GFRα2 isoforms are expressed on human airway macrophages?

One study revealed the differential functions exerted by the three GFRα2 splice variants: GFRα2a, GFRα2b and GFRα2c. Whereas ligand activation of the GFRα2a and GFRα2c isoforms induced neurite outgrowth, GFRα2b activation inhibited the functional effect of the other two isoforms (Yoong & Too 2007). Although stimulation of the three different isoforms with GDNF resulted in diverse activation of downstream signalling molecules, Nrtn activated ERK1/2 and Akt signalling pathways at similar levels through GFRα2a, GFRα2b and GFRα2c (Yoong & Too 2007). This data suggests that not only ligand-specific variations in GFRα2 signalling exist, but activation of different isoforms of GFRα2 exert differential functional outcomes on the cells that they are expressed by. The characterisation of GFRα2 isoform expression on human airway macrophages has not been explored within this thesis however would be an important question to address in the future.

5.3.5 Dysregulation of the type I IFN response

Type I IFNs are important in host defence against viral and bacterial infections. However, dysregulated type I IFN signalling can lead to chronic infections, autoimmune diseases and cancer (Di Domizio & Cao 2013). Counterintuitively, type I IFNs can also have protective roles, with type I IFN therapy currently used as a treatment in some of these chronic diseases. We describe an induction of RET expression on human macrophages following type I IFN stimulation. Prolonged type I IFN signalling may enhance the expression of RET and therefore could be an important factor to investigate in the development of chronic infection or disease.

5.3.5.1 Dysregulation of the type I IFN response in asthma and COPD exacerbations

Airway viral infections cause the exacerbation of asthma and COPD and type I IFN responses are reported to be defective in these chronic airway diseases. The production of IFNβ from the airway epithelial cells of asthmatic patients is lower than that of healthy subjects (Wark et al. 2005). Likewise, COPD patients experimentally infected with rhinovirus display reduced levels of IFN-α, IFN-β and IFN-λ in BAL fluid compared to healthy subjects (Mallia et al. 2011). Therefore, it would be interesting to

185 investigate whether GDNF receptor family expression in the airways is altered in asthmatic or COPD patients with exacerbations.

5.3.5.2 A role of the type I IFN response in chronic infections

If a pathogen is unable to be cleared, simultaneous inflammation and immunosuppression ensues leading to chronic infections (Snell et al. 2017). Type I IFNs are at the forefront of the development of chronicity; able to drive an inflammatory response and induce the expression of suppressive factors, such as PD- L1 and IL-10 (Spranger et al. 2013; Cunningham et al. 2016). In a model of chronic lymphocytic choriomeningitis virus (LCMV), inhibition of type I IFNs using IFNAR blocking antibodies reduced immunosuppressive factors and chronic inflammation associated with persistent infection (Teijaro et al. 2013; Wilson et al. 2013). In concurrence, a type I IFN signature is detected in patients who are chronically infected with HCV and HIV (Forster 2012) and in chronic mycobacterial tuberculosis (Teles et al. 2013). It is unknown whether the GDNF family play a role in the development of chronic infections.

5.3.5.3 A link between the GDNF family and type I IFNs in autoimmune diseases

Type I IFNs are also implicated in the development of autoimmune diseases, including SLE, rheumatoid arthritis and multiple sclerosis (Rönnblom 2016). A chronic increase of type I IFNs and the associated type I IFN response is seen in various autoimmune diseases such as systemic lupus erythematosus (SLE) and rheumatoid arthritis (Hall & Rosen 2010). SLE patients treated with anti-IFNAR have marked improvement in the severity of their symptoms (Furie et al. 2015). To date, the role of neurotrophic factors in SLE or rheumatoid arthritis has not been extensively researched.

In contrast to SLE, one of the current treatments for multiple sclerosis is IFNβ therapy. Multiple sclerosis is a chronic inflammatory autoimmune disease, characterised by demyelination, loss of oligodendrocytes and axonal degeneration (Caggiula et al. 2006). Interestingly, a link between multiple sclerosis and neurotrophic factors has been described. Although the GDNF receptor family have not been thoroughly investigated in this autoimmune disease, the neurotrophin, BDNF is more highly produced in PBMCs from multiple sclerosis patients compared to healthy controls 186

(Sarchielli et al. 2002). Interestingly, IFNβ enhances the PBMC production of neurotrophins from multiple sclerosis patients, which is predicted to be beneficial in employing neuroprotective effects in this disease (Lalive et al. 2008). Furthermore, the neuropoietic cytokines, CNTF and LIF, ameliorate experimental autoimmune encephalomyelitis, which is an animal model of multiple sclerosis, by promoting survival of oligodendrocytes (D’Souza et al. 1996; Butzkueven et al. 2002) and suppressing Th17 cell differentiation (Cao et al. 2011). The role of the GDNF family, and neurotrophic factors in general, in the development and/or treatment of autoimmune diseases is currently under-researched. In a similar manner to type I IFNs, the GDNF factors may have beneficial or deleterious roles in autoimmunity, depending on the disease. Nevertheless, it would be interesting to characterise the role of this family of neurotrophic factors in autoimmunity, especially in relation to type I IFN-mediated signalling.

5.3.5.4 A link between the GDNF family and type I IFNs in cancer

Excessive inflammation in chronic infections or autoimmune diseases can lead to the formation of tumours (Balkwill & Mantovani 2001). Our research suggests that the expression of the GDNF family, and specifically RET, may be altered in these conditions due to a dysfunction in type I IFN responses. Gain-of-function mutations in the RET proto-oncogene are associated with familial neuroendocrine tumours and medullary thyroid cancers (Jhiang 2000). However, it is not only mutations in the RET gene which links RET to cancer, as RET expression in pancreatic and breast cancers is associated with a poorer prognosis (Zeng et al. 2008; Kang et al. 2009). Given the importance of RET in bone marrow haematopoiesis (Fonseca-Pereira et al. 2014), RET is also implicated in patients with chronic myelomonocytic leukemia and acute myeloid leukemia (Ballerini et al. 2012); both haematopoietic cancers. Moreover, oncogenic RET has been discovered in lung adenocarcinomas (Kohno et al. 2012; Suehara et al. 2012; Takeuchi et al. 2012). One mechanism by which RET activation exacerbates tumour progression is through the release of pro-inflammatory cytokines and chemokines that leads to the recruitment of immune cells and enhanced inflammation (Borrello et al. 2005). Therefore, it is not surprising that RET inhibitors are a potential therapeutic for cancer patients.

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Patient responsiveness to TLR agonists or type I IFNs have shown promise in certain tumour types and subsets of patients (Kaczanowska et al. 2013; Zitvogel et al. 2015). However, it is clear that predictive markers are required in order to determine which patients will benefit from these treatments. RET expression on immune cells recruited to the tumour microenvironment has not previously been considered and could be altered in the course of TLR agonist or type I IFN treatment. This would be an exciting area of research to explore further.

5.3.6 Conclusion

In conclusion, we have described for the first time the potential role of the GDNF family in airway host defence against infection. We propose that Nrtn is released from airway epithelial cells following TLR recognition of a virus or bacteria. Simultaneously, TLR activation triggers the production of type I IFNs, which activate the IFNAR receptor on airway macrophages and induce the expression of a novel ISG, the GDNF family signalling receptor RET. Nrtn binds to the GFRα2 receptor on airway macrophages and stimulates RET recruitment to the active signalling complex. Subsequent RET activation may exert antiviral activity on airway macrophages. Furthermore, dysregulation of type I IFN signalling leads to chronic infection, autoimmunity and cancer. Further research into understanding the role of the GDNF family in these chronic diseases in relation to type I IFNs may uncover potentially new therapeutics.

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Chapter 6 : Final Discussion

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6.1 Discussion

Neuronal and immune cells communicate with one another through their ability to detect and respond to the soluble mediators both systems produce. The importance of this interaction is becoming increasingly evident, however so far, we have only begun to scratch the surface of the pathways involved in this crosstalk. Although previous studies have addressed the function of neuronal factors in the immune system, the expression of these factors within the airways, and in particular on airway macrophages, has not been extensively characterised. Airway macrophages are the predominant cell type residing in the healthy airspaces and their location means they are continuously exposed to the external environment. These cells perform crucial homeostatic duties by clearing products of matrix turnover and natural cell death. However, they can also detect harmful micro-organisms when required and are instrumental in mounting an inflammatory response to protect the host.

The balance between homeostatic duties versus inflammation requires processes that enable them to distinguish between these two very disparate responses. The laboratory has investigated for some time how the intact epithelium instructs a tolerant state in airway macrophages via the secretion of surfactant proteins and the expression of ligands that bind macrophage inhibitory receptors (e.g CD200R and SIRP). It is possible that we have discovered another form of cross-talk via epithelial neurturin binding to GFRα2 on airway macrophages.

It is also possible that epithelial neurturin influences the dense network of peripheral sensory neurons in the lung, either by preventing their activity and/or driving their development. Stimulation of sensory neurons exacerbates airway inflammation and hyperresponsiveness in patients with chronic airway disease, such as asthma. Therefore, communication between sensory nerves and immune cells is evident within the airways.

In this thesis we define for the first time the expression of the neurotrophic factor receptor, GFRα2 on mouse and human airway macrophages. In concurrence with previous studies, observing the expression of the GFRα2 ligand, Nrtn, in airway epithelial cells in both mice (Golden et al. 1999) and humans (Hackett et al. 2012), we

190 describe the constitutive expression of Nrtn on human airway epithelial cells. In order to define the role of this interaction on airway macrophages, the laboratory has now instigated the development of a transgenic mouse with the GFRα2 gene floxed that will allow deletion in individual cell types expressing Cre recombinase. For example, it will be possible to cross GFRα2 floxed mice with CX3CR1-cre mice, thus deleting this gene in macrophages.

6.2 Does Nrtn affect the function of airway macrophages in allergic airway disease?

Previous studies highlight the dysfunction of airway sensory nerves in patients with allergic asthma, which manifests as increased sensitivity to stimuli and enhanced release of neuropeptides (Nockher & Renz 2006). Furthermore, in a mouse model of allergic asthma, Nrtn ameliorates the airway hyperresponsiveness and type 2 inflammatory response characteristic of this disease (Michel et al. 2011). This suggests that neurturin may inhibit inflammation in some settings. In our studies IL-4, which is upregulated in allergic asthma, enhances the expression of GFRα2 in mouse and human airway macrophages. The expression of GFRα2 was undetectable on the surface of mouse alveolar and interstitial macrophages from naïve mice, which begs the question of whether IL-4 stimulation is required for receptor translocation to the cell surface in order to mediate Nrtn signalling. Furthermore, we show that in a mouse model of allergic asthma, the levels of Nrtn are enhanced in the lung.

It should be noted however that IL-4 stimulation did not induce the expression of the canonical signalling partner for GFRα2, RET. The precise events leading to signalling therefore remain to be identified. It was interesting that GFRα2 expression was not enhanced on airway macrophages obtained from the induced sputum of patients with allergic asthma. This may reflect that the receptor is already optimally expressed and that the level of neurturin or the recruitment of RET may be the limiting factors. Unfortunately we did not have a soluble sample available to measure Nrtn expression in induced sputum from asthma patients.

Though we focus on airway macrophages, previous studies show that in mouse models of allergic airway disease, Nrtn inhibits the activation of DCs and CD4+ T cells, which 191 reduces the type 2 cytokine inflammatory response (Michel et al. 2011; Mauffray et al. 2015). Therefore, although Nrtn may play a role in allergic airway disease, this may not be through its effect on airway macrophage function.

6.3 Does Nrtn have an anti-inflammatory function on airway macrophages?

The GDNF family ligands belong to the wider TGFβ superfamily. As TGFβ is well characterised as an anti-inflammatory cytokine, many studies have investigated the potential of Nrtn to act as an anti-inflammatory mediator. As mentioned above, Nrtn decreases the inflammatory response in a mouse model of allergic asthma through a reduction in the levels of Th2 cytokines and recruitment of eosinophils to the airways (Michel et al. 2011). However, Nrtn is also implicated in inhibiting the expression of Th1 cytokines. For example, Nrtn-deficient mice display increased levels of IL-1β, TNFα and MMP9 in the corneal epithelium compared to wild type controls (Song et al. 2003). Furthermore, these mice also display an enhanced production of the chemokines MIP- 2 and KC by the corneal epithelial cells, which increases the infiltration of immune cells to the eye (Song et al. 2003). Vargas-Leal et al., also describe a role for Nrtn in regulating the production of the pro-inflammatory cytokine, TNF-α (Vargas-Leal et al. 2005). Nrtn decreases the levels of TNF-α in the supernatants of human PBMCs stimulated with a combination of LPS and IFNγ (Vargas-Leal et al. 2005). In addition, Mauffray et al., observed reduced levels of TNF-α and IL-6 in the supernatants of OVA- stimulated DCs and airway epithelial cells by Nrtn (Mauffray et al. 2015). Our data is in concurrence with these studies. We have shown that Nrtn decreases the level of the pro-inflammatory cytokines, TNF-α and IL-6, in LPS-stimulated GM-CSF-differentiated BMDMs. However, interestingly we did not observe this reduction in pro- inflammatory cytokines levels in LPS-stimulated M-CSF-differentiated BMDMs, human MDMs or human airway macrophages. Therefore, previous studies and our data suggest that Nrtn has anti-inflammatory effects on different cell types, but not on human airway macrophages. It is possible, however, that neurturin affects other macrophage responses including efferocytosis, migration and/or T cell priming.

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6.4 Does Nrtn have an effect on airway macrophages in viral infection?

Although GFRα2 is expressed by airway macrophages at steady state, the canonical co- receptor RET is undetectable in these cells. We show for the first time that the expression of RET in airway macrophages is specifically up-regulated by type I IFNs, and as such is potentially an interferon-stimulated gene that has not previously been reported. Furthermore, we demonstrate that the production and release of the respective ligand for GFRα2, Nrtn, is enhanced in airway epithelial cells following TLR activation. Therefore, we hypothesise that the detection of an invading pathogen by airway epithelial cells by TLRs induces the release of, not only cytokines, chemokines, anti-microbial peptides and interferons, but also the neurotrophic factor Nrtn. Our data suggests an important role for Nrtn in airway host defence against viral infection at a time when high levels of type I IFNs are present in the airways (Ivashkiv & Donlin 2014). Further supporting a role for the GDNF family in host defence, Ibiza et al., show that RET regulates the production of IL-22 from enteric ILC3s, which acts on epithelial cells to mediate host defence against infection in the gut (Ibiza et al. 2016). This study also describes the expression of Nrtn by glial cells, which is enhanced by activation with TLR2 and TLR4 agonists and the alarmins, IL-β and IL-33 (Ibiza et al. 2016). Moreover, Nrtn promotes anitviral activity by inhibiting viral replication in adult sensory neurons infected with herpes simplex virus (Yanez et al. 2017).

It is interesting to note that the levels of Nrtn in BAL fluid are enhanced in influenza- infected mice compared to naïve controls. This may represent active release or passive release from epithelium as a consequence of virus-induced cytopathology. Based on the work presented in this thesis we can collectively infer the following: 1) airway epithelial cells detect the influenza virus via their expression of TLRs, which stimulates the release of Nrtn. 2) TLR activation of airway epithelial cells and immune cells also triggers the secretion of type I IFNs, which bind to their receptor on airway macrophages. This leads to production of ISGs, including the RET receptor tyrosine kinase. Nrtn binds to the GFRα2 receptor on airway macrophages, which induces the formation of the GFRα2/Nrtn/RET complex and leads to RET activation. The consequence of this activation on airway macrophage function is still yet to be 193 identified. However, our data strongly suggests an important role for Nrtn on airway macrophages in host defence against viral infection (Figure 6.1).

Figure 6.1: The regulation of the GDNF family in airway viral infection. Airway epithelial cells recognise an invading virus and release neurturin. Type I IFNs are highly produced by a range of cells during viral infection and bind to their receptor, IFNAR, on airway macrophages. This initiates the production of the RET receptor. Neurturin binds to the GFRα2 receptor expressed on macrophages, which stimulates the recruitment of RET and its subsequent activation.

6.5 The implications of RET as an interferon-stimulated gene

Viral respiratory infections can cause severe disease in some young children and cause exacerbations in patients with chronic respiratory diseases, such as asthma and COPD (Matsumoto & Inoue 2014; Vissers et al. 2014). Therefore, our understanding of how viruses are effectively cleared from the airspaces is vital in treating those most at risk of infection. Alveolar macrophages are one of the first cells to respond to an invading pathogen within the airways and therefore, these cells have a major role in promoting the innate immune response to viruses and ultimately resolving the infection. The role of neurotrophic factors in the context of airway viral infection has not previously been examined. Thus, our data is the first to acknowledge a potential role of the GDNF

194 family in airway viral infection. Our data suggests that the neurotrophic factor receptor, RET, is a novel interferon-stimulated gene and therefore may be important in mediating the antiviral activities of macrophages. Manipulation of this pathway therefore may lead to more effective and efficient clearance of a virus.

Dysregulation of the type I IFNs is a known contributor of autoimmune diseases and cancer (Di Domizio & Cao 2013). This is relevant to our research as RET has been extensively studied in cancer. Activating mutations of RET cause the development of familial neuroendocrine tumours and medullary thyroid cancers (Jhiang 2000). Furthermore, neurotrophic factors are implicated in the autoimmune disease, multiple sclerosis, and have a role in not only promoting nerve regeneration and survival, but also in the ensuing inflammatory response (Lalive et al. 2008; Cao et al. 2011). Therefore, understanding the role of RET in autoimmune diseases and cancer, especially in the context of dysregulated type I IFN signalling, may lead to the development of novel therapeutics for these diseases.

6.6 Future Directions

The next questions to address in the continuation of this research are:

1) Does stimulation of human airway macrophages with type I IFNs induce the protein expression and translocation of GFRα2 and RET to the cell surface or is Nrtn also required for this process? 2) What is the effect of Nrtn stimulation on human airway macrophages in the presence of type I IFNs? 3) In an in vivo mouse model of airway viral infection, what is the effect of GFRα2 gene knockout in macrophages?

To investigate the first question, human airway macrophages could be stimulated with type I IFNs in the presence or absence of Nrtn and the localisation of GFRα2 and RET assessed by immunocytochemistry and immunofluorescence at different time points. The purpose of this technique would be to reveal the optimal time point at which to stimulate human airway macrophages with Nrtn after induction of RET by type I IFNs to observe the maximal effect of this neurotrophic factor. This would then pave the

195 way to addressing the second question, what is the function in human macrophages? The influence of neuturin on macrophages has so far eluded our attempts to define effects. This is likely due to the complex array of signals required to up-regulate all the components required for signalling. One possible hypothesis free approach to determine the effect of Nrtn on human airway macrophages would be to stimulate them with type I IFNs in the presence or absence of Nrtn and perform RNA- sequencing. This technique would allow for the comprehensive detection of genes up- and down-regulated by Nrtn stimulation and give an insight into the function of the GFRα2 and RET receptors on human airway macrophages.

The data presented in this thesis concentrates on the analysis of human macrophages in vitro. To propel this data forward, the function of neurturin on airway macrophages in vivo would need to be assessed. Our data suggests a role for neurturin, through its interaction with GFRα2 and RET on airway macrophages, in viral infection. Therefore, to test this hypothesis we would utlilize the GFRα2 floxed mice with a macrophage specific-cre, such as CX3CR1-cre mice as described before. Although these mice would display GFRα2 gene deletion in all macrophages and monocytes, in the absence of an airway macrophage specific marker, it is the closest possible model at this time that would enable studies on both tissue-resident airway macrophages and monocytes recruited to the airways during infection.

6.7 Conclusion

In conclusion, the data presented in this thesis has added to our knowledge of the role of neuronal factors within the immune system, specifically in the airways. We have defined the novel expression of the GDNF family receptors, GFRα2 and RET, on airway macrophages and elucidated a potential role for these neurotrophic factor receptors in airway viral infection. Furthermore, we have described the expression of the GFRα2 ligand, Nrtn, in airway epithelial cells, thereby elucidating a novel pathway of communication between airway macrophages and epithelial cells. Our data highlights the importance of the GDNF family in neuroimmune interactions and researching their role within the airways will enhance our understanding of how airway macrophages combat viral infection. This thesis has opened many additional avenues for investigation. Though the fold increase was less impressive, there were many more 196 neuronal factors unique to specific macrophages that were not taken forward in this thesis and should be examined in the future. Furthermore, though not the focus of this thesis, GFRα1 was observed on airway epithelial cells suggesting that signalling upon binding GDNF may influence their properties. Just as the epithelium regulates airway macrophage function, perhaps airway macrophages influence the epithelium via this neurotrophic receptor. Clearly, the regulatory cross talk between different cell types is complex and not yet fully appreciated. Furthermore, the function of a molecule on one cell type can be entirely different on another cell subset. Evolution retains those processes that promote survival, and so it would be interesting in the future to examine neurotrophic receptor expression and function on innate immunity in less sentient species.

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