Investigating Single-Gene Disorders of Childhood Infectious Disease

INVESTIGATING SINGLE-GENE DISORDERS OF CHILDHOOD INFECTIOUS DISEASE

Bayarchimeg Mashbat

A thesis submitted for the degree of

Doctor of Philosophy

Section of Paediatrics, Division of Infectious Diseases

Department of Medicine, Imperial College London

United Kingdom

October 2017

Abstract

A common feature of infectious diseases, including an infection with Neisseria meningitidis (Nm), is that only a small proportion of the individuals exposed to the same strain of the bacteria suffer from the clinical disease. Host genetics has long been considered to be an important determinant of both predisposition to and severity of outcome from invasive meningococcal disease (IMD). The human complement system is central to protection against IMD. It is well established that individuals with terminal or alternative complement deficiencies are predisposed to invasive, often recurrent meningococcal infections. However, the occurrence of these putative genetic deficiencies is rare, such that complement deficiencies account for less than 3 % of the disease cases. The current study sought to uncover novel genetic aetiologies of IMD, by employing WES and GWAS, in conjunction with molecular functional characterisation assays. Firstly, genetic analysis of six familial IMD exomes revealed a novel mutation in the SPLUNC1 gene. The encoding protein has been shown to play an important role in innate immune defence against a number of Gram-negative bacterial infections. The characterisation assays undertaken in this work suggest that the protein encoded by SPLUNC1 is also implicated with host innate immune defence against Nm infection, by providing protection against nasopharyngeal colonisation of a pathogenic Nm strain. The results further suggest that harbouring rare pathogenic mutations that impact the function of the encoding protein is associated with reduced host defence activities in the resulting protein, which in turn may possibly lead to increased susceptibility to IMD in the carriers. Furthermore, a large-scale GWAS was performed to define common polymorphisms underlying host susceptibility and severity of IMD, using 1236 individuals with confirmed disease and over 5000 controls. In this work, efforts were made to understand the biological plausibility of the genetic associations identified through the GWAS analysis.

Declaration of Originality

This thesis is submitted for the degree of Doctor of Philosophy to Imperial College London. The work presented here was undertaken in the Section of Paediatrics, Department of Medicine at Imperial College London. The research was co- supervised by Dr.Vanessa Sancho-Shimizu and Professor Michael Levin.

I declare that none of the research results offered in this thesis has been previously submitted by me for any other degree or qualifications at Imperial College London or any other university. I certify that all the material included in this thesis is my own and those from contributors have been appropriately acknowledged and referenced.

iii

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

Acknowledgements

I would like to thank my supervisors, Dr. Vanessa Sancho-Shimizu and Prof. Michael Levin for the opportunity they have given me to undertake this exciting project at Imperial College London. I would like to thank Dr. Sancho-Shimizu for her excellent knowledge, trust in me and endless encouragements through the ups and downs of my PhD. I would also like to thank Prof. Levin for his continuous support and providing me with the opportunity to develop my research skills through international collaborations. I am truly inspired by both these wonderful mentors for their unwavering passion and dedication to their daily work and their ambitious visions to help alleviate suffering from some of the most fatal diseases in the world.

I am also very grateful for the patients and their families who provided samples for this study. I would also like to thank the EUCLIDS Consortium members for their huge contributing to my development as a scientist through many scientific meetings, where I was given the opportunities to present my research and obtain valuable feedback. I would like to extend my thanks to Irene and Elli from EUCLIDS for offering me their friendship, sharing so many good times during our socials and being there for me when I needed their support. I would like to extend my thanks to my assessors, Dr. Simon Nadel and Dr. Anna Puel for taking diligent care to review this thesis.

I would like to thank everyone in Paediatrics and especially to those who provided support, guidance and mentorship throughout the years including Prof. P.Langford, Dr. M.Li, Dr .F.Bidmos, Dr. V.Wright, Dr. Y.Li, Dr. A.Cunnington, Dr. J.Herberg and Dr. C.Hoggart. I would also like to thank my work friends Liyana, Roberto, Shea, Stephanie, Beth, Tom, Myrsini, Evan and Rahmeen for their consolidation over coffee breaks, shared laughs, and attempted running clubs.

I am truly blessed to have the most wonderful friends Simon, Kate, Kasia, Pawel, Enkhjargal and David, whom I was always able to depend on in every way possible. Most importantly, I would like to thank my parents and my siblings, Saruul, Badamtsetseg and Amartaivan for their love and support from afar.

vii

Special thanks go to my aunty, Mashbileg who has always been my inspiration and taught me to excel in everything I do. Finally, I thank my partner, Karim for his encouragement for me to embark on this challenge and always helping me to live life to the full.

viii

To my love and my parents,

Table of Contents

Abstract ...... i

Declaration of Originality ...... iii

Acknowledgements ...... vii

Table of Contents ...... xi

Abbreviations ...... xvii

List of Figures ...... xxi

List of Tables ...... xxv

Chapter 1 ...... 1

Introduction ...... 2

1.1. Genetic basis of infectious diseases ...... 2

1.2. Genetic evidence from twin and adoptee studies ...... 3

1.3. Single gene defects underlying host susceptibility to infection ...... 3

1.4. Genomic approaches for identifying genetic cause of infectious diseases ...... 5

1.5. Whole exome sequencing for uncovering genetic basis of Mendelian disease ...... 6

1.6. Genome-wide association studies uncovering polymorphisms ...... 9

1.7. Neisseria meningitidis ...... 11

1.8. Nm colonisation and nasopharyngeal carriage ...... 12

1.9. Experimental models to study Nm colonisation and host-pathogen interactive biology 13

1.10. Invasive meningococcal disease ...... 14

1.11. Antibiotic treatments and vaccination ...... 15

1.12. Host immunity to Nm ...... 17 1.12.1. Innate immune response to Nm ...... 18

1.12.1.1. Mucosal barrier ...... 18 1.12.1.2. Recognition of Nm by the innate immune system...... 20 1.12.1.3. Complement cascade ...... 21 1.12.2. Humoral immune response against Nm ...... 23

1.13. Host genetics underlying susceptibility and severity of IMD ...... 24 1.13.1. Mendelian defects in IMD ...... 25 1.13.1.1. Complement deficiencies ...... 25 1.13.1.2. Properdin and MBL ...... 26 1.13.1.3. Innate immune signaling ...... 26 1.13.2. Polymorphisms associated with susceptibility and severity to IMD ...... 27 1.13.3. Complement regulatory proteins ...... 30 1.13.4. Genetic variants of acquired immunity ...... 31 1.13.5. Coagulation ...... 31 1.13.6. Inflammatory cytokine genes ...... 32

1.14. Summary ...... 32

1.15. Aims of the study ...... 33

Chapter 2 ...... 35

2. Materials and Methods ...... 36

2.1. Bacterial strains and growth conditions ...... 36

2.2. Heat-killing of Nm ...... 36

2.3. Antibiotics ...... 36

2.4. Genetic DNA manipulation techniques ...... 37 2.4.1. Genomic DNA and RNA extraction ...... 37 2.4.2. Primers used in this work ...... 38 2.4.3. Polymerase Chain réaction ...... 39 2.4.4. Quantitative RT- PCR ...... 39 2.4.5. Agarose gel electrophoresis...... 39 2.4.6. Restriction endonuclease ...... 40 2.4.7. DNA ligation ...... 40 2.4.8. Transformation...... 40 2.4.9. Isolation of plasmid DNA ...... 40 2.4.10. Genomic DNA sequencing ...... 40 2.4.11. Mutagenesis ...... 40

xii

2.4.12. Whole exome sequencing ...... 41

2.5. Human Tissue Culture ...... 43 2.5.1. Growth of human cell lines ...... 43 2.5.2. Air liquid interface epithelial cultures ...... 43 2.5.3. Transfection of epithelial cells ...... 44 2.5.4. Generation of human epithelial cells overexpressing SPLUNC1 variants ...... 44

2.6. Western blotting ...... 45 2.6.1. Bacterial cell lysate preparation ...... 45 2.6.2. Human cell lysate preparation ...... 45 2.6.3. Protein quantification ...... 46 2.6.4. SDS polyacrylamide gel electrophoresis ...... 46 2.6.5. SDS-PAGE gel staining ...... 46 2.6.6. Transfer ...... 47 2.6.7. Protein identification ...... 47

2.7. Production of recombinant SPLUNC1 proteins ...... 47 2.7.1. Expression and purification of recombinant SPLUNC1 variants ...... 47 2.7.2. Purification of rSPLUNC1 variants ...... 48

2.8. Growth of MC58 for the SPLUNC1 treatment ...... 48

2.9. Nm viability in presence of SPLUNC1 treatment ...... 48

2.10. Nm biofilm formation assay...... 49

2.11. Adhesion and invasion of airway epithelial cells ...... 49

2.12. LPS-binding assay ...... 50

2.13. Epithelial cell stimulation with LPS or heat killed Nm ...... 51

2.14. Cytokine measurements ...... 51

2.15. Taqman custom genotyping ...... 52

2.16. Genotyping of lncRNA SNP by sequencing ...... 52

2.17. Whole blood assay ...... 53

2.18. Calcium analysis by FACS...... 53

Chapter 3 ...... 55

3. WES to identify single genes underlying childhood IMD ...... 56

xiii

3.1. Background ...... 56

3.2. WES study cohort ...... 57

3.3. Bioinformatics and familial analysis approach ...... 58

3.4. Molecular genetic analysis and discovery of a novel missense heterozygous mutation in SPLUNC1 in familial IMD cases ...... 61

3.5. Targeted sequencing identifies G22E mutation in an unrelated IMD case ...... 69

3.6. Clinical presentation of IMD cases with SPLUNC1 mutation ...... 70

3.7. Deleteriousness of the candidate SPLUNC1 (c.65 G>A, p.G22E) mutation ...... 71

3.8. Sequence confirmation of the SPLUNC1 missense mutation ...... 72

3.9. Discussion ...... 74

Chapter 4 ...... 79

4. Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model...... 80

4.1. Generation of recombinant SPLUNC1 proteins ...... 80

4.2. Construct of SPLUNC1 allelic missense plasmid ...... 81

4.3. Expression and purification of rSPLUNC1 variants ...... 82

4.4. Investigation of the biological role of SPLUNC1 in IMD ...... 86 4.4.1. Bacterial survival assay ...... 86 4.4.2. Bacterial biofilm biomass assay ...... 89 4.4.3. Nm adhesion and invasion assay ...... 92 4.4.4. Discussion ...... 96

Chapter 5 ...... 101

5. Characterisation of G22E mutation using in vitro models of cultivated epithelial cells ...... 102

5.1. Overexpression of SPLUNC1 variants in epithelial cell lines: 16HBE14, CALU-3, HEK293 and CORL-23 ...... 103 5.1.1. Testing the overexpression of SPLUNC1 ...... 106 5.1.1.1. qPCR analysis of SPLUNC1 overexpression ...... 106 5.1.1.2. Western blot analyses of SPLUNC1 over expression ...... 108

xiv

5.2. Pro-inflammatory cytokine production after stimulation with LPS or HK Nm ...... 111

5.3. Creating stably transfected SPLUNC1+/+ cell lines ...... 116 5.3.1. Generation of lenti-SPLUNC1 constructs ...... 117 5.3.2. Transduction and selection of stable SPLUNC1 constructs ...... 119 5.3.3. Determination of stable SPLUNC1 expression ...... 119 5.3.3.1. Western blot analysis of SPLUNC1 overexpression ...... 119 5.3.3.2. Cytokine measurements of stable transfectants ...... 121

5.4. LPS binding assay ...... 123

5.5. Effect of G22E on anti-biofilm activity ...... 124

5.6. Effect of G22E on bacterial adhesion and invasion ...... 125

5.7. Molecular characterization and determining mechanisms underlying modified activity of the heterozygous missense G22E mutant ...... 128

5.8. Discussion ...... 130

Chapter 6 ...... 135

6. Investigating the role of GWAS candidate SNPs in IMD ...... 136

6.1. Genome-wide study participants ...... 136

6.2. GWAS analyses ...... 137

6.3. Candidate gene and SNPs ...... 140

6.4. Genotyping candidate SNPs in healthy controls ...... 144

6.5. Ex vivo blood assay to examine genotype dependent immune response to stimuli 145

6.6. Oxidative burst and neutrophil degranulation ...... 150

6.7. Calcium Flux measurement ...... 152

6.8. Discussion ...... 157

Chapter 7 ...... 161

7. Conclusion and future recommendations ...... 162

7.1. Overview ...... 162

7.2. Main findings ...... 164

7.3. Study limitations and future recommendations...... 166

7.4. Concluding remarks ...... 170

References ...... 171

xvi

Abbreviations

ALI Air liquid interface AMP Antimicrobial peptides aPTT Activated partial thromboplastin time ATCC American type culture collection BPI Bactericidal/permeability-increasing protein CADD combined annotation dependent depletion Cap- Capsule deficient CEACAM Carcinoembryonic antigen cell adhesion molecules CF Cystic fibrosis CFH Complement factor H CFHR3 Complement factor H-related protein 3 CRP C-reactive protein DC Dendritic cell DMEM Dulbecco’s modified eagle medium DNA Deoxyribonucleic acid DPBS Dulbecco’s phosphate buffer saline eCa2+ Extracellular Ca2+ ECACC European collection of authenticated cell cultures eDNA Extracellular deoxyribonucleic acid ELISA Enzyme-linked immunosorbent assay ENaC Epithelial sodium channel EUCLIDS European union life-threatening infectious diseases study EVS Exome variant server FBS Foatal bovine serum FcγR Fc receptors GAPDH Glyceraldehyde 3-phosphate dehydrogenase GDI Gene damage index

xvii

GMSPS Glasgow meningococcal septicaemia prognostic score HK Heat-killed HSE Herpes simplex encephalitis IgG Immunoglobulin G IMD Invasive meningococcal disease INR International normalized ratio IPTG Isopropyl-1-thio-D-galactopyranoside IRAK-4 IL-1 receptor associated kinase 4 LBP LPS-binding protein LD Linkage disequilibrium LncRNA Long intergenic non-protein coding RNA LOS Lipooligosaccharide LPS Lipopolysaccharide LTA Lipoteichoic acid LTRs Long terminal repeats MAC Membrane attack complex MAF Minor allele frequency MBL Mannose-binding lectin MRF Meningitis Research Foundation MSMD Mendelian susceptibility to mycobacterial diseases NadA Neisserial adhesion A NCAM Neuronal cell adhesion molecule NEA Non-essential amino acid solution NGS Next generation sequencing Nm Neisseria meningitidis OMP Outer membrane proteins OPD O-phenylenediamine di-hydrochloride PAI-1 Plasminogen activator inhibitor 1 PAMPs Pathogen-associated molecular patterns

xviii

PBMC Peripheral mononuclear cells PCR Polymerase chain reaction PID Primary immunodeficiency pilE- Pili deficient PMA Phorbol myristate acetate PRISM Paediatric risk of mortality score in MD PRRs Pattern recognition receptors PVDF Preactivated polyvinylidene fluoride RIPA Radioimmunoprecipitation assay ( SDS-PAGE Sodium dodecyl sulfate –polyacrylamide S-IgA Secretory immunoglobulin A TAE Tris acetate ethylenediaminutesetetraacetic Tfp Type IV pili TLR Toll-like receptor UNC93B Unc93 homologue B WCC White cell count WES Whole exome sequencing WGS Whole genome sequencing WHO World Health Organisation

xix

List of Figures

Figure 1.1: Diagram shows the diverse types of human genetic susceptibilities that confer predisposition to infectious diseases ...... 5

Figure 1.2: Outline of the whole exome sequencing process ...... 7

Figure 1.3: Approaches used for exome analysis for identifying causal variant 9

Figure 1.4: Outline for GWAS: cohort selection, quality control, analyses, replication and validation...... 10

Figure 1.5.Schematic representation of a cross-section of the meningococcal outer membrane ...... 13

Figure 1.6: Overview of human innate immune mechanisms involved in protection against Nm ...... 19

Figure 1.7: Overview of the three complement pathways that converge to result in the production of MAC and inflammatory response upon microbial invasion ...... 22

Figure 1.8.Comparison of genetic variants identified using WES versus GWAS approaches...... 25

Figure 3.1.WES analysis pipeline used in this study ...... 60

Figure 3.2. Pedigree segregation of two IMD siblings ...... 62

Figure 3.3: Schematic diagram of the SPLUNC1 protein ...... 68

Figure 3.4: 3D structure of SPLUNC1 ...... 68

Figure 3.5: Pedigree of 3rd affected unrelated case with missense heterozygous SPLUNC1 (c.65 G > A, p.G22E) mutation ...... 70

Figure 3.6.Multiple sequence alignment of a section of SPLUNC1 and primate orthologues ...... 72

xxi

Figure 3.7. CADD scores for rare SPLUNC1 variants versus MAF results from ExAC database ...... 72

Figure 3.8: Gel image of SPLUNC1 exon 2 amplicon ...... 73

Figure 3.9: Sanger sequence confirmation of SPLUNC1 (c.65 G > A, p.G22E) mutation in three IMD patients and a control sample ...... 74

Figure 4.1: Sequence confirmation of successfully inserted two independent point mutations in pSPLUNC1-WT plasmid...... 82

Figure 4.2: Amplification of SPLUNC1 allelic variants using directional cloning primers cloning-f and cloning-r. G22E allelic mutant was analysed in lane 2 ...... 82

Figure 4.3: Recombinant SPLUNC1 expression. Expression of pET-SPLUNC1- WT and pET-SPLUNC1-G22E ...... 83

Figure 4.4: Purification of rSPLUNC1 variants with nickel-affinity columns .... 85

Figure 4.5: Identification of purified rSPLUNC1 protein ...... 85

Figure 4.6: Wild type SPLUNC1 is not bactericidal against Nm ...... 88

Figure 4.7: Wild type and mutant MC58 growth curve ...... 90

Figure 4.8: rSPLUNC1 inhibits Nm biofilm formation on polystyrene surface. 91

Figure 4.9: Human bronchial epithelial cell line, 16HBE14 does not endogenously express SPLUNC1...... 94

Figure 4.10: rSPLUNC1 inhibits adhesion and invasion of human epithelial cells by Nm...... 95

Figure 5.1: Optimisation of transient transfection in epithelial cell lines, demonstrated using 16HBE14...... 105

Figure 5.2: Overexpression of SPLUNC1-WT and SPLUNC1-G22E allelic mutant in in human epithelial cells analysed by qPCR ...... 107

xxii

Figure 5.3: Overexpression of SPLUNC-WT and SPLUNC1–G22E allelic mutant in human epithelial cell lines analysed by western blotting...... 110

Figure 5.4: Comparing expression of heterozygous, wild type SPLUNC1 and G22E mutant ...... 111

Figure 5.5: IL-6 response to LPS and HK Nm in cells expressing SPLUNC1 variants ...... 112

Figure 5.6: IL-8 cytokine response to LPS and HK Nm in cells expressing SPLUNC1 allelic variants ...... 115

Figure 5.7.IL-8 production in epithelial cells transfected with various empty plasmids ...... 116

Figure 5.8: Schematic diagram of the sub-cloning of cDNA SPLUNC1 allelic variant clones into pEmpty-lenti vector ...... 118

Figure 5.9: Expression of SPLUNC1 from stably transduced 16HBE14 and CALU-3 cells by western blotting ...... 120

Figure 5.10: Development of tight junctions of CALU-3 and 16HBE14 monolayers ...... 121

Figure 5.11: Inflammatory cytokine response in stably transfected SPLUNC1 expressing cells after stimulation with TLR-4 agonists ...... 122

Figure 5.12: LPS binding ability of SPLUNC1 variants ...... 124

Figure 5.13: SPLUNC1 inhibits Nm biofilm formation ...... 125

Figure 5.14: The effect of the G22E mutant on Nm adhesion and invasion of human epithelial 16HBE14 cells...... 127

Figure 5.15: The mutant G22E SPLUNC1 allele impedes inhibition of Nm adherence and invasion by the wild type SPLUNC1 allele ...... 129

Figure 6.1: Position of LncRNA gene, LL22NC03-86D4.1 denoted by blue shading on X-axis plotted against the combined P value on the Y-axis. . 139

xxiii

Figure 6.2: Diverse mechanisms employed by lncRNAs in regulation of genes and proteins expression and functions...... 141

Figure 6.3: Details of lncRNA SNPs significantly associated with WCC ...... 143

Figure 6.4: PCR amplified product of polymorphism, rs145723387 flanking region...... 145

Figure 6.5: Electropherogram showing the three allelic genotypes of lncRNA SNP (rs145723387)...... 145

Figure 6.6: IL-6 cytokine kinetics ...... 146

Figure 6.7: Dose dependent response of the induction of IL-6 cytokine in whole blood...... 148

Figure 6.8: Evaluation of genotype dependent cytokine response in supernatants of whole blood...... 150

Figure 6.9: FACS data representative of neutrophil and monocyte oxidative burst and degranulation ...... 151

Figure 6.10: Evolutionary conservation of lncRNA SNP rs145723387 among primates...... 153

Figure 6.11: lncRNA SNP (rs73155936) genotype impacts calcium mobilisation upon stimulation with ionomycin...... 155

Figure 6.12: The effect of rs73155936 genotype is even more exaggerated with in the presence of extracellular calcium ...... 156

xxiv

List of Tables

Table 1.1. Genetic polymorphisms conferring increased susceptibility or severity of IMD ...... 27 Table 2.1. Bacterial strains used in this study ...... 37 Table 2.2. Primer pairs designed to amplify a full length SPLUNC1 ...... 38 Table 2.3.Mutagenesis primer pairs designed for this work...... 39 Table 2.4. List of plasmids used in this study...... 42 Table 3.1. Summary statistics of the shared rare variants in related IMD siblings described in this study...... 61 Table 3.2. Top 15 rare variants shared between the two IMD siblings (P1 and P2)...... 64 Table 6.1. IMD severity endpoints broken down by the number of cases and controls from individual cohorts...... 138 Table 6.2. Clinical markers of invasive meningococcal disease utilised for GWAS analyses broken down by each case cohort ...... 131 Table 6.3. Individual and combined P values of LncRNA SNPs in the three cohorts ...... 139

xxv

xxvi

Chapter 1

I – Introduction - 2 -

Introduction

1.1. Genetic basis of infectious diseases

Infectious diseases continue to pose a considerable threat to human well-being and remains among the leading cause of mortality and morbidity worldwide. According to the World Health Organisation report, death from infectious diseases accounted for approximately 4.6 million in the year 2015 (WHO, 2018). The considerable difference in clinical outcome between individuals and populations exposed to the same pathogen can be attributable to the complex relationship between genetic variability in both the host and infecting microbe, as well as non-genetic environmental factors. The evolving genetic variability in human immunity to overcome infectious diseases has been heavily shaped by the selective pressure for survival (Lederberg, 1999). This adaptability to produce an effective immune response against diverse pathogens has resulted in marked diversity and in the greatest number of immune genes constituting the human genome (Murphy, 1993). The most significant example of human susceptibility to infectious disease is located within the region spanning the human leukocyte antigen (HLA), where the allelic heterozygous genotype of class I HLA determines the HIV progression of disease status or even risk of death (Carrington et al., 1999). In contrast, the homozygous allelic genotype for HLA has been reported to confer susceptibility to infection in genetically homogenous populations (Black et al., 1995).

Over the past 70 years, it has become apparent that host genetic factors play an important role in determining susceptibility to or outcome of a given infection in humans. It is well described that infections caused by the same infectious agent can produce diverse effects in different individuals, that these differences can be best assessed when the same strain of organism spontaneously infects previously

I – Introduction - 3 - unexposed individuals at the same time (Cooke and Hill, 2001). In the past, therapeutic strategies to treat syphilis using Plasmodium falciparum, a causative agent for malaria resulted in variable inter-individual immune responses among the patients (James et al., 1932). In concordance, likewise results have been observed in vaccine trials of malaria, where healthy volunteers produce diverse immune responses to the same antigen.

1.2. Genetic evidence from twin and adoptee studies

Conventionally, twin and adoptee studies have been effectively used to decipher the genetic determinants of susceptibility to human infectious diseases. Twin studies are often based on the assumption that identical twins are envisaged to have higher disease concordance level compared with non-identical twins, if an infectious disease has a genetic basis rather than an environmental influence. This prediction has shown to be evident in various chronic disorders with low infection rates, such as leprosy, poliomyelitis and hepatitis B infections (Cooke and Hill, 2001). These findings suggest that the genetic variability between individuals plays an important role in susceptibility to infectious diseases. One study investigated the causes of death from infection, in a large set of Danish families, comparing the risk of death in adopted children versus their biological or adoptive parents (Petersen et al., 2002). The risk of an adoptee dying from infection was six times greater when the biological parent died earlier from infection, but there was no correlation with the premature death of an adoptive parent, suggesting the genetics rather than environmental factors was the principal determinant of risk of death from infectious disease. Taken together these observations indicate that heritability of genetic defect underlies predisposition to infectious disease, as well as a determinant of severe clinical outcome.

1.3. Single gene defects underlying host susceptibility to infection

Classic immunodeficiency that follows the Mendelian inheritance pattern has been typically associated with multiple and recurrent infections caused by multiple pathogens (Picard et al., 2006) e.g. severe combined immunodeficiency. Previously, single gene mutations in a specific pathway associated genes with moderate clinical

I – Introduction - 4 - penetrance were identified to underlying severe infectious diseases of childhood such as IL-12/IFN-γ pathway and atypical mycobacterial disease (Alcaïs et al., 2010). More recently, single gene defects associated with increased susceptibility to a specific infection type in otherwise healthy individuals are being described (Casanova and Abel, 2007). These mutations provide insight into the genes and pathways controlling the resistance and susceptibility of a given infection. Patients with properdin deficiencies or autosomal recessive defects in the terminal components (C5 – C9) of the complement system, responsible for formation of membrane attack complex for bacterial clearance, is widely considered to confer susceptibility to IMD (Fredrikson et al., 1996; Würzner et al., 1992). Patients with IL-1 receptor associated kinase 4 (IRAK-4) and MyD88 deficiencies confer predisposition to invasive pneumococcal disease (Ku et al., 2007; von Bernuth et al., 2008). The best described genetic aetiology of single gene defect of IFN-γ receptor 1 deficiency causes Mendelian susceptibility to mycobacterial diseases (MSMD) (Jouanguy et al., 1996; Newport et al., 1996).

Collectively, the examples given above only represent a single type of genetic susceptibility to infectious diseases out of the wide array of different categories, whereby genetic defects of a single gene or small number of genes confer predisposition to a narrow variety of pathogens. Other examples of the diversity in this phenomenon are illustrated in Figure 1.1, where the most distinguished genetic infection models have been highlighted according to the factors that determine an individual’s susceptibility to an infection, such as the number of pathogens to which the individual may be susceptible to, and the contributing impact exhibited by each gene. These well-described examples of genetic susceptibilities underlying human infectious diseases include a) HSE, a single gene predisposing to infection by a specific pathogen, b) SCID associated infections, a single gene predisposing to an array of different infections, c) leprosy, a modest collection of genes underlying infection caused by a specific microorganism, d) HLA associated infections, allelic variants underlying a collection of infections.

I – Introduction - 5 -

Figure 1.1: Diagram shows the diverse types of human genetic susceptibilities that confer predisposition to infectious diseases. Illustration highlights the seminal findings that defined the different spectrum of genetic susceptibilities to infectious diseases. Adapted from Alcaïs et al. (2009).

1.4. Genomic approaches for identifying genetic cause of infectious diseases

While single gene defects associated with increased susceptibility to a specific type of infection highlight the critical immune response genes and pathways, they are very rare and do not explain susceptibility to infectious disease at a population level. A large proportion of human infectious diseases are ‘complex’ traits, meaning heritability of genetic variants has a small contribution to the overall susceptibility risk to infection, and other factors such as environmental or the ever evolving microbial genome are in interplay (Chapman and Hill, 2012). Early efforts to identify genetic susceptibility to underlying infectious diseases employed candidate-gene approach and genome–wide linkage analysis. Candidate-gene approaches relied on investigation of select genes, which were suspected for their biological relevance and plausibility to an infection, for comparison of polymorphism frequencies between unrelated cases and controls. While this approach led to a select number of valid

I – Introduction - 6 - associations, many of the findings had poor replication in independent cohorts due to a number of reasons, such as inadequate cohort sizes and erroneously selected genes based on the somewhat limited knowledge of the disease (Brouwer et al., 2010; Hill, 2006).

Genome-wide linkage studies involved examination of affected sibling pairs to identify genetic loci associated with susceptibility to an infection. The main limitation of this type of approach was not being able to enrol adequate numbers of affected cases and having enough power for subsequent analysis. Despite these limitations, linkage approaches successfully identified disease related loci, such as leprosy (Cooke and Hill, 2001; Misch et al., 2010). With the growing technological advancement of variant calling and analytical techniques, whole genome/exome sequencing and genome-wide association studies are widely utilised and provide the possibility to uncover many more genetic defects underlying inherited cases, for which there is no genetic diagnosis for individual’s illness. The identification and molecular characterisation of the genetic variations underlying susceptibility and severity of infection should lead to better insight into the disease pathogenesis and possibly development of targeted therapies or improved preventative interventions.

1.5. Whole exome sequencing for uncovering genetic basis of Mendelian disease

As of 2015, next generation sequencing (NGS) technologies have become a widely used tool for elucidation of the genetic basis of Mendelian defects, where the limitations presented in former variant identification strategies have been successfully overcome. The strategy of combining targeted capture and massively parallel DNA sequencing techniques have allowed advancement in cost effective approach for sequencing of all protein coding regions of the genome, constituting less than 2 % of the genome, referred to as whole exome sequencing (WES) (Mamanova et al., 2010). Despite lacking the ability to capture variants from noncoding regions of the genome, WES in comparison to whole genome sequencing (WGS) has numerous advantages.

For instance, cost effectiveness per genome basis, sequencing covers regions enriched for pathogenic variants (more than 85 % of all known causative genes are

I – Introduction - 7 - located in the exome) and do not require cumbersome analytical tools for variant processing (Bamshad et al., 2011). The basic stepwise principle of WES is shown in Figure 1.2. Briefly, it begins with sample preparation, where the DNA samples are randomly sheared to produce fragments of around 250 bp and the fragment ends are repaired, followed by ligation of adaptors on the ends. To enrich the targeted library, the complementary sequences on the fragment linked adaptors are hybridised to biotinylated nucleic-acid based baits (DNA or RNA depending on the platform used) and captured by streptavidin-based tools. Finally, the quality of the enriched library is checked and the target library amplified using massively parallel sequencing, followed by data analysis (Rabbani et al., 2012).

Figure 1.2: Outline of the whole exome sequencing process. Adapted from Bamshad et al. (2011).

Different strategies are exercised for identifying novel causal variants for Mendelian or complex traits, based on the clinical and phenotypic information of the exome samples. Some of these approaches for identifying causal variants are demonstrated in Figure 1.3. One of the biggest challenges of WES is filtering out the causal variant from all other non-pathogenic variants. On average, exome sequencing results in 20,000 – 30,000 variants per exome and around 95 % are common non-pathogenic variants (Bamshad et al., 2011). Filtering for causal variants depends on many factors, such as phenotypically associated allelic segregation of the pedigree,

I – Introduction - 8 - ethnicity of the affected individuals and locus heterogeneity of the trait. One approach is to annotate variants by filtering out synonymous SNPs and reported pathogenic variants using demographically matched control samples, as well as public databases such as dbSNP (Sherry et al., 2001), Exome Variant Server ((EVS) http://evs.gs.washington.edu/EVS/) gnomAD (http://gnomad.broadinstitute.org), and 1000 genomes (Abecasis et al., 2010). This type of filtering strategy applied to a small number of unrelated affected cases has shown to effectively deduce the large number of identified variants to a select plausible candidate/s, and this same quality makes WES a far superior tool for identifying rare genetic variants relative to alternative genomic approaches (Ng et al., 2010).

In addition, candidate alleles with pedigree details can be restricted to search for variants with minor allele frequency (MAF) of less than 1 %. Further stratification methods include prioritising the candidate list based on the predicted functional effect on the encoding protein such as frameshifts, stop codons, alterations of splice sites and missense. The biological relevance and existing disease associations can further facilitate narrowing down the possible causal variant list. Moreover, incorporating the mode of inheritance can increase the power to sequence less number of individuals to obtain meaningful results. For example, sequencing two phenotypically identical affected first-degree cousins (who share approximately one eighth of their genome) can limit the search to a shared haplotype region, in turn reducing the number of candidate genes or variants (Bamshad et al., 2011).

I – Introduction - 9 -

Figure 1.3: Approaches used for exome analysis for identifying causal variant. A) Parents and affected child trios used to screen for de novo variants. B) Multiple affected individuals (shaded) from family pedigree used to screen for causal variant shared among affected members. C) Individuals with an extreme spectrum of the disease phenotype used for screening rare causal variants. D) Unrelated individuals with the same phenotype used for screening novel causal variants. Adapted from Bamshad et al. (2011).

1.6. Genome-wide association studies uncovering polymorphisms

The genetic basis for susceptibility or resistance to infectious diseases may arise from Mendelian defects, with high clinical penetrance, or rather, from common SNPs making a moderate contribution to the overall risk (Cooke and Hill, 2001). In the latter case, before the development of NGS tools, candidate gene approach and linkage analysis were used to disentangle genetic traits associated with common diseases. While these genomic approaches successfully identified a select number of associations, their candidate gene focused strategy limited their power of discovery for novel candidates (Chapman and Hill, 2012). However, the publication of a complete human genome in 2003, followed by the HapMap / 1000 Genomes project (mapping of common human SNPs), and high-throughput genotyping technologies gave rise to the development of GWAS, permitting discovery of novel SNPs associated with disease phenotypes. The human genome is made up of 3

I – Introduction - 10 - billion base pairs and approximately 10 million SNPs are predicted to be mutable to a population-wide significance (Panagiotou et al., 2012). The basic principle of this approach compares the allelic frequency of common SNPs across the human genome between cohorts of phenotypically selected individuals (affected) and control samples. The HapMap project displays information regarding the association between SNPs. Thus GWAS generated data can be used to identify the causal variants directly or through other SNPs that are highly correlated with the causal variant using imputation (Xavier and Rioux, 2008).

Figure 1.4: Outline for GWAS: cohort selection, quality control, analyses, replication and validation.

The multi-step processes involved in GWAS are outlined in Figure 1.4. To eliminate false-positive variants, it is considered crucial to include a sufficient number of cohorts, consisting of clearly defined affected cases, as well as appropriately

I – Introduction - 11 - matched control samples, and conduct a meticulous quality check of the genotyping data before analyses (Hirschhorn and Daly, 2005; Wang et al., 2005). In theory, it is hoped that the most significant 50 SNPs found to be associated with the test parameters will lead to the identification of novel genes that confer disease risk. However, in practice, it has proved more difficult than anticipated. To overcome these analytical challenges alternative strategies have been developed, such as pathway based or network analyses, which incorporate the biological plausibility of the genes into the analyses (Wang et al., 2007). In any case, the findings of GWAS require replication in an independent dataset. The results should be replicated and the phenotype should stay consistent between the studies (Chanock et al., 2007). One of the most successful GWAS, which included 475 meningococcal disease cases and 4703 population controls all from the UK (Wellcome Trust Case Control Consortium), identified 79 highly significant SNPs with genome wide association, with P < 1 x 10-4 (Davila et al., 2010). The findings were validated in two independent cohorts, from South and West European MD cases, involving 968 and 1376 controls. Combined analyses revealed 2 highly significant SNPs in complement factor H (CFH) and 3 others in close range CFH-related protein 3 (CFHR3). In each case, the minor allele was found to be protective against MD compared with wild type allele. This finding was seminal evidence that genetic variants in the complement pathway confer susceptibility to MD in the general population, in addition to the described Mendelian complement defects.

1.7. Neisseria meningitidis

Nm is a human specific commensal Gram-negative bacterium that specifically colonises the human nasopharynx, and is a major cause of life-threatening childhood meningitis and septicaemia (Virji, 2009). It exists as an aerobic diplococcus and humans serve as the sole host for the meningococcus (Stephens, 2009). This commensal bacterium is transmitted from one host to another by airborne droplets or saliva, by forming a temporary attachment to non-ciliated epithelial cells of the upper respiratory tract, where it establishes colonisation (Serruto et al., 2012; Yazdankhah and Caugant, 2004). Apart from colonising the oropharyngeal mucosal surfaces, it has known to reside sporadically in the mucosal surfaces of the rectum and genitourinary tract (Faur et al., 1975).

I – Introduction - 12 -

Meningococcus has successfully developed a number of virulence factors (Figure 1.5) for host evasion including, the polysaccharide capsule, outer membrane embedded proteins (Por-A and -B), and endotoxin (lipooligosaccharide; LOS) (Virji, 2009). Invasive meningococcal strains express polysaccharide capsule, which prevents opsonisation and phagocytosis by the host immune cells and plays a crucial role in Nm survival in the bloodstream (Serruto et al., 2012). The structural architecture and immunogenicity of the capsular polysaccharide on the outer surface of Nm forms the basis of 13 different serogroups. The majority of invasive disease is accountable to serogroups A, B, C, W, X and Y (Bakir et al., 2001). The meningococcus lacks motility and forms attachment to host non-ciliated epithelial cells, using its surface membrane adhesion proteins including pili, Opa and Opc (Pathan et al., 2003). Other virulence factors include expression of IgA proteases, processes that inhibit ciliary function and the ability of the bacterium to modify its surface antigens, such as endotoxin and proteins (Achtman, 1995).

1.8. Nm colonisation and nasopharyngeal carriage

Colonisation of the human nasopharyngeal mucosal membranes by meningococci is the first step of the host-bacterium interaction, often leading to asymptomatic carrier state in most individuals (Broome, 1986). The carriage state is reported to last from anywhere between seven days or up to six months or more (Jones et al., 1998). The underlying variables for prolonged carriage are not well understood, but social and genetic factors have been associated to confer increased susceptibility to meningococcal carriage (MacLennan et al., 2006).

Lappann et al. (2013) have postulated that prolonged mucosal colonisation of the host is dictated by the ability of disease-causing pathogenic clones, such as CC- 41/44 or CC-32 to utilise extracellular DNA (eDNA) during biofilm formation, thus resulting in ‘settler’ status. In contrast, meningococci with ‘spreader’ status are not dependent on eDNA utilisation and form instable biofilms, allowing an enhanced opportunity for transmission from one host to another. Furthermore, the virulence mechanism used for tight adhesion to the host nasopharynx membrane through stable biofilm formation is correlated with increased resistance to antimicrobial

I – Introduction - 13 - agents and prevention of host immune activation, leading to the prolonged mucosal colonisation of the host (Hey et al., 2013).

Figure 1.5.Schematic representation of a cross-section of the meningococcal outer membrane. Reproduced by permission from Macmillan Publishers Ltd: [Nature Reviews, Microbiology] (Virji et al. 2009), copyright (2017).

1.9. Experimental models to study Nm colonisation and host- pathogen interactive biology

Nm is adapted to specifically colonise the human host and it’s only known reservoir is the nasopharyngeal mucosa, which consists of diverse combination of cell types. This human specific nature of Nm presents a major challenge for development of relevant experiments with animal models to study the meningococcal colonisation and pathogenesis. Monolayer of human epithelial cell lines, nasopharyngeal explants and cultured tonsillar explants provide relevant model systems to study the host- meningococcal interaction (Rayner et al., 1995; Read et al., 1995), however, each one presents some advantages and disadvantages.

I – Introduction - 14 -

The human organ culture model with nasopharyngeal explants most closely resembles the in vivo environment, as it constitutes an intact epithelial cellular barrier, comprised of ciliated and non-ciliated cellular subtypes joined together by tight junction and mucin secreted by goblet cells covers the outer surfaces (Wiszniewski et al., 2006). The inaccessibility in obtaining these tissues, inter- variability between different hosts and the absence of intact cellular or complement mediated responses are some of the disadvantages (Rayner et al., 1995; Read et al., 1995; Stephens, 1989; Townsend et al., 2002). In addition, culturing these explants is technically challenging, their viability is not sustained and appropriate specimens are not readily available, making it costly and time consuming for experimental studies (Exley et al., 2009; Read et al., 1995). Nevertheless, these culture models have provided important insights into the mechanisms of meningococcal colonisation of the human nasopharynx and subsequent infection.

The challenges presented above by the organ culture model have necessitated the development of alternative models to investigate the colonisation and related aspects of the meningococcal infection. In the absence of suitable animal model, in vitro biofilms grown on the surface of plastic (abiotic model) (Lappann et al., 2006; O'Dwyer et al., 2009; Yi et al., 2004) or microcolonies formed on the surface of monolayer of epithelial cells (Grifantini et al., 2002; Lappann et al., 2010; Neil et al., 2009; O'Dwyer et al., 2009; Yi et al., 2004) are increasingly used to model the meningococcal colonisation state and study the host-pathogen interaction. The use of abiotic model system allows controlled experimental set up, in which to test a large number of variables such as different experimental treatments at the same time. In contrast, the microcolonies formed on epithelial cells closely mimic the physiological conditions of host-meningococcal interaction; however, the variability in cell type used may present problems such as expression of appropriate cell- associated receptors essential for meningococcal attachment (Arenas and Tommassen, 2017).

1.10. Invasive meningococcal disease

It is only in a subset of colonised individuals that, meningococci invade the oropharyngeal epithelial surfaces into the bloodstream and subsequently cross the

I – Introduction - 15 - blood-brain barrier, causing severe meningitis and/or septicaemia, with often lethal consequences due to the septic shock (Caugant, 2008). Occasionally, an incorrect diagnosis can arise from the confusion of early symptoms of IMD resembling that of viral or other respiratory infections. This could lead to delay in critical diagnosis and a missed opportunity to save lives. Onset of IMD can be very rapid in the susceptible individuals, in the short time between presentation of symptoms (fever, headache, vomiting, loss of consciousness, purpuric skin lesions, photophobia and neck stiffness), and risk of death within twenty-four hours, if an appropriate treatment is not provided (Thompson et al., 2006).

The condition for an invasive disease to occur is dependent on various host specific, social or environmental factors. These include colonisation with a pathogenic meningococcal strain, immunodeficiency of the host, preceding respiratory viral infection and social contacts (Serruto et al., 2012). The peak carriage rate of meningococci reaches up to 35% among adolescents from 15 – 25 years of age and in social conditions in which large groups of people gather together contributes to increased transmission, such as in university dormitories and military camps (Thompson et al., 2006).

The highest risk of IMD occurs in children less than 3 years of age, followed by a second peak in adolescents. The incidence of IMD varies widely across the globe and is serogroup dependent. Serogroups B and C predominantly cause IMD in < 2 cases per 100,000 in Europe and North America. Whereas, recurrent seasonal epidemics caused by serogroup A may affect as many as 1 - 100 cases per 10,000 in the African meningitis belt. The morbidity and mortality rate of IMD due to Nm is substantial and case fatality of the disease is 10 % in the developed countries (Pelton, 2016). The survivors will often experience reduced quality of life and up to 19% of the individuals continue to suffer from lifelong debilitating sequelae, including loss of hearing, amputation and neurological damage (Pace and Pollard, 2012).

1.11. Antibiotic treatments and vaccination

Early recognition of symptoms and prompt administration of parenteral antibiotic therapy are critical in reducing the mortality rate of IMD, which may result in fatality risk of up to 50% if timely treatment is not provided (Nadel, 2016). The use of

I – Introduction - 16 - antibiotics has seen a substantial decrease in risk of death from IMD compared with the pre-antibiotics era, approximately 85 % down to the current reported rate of 10 % (Macneil, 2011). Following an acute diagnosis of IMD in individuals, the preferred treatments are with cefotaxime, ceftriaxone and penicillin therapy. In resource rich settings, where penicillin-resistance is the exception rather than the rule, the initial treatment of benzylpenicillin should be followed up with cefotaxime, ceftriaxone and rifampin to clear mucosal colonisation and reduce the risk of transmission to unaffected family members (Macneil, 2011; Nadel, 2016). Use of chloramphenicol and meropenem has also been reported as antibiotic therapy (Nadel, 2016). Due to the difficulty in early diagnosis and the fatality risk associated with misdiagnosis, the best management approach in reducing mortality from IMD is through mass vaccination against the pathogen.

Invasive disease is reported to occur in patients lacking strain specific bactericidal antibodies, the foremost preventative approach is to induce immunogenic memory through the use of vaccines in susceptible individuals (van Deuren et al., 2000). Since the 1970s, Nm polysaccharide capsule known for its highly immunogenic properties, has been widely utilised as the preferred vaccine target against serogroups A, C, Y and W (Gotschlich et al., 1969; Griffiss et al., 1981). These unconjugated vaccines were safe and provided effective protection in older age groups, including individuals with complement deficiencies. Nevertheless, due to their unconjugated nature, they were inefficient at producing immunity in age groups less than 2 years of age and were not able to offer lasting protection against the pathogen (Caugant, 2008). The strategy of conjugating polysaccharide to carrier proteins (most successful being diphtheria toxoid, DT, CRM197 and tetanus toxoid, TT) has markedly boosted efficacy of vaccines against these serogroups, including in young infants as a consequence of effective short-term protection and consequent decrease in the acquisition of virulent strains due to herd immunity (Bijlsma et al., 2014).

This new generation of vaccines have shown to reduce carriage rate of virulent strains, belonging to the clonal complexes ST-11 and ST-8 including in unvaccinated population through herd immunity (Bijlsma et al., 2014). Monovalent conjugated vaccine against Nm serogroup C has proved effective in reducing burden of IMD in

I – Introduction - 17 - industrialised countries, including in the UK, resulting in a reduction of incidence by > 90 % since its introduction in 1998 (Trotter et al., 2004). However, there have been reports of increased incidence of IMD caused by serogroup Y across Europe, in recent years (Whittaker, 2007). The latest licensed vaccines for industrialised countries incorporates quadrivalent ACYW conjugated to one of the three effective carrier proteins mentioned above, whereas, cost-effective monovalent conjugate vaccine against serogroup A meningococcus, MenAfriVac is being used to elevate the epidemic burden of IMD in the African meningitis belt (LaForce and Okwo-Bele, 2011).

Until recently, a capsule based vaccine against serogroup B proved difficult due to the structural resemblance of the B polysaccharide to human neuronal cell adhesion molecule (NCAM) posing a risk of autoimmunity (Pathan et al., 2003). Outer membrane proteins (OMPs) have been targeted as an alternative antigen for producing the multicomponent vaccine, 4CMenB, Bexsero, and the UK became the first country to introduce it into the national immunisation programme. The initial surveillance analyses suggest the vaccine is effective; while, continued surveillance will help determine the long-term effects among the vaccinated group (Parikh et al., 2016).

1.12. Host immunity to Nm

The reasons why specific strains of meningococcus cause severe disease in only a small proportion of the exposed individuals is not well understood. The capability of host evasion mechanisms and high rate of replication of Nm in the blood are important for IMD to occur (Pathan et al., 2003). Both the innate and humoral arms of the human immune system together play an essential role in protection and elimination of the meningococcus during colonisation and consequent invasive disease. A number of seminal epidemiological studies have established that acquired immunity through the development of serum bactericidal antibody against the invading strain is the most effective host defence mechanism (Goldschneider et al., 1969a, b). These studies provided evidence for the age-related incidence of disease being inversely correlated with the acquisition of humoral antibodies in the serum against meningococci. It was shown that the highest risk of IMD occurs in

I – Introduction - 18 - infants around six-months to two-years of age, correlating with the period when the cross placental transfer of humoral antibodies are at their lowest (Goldschneider et al., 1969a). Although the main immune protection is provided by circulating antibodies, the existing evidence suggest that the innate immune mechanisms are equally important in protecting young children, especially in the period between colonisation of the nasopharynx and acquisition of protective immunity (Pathan et al., 2003).

1.12.1. Innate immune response to Nm

1.12.1.1. Mucosal barrier

The mucosal barrier in the respiratory tract provides the first line of immune defence against meningococcal infection (Figure 1.6). The mucosal epithelium of the nasopharynx mostly consists of pseudostratified, columnar and mucin producing cells with ciliary protrusions. Nasopharyngeal epithelial surfaces present hindrance to neisserial colonisation of the nasopharynx through mechanical and physical means including, ciliary beating, rapid movement of secretory fluid, and encasing of glycocalyx on the outer membrane (Read et al., 1991). It has been reported that virulence factors of Nm promote adherence to host nasopharyngeal epithelium through regions with non-ciliated epithelial cells (Yazdankhah and Caugant, 2004). Mucus consists of complex mixtures of globular proteins, polysaccharides, antimicrobial peptides (AMPs) amongst other secreted molecules. The innate immune secretions in the respiratory airways include a mixture of mucin enlaced with lysozymes, lactoferrin, interferons, peroxidases and proteases to mount inflammatory responses (Laver et al., 2015).

This complex mixture of mucosal secretions together plays an important role in modulation of rapid innate immune responses, while facilitating mediation of adaptive responses against the invading pathogen. For instance, β-defensins and cathelicidin LL-37 are soluble AMPs that are postulated to operate through direct binding to LPS on the meningococcal outer membrane and disrupt membrane integrity leading to direct bacterial lysis (Tzeng and Stephens, 2015). Besides their direct antimicrobial activities, AMPs are involved in recruitment and stimulation of inflammatory cells (neutrophils and macrophages) for producing cytokines on bacterial exposure in the mucosal airways (Tecle et al., 2010). Another well-known AMP also present in

I – Introduction - 19 - mucosal surfaces and neutrophil granules is bacterial permeability increasing protein, bactericidal/permeability-increasing protein (BPI). It has been reported to bind to LPS from meningococci and has endotoxin neutralising ability, in addition to antimicrobial activity (Schultz and Weiss, 2007).

Figure 1.6: Overview of human innate immune mechanisms involved in protection against Nm. In the respiratory airway, host epithelial cells mount an effective immune response by secreting antimicrobials such as reactive oxygen and nitrogen species (ROS, RNS), AMPs and complement components. Adapted from Trivedi et al. (2011).

Furthermore, the nasal mucosal secretions covering the epithelia in the upper respiratory tract constitute a number of non-specific innate immune defence molecules, including surfactant proteins SP-A, B, C and D, belonging to the collectin family of proteins, produced from the lungs. These surfactant proteins have been shown to regulate rheological characteristics of airway fluids and modulate immune responses through complement-independent opsonophagocytosis of meningococci (Schicht et al., 2013). Even in the absence of disease, a large proportion of saliva

I – Introduction - 20 - consists of secretory immunoglobulin A (S-IgA) and some complement proteins, C3a and C5a (Findlow et al., 2011; Van Zele et al., 2009). Together the evidence indicates that meningococci colonizing the nasopharynx are exposed to various immune and non-immune mediated host immunity triggers at multiple levels, which works independently, or in combination, to combat the virulence factors elicited by Nm.

1.12.1.2. Recognition of Nm by the innate immune system

Innate immunity constitutes the first line of defence against invading pathogens, and plays a key role in the early recognition and subsequent inflammatory responses against pathogens, including meningococci. The initial interaction between Nm and host nasopharyngeal epithelium is largely mediated by type IV pili (Tfp) on the Nm, which play multiple roles in many stages of the infection process, including adhesion, twitching motility, bacterial aggregation (in biofilm formation) and DNA transformation (in genetic adaptability of Nm) (Carbonnelle et al., 2009). It has been demonstrated in piliated organisms that pili interact with CD46, a membrane co-factor protein (Johansson et al., 2003). After this initial attachment, additional adhesion molecules, such as Opc binds to host extracellular matrix proteins, while Opa binds to carcinoembryonic antigen cell adhesion molecules (CEACAM), integrin and heparin sulphate proteoglycan (Carbonnelle et al., 2006). It has been suggested that the binding of Opa with CEACAM1 leads to cellular invasion (Carbonnelle et al., 2009). In addition to these adhesion molecules, recent findings demonstrated that neisserial adhesion A (NadA), a trimeric auto-transporter belonging to the Oca protein family, binds to epithelial cells (Nägele et al., 2011).

To combat colonisation by invading Nm, human innate immunity uses various sensory molecules (Figure 1.6), at mucosal surfaces. The innate immune system, comprised of antigen-presentation or phagocytic cells (granulocytes, macrophages and dendritic cells) possess pattern recognition receptors (PRRs) for detection of conserved pathogen-associated molecular patterns (PAMPs) expressed by microbes (Medzhitov, 2013). TLRs are the best-characterised classes of pattern recognition molecules; of which 13 members exist. To date, TLR-4, TLR-2 and TLR-9 have been implicated to contribute to the recognition of Nm. LPS (or LOS), the central inflammatory inducer in the outer membrane of meningococci, activates innate

I – Introduction - 21 - immune responses through TLR-4 (Chow et al., 1999). Other components in the outer membrane include lipoteichoic acid (LTA) and Por-A, important adhesins facilitating initial attachment of piliated Nm to the nasopharyngeal epithelial surface and subsequent invasion, known to bind to TLR-2 (Ingalls et al., 2001). Activation of TLR-2 and TLR-4 is reported to involve CD14 (Akashi et al., 2003). TLR-9 is also postulated to contribute to the inflammatory response to Nm through detection of meningococcal CpG DNA (Mogensen et al., 2006). Upon binding, TLRs activate signaling cascades via TIRAP and MyD88 adaptor molecules leading to induction of translocation factor, NFkB into the nucleus and subsequent transcription of inflammatory cytokines genes (IL-6, IL-8, TNF-α, IL-10, IL-1β) and activation of complement C3 expression. The latter expression, in turn, contributes to phagocytosis of Nm and regulation of IL-1 family cytokines, which then facilitates recruitment of neutrophils to the site of infection (Sanders et al., 2011b). In the context of IMD, PRRs of the innate immune system play two distinct and yet complementary roles; firstly activation of pro-inflammatory cytokines and second elimination of meningococci via opsonophagocytosis through complement cascade.

1.12.1.3. Complement cascade

The human complement system plays a central role in innate immune defence against invading Nm, and it is well established that terminal complement deficiencies confer susceptibility to IMD (Figueroa and Densen, 1991). Complement systems also play an important effector role to the adaptive immune response as complement activation mediates antigen specific response (Morgan et al., 2005). Other roles of complement during infection include activation of the inflammatory response and the clotting pathways. The evidence of these functions has been demonstrated in meningococcal sepsis, characterised by overactive cytokine responses and disseminated intravascular coagulation (van Deuren et al., 2000). Exposure to Nm activates all three pathways of the complement system (Figure 1.7), the classical pathway is mediated by C1q binding to antigen-antibody complex. The mannose- binding lectin (MBL) pathway is initiated by MBL binding to microbial surface associated carbohydrates and activates MBL-associated serine proteases. Lastly, the alternative pathway is activated upon an association between C3 with Factor B or D to produce C3b and acts as an enhancer for the other two complement

I – Introduction - 22 - pathways. All three pathways activate complement components in a cascade and eventually converge to produce C3b, which mediates elimination of meningococci in one of two ways. Firstly, C3b coats microbial surfaces in opsonin, encouraging uptake by phagocytic cells. Secondly, C3b is involved in the assembly of the terminal components (C5 – 9) and formation of membrane attack complex (MAC), which makes pores in the bacterial cell membrane and causes cell death (Hibberd et al., 2001; Schneider et al., 2007). The activation of the complement system is regulated via a number of effector proteins mainly distributed within the plasma and some on vascular endothelium. Including membrane-embedded factors, such as CD46, CD59, decay accelerating factor and extracellular proteins, such as C4 binding protein, C1q inhibitor and complement factor H have all been reported. High levels of complement factor proteins are distributed into the plasma from the liver, the main source of production, but detectable levels circulate in the mucosal surfaces in the airway and genital tracts, which are locally produced by the epithelium (Lo et al., 2009).

Figure 1.7: Overview of the three complement pathways that converge to result in the production of MAC and inflammatory response upon microbial invasion. Adapted from Hibberd et al. (2001).

I – Introduction - 23 -

1.12.2. Humoral immune response against Nm

We know now that antibody plays a critical role in the protection against IMD by direct attachment to meningococcal surface bound motifs and activation of complement mediated opsonophagocytosis or direct bactericidal killing. Since the early studies of Goldschneider et al. (1969), it is well understood that age related incidence of meningococcal disease is highly correlated with strain specific anti- meningococcal antibody or serum bactericidal activity (Goldschneider et al., 1969a). As mentioned previously, adaptive immunity can be directly activated in individuals on neisserial exposure or through cross-reactive immunity with non-virulent neisserial strains such as N. lactamica (Yazdankhah and Caugant, 2004). The human immune response against Nm depends upon serum immunoglobulin G (IgG), binding to bacterial antigen inducing complement mediated bacterial elimination.

The importance of IgG is evident in an inverse relation to serum IgG levels and incidence of disease. However, the role of mucosal antibodies in preventing bacterial carriage is not clearly understood. IgA is the most commonly expressed Ig class in human mucosal secretions and saliva. It is thought that a large proportion of mucosal IgA is produced locally by the salivary glands and referred to as secretory IgA, in contrast to the mucosal expression of IgG, which is considered to mainly originate in the serum, and then subsequently transported to mucosal surfaces (Brandtzaeg, 2013). The secretory IgA provides protection against Nm by binding to the bacterial surface to inhibit attachment to host epithelial receptors and facilitating their removal (Mantis et al., 2011).

A cellular response is central in production and long-term effectiveness of this protective response. The T-helper cells modulate the generation and development of humoral responses to T-cell mediated antigenic proteins, leading to long-term memory (Robinson et al., 2002). The cellular response and cytokine profiles from IMD and convalescent patients revealed that an age- dependent Th response exists, whereby older age groups produced a Th-2 mediated response with a higher IL-10/ IFN-γ ratio compared with infants who a generated Th-1 dependent response with a lower IL-10/ IFN-γ ratio, indicative of their developing immunity (Pollard et al., 1999).

I – Introduction - 24 -

In order to evade host immunity, Nm has developed a number of virulence strategies, including the capacity to change the expression of surface associated proteins to hide from host immune cells, while, the polysaccharides, component of the meningococcal capsule activates B cells independently from T-cell dependency, functioning without the involvement of MHC. This form of antigenic induction results in weakly immunogenic IgM Ab classes and prevents effective subsequent responses to the same strain (Gasparini et al., 2015). The opsonic action of Abs is also a key contributor to protection and elimination of IMD, as shown by the cellular activation of phagocytic cells, including neutrophils, macrophages and dendritic cells during the clinical course of infection.

Cerebral fluid extracts from IMD cases have been reported to contain large clusters of neutrophils encompassing large amounts of pathogen (also known as neutrophil extracellular traps; NET) and generate high levels of cathepsin G. In defence, Nm uses number of mechanisms to evade NET induced killing: 1) modification of lipid A moiety of LPS with phosphoethanolamine prevented digestion by cathepsin G within the NETs, 2) production of spontaneous blebs to dispel NET formation, and 3) expression of the high affinity zing uptake receptor, ZnuD provided resistance to NET mediated nutritional pressure (Lappann et al., 2013). Another important virulence factor of Nm of host evasion is the polysaccharide capsule, which has been the main target of adaptive immunisation strategies such as vaccination (Vipond et al., 2012).

1.13. Host genetics underlying susceptibility and severity of IMD

Infection with Nm results in a broad range of phenotypes, from asymptomatic colonisation state, where some individuals do not develop any symptoms, and then there are individuals who acquire the disease but recover fairly quickly and then those who suffer from a fulminant course of disease leading to severe outcome or even death. Genetic variations in the host immune response to a given pathogen is known to be an important determinant of disease susceptibility and severity (Sørensen et al., 1988). Haralambous et al. (2003) provided evidence for genetic influence on IMD, quantifying the sibling risk ratio of disease (λs), the risk to a sibling

I – Introduction - 25 - of an affected individual compared with the risk in the community. The study calculated the host genetic component contributed to about one-third of the total risk. A considerable number of studies have revealed that genetic variations can contribute to the dysfunction of host immune systems and related pathways and can confer predisposition to and determine the outcome of disease. Although the collective evidence indicates that, the genetic variants that determine susceptibility may not correlate with those that contribute to the severity of disease (Dale and Read, 2013; Wright et al., 2009). Figure 1.8 outlines the type of genetic variants identifiable using the two main genetic approaches, WES and GWAS.

Figure 1.8.Comparison of genetic variants identified using WES versus GWAS approaches. Adapted from Tsuji. (2010).

1.13.1. Mendelian defects in IMD

1.13.1.1. Complement deficiencies

Innate immunity serves as the first line of defence against neisserial invasions, such as the alternative complement pathway in the absence of antibody, which mediates opsonophagocytosis of the pathogen, and bacterial lysis through the formation of terminal MAC. Many familial cases with genetic mutations underlying their

I – Introduction - 26 - complement deficiencies have been described. Patients with mutations in the terminal complement component C5, C6, C7 and C8 genes have reported suffering from typically milder and often recurring IMD, despite acquiring antibodies (Arnold et al., 2009; Barroso et al., 2010; Fijen et al., 1999; Orren et al., 2012). These cases often result from an inability to form active MAC to combat invading Nm, and their less severe phenotypes highlight the destructive effects of complement activation during IMD. In a small subset of familial studies showed that genetic variants in Factor D, a serine protease responsible for activation of alternative complement pathway, are associated with increased risk to IMD (Sprong et al., 2006). The deficiency of Factor D leads to impaired activation of the alternative pathway in response to meningococci.

1.13.1.2. Properdin and MBL

Properdin a positive regulator of the alternative complement activation plays an important role in the stabilisation of C3b-Bb and –BbC3 enzymes through binding of C3. Properdin deficiency results in a rare X-linked condition, which has been implicated to increase susceptibility to IMD (Sjöholm et al., 1988). Individuals with properdin deficiency display a wide range of outcomes subject to the infecting Nm serogroup as well as confounding genetic factors (Emonts et al., 2003). In addition, familial MBL variants were found to occur more frequently in patients compared with controls, indicating increased susceptibility to IMD (Faber et al., 2007; Hibberd et al., 1999). Patients with MBL deficiency tended not to suffer from recurrent infection following the production of antibodies, unlike other complement deficiencies (Hibberd et al., 1999). However, a recently published larger follow up case-control study reported that the previously identified MBL2 variants were not reproducible when the control samples were more genetically heterogeneous (Bradley et al., 2012).

1.13.1.3. Innate immune signaling

The host innate immune response to invading Nm is activated upon TLR-4 binding to LPS on the outer membrane of the bacteria, which triggers a signaling cascade via MyD88 and IRAK-4, resulting in transcription of pro-inflammatory cytokine genes. A patient with compound heterozygous IRAK-4 mutations underlying complete deficiency of IRAK-4, more commonly linked to Gram-positive bacterial diseases was reported to have suffered from IMD (Medvedev et al., 2003). The identified mutations

I – Introduction - 27 - in IRAK-4 resulted in impaired TLR-4 mediated downstream signaling via NFkB and hypo-responsiveness to LPS, conferring susceptibility to recurrent bacterial infections in the patient. These results suggest that the innate immune pattern recognition and downstream signaling pathways may play an important role in containment of the bacterium during colonisation and prevention from successive invasive disease.

1.13.2. Polymorphisms associated with susceptibility and severity to IMD

In the past ten years, genetic association approaches, such as GWAS have been used extensively for the discovery of genetic variants that may underlie susceptibility to as well as the severity of IMD. However, a large proportion of these studies have been criticised for their methodological rigour and use of small sample size. It follows that many of the findings have yet to be successfully replicated and the findings reviewed below, therefore, must be deciphered carefully (Table 1.1). Nonetheless, the genetic variants identified to date have added great merits to our understanding of the genes and mechanisms that control IMD pathogenesis. In addition, they have paved the standards for future studies to come.

Table 1.1: Genetic polymorphisms conferring increased susceptibility or severity of IMD.

Gene SNPs Effect Reference Comment

Haplotype:

CEACAM C/ CEACAM-6 (Callaghan et al., 2008) Susceptibility SSS 3, 6 B/CEACAM – 3

B/CEACAM-6

Allele 1A1 Susceptibility/ SP-A2 5 (Jack et al., 2006) SCS Allele 1A severity Gln223Lys

I – Introduction - 28 -

(Schröder and Asp299Gly Susceptibility/ TLR-4 Schumann, 2005) SSS rare variants severity (Smirnova et al., 2003)

Homozygous allele TLR-9 Susceptibility (Sanders et al., 2011a) SSS of [+2848-A]

NO SCS, C allele of (Haralambous et al., CFH susceptibility 2006) SSS with [C-496T], meta- (Davila et al., 2010) analysis rs1065489

SSS with CFH3 susceptibility (Davila et al., 2010) meta- rs426736 analysis

(Binder et al., 2007; SERPINE1 Indel 5G/4G Severity Brouwer et al., 2010; SCS Geishofer et al., 2005)

TNF-α 308 G/A Severity (Nadel et al., 1996) SSS

IL-1β -511 C/T Severity (Read et al., 2000) SCS

IL-6 -174 G/G Severity (Balding et al., 2003) SSS

IL-10 1028 A/G Severity (Balding et al., 2003) SSS

Keys: NA – No association, SCS – substantial cohort size (more than 1000), SSS – small scale study (less than 1000).

I – Introduction - 29 -

1.13.2.1. Genetic variants of innate immunity

Nm is an asymptomatic coloniser of the nasopharynx and upper respiratory tract. The airway epithelium acts as a protective barrier by producing innate immune proteins to provide early defence against respiratory microorganisms. A considerable number of genetic variants in host epithelial adhesion and invasion response mechanisms have been linked to IMD susceptibility (Callaghan et al., 2008; Jack et al., 2006). Colonisation of the nasopharyngeal epithelial surfaces by Nm involves attachment of meningococcus outer membrane proteins, such as Opa to host CEACAM. It is a general consensus that invasive infection occurs soon after meningococci established colonisation on nasopharynx (Devine et al., 1970; Edwards et al., 1977), however, late invasion has also been reported (Neal et al., 1999). Thus far, investigators have hypothesised genetic variation in CAECAM family of encoding genes may influence neisserial colonisation and encourage occurrence of IMD in carriers. Callaghan et al. (2008) highlighted that haplotype C in CEACAM-6 was highly correlated with increased susceptibility to IMD compared with controls, and found haplotypes C and B correlates with protection to IMD in CEACAM3 and CEACAM6, respectively. Their results may suggest an association of genetic diversity of CEACAM and susceptibility to IMD, but additional work is required to confirm these findings.

In addition, nasal mucosa components, including SP-A and SP-D are expressed in the nasopharynx and respiratory tract, thus constitute the innate immunity at the site of meningococcal colonisation. SP-A and SP-D are known to recognise and bind to structural motifs on the surface of Nm and modulate host immune responses via phagocytosis and inflammation, independent of the complement system (Crouch and Wright, 2001). One study proposed that SNPs in genes encoding SP-A and SP-D proteins may contribute to risk to IMD. Jack et al. (2006) showed that a rare SNP (Gln223Lys) in 1A allele of SP-A2 was correlated with increased susceptibility to IMD. Interestingly, allele 1A5 of SP-A2 was protective against IMD, and inversely homozygous allele 1A1 of SP-A2 increased the risk to disease relative to controls. There was no association between polymorphisms in SP-A1 or SP-D and susceptibility to IMD (Jack et al., 2006). Their findings indicate the genetic variation

I – Introduction - 30 - in secreted innate immune proteins contributing to susceptibility to IMD, but again the findings need to be validated in a separate cohort.

Moreover, other host genetic factors controlling IMD include the TLR-4 and TLR-9 pathways, which detect pathogen-associated motifs, such as LPS on the surface of meningococci or bacterial genomic DNA, respectively. These interactions between TLRs with bacterial structural motifs triggers signaling cascade and consequently result in the production of pro-inflammatory cytokines (Sanders et al., 2011b). The carriers of common SNP (Asp299Gly) in TLR-4 display diminished response to LPS, and this is in line with mice studies which showed the mutants elicited reduced responsiveness to relevant other bacterial infections. However, no significant association has been established for this polymorphism and susceptibility to IMD. Smirnova et al. (2003) identified a high proportion of rare TLR4 variants in children with IMD. These rare heterozygous missense mutations in protein coding regions of TLR-4 were found in 21% IMD patients compared with 1.3% healthy controls (Smirnova et al., 2003). These findings suggested that rare mutations, unlike common polymorphisms in the TLR4 signaling pathway, may pose an increased risk to IMD.

Until recently, no association was observed for genetic variants in TLR-2 or TLR-9 with susceptibility to or severity of IMD. Sanders et al. (2011) explored the influence of TLR-9 polymorphisms at loci -1237 and +2848. Given that TLR-9 receptors bind to bacterial CpG DNA, genetic variations in TLR-9 may manipulate susceptibility or severity of IMD. Their findings revealed that homozygous allele of the +2848 polymorphism provided protection against contaminating IMD, and no correlation was found with the -1237 polymorphism. Further genotyping analysis revealed haplotype I was associated with risk to IMD (Sanders et al., 2011a). The rarity of genetic variants in TLRs and their varying allelic frequencies suggest that their effect may exhibit different levels depending on ethnic background.

1.13.3. Complement regulatory proteins

CFH is a negative regulator of the complement alternative pathway and prevents potential adverse effects on host cells. It regulates the alternative pathway by competing with complement Factor B for binding to C3 convertase, resulting in

I – Introduction - 31 - inactive C3b. CFH also facilitates factor I mediated decay of C3b and inactivates the downstream complement cascade (Walport, 2001). Haralambous et al. (2006) postulated the genetic variants that cause elevated plasma levels of CFH may have increased susceptibility to IMD. They found that SNP (C-496T) in the CFH promoter was more frequently found in patients compared with controls. The homozygous C allele appeared enriched in patients, suggesting homozygous carriers of the C allele associated with susceptibility to IMD; specifically due to serogroup C strains (Haralambous et al., 2006). Moreover, as described earlier in section 1.4.2, separate polymorphisms in CFH and CFH3 inversely correlated with susceptibility to IMD (Davila et al., 2010). It has been suggested that an intricate balance in CFH serum levels is necessary for effective complement mediated bacterial killing, as both over production due to the C-496T polymorphism or complete deficiency of this protein have both been implicated with IMD (Wright et al., 2009).

1.13.4. Genetic variants of acquired immunity

Complement mediated killing of pathogens depend on the Fc receptors (FcγR) binding to specific IgG regions (Fcγ) and initiating opsonisation and subsequent phagocytosis. Three FcγR variants exist: FcγR I (CD64), FcγR II (CD32) and FcγR III (CD16), and forms of the circulating FcγR IIa and FcγR IIb subtypes have been correlated with IMD pathogenesis (Platonov et al., 1998). Numerous investigators have studied the genetic variations of these receptor allotypes in relation to altered phagocytosis and the consequent effect on susceptibility and severity of IMD. Despite many of the studies observing the higher frequency of polymorphisms in specific allotypes of FcγR, many of them tended to be small scale and failed to find an association between SNPs in FcγR and susceptibility to IMD. Hence, further investigations are required to interpret the findings (Dale and Read, 2013; Wright et al., 2009).

1.13.5. Coagulation

One of the devastating characteristic features of IMD is the purpuric skin lesions due to excessive activation of coagulation pathways leading to build up of circulating fibrin and arrangement of microthromboses. The coagulation pathway is tightly regulated by various fibrinolytic mechanisms to prevent the devastation caused by microthromboses in IMD. Fibrinolysis is induced by inhibition of tissue plasminogen

I – Introduction - 32 - activator and urokinase leading to upregulation of plasminogen activator inhibitor 1 (PAI-1). An indel polymorphism (5G/4G) in the SERPINE1 gene (Table 1.1) encoding PAI-1 has been reported to correlate with severity of IMD and poor outcome (Brouwer et al., 2010). Recent studies have provided proof of the association between the 4G/4G genotype and severe IMD phenotypes, such as sepsis with a high risk of mortality (Binder et al., 2007; Geishofer et al., 2005). These findings emphasise the important role of fibrinolytic mechanisms in contributing to the degree of severity in IMD.

1.13.6. Inflammatory cytokine genes

Cytokines are essential products of the inflammatory mechanisms involved in the protection against Nm infection. Effectors at multilevel processes determine the concentrations produced in response to invading pathogen that influences activation of gene transcription through successful NFkB signaling (Akira and Sato, 2003). Studies have demonstrated that severe cases of IMD are often correlated with an excessive amount of systemic pro-inflammatory cytokines, including IL-6, TNF-α, IL- 1 (Sanders et al., 2011a; Waage et al., 1989). Up to date, many investigations have focused on identifying genetic variants in cytokine encoding genes that control inflammatory responses through the course of IMD. To name a few, polymorphisms - 308 in TNF-α promoter (Nadel et al., 1996), -511 in IL1β (Read et al., 2000), -174 in the IL-6 promoter (Balding et al., 2003) and A1028G in IL-10 (Balding et al., 2003), have all been reported to correlate with either severity of disease or increased mortality risk to IMD. Again further investigations are required to confirm these findings.

1.14. Summary

This chapter highlights the current knowledge on the genetic basis of human infectious diseases with a focus on IMD and provides some of the most prominent evidence that support the case. It describes the latest advancements in methodology and technology that are currently being utilised to facilitate the discovery of genetic variants that determine susceptibility or severity of infectious diseases. Up to date literature review on the genetic markers of Nm infection has been reviewed and highlights the gaps in our knowledge about the genetic determinants of this life-

I – Introduction - 33 - threatening disease. Thus, it leads us to the questions, which this thesis aimed to answer.

1.15. Aims of the study

 To identify rare disease causing gene/mutations that confer predisposition to invasive meningococcal disease using the WES approach.

 To carry out functional validation to understand the role of identified gene/pathways in the context of invasive meningococcal disease.

 To characterise the mechanism by which the rare gene/mutation may lead to susceptibility or severity of invasive disease.

 To utilise GWAS in identification of polymorphisms that may influence susceptibility to and severity or outcome in IMD.

 To undertake functional work in validating GWAS findings.

I – Introduction - 34 -

Chapter 2

II – Materials and Methods - 36 -

2. Materials and Methods

2.1. Bacterial strains and growth conditions

Wild type and mutant Nm strain MC58 was cultured on BHI agar prepared as follows: 37 g BHI broth (Oxoid) and 15 g bacteriological agar (BD biosciences) were dissolved in 1 L of dH2, autoclaved and supplemented with 10 % heat-inactivated foetal bovine serum (FBS) (Gibco). MC58 strains were cultured on BHI agar plates at

37 °C with 5 % CO2 overnight (16 -18 hours).

Escherichia.coli was grown in Luria-Brentani broth (20 g LB broth powder

(Invitrogen) dissolved in 1 L of dB2O) at 37 °C with shaking or on solid LB media (1.5 % agar wt/vole (Sigma Aldrich). Bacterial stocks were stored in 30 % glycerol containing media and stored at – 80 °C. The bacterial strains used in this study are shown in Table 2.1.

2.2. Heat-killing of Nm

Overnight growth of a planktonic culture of Nm was diluted to an appropriate OD600 using PBS (pH 7.2). The dilutions were transferred to tightly sealed tubes and incubated in a water bath at 56 °C for 1 hour, and heat-killing confirmed by plating out on solid agar and incubating at 37 °C overnight.

2.3. Antibiotics

Antibiotics were used for E. coli growth at the following final concentrations:

 100 µg/mL of kanamycin

 100 µg/mL of ampicillin

II – Materials and Methods - 37 -

 35 µg/mL of chloramphenicol

In addition, gentamicin was used for Nm killing at a final concentration of 100 µg/mL, and puromycin at 2 – 3 µg/mL as a selective agent.

Table 2.1: Bacterial strains used in this study

Species Strain Description/ Origin

N. meningitidis MC58 Serogroup B clinical isolate

MC58 pil-E Serogroup B clinical isolate

MC58 cap- Serogroup B clinical isolate

E. coli XL10-Gold Life technologies

TOP10 Life technologies

BL21 Life technologies

2.4. Genetic DNA manipulation techniques

2.4.1. Genomic DNA and RNA extraction

To extract DNA from whole blood, 1 mL of blood sample was obtained from each patient or control samples in heparinized blood tube (BD biosciences) and the genomic DNA was extracted using as per the manufacturer’s protocol (Qiagen). To extract DNA or RNA from cultured human epithelial cells, the supernatants were removed from wells, the cells were rinsed with 0.5 mL of ice cold 1 x PBS and scraped in 50 µL of 1 x PBS using cell scraper (TPP). The contents were transferred to 1.5 mL Eppendorf, centrifuged at 2,000 x g for 5 min at 4°C. The supernatants were removed and replaced with lysis buffer, and the downstream steps were carried out according to manufacturer’s protocols. The resulting nucleic acids were eluted in dH2O and quantified using Nanodrop (ND-1000 Spectrophotometer).

II – Materials and Methods - 38 -

2.4.2. Primers used in this work

The primer pairs used for amplification of full length SPLUNC1 or for plasmid sequence confirmation were designed using Primer3 software and shown in Table 2.2. Overlapping primer pairs for site-direct mutagenesis were manually designed to introduce the single nucleotide substitution at the mutation site of interest. These primers have been listed in Table 2.3.

Table 2.2: Primer pairs designed to amplify a full length SPLUNC1

Primer Sequence Details gSPLUNC1_exon1f CGCTCAGGAAACCATAAAGTCT genomic DNA sequencing gSPLUNC1_exon1r CCACATTGGTAACCTCAAGCT gSPLUNC1_exon2f GGTAACAGGTGCCCATGTCT genomic DNA sequencing gSPLUNC1_exon2r AAGGAGGCCACCAGAAGTAC gSPLUNC1_exon3f GGGTGTATGTGTGCATGTGT genomic DNA sequencing gSPLUNC1_exon3r GCTGGCAGATCTTCACCTG gSPLUNC1_exon4f GTGTGTGTCAGATCTGTTCCAG genomic DNA sequencing gSPLUNC1_exon4r CTTGCCAAGAATGCTAGCCT gSPLUNC1_exon5f AGATAAGTACAACTGTGGGCAAG genomic DNA sequencing gSPLUNC1_exon5r TCCATCAACCCAACCATCTAAC gSPLUNC1_exon6f TCCATCAACCCAACCATCTAAC genomic DNA sequencing gSPLUNC1_exon6r ACATGGACAGATGGATCAATGG gSPLUNC1_exon7-8f AGTCTTTCAACCTATGCTTGGG genomic DNA sequencing gSPLUNC1_exon7-8r TGTGGATTTCTCTGTGCATCC gSPLUNC1_exon9f ACTCACCACACATAAGTACACG genomic DNA sequencing gSPLUNC1_exon9r TGGGAAAGCCTTCTGAAATCC cSPLUNC1_f GAGCTCGTTTAGTGAACC cDNA sequencing cSPLUNC1_r CTACGCCTAGGTTTAAACC

Cloning-F CACCCAGTTTGGAGGCCTG rSPLUNC1 cloning Cloning-R GTTTAAACCTTATCGTCGTCATCCTTG

II – Materials and Methods - 39 -

Table 2.3.Mutagenesis primer pairs designed for this work.

Primer Sequence Details

G22E_for CATGGCCCAGTTTGAAGGCCTGCCCGTG Generation of G22E mutation in SPLUNC1 G22E_rev CACGGGCAGGCCTTCAAACTGGGCCATG Q30E_for GCCCCTGGACGAGACCCTGCCCTTGAATG Generation of Q30E mutation in SPLUNC1 Q30E_rev CATTCAAGGGCAGGGTCTCGTCCAGGGGC

2.4.3. Polymerase Chain réaction

Standard Polymerase Chain Reaction (PCR) was carried out using Taq polymerase (Invitrogen), Advantage GC Genomic LA polymerase (Clontech Laboratories, Inc.) or Phusion High Fidelity DNA polymerase (NEB). For individual reactions, the manufacturer’s recommendation was followed, and products were cleaned up, where necessary, using the QIAquick PCR Purification kit (Qiagen).

2.4.4. Quantitative RT- PCR

Cultured epithelial cells were lysed in RNA Late reagent and total RNA was isolated using a Rneasy Mini Kit (Qiagen). cDNA was synthesised using the High-capacity RNA-to-cDNA kit (Thermo Fisher Scientific). cDNA was then amplified by real-time PCR following the maufacturer’s protocol using predesigned Taqman primers and a probe set specific for human SPLUNC1 (assay ID Hs00213177_m1) and human GAPDH (assay ID Hs02758991_g1) on an ABI StepOnePlus Real Time PCR System (Life Technologies). Data were analysed using StepOne Software V2.1.

2.4.5. Agarose gel electrophoresis

DNA samples were combined with 1 part 6 x gel loading dye (NEB) and separated on 0.8 – 1 % agarose gels in 1 x Tris acetate ethylenediaminutesetetraacetic (TAE) buffer. DNA was visualised using ethidium bromide (Sigma Aldrich) under ultra violet light. The images were recorded and analysed using the Gel Doc EZ system (Biorad). For downstream processes, DNA samples were excised from the gel and purified using QIAquick gel extraction kit following the manufacturer’s instructions.

II – Materials and Methods - 40 -

2.4.6. Restriction endonuclease

DNA was digested using restriction endonucleases at the concentrations and conditions advised in the manufacturer’s protocol (NEB). Digestion was carried out in 50 µl volume reactions, and products were purified as described above using the QIAquick gel extraction kit.

2.4.7. DNA ligation

DNA ligation was carried out overnight at 16 °C with T4 ligase (NEB) using the manufacturer’s recommended conditions.

2.4.8. Transformation

E. coli (Invitrogen) competent cells were carefully thawed on ice, DNA samples added, and incubated on ice for 30 minutes. Cells were heat-shocked to take up DNA at 42 °C for 45 seconds, followed by incubation on ice for two minutes, and 500 µl pre-warmed SOC medium added. The cells were incubated at 37 °C for 1 hour with vigorous shaking at 200 rpm, and subsequently plated on antibiotic selective media for overnight growth.

2.4.9. Isolation of plasmid DNA

Plasmid DNA was isolated from E. coli using the QIAprep spin miniprep kit (Qiagen) according to the manufacturer’s instructions. The plasmids used in this work are listed in Table 2.4.

2.4.10. Genomic DNA sequencing

For sequencing of SPLUNC1 in patient’s genomic DNA, 7 coding and 2 non-coding exons along with intron and exon flanking regions were amplified by PCR. The PCR products were cleaned up by a PCR purification kit (Qiagen) using the manufacturer’s instructions. Sanger sequencing was carried out using a BigDye terminator (Invitrogen), and results analysed in Genalys Win3.3 software.

2.4.11. Mutagenesis

Site directed mutagenesis was performed with the QuikChange Lightning Site- Directed Mutagenesis kit (Agilient Technologies) for the introduction of the point mutation into the pSPLUNC1-WT expression vector that is C-terminally tagged with

II – Materials and Methods - 41 -

Myc-DDK (Origene). The mutant alleles were generated using PCR (95˚C for 10 minutes, x18 cycles of [95 ˚C for 20 seconds, 65 ˚C for 10 seconds, 68 ˚C for 5 minutes], 68 ˚C for 5 minutes) with custom designed primers as detailed in Table 2.3. The parental plasmids in the PCR product were digested with restriction enzyme, DpnI at 37 ˚C for 5 minutes, and transformed into either E. coli TOP10 or XL10-Gold ultracompetent cells (see Table 2.1). The cells were cultured on kanamycin (100

µg/mL) BHI agar plates overnight at 37 ˚C with 5% CO2. Next, DNA samples were purified with QIAprep spin miniprep kit, and sequenced with a BigDye terminator (Invitrogen) to confirm insertion of the desired mutation.

2.4.12. Whole exome sequencing

One or several individuals from each pedigree were subject to WES depending on the mode of inheritance of the disease. Genomic DNA library preparation and capture was carried out using the SureSelectXT Target Enrichment System for Illumina Paired-End Multiplexes Sequencing Library protocol (Agilent Technologies) at the Oxford Gene Technology (OGT, Oxfordshire, United Kingdom). The captured fragments were sequenced at the Wellcome Trust Centre for Human Genetics (Oxford Genomics Centre, United Kingdom) on an Illumina Sequencer Hi-Seq 4000 platform (Illumina, Inc.).

II – Materials and Methods - 42 -

Table 2.4: List of plasmids used in this study.

Plasmids Details Origin

pET100/D-TOPO Cloning vector, ampicillin resistant cassette Invitrogen pEGFP Expression vector, for visualising transfection efficiency Abcam pCMV6-empty Cloning vector, kanamycin resistant cassette Origene pEmpty-Lenti Cloning vector, chloramphenicol and puromycin resistant cassettes Origene pSPLUNC1-WT Expression vector, kanamycin resistant cassette, C-terminally tagged with MYC-DDK Origene pSPLUNC1-G22E Cloned from pSPLUNC1-WT, G22E mutation introduced using site-directed This study mutagenesis pSPLUNC1-WT_Lenti Derived of pEmpty_Lenti to include SPLUNC1 ORF from pSPLUNC1-WT This study pSPLUNC1-G22E_Lenti Derived of pEmpty_Lenti to include mutated SPLUNC1 ORF from pSPLUNC1-G22E This study pET100-SPLUNC1-WT Derived of pET100/D-TOPO to include SPLUNC1 from pSPLUNC1-WT This study Derived of pET100/D-TOPO to include mutant form of SPLUNC1 from pSPLUNC1- This study pET100-SPLUNC1-G22E G22E

II – Materials and Methods - 43 -

2.5. Human Tissue Culture

2.5.1. Growth of human cell lines

The 16HBE14 cells are derived from human bronchial epithelial cells and immortalized using the SV40 virus. The cell line was a kind gift from Ming-shi Li (Imperial College London). HEK293 cells (ATCC: CRL1573) are derived from human embryonic kidney cells. Both the HEK293 and 16HBE14 cell were cultured in Dulbecco’s Modified Eagle Medium (DMEM) GlutaMAX (Invitrogen) supplemented with 10 % of heat-inactivated FBS (Gibco) in a humidified atmosphere at 37 °C with

5% CO2.

Calu-3 cells (ATCC; HTB-55) are derived from lung adenocarcinoma and were cultured in Minimum Essential Medium α (MEM α) supplemented with 10 % heat- inactivated FBS and 1 x MEM Non-essential Amino Acid Solution (NEA) (Sigma

Aldrich) in a humidified atmosphere at 37 °C with 5% CO2. The COR-L23 cells (ECACC: 92031929) are derived from human lung carcinoma cells with epithelial morphology. The latter cell line was cultured in RPMI1640 (Invitrogen) supplemented with 10 % of heat-inactivated FBS (Gibco) and 1 x MEM NEA in a humidified atmosphere at 37 °C with 5% CO2.

EBV-transformed B cell lines were obtained from a healthy adult control population from The Centre for Applied Genomics at The Hospital for Sick Children, Toronto, ON, Canada). The cell line was cultured in RPMI1640 (VWR International) supplemented with 10 % FBS (Gibco), 1 mM sodium pyruvate, 0.1 mM nonessential amino acids, 2 mM L-glutamine and 10 mM HEPES (all cell culture reagents for this cell line obtained from Life Technologies, unless otherwise stated) in a humidified atmosphere at 37 °C with 5% CO2.

2.5.2. Air liquid interface epithelial cultures

CALU-3 and 16HBE14 cells were seeded on 0.4 µm pore size (BD Biosciences) semi-permeable membranes at a density of 5 x 105 and 4 x 105 in 24-well plates, respectively. The culture media was removed from the apical side after 2 days of cell seeding (100 % confluency reached by cells) and replaced every 2 days in the basolateral chamber. The formation of tight junctions was confirmed by trans-

II – Materials and Methods - 44 - epithelial resistance using a volt-ohm meter (Millipore). After 14 days of Air Liquid Interface (ALI) creation, apical side of the cells were rinsed in PBS and collected. Harvested supernatants were centrifuged at 8,273 x g for 10 minutes and protein contents concentrated approximately 5 x times using 5 kDa centrifugal filters (Amicon).

2.5.3. Transfection of epithelial cells

Monolayers of 16HBE14 or HEK293 cells were seeded in 24-well plates as described in 2.5.1. When the cells reached ~70 % confluency on the next day, culture media was removed and replaced with a fresh 400 µl of culture media. 16HBE14, CALU-3 and CORL-23 cells were transfected using Lipofectamine LTX, and HEK293 cells with lipofectamine 2000 (L2000) (Invitrogen). Plasmid DNA was diluted to an appropriate concentration in 50 µl of Opti-MEM medium (Invitrogen). In a separate Eppendorf tube, LTX or L2000 were diluted in 50 µl of Opti-MEM medium and mixed with diluted DNA. Plus reagent was added to LTX and DNA mixture to achieve optimal transfection. The mixture was incubated at room temperature for 5 minutes and added to cells in a dropwise manner. The plates were given a gentle mix and incubated at 37 °C with 5 % CO2 in a humidified atmosphere overnight. After 24 - 72 hours, the percentage of transfection was analysed by fluorescent microscope.

2.5.4. Generation of human epithelial cells overexpressing SPLUNC1 variants

The mutagenized constructs from above (Section 2.4.11) were sub-cloned into the pEmpty-Lenti plasmid using AsiSI and MLul-HF (NEB) unique restriction sites. The resulting pSPLUNC1-WT_Lenti and pSPLUNC1-G22E_Lenti plasmids selected from chloramphenicol resistant transformants was confirmed using SPLUNC1 cDNA primers (cSPLUNC1_f and cSPLUNC1_r) shown in Table 2.2. These plasmids were then used to create SPLUNC1 stable expressing CALU-3, 16HBE14 and HEK293 cells using the Calcium Phosphate Transfection kit (Invitrogen). As lentiviral vectors are not able to replicate on their own, pseudoparticles were generated in HEK293 cells by co-transfecting with plasmids encoding G protein from vesicular stomatitis virus (VSV-G) and HIV structural proteins and enzymes (Gag-Pol) using the Calcium

II – Materials and Methods - 45 -

Phosphate Transfection kit (Invitrogen). Briefly, HEK293 cells were plated in 6-well plates at a density of 2 x 105 cells per mL and grown overnight to reach ~ 50 % confluency. A fresh medium containing 2 % FBS was added to cells prior to transfection. Cells were co-transfected with final concentrations of 2 µg of pSPLUNC1_lenti variants (see Table 2.4) or pEmpty-lenti mock vector, 0.4 µg of pGAG-Pol and 1.4 µg of pVSV-G at conditions detailed in in the manufacturer’s instructions. Next day, the cells were replenished with fresh 10 % FBS containing growth media. The pseudoparticles from cell supernatants were harvested at 48 hours and 72 hours post transfection, and filtered through a 0.45 µm filter.

Cells (16HBE14, Calu-3 and HEK293) were seeded in 6-well plates at density of 4 x 105 cells per mL and grown overnight ~ 70% confluence. Next day, the cells were replaced with 1 mL growth media containing varying amounts of viral supernatant (100 µl, 200 µl and 500 µl) along with polybrene at a final concentration of 5 µg/mL per well. Cells containing media with polybrene served as control. After 24 hours, the viral particles were removed and cells were placed in fresh growth media. From the following day, 3 µg/mL of puromycin containing media added, and only the cells containing puromycin resistance selected to expand. The stable expressing cells were maintained in puromycin containing media throughout.

2.6. Western blotting

2.6.1. Bacterial cell lysate preparation

Bacterial cells were propagated overnight as detailed above in Section 2.1. Cultures were diluted in PBS and the OD600 adjusted to 0.5. An 0.5 mL aliquot of this cell suspension was centrifuged at 13,981 x g for 3 minutes and subsequently suspended in 1 x Laemmli buffer (1M Tris pH 6.8, 4 % SDS, 0.1 % bromophenol blue, 0.2 M DTT, 20 % glycerol). The suspension was heated at 95 °C and analysed by sodium dodecyl sulfate - polyacrylamide (SDS-PAGE).

2.6.2. Human cell lysate preparation

Medium bathing the adherent culture cells was removed and cells washed once with ice cold Dulbecco’s phosphate buffer saline (DPBS) (Invitrogen). DPBS was removed and replaced with 50 µl of lysis buffer (0.15 M NaCl, 1 % Triton X – 100,

II – Materials and Methods - 46 -

0.5 % sodium deoxycholate, 0.1 % SDS, 0.05 M Tris-HCL pH 8) complemented with complete ULTRA protease inhibitor cocktail (Roche). Samples in lysis buffer were either stored at - 80 °C for future use or incubated for 30 minutes at 4 °C with agitation. Samples were centrifuged at 8,273 x g for 10 minutes at 4 °C and proteins were collected in the supernatant. Protein concentrations were determined using the Bradford reagent (Biorad laboratories). Desired quantity of sample was mixed with 1 x NuPAGE LDS sample buffer and 1 x NuPAGE sample reducing agent (all from Invitrogen), and boiled at 95 °C before analysis on an SDS-PAGE gel.

2.6.3. Protein quantification

The Bradford assay was used to determine the total protein quantities in each sample. Samples were centrifuged at 8,273 x g for 5 minutes to remove any cell debris, and supernatants transferred to a new 1.5 mL Eppendorf tube. Samples were diluted 1:20 with dH2O. A serial dilution of purified BSA (Thermo Scientific Pierce) was made with concentrations ranging from 1.95 - 1000 µg/mL with dH2O. A 20 µl aliquot of unknown or standards were placed in 96-well NUNC polystyrene plates.

Wells containing dH2O alone served as blanks. An equal volume of Bradford reagent was added to each sample and the plate read at OD595 Nm. The protein concentration in unknown samples was calculated from the standard curve.

2.6.4. SDS polyacrylamide gel electrophoresis

Samples were analysed by the XT Bis-Tris gel system (Biorad). Equal amounts of each sample was mixed with appropriate loading buffers (see 2.5.1 or 2.5.2), heated at 95 °C for 5 minutes and separated XT Bis-Tris SDS-PAGE with XT MOPS buffer (Biorad). Samples were run at 150 V for 45 – 75 minutes.

2.6.5. SDS-PAGE gel staining

Polyacrylamide gels were rinsed with dH2O at least twice before being fully submerged in coomassie blue staining buffer (Sigma Aldrich) overnight at room temperature. The gels were then rinsed with 20 mL of dH2O at least three times, for 15 minutes at a time.

II – Materials and Methods - 47 -

2.6.6. Transfer

Proteins separated on SDS-PAGE polyacrylamide gels were transferred to a preactivated polyvinylidene fluoride (PVDF) membrane using the iBlot Western Blotting Gel Transfer System (Invitrogen). Briefly, the polyacrylamide gel was sandwiched between a pair of pre-activated PVDF transfer stacks and Whatman paper, and dry blotted for 7 minutes.

2.6.7. Protein identification

The PVDF membrane was transferred to blocking buffer (5 % semi-skimmed milk, 0.5 % tween 20, 1 x PBS) and incubated for 1 hour with gentle shaking at room temperature. After blocking, the membrane was incubated with an appropriate concentration of primary antibody, diluted in blocking buffer, overnight at 4 °C with gentle shaking. Excess antibodies were removed by washing three times with wash buffer (0.5 % Tween 20, 1 x PBS) for 5 minutes each time, with gentle agitation. Next, the membrane was incubated with an appropriate secondary antibody conjugated to horseradish peroxidise for 1 hour at room temperature with gentle shaking. Protein bound antibodies were developed using the ECL Western Blotting kit (GE Healthcare) and analysed using ImageJ software.

2.7. Production of recombinant SPLUNC1 proteins

2.7.1. Expression and purification of recombinant SPLUNC1 variants

Amplifications of wild type and mutant SPLUNC1 from cDNA clones were carried out using primers detailed in Table 2.2 (Cloning-F and Cloning-R). The Champion pET Directional TOPO Expression Kit (Life Technologies) was used to clone the amplicons into the pET100/D-TOPO vector (see Table 2.4). The DNAs were sequenced using specific primers to confirm cloning (see Table 2.2). The clones were transformed into E. coli expression strain BL21 and grown overnight in 10 mL of LB broth containing ampicillin at conditions outlined in 2.2. Overnight cultures were inoculated into 100 mL of LB containing ampicillin and grown until the OD600 reached 0.5. Protein expression was induced with the addition of 0.8 mM isopropyl- 1-thio-D-galactopyranoside (IPTG). Cultures were cultured for a further 3 hours, and cell lysates processed from each hour were analysed on SDS-PAGE as described in 2.3.2.

II – Materials and Methods - 48 -

2.7.2. Purification of rSPLUNC1 variants

Cultures containing expression proteins were centrifuged and subsequently pellets were re-suspended in lysis buffer (0.02 M NaH2PO4, 0.5 M NaCl, 0.1 M KCl, 10% glycerol, 0.5% Triton X-100, 0.01 M imidazole, 7.5 µg/mL lysozyme). The suspension was incubated in a 37 °C water bath followed by incubation at – 80 °C for 30 minutes, and this was repeated 2 – 3 times. Cell lysates were separated into soluble and insoluble fractions by centrifuging at 13,981 x g for 10 minutes. All SPLUNC1 variants were purified from soluble fractions of E. coli BL21 cell lysates using a Ni-Sepfast gravity column (Flowgen Bioscience). The bound proteins were rinsed in buffers (0.2 M NaH2PO4, 0.5 M NaCl, 0.1 M KCl, 10% glycerol, 0.5% Triton X-100) with 0.02 M, 0.05 M, 0.08 M and 0.1 M of imidazole. The bound proteins were released from the column using the same buffers containing 0.5 M of imidazole. Protein purity was assessed by SDS-PAGE and subsequently proteins were dialysed into PBS using Slide-A-Lyser Dialysis Cassettes (Thermo Fisher Scientific). The resulting purified proteins were quantified with Bradford reagent (Biorad).

2.8. Growth of MC58 for the SPLUNC1 treatment

Nm strain MC58 was cultured overnight in 10 mL BHI broth (see 2.1 for culture conditions) with shaking at 190 rpm. Broth cultured in the absence of bacteria served as the negative control. Next morning, the culture was diluted 1 in 10 with fresh BHI broth and incubated at 37 °C in 5 % CO2 for 2 - 3 hours to obtain mid-log phase growth. The resulting culture was diluted 1 in 50 in PBS and the OD600 measured to determine the colony forming units (CFU). The calculation was made based on the 9 estimation that OD600 1 equates to ~10 CFU per mL. The culture was diluted to an

OD600 of 0.1, and 10 µl inoculated into 190 µl per well of BHI in 96-well flat bottom polystyrene plates.

2.9. Nm viability in presence of SPLUNC1 treatment

For protein treatment, wild type SPLUNC1 or control protein (BSA) was added directly to MC58 cultures at increasing final concentrations of 1mL, 5 mLor 10 µg/mL. The assay was carried out in 200 µl per well in 96-well flat bottom polystyrene plates. MC58 cultured in media was included as a control. At specific

II – Materials and Methods - 49 - time points (0 minutes, 30 minutes, 60 minutes, 90 minutes 180 minutes, 24 hours), 10 µl of inoculum was removed, appropriate dilutions made in PBS, and bacteria plated in 10 µl spots on BHI agar plates for overnight growth (see 2.1 for conditions). After overnight incubation, CFU were counted from each spot to calculate the viable counts of surviving bacteria.

2.10. Nm biofilm formation assay

Wild type MC58 and mutant (MC58 pil-E and MC58 cap-) strains were cultured overnight on BHI agar plates (see 2.1 for culture conditions). Next morning, bacterial colonies were collected using a sterile green loop and re-suspended in 2 mL of PBS.

A 50 µl aliquot of each suspension was mixed with 950 µl of PBS and the OD600 was measured. Bacterial CFUs were calculated using OD600 measurements (as detailed in 2.3). Each suspension was diluted to an OD600 of 0.5 in DMEM (approximately 5 x 108 CFU/mL), and 10 µl inoculated into an appropriate volume of DMEM media in 96 – well polystyrene flat bottom plates. Wild type SPLUNC1, G22E allelic mutant and N-terminus deleted (ΔN, lacking amino acids 1 – 44) mutant recombinant proteins were appropriately diluted in DMEM media and the final assay volume made up with DMEM media to 100 µl per well. Wells containing DMEM media alone and BSA at the relevant concentrations were included as controls. The static biofilms were formed by incubating the suspensions at 37 °C in 5 % CO2. After 3 hours, the planktonic neisserial culture was removed from the wells and bacteria attached to plate surfaces were killed and fixed by incubating at 60 °C for 1 hour. The biofilm forming colonies attached to the surface of polystyrene plates were stained using 100 µl of 0.5 % aqueous crystal violet (0.5 g of crystal violet powder (Sigma Aldrich), dissolved in 80 mL dH2O and 20 mL methanol) for 15 minutes at room temperature.

Subsequently, the wells were washed 3 times with 200 µl of dH2O and stained biofilms incubated for 10 minutes in 80/20 % ethanol/ acetone solution. The optical density was measured at 590 Nm using a Molecular Devices plate reader attached to Softmax Pro software.

2.11. Adhesion and invasion of airway epithelial cells

Human respiratory epithelial 16HBE14 cells were cultured as described in 2.4.1. Cells were rinsed one time with DPBS and detached by incubating with 3 mL 1 x

II – Materials and Methods - 50 - trypsin (Gibco) from culture flasks. The detached cells were re-suspended in a fresh complete growth medium to obtain a single cell suspension. The cell numbers were determined by mixing with an equal amount of trypan blue dye (Invitrogen) and counting with an automated hemocytometer (Invitrogen). Cells were seeded at a density of 2.5 x 105 cells per well in 24-well tissue culture flat bottom plates. The following day, fully confluent monolayers were challenged with MC58 at an MOI of 1: 1. Bacterial CFUs were determined as described previously. Dilutions of recombinant SPLUNC1 or BSA were added to wells and the culture incubated at 37 °C in 5 %

CO2 in a humidified incubator with a gentle shaking. After 4 hours, wells were washed three times with PBS. Subsequently, monolayers were incubated at 37 °C in

5 % CO2 with 1 % saponin (Sigma) to lyse cells and release cell adherent bacterial colonies. Serial dilutions were made from saponin suspensions and plated on BHI agar plates overnight to determine CFUs.

2.12. LPS-binding assay

A slightly modified version of an enzyme-linked immunosorbent assay (ELISA) based LPS binding test (Bantroch et al., 1994) was used to measure the LPS binding abilities of SPLUNC1 proteins. Briefly, a 96-well flat bottom microtitre plate was coated with 200 ng of purified LPS from Nm, strain H44/76 (a kind gift from Peter Van Der Ley) or Salmonella enterica subsp. Minnesota R595 (Invitrogen) and incubated at 4 °C overnight. Coating was done in 50 µl per well. Next, the unbound LPS was rinsed four times with 0.05 % PBST (PBS-Tween 20) and wells blocked with 200 µl of blocking buffer (PBS – 1 % BSA) for 1 hour at room temperature. Two- fold serial dilutions of 250 ng recombinant SPLUNC1 were added to wells and incubated for 3 hours at room temperature. Wells containing dilution buffer (PBS) without protein served as a control. After four washes with 0.05 % PBST, wells were incubated for 2 hours at room temperature with 50 µl per well of goat anti-human PLUNC (R&D systems) antibody diluted to 500 ng/mL final concentration. Wells were washed four times with 0.05 % PBST and subsequently incubated with a 1:15000 dilution of anti-goat HRP-conjugated secondary antibody for 1 hour at room temperature. Wells were washed four times with 0.05 % PBST and developed with 1 x TMB substrate (Biorad) for up to 30 minutes. The reaction was stopped by adding

II – Materials and Methods - 51 -

50 µl of 2 M H2SO4 and the absorbance was measured at OD450 Nm using a Molecular Devices microplate reader connected to Softmax Pro software.

2.13. Epithelial cell stimulation with LPS or heat killed Nm

Human epithelial cells either transiently transfected (with plasmids encoding either SPLUNC1-WT or –G22E mutant) or stable expressing SPLUNC1 (-null empty plasmid, wild type SPLUNC1 or G22E) were seeded in flat bottom 24/96-well plates at a density of 5 x 105 cells per mL in 200 µl or 500 µl per well. Next day, the media was removed and replaced with a fresh complete growth medium (see details in 2.4.1) prior to stimulation. Cells were stimulated with increasing dose of TLR-4 ligand LPS (derived from S. Minnesota R595; InvivoGen) or heat-killed Nm MC58 (see details for heat killing in 2.2). LPS was used at final concentrations of 0.1, 0.5 or 1 µg/mL whereas heat-killed MC58 was used at ~106, 107 and 108 CFU/mL. Epithelial cells incubated in growth media alone served as non-stimulated controls. After 24 or 48-hour stimulation, supernatants were collected and stored at – 80 °C or used directly for cytokine activation.

2.14. Cytokine measurements

Human TNF-α or IFN-γ cytokines were measured from supernatants using capture and detection antibody pairs. In general, anti-human TNF-α or IFN-γ capture antibodies (Pharmingen) were diluted in coating buffer (0.1 M NaHCO3, pH 8.4) to give a final concentration of 2 µg/mL. Fifty µl aliquots were added to 96-well NUNC- immuno plates (Sigma-Aldrich) and incubated at 4 °C overnight. Next day, the plates were rinsed twice with 0.05 % PBST and blocked with 200 µl of buffer (PBS + 10 % FBS) at room temperature for 2 hours, and the previous washing step was repeated. All unknowns or standards, recombinant TNF-α or IFN-γ (Pharmingen) were diluted in diluent (0.05 % PBST + 10% FBS) to appropriate concentrations and incubated with coated capture antibody at room temperature for 4 hours. In each case, standard curves were from 10 pg/mL to 19 pg/mL, and diluents incubated alone used as blanks. After 4 hours, plates were washed four times in 0.05 % PBST. Biotin labelled detection antibodies (Pharmingen) were diluted in diluent to give 1 µg/mL and added to wells and incubated for 1 hour at room temperature. Plates were washed six times with 0.05 % PBST. Avidin-peroxidase (Sigma Aldrich) was diluted

II – Materials and Methods - 52 - to 1 µg/mL, added to wells and incubated for 30 minutes at room temperature in the dark. Plates were washed eight times in 0.05 % PBST. o-phenylenediamine di- hydrochloride (OPD)(Sigma Aldrich) tablets were dissolved in citrate buffer (5.19 g of citric acid, 9 g of Na2HPO4.2H2O dissolved in dH2O, pH 5) and 10 µl H2O2 was added at the last minute. One hundred µl of OPD substrate mixture was added to wells and incubated for up to 20 minutes. The reaction was stopped by adding 2M

H2SO4 and samples read at OD490 Nm.

Human IL-6, IL-1β and IL-8 cytokines were measured from epithelial cells or whole blood supernatants using ELISA Ready-SET-GO! kit reagents following the manufacturer’s protocols (eBioscience).

2.15. Taqman custom genotyping

DNA samples were extracted as previously described (2.4.1) from affected individuals and dilutions were made to 20 ng per microliter. Taqman custom human SNP genotyping assay probes tagged with fluorescent labels were designed by the manufacturer (Applied Biosystems). Real-time PCR was performed for polymorphism (rs73155936; Applied Biosystems, 5936_4351379) in 25 µl per well with 20 ng of DNA following the manufacturer’s instructions. Briefly, PCR components were set up with 11.25 µl nuclease-free H2O, 12.5 µl of 2 x Taqman universal PCR master mix (AmpliTaq Gold DNA polymerase, uracil-DNA glucosylase, dNTPs with dUTP, ROX as passive reference), 1.25 µl of 20x SNP assay probe, and 1 µl of DNA diluted to 20 ng. PCR was performed using a standard protocol on StepOnePlus and data analysed with Taqman genotyper software.

2.16. Genotyping of lncRNA SNP by sequencing

One of the top hits from the GWAS severity analysis in our meningococcal disease cohort was the long non-coding RNA SNP: rs145723387. This SNP was genotyped in 57 healthy adults by Sanger sequencing. The blood donors were consented to take part in the study and each donated 1 mL of venous blood. DNA samples were extracted as described previously (see 2.4.1). Sequence-specific oligos (Table 2.2) ,flanking approximately 300 nucleotide bases on either side of the SNP, were designed using Primer 3 software based on the genomic sequence and location.

II – Materials and Methods - 53 -

DNA samples were subject to PCR using Taq polymerase (see conditions in 2.4.1). The resulting amplicons were confirmed on agarose gel electrophoresis (see 2.4.3 for details), and purified using the QIAquick PCR Purification kit (Qiagen) before being sent for sequencing at the MRC Genomic Core Laboratory (Imperial College London). The electrophoresis data was analysed using GenalysWin3.3b software against a reference sequence downloaded from Ensembl database.

2.17. Whole blood assay

The whole blood stimulation assay protocol used in this study is adapted from similar work carried out in a previous study (Nolte et al., 2002). An equal number of healthy adults with either wild type homozygous (C>C), heterozygous (C>T) or homozygous (T>T) allelic genotypes for long non-coding RNA (lncRNA) SNP (rs145723387) were selected for whole blood assay. A fresh collection of heparinised blood samples were diluted 1:2 in RPMI 1640 (Invitrogen) and 180 µl of the mixture aliquoted in 96-well plates. Diluted blood samples were co-cultured at 37 °C in 5 % CO2 for 24 or 48 hours with a range of TLR agonists at the following concentrations. Heat-killed MC58 (104 to 108 cfu/mL), TLR-4 agonist LPS from S. Minnesota (100 ng/mL), IL-1β (100 ng/mL), TLR-2 agonist lipoteichoic acid from S. aureus (LTA-SA, 1 µg/mL), TLR-2/6 agonist synthetic bacterial lipoprotein (PAM2-CSK4, 500 ng/mL), TLR-1/2 agonist a synthetic triacylated lipopeptide (PAM3-CSK4, 500 ng/mL), phorbol myristate acetate (PMA, 5 ng/mL) and Ionomycin (500 ng/mL). All agonists were purchased from InvivoGen unless otherwise stated. Wells containing non-stimulated blood samples were included as controls. After stated periods, serum supernatants were collected and stored at – 80 °C until used in an ELISA for cytokine detection.

2.18. Calcium analysis by FACS

This assay was carried out using previously published methods with the help of Dr.Trang Duong and Dr. Martin Alphonse from the Department of Immunology, University of Toronto (Alphonse et al., 2016). EBV-transformed B cells (7 – 8 x 106 cells) were stained with Fluo-4 AM and Fura Red (Life technologies) loading dyes in Ca2+ free complete media and incubated at 37°C for 45 minutes, in the dark. Any excess or unbound loading dyes were removed and cells were diluted to 3 x 106 cells per mL in Ca2+ free DMEM supplemented with culture media (as detailed in

II – Materials and Methods - 54 - section 2.5.1). The cells were subsequenty stained with Dapi nuclear stain and rested for 20 minutes at room temperature. [Ca2+] mobilization was acquired for a continuous 10 minutes using a BD LSR II analyzer (BD Biosciences). To flux Ca2+, ionomycin (1 µM) was added at 1 minute without stopping the acquisition. To flux Ca2+ in the presence of calcium source, during the 10 minutes of continuous acquisition, CaCl2 (1.5 µM) was added at 1 minute followed by continued acquisition for further 3 minutes and subsequent addition of ionomycin (1 µM). Results were analysed on a FlowJo v9 (Tree Star, OR).

Chapter 3

III – WES to identify single genes underlying childhood IMD - 56 -

3. WES to identify single genes underlying childhood IMD

3.1. Background

Genetic variations in host immune response genes are key mediators of susceptibility to and severity of a given infection (Chapman and Hill, 2012). As detailed in the introduction, evidence from twin and adoptee studies strongly support the notion that host genetics is an important determinant of predisposition to infectious diseases. In meningococcal disease, the sibling risk ratio of disease, λs, indicative of the risk of disease in siblings of affected cases compared with the risk of disease in the community has been calculated to be 30 %, . A high risk of disease in siblings suggests host genetics contributing to disease susceptibility (Haralambous et al., 2003).

The identification of genetic variants that underlie susceptibility to and outcome of IMD is fundamental to unravelling the reasons behind why certain Nm strains cause disease in small number of individuals despite the high carriage rate in the general population, and the reasons behind the varying degree of severe manifestations found among IMD suffers. It is well-established that individuals with complement deficiencies are at increased risk to developing IMD (Arnold et al., 2009; Barroso et al., 2010; Fijen et al., 1999; Orren et al., 2012) and properdin deficiency is associated with non-recurrent meningococcal infection (Sjöholm et al., 1988). Altogether, these putative genetic deficiencies only account for a small proportion (3 %) of the disease cases (Fijen et al., 1999). Furthermore, the diverse manifestations seen in meningococcal disease patients are indicative that there may be many more

III – WES to identify single genes underlying childhood IMD - 57 - undiscovered genetic traits that underlie the remaining proportion of the unexplained cases.

In the past decade, the many research efforts to identify genetic variants that impact on susceptibility to or outcome of IMD have been heavily based on association studies such as GWAS. Whilst, these studies have provided important insight into the pathogenesis of IMD, many of these studies have been criticised for their inadequate sample sizes or use of inappropriate controls that are not representative of the healthy general population. In addition, many of the significant findings have not been successfully replicated by other investigators (Chapman and Hill, 2012; Wright et al., 2009), which raised concerns over the credibility of the initial reported findings.

Due to the limitations of these association studies, there has been a need for development of more robust and high-throughput systems approach for the field. With rapid technological advancement and rapid reduction in cost, many genetic studies have turned to the use of WES for identification of variants, followed by a functional characterisation approach. The major advantage of WES compared with earlier genomic studies such as the candidate-gene and genome-wide linkage analysis is the power to discover rare genetic variants, in a non-candidate driven approach, from both isolated single case (Byun et al., 2010) and a small subset of unrelated affected cases (Hoischen et al., 2010). The identification of causative variants underlying IMD will in turn lead to greater understanding of the disease pathogenesis and facilitate accurate diagnosis when alternative methods are either costly or inefficient, and aid the development of targeted therapies in the future. Using WES on clearly defined phenotypes of IMD cases, this study aims to identify novel and rare variants in genes underlying immune responses to Nm infection.

3.2. WES study cohort

A large cohort of patients with major childhood infections including meningococcal septicaemia, meningitis, and infections caused by the pneumococcus, S. aureus, Group A Streptococcus, E. coli and Salmonella, along with controls were collected through the EUCLIDS consortium. This consortium aimed to undertake a large-scale genomics study to investigate the genes and mechanisms involved in determining

III – WES to identify single genes underlying childhood IMD - 58 - susceptibility and severity of life-threatening bacterial infections, using meningococcal disease as a model. The patient cohorts of a range of childhood infections were established in collaboration from 11 study sites based in 7 countries including the UK, Spain, Holland, Germany, Italy, Switzerland and Gambia. In the meningococcal disease cases, the causative Gram-negative bacterium, Nm was confirmed by microbiological culture at the individual study sites, as well as by PCR amplification at the diagnostic Micropathology laboratory based in Warwick, UK.

The meningococcal cohort (n = 261) from the UK was recruited through the intensive care unit at St Mary’s Hospital as well as the Meningitis Research Foundation (MRF) charity network. The MRF has helped to establish a unique cohort of familial cases consisting of index cases and their affected siblings and parental samples. Full ethical approval was obtained from local and international authorities and written consent was obtained from all study participants. Participants with known complement genetic deficiencies were excluded from the WES pipeline. The inclusion criteria for WES cohort consisted of the following conditions: (I) the causative pathogen was microbiologically confirmed by culture of Nm from CSF or blood, (II) the onset of diagnosis under the age of 16 years, (III) related siblings who presented with IMD on separate occasions, and/or (IV) individuals who presented with severe manifestations or outcomes such as amputation, mechanical ventilation or death.

3.3. Bioinformatics and familial analysis approach

Genetic analyses of the WES data was undertaken by Dr. Vanessa Sancho Shimizu and Dr. Evangelos Bellos (Imperial College London). In some of these multiplex families; it was not possible to obtain parental DNA samples, which in turn presented difficulties with defining the mode of inheritance in these families and hindered the possibilities of some analysis methods. Several different approaches were employed to identify candidate gene mutations in the whole cohort; however, for the purposes of this thesis, the familial analysis approach is explained. Briefly, the initial phase of the analysis consisted of identifying the shared haplotype segments between the related sibling’s exomes using SHAPIT software (O'Connell et al., 2014). Then, the searches within the matched segments were restricted to identifying novel or rare

III – WES to identify single genes underlying childhood IMD - 59 - variants with MAF less than 0.01 in the general healthy population. The list of called variants was annotated using Ensembl’s Variant Effect Predictor to filter out synonymous or those variants that were predicted to have low impact at protein levels. A simplified version of the familial pathway analysis method is displayed in Figure 3.1. The final list of variants were annotated on a singular basis and function of the mutated gene together with possible relevance to infection pathogenesis, an approach considered for optimal candidate selection for further functional characterisation.

III – WES to identify single genes underlying childhood IMD - 60 -

Joint sample genotyping Raw variant set

Population Impact Deleteriousness Variant annotation allele frequency

Source 1000G & ExAC Ensembl’s VEP CADD

Variant filtering <5% missense LoF >20

Filtered variant set

Dataset split Familial cases Unrelateds

Analysis approach Mendelian segregation Case/control study

Unrelated Parents sequenced cases

Phasing All variants Case/control study shared by affected ca Only IBD variants in affected

Familial validation set

Figure 3.1.WES analysis pipeline used in this study. The detailed focus is on the familial analysis pipeline and some of the case/control pipeline is not fully described in this diagram. This diagram was provided by Dr. Evangelos Bellos.

III – WES to identify single genes underlying childhood IMD - 61 -

3.4. Molecular genetic analysis and discovery of a novel missense heterozygous mutation in SPLUNC1 in familial IMD cases

A large body of evidence suggests that family history confers a risk for predisposition to meningococcal infection (Brouwer et al., 2009; Brouwer et al., 2010; Domingo et al., 2002; Olea et al., 2017; Wright et al., 2009). In an effort to uncover the Mendelian predisposition to childhood IMD, multiplex families containing affected first- or second-degree relatives or affected parent and sibling pairs were hand-selected for exome sequencing. In total, six multiplex families met our inclusion criteria and were included in our exome sequencing cohort. This approach has previously been successful in the discovery of genetic markers contributing to childhood idiopathic infections (Alcaïs et al., 2010). As detailed in the Materials and Methods (Section 2.4.12), the WES was carried out by the Oxford Gene Technology and Wellcome Trust Centre for Human Genetics. The statistics on coverage and depth was provided as part their quality control measures. The reported mean target coverage across the exome was 69 % to a depth of at least 20 fold across the whole cohort.

The molecular genetic analysis of six IMD families uncovered a novel missense heterozygous SPLUNC1 (c.65 G > A, p.G22E) mutation in two siblings in one of the multiplex families, where both patients suffered from meningococcal meningitis and septicaemia from two independent episodes (P1 and P2; family 1; Figure 3.2).

P1 P2

WT/ G22E WT/ G22E

Figure 3.2: Pedigree segregation of two IMD siblings. The affected individuals are shaded in black and proband indicated by an arrow.

III – WES to identify single genes underlying childhood IMD - 62 -

The statistical analysis on coverage and depth at the mutant locus G22E was carried out by Dr. Evangelos Bellos. At this particular locus, 93.4 % of the reads were aligned to the target region and the mean target coverage was on average 40 fold, and approximately 62.2 % reads aligning to the target region to a depth of at least 20 fold.

In total, these two related cases harbored 231 rare candidate variants shared between them. A summary of these rare and novel alterations is presented in Table 3.1. Among these identified rare variants, we prioritized SPLUNC1 as a candidate gene likely to be important to IMD pathogenesis, based on its specific expression in the nasopharyngeal region (Bingle and Bingle, 2000) and from previous studies suggesting that the expressed protein is involved in protection against Gram- negative bacterial infections (Liu et al., 2013a; Liu et al., 2013b; Lukinskiene et al., 2011). In addition to the SPLUNC1 mutation, the next highest-ranking 14 variants considered to be deleterious based on their evolutionary conservation and functional consequence predictions by SIFT and Polyphen are displayed in Table 3.2.

III – WES to identify single genes underlying childhood IMD - 63 -

Table 3.1: Summary statistics of the shared rare variants in related IMD siblings described in this study.

Primary Primary effect Polyphen CADD phred 1000 genomes ExAc Sift prediction consequence on protein prediction score

120 6 stop 9 high 144 191 73 47 probably variants < gained impact reported reported deleterious damaging 20

222 86 variants 2 splice 30 possibly moderate 87 absent 40 absent 95 tolerated >20 and donor damaging impact 30 <

63 24 variants 1 splice unpredictab 106 benign >30 and acceptor le <40

222 48 1 variant missense unpredictable >40

III – WES to identify single genes underlying childhood IMD - 64 -

Table 3.2: Top 15 rare variants shared between the two IMD siblings (P1 and P2).

Variant Variant AF_1000 Primary Primary SIFT PolyPhen Gene Function of gene* AF_ESP AF_ExAC position change G Consequence Effect prediction prediction This protein may play a role in cytoskeletal PADI6 17723586 C>T reorganization in the 5.99E-04 0.00204 0.00177 stop_gained HIGH unknown unknown egg and in early embryo development May play a role in MICU3 16884980 G>A mitochondrial calcium . . 1.72E-05 stop_gained HIGH unknown unknown uptake.

0.009185 splice_donor_ LRRC69 92213022 T>A Function unknown. 0.01227 0.009095 HIGH unknown unknown 3 variant

Non--coding RNA KRTAP5-1 1605919 G>T gene, function 3.99E-04 0.00215 . stop_gained HIGH unknown unknown unknown An important paralog of this gene is ABHD12. Mutations in this gene are associated with the neurodegenerative disease, PHARC 0.001996 splice_donor_ ABHD12B 51348345 G>T 0.007 0.008549 HIGH unknown unknown (polyneuropathy, 8 variant hearing loss, ataxia, retinitis pigmentosa, and cataract), resulting from an inborn error of endocannabinoid metabolism.

III – WES to identify single genes underlying childhood IMD - 65 -

The encoded preproprotein is proteolytically processed to generate ADAMTS1 77325185 C>T the mature protein, . 1.54E-04 3.30E-05 stop_gained HIGH unknown unknown 8 which may regulate hemostatic balance and function as a tumor suppressor. This gene is a member of the RecQ DEAH helicase family and interacts with the BRCT repeats of breast cancer, type 1 (BRCA1). The bound complex is important BRIP1 59793412 G>A . 1.54E-04 1.48E-04 stop_gained HIGH unknown unknown in the normal double- strand break repair function of breast cancer, type 1 (BRCA1). This gene may be a target of germline cancer- inducing mutations The protein encoded by this gene is the alpha-3 subunit of one of several alpha/beta- subunit heterodimeric splice_accept HIF3A 46838160 A>G . . . HIGH unknown unknown transcription factors or_variant that regulate many adaptive responses to low oxygen tension (hypoxia).

III – WES to identify single genes underlying childhood IMD - 66 -

This gene belongs to the transport and Golgi organization family, whose members are TANGO2 20024596 C>G 7.99E-04 0.00715 0.00636 stop_gained HIGH unknown unknown predicted to play roles in secretory protein loading in the endoplasmic reticulum ZFP42 Zinc Finger Protein is associated probably_ missense_vari MODER deleterious ZFP42 188924713 G>A with ZFP42 . 6.15E-04 7.25E-04 damaging ant ATE (0) include Mixed Germ (1) Cell Cancer. The read-through transcript is a candidate for nonsense-mediated mRNA decay (NMD) missense_vari probably_ HSPB2- based on the use of 0.002595 MODER deleterious 111784401 G>A 0.00546 0.006721 ant&NMD_tra damaging C11orf52 the supported HSPB2 9 ATE (0) nscript_variant (1) translational start codon, and it is therefore unlikely to produce a protein product. The protein encoded by this gene forms functional heteromeric probably_ kainate-preferring ionic missense_vari MODER deleterious GRIK4 120827611 G>T . . 8.24E-06 damaging channels with the ant ATE (0) (1) subunits encoded by related gene family members. The product of this gene targets latent probably_ 0.003993 missense_vari MODER deleterious LTBP1 33567971 G>T complexes of 0.00723 0.00705 damaging 6 ant ATE (0) transforming growth (0.999) factor beta to the

III – WES to identify single genes underlying childhood IMD - 67 -

extracellular matrix, where the latent cytokine is subsequently activated by several different mechanisms. Nicotinic acid is converted to nicotinamide adenine dinucleotide, which serves as a coenzyme probably_ in cellular redox 0.002396 missense_vari MODER deleterious NAPRT1 144658630 G>A 0.00446 0.004937 damaging reactions and is an 2 ant ATE (0) (0.999) essential component of a variety of processes in cellular metabolism including response to stress. The encoded protein is specifically expressed in the nasopharynx missense_vari MODER Tolerated benign 31825582 G>A and is shown to play - - - SPLUNC1 ant ATE (1.0) (0.001) antimicrobial activity against Gram-negative bacteria.

*Details of the known functions of the genes were obtained from GeneCards [available at www.genecards.org].

The identified candidate SPLUNC1 mutation changed G to A at nucleotide position 65, in turn resulting in a change of glycine to glutamic acid at amino acid position 22 (Figure 3.3). The precise biological function of SPLUNC1 protein encoded by the candidate SPLUNC1 gene is not known. This potential pathogenic SPLUNC1 (G22E) mutation is located in the N-terminus of the encoded protein that is posited to regulate the epithelial sodium channel (ENaC) activity (Figure 3.4), important for maintaining airway surface fluid homeostasis and mucociliary clearance of the airway epithelium (Garcia-Caballero et al., 2009).

G22E

1 4 10 24

2 NH 1 ENaC 4 BPI alpha/beta domain 5 256 COOH 2 site

Figure 3.3: Schematic diagram of the SPLUNC1 protein. The grey boxes indicate the ENaC regulatory region and BPI alpha/beta shared domain respectively. The arrow indicates the position of the missense mutation.

ENaC regulatory site

Figure 3.4: 3D structure of SPLUNC1 (Walton et al., 2016). The crystal structure of human SPLUNC1 represented as a super-coiled structure consisting of a curved β-sheet flanked by α-helices form a highly hydrophobic core consists of leucine residues.

III – WES to identify single genes underlying childhood IMD - 69 -

In addition, there is growing evidence that suggests SPLUNC1 is a secreted human innate immune protein that is expressed by the salivary gland, surface epithelia, submucosal glands and ducts of the trachea, bronchus, nasal epithelium, and nasopharynx (Bingle and Bingle, 2000; Musa et al., 2012; Weston et al., 1999). The abundance of expression in these regions have been correlated with a crucial role in homeostasis maintenance in the airway mucosal liquid through regulation of surface liquid volume (Garcia-Caballero et al., 2009), and tension (Liu et al., 2013b).

SPLUNC1 and related proteins constitute a larger protein family called the bactericidal/permeability increasing (BPI)-fold containing proteins. Human SPLUNC1 shares a structural homology with innate immune proteins, BPI and LPS-binding protein (LBP) protein (Bingle and Craven, 2002; Elsbach and Weiss, 1998; Fenton and Golenbock, 1998). Studies employing animal models have suggested that Splunc1 has direct antimicrobial and immunomodulatory properties against bacterial and viral pulmonary pathogens. For example, the absence of Splunc1 in mice did not lead to development of spontaneous lung disease under normal conditions, but was associated with an impaired immune response following a challenge with Mycoplasma pneumoniae (Gally et al., 2011), influenza A virus (Akram et al., 2017), P. Aeruginosa and K. pneumoniae (Liu et al., 2013b).

3.5. Targeted sequencing identifies G22E mutation in an unrelated IMD case

In order to determine whether the missense SPLUNC1 (c.65 G> A, p.G22E) mutation is more frequently found in IMD infection, mutation flanking region of the SPLUNC1 gene was sequenced with a help of Master’s student Yaxuan Lu. In total, a cohort of 186 unrelated IMD cases from the St Mary’s legacy cohort not included in the EUCLIDS study were randomly selected for sequencing of the exon 2 only. Although, initial attempts were made to sequence the entire SPLUNC1 gene in all of these additional unrelated IMD cases, after series of setbacks with the initial PCR amplification step in few of the amplicons, we resolved to focus our sequencing efforts on the missense SPLUNC1 mutation-flanking region. The investigation identified a third unrelated IMD case (P3; family 2; Figure 3.5) to retain the same candidate SPLUNC1 (c.65 G

III – WES to identify single genes underlying childhood IMD - 70 -

WT/ G22E Figure 3.5: Pedigree of 3rd affected unrelated case with missense heterozygous SPLUNC1 (c.65 G > A, p.G22E) mutation. The affected case is shaded in black and the proband is indicated by an arrow.

3.6. Clinical presentation of IMD cases with SPLUNC1 mutation

In family 1, the proband is a girl (P1) and was diagnosed with meningococcal meningitis and septicaemia (confirmed Nm serogroup C) at 10 years of age. On a separate occasion, her younger brother (P2) was diagnosed with meningococcal meningitis and septicaemia (Nm serogroup unknown) at 2 years of age (Figure 3.2). To our knowledge, neither of them suffered from a fatal outcome. As these affected cases were recruited to our study via GP referral, the questionnaires collected at the time did not include information regarding their anti-meningococcal bactericidal antibody titres. In addition, the date of IMD diagnosis in each of these cases suggest that neither patients would have been immunised against Nm prior to acquiring IMD.

In family 2, the 3rd unrelated IMD case (P3) identified to retain the same missense heterozygous SPLUNC1 (G22E) mutation using Sanger sequencing of the SPLUNC1 gene is a Caucasian girl and was diagnosed with meningococcal septicaemia (Nm serogroup B) at 2 years of age (Figure 3.5). To date, it is not established whether this patient has any other known primary immunodeficiency (PID) or complement deficiencies associated with IMD. This patient is currently in the process of being exome sequenced to rule out the possibility of other causative deficiencies. At the time of recruitment, anti-meningococcal bactericidal antibody titre was not measured in this patient. Although there is no information regarding their immunization status, but their age would suggest that they would have been eligible for the UK meningococcal MenC vaccination program implementation.

III – WES to identify single genes underlying childhood IMD - 71 -

3.7. Deleteriousness of the candidate SPLUNC1 (c.65 G>A, p.G22E) mutation

The candidate G22E mutation was found to be evolutionary conserved among primates (Figure 3.6). This missense heterozygous mutation was not reported in public databases including dbSNP (Sherry et al., 2001), EVS (http://evs.gs.washington.edu/EVS/), gnomAD (http://gnomad.broadinstitute.org), 1000 genomes (Abecasis et al., 2010) and in our in-house database comprising over 500 exomes of children with varied life-threatening infections.

The human gene damage index (GDI) server was used to calculate the overall mutational damage to SPLUNC1 gene in the general population. The results predicted that all SPLUNC1 variants to pose a ‘medium’ risk for all disease types with a predicted GDI score of 18.057 and GDI-Phred score of 0.629735 (Itan et al., 2015). We then used the combined annotation dependent depletion (CADD) score to calculate the deleteriousness of the rarest SPLUNC1 variants (MAF < 0.01) and plotted against their individual MAF from ExAC (Figure 3.7). This type of approach has previously been successfully used to identify potential disease-casing mutations underlying monogenic diseases, while accurately predicting false-positive variants as benign (Itan et al., 2015). Although, this approach was not very useful in determining the deleteriousness of the missense mutation identified through WES because the novelty of the candidate mutation meant the allele frequency and CADD score could not be appropriate determined.

While many of these variant annotation tools have been developed to incorporate diverse range of information (e.g. conservation, type of mutation, allele frequency) for analysis, most of them are geared towards identifying ‘loss-of-function’ mutations. To that respect, we have used the variant annotation software, BSIFT (Lee et al., 2009) for our candidate mutation. This software predicted the novel missense SPLUNC1 variant as a ‘damaging’ gain-of-function mutation. The exome analysis also confirmed that P1 and P2 did not carry any known complement, IRAK-4 or properdin deficiencies (see list of IRAK-4 and properdin deficiencies in Table 1.1).

III – WES to identify single genes underlying childhood IMD - 72 -

Patient 1 M F Q T G G L I V F Y G L L A Q T M A Q F E G L P V P L D Q T 31 Homosapien 1 M F Q T G G L I V F Y G L L A Q T M A Q F G G L P V P L D Q T 31 Chimp 1 M F Q T G G L I V F C G L L A Q T M A Q F G G L P V P L D Q T 31 Gorilla 1 M F Q T G G L I V F Y G L L A Q T V A Q F G G L P V P L D Q T 31 Rhesus 1 M F Q T G V L I V F Y G L L A Q T M A Q F G G L P V P L D Q A 31 Baboon 1 M F Q T G V L I V F Y G L L A Q I M A Q F G G L P V P L D Q A 31 Marmoset 1 M F Q T G G L L V F Y G L L A Q T M A Q Y G G L P I P L D Q A 31 Mouse 1 M F l V G S L V V L C G L L A H S T A Q L A G Q L L P L A Q G 31 Rat 1 M F L V G S L V V L C G L L A Q S T A Q L A G G P L P L G Q G 31 Cow 1 M F H I G S L V V L C G L L A P T T A L L E A L P T P L G Q T 31 Sheep 1 M F Q I G S L V V L C G L L A Q T T A L L E A L P V P L D Q N 31 Horse 1 M F Q I G A L I V F C G L L A Q T T A L L E A V P S P L D P T 31

Figure 3.6.Multiple sequence alignment of a section of SPLUNC1 and primate orthologues. Residue alteration G22E is highlighted in the red box.

4 0

3 0

c S

2 0 D

n o v e l m is s e n s e m u ta tio n D

A S P L U N C 1 (c .6 5 C > A , p .G 2 2 E ) C 1 0

0 0 .0 0 0 0 0 .0 0 0 2 0 .0 0 0 4 0 .0 0 0 6 0 .0 0 0 8 0 .0 0 1 0 E x A C M A F

Figure 3.7. CADD scores for rare SPLUNC1 variants versus MAF results from ExAC database. Scatter plot showing the CADD-Phred scores for missense/nonsense/frameshift/in-frame/splice variants in the ExAC database with an MAF < 0.01. The position of the novel SPLUNC1 missense mutation in the 3 IMD patients is indicated by the red arrow.

3.8. Sequence confirmation of the SPLUNC1 missense mutation

The initial step in the functional validation of the candidate mutation in SPLUNC1 was sequence confirmation of the identified variant in the affected individuals. The results were used to rule out any sequencing artefacts from whole exome data.

III – WES to identify single genes underlying childhood IMD - 73 -

Primers were designed using in-silico Primer3 software against the genomic DNA sequence of the SPLUNC1 gene, covering the entire coding region of exon 2 and at least 150 bases flanking the intronic regions on either side. DNA was extracted from patient’s whole blood using the Qiagen blood mini kit as per manufacturer’s instructions, and eluted in nuclease free dH2O. PCR amplification of SPLUNC1 exon 2 was performed with Taq polymerase and the resulting amplicon was visualised on a 1 % agarose gel, before purification using the PCR purification kit (Qiagen), to remove excess reagents from the PCR product. A representative gel image from exon2 amplification in IMD patients and negative control samples is shown in Figure 3.8.

1000 bp

500 bp

Figure 3.8: Gel image of SPLUNC1 exon 2 amplicon. PCR amplification of SPLUNC1 exon 2 from IMD patients and negative control sample resolved on a 1 % agarose gel. Arrow indicates the position of the mutation.

Once the resulting amplicon size was confirmed by agarose gel electrophoresis, amplicons were sequenced using BigDye at the Genomics Core Lab, MRC Clinical Sciences Centre. The results were analysed using Genalys Win 3.3 software, where individual electropherograms were compared to reference fasta sequence downloaded from the Ensembl database (https://www.ensembl.org/). The analysis confirmed that the three IMD cases contained the heterozygous mutation in their genomic DNA (Figure 3.9). In addition to sequence confirmation of the identified mutation, the remaining 8 coding exons and exon-intron boundary flanking regions of

III – WES to identify single genes underlying childhood IMD - 74 - their entire SPLUNC1 gene was sequence validated in all there affected individuals. No other variants shared between the three IMD cases were found.

Figure 3.9: Sanger sequence confirmation of SPLUNC1 (c.65 G > A, p.G22E) mutation in three IMD patients and a control sample. Arrow indicates the position of the mutation.

3.9. Discussion

This study investigated the genetic susceptibility of IMD in unexplained cases from selected families of white European descent with no known consanguinity. WES was performed on six multiplex families, which is defined as two or more family members affected by the same phenotype. The raw data was filtered using step-wise analysis pipeline. The forward selected candidate genes and the prospective pathogenic mutations were validated using Sanger sequencing in the affected patients and family members, where DNA sample was available. In addition, targeted sequencing was undertaken in unrelated and ethnically matched 186 IMD cases to search for other patients possibly harboring either the same novel SPLUNC1 G22E mutation or additional rare variants in the same gene .

In these multiplex families, the analysis strategy involved searching for the potential candidate genes and causative mutation/s within the shared haplotypes of a pair of affected family members. We limited our search to rare and novel variants with < 1 % MAF in the general population and excluded synonymous variants reported on public databases such as dbSNP (Sherry et al., 2001), EVS (http://evs.gs.washington.edu/EVS/), 1000 genomes (Abecasis et al., 2010), and

III – WES to identify single genes underlying childhood IMD - 75 - gnomAD (http://gnomad.broadinstitute.org). The restrictiveness that comes with this type of stratification is of consideration, as the expanding large public datasets will likely incur greater number of rare variants (Bamshad et al., 2011). For this reason, in a parallel approach, the search for rare variants were filtered using MAF cut off of 1 % in our in-house 500 unrelated exome sequences as control. Other research studies have reported using similar stratification methods when prioritizing for potential causal variants from WES data as employed in this study (Fogel et al., 2014; Gonzaga-Jauregui et al., 2015). The genetic analysis of one multiplex family, in which two affected siblings (P1 and P2) suffered from IMD on separate episodes, identified a total of 231 rare shared prospective variants. The stratification of these candidate variants based on their functional deleteriousness revealed 9 alleles with potentially high impact on the encoded protein such as stop codon, splice donor and splice acceptor alterations.

A literature search on the functions of these predicted to have high impact, 9 candidate genes revealed no known association with IMD, while 2 of the candidate variations had no identified function (LRRC69 and ABHD12B). This simplified filtering approach did not consider potentially causal candidates that do not directly change the protein coding residues or those variants affecting the splice sites. Following this, the literature search on the IMD disease relevance was extended to the remaining 222 rare variants shared between the affected siblings, such as those with moderate consequence on the encoded protein, including missense variants (subset of these candidate variants are highlighted in Table 3.1). This approach led to the discovery of the novel missense heterozygous SPLUNC1 (G22E) mutation in this family. Albeit the precise biological function of the encoded SPLUNC1 protein is unclear, the specific expression in the nasopharynx (Bingle and Bingle, 2000) and its suspected innate immune defence role against Gram-negative bacterial infections (Liu et al., 2013a; Liu et al., 2013b) provided biological plausibility for this candidate.

To date, only one case-control study in a relatively small Chinese population observed the genetic variations in SPLUNC1 associated with risk to nasopharyngeal carcinoma. He et al. (2005) identified 8 SNPs distributed across the promoter and exon-intron boundary regions of SPLUNC1 gene and postulated C/C haplotypes at both -2128T>C and -1888T>C polymorphisms to correlate with increased

III – WES to identify single genes underlying childhood IMD - 76 - susceptibility to nasopharyngeal carcinoma in the patient cohort compared with controls (OR = 2.8, P < 0.006 and OR = 3.3, P < 0.0001, respectively). Furthermore, another study has purposefully created various mutations spanning the whole SPLUNC1 protein to elucidate the structural basis of its capacity to act as surface fluid spreading surfactant and ability to bind to Gram-negative bacterial endotoxin, LPS, a property that is postulated to be involved in bacteriostatic and innate immune defence roles of this protein on the respiratory epithelial surfaces (Walton et al., 2016). Indeed, in a separate study carried out by the same group, the potential causative G22E mutation found through the WES approach in the present study is shown to be located within a region (G22 – A39) important for the protection of proteolytic cleavage and normal functioning of ENaC, involved in airway surface hydration and mucosal clearance of foreign microbes from the airway surfaces (Garland et al., 2013). In the latter study, the investigators postulated the reduced pH exhibited in cystic fibrosis (CF) patients respiratory epithelium may alter SPLUNC1’s ability to regulate ENaC and hence lead to dehydration in the CF patient’s airway liquid and consequently result in increased susceptibility to the chronic condition (Garland et al., 2013). This may suggest the prospective pathogenic G22E allele may exist in a functional site on the encoded protein.

In this study, we were unable to obtain DNA samples from parents of the affected IMD cases (P1 – P3) from either families, in a timely fashion. So the allelic segregation of the G22E mutation could not be determined. Parents, one of whom must be a carrier too did not report family history, hence incomplete clinical penetrance is expected. The molecular basis of the incomplete penetrance of single- gene disorders of infectious disease remains unexplained, yet the reported cases are widespread as evidenced by the growing number of studies (Israel et al., 2017; Okada et al., 2016). As mentioned previously, the potentially causal SPLUNC1 (G22E) mutation identified in the present study is novel and was not found in public databases such as dbSNP (Sherry et al., 2001), EVS (http://evs.gs.washington.edu/EVS/), 1000 genomes (Abecasis et al., 2010), gnomAD (http://gnomad.broadinstitute.org) or in our in-house over 500 exome sequences, which included diverse array of bacterial and viral life-threatening diseases. Thus, the identification of 3rd unrelated IMD patient (P3) using targeted

III – WES to identify single genes underlying childhood IMD - 77 - sequencing further supported our hypothesis that this rare candidate allele may be important in the susceptibility to IMD.

In summary, this study demonstrates that WES and appropriate sequential filtering steps of the candidate variants can lead to the discovery of a single or small number of prospective variant/s. The pathogenicity of the prospective variant/s can be elucidated using functional validations. This method will facilitate in the identification of genetic aetiologies of IMD in previously unexplained affected patients.

III – WES to identify single genes underlying childhood IMD - 78 -

Chapter 4

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 80 -

4. Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model

This chapter describes work carried out in order to understand the role of wild type SPLUNC1 in the context of IMD. Unfortunately, the affected individuals described in this study were recruited some 30 years prior to the EUCLIDS study being set up. Despite efforts to re-contact the affected cases and related family members, it was not possible to obtain fresh samples (throat swabs for culturing human oral epithelial cells) for cell biology and molecular based functional validation studies. In this chapter the expression and purification of recombinant SPLUNC1 variant proteins in E. coli (Section 4.1 – 4.3), and the functional assays developed to elucidate a role for SPLUNC1 in the context of IMD (Section 4.4) are described.

4.1. Generation of recombinant SPLUNC1 proteins

The production of recombinant proteins in microbial systems is a commonly used approach when studying the function of a given protein. The expression and purification of the desired protein in unlimited amount provides a platform in which to investigative the possible function of the desired protein through a variety of means. In theoretical terms, the approach involves few simple steps: (I) clone the gene of interest into an appropriate expression vector, (II) transform into a host of choice including bacteria, yeast, fungi, algae and human cell lines, and (III) purify recombinant protein from the host system contaminating proteins for further characterisation. However, practically, many impediments during any one of the above stages can lead to unsatisfactory results such as host system dysfunction,

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 81 - formation of inclusion bodies, yielding functional inactive protein, or lack of protein production (Rosano and Ceccarelli, 2014).

Alternative approaches include purchase of a commercially available recombinant protein or to employ a biotechnology company to produce the protein of interest. Even then, there is no guarantee of successful protein production. As mentioned previously, there are many choices of host systems for protein production and each has disadvantages and advantages. The choice is often dependent on the protein of interest (Adrio and Demain, 2010). The use of E. coli as a host system is well documented. This bacterium has one of the fastest growth kinetics, requires inexpensive reagents for growth media, high cell numbers can be reached rapidly, and transformation with exogenous DNA in plasmid form is, in general, easily attainable (Pope and Kent, 1996; Sezonov et al., 2007; Shiloach and Fass, 2005).

Other studies investigating the function of SPLUNC1 with the use of in vitro infection models have successfully used E. coli as the host to produce recombinant protein (Liu et al., 2013a; Sayeed et al., 2013). In this study, recombinant wild type SPLUNC1 and allelic mutants based on the exome findings were generated to investigate their biological roles in Nm infection.

4.2. Construct of SPLUNC1 allelic missense plasmid

Initially, the commercially available cDNA clone of SPLUNC1 ORF (Origene) was transformed into E. coli XL10-Gold ultracompetent cells for propagation, generating pSPLUNC1_WT expression plasmid. The resulting plasmid was purified and sequence confirmed using cSPLUNC1_f and cSPLUNC1_r primers designed against the cDNA sequence of SPLUNC1 (see sequence details in Table 2.2). Subsequently, the allelic missense variant was introduced into the pSPLUNC1_WT expression vector by site directed mutagenesis (see Chapter 2.4.10 for a detailed protocol), with the use of overlapping primer pairs (G22E_for & G22E_rev) containing the point mutations. The resulting pSPLUNC1_G22E plasmid was transformed into E. coli XL10-Gold ultracompetent cells and grown on LB plates containing kanamycin (100 µg/mL). Plasmid DNAs from the successful transformants were purified and subsequently sequenced to confirm the desired individual point mutation (Figure 4.1). The benefit of using the QuikChange Lightning Enzyme blend

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 82 - that incorporates a derivative of PfuUltra high-fidelity DNA polymerase was evident, as sequencing of the plasmid in its entirety confirmed there were no other unwanted second-site errors introduced during the mutagenesis process in the recombinant plasmid.

Figure 4.1: Sequence confirmation of successfully inserted two independent point mutations in pSPLUNC1-WT plasmid. Alignment of pSPLUNC1-W and pSPLUNC1-G22E mutant plasmids. The change in nucleotide is highlighted in red rectangles.

4.3. Expression and purification of rSPLUNC1 variants

The wild type and mutant SPLUNC1 constructs (Section 4.2) were amplified to generate blunt-end PCR products, using the directional cloning primer pair, cloning-F and cloning-R. The amplification of PCR products failed number of times due to suboptimal conditions. However, successful amplicon for each allele was obtained upon optimization of the PCR conditions. As the missense mutant contained a single nucleotide change, all SPLUNC1 alleles each produced a PCR product of 819 bp, as analysed on agarose gel in Figure 4.2. The blunt-end amplicons were subsequently ligated into pET100/D-TOPO vector to generate pET100-SPLUNC1-WT and pET100-SPLUNC1-G22E.

Figure 4.2: Amplification of SPLUNC1 allelic variants using directional cloning primers cloning-f and cloning-r. G22E allelic mutant was analysed in lane 2. Wild type SPLUNC1 analysed in lane 1.

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 83 -

For expression of recombinant SPLUNC1 variants, the three SPLUNC1 allelic variants (pET100-SPLUNC1-WT and pET100-SPLUNC1-G22E) were transformed into E. coli BL21 Star (DE3) cells as previously outlined in section 2.7.1. For ease of downstream purification and analysis, all recombinant SPLUNC1 protein variants (26.7 kDa) were expressed in-frame with N-terminal fusion 6 x His tags (1.0 kDa), bringing the total protein size to 27.7 kDa. Optimum expression was obtained after 4 hours of induction with 0.8 mM IPTG for all SPLUNC1 variants (Figure 4.3). Similar amounts of SPLUNC1-WT and SPLUNC1–G22E.

Figure 4.3: Recombinant SPLUNC1 expression. Expression of pET-SPLUNC1- WT and pET-SPLUNC1-G22E. IPTG (0.8 mM) was added to E. coli BL21 cells transformed with pET-SPLUNC1 variants that were grown to mid-log (OD600 = ~0.5). Induction of protein expression was for 4 hours with analysis at 2 hourly intervals (lanes 3 and 5). Samples with no added IPTG were also analysed (lanes 2 and 4). A sample from the zero time point was is shown in lane 1. The arrows indicate rSPLUNC1 proteins. The molecular weight lane marker was Precision Plus Protein Dual Colour Standards (Biorad).

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 84 -

Over-expressed His-tagged rSPLUNC1 protein variants were purified from BL21 cells with nickel-affinity gravity columns using techniques previously described in Section 2.7.3. All allelic variants of rSPLUNC1 were expressed as soluble proteins as clearly demonstrated in the representative coomassie blue stained SDS-PAGE gel shown in Figure 4.4. The identity of each purified variant was confirmed as SPLUNC1 by western blot analysis using specific antibody against the N-terminus His-tag. Briefly, the same samples employed in Figure 4.4 were run on a concurrent SDS-PAGE gel, electro-blotted to a PVDF membrane, and probed with human anti- His-antibody to determine the identity of rSPLUNC1 in each of the fractions from the purification steps (Figure 4.5). Purified proteins retained in buffer containing 500 mM imidazole were dialysed overnight at 4°C. Insoluble material, believed to be destabilised protein clumps, following dialysis were removed by centrifugation and protein concentration was assessed for each variant using the protein quantification Bradford assay. A secondary band of slightly smaller size was observed in miniscule amounts in both coomassie blue staining and western blot analysis for all variants. This faint band was assumed to be degradation products of the full length SPLUNC1 protein fragment.

In conclusion, recombinant SPLUNC1 was successfully expressed and purified using E. coli expression system. However, the quantity of recombinant proteins required for further functional studies was difficult to achieve in a given time. Therefore external source was sought to carry out further investigation in a timely fashion (described below), where wild type rSPLUNC1 and G22E allelic mutant were available. The majority of the functional work in this thesis was undertaken using recombinant proteins produced by our collaborators at the University of Pittsburgh, prior to production of the recombinant SPLUNC1 variants described above. All recombinant proteins used in this thesis were expressed and purified in the same manner, as previously described in Section 2.7. Our collaborators have previously established their recombinant proteins are functional in various in vitro and in vivo studies (Liu et al., 2013b; Lukinskiene et al., 2011; Walton et al., 2016).

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 85 -

Figure 4.4: Purification of rSPLUNC1 variants with nickel-affinity columns. Insoluble fraction of BL21 cell pellet did not contain the protein of interest (lane 1) and soluble protein mixture contained rSPLUNC1 protein (lane 2). The majority of the impurities were recovered in the flow-flow (lane 3), as well as in the wash buffers with increasing imidazole concentrations from 20 mM (lane 4), 50 mM (lane 5) and 80 mM (lane 6). Over 90% of purified protein is recovered in the first eluate with 500 mM imidazole (lane 7, and small quantities detected in the subsequent eluates with the same imidazole concentration (lanes 8 and 9).

Figure 4.5: Identification of purified rSPLUNC1 protein. Anti-His antibody specifically bound to the soluble fraction of the starting material (lane 2) and purified protein eluates (lanes 7 - 9). The size detected by the anti-His antibody matched the estimated molecular weight of rSPLUNC1 protein at approximately ~27.7 kDa. There was no detectable loss of rSPLUNC1 at different stages of the process as evidenced by lack of protein found in flow- though and succeeding wash fractions (lanes 3 to 6).

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 86 -

4.4. Investigation of the biological role of SPLUNC1 in IMD

The function of SPLUNC1 has never been investigated in the context of Nm infection. Based on the available published data, we hypothesized that SPLUNC1 has a role in preventing Nm colonising nasopharyngeal epithelial surfaces, and progression to invasive disease. SPLUNC1 is reported to function as a major surfactant protein in the upper respiratory tract, and its abundance inversely correlates with surface tension in primary cultures of human airway epithelia (Liu et al., 2013a). Other such surfactant proteins expressed at the nasopharynx and other parts of respiratory tract by the epithelia are SP-A and SP-D, which belong to the collectin protein family (Jack et al., 2006).

Carriage studies have established that mucosal immunity provides the first line of defence against meningococcal infection, and its effectiveness is signified by the low frequency of carriers progressing to invasive disease (Kvalsvig and Unsworth, 2003). One aim of the work in this thesis was to identify novel genes and mutations using WES and validate the findings in the context of the relevant disease model by undertaking functional investigation. Since the exact role of SPLUNC1 was not well defined, the initial investigation of the exome finding consisted of characterising the wild type SPLUNC1 in the context of IMD.

4.4.1. Bacterial survival assay

The observations from previous studies have suggested that SPLUNC1 is bactericidal against microorganisms other than meningococci (Bartlett et al., 2008; Zhou et al., 2008). In this work, the antimicrobial function of SPLUNC1 was assessed by incubating MC58, a clinical serogroup B isolate of Nm, with recombinant SPLUNC1 protein, which had been previously reported to have antimicrobial activity against another Gram-negative bacterium P. aeruginosa (Lukinskiene et al., 2011).

Overnight cultures of bacterial cells were sub-cultured in complete growth medium and allowed to reach mid-log phase of growth represented as OD600 = 0.5. The culture was then diluted in fresh growth medium to give a final concentration of 106 CFU per mL. This cell concentration was chosen as it falls in the range of bacterial

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 87 - counts found in CSF of meningococcal disease patients, where a large percentage of cases had cell counts ranging from 105 CFU - 107 CFU per mL (Bingen et al., 1990). Initially, the bacterial cells were incubated with increasing concentrations of recombinant human SPLUNC1 protein (1 – 10 µg/mL) for three hours, a typical time for a bactericidal assessment of Gram-negative antibacterial activity (Taylor, 1983). BSA, which does not have bactericidal activity against Gram-negative bacteria or surfactant properties such as being a surface tension mediator, was included at relevant concentrations as a control. The concentrations employed in this work for recombinant SPLUNC1 falls in the physiologically reported amounts found in sputum or epithelial cell secretions (Gakhar et al., 2010; Sayeed et al., 2013).

There was no difference in bacterial growth following treatment with SPLUNC1 compared with either protein control, BSA or blank control (absence of treatment) for 3 hours (Figure 4.6A). This finding is consistent with previous studies where the same source of recombinant human SPLUNC1 was demonstrated not to possess direct bacterial killing activity against other Gram-negative bacteria, including K. pneumoniae and P. aeruginosa (Liu et al., 2013a; Sayeed et al., 2013). As the meningococcus has slower growth kinetics compared with other Gram-negative bacteria such as E. coli, the bacterial viability assay was also measured up to 24 hours to investigate the potential long-term effects of the treatment. No difference in bacterial viability was found at 24 hours between any treatments (Figure 4.6B). Thus, we concluded that SPLUNC1 does not exhibit bactericidal activity against Nm, under the conditions tested.

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 88 -

Figure 4.6: Wild type SPLUNC1 is not bactericidal against Nm. Wild type Nm strain; serogroup B clinical isolate MC58 was cultured alone in complete culture media, in the presence of control protein, BSA or rSPLUNC1 for (A) 3 hours or (B) 24 hours. The bacterial viability was assessed by plating on solid agar plates at specific time points and counting CFU on the following day. Results are means ± SD from two independent experiments carried out in triplicates.

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 89 -

4.4.2. Bacterial biofilm biomass assay

In light of recent discoveries regarding the potential role of SPLUNC1 in prevention of biofilm formation by Gram-negative bacteria, in this work, we evaluated whether SPLUNC1 would abrogate biofilm formation by other Gram-negative species such as Nm using the standard microtitre plate assay. A number of studies have documented that Nm can adhere to epithelial surfaces and various abiotic materials to form complex micro-colonies, commonly referred to as the biofilm state (Lappann et al., 2006; Yi et al., 2004). Biofilm formation by Nm has not been widely investigated, and the existing handful of studies has mostly employed mucosal commensal species (Kaplan and Fine, 2002; Kinniment et al., 1996; Leonhardt et al., 1995; Saunders and Greenman, 2000). The initial stage of neisserial colonisation begins with attachment of pili, followed by adherence of other surface associated molecules with the host epithelia (Virji et al., 1993).

Firstly, we assessed whether the host surfactant protein SPLUNC1 would play a role in preventing biofilm formation by Nm on an abiotic surface. We used MC58 serogroup B strain of meningococci as it is known to form biofilm on human epithelial cultured cells (Grifantini et al., 2002; Hey et al., 2013). Kyungcheol et al. (2004) indicated that greater numbers of meningococcal carriage strains have the ability to form biofilms compared with hyper-virulent disease causing isolates. This may be because of surface capsular expression. However, it is suspected that all meningococcal strains have the capacity to form biofilm through switching off their capsular expression, employing mechanisms such as slipped strand mispairing (Yi et al., 2004). For example, genes responsible for capsule biosynthesis were down- regulated when MC58 adhered to human epithelia in vitro (Hey et al., 2013). Thus, we included capsule deficient (cap-) MC58 mutant strain as control for these biofilm experiments. Previous studies have shown that capsule-deficient strains of Nm form twice the amount of biofilm biomass compared with that of wild type parental strains (O'Dwyer et al., 2009).

As we did not know the effect SPLUNC1 may have on Nm biofilm formation, we also included a pili deficient (pilE-) MC58 mutant strain as a control, since a previous study demonstrated that pili-deficient strains of Nm form relatively thinner biofilms

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 90 - compared to wild type parental strains (Yi et al., 2004). These and many other authors (Arenas and Tommassen, 2017; Lappann et al., 2006; O'Dwyer et al., 2009) have highlighted the importance of pili in biofilm formation of Nm, as alteration in biofilm structure may result in lack of pili mediated twitching motility and lead to formation of flattened structures.

In order to eliminate any potential bias arising from growth of MC58 wild type and isogenic mutants, their comparative growth rate was determined. The detailed protocol can be found in Material and Methods Section. The results suggest there was no difference in growth between wild type MC58 and the pilE- mutant when grown in DMEM supplemented with Glutamax (Thermo Fisher), as a glutamine source.

However, the growth of the cap- mutant was comparatively slower than both wild type and pilE- mutant (Figure 4.7). Since cap- showed much slower growth, it was incompatible for further investigation.

Figure 4.7: Wild type and mutant MC58 growth curve. The growth of individual strains in DMEM was monitored by measuring OD600 at various time points. cap- denotes capsule deficient MC58, and pilE- denotes pili deficient MC58 mutant.

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 91 -

The microtitre plate assay employed in this work is a modified version of that developed by O.Toole and colleagues (O'Toole et al., 1999). This assay measures the ability of bacteria to form a biofilm on abiotic surfaces, such as polystyrene, and allows the convenient measure of multiple factors such as different treatment conditions at the same time. In order to ascertain that the effect is specific to recombinant SPLUNC1, we included BSA as control, a protein not known to have any effect on bacterial biofilm formation or surface tension of solutions, even at high concentrations (Bartlett et al., 2011). Initially, we optimised the assay with varying amounts of SPLUNC1 and control proteins statically incubated with the different MC58 strains for 3 hours.

The results showed that recombinant SPLUNC1 inhibited early biofilm formation by Nm on polystyrene surface. There was a marked reduction in Nm biofilm biomass when the bacterial cells were co-cultured with 10 µg per ml of SPLUNC1 protein compared to controls (Figure 4.8). These results are consistent with those of others whom reported that SPLUNC1 exhibits surfactant properties, and was able to inhibit biofilm formation of Gram-negative bacteria such as K. pneumoniae (Liu et al., 2013a) or P. aeruginosa (Gakhar et al., 2010) in in vitro models.

M C 5 8 a lo n e

C o n tro l (B S A 1 0  g /m l)

1 .5 0 rS P L U N C 1 (1 0  g /m l) )

0 * 9

5 1 .2 5

O (

1 .0 0

s s

a 0 .7 5

i b

0 .5 0

l i

f 0 .2 5

i B 0 .0 0

8 8 5 5 C C M M e - p lE y i t p d il w

Figure 4.8: rSPLUNC1 inhibits Nm biofilm formation on polystyrene surface. MC58 wild type and pilE- mutant were allowed to form a biofilm on a polystyrene surface for 3 hours in the absence or presence of rSPLUNC1 or control BSA at 10 µg per mL. Crystal violet straining was used to measure the biofilm biomass. Results are derived from experimental triplicates repeated at least three independent occasions and plotted as mean ± SEM. *P < 0.0001.

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 92 -

The concentration of SPLUNC1 used in our study is within the range of physiological concentrations reported in human airway epithelial secretions (Gakhar et al., 2010; Sayeed et al., 2013). We, and other investigators (Liu et al., 2013a) have found there is a delicate balance between the amount of SPLUNC1 and bacterial load, as 5 µg of rSPLUNC1 was sufficient in inhibiting P. aeruginosa growth (Sayeed et al., 2013). However, we found that at least double the dose of the same rSPLUNC1 was required to achieve effective inhibition of Nm early biofilm formation, indicating there may be a pathogen-specific SPLUNC1 dosage effect.

4.4.3. Nm adhesion and invasion assay

To understand whether this anti-biofilm effect of rSPLUNC1 may protect against bacterial infection in a physiological setting, we assessed the potential effect of SPLUNC1 on Nm adhesion and invasion of human epithelial cells. Nm harmlessly colonises 10 – 30 % of the general healthy population at a given time, and this colonisation of the mucosal surfaces serves as the first step in the host-pathogen interaction, which leads to host immune activation (O'Dwyer et al., 2009; Yazdankhah and Caugant, 2004).

Despite being classified as an extracellular pathogen, evidence from in vitro studies show that Nm can enter into human epithelial cells using type IV pili and surface associated adhesins, such as Opc and Opa (Virji, 2009). Other studies using nasopharyngeal tissue culture found that Nm attaches selectively to non-ciliated epithelia, and can subsequently invade these cells (Stephens, 1989). In addition, studies using respiratory epithelial cells grown at the ALI on semi-permeable membranes found that Nm tightly attaches to the epithelial surfaces, and subsequently invades via the transcellular route without incurring any tissue damage in the process (Sim et al., 2000; Sutherland et al., 2010).

In this work, we carried out a short time course adhesion and invasion assays, coincubating MC58 with human 16HBE14 bronchial epithelial cells for up to four hours, as our group and others have previously used relatively similar method as an in vitro model of neisserial colonisation (Grifantini et al., 2002; Hey et al., 2013). For the adhesion assays, after the 4 hour cocultivation period the non-epithelial cell associated planktonic bacterial cells were removed by washing, and the cell-

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 93 - associated bacteria subsequently diluted and plated on solid medium to calculate CFUs. A similar protocol was used for bacterial invasion assays, except the planktonic cell removal wash steps were followed by gentamicin killing of the surface adherent cells. Saponin was used to release intracellular bacteria, enumerated by plating and determination of CFUs. A detailed protocol is outlined in Section 2.11.

To address the potential effect of SPLUNC1 using this in vitro host pathogen interaction model, monolayers of polarised human epithelial cell line 16HBE14 were grown to a full confluency (> 95 %) in 24 well plates and inoculated with MC58 at an MOI of 1 for 4 hours. An MOI of 1 equated to a 2 x 105 CFU meningococci per 200 µl assay well or 1 x 106 CFU per mL. As previously shown, this bacterial cell density falls in the mid-range of bacterial numbers isolated from CSF of meningococcal disease patients, where the counts range from 105 CFU to 107 CFU per mL (Bingen et al., 1990).

We first assessed whether the 16HBE14 cell line endogenously expresses our protein of interest, as SPLUNC1 is known to be abundantly expressed throughout the respiratory tract (Bingle and Bingle, 2000). Our immunoblotting results demonstrated that SPLUNC1 is not constitutively produced by our model cell line, 16HBE14 (Figure 4.9). Therefore, using this cell line as a SPLUNC1 knockout model system, the function of the encoding SPLUNC1 protein was assessed by supplementing the 16HBE14 epithelial monolayer with either human recombinant SPLUNC1 or control protein, BSA that is known not to have impact on Nm adhesion or invasion into epithelial cells during nasopharyngeal colonisation.

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 94 -

Figure 4.9: Human bronchial epithelial cell line, 16HBE14 does not endogenously express SPLUNC1. Detection of endogenous secretion of SPLUNC1 protein from two different sources of human primary airway epithelial cells as well as 16HBE14 cells, grown at the ALI. The cell surfaces were rinsed apically to collect secretions. Recombinant SPLUNC1 (rSPLUNC1) used in this work included as immunoblotting control. The secretions were immunoblotted using specific SPLUNC1 antibody, 200 ng of recombinant human SPLUNC1 was included as control.

There was a marked reduction in the number of human epithelial cell surface adherent Nm when supplemented with rSPLUNC1 in coculture compared to controls (> 1.5 log difference, P < 0.0001, Figure 4.10A). Accordingly, we also detected a significant decrease in the number of MC58 that subsequently invaded the human epithelial 16HBE14 cells with the presence of rSPLUNC1 compared with control wells (Figure 4.10B). Notably, our earlier bacterial survival assay showed that SPLUNC1 is not bactericidal against Nm, as we failed to observe any direct bacterial killing. Hence, the significant decrease in number of adherent and invasive bacterial cells is not likely to result from reduced bacterial viability through direct bacterial killing. It is more likely that the decrease is mediated by disruption of early biofilm formation or attachment of Nm to human epithelial cells.

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 95 -

* *

5 ) 4  1 0

L M C 5 8 a lo n e

U C o n tro l (B S A 1 0  g /m l)

3  1 0 5

F C

( rS P L U N C 1 (1 0  g /m l)

o 5

i 2  1 0

h d 5 a 1 1 0



5 C

M 0

e l) l) n m m lo / / a g g   8 0 0 5 1 1 C ( A M S 1 B C ( N l U o r L t P n S o r C

* *

5  1 0 2 )

L M C 5 8 a lo n e M / 4  1 0 2

U C o n tro l (B S A 1 0  g /m l)

F C

( S P L U N C 1 (1 0  g /m l)

3  1 0 2

o i

s 2

a 2  1 0

8 1  1 0 2

C M 0

e l) l) n m m lo / / a g g   8 0 0 5 1 1 C ( M A 1 S C (B N l U o L tr P n S o C

Figure 4.10: rSPLUNC1 inhibits adhesion and invasion of human epithelial cells by Nm. Human epithelial 16HBE14 monolayers were cocultured with MC58 in the absence and presence of rSPLUNC1 or control protein BSA for 4 hours. (A) Numbers of adherent meningococcal CFU were obtained from three biological replicates. (B). Numbers of intracellular meningococcal CFU were obtained from three biological replicates. Results represented as mean ± SEM. A significant difference (* * P<0.0001) between SPLUNC1 treatment and controls was found.

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 96 -

4.4.4. Discussion

As discussion in previous Chapters, Nm is a human specific commensal obligate pathogen and found to asymptomatically colonise up to 30 % of the general healthy population, at one time. Only in rare circumstances, the bacteria invade nasopharyngeal epithelial barriers to reach bloodstream and cause a life-threatening IMD, with often fatal consequences. Following colonisation with carriage strains, the host immune response elicits strain specific antibodies within the first two weeks (Neil and Apicella, 2009; Yazdankhah and Caugant, 2004). Although the production of circulating bactericidal antibodies against Nm is considered an effective host defence mechanism, the barrier functions of nasopharyngeal epithelium and non- specific innate immune effectors are important in providing protection, especially during the period, prior to antibody development (Caugant et al., 2007; Pathan et al., 2003; Trivedi et al., 2011). In this study, we investigated the potential biological role of SPLUNC1, a human airway secreted protein, in host defence against Nm infection.

SPLUNC1 is constitutively expressed and secreted by conducting airway epithelia, and the submucosal glands (Bingle and Bingle, 2000; Musa et al., 2012; Weston et al., 1999). Due to its structural homology with host innate immune defence proteins BPI and LBP, it is hypothesised to play a similar antimicrobial role in the conducting airways, where these prominent antimicrobial proteins are not expressed (Bingle and Craven, 2002; Elsbach and Weiss, 1998; Fenton and Golenbock, 1998). In support of this proposal, studies have shown mice overexpressing Splunc1 displayed improved protection against intranasal induction of the Gram-negative pathogen P. aeruginosa (Lukinskiene et al., 2011). In humans, SPLUNC1 expression is elevated in chronic airway inflammation disorders such as cystic fibrosis, and also shown to increase expression in response to various bacterial and viral pathogens, during the initial phase of infection (Akram et al., 2017; Bartlett et al., 2011; Sayeed et al., 2013). Similarly to its innate immune defence protein family members BPI and LBP, SPLUNC1 has the ability to bind LPS, a major component of the Gram-negative bacterial cell wall (Liu et al., 2013b; Sayeed et al., 2013). In addition, concentration of SPLUNC1 is decreased during the inflammatory response to allergic rhinitis (Ghafouri et al., 2006), oldfactory bulbectomy (Sung et al., 2002), and chemical

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 97 - irritations such as smoking (Ghafouri et al., 2002). However, the host defence activity of SPLUNC1 has never been addressed in the context of Nm infection.

In this study, we successful expressed and purified recombinant human wild type and mutant SPLUNC1 proteins in order to assess the biological roles associated with this protein. The biological activity of the wild type and G22E allelic mutants were assessed and showed comparable to each other. SPLUNC1 showed no bactericidal activity against Nm, as we failed to observe inhibition of bacterial viability in a conventional in vitro experimental setting (Figure 4.6). Similarly, other investigators have also reported no direct killing against E. coli and Listeria monocytogenes (Bartlett et al., 2008). Conversely, the chinchilla homologue of SPLUNC1 exhibited direct bactericidal killing of Haemophilus influenzae (McGillivary and Bakaletz, 2010), as well as considerable growth suppression of M. pneumoniae (Chu et al., 2007) and P. aeruginosa (Liu et al., 2013c) were reported with purified SPLUNC1.This cumulative evidence showing that SPLUNC1 does not display uniform host defence effects against diverse pathogens may indicate that unlike other non-specific secreted innate immune antimicrobial proteins, SPLUNC1 could possibly exhibit a pathogen specific role in host defence., reflective of its multifunctional nature.

In addition, several lines of evidence suggest that SPLUNC1 is a surfactant of the airway epithelium that plays an important role in regulation of the airway surface liquid (Garcia-Caballero et al., 2009) and surface tension (Gakhar et al., 2010; McGillivary and Bakaletz, 2010). In these studies, contact angle measurements were used to investigate the spreading properties of aqueous droplets on a hydrophobic surface, and found that addition of recombinant SPLUNC1 (at 10 µg or more) to the drop resulted in a significantly reduced contact angle compared with drops without the protein. These results indicate that SPLUNC1 possesses a spreading property, which is commonly associated with surfactant molecules. The high degree of hydrophobicity in human SPLUNC1 protein also resembles the alveolar surfactant proteins SP-B and SP-C, which are also highly hydrophobic in their active forms (Bartlett et al., 2011) and furthermore, genetic variations in genes encoding SP-A and SP-D proteins suggested to increase susceptibility to IMD (Jack et al., 2006). There is growing evidence that suggests the surfactant property of SPLUNC1 is attributed to prevention or disruption of microbial biofilm formation (Bartlett et al.,

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 98 -

2011; Gakhar et al., 2010; Liu et al., 2013a). Indeed, the same source of rSPLUNC1 used in the present study was previously reported to display surface tension lowering activity that was associated with anti-biofilm activity against the Gram-negative bacterium K. pneumoniae (Liu et al., 2013a).

We show, for the first time, that SPLUNC1 is an important host defence protein of the human mucosal epithelium, which restricts Nm colonisation by hindering biofilm formation and early attachment of bacteria to epithelial surfaces. Our in vitro studies of Nm biofilm formation on an abiotic surface showed that presence of rSPLUNC1 results in significant suppression of early biofilm establishment (Figure 4.8). Our finding is consistent with previous reports on anti-biofilm effect seen with other Gram-negative bacteria, such as P. aeruginosa (Bartlett et al., 2011; Liu et al., 2013d) and K. pneumoniae (Liu et al., 2013a) in an in vitro and in vivo settings. It is evident; however, that the anti-biofilm role of SPLUNC1 is not connected with direct bactericidal killing, as we have demonstrated earlier with Nm, together with other pathogens described above. Therefore, SPLUNC1 may contribute to innate immunity by moderating surface tension of the mucosal liquid on airway epithelial surfaces, thus disrupting early Nm biofilm development, such as bacterial aggregation and microcolony formation. This in turn may facilitate Gram-negative bacteria to become more susceptible to antimicrobial effectors produced by the host innate immunity by the epithelial mucosa.

Furthermore, given that Nm specifically colonises the nasopharyngeal epithelial surfaces, the relevance of this anti-biofilm effect of SPLUNC1 in protection against Nm infection was sought in this study, using an in vitro human polarised airway epithelial cell culture model (16HBE14 cells). Our findings demonstrate that addition of exogenous SPLUNC1 at the same time as Nm resulted in a significant abrogation of neisserial adhesion, as well as subsequent invasion into human epithelial cells compared to control (Figure 4.10). Notably, our bacterial survival assay showed that SPLUNC1 does not display direct bactericidal effect on Nm growth, as we failed to detect any direct bacterial killing. Therefore, the inhibition of bacterial adhesion and invasion is not attributable to reduced bacterial burden or viability, but rather through the interference of early biofilm formation or attachment to epithelial cell surfaces. These findings support earlier reports of the inhibitory effect of SPLUNC1 on biofilm

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 99 - formation by Gram-negative bacteria, including K. pneumoniae, where the absence of SPLUNC1 was associated with increased susceptibility to infection (Liu et al., 2013a).

The constitutive expression of SPLUNC1 in the nasopharynx and surrounding area negates the role of this protein being specific to meningococci only, and hence it is likely that the protein will have broader impact, affecting pathogenesis of diverse microorganisms that associate with the upper respiratory tract. In addition to the microorganisms discussed above, a recent study has reported the protective effect of SPLUNC1 against Influenza A virus (Akram et al., 2017). Therefore, it is important to characterise the genetic variations that may determine the susceptibility or even severity of a specific infection.

In summary, findings presented in this Chapter provides in vitro evidence that SPLUNC1 plays an important host defence role against Nm infection, through inhibition of bacterial adhesion and invasion to epithelial surfaces, which in turn abrogates early biofilm formation, leading to increased exposure of bacteria to host innate immune antimicrobial elements in the epithelial surface of the nasopharynx.

IV – Characterisation of SPLUNC1/BPIFA1 using an in vitro meningococcal colonization model - 100 -

Chapter 5

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 102 -

5. Characterisation of G22E mutation using in vitro models of cultivated epithelial cells

This chapter outlines investigations undertaken to functionally determine whether the prospective pathogenic heterozygous missense mutation in SPLUNC1 gene leads to increased susceptibility to IMD in the carriers. In this chapter, the overexpression method using transient transfection of cultured cells (Section 5.1), determination of pro-inflammatory cytokine responses in cells expressing SPLUNC1 variants (Section 5.2), the attempts at generating human cell lines that overexpress SPLUNC1 variants and culturing of these cells at the ALI to model the respiratory surface (Section 5.3), and functional studies to decipher the potential pathogenicity of the G22E mutation in susceptibility to Nm infection (Sections 5.4 – 5.7) are all described.

In the preceding Chapter, using in vitro assays, we demonstrated that SPLUNC1 contributes to airway mucosal protection against neisserial adhesion and invasion of epithelial cells. Therefore, we propose that SPLUNC1 plays an important role in host defence against respiratory pathogens. In view of these findings, coupled with the knowledge that, the heterozygous missense variant SPLUNC1 (c.65G > A p.G22E) has never been identified previously other than in those three IMD patients and its high evolutionary conservation among mammals and in a functional domain, led us to hypothesise that this rare missense mutation may alter the function of SPLUNC1 in host respiratory epithelium defence mechanism, thereby conferring susceptibility to IMD in otherwise healthy individuals.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 103 -

5.1. Overexpression of SPLUNC1 variants in epithelial cell lines: 16HBE14, CALU-3, HEK293 and CORL-23

In order to address the potential pathogenic effect of the missense G22E mutation, we initially used transient transfection to overexpress the SPLUNC1 variants in disease relevant cells. This allowed us to introduce the wild type and G22E allelic mutants, in the form of plasmid DNA, into various human epithelial cells to study the gene function, as well as the resulting protein functions on an individually comparable basis. For these assays, we purchased the wild type SPLUNC1 expression plasmid from Origene (NC accession: NM_130852) for the clone RC203060, and manually introduced the point mutation SPLUNC1 c.65G>A, p.G22E using site directed mutagenesis, as described previously in Chapter 4, section 4.2. As transiently transfected genes do not incorporate into the destination cell genome, the expression lasts only for a short period. As the efficacy of the transfection is dependent on the individual cell type being used, the procedure requires optimisation in each case.

In addition to the human 16HBE14 respiratory cell line, we used CALU-3 derived from human lung adenocarcinoma cells, human HEK293 derived from epithelial kidney cells, and CORL-23 cells derived from human lung large cell carcinoma. These cells were all selected as being suitable for this work due to either technical ease or biological relevance to Nm infection (Grifantini et al., 2002; Hey et al., 2013; Sutherland et al., 2010). To achieve optimal transient transfection in these cell lines, measures such as high efficiency of transfection, low cell toxicity, minimum effects on normal physiology and reproducibility of results were considered. For this procedure, lipofectamine LTX with plus reagent, known to produce high transfection efficiency in technically challenging cell types, was used for transfection of 16HBE14, CALU-3, or CORL-23 cells, whereas lipofectamine 2000 was used with HEK293 cells, as it is easier to transfect.

A more detailed transfection protocol can be found in Materials and Methods Section 2.5.2). Briefly, the underlying principle involves the use of cationic lipid, in the form of lipofectamine, forming a lipid-nucleic acid complex in a serum free media, which then gets introduced to a semi-confluent monolayer of cells, and introduction of these pre-

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 104 - formed complexes to the cell allows them to fuse to the negatively charged cell membrane. The lipid-nucleic acid complex is taken up by the cells via phagocytosis/ endocytosis, and the transfected DNA is then transported to the nucleus to be expressed (Kim and Eberwine, 2010).

Initial optimisation experiments were performed by co-transfecting the gene of interest with GFP encoding plasmid, pEGFP. Cells were harvested at 24 hours post transfection and visually assessed by fluorescent microscopy for transfection efficiency, whereby the cells successfully transfected with GFP emitted a fluorescent signal expressed by the cells. The efficiency was determined with a range of DNA concentration: lipofectamine ratios and cell densities in 24 well plate formats.

According to the manufacturer’s instructions, cells needed seeding the day before and should reach 70 – 90 % confluency at the time of transfection. In 24 well plate format, the optimal seeding density for all cell lines was determined to be 1 x 105 cells per well. For all transfection procedures, the total concentration of plasmid DNA per well was kept at 500 ng, to reduce cytotoxic effects and cell death. We found 1.5 µl of L2000 and 2 µl of LTX with 0.5 µl of plus reagent produced the highest percentage of transfected cells, and also the highest fluorescence intensity (Figure 5.1). Thus, these transfection conditions were used in all future experiments.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 105 -

Phase GFP Merge

0.5 µl LTX

1.0 µl LTX

1.5 µl LTX

2.0 µl LTX

Figure 5.1: Optimisation of transient transfection in epithelial cell lines, demonstrated using 16HBE14. Cells were seeded at 1 x105 cells per well in 24 well plates. The next day, the cells reached 70 – 90 % confluency for transfection. 500 ng of total DNA was diluted in Optimem and mixed with 2 µl of LTX or 1.5 µl of L2000 and allowed to form DNA-lipid complexes. After 5 minutes, the DNA-lipid mixture was added to the cells in 10 % serum containing media. After 24 hours, the transfection efficiency was observed by fluorescent microscopy. Representative images of 16HBE14 cell transfection with increasing amounts of lipofectamine (0.5 µl – 2 µl).

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 106 -

5.1.1. Testing the overexpression of SPLUNC1

5.1.1.1. qPCR analysis of SPLUNC1 overexpression

Next, we wanted to determine if the expression at the protein level is consistent with expression at transcription level. Hence, we isolated RNA samples from the epithelial cells following 48-hour transfection, prepared cDNA via reverse transcription, and determined SPLUNC1 gene expression using Taqman based qPCR. This required transient transfection of epithelial cells (16HBE14, HEK293, and CORL-23) using methods outlined as above. At 48 hours post transfection, total RNA samples were isolated from cells cultured in 24 well plates. The RNA isolation involved removing media from wells following transfection, washing cells in PBS, followed by scraping and resuspension in 50 µl RNA-later buffer per well. From here on, the total RNA was extracted with the additional DNase-I step using the manufacturer’s protocol as described previously (see details in Section 2.4.1.). The resulting total RNA was reverse transcribed to make cDNA, and 50 ng of each sample was used as a template for the subsequent Taman quantitative RT-PCR assay for quantification of SPLUNC1 expression.

The level of SPLUNC1 mRNA expression was consistent with protein expression levels, in that at least 1 fold increase was detected when 16HBE14, HEK293 and CORL-23 cells were transfected with 100 ng of pSPLUNC1-G22E mutant compared with 100 ng of pSPLUNC1-WT (Figure 5.2). Although the difference in expression was not so obvious in 16HBE14 cells, the overall trend was in the same direction as with the other two cell lines. However, there was no difference found when the cells were co-transfected with equal amounts of pSPLUN1-WT and pSPLUNC1-G22 mutant plasmids compared with cells that were individually transfected with either plasmid. One possibility is that the difference in protein expression may be a consequence of differences at the post-translational level e.g. modification or translocation of mature folded protein to the cell membrane for secretion, as SPLUNC1 is a secreted protein.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 107 -

Figure 5.2: Overexpression of SPLUNC1-WT and SPLUNC1-G22E allelic mutant in in human epithelial cells analysed by qPCR. SPLUNC1 expression was quantified using qPCR in human epithelial cell lines upon transient transfection with 100 ng of pSPLUNC1-WT ( normal allele WT/WT), 50 ng of equal quantities of pSPLUNC1-WT and pSPLUNC1-G22E (heterozygous mutant allele WT/G22E) and 100 ng of pSPLUNC1-G22E ( mutant allele, G22E/ G22E) for 48 hours. Fifty ng of nucleic acid was used for individual RT-PCR reactions as template. SPLUNC1 mRNA expression is represented as relative induction to the housekeeping gene GAPDH. Experiments were performed at least two times independently per cell line. Error bars represent SD of one experiment done in triplicate.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 108 -

5.1.1.2. Western blot analyses of SPLUNC1 over expression

To better understand the consequence of the heterozygous missense SPLUNC1 (G22E) mutation, we assessed the expression of SPLUNC1 by western blotting. As described above for the transient transfection, cells were seeded at 1 x 105 per well in 24 well plates, and transfected on the following day using 500 ng of total plasmid, consisting of 100 ng of gene of interest (pSPLUNC1-WT or pSPLUNC1-G22E) complete with 400 ng of plasmid encoding empty-vector, pCMV6-empty. Wells containing 500 ng of empty vector or lipofectamine without any DNA were included as controls, in case if any unspecific effect produced from the transfection reagents or the downstream processes (as shown in Figure 5.3).

At 48 hours after transfection, protein samples were isolated by lysing cells in radioimmunoprecipitation assay (RIPA) buffer and total amount of protein quantified using Bradford reagent (see detailed protocol outlined in section 2.6.2). 25 µg of each sample was loaded and equal loading of samples was determined by probing blots for Glyceraldehyde 3-phosphate dehydrogenase (GAPDH). The level of SPLUNC1 expression upon transfection was assessed by probing blots using SPLUNC specific antibody (goat anti-hSPLUNC1, 1 : 2000 dilution) or DDK (mouse anti-DDK 1:1000 dilution), as the plasmids encoding SPLUNC1 variants were C- terminally fused with a DDK-tag. To ensure these antibodies were specifically targeting the protein of interest, 40 ng of rSPLUNC1-WT was used as a positive control. Anti-SPLUNC antibody recognised both recombinant and overexpressed homologs of SPLUNC1, as evidenced by the detection of an approximately 26.7 kDa band corresponding to the estimated size of the protein of interest. Whereas, anti- DDK antibody recognises the overexpressed form of SPLUNC1 only, as the tag is specific to the plasmid encoding the SPLUNC1 variants. The detection with anti-DDK antibody corresponds to slightly larger size of 28.8 kDa, due to the MYC-DDK tags (as shown in Figure 5.3).

In the absence of recombinant control or overexpression, there was no signal detected from the control wells. The absence of signal from wells without exogenous SPLUNC1 confirmed that the epithelial cells (16HBE14, HEK293, CORL-23) do not endogenously express the protein of interest. Hence, the signal is solely due to the exogenous addition of SPLUNC1 i.e. recombinant protein control or overexpression

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 109 - from recombinant plasmid. The immunoblotting analysis of complete epithelial cell lysates likewise showed marked increase in expression of G22E mutant (approximately 1 – 1.5 fold higher) compared with that of wild type SPLUNC1 (Figure 5.3).

Since WES identified missense variant G22E being heterozygous in all three IMD cases, we sought to determine whether the variant in heterozygous versus allelic forms might affect the expression of SPLUNC1 differently. For this, epithelial CORL- 23 and HEK293 cells were transiently transfected with 400 ng of empty-vector complete with either 100 ng of pSPLUNC1-WT, or 50 ng of equal mixture of each pSPLUNC1-WT and pSPLUNC1-G22E, or 100 ng of pSPLUNC1-G22E. At least 1 fold increase was detected in expression of SPLUNC1 in whole cell lysates of CORL-23 or HEK293 cells transfected with either heterozygous or G22E mutant compared with SPLUNC1-WT plasmid. The band intensities between heterozygous and G22E alleles were comparable and were noticeably different from that of wild type SPLUNC1 allele (Figure 5.4). The results demonstrate that the expression of potentially pathogenic G22E allelic mutant is markedly increased compared to that of wild type SPLUNC1 upon overstimulation in number of cell lines. Although this increased expression of the G22E mutant could be an indication of the functional impact of this missense mutation at the protein level, a precaution needs to be taken when interpreting data from transient transfection systems, as these results do not extend to the details on the post-translational processing of the expressed protein. We cannot dismiss the possibility of the G22E mutant protein being inappropriately processed, leading to aggregation inside the cell, compared with the wild type SPLUNC1, which is conversely processed appropriately and subsequently secreted out of the cells, thereby avoiding aggregation.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 110 -

HEK293 cells

16HBE14 cells

Figure 5.3: Overexpression of SPLUNC-WT and SPLUNC1–G22E allelic mutant in human epithelial cell lines analysed by western blotting. Anti-DDK targeting the C-terminal tag on SPLUNC1 expression clones was used to detect overexpression in 25 µg of whole cell lysates. GAPDH was included as a loading control. Band intensity of SPLUNC1 expression from WT and G22E mutants were normalised to GAPDH expression and represented as relative expression level of SPLUNC1. Quantification analysis carried out using Image J and results represented as mean ± SEM from at least two biological replicate samples.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 111 -

Figure 5.4: Comparing expression of heterozygous, wild type SPLUNC1 and G22E mutant. Human COR-L23 and HEK293 cell lines were transfected with either 100 ng of pSPLUNC1-WT or 100 ng of pSPLUNC1-G22E plasmids independently or 50 ng of equal mixtures of these plasmids. Anti-SPLUNC diluted 1:2000 to detect SPLUNC1 expression specifically, while anti-DDK diluted in 1:1000 was used to target the DDK tag on the plasmid backbones used for transfection. Protein bound antibodies were developed using ECL western blotting solutions, and analysed using Image J software.

5.2. Pro-inflammatory cytokine production after stimulation with LPS or HK Nm

To further characterise the impact of the missense G22E mutation in Nm infection, we evaluated the cytokine production of SPLUNC1 expressing cells following

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 112 - stimulation with PAMPs, such as LPS or heat-killed Nm (HK Nm). We have established through our overexpression optimisation assays that SPLUNC1 expression is at the optimal level between 24 and 48 hours. Human epithelial 16HBE14 cell line, known to express TLR-4 receptors (Greene et al., 2005) was firstly transiently transfected in 24 well plates, as described above. At 24 hours post transfection, culture media were removed and replaced with a fresh complete growth media, followed by 24 hours stimulation with varying concentrations of LPS (0.1 – 1 µg per ml) or HK Nm (106 - 108 CFU per ml). Cell supernatants were collected and cytokine concentrations were measured by ELISA-based assays to determine whether the SPLUNC1 expressing cells influence cytokine production levels during early infection. Non-transfected and mock-transfected cells were included as controls for the transfection condition and reagents used.

As epithelial cells are not specialised immune cells, we failed to observe any detectable amounts of pro- or anti- inflammatory cytokines or chemokines such as IL-1β, TNF-α, IL-10 or IFN-γ after stimulation. We found similar levels of IL-8 cytokine induction from cells regardless of their SPLUNC1 expression, but the magnitude of the response in both IL-6 and IL-8 were consistently elevated in supernatants from G22E allelic mutant expressing cells compared with those from wild type SPLUNC1 expressing cells (Figures 5.5 and 5.6).

There was a significant rise of IL-6 activation after stimulation with various concentrations of LPS in supernatants from 16HBE14 cells transfected with pPCMV6-empty vector compared with that of pSPLUNC1-WT cells (P < 0.001), indicating the expression of SPLUNC1 possibly reduces IL-6 production by 16HBE14 cells (Figure 5.5 A). Similar trend was seen with pSPLUNC1-WT cells following stimulation with HK Nm compared with that of pPCMV6-empty cells, although the difference was not statistically significant (Figure 5.5 B). Transfection with the pSPLUNC1-G22E plasmid resulted in a significantly higher IL-6 cytokine induction upon LPS and HK Nm stimulation compared with pSPLUNC1-WT cells (P < 0.001), suggesting that the G22E allele may alter the cytokine production in response to stimuli.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 113 -

16HBE14 cells 2500

)

l Non-stimulated

m / 2000 g LPS ( 0.1 g/ml)

(

n LPS ( 0.5 g/ml) 1500

c LPS (1 g/ml)

u 1000

p 500

I 0 d k T E e c ty 2 t o p W 2 c 1 fe M m G s E C 1 n N C a U r L N -t U n P L o S P N S

16HBE14 cells 3000

)

l Non-stimulated

m / 6 g Heat-killed Nm (10 cfu/ml)

( 2000 7 n Heat-killed Nm (10 cfu/ml)

c 8

u Heat-killed Nm (10 cfu/ml)

o 1000

I 0 d k T E e c ty 2 t o p W 2 c 1 fe M m G s E C 1 n N C a U r L N -t U n P L o S P N S

Figure 5.5: IL-6 response to LPS and HK Nm in cells expressing SPLUNC1 variants. Human 16HBE14 epithelial cells were transfected with empty plasmid and SPLUNC1 variants for 24 hours and subsequently stimulated with varying concentrations of (A) LPS or (B) HK Nm. IL-6 cytokine concentrations in cell supernatants were measured after 24 hour stimulation using a standard ELISA. Results are represented as mean ± SD of three replicates of each condition repeated at least three independent times.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 114 -

We also observed significant reduction in IL-8 induction by pSPLUNC1-WT expressing cells upon stimulation with LPS compared with that of empty control expressing cells (P < 0.001), and stimulation with HK Nm showed a trend toward lower IL-8 production, as with IL-6 induction, however the difference was not significant (Figure 5.6). These results together with previous study using Splunc1 knockout mouse infection model (Liu et al., 2013c) may suggest that SPLUNC1 is a key regulator of the host inflammatory response against Gram-negative bacterial infections, which may help to prevent over activation of cytokine production and minimize damage to host tissues, as is seen in severe IMD cases (Waage et al., 1989).

The raised IL-8 production in non-stimulated 16HBE14 cells of different genotypes indicates the transfection procedure resulted in an increase in the basal inflammatory response due to unknown mechanisms. We suspected this could be due to contamination of the plasmid encoding the empty vector, but found there was no difference when different empty vectors were tested (Figure 5.7). Thus concluded, it was possibly due to the nature of the epithelial cell response to stimuli i.e. transfection with plasmid.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 115 -

A. 16HBE14 cells

1500

)

l Non-stimulated

m /

g LPS ( 0.1 g/ml)

( 1000

n LPS ( 0.5 g/ml)

c LPS (1 g/ml)

o 500

L I 0

d k T E e c ty 2 t o p W 2 c 1 fe M m G s E C 1 n N C a U r L N -t U n P L o S P N S

B. 1 6 H B E 1 4 c e lls

1 5 0 0 )

l N o n -s tim u la te d

m / 6 g H e a t-k ille d N m (1 0 c fu /m l)

p (

1 0 0 0 7

n H e a t-k ille d N m (1 0 c fu /m l)

i t

c 8

u H e a t-k ille d N m (1 0 c fu /m l)

o 5 0 0

r p

8 -

L I 0

d k y T E e c t 2 t o p W c 2 M m 1 G fe E C s N 1 n C a U r L N -t P U n S L o P N S

Figure 5.6: IL-8 cytokine response to LPS and HK Nm in cells expressing SPLUNC1 allelic variants. Human 16HBE14 epithelial cells were transfected with empty plasmid and SPLUNC1 variants for 24 hours and subsequently stimulated with varying concentrations of (A) LPS or (B) HK Nm. IL-8 cytokine concentrations in cell supernatants were measured after 24 hour stimulation using a standard ELISA. Results are represented as mean ± SD of three replicates of each condition repeated at least independent times. Host genetics and outcome in meningococcal disease: a systematic review and meta-analysis

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 116 -

16HBE14 cells non-stimulated LPS (0.1 µg/ml) 800 600 400

200

8 production 8 (pg/ml) -

IL 0

Figure 5.7.IL-8 production in epithelial cells transfected with various empty plasmids. 16HBE14 cells were transfected with several empty plasmids for 24 hours and subsequently stimulated with TLR-4 ligand LPS at a final concentration of 0.1 µg/mL for 2 hours. The cytokine concentrations were determined by ELISA and data from three replicates are plotted as mean ± SD.

5.3. Creating stably transfected SPLUNC1+/+ cell lines

To explore further the role of the missense SPLUNC1 p.G22E mutation in susceptibility to IMD, we made several attempts to create cell lines that would constitutively express SPLUNC1 allelic variants. In contrast with transiently transfected genes, stably transfected genes are incorporated into the host genome and sustain expression even after the host cells replicate. Hence stable transfection allows long-term as well as defined and reproducible expression of the gene of interest (Kim and Eberwine, 2010). SPLUNC1 is a secreted protein and our functional studies have showed that it plays an essential role in inhibiting neisserial adhesion and invasion; therefore, we wanted to create an in vitro model system to assess the functional impact of the candidate mutation in the disease relevant context.

A previous study investigating the role of SPLUNC1 in respiratory bacterial infection has used human CALU-3 cells for stable expression of SPLUNC1 (Liu et al., 2013a). As polarised CALU-3 monolayers can differentiate to form tight junctions and produce cell secretion in the form of mucin, these cells have successfully been used

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 117 - for studying host pathogen interactions, and transversal of the epithelial barrier by Nm (Sutherland et al., 2010). In addition to CALU-3 cells, 16HBE14 and HEK293 cells were also used for stable transfection of SPLUNC1.

The technical notes for establishing stable cell lines are outlined in Material and Methods. Briefly, the SPLUNC1 gene variants were cloned out of the expression SPLUNC1 constructs and sub-cloned into the packaging vector, pEmpty-lenti-C- Myc-DDK-IRES-Puro. Lentiviral constructs were co-transfected into HEK293 cells along with plasmids encoding VSV-G (envelope vector), and Gag-Pol (packaging vectors) using a Calcium phosphatase transfection kit. The pEmpty-lenti-C-Myc- DDK-IRES-Puro encodes the viral long terminal repeats (LTRs), so co-transfection with viral envelop and packaging vectors allow generation of infectious transgenic lentiviral particles containing our constructs of interest.

At 48 and 72 hours following the transfection, supernatants containing the SPLUNC1 incorporated pseudo viral particles were harvested, filtered and used for infecting desired cell lines. In theory, the infection of cells with pseudoparticles results in incorporation of constructs into the host cell genome and expression of the gene of interest when the cells replicate. Successful incorporation of the target gene can be assayed using a selection marker, in this case the puromycin resistant gene, to expand only the cells of interest. This selection marker is then used for maintenance of the SPLUNC1 expressing cells in the long term.

5.3.1. Generation of lenti-SPLUNC1 constructs

The sub-cloning of SPLUNC1 expression cDNA constructs into the pEmpty-lenti plasmid involved restriction digestion of both destination and expression clones with AsiSI and Mlul-HF enzymes, ligating insert with pEmpty-lenti backbone and subsequent transformation into E. coli TOP10 competent cells. The use of these unique restriction enzymes for digestion of both current and destination vectors allowed directional cloning of the cut insert (encoding SPLUNC1) into the destination vector, pEmpty-lenti, in a known orientation (Figure 5.8A). Several attempts were made to generate the SPLUNC1 expression constructs. Incomplete double digestion of the SPLUNC1 expression clones, insufficient ligation into pEmpty-lenti vector, and plasmid contamination between SPLUNC1 variants were all problems encountered.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 118 -

However, after resolution of these individual issues, constructs containing the correct inserts yielded recombinants with an estimated size of 8.3 Kb. Constructs encoding the different SPLUNC1 allelic variants were confirmed by PCR using cDNA specific primers (cSPLUNC1_for and cSPLUNC1_rev) yielding approximately 983 bp amplicons (Figure 5.8B), and subsequent sequencing confirmed individual clone identities (data not shown). The final constructs, pSPLUNC1-WT_lenti and pSPLUNC1-G22E_lenti, were transformed into E. coli TOP10 competent cells and plasmid DNAs were purified using a maxi-prep kit (Qiagen).

A. B.

Figure 5.8: Schematic diagram of the sub-cloning of cDNA SPLUNC1 allelic variant clones into pEmpty-lenti vector. Plasmids encoding the SPLUNC1-WT and –G22E allelic mutant as well as the destination vector, containing the leniviral packaging vectors, were all digested using unique restriction enzymes, MluI and SgfI. Complementary sticky ends from the insert were annealed and ligated into pEmpty-lenti—Puro backbone (A) and transformed into TOP10 competent cells. (B) Successful ligations were identified by PCR amplification yielding an amplicon of approximately 983 bp. The diagram was made with SnapGene.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 119 -

5.3.2. Transduction and selection of stable SPLUNC1 constructs

As described above, the pSPLUNC1-WT_lenti or pSPLUNC1–G22E_lenti constructs were transiently co-transfected into HEK293 cells with viral packaging/ envelop vectors to generate viral pseudoparticles. Viral particles containing the packaged constructs were then used for infecting 16HBE14, CALU-3 and HEK293 epithelial cells to generate stable SPLUNC1 expression. Briefly, the epithelial cells were plated in 6 well plates to reach approximately 50 % confluency the next day. One hundred µl, 250 µl or 500 µl of aliquots of the pseudoparticles were used to infect each cell type, and wells containing media alone were included as a control. Infectious particles were removed from the media 6 hours post inoculation and replenished with fresh complete growth media. At 48 hours post infection, puromycin was added to all wells and successful recombinants were expanded in the selection media. Cells plated in control wells died 24 hours after the selection.

5.3.3. Determination of stable SPLUNC1 expression

5.3.3.1. Western blot analysis of SPLUNC1 overexpression

The overexpression of SPLUNC1 variants in stably transduced 16HBE14, CALU-3 HEK293 epithelial cells, was determined from cultures grown at the ALI or in whole cell lysates by western blotting. For growth of epithelial cells in ALI cultures, CALU-3 and 16HBE14 cells were used, as these differentiate and form tight junctions – resembling the squamous epithelial cells of the nasopharynx (O'Dwyer et al., 2009; Sutherland et al., 2010). Epithelial cells were cultured at the ALI and apical washes were processed as outlined in section 2.6.2. Briefly, to isolate proteins from whole cell lysates, cells were lysed in RIPA buffer and their concentration quantified using the Bradford reagent against a BSA standard curve. Twenty five µg of each sample was separated by SDS-PAGE, and identification of SPLUNC1 was determined by probing with SPLUNC1 specific (human anti-PLUNC) or anti-DDK antibodies.

The level of SPLUNC1 expression was comparable for SPLUNC1-WT_lenti and pSPLUNC1–G22_lenti mutant constructs. These results did not replicate the activating expression levels of transient transfection with G22E allelic mutant compared to wild type SPLUNC1. In general, the stably transduced cells expressed

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 120 - less SPLUNC1 compared with that of transiently transfected cells (Figure 5.9). We suspected the low level of SPLUNC1 expression in stably transduced cells was likely due to the low copy number of constructs integrated into the host genome. It is commonly understood that transiently transfected cells will in comparison have a much higher copy number of the gene. Hence, it was possible that the higher expression of the G22E allelic mutant from stably transduced cells would not be obvious due to low expression.

Figure 5.9: Expression of SPLUNC1 from stably transduced 16HBE14 and CALU-3 cells by western blotting. Human anti-SPLUNC1 used at 1:1000 dilution to detect the SPLUNC1 expression in lentiviral transduced cell lies. Twenty five µg of whole cell lysates from each sample were loaded. SPLUNC1 expression is represented as relative intensity to loading control GAPDH. Quantification analysis carried out using Image J, and results represented as mean from at least two experimental replicate samples.

The formation of tight junctions in both CALU-3 and 16HBE14 cultures grown at the ALI were confirmed by monitoring the trans-epithelial resistance using a volt-ohm meter (Figure 5.10). The tight junction was maintained up to 14 days by both CALU- 3 and 16HBE14 cells. Despite repeated attempts, we did not detect the secreted form of SPLUNC1 in supernatants of the stably transduced cell lines.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 121 -

Figure 5.10: Development of tight junctions of CALU-3 and 16HBE14 monolayers. Cells were seeded and the ALI created 2 days after cell seeding, by removing the media from the apical side. Media in the basolateral chamber was changed and level of TEER was monitored every other day. The results shown are from representative of two independent experiments.

5.3.3.2. Cytokine measurements of stable transfectants

The stable SPLUNC1 variant expressing epithelial cells were stimulated with LPS and HK Nm, as done previously with transiently transfected cells, to determine their cytokine response. Briefly, cells were plated in 24 well plates at density of 5 x 105 and stimulated with varying concentrations of the agonists. Supernatants were collected after 24 and 48 hours following the stimulation and IL-6 levels were determined using ELISA. There were marked differences in the IL-6 response to LPS and HK Nm by different genotypes. The inflammatory response from the stably transfected SPLUNC1-G22E allelic mutant was significantly elevated compared with that of pSPLUNC1-WT plasmid expressing cells (Figure 5.11), consistent with previously shown with transient transfected cells.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 122 -

2 4 h r s tim u la tio n

1 0 0 0 N S

L P S 1 0 0 n g /m l 8 0 0

) H K M C 5 8 1 0 ^ 6 C F U /m l

l m / 6 0 0 H K M C 5 8 1 0 ^ 7 C F U /m l

(

6 4 0 0

- L I 2 0 0

T E 2 W 2 1 G C N 1 U C L N P U S L P 4 1 S E 4 B 1 H E 6 B 1 H 6 1

4 8 h r s tim u la tio n

1 0 0 0 N S

8 0 0 L P S (0 .1  g /m l) )

l m

/ 6 0 0 H K M C 5 8 (1 0 ^ 6 c fu /m l)

(

6 4 0 0 H K M C 5 8 (1 0 ^ 7 c fu /m l)

L I

2 0 0

T E 2 W 2 1 G C N 1 U C L N P U S L P 4 1 S E 4 B 1 H E 6 B 1 H 6 1

Figure 5.11: Inflammatory cytokine response in stably transfected SPLUNC1 expressing cells after stimulation with TLR-4 agonists. 16HBE14 cells were plated in 24 well plates and stimulated with varying concentrations of LPS or HK Nm. IL-6 production was measured in supernatants from 24 hour or 48 hours post inoculation. Results are represented as mean ± SEM from three independent experiments. Two-way ANOVA with Tukey’s correction testing was used to determine statistical significance of cytokine responses of different genotypes.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 123 -

5.4. LPS binding assay

Previous investigators have demonstrated that SPLUNC1, belongs to the family of neutrophil proteins such as BPI and LBP, and thus share the ability to bind directly to LPS expressed on the outer surface of Gram-negative bacteria such as E. coli and P. aeruginosa (Ghafouri et al., 2004; Sayeed et al., 2013). In humans, the antimicrobial and immuno-modulatory role of these antagonistic LPS binding proteins in host response to Gram-negative bacteria, including Nm is well documented (Dentener et al., 1993). LPS binding ability of BPI confer diverse range of innate immune responses, including direct bacterial killing, endotoxin neutralisation activity, opsonisation of bacterial surface to promote phagocytocysis by neutrophils and monocytes, and inhibition of LPS induced cytokine production by peripheral blood mononuclear cells. In contrast, LBP activates CD14+ macrophages and results in increased production of pro-inflammatory cytokines, including TNF-α and IL-1β, which subsequently regulate recruitment of neutrophils (Dentener et al., 1993; Schultz and Weiss, 2007; Weiss, 2003).

Based on these observations, we investigated the LPS binding capacity of SPLUNC1 to LPS derived from Gram-negative bacteria such as Nm and S. Minnesota and whether the G22E mutation has an impact on this proposed function. As outlined in Material and Methods, an adapted version of the ELISA based LPS binding detection method was used to determine how wild type rSPLUNC1 interacts with Nm LPS and whether the G22E allelic mutant impacts the LPS binding ability of SPLUNC1. Briefly, a 96-well flat bottom microtitre plate was coated with 200 ng of purified LPS from Nm serogroup B or S. Minnesota overnight, wells blocked with 0.05 % PBST and rSPLUNC1-WT and rSPLUNC1–G22E allelic mutant protein serial dilutions were added to attach to plate surface bound LPS. Wells containing buffer alone was included as a negative control. As we were unable to source wild type Nm LPS, we used LPS from the serogroup B Nm lgtB mutant, which lacks the terminal galactose residue and has been reported to specifically mediate dendritic cell (DC) driven immune response, but is not known to impact binding to surface proteins (Steeghs et al., 2006). Nm LPS interaction with rSPLUNC1 was evaluated using a SPLUNC1 specific antibody. There was no interaction detected from wells with buffer alone. There was no difference in the LPS binding capacity between recombinant

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 124 - wild type SPLUNC1 and G22E mutant proteins, although we observed stronger binding of SPLUNC1 proteins to S. Minnesota LPS compared with that of Nm LPS (Figure 5.12).

S .M in n e s o ta L P S (S P L U N C 1 -W T )

S .M in n e s o ta L P S (S P L U N C 1 -G 2 2 E )

N m L P S (S P L U N C 1 -W T ) 2 .0 N m L P S (S P L U N C 1 -G 2 2 E )

)

m n

1 .5

5 4

O (

1 .0

c n

b r

o 0 .5

s b

0 .0 0 1 0 0 2 0 0 3 0 0

C o n c e n tr a tio n (n g )

Figure 5.12: LPS binding ability of SPLUNC1 variants. Binding of LPS from S. Minnesota or Nm with increasing concentration of rSPLUNC1 variants was analysed. Data are plotted as mean ± SD from three independent experiments. Student’s t-test was used to assess difference in LPS binding abilities of SPLUNC1 allelic variants.

5.5. Effect of G22E on anti-biofilm activity

As we have established in our previous section (Chapter 4) that wild type SPLUNC1 plays an essential role in inhibiting early biofilm formation of Nm on abiotic surfaces, we asked the question whether the G22E allelic mutant may influence this activity. So we assessed the ability of the G22E mutant using the same experimental set up as we did for assessment of wild type SPLUNC1 ability to inhibit Nm biofilm Section 4.1.1). As the G22E missense mutation is located in the N-terminus, a previously described mutant lacking the whole N-terminus (ΔN SPLUNC1; amino acids 1 – 44, (Walton et al., 2016) was included to determine the specificity of the G22E mutant. It has been established in previous molecular studies that the N-terminus of the SPLUNC1 protein directly regulates the ENaC, which plays an important role in

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 125 - maintenance of homeostasis of the airway surface liquid (Garland et al., 2013), but has never been shown to regulate the anti-biofilm property.

In line with our previous finding, the treatment with wild type rSPLUNC1 significantly inhibited early biofilm formation of wild type Nm MC58, the biofilm biomass produced being comparable to that of the MC58 pilE- mutant (Figure 5.13; ** P < 0.001, * P < 0.05). Both the treatments with G22E allelic mutant and ΔN SPLUNC1 mutants were able to inhibit MC58 biofilm biomass, but at a markedly reduced level compared with the inhibition of wild type SPLUNC1. We conclude that SPLUNC1 requires an intact N-terminus for full inhibition of Nm biofilm in vitro. The effect was determined to be specific, as treatment with the control protein, BSA at the same concentration (10 µg / ml), had no effect on Nm biofilm biomass.

MC58 alone Control (BSA 10 g/ml) * rSPLUNC1 WT (10 g/ml) * ** rSPLUNC1 p.G22E (10 g/ml) 1.0 ) ** 0 rSPLUNC1 N (10 g/ml)

5 **

D 0.8

(

s 0.6

i 0.4

l i 0.2

i B 0.0 T - lE W i 8 p 5 8 C 5 M C M

Figure 5.13: SPLUNC1 inhibits Nm biofilm formation. Bacterial biofilm biomass formation on microtitre plates measured after 3 hours treatment in the absence or presence of wild type, G22E allelic mutant and ΔN mutant SPLUNC1 at 10 µg/ml using crystal violet staining (OD590). Protein control, BSA, was included for treatment specificity. Results are means ± SEM from three independent experiments.

5.6. Effect of G22E on bacterial adhesion and invasion

Having demonstrated the role of wild type SPLUNC1 in host defence against Nm adherence and invasion in an in vitro model, we tested the effect of the G22E mutant

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 126 - using models of cultivated epithelial cells. As mentioned above, we were not able to detect the secreted form of SPLUNC1 protein variants from the transiently or stably transfected cell lines, despite culturing cells at ALI, a technique which has shown to promote mucin like secretion in cultured epithelial cells such as CALU-3 (Liu et al., 2013a; Sutherland et al., 2010). As an alternative approach, we measured adhesion and invasion of Nm using previously established in vitro meningococcal colonization model with human 16HBE14 cell line in the presence of and absence of recombinant SPLUNC1 variants (obtained from our collaborators at the University of Pittsburg). Briefly, monolayers of 16HBE14 cells were grown to nearly 100 % confluency and inoculated with Nm MC58 in the absence or presence of rSPLUNC1 variants, including wild type, G22E and ΔN mutants at an MOI of 1 for 4 hours. BSA was included as a control to assess protein specificity.

There was marked reduction (4 fold decrease) in CFU of Nm adhered to human 16HBE14 epithelial cells in the presence of the recombinant G22E allelic mutant compared with wells with no exogenous protein or BSA at the comparable concentration (Figure 5.14A). The same level of inhibition of bacterial adherence to 16HBE14 cells was observed with the recombinant ΔN mutant, and the amount of adherent bacteria was significantly lower than that of blank control or BSA treatments (**P < 0.0001, *P <0.05).

In terms of SPLUNC1 effect on invasion into 16HBE14 cells, we found that there were approximately three orders of magnitude less Nm that had invaded compared to the numbers adhered to the epithelial cell surface (Figure 5.14B). The ability of the wild type SPLUNC1 to inhibit Nm adhesion was also reflected in the significantly reduced CFU of bacteria within epithelial cells. However, the reduced level of inhibition by the G22E mutant was less clear compared with that of wild type SPLUNC1, as we failed to observe any effect on Nm invasion in the presence of the G22E mutant protein (Figure 5.14B).

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 127 -

* *

* * 4  1 0 5

n s M C 5 8 a lo n e )

L C o n tr o l ( B S A 1 0  g /m l)

5 M

3  1 0 /

U S P L U N C 1 W T (1 0  g /m l) F

C * ( 5

2  1 0 S P L U N C 1 G 2 2 E (1 0  g /m l)

n * o

i S P L U N C 1  N (1 0  g /m l) s

e 1  1 0 5

d A

e l) l) l) l) n m m m m lo / / / / a g g g g     8 0 0 0 0 5 1 1 1 1 C ( ( ( A M T E N S 2  B W 2 ( 1 G 1 l C o C 1 r N N t C U n U N L o L U P C P L S S P S

* * 6  1 0 2 n s

M C 5 8 a lo n e )

L C o n tr o l ( B S A 1 0  g /m l)

M / 4  1 0 2

U S P L U N C 1 W T (1 0  g /m l)

F C

( G 2 2 E ( 1 0  g /m l)

n o

i 2

s 2  1 0

n I

e l) l) l) n m m m lo / / / a g g g    8 5 0 0 0 1 1 1 C ( ( M A T E S 2 W (B 2 l 1 G o C tr N n U o L C P S

Figure 5.14: The effect of the G22E mutant on Nm adhesion and invasion of human epithelial 16HBE14 cells. Monolayers of 16HBE14 were cocultured with MC58 in the presence of wild type or mutant rSPLUNC1 or control protein BSA. The number of Nm had adhered to (A) or invaded (B) the human 16HBE14 cells were obtained by plating on solid media and counting viable CFU. The data are represented as mean ± SD of three independent experiments for protein treatment comparison. The statistical significance (** P < 0.0001) was calculated using Two-Way ANOVA, with Tukey’s multiple correction testing.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 128 -

5.7. Molecular characterization and determining mechanisms underlying modified activity of the heterozygous missense G22E mutant

We then addressed the effect of the SPLUNC1 allele at the molecular level by quantitatively assessing the impact of the heterozygous and homozygous G22E SPLUNC1 alleles in our established in vitro models of adhesion and invasion of human epithelial cells by Nm. To mimic the different G22E allelic genotypes, we mixed different proportions of wild type and G22E recombinant proteins, the total concentration of each well adding up to 10 µg per ml (a concentration determined as physiologically active in previous assays). As before, the human epithelial monolayers were incubated with Nm at an MOI of 1, in the absence or presence of SPLUNC1 allelic proteins. Wells containing relevant protein control were included as a control.

We observed impairment of SPLUNC1’s ability to inhibit Nm adherence and invasion of human epithelial 16HBE14 cells when increasing proportions of G22E was mixed with decreasing proportions of wild type SPLUNC1 allele (Figure 5.15). All combinations of the G22E allele (10 µg/ml of G22E, 7.5 µg/ml of WT + 2.5 µg/ml of G22E, 5 µg/ml of WT + 5 µg/ml of G22E and 2.5 µg/ml of WT + 7.5 µg/ml of G22E) with the wild type allele performed relatively similar to the G22E allelic form. However, all wells containing the G22E allele performed less well in inhibiting Nm adhesion and invasion compared to the wild type SPLUNC1 allele. There was a dose dependent impediment in activity of wild type SPLUNC1 allele when supplemented with increasing amounts of the G22E allele (Figure 5.15). The data does not provide enough evidence to decipher if there is a haploinsufficiency at the SPLUNC1 locus or whether the G22E allele is dominant negative. Additional assays using varying concentrations of wild type SPLUNC1 control are required to resolve this question in the future.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 129 -

* * A. * *

n s 2 .5  1 0 5

) 5 *

L 2  1 0

M * /

U 5

F 1 .5  1 0 *

(

n *

o 5

i 1  1 0

e h

d 5  1 0 4 A

e l) l) l) ) ) ) n m m m o m m m / / / l / / / g g g a g g g       8 0 5 5 5 5 0 0 . ( . 1 1 (1 2 7 C ( ( ( E ( M A T E E 2 E 2 2 2 2 S W 2 G B 2 2 1 G G + G C 1 + l) + N C ) ) U N l /m l L U /m g /m P L g  g S P  (5  S 5 . T .5 7 2 ( W ( T T W W * * B. * 2

8  1 0 * * )

L * M

/ 6 1 0 2

U  n s

C (

n 2

o 4  1 0

s a

n i

2  1 0 2

5 C

M 0

e l) l) l) l) l) l) n m m m m m m lo / / / / / / a g g g g g g       8 0 0 0 5 5 5 5 1 1 . ( . (1 ( 2 7 C ( E ( M A T E S 2 E 2 E W 2 2 2 2 (B 2 G 2 l 1 G / o C 1 G l) G r / / t N C l) m l) n U N / o L /m g /m U  C P L g g   S P (5 5 5 S . T . 7 2 ( W ( T T W W

Figure 5.15: The mutant G22E SPLUNC1 allele impedes inhibition of Nm adherence and invasion by the wild type SPLUNC1 allele. Monolayers of 16HBE14 cells were incubated with MC58 at an MOI of 1 for 4 hours, in the absence and presence of or heterozygous SPLUNC1 wild type and G22E allelic mutants. The number of MC58 that adhered to (A) or invaded (B) human epithelial 16HBE14 cells in the presence of different allelic SPLUNC1 genotypes were evaluated by CFU counting from solid agar plates. Data are represented as mean ± SD from at least two independent experiments. Statistical significance (* P < 0.01, ** P < 0.0001) between genotypes were analysed using Two-way ANOVA with Tukey’s multiple correction.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 130 -

5.8. Discussion

We have shown previously that recombinant SPLUNC1 exhibits anti-biofilm activity on abiotic surfaces. The results of our epithelial colonisation model using polarised 16HBE14 human epithelial cells, also demonstrated that presence of SPLUNC1 significantly reduces adhesion and subsequent invasion by Nm, suggesting an important role of the protein in early host defence mechanisms against Nm colonisation. This study aimed to further characterize the host defence activity of SPLUNC1 against Nm at a molecular level and decipher the pathogenicity of the rare missense G22E mutation in the context of IMD.

Notably, significantly higher SPLUNC1 mRNA and protein expression was observed when the 16HBE14 cells were either transiently transfected or retrovirally transduced with the G22E mutant allele compared with the wild type allele, indicating that the mutation may alter the potential role of SPLUNC1 protein at a functional level. Previous studies have shown that SPLUNC1 is able to bind directly to bacterial LPS and mediate local inflammatory responses through recruitment of neutrophils and macrophages to site of infection (Thaikoottathil et al., 2012), and play a role in host defence against P. Aeruginosa (Sayeed et al., 2013). We show that human rSPLUNC1 is able to bind to LPS isolated from two different Gram-negative bacteria, including Nm and S. Minnesota. We did not detect any difference in LPS binding to wild type and G22E mutant protein, indicating the LPS binding site on the SPLUNC1 protein is perhaps distinct from the region accountable for the posited antibacterial roles such as anti-biolfilm and inhibition of Nm adhesion and invasion of epithelial layers. Previous studies have also suggested the possibility of SPLINC1 having distinct functional sites for its various proposed roles (Bartlett et al., 2011; Liu et al., 2013a; Walton et al., 2016). The potential binding of SPLUNC1 to LPS has been suggested to modulate LPS mediated innate and inflammatory responses to Gram- negative bacterial infection (Chu et al., 2007; Lukinskiene et al., 2011) as observed with several innate immune molecules including the β-defensins, the human cathelicidin LL37 and BPI (Ganz and Weiss, 1997; Schultz and Weiss, 2007).

One of the key regulators of immunological and inflammatory responses is the production of cytokines. In meningococcal infection, elevated cytokine levels are

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 131 - commonly correlated with disease severity and detrimental outcomes in patients. Therefore, a fine balance is critical to achieve an effective host defence (Pathan et al., 2003). We used transient and stable expression of SPLUNC1 to assess the potential implications of the G22E mutant after Nm challenge. Our results show that the G22E mutant expressing cells produced significantly higher production of pro- inflammatory cytokines (IL-6 and IL-8) compared with the wild type SPLUNC1 expressing cells at both basal level and following stimulation with LPS and HK Nm. We also found that the wild type SPLUNC1 expression was correlated with reduction of epithelial pro-inflammatory cytokine production induced by LPS or HK Nm. The latter result is consistent with earlier study by Chu et al. (2007), where expression of SPLUNC1 was induced following Mycoplasma infection in mice and human cultured cells, leading to higher IL-8 production and increased bacterial clearance. Lukinskiene et al. (2011) also showed that expression of Splunc1 exhibited higher bacterial clearance, reduced neutrophil infiltration and moderated pro-inflammatory cytokine and chemokine levels. However, the significant elevation in constitutive activation of IL-6 and IL-8 by the G22E overexpressing cells compared with wild type is suggestive of an excessive inflammatory response, which is commonly correlated with adverse effects on host tissues and increased risk of mortality, e.g. as seen with patients with meningococcal septic shock (Waage et al., 1989).

Despite several attempts to obtain transduced cells on semi-permeable inserts, we failed to detect SPLUNC1 in the epithelial cell surface secretions. To overcome these experimental challenges, rSPLUNC1 protein based on the G22E point mutation was generated to assess potential differences in allelic variants. The expression of the mutant allele was associated with impaired ability to inhibit early stages of meningococcal biofilm formation on abiotic surfaces. This impairment was also consistent when we used an in vitro meningococcal colonization model with human 16HBE14 epithelial cells, where marked increase in Nm adhesion and subsequent invasion was detected. The effect of the G22E mutation does not result in complete lack of function of the protein, but rather in partial impairment, as there were still significant levels of reduction in bacterial attachment and invasion of epithelial cells compared with protein control or cultures without any exogenous protein. This indicates that the degree of partial impairment elicited by the

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 132 - heterozygous mutant protein may in turn directly impact the ability of meningococcus to colonise the nasopharynx, and act as determinant of increased susceptibility to Nm infection.

It has been demonstrated that the N-terminal region of SPLUNC1 (G22 – A39) is involved in protection of the ENaC, which protects airway surface liquid volume from proteolytic cleavage (Garland et al., 2013). Given the location of our rare mutation within this functional region, it is possible to assume that it may increase susceptibility to Nm infection in other ways. In the present study, we showed that complete N-terminus deletion (ΔN) of SPLUNC1 results in the same level of impediment as the G22E mutant, as evidenced by the levels of reduction in ability to inhibit Nm adherence and invasion. Constitutive expression of SPLUNC1 was shown to mediate mucosal surface liquid volume and proposed to facilitate clearance of microorganisms from the airway (Garcia-Caballero et al., 2009), an important host defence mechanism employed in protection against invading Nm (Carbonnelle et al., 2009). Therefore, any genetic mutation that causes diminished SPLUNC1 activity, and thus reduced airway surface liquid volume in an ENaC dependent manner, is postulated to impact on mucociliary clearance (Garcia-Caballero et al., 2009). However, our failure to produce different allelic SPLUNC1 expressing cell types did not allow the investigation of the relationship between mutations in the protein, mucosal ciliary clearance and increased susceptibility to Nm disease.

In summary, this study showed that the rare missense mutation found in the three IMD cases results in modified expression of SPLUNC1 at transcriptional as well as translational levels. The expression of G22E mutant in human epithelial cells results in marked increase in pro-inflammatory cytokine production after stimulation with HK Nm and LPS. We also show that SPLUNC1 has the capacity to directly bind to Nm LPS and the missense mutation does not impact this ability. We also show that the G22E mutant has impaired ability to prevent early Nm biofilm formation on an abiotic surface as well as in our colonization models of cultivated epithelial 16HBE14 cell (adhesion and invasion assays), resulting in increased susceptibility to Nm colonisation. Although further functional investigation is required to determine whether its haploinsufficiency at the G22E locus or that this allele is dominant negative. Taken together, these results suggest that the G22E mutation may

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 133 - contribute to impaired host defence against Nm and thereby lead to increased susceptibility to IMD in the carriers.

V – Characterisation of G22E mutation using in vitro models of cultivated epithelial cells - 134 -

Chapter 6

VI – Investigating the role of GWAS candidate SNPs in IMD - 136 -

6. Investigating the role of GWAS candidate SNPs in IMD

The work in this chapter follows up a single nucleotide polymorphism, and proxy variants in strong linkage disequilibrium (LD), in a long non-coding RNA gene found to be associated with severity of invasive meningococcal disease from a GWA study. The details of the study participants, a brief description of the GWAS analyses carried out by Dr.Clive Hoggart (Imperial College London) and the investigations undertaken to functionally validate these genome-wide association study findings are all outlined.

6.1. Genome-wide study participants

Meningococcal disease was diagnosed in the patients who presented with a distinguishing petechial or purpuric rash and clinical presentations of severe septicaemia and/or meningitis. The causative pathogen was microbiologically confirmed by culture of Nm from CSF or blood or by PCR amplification of Nm DNA from blood. The affected cases consisted of three separate European cohorts pooled together. The UK patient cohort (n = 475) have been previously described (Binder et al., 2007; Emonts et al., 2010; Haralambous et al., 2003). Briefly, the samples were collected from the PICU at St Mary’s Hospital, London between 1995 and 2008 and from MRF charity between 1995 and 2002, with median ages 3 and 11 years respectively. The Spanish affected cases (n = 417) were enrolled through the Spanish Meningococcal Disease research network ESIGEM between 2006 and 2009. The combined Austrian and Dutch cohorts (n = 344) enrolled via the PICU of either Erasmus MC Sophia Hospital and Emma Children’s Hospital, The Netherlands between 1988 and 2005 (median age of 3) or the Medical University of Graz

VI – Investigating the role of GWAS candidate SNPs in IMD - 137 - between 2000 and 2007 (median age 4 years) respectively. More detailed information on these cases can be found in previous studies (Davila et al., 2010; Martinón-Torres et al., 2016). For each individual case cohort, ethnically matched controls were included.

6.2. GWAS analyses

To understand genetic determinants of meningococcal disease, both susceptibility and severity analyses were performed. However, we describe here only the severity analyses because the present functional characterisation study deals with this aspect of the work. Genotyping for cases and controls were performed using the Illumina Human 610K Quad BeadChip, except for the UK controls (accessed data with permission from the Wellcome Trust Case-Control Consortium 2 study), which were genotyped with 1.2M chip. SNPs found to be of poor quality (SNPs with call quality of < 95 %) in either cases or controls were excluded from the analyses. I Imputation was performed using the 1000 Genomes (Abecasis et al., 2012) and the European CEU HapMap population reference panels. Genome-wide meta-analyses of significant association with numerous severity phenotypes of IMD (see Tables 6.1 – 6.2) were evaluated using linear and logistic regression methods for continuous and binary traits respectively, The top two principal components were included as covariates in the analysis to control for potential population stratification; in addition a covariate for age of diagnosis was included. The strongest evidence of a genome– wide significant (P < 5 x 10-8) association was at SNP (rs145723387) in lncRNA gene on chromosome 22 with white cell count (WCC) (Figure 6.1). The minor T allele of this SNP was associated with decreasing amounts of WCC (P = 2.5 x 10-9), platelets (P = 0.0025), base excess (P = 0.025), CRP (P = 0.0089) and increasing likelihood of mechanical ventilation (P = 0.0015 – met OR=0.17), GMSPS (P = 0.0075), INR (P = 0.0053), aPTT (P = 0.041), death in the Austrian and Dutch cohort (P = 0.05). No significance was detected by a heterogeneity test, suggesting consistent direction of effect across the three cohorts. In addition, seven other SNPs in the region associated with WCC with P value < 10-8 (Table 6.3).

VI – Investigating the role of GWAS candidate SNPs in IMD - 138 -

Table 6.1: IMD severity endpoints broken down by the number of cases and controls from individual cohorts. The table is obtained from C.Hoggart.

Endpoint UK Spain Austrian + Dutch Total

Cases Controls Cases Controls Cases Controls Cases Controls

Severity endpoints:

Death 18 424 8 354 19 314 45 1092

Skin graft/ 18 424 9 264 15 318 42 1006 amputation

Skin graft/ 36 406 16 257 34 299 86 962 amputation/death

Mechanical 321 121 62 185 75 245 458 551 ventilation

Table 6.2: Clinical markers of invasive meningococcal disease utilised for GWAS analyses broken down by each case cohort. The table is obtained from C.Hoggart.

Measure UK Spain Austrian + Dutch Total Plasma measures: aPTT 355 211 281 847 Base excess 371 218 240 829 CRP 350 0 288 638 Fibrogen 311 181 231 723 INR 344 165 127 636 Lactate 244 0 115 359 Platelets 391 265 313 969 Potassium 388 246 308 942 White cell count 393 267 324 984 Severity scores: PRISM 276 217 42 535 GMSPS 395 0 255 650

PRISM – Paediatric risk of mortality score in MD; GMSPS – Glasgow meningococcal septicaemia prognostic score

VI – Investigating the role of GWAS candidate SNPs in IMD - 139 -

Figure 6.1: Position of LncRNA gene, LL22NC03-86D4.1 denoted by blue shading on X-axis plotted against the combined P value on the Y-axis. The most significant SNP, rs145723387 represented by a purple circle and the surrounding red circles refer to other significant SNPs in LD (r2 > 0.8) with the top hit. Diagram produced by C.Hoggart.

Table 6.3: Individual and combined P values of LncRNA SNPs in the three cohorts. The data is obtained from C.Hoggart.

P value SNP ID Location UK Spain Austrian + Dutch Combined rs145723387 34,477,199 0.0008 0.011 9.4 x 10-6 8.7 x 10-10 rs11704266 34,477,467 0.0022 0.020 1.1 x 10-5 5.5 x 10-9 rs11089643 34,477,683 0.0022 0.020 1.1 x 10-5 5.5 x 10-9 rs11089644 34,478,427 0.0032 0.022 8.3 x 10-6 7.2 x 10-9 rs62229304 34,479,034 0.0032 0.022 8.3 x 10-6 7.1 x 10-9 rs17749103 34,473,635 0.0022 0.020 1.6 x 10-5 7.6 x 10-9 rs73155936 34,481,644 0.0038 0.022 7.2 x 10-6 7.6 x 10-9 rs113868964 34,477,043 0.0022 0.030 5.4 x 10-5 3.5 x 10-8

VI – Investigating the role of GWAS candidate SNPs in IMD - 140 -

6.3. Candidate gene and SNPs

The candidate lncRNA gene LL22NC03-86D4.1, like many others, has not been functionally characterised. The existing literature suggests lncRNA are a diverse class of transcribed RNA molecules longer than 200 nucleotides that do not encode proteins. Similarly with other non-coding transcripts including ribosomal RNAs, transfer RNAs and micro RNAs, which are shown to play important roles in regulating cellular mechanisms. LncRNA have also been demonstrated to be regulated during cell proliferation (Dinger et al., 2008), localise to defined regions of the cell (Sasaki et al., 2009), display tissue specific induction patterns (Mercer et al., 2008) and involved in immunity to diseases (Prasanth and Spector, 2007). Although only a select number of lncRNAs have been functionally characterised, there is growing evidence of regulatory roles that they play in modulating expression and function of genes and proteins in health and disease (Turner et al., 2014; Wilusz et al., 2009). Figure 6.2 below highlights some of these diverse molecular functions of lncRNA. Briefly, transcription of lncRNAs has illustrated to cause transcriptional interference of close-proximity gene expression by disrupting assembly of transcription factors at the gene promoter site or mediating epigenetic modifications, as shown with SRG1 preventing transcription factor binding to SER3 promoter site (Jacquier, 2009) and transcription modification of PHO84 in yeast (Camblong et al., 2007).

LncRNAs are involved in the processing of other RNAs by either altering splice sites such as in the case of rncs-1, which is stipulated to compete with siRNA binding to Dicer, thereby regulating downstream gene expression (Hellwig and Bass, 2008). Alternatively, lncRNAs can be produced into pseudogenes, which could act as transcription regulators (Tam et al., 2008). LncRNAs have also shown to exhibit regulation of various aspects of protein expression and functionality via direct RNA- protein interaction or modulation of other protein binding elements (Wilusz et al., 2009). For instance, lncRNA HSR1 interacts with HSF1, enhancing activation of respective proteins following heat-shock stimuli (Shamovsky et al., 2006). Alternatively, NRON binding to its target protein disrupts translocation of transcription factor NFAT into the nucleus, resulting in inhibition of downstream genes to be transcribed (Willingham et al., 2005). LncRNAs such as MALAT1 has demonstrated

VI – Investigating the role of GWAS candidate SNPs in IMD - 141 - to act as precursor for a small RNA, mascRNA, that exhibits distinct cellular localisation, rapid degradation pattern and possibly unrelated function compared to its full length parental lncRNA (Wilusz et al., 2008). These examples provide an insight into the fascinating world of lncRNAs and it is postulated that more functions will be discovered with future advancements in the field. For now, the existing mechanisms will serve as the basis for characterisation of the identified disease associated candidates.

Wilusz et al. Genes Dev. 2009. 23: 1494-1504. PMID: 19571179.

Figure 6.2: Diverse mechanisms employed by lncRNAs in regulation of genes and proteins expression and functions.

VI – Investigating the role of GWAS candidate SNPs in IMD - 142 -

On closer look, Figure 6.3 shows the location of all eight intronic SNPs significantly associated with decreasing WCC (severity markers of IMD) as well as the sequence alignment of the top candidate SNP among primates. Despite their position in intronic regions of the lncRNA all 8 SNPs were highly conserved across primates, suggesting there is an evolutionary pressure applied to these SNPs possibly due to their functional role in regulation of immune mediated responses during infection.

Human TAAACTCATCCTTTTTTATGG Chimpanzee TAAACTCATCCTTTTTTATGG Gorilla TAAACTCATCCTTTTTTATGG Orangutan TAAACTCATCCTTTTTTATGG Vervet-AGM TAAACTCATCCTTTTTTATGG Macaque GAAACTCATCCTTTTTTATGG Olive baboon TAAACTCATCCTTTTTTATGG

VI – Investigating the role of GWAS candidate SNPs in IMD - 143 -

I. II. III. IV. V. VI/VII. VIII

rs17749rs113868rs145723rs11704rs11089rs11089rs62229rs73155 Both diagrams were obtained from http://enseml.org 103 964 387 266 643 644 304 936

Figure 6.3: Details of lncRNA SNPs significantly associated with WCC. A) Evolutionary conservation of the most significant SNP rs145723387 among primates and arrow indicates the position of the polymorphism. B) location of all lncRNA SNPS (top hit highlighted in red) most significantly associated with severity of IMD. Roman numerals indicate the exon numbering of the gene.

VI – Investigating the role of GWAS candidate SNPs in IMD - 144 -

In the case of our candidate lncRNA, LL22NC03-86D4.1 the cell type or tissue specific localisation has not been reported to date. Thus far, our initial investigation strategies involved genotyping of the candidate SNP (rs145723387) in healthy adult control DNAs followed by an evaluation of the potential genotype dependent immune responses after stimulating with pathogen associated agonists. Using an ex vivo human whole blood infection model, this work aimed to evaluate if the lncRNA SNP genotype is a determinant of individual’s cytokine response to meningococci infection or other bacterial associated agonistic stimuli, and hence may influence outcome of disease. The importance of leukocyte dysfunction in conjunction to the lncRNA SNP genotype was also investigated by assessing oxidative burst in neutrophil and monocytes upon stimulation with HK Nm and appropriate control agonists. Genotype associated effect on calcium signalling was examined using EBV transformed B-cells which were normalised for allelic genotype in various calcium signalling regulator factors.

6.4. Genotyping candidate SNPs in healthy controls

The control group consisted of healthy adult volunteers who were enrolled from among the students and staff of Imperial College London. The MAF of risk T allele was 0.24 in the population control (with individual genotype frequencies of C/C = 0.577, C/T = 0.365, and T/T = 0.057) according to 1000 Genomes Project Phase 3. In the lab, over 50 individuals consented to provide blood and their DNAs were extracted as described previously in Materials and Methods section. All individuals were genotyped for the most significant candidate SNP (rs145723387) in LL22NC03- 86D4.1 gene (as all 8 SNPs with P < 5 x10-8 were in LD with each other) using Sanger sequencing technique. Primer pairs (LL22_rs87f and LL22_rs87r) were designed with Pimer3 software, checked for self-complementation and exclusion of polymorphisms. PCR amplification of their DNAs yielded a product of approximately 616 bp (figure 6.4), which were subjected to purification and subsequent sequencing with Big Dye terminator. The annotation of 57 sequenced samples revealed 29 individuals with C/C genotype, 25 with C/T genotype and only 3 whom carried the T/T genotype (Figure 6.5). Therefore, we carried out the subsequent whole blood assays using three of each genotype for the cytokine response comparisons.

VI – Investigating the role of GWAS candidate SNPs in IMD - 145 -

Figure 6.4: PCR amplified product of polymorphism, rs145723387 flanking region. The arrow indicates the expected size of the product.

(C/C)

(C/T)

(T/T)

Figure 6.5: Electropherogram showing the three allelic genotypes of lncRNA SNP (rs145723387). Arrow signifies the nucleotide change for this SNP.

6.5. Ex vivo blood assay to examine genotype dependent immune response to stimuli

The cytokine kinetics and dose response were initially evaluated by monitoring cytokine production at specific time points after infection (figure 6.6) and by stimulating the blood with varying concentrations of stimuli (figure 6.7). To assess the cytokine kinetics, diluted blood sample from a single donor was inoculated with various final concentrations (104 – 108 CFU/ml) of HK Nm, strain MC58 and incubated at 37°C for 24 hours. Serial supernatant samples were collected during

VI – Investigating the role of GWAS candidate SNPs in IMD - 146 - this period and IL-6 production was measured using ELISA, according to manufacturer’s instructions. Whole blood dilution ratios: 1:2 and 1:10 were tested for the efficacy of IL-6 induction and as the results were consistent between the dilutions, 1 in 10 dilutions were selected for subsequent experiments to reduce the amount of starting quantity of blood (data not shown). LPS, an important component of outer membrane of meningococci, shown to be a potent activator of pro- inflammatory cytokines and chemokines including IL-6, TNF-α, IFN-γ and IL-β (van der Ley and Steeghs, 2003) was used alongside wells non-stimulated as controls in the present study.

ns MC58 (10^4 CFU/ml) MC58 (10^5 CFU/ml) MC58 (10^6 CFU/ml) 8000 MC58 (10^7 CFU/ml) MC58 (10^8 CFU/ml) 7000 LPS (10 ng/ml) 6000 5000

4000 6 (pg/ml) 6

- 3000 IL 2000 1000 0 2 4 6 24 Time (hours)

Figure 6.6: IL-6 cytokine kinetics. Whole blood was co-cultured with increasing concentrations (104 – 108 CFU/ml) of heat-killed Nm, strain MC58 for 24 hours. LPS was included as control for cytokine induction and non-stimulated diluted blood was included as an experimental control. IL-6 production was measured from supernatants collected at 2, 4, 6, 24-hour time points. The experiment was carried out two separate times in triplicates.

VI – Investigating the role of GWAS candidate SNPs in IMD - 147 -

We observed a dose dependent response in IL-6 production when the diluted blood was inoculated with increasing concentrations of HK meningococci at all time points tested, apart from the highest bacterial dose at 108 CFU/ml (Figure 6.6). The reasons for the downregulation of cytokine production at the highest dose compared with lower doses tested are not well understood. However, it is speculated that number of other regulatory factors produced in the blood can have a direct effect on the secretion of IL-6, including anti-inflammatory cytokines such as IL-10. High concentration of the latter cytokine is shown to inhibit LPS-induced monocyte activation during Nm infection, resulting in prevention of over-activated ‘cytokine storm’ and thereby protecting the host from detrimental tissue damage (Brandtzaeg et al., 2001). The results also revealed that there was minimal detection of IL-6 at early time points (2 – 4 hours) and levels continued to increase even at 24 hours of culture. Similar culture conditions were utilised by other investigators for detection of LPS or non-LPS induced cytokine productions (TNF-α and IFN-γ) from peripheral mononuclear cells (PBMCs) (Sprong et al., 2001). Hence, 24-hour incubation was considered optimal for subsequent assays.

In a parallel set of experiments, the effect of dose of various stimuli on the induction of IL-6 cytokine in the supernatants was assessed. The results demonstrated that 0.1 µg/ml of TLR1/2 agonist PAM3, 0.01 µg/ml of TLR4 agonist LPS and 104 CFU/ml of HK MC58 induced detectable levels of IL-6 following 24-hour culture (Figure 6.7A). While 0.5 µg/ml of TLR2/6 agonist PAM2, 1 µg/ml of TLR2 agonist LTA, 0.2 µg/ml of IL-1β and, a combination of 0.02 µg/ml of PMA and 0.5 Ionomycin induced the highest levels of IL-6 during the same culture period (Figure 6.7B). Maximum doses were equally or less successful for PAM2 or PMA and Ionomycin combinations.

Using the above parameters, production of cytokines including IL-6, TNF-α and IFN- γ were assessed in individuals’ representative of the three allelic genotypes (C/C, C/T and T/T) of lncRNA SNP, rs145723387 in the supernatants from the blood. After stimulation with LPS (0.01 µg/ml) and HK MC58 (104 - 106 CFU/ml) all three cytokines were produced at high levels compared with non-stimulated control wells from the same set of individuals (Figure 6.8). In addition, combination of PMA and ionomycin produced detectable amounts of IL-6 and TNF-α (Figure 6.8A and B). Whereas, stimulation with PAM3, PAM2, LTA and IL-1β produced low levels of IL-6

VI – Investigating the role of GWAS candidate SNPs in IMD - 148 - responses compared with non-stimulated controls (Figure 6.8A). Marked increase in IL-6 response by C/T genotype was observed compared with responses produced by that of C/C genotype (P = 0.0002) and some suggestive difference was also seen with T/T genotype (P = 0.0552). Otherwise, no other significant differences were detected in cytokine response between the three genotypes of the lncRNA.

A. 6000 5000

4000 3000

6 (pg/ml)6

- 2000 IL 1000 0 0.1 0.01 10^4 cfu/ml

PAM3 LPS MC58 Stimuli

1200 1000 800

600 6 6 (pg/ml)

- 400 IL 200

1 1

0.1 0.1 0.5 0.1 0.5 0.2

0.02

0.05 + 0.5 + 0.05 0.02 + 0.5 + 0.02

0.005 + + 0.5 0.005 10^4 cfu/ml 10^4 ns PAM2 LTAStimuli IL1B PMA+I MC58

Figure 6.7: Dose dependent response of the induction of IL-6 cytokine in whole blood. Diluted blood sample was co-cultured with a selection of stimuli at various concentrations and supernatants were recovered at 24 hours, and subsequently tested for IL-6 cytokine production by ELISA. A) A single dose of TLR1/2 synthetic agonist PAM3, TLR4 agonist LPS (derived from S. Minnesota R595) and HK Nm, strain MC58. B) Three doses of TLR2/6 synthetic agonist PAM2, TLR2 synthetic agonist LTA, IL-1β and PMA+Ionomycin were evaluated. Experiments were carried out in triplicates and all results are expressed as mean ± SEM.

VI – Investigating the role of GWAS candidate SNPs in IMD - 149 -

1 5 0 0 0 C /C

C /T

T /T

) 1 0 0 0 0

l * *

(

L I 5 0 0 0

0 4 6 8 1 0 1 0 1 0

n s P A M 3 L P S P A M 2 L T A M C 5 8 P M A + I IL -1 

2 5 0 0 C /C

2 0 0 0 C /T

) l

T /T

m /

g 1 5 0 0

(



- 1 0 0 0

N T

5 0 0

0 4 6 8 1 0 1 0 1 0

n s L P S M C 5 8 P M A + I

VI – Investigating the role of GWAS candidate SNPs in IMD - 150 -

2 5 0 0 0 C /C

2 0 0 0 0 C /T )

l T /T m

/ 1 5 0 0 0

(



- 1 0 0 0 0

F I

5 0 0 0

0 4 6 8 1 0 1 0 1 0 n s L P S M C 5 8

Figure 6.8: Evaluation of genotype dependent cytokine response in supernatants of whole blood. Diluted blood samples representative of C/C genotype (n ≥ 6), C/T genotype (n ≥ 6) and T/T (n = 3) of the lncRNA SNP rs145723387 were stimulated with various stimuli. After 24-hour, supernatants were removed and cytokine responses were tested by ELISA. A) Samples were stimulated with 0.1 µg/mL of PAM3, 0.01 µg/mL of LPS, 0.5 µg/mL of PAM2, 1 µg/mL of LTA, 0.2 µg/mL of IL-1β and 0.02 µg/mL of PMA in combination with 0.5 µg/mL of ionomycin, as well as increasing levels of HK MC58. IL-6 cytokine induction was tested in the supernatants. B) After stimulation with LPS, PMA in combination with ionomycin and various amounts of HK MC58, TNF-α secretions were measured in supernatant C) Samples were stimulated with LPS and various concentrations of HK MC58 and IFN-γ production was evaluated. The experiments were repeated at least two independent times in triplicates and results are represented as mean ± SEM. ** P < 0.001 for comparison between genotypes. Two-way ANOVA with Tukey’s correction testing was used to calculate statistical significance.

6.6. Oxidative burst and neutrophil degranulation

We hypothesised that specific genotype of the SNP in lncRNA may influence leukocyte dysfunction. We tested oxidative burst in neutrophil and monocytes upon stimulation with HK Nm and positive control PMA with the help of Dr.Aubrey Cunnington (Imperial College London). The oxidative burst in leukocytes was quantified by the rhodamine fluorescence intensity (MFI) and degranulation was measured by the fold increase in surface CD11b MFI from non-stimulated to the stimulated sample. The results shown below represent the analysis from one set of

VI – Investigating the role of GWAS candidate SNPs in IMD - 151 - experiment (Figure 6.9). We were not able to replicate these results upon repeating the experiment and hence were not able to draw any definitive conclusions from these data.

Neutrophils Monocytes

6 0 0 0 0 2 5 0 0

C /C C /C I

C /T I 2 0 0 0 C /T

M M

4 0 0 0 0

T/T T/T e

e 1 5 0 0

a a

d 1 0 0 0 d

o 2 0 0 0 0

h R R 5 0 0

0 0

S ) A L S A ) N M N L /M M M P P / U U F F 9 C 9 C 0 0 1 1 X X .6 .6 (1 (1 8 5 8 C 5 C M M

1 5 3

C /C C /C

o i

i C /T C /T

)

l g g 1 0 2 T/T

T/T u

b b

o 5

o 1

(

C C

0 0

) ) A L A M L M M M P / P / U U F F 9 C 9 C 0 1 0 1 X X 6 . .6 (1 1 ( 8 8 5 5 C C M M

Figure 6.9: FACS data representative of neutrophil and monocyte oxidative burst and degranulation. Select monocyte and neutrophil population was stimulated with positive control; PMA and heat-killed NM (strain MC58) 1.6 x10^9 (cfu/mL) (x-axis) and, rhodamine MFI or CD11b upregulation (y-axis) as measurement of oxidative burst or degranulation of leukocyte respectively. The two panels represent the flow cytometer results of neutrophils (left) and monocytes (right) upon stimulation.

VI – Investigating the role of GWAS candidate SNPs in IMD - 152 -

6.7. Calcium Flux measurement

Next, we assessed whether the lncRNA, LL22NC03-86D.4 SNPs associated with decreasing WCC functionally impacted outcome from meningococcal disease by indirect mechanisms including modulation of cell signaling pathways, as shown with other lncRNA genes, such as NRON which downregulates gene transcription by impeding NFAT signalling cascade (Willingham et al., 2005). Calcium signaling plays a central role in cell proliferation, gene expression, muscle contraction and enzyme secretion (Berridge et al., 2000). Number of bacterial pathogens, including Nm has been reported to subvert calcium signaling in host cells as a virulence mechanism to promote adherence to and subsequent invasion of meningococci into host cells (Asmat et al., 2014).

In this work, we sought to decipher whether the lncRNA SNPs correlated with severity of IMD in our GWAS analysis could possibly mediate the regulation of host calcium signaling pathway, in turn influencing downstream immune and inflammatory response mechanisms in host defence. To follow this up, we genotyped healthy controls for one of the lncRNA SNPs (rs73155936), in which the T allele is significantly associated (P < 7.6 x 10-9) with severity markers of IMD in our GWAS analysis. Notably, the reference, G allele for this SNP is extremely well conserved among the primate kingdom (Figure 6.10) much like the other SNP rs145723387 in the same gene. We screened a total of 384 healthy adult control EBV- transformed B cells, from the healthy subject biobank (The Centre for Applied Genomics) and found 18 individuals with TT allele (4.8 %).

VI – Investigating the role of GWAS candidate SNPs in IMD - 153 -

Human TGTCTGGGTTGCTACAACAAA Chimpanzee TGTCTGGGTTGCTACAACAAA Gorilla TGTCTGGGTTGCTACAACAAA Orangutan AGTCTGGGTTGCTACAACAAA Vervet-AGM TGCCTGGGTTGCTTCAACAAA Macaque TGCCCGGGTTGCTTCAACAAA Olive baboon TGCCTGGGTTGCTTCAACAAA Marmoset TGCCTGGGTTGCCTCAACAAA Figure 6.10: Evolutionary conservation of lncRNA SNP rs145723387 among primates. Arrow indicates the position of the polymorphisms of interest.

To evaluate the calcium mobilisation, flow cytometry was performed on EBV- immortalised B cells from three to five individuals of each genotype (GG, GT, TT) at rs73155936 using ratiometrically opposite Ca2+ indicator dyes (Fluo-4 AM and Fura- 3 AM) in Ca2+ free media. The cells with specific genotype were selected at random, if they were also wild type for other recognised calcium signalling markers including NCX1, ITPCKC and BLK. The assay was accomplished with the help of Dr.Trang Duong and Dr.Marin Alphonse (The Hospital for Sick Children Institute) using a slightly modified version of a previously established assay method (Alphonse et al., 2016). Briefly, the immortalised B cells were cultured in complete RPMI1640 to reach 6 - 8 x 106 cells and were stained with Fluo-4 AM and Fura-3 AM dyes in Ca2+ free media. After 45 minutes, the unbound dyes were rinsed, cells diluted to appropriate density and loaded with Dapi (nuclear stain). Intracellular Ca2+ (iCa2+) mobilisation was monitored over a period of 10 minutes by acquiring basal Ca2+ for the initial minute followed by an addition of 1 µM of ionomycin to the cells.

The calcium flux experiments undertaken on the five individuals of three allelic genotypes at rs73155936 showed no difference in baseline iCa2+ quantities (Figure 6.11A and C). However, we observed obvious differences in iCa2+ flux after stimulation with ionomycin between the three genotypes, where a sharp increase (approximately 1.5-fold rise) in iCa2+ was seen with both GT and TT (P < 0.0001) genotypes compared with the gradual rise observed in cells with GG allele (Figure 6.12 A and B), indicating the T allele effects iCa2+ mobilisation kinetics upon

VI – Investigating the role of GWAS candidate SNPs in IMD - 154 - stimulation with external stimuli. This sharp rise in iCa2+ in the absence of extracellular Ca2+ (eCa2+) was sustained throughout by the cells with GT and TT genotypes and failed to reach the levels obtained by cells with GG genotype nor return to baseline for the duration of the experiment.

Additionally, in a small subset of EBV-transformed B cells, we evaluated the iCa2+ kinetics between the different genotypes after stimulation with 1 µM of ionomycin in the presence of eCa2+. The iCa2+ flux acquisition was continued for 10 minutes. Consistent with the method described above, we acquired the baseline iCa2+ by flow cytometry for the initial 1 minute followed by addition of 1.5 µM of CaCl2 (as a source of extracellular calcium) and subsequently stimulated the cells with 1 µM of ionomycin for the final 6 minutes.

2+ The results of the iCa flux assay showed that addition of exogenous CaCl2 to the cells did not alter the baseline iCa2+ levels regardless of genotypes at rs73155936. However, even more overexaggerated kinetics (approximately 2- 2.5-fold increase) was observed in cells with both GT and TT genotypes compared with reference GG allele after stimulation with ionomycin, which was sustained at extremely high levels for the duration of the measurement (Figure 6.12).

The calcium signalling pathway has shown to be a central mediator in numerous downstream immune mechanisms during host response to foreign pathogens (Vig and Kinet, 2009). These results suggest the allelic variation at rs73155936 in the lncRNA; LL22NC03-86D.4 transcript can lead to dysfunctional iCa2+ mobilisation at a cellular level in the presence and absence of eCa2+ and hence may alter the downstream transcription of genes that play an important role in the regulation of host immune responses during neisserial infection.

VI – Investigating the role of GWAS candidate SNPs in IMD - 155 -

A. 5  1 0 2

4  1 0 2 i

] GT

+ 2 2 3  1 0 * *

a TT

[

I 2  1 0 2 F

M 1  1 0 2

0 0 1 2 3 4 5 6 7 8 9 1 0

T im e (m in u te s ) io n o m y c in * p < 0 .0 0 1 B. C. GG

+ B a s a l in tra c e llu la r C a 2 le v e l

6 0 0 ]

o u

l 4 0 0 F

- a

r 2 0 0 GT

[

I F M 0 G T T G G T

L n c R N A S N P (rs 7 3 1 5 5 9 3 6 )

ionomycin

Figure 6.11: lncRNA SNP (rs73155936) genotype impacts calcium mobilisation upon stimulation with ionomycin. A) Mean fluorescence intensity of Fluo-4 AM in EBV-transfected B cells with various genotype (GG, n = 5; GT, n = 3 and TT; n = 3) monitored by flow cytometry for continuous 10 minutes. B) Baseline cytosolic calcium in cells, shown as the fluorescence intensity ratio of Fura-3 AM to Fluo-4 AM. C) Representative graphs of calcium flux kinetics over time. The experiments were carried out on at least five separate occasions. The results are represented as means ± SEM and statistical significance * P < 0.0001 for genotype comparisons determined using Two-way ANOVA with Tukey’s multiple correction test.

VI – Investigating the role of GWAS candidate SNPs in IMD - 156 -

A. 8  1 0 2

6  1 0 2

] +

2 * GG a 2 C 4  1 0

[ GT

F TT M 2  1 0 2

0 0 1 2 3 4 5 6 7 8 9 1 0

T im e (m in u te s )

C a C l2 io n o m y c in

B. GG

CaCl ionomycin 2

Figure 6.12: The effect of rs73155936 genotype is even more exaggerated with in the presence of extracellular calcium. A) Mean fluorescence of Fluo-4 in immortalised B cells with various genotypes (n = 1 of each genotype) measured over time. B) Representative plots of calcium flux kinetics over time. The experiments were carried out on at least three separate occasions. The results are represented as means ± SD and statistical significance * P < 0.01 for genotype comparisons determined using One-way ANOVA with Tukey’s multiple comparisons test.

VI – Investigating the role of GWAS candidate SNPs in IMD - 157 -

6.8. Discussion

Since the advancement of NGS technologies, GWAS has been widely employed as one of the main platforms for the discovery of common SNPs associated with susceptibility to and severity of diverse infectious diseases. The genomic studies carried out on IMD have been based on the idea that the underlying genetic determinants will be enriched in the disease populations relative to the controls. To identify genetic markers of IMD severity or outcome, the current GWAS study was designed by Professor M. Levin and colleagues with special consideration to include a well-defined phenotype of a large group of patients, representing diverse clinical manifestations of meningococcal infection. The idea behind it is that genes regulating severity of IMD may not come from comparing the frequency of common polymorphisms among affected cases and healthy control groups, but may reside in the difference in distinct clinical manifestations of meningococcal infection. As an example, the same group highlighted the genetic determinants of coagulation may not be a useful indicator of susceptibility to IMD but could provide an important clue on whether a patient will go onto develop vasculitis or thrombocytopenia (Wright et al., 2009).

To identify host genetic variants underlying susceptibility or outcome of the meningococcal disease, a large scale GWAS was performed on IMD cases and ethnically matched population controls, which were mostly collected at the same time as the recruitment of affected cases to the study. As mentioned above, most of these IMD cases and control groups have been used in previous studies and further information on the clinical and demographic data can be found in relevant manuscripts (Binder et al., 2007; Emonts et al., 2010; Haralambous et al., 2003, Davila et al., 2010; Martinón-Torres et al., 2016). The genotyped SNPs were put through a strict QC and extra SNPs were imputed from the 1000 Genomes (Abecasis et al., 2012) as well as the European CEU HapMap population references to encompass approximately 1 million SNPs in the final analysis. The meta-analyses on the combined IMD cases of mixed European population showed that several intronic lncRNA SNPs were highly associated (P–value < 5 x 10-8) with plasma markers of severity in IMD, where independent associations were seen with abnormal laboratory measures such as WCC, platelets, CRP, base excess and

VI – Investigating the role of GWAS candidate SNPs in IMD - 158 - clinical severity scores including mechanical ventilation, GMSPS, INR, aPTT and death. Currently, a validation study is underway to replicate the findings from this initial GWAS study, in a large cohort of meningococcal disease cases enrolled through the EUCLID consortium.

Using functional studies, various attempts were sought in characterising the intronic lncRNA SNPs, which have been shown to correlate with severity or outcome of IMD in the initial GWAS analysis. According to the International Human Genome Sequencing Consortium, the human genome comprises of no more than 25,000 genes which encode for a protein, corresponding to less than 2 % of the complete genomic sequences (Consortium, 2004). Since the publication of these figures, follow-up cDNA cloning and array studies have uncovered that more than 90 % of the human genome has the potential to be transcribed (Birney et al., 2007), yielding thousands of lncRNA transcripts which often share a large homology with other transcripts in the genome (Birney et al., 2007). Our candidate lncRNA gene among thousands of others have yet to be characterised and the research in this field is only beginning to understand the complex and diverse regulatory functions of lncRNA in human health and disease. Our ex vivo blood assay results showed that genetic variations at rs145723387 in lncRNA gene, LL22NC03-86D.4 may influence LPS mediated IL-6 cytokine responses, where a marked increase in IL-6 production was observed in CT allele compared with reference CC allele in supernatants. It is interesting however that we did not see the similar effect upon stimulation with HK meningococci. Although it is possible that heat-killing process may have damaged the outer surface of meningococci, such that HK Nm may not express intact LPS and hence were not able to induce effective cytokine response in human blood.

On the other hand, it has been demonstrated that LPS and non-LPS components of meningococcus can induce host immune responses as effectively and in a synergistic manner (Sprong et al., 2001). Therefore, the non-LPS portions of the HK Nm should have elicited the required cytokine production in a comparable manner to LPS mediated response, if the lncRNA SNP is somehow orchestrating the response to both stimuli. Nevertheless, the whole blood contains numerous cell populations, which were not controlled for in this work due to the late setting up of blood count assay, normally provided for clinical samples rather than research purposes. In addition, the results of our oxidative burst analysis using FACs in monocyte and

VI – Investigating the role of GWAS candidate SNPs in IMD - 159 - neutrophils upon stimulation with HK Nm demonstrated that there was no SNP genotype dependent impact on leukocyte dysfunction. Previous studies have shown that lncRNA regulate immune response gene transcription via indirect mechanisms, such as affect gene expression by disrupting translocation of transcription factors to the nucleus (Willingham et al., 2005) or inhibiting assembly of transcription elements (Mariner et al., 2008). Thus, we evaluated the relevance of the candidate lncRNA SNPs in calcium signalling pathway, which sits at the crucial intersection in many cellular mechanisms during infection (TranVan Nhieu et al., 2004). Our FACS analysis of the calcium mobilisation in the presence and absence of extracellular calcium provided a unique connection between allelic variations at rs73155936 in the candidate lncRNA gene, LL22NC03-86D.4 and calcium flux in healthy control EBV- transformed B cells.

Our functional assays showed that genetic variations at lncRNA SNP; rs73155936 have no effect on resting calcium levels, nevertheless impact stimulated iCa2+ levels differently, where EBV-transformed B cells with GT or TT genotypes produced a marked increase in iCa2+ upon stimulation and sustained over-activated calcium levels compared to cells with reference GG allele. The addition of extracellular calcium source exaggerated these increase in levels of iCa2+ observed with GT or TT genotypes (Figure 6.12). The relevance of this dysregulated iCa2+ may impact negatively on various downstream mechanisms that are regulated by calcium mobilisation of host cells, especially during host cell interactions with bacteria (TranVan Nhieu et al., 2004), including Nm. An increase in iCa2+ in host cells are shown to be an important regulator of bacterial toxin mediated gene expression of pro-inflammatory genes such as IL-6 and IL-8 cytokines or mucin (Dolmetsch et al., 1997; Räth et al., 2013). Although cytokine production from the B cells is yet to be tested, it is tempting to speculate that the candidate lncRNA genotype modulated increase in iCa2+ may result in over induction of cytokines during neisserial infection and hence lead to the severe outcome from the disease. In support of this idea, fulminant cases of meningococcal disease have been reported to exhibit extremely high levels of proinflammatory cytokines, which are suspected to cause damage to host tissues during infection as well as in convalescent phase (Pathan et al., 2004).

In addition, calcium flux is reported to be a key modulator of cytoskeletal rearrangement necessary for type IV pili mediated neisserial interaction with

VI – Investigating the role of GWAS candidate SNPs in IMD - 160 - phagocytic cells to initiate internalisation and subsequent neutralisation of the pathogen (Opitz et al., 2009). It has also been reported that virulence factors of bacterial species, including but not restricted to Salmonella typhimurium (Gewirtz et al., 2000) and Listeria monocytogenes (Gekara et al., 2007) promote calcium influx of host cells for successful adhesion and invasion into host target cells. Therefore, it will be extremely interesting to investigate the mechanisms behind how thesecandidate lncRNA SNPs affect diverse downstream signalling mechanisms to impact severity and outcome of meningococcal infection.

In conclusion, we show here that a large-scale GWAS analysis performed on a mixed European population has uncovered a novel lncRNA gene, LL22NC03-86D.4 to associate with severity and outcome of IMD, where the majority of previous studies have sought to discover genetic determinants of disease susceptibility. The severity analysis was possible due to the enrolment of meningococcal disease cases presenting with diverse manifestations or progression of disease. End-point as well as intermediate laboratory markers of IMD severity correlated with several intronic SNPs in the candidate lncRNA transcript. Their highly conserved pattern among primates suggests a functional importance of this transcript. Our functional ex vivo assay indicates that allelic genotypes of these series of SNPs may play a role in LPS mediated host immune response. Further analysis in calcium mobilisation shows that predicted risk alleles of these lncRNA SNPs directly affects calcium influx when stimulated and hence may affect related downstream mechanisms involved in host defence during neisserial infection. Overall, the ongoing replication study for the GWAS analyses in an independent dataset and further functional analysis will facilitate the understanding of this intriguing revelation in host response against Nm.

Chapter 7

VII – Conclusion and future recommendations - 162 -

7. Conclusion and future recommendations

7.1. Overview

A common feature of infectious diseases is that only a small proportion of exposed individuals suffer from the clinical course of the disease. There is also a large degree of variability in the disease manifestations that often yield a diverse range of phenotypes. Some of the early evidence that these inter-individual differences in host susceptibility to infectious diseases is partly attributed to the host genetic factors originated from studies involving twins and adoptees (Cooke and Hill, 2001; Petersen et al., 2002). It is now well established that host genetic differences play an important role in determining susceptibility to infectious disease. In IMD, the genetic heritability rate between siblings has been calculated to contribute to approximately one third of the total disease risk (Haralambous et al., 2003).

A series of seminal studies carried out by Goldschneider and colleagues in 1969 have demonstrated that important correlates of protection for meningococcal infection are provided by the development of specific antibodies. Antibody titres were shown to increase following nasopharyngeal colonisation (Goldschneider et al., 1969b). A study investigating the factors that confer susceptibility to development of meningococcal disease among prospective military recruits found that susceptible individuals lacked presence of antibodies to the homologous meningococcal strains in baseline sera at the initial enrolment. These individuals however retained the ability to initiate an immune response to meningococcal antigens, as evident from increased antibody titres in convalescent sera. The increase in antibody titre was accompanied by an increase in bactericidal activity (Goldschneider et al., 1969a).

VII – Conclusion and future recommendations - 163 -

Moreover, individuals with complement deficiencies are known to suffer from recurrent meningococcal infections (Arnold et al., 2009), which demonstrates the importance of serum bactericidal activity in protection against NM.

To date, numerous GWAS studies have identified polymorphisms both in innate and adaptive immunity that are associated with susceptibility of IMD. While, many of the identified associations await further validation, some plausible discoveries have emerged, including genes encoding the CFH and CFH-related 3 proteins (Davila et al., 2010), IL-1 gene clusters (Read et al., 2000) and airway surfactant SP-A2 (Jack et al., 2006). Moreover, many Mendelian genetic mutations in the complement components, alternative complement regulator properdin and IRAK4 genes are well established to confer predisposition to IMD, as described previously in the Introduction Section 1.10.1. A previous study assessing the prevalence of complement deficiencies in IMD have reported that these genetic deficiencies accounted for approximately 3 % of the total cases (Fijen et al., 1999), indicating there may be many more undescribed genetic aetiologies underlying IMD in the unexplained cases. Therefore, this study as part of the EUCLIDS consortium was set up to identify rare and undescribed causative mutations that may underlie susceptibility to, and severity of IMD and other life-threatening childhood diseases.

As part of the EUCLIDS study, WES was carried out on over 500 cases of various life-threatening infectious cases, including meningococcal disease and put through our in-house analysis pipeline. In a parallel approach, GWAS was performed on over 1000 well-characterised unrelated IMD cases with microbiologically proven meningococcal disease. In the first instance, WES and subsequent genetic analysis led to the discovery of a novel mutation in the SPLUNC1 gene, suspected to confer susceptibility to IMD in two related siblings who suffered from the disease on independent occasions. In the second instance, the GWAS analysis on three cohorts from European decent identified several polymorphisms in a lncRNA gene (LL22NC03-86D4.1) on chromosome 22 associated with severe outcomes of meningococcal disease. The research presented in the present study aimed to functionally validate these novel findings using various molecular genetics and immunologic assays in a disease relevant context.

VII – Conclusion and future recommendations - 164 -

7.2. Main findings

Initial WES analysis in the two related IMD cases resulted in a total of 231 rare candidate variants. Of these, 9 variants were predicted to impact the function of the encoding protein based on their potential effect on protein structure and evolutionary conservation of the loci. However, the genes and encoded proteins harbouring these predicted ‘significant’ candidates showed no relevance to disease pathophysiology. Thus, an extensive literature search was applied to all potential rare candidate variants, resulting in the possibly pathogenic candidate SPLUNC1 (c.65G > A, p.G22E) mutation. The protein encoded by the same name SPLUNC1 showed specific expression in the nasopharyngeal region (Bingle and Bingle, 2000) and previous studies implicated the importance of this protein in protection against other Gram-negative bacterial infections (Chu et al., 2007; Liu et al., 2013a; Lukinskiene et al., 2011). Further targeted sequencing in randomly selected 186 meningococcal disease cases uncovered an additional unrelated individual carrying the same mutation. This missense mutation is novel and was not found in any public databases (dbSNP, the 1000 genomes, EVS and gmonAD) or in our in-house of over 500 exome sequences.

The biological function of SPLUNC1 is not clearly defined. The structural analysis of the protein was illustrated to share a structural homology with neutrophil proteins, BPI or LBP and thus, postulated to play an important role in human host defence against invading microorganisms (Bingle and Craven, 2002). This study shows, for the first time, that recombinant SPLUNC1 is able to inhibit early Nm biofilm formation on abiotic surfaces (Chapter 4). Moreover, using in vitro colonisation models we demonstrate that purified SPLUNC1 significantly impedes meningococcal adherence to human respiratory epithelial 16HBE14 cells and subsequent invasion of the epithelial layer. As we did not observe direct bacterial killing in the presence of recombinant SPLUNC1, we concluded that the reduction observed in biofilm biomass or human colonisation models of adhesion and invasion assays was unlikely due to the lower bacterial burden resulting from direct bactericidal activity exhibited by the protein, but rather through the direct interaction of SPLUNC1 with meningococcal motifs, such as LPS and perhaps by forming a physical barrier restricting bacterial attachment to each other and to host epithelial cell surfaces.

VII – Conclusion and future recommendations - 165 -

Further functional characterisation of the G22E mutation using transient transfection and stable transduction revealed that the mutant-expressing epithelial cells have higher intracellular expression of SPLUNC1 at the transcriptional and protein levels. This study also found that the mutant G22E expressing cells produced markedly higher pro-inflammatory cytokine production in response to LPS and HK Nm stimulation (Chapter 5). SPLUNC1 has been demonstrated to directly bind LPS from various Gram-negative bacteria, including P. aeruginosa and E. coli (Ghafouri et al., 2004; Sayeed et al., 2013). This study demonstrated the LPS binding capacity of SPLUNC1 also applies to LPS from Nm and S. Minnesota, however, the G22E allelic mutation does not impact this function of the protein. The same in vitro assays used to assess the role of SPLUNC1 in host defence against Nm was used to determine the potential impact of the G22E mutation on the encoding protein. The preliminary data presented in this study suggested that biofilm biomass was increased in presence of the mutant G22E compared with the wild type SPLUNC1. Moreover, there was marked increase in meningococcal adhesion and subsequent invasion into 16HEB14 cells when the culture was supplemented with G22E mutant compared with that of wild type recombinant SPLUNC1, indicating this missense mutation may impair the normal function of the protein. Further functional investigation is required to decipher whether this effect is due to haploinsufficiency or dominant negativity, as the patients were heterozygous for the mutation.

On the other hand, the functional characterisation of the GWAS findings proved more challenging due to the somewhat limited knowledge on the functions of lncRNAs in regulating infectious disease pathophysiology. The collection of eight SNPs in the lncRNA gene showed in LD with one another. As it was not possible to obtain fresh blood samples from the patients that displayed different genotypes at the lncRNA SNPs, we utilised healthy adult donors for the genotype analysis (for rs145723387) and subsequently employed ex vivo blood stimulation assays. The cytokine profile results were indicative of genotype dependent difference in response to the TLR-4 agonist LPS, but not to any other stimuli. The same donors were utilised in assessing the oxidative bust and neutrophil degranulation between the three genotypes and there was also no significant difference found. However, the investigation of these lncRNA SNPs in relation to calcium signalling using the calcium flux assay demonstrated a potential avenue for exploration. The preliminary

VII – Conclusion and future recommendations - 166 - results suggest that there is a significant lncRNA genotype dependent effect on calcium mobilisation, as shown in EBV transformed B cells, which were also wild type for other known calcium signalling markers including NCX1, ITPCKC and BLK (Chapter 6). Due to the limited time available for this work, I was unable to undertake any further investigation of the potential effect this calcium signalling might have on downstream mechanisms involved in regulating the disease pathophysiology during IMD.

In summary, this study reports that WES combined with functional characterisation is an effective approach for uncovering rare and novel genetic determinates underlying IMD. The present study suggests that nasopharyngeal respiratory tract secreted protein SPLUNC1 may contribute to host defence against meningococcal colonisation and possibly prevention of invasive disease. We found that the G22E mutant protein has altered function compared with that of wild type SPLUNC1 protein suggesting the missense mutation may impact on the protein at a functional level. On the other hand, GWAS remains a useful tool in identifying common polymorphisms, particularly located in non-coding regions of the genome, associated with disease severity and outcome, as shown by the discovery of lncRNA SNPs.

7.3. Study limitations and future recommendations

While the WES and GWAS analyses and functional validations in this study demonstrate the use of these two unique techniques in discovering potential genetic factors that may underlie susceptibility to and severity of IMD, there are a number of drawbacks. One of the advantages of WES over that of GWAS is its effectiveness in identifying potential disease-causing mutations in a single affected case (Byun et al., 2010) to a small number of affected individuals (Hoischen et al., 2010). In contrast, a large cohort of affected cases (at least over 1000) is required for a GWAS study to obtain the statistical power to determine genome-wide significance (Dale and Read, 2013) and maybe, even more, to be able to replicate the initial findings. This need for a large cohort presents several challenges. Firstly, the sample collection of rare diseases such as meningococcal infection presents a huge task for the clinical team responsible for recruitment of samples from affected cases and controls. Secondly, another related issue to the previous point is the need for rigorous phenotype assignment to individual disease cases accompanied by detailed demographic and

VII – Conclusion and future recommendations - 167 - clinical data. Thirdly, the route of enrolment and how soon after the enrolment the sample is used in the study may present difficulty for subsequent functional characterisation studies. WES analysis revealed the novel heterozygous missense mutation In SPLUNC1 gene, and despite attempts to re-contact the patients to ask for relevant samples such as throat swab or epithelial cell brushings, it was not possible due to change in their contact details.

Some technical limitations commonly apply to both WES and GWAS approaches, for example, the limiting factors may come from defining the target region or the number of SNPs to genotype. The capture library for WES is based on the current knowledge of the ‘target exome region’ from public databases, which will likely to expand in the future. In the meantime, the undiscovered exons are not captured, meaning the exome target is not comprehensive (Ku et al., 2012). Similarly, the genotyping SNP Chip used for GWAS approach is also based on public databases, although imputation of additional SNPs can be employed to overcome this technical limitation, provided the demographically matched reference panels is made available. The GWAS data presented in this was based on mainly European decent white populations, thus it was possible to impute additional SNPs from the 1000 Genomes (Abecasis et al., 2012) and the European CEU HapMap population panels, which consist of ethnically homogeneous populations. Other technical challenges specific to WES approach include low coverage of target regions spanning high GC content or repetitive sequence and not being able to detect copy number variants, which has been correlated with rare or complex traits (Weischenfeldt et al., 2013). In cases where there is low coverage due to technical limitation, then targeted sequencing of the specific region is recommended. But the fact that WES involves sample amplification step means it will be difficult to detect copy number variations.

The exome sequencing analysis pipeline described here did not consider non-coding regions and related variants. There remains a great deal of uncertainty around the extent to which these types of variants may contribute to disease initiation and development mechanisms (Cooper et al., 2010). The GWAS data described here highlights the somewhat limited knowledge of our understanding of the diverse functional roles of these non-coding genes in human health and disease. As these non-coding genes outnumber coding genes in the order of 3 to 5 times (Iyer et al., 2015), it is possible that some causal variants can be missed due to the technical

VII – Conclusion and future recommendations - 168 - limitation of a given genomic technique. The method to overcome these technical challenges will be to perform WGS, but at present, the high cost and immense computational power required for data analysis mean WES or GWAS remain viable methods of choice for genetic studies, depending on the research question.

In this work, the respiratory epithelial cell lines used displayed no detectable expression of SPLUNC1, thus we were not able to use gene editing tools to assess the function of the protein. A previous study has shown that SPLUNC1 is readily secreted by human primary bronchial epithelial cells (Liu et al., 2013a) and the use of shRNA or siRNA will allow knock-down or knock-out of the SPLUNC1, which can be used to address the specificity of SPLUNC1’s proposed roles in host defence against Gram-negative bacteria. Future investigations, however, could obtain epithelial cell brushings from the patient with the specific mutation, as recent studies have demonstrated successful culture techniques for these type of cells (Reuschl et al., 2017). Alternatively, human primary epithelial cells derived from healthy donors can be obtained from commercial means (www.lonza.com) and genetic editing techniques can be used to mimic the patient’s specific mutation for further functional validation work.

Another drawback of this study and many other studies on meningococcal disease is the lack of suitable animal models to assess the molecular basis of certain elements in an in vivo setting. Although the results of this assay provided insight into the biological function of SPLUNC1 in the context of IMD, we are aware that the use of recombinant protein in an in vitro setting does not provide a prospective on the interplay between SPLUNC1 and other innate immune-induced mediators secreted in the respiratory airways on exposure to Nm. The issue of assessing the protein function alongside other known innate immune mediators can be overcome by applying the resulting human primary bronchial epithelial cells in a contact independent co-culture system involving THP-1 monocytic cells (or alternative leukocyte subpopulation derived cell lines) to mimic the co-existence of the epithelial and myeloid compartments in the airways during infection with microorganisms. A recent study has used this type of co-culturing technique to successfully assess the host response to Mycobacterium tuberculosis (Reuschl et al., 2017).

VII – Conclusion and future recommendations - 169 -

One limitation of this study has to be noted is the investigation concerning the ENaC regulation and the potential impact of the selected mutation being located in the protein domain responsible for this particular function. Previous studies have suggested that the N-terminal region spanning the G22E mutation is important in regulating ENaC, which plays an essential role in the context of infection by increasing mucus production and removal of invading pathogen from the epithelial surfaces (Garcia-Caballero et al., 2009; Garland et al., 2013; Walton et al., 2016). One suggestion could be a use of human primary cultured cells described above, as this type of culture is known to form a differentiated and polarised epithelial layer that produces cilia accompanied by mucin secretions when cultured on semi-permeable transwells (Abdullah et al., 2012). It may be possible to create the heterozygous mutation in question using CRISPR CAS-9 method to mimic the patient’s mutation in these cells, so that they could be used to study the potential impact of the mutant on the ENaC regulation and related bacterial clearance functions.

The limitation of the ex vivo blood assay employed to investigate the lncRNA SNPs in association with severity of IMD was that there was no service available to carry out a full blood count prior to and after the stimulation, thus it is possible that variation in response to stimuli could arise from differences between individual donors’ WCC or activation of their specific white cell sub-populations. Although I managed to set up the full blood count service through the Imperial College NHS Trust, It came inevitably too late for these assays. But this type of analysis will be useful for future studies, where underlying factors due to blood count can be appropriately controlled. Alternatively, PBMCs obtained from healthy control donors can be used for the stimulation assay and the response as well as the leukocyte sub- populations in each sample can be determined quantitative analysis by FACS.

The exciting finding on the lncRNA and genotype dependent manner in which the calcium flux is affected indicates that the identified SNPs may regulate other important signalling pathways of the cell in human health and disease. It would be very interesting to examine whether these lncRNA SNPs will have effects on other cellular signalling mechanisms and the molecular mechanisms underlying their effect in the context of the disease. The next step would be to stimulate the same EBV transformed B cells, representative of the different genotypes and characterise a range of signalling events, including protein-protein interactions, post-translational

VII – Conclusion and future recommendations - 170 - modifications and protein expression. One viable method for this type of analysis is the mass spectrometry-based proteomics approach, which has shown to be highly sensitive over the conventional antibody based procedures, such as western blotting (Choudhary and Mann, 2010).

7.4. Concluding remarks

The findings of the work presented here illustrate the usefulness of the NGS technologies in the discovery of rare and novel variants that may act as important determinants of susceptibility and severity to IMD. The functional characterisation of the genetic variant in SPLUNC1 in the context of meningococcal disease has led to a better understanding of the disease pathogenesis, in particular, the early events of infection development and progression. The suggestive evidence of the innate immune defence function of this protein reported in this thesis, together with the exploration of the structural modifications of this protein reported by others, may facilitate the develop of new therapeutic strategies, perhaps as a prophylactic therapy based on the existing evidence. The molecular characterisation work on the lncRNA SNPs has provided important groundwork for future studies in the exploration of the underlying mechanisms involved in these common polymorphisms in health and severe infectious disease. Overall, the work carried out in this thesis provides evidence that there may be many more genetic aetiologies of IMD, which will need to be elucidated using NGS.

References - 171 -

References

Abdullah, L. H., C. Wolber, M. Kesimer, J. K. Sheehan, and C. W. Davis, 2012, Studying mucin secretion from human bronchial epithelial cell primary cultures: Methods Mol Biol, v. 842, p. 259-77. Abecasis, G. R., D. Altshuler, A. Auton, L. D. Brooks, R. M. Durbin, R. A. Gibbs, M. E. Hurles, G. A. McVean, and G. P. Consortium, 2010, A map of human genome variation from population-scale sequencing: Nature, v. 467, p. 1061- 73. Abecasis, G. R., A. Auton, L. D. Brooks, M. A. DePristo, R. M. Durbin, R. E. Handsaker, H. M. Kang, G. T. Marth, G. A. McVean, and G. P. Consortium, 2012, An integrated map of genetic variation from 1,092 human genomes: Nature, v. 491, p. 56-65. Achtman, M., 1995, Epidemic spread and antigenic variability of Neisseria meningitidis: Trends Microbiol, v. 3, p. 186-92. Adrio, J. L., and A. L. Demain, 2010, Recombinant organisms for production of industrial products: Bioeng Bugs, v. 1, p. 116-31. Akashi, S., S. Saitoh, Y. Wakabayashi, T. Kikuchi, N. Takamura, Y. Nagai, Y. Kusumoto, K. Fukase, S. Kusumoto, Y. Adachi, A. Kosugi, and K. Miyake, 2003, Lipopolysaccharide interaction with cell surface Toll-like receptor 4-MD- 2: higher affinity than that with MD-2 or CD14: J Exp Med, v. 198, p. 1035-42. Akira, S., and S. Sato, 2003, Toll-like receptors and their signaling mechanisms: Scand J Infect Dis, v. 35, p. 555-62. Akram, K. M., N. A. Moyo, G. H. Leeming, L. Bingle, S. Jasim, S. Hussain, A. Schorlemmer, A. Kipar, P. Digard, R. A. Tripp, R. V. Shohet, C. D. Bingle, and J. P. Stewart, 2017, An innate defense peptide BPIFA1/SPLUNC1 restricts influenza A virus infection: Mucosal Immunol. Alcaïs, A., L. Quintana-Murci, D. S. Thaler, E. Schurr, L. Abel, and J. L. Casanova, 2010, Life-threatening infectious diseases of childhood: single-gene inborn errors of immunity?: Ann N Y Acad Sci, v. 1214, p. 18-33. Alphonse, M. P., T. T. Duong, C. Shumitzu, T. L. Hoang, B. W. McCrindle, A. Franco, S. Schurmans, D. J. Philpott, M. L. Hibberd, J. Burns, T. W. Kuijpers, and R. S. Yeung, 2016, Inositol-Triphosphate 3-Kinase C Mediates Inflammasome Activation and Treatment Response in Kawasaki Disease: J Immunol, v. 197, p. 3481-3489. Arenas, J., and J. Tommassen, 2017, Meningococcal Biofilm Formation: Let's Stick Together: Trends Microbiol, v. 25, p. 113-124. Arnold, D. F., A. G. Roberts, A. Thomas, B. Ferry, B. P. Morgan, and H. Chapel, 2009, A novel mutation in a patient with a deficiency of the eighth component

References - 172 -

of complement associated with recurrent meningococcal meningitis: J Clin Immunol, v. 29, p. 691-5. Asmat, T. M., T. Tenenbaum, A. B. Jonsson, C. Schwerk, and H. Schroten, 2014, Impact of calcium signaling during infection of Neisseria meningitidis to human brain microvascular endothelial cells: PLoS One, v. 9, p. e114474. Bakir, M., A. Yagci, N. Ulger, C. Akbenlioglu, A. Ilki, and G. Soyletir, 2001, Asymtomatic carriage of Neisseria meningitidis and Neisseria lactamicain relation to Streptococcus pneumoniae and Haemophilus influenzaecolonization in healthy children: Apropos of 1400 children sampled: Journal of Epidemiology, v. 17, p. 1015-1018. Balding, J., C. M. Healy, W. J. Livingstone, B. White, L. Mynett-Johnson, M. Cafferkey, and O. P. Smith, 2003, Genomic polymorphic profiles in an Irish population with meningococcaemia: is it possible to predict severity and outcome of disease?: Genes Immun, v. 4, p. 533-40. Bamshad, M. J., S. B. Ng, A. W. Bigham, H. K. Tabor, M. J. Emond, D. A. Nickerson, and J. Shendure, 2011, Exome sequencing as a tool for Mendelian disease gene discovery: Nat Rev Genet, v. 12, p. 745-55. Barroso, S., M. López-Trascasa, D. Merino, A. J. Alvarez, A. Núñez-Roldán, and B. Sánchez, 2010, C7 deficiency and meningococcal infection susceptibility in two spanish families: Scand J Immunol, v. 72, p. 38-43. Bartlett, J. A., J. Bartlett, L. Gakhar, J. Penterman, P. K. Singh, P. Singh, R. K. Mallampalli, E. Porter, and P. B. McCray, 2011, PLUNC: a multifunctional surfactant of the airways: Biochem Soc Trans, v. 39, p. 1012-6. Bartlett, J. A., B. J. Hicks, J. M. Schlomann, S. Ramachandran, W. M. Nauseef, and P. B. McCray, 2008, PLUNC is a secreted product of neutrophil granules: J Leukoc Biol, v. 83, p. 1201-6. Berridge, M. J., P. Lipp, and M. D. Bootman, 2000, The versatility and universality of calcium signalling: Nat Rev Mol Cell Biol, v. 1, p. 11-21. Bijlsma, M. W., M. C. Brouwer, L. Spanjaard, D. van de Beek, and A. van der Ende, 2014, A decade of herd protection after introduction of meningococcal serogroup C conjugate vaccination: Clin Infect Dis, v. 59, p. 1216-21. Binder, A., G. Endler, M. Müller, C. Mannhalter, W. Zenz, and E. M. S. Group, 2007, 4G4G genotype of the plasminogen activator inhibitor-1 promoter polymorphism associates with disseminated intravascular coagulation in children with systemic meningococcemia: J Thromb Haemost, v. 5, p. 2049- 54. Bingen, E., N. Lambert-Zechovsky, P. Mariani-Kurkdjian, C. Doit, Y. Aujard, F. Fournerie, and H. Mathieu, 1990, Bacterial counts in cerebrospinal fluid of children with meningitis: Eur J Clin Microbiol Infect Dis, v. 9, p. 278-81.

References - 173 -

Bingle, C. D., and L. Bingle, 2000, Characterisation of the human plunc gene, a gene product with an upper airways and nasopharyngeal restricted expression pattern: Biochim Biophys Acta, v. 1493, p. 363-7. Bingle, C. D., and C. J. Craven, 2002, PLUNC: a novel family of candidate host defence proteins expressed in the upper airways and nasopharynx: Hum Mol Genet, v. 11, p. 937-43. Birney, E., J. A. Stamatoyannopoulos, A. Dutta, R. Guigó, T. R. Gingeras, E. H. Margulies, Z. Weng, M. Snyder, E. T. Dermitzakis, R. E. Thurman, M. S. Kuehn, C. M. Taylor, S. Neph, C. M. Koch, S. Asthana, A. Malhotra, I. Adzhubei, J. A. Greenbaum, R. M. Andrews, P. Flicek, P. J. Boyle, H. Cao, N. P. Carter, G. K. Clelland, S. Davis, N. Day, P. Dhami, S. C. Dillon, M. O. Dorschner, H. Fiegler, P. G. Giresi, J. Goldy, M. Hawrylycz, A. Haydock, R. Humbert, K. D. James, B. E. Johnson, E. M. Johnson, T. T. Frum, E. R. Rosenzweig, N. Karnani, K. Lee, G. C. Lefebvre, P. A. Navas, F. Neri, S. C. Parker, P. J. Sabo, R. Sandstrom, A. Shafer, D. Vetrie, M. Weaver, S. Wilcox, M. Yu, F. S. Collins, J. Dekker, J. D. Lieb, T. D. Tullius, G. E. Crawford, S. Sunyaev, W. S. Noble, I. Dunham, F. Denoeud, A. Reymond, P. Kapranov, J. Rozowsky, D. Zheng, R. Castelo, A. Frankish, J. Harrow, S. Ghosh, A. Sandelin, I. L. Hofacker, R. Baertsch, D. Keefe, S. Dike, J. Cheng, H. A. Hirsch, E. A. Sekinger, J. Lagarde, J. F. Abril, A. Shahab, C. Flamm, C. Fried, J. Hackermüller, J. Hertel, M. Lindemeyer, K. Missal, A. Tanzer, S. Washietl, J. Korbel, O. Emanuelsson, J. S. Pedersen, N. Holroyd, R. Taylor, D. Swarbreck, N. Matthews, M. C. Dickson, D. J. Thomas, M. T. Weirauch, J. Gilbert, et al., 2007, Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project: Nature, v. 447, p. 799-816. Black, F. L., G. Schiffman, and J. P. Pandey, 1995, HLA, Gm, and Km polymorphisms and immunity to infectious diseases in South Amerinds: Exp Clin Immunogenet, v. 12, p. 206-16. Bradley, D. T., T. W. Bourke, D. J. Fairley, R. Borrow, M. D. Shields, I. S. Young, P. F. Zipfel, and A. E. Hughes, 2012, Genetic susceptibility to invasive meningococcal disease: MBL2 structural polymorphisms revisited in a large case-control study and a systematic review: Int J Immunogenet, v. 39, p. 328- 37. Brandtzaeg, P., 2013, Secretory immunity with special reference to the oral cavity: J Oral Microbiol, v. 5. Brandtzaeg, P., A. Bjerre, R. Øvstebø, B. Brusletto, G. B. Joø, and P. Kierulf, 2001, Neisseria meningitidis lipopolysaccharides in human pathology: J Endotoxin Res, v. 7, p. 401-20. Broome, C., 1986, The carrier state: Neisseria meningitidis.: Journal of Antimicrobial Chemotherapy, v. 18, p. 25-34. Brouwer, M. C., J. de Gans, S. G. Heckenberg, A. H. Zwinderman, T. van der Poll, and D. van de Beek, 2009, Host genetic susceptibility to pneumococcal and meningococcal disease: a systematic review and meta-analysis: Lancet Infect Dis, v. 9, p. 31-44.

References - 174 -

Brouwer, M. C., R. C. Read, and D. van de Beek, 2010, Host genetics and outcome in meningococcal disease: a systematic review and meta-analysis: Lancet Infect Dis, v. 10, p. 262-74. Byun, M., A. Abhyankar, V. Lelarge, S. Plancoulaine, A. Palanduz, L. Telhan, B. Boisson, C. Picard, S. Dewell, C. Zhao, E. Jouanguy, S. Feske, L. Abel, and J. L. Casanova, 2010, Whole-exome sequencing-based discovery of STIM1 deficiency in a child with fatal classic Kaposi sarcoma: J Exp Med, v. 207, p. 2307-12. Callaghan, M. J., K. Rockett, C. Banner, E. Haralambous, H. Betts, S. Faust, M. C. Maiden, J. S. Kroll, M. Levin, D. P. Kwiatkowski, and A. J. Pollard, 2008, Haplotypic diversity in human CEACAM genes: effects on susceptibility to meningococcal disease: Genes Immun, v. 9, p. 30-7. Camblong, J., N. Iglesias, C. Fickentscher, G. Dieppois, and F. Stutz, 2007, Antisense RNA stabilization induces transcriptional gene silencing via histone deacetylation in S. cerevisiae: Cell, v. 131, p. 706-17. Carbonnelle, E., S. Helaine, X. Nassif, and V. Pelicic, 2006, A systematic genetic analysis in Neisseria meningitidis defines the Pil proteins required for assembly, functionality, stabilization and export of type IV pili: Mol Microbiol, v. 61, p. 1510-22. Carbonnelle, E., D. J. Hill, P. Morand, N. J. Griffiths, S. Bourdoulous, I. Murillo, X. Nassif, and M. Virji, 2009, Meningococcal interactions with the host: Vaccine, v. 27 Suppl 2, p. B78-89. Carrington, M., G. W. Nelson, M. P. Martin, T. Kissner, D. Vlahov, J. J. Goedert, R. Kaslow, S. Buchbinder, K. Hoots, and S. J. O'Brien, 1999, HLA and HIV-1: heterozygote advantage and B*35-Cw*04 disadvantage: Science, v. 283, p. 1748-52. Casanova, J. L., and L. Abel, 2007, Human genetics of infectious diseases: a unified theory: EMBO J, v. 26, p. 915-22. Caugant, D. A., 2008, Genetics and evolution of Neisseria meningitidis: importance for the epidemiology of meningococcal disease: Infect Genet Evol, v. 8, p. 558-65. Caugant, D. A., G. Tzanakaki, and P. Kriz, 2007, Lessons from meningococcal carriage studies: FEMS Microbiol Rev, v. 31, p. 52-63. Chanock, S. J., T. Manolio, M. Boehnke, E. Boerwinkle, D. J. Hunter, G. Thomas, J. N. Hirschhorn, G. Abecasis, D. Altshuler, J. E. Bailey-Wilson, L. D. Brooks, L. R. Cardon, M. Daly, P. Donnelly, J. F. Fraumeni, N. B. Freimer, D. S. Gerhard, C. Gunter, A. E. Guttmacher, M. S. Guyer, E. L. Harris, J. Hoh, R. Hoover, C. A. Kong, K. R. Merikangas, C. C. Morton, L. J. Palmer, E. G. Phimister, J. P. Rice, J. Roberts, C. Rotimi, M. A. Tucker, K. J. Vogan, S. Wacholder, E. M. Wijsman, D. M. Winn, F. S. Collins, and N.-N. W. G. o. R. i. A. Studies, 2007, Replicating genotype-phenotype associations: Nature, v. 447, p. 655-60.

References - 175 -

Chapman, S. J., and A. V. Hill, 2012, Human genetic susceptibility to infectious disease: Nat Rev Genet, v. 13, p. 175-88. Choudhary, C., and M. Mann, 2010, Decoding signalling networks by mass spectrometry-based proteomics: Nat Rev Mol Cell Biol, v. 11, p. 427-39. Chow, J. C., D. W. Young, D. T. Golenbock, W. J. Christ, and F. Gusovsky, 1999, Toll-like receptor-4 mediates lipopolysaccharide-induced signal transduction: J Biol Chem, v. 274, p. 10689-92. Chu, H. W., J. Thaikoottathil, J. G. Rino, G. Zhang, Q. Wu, T. Moss, Y. Refaeli, R. Bowler, S. E. Wenzel, Z. Chen, J. Zdunek, R. Breed, R. Young, E. Allaire, and R. J. Martin, 2007, Function and regulation of SPLUNC1 protein in Mycoplasma infection and allergic inflammation: J Immunol, v. 179, p. 3995- 4002. Consortium, I. H. G. S., 2004, Finishing the euchromatic sequence of the human genome: Nature, v. 431, p. 931-45. Cooke, G. S., and A. V. Hill, 2001, Genetics of susceptibility to human infectious disease: Nat Rev Genet, v. 2, p. 967-77. Cooper, D. N., J. M. Chen, E. V. Ball, K. Howells, M. Mort, A. D. Phillips, N. Chuzhanova, M. Krawczak, H. Kehrer-Sawatzki, and P. D. Stenson, 2010, Genes, mutations, and human inherited disease at the dawn of the age of personalized genomics: Hum Mutat, v. 31, p. 631-55. Crouch, E., and J. R. Wright, 2001, Surfactant proteins a and d and pulmonary host defense: Annu Rev Physiol, v. 63, p. 521-54. Dale, A. P., and R. C. Read, 2013, Genetic susceptibility to meningococcal infection: Expert Rev Anti Infect Ther, v. 11, p. 187-99. Davila, S., V. J. Wright, C. C. Khor, K. S. Sim, A. Binder, W. B. Breunis, D. Inwald, S. Nadel, H. Betts, E. D. Carrol, R. de Groot, P. W. Hermans, J. Hazelzet, M. Emonts, C. C. Lim, T. W. Kuijpers, F. Martinon-Torres, A. Salas, W. Zenz, M. Levin, M. L. Hibberd, and I. M. G. Consortium, 2010, Genome-wide association study identifies variants in the CFH region associated with host susceptibility to meningococcal disease: Nat Genet, v. 42, p. 772-6. Dentener, M. A., E. J. Von Asmuth, G. J. Francot, M. N. Marra, and W. A. Buurman, 1993, Antagonistic effects of lipopolysaccharide binding protein and bactericidal/permeability-increasing protein on lipopolysaccharide-induced cytokine release by mononuclear phagocytes. Competition for binding to lipopolysaccharide: J Immunol, v. 151, p. 4258-65. Devine, L. F., W. E. Pierce, T. M. Floyd, S. L. Rhode, E. A. Edwards, E. E. Siess, and R. O. Peckinpaugh, 1970, Evaluation of group C meningococcal polysaccharide vaccine in marine recruits, San Diego, California: Am J Epidemiol, v. 92, p. 25-32. Dinger, M. E., P. P. Amaral, T. R. Mercer, K. C. Pang, S. J. Bruce, B. B. Gardiner, M. E. Askarian-Amiri, K. Ru, G. Soldà, C. Simons, S. M. Sunkin, M. L. Crowe, S.

References - 176 -

M. Grimmond, A. C. Perkins, and J. S. Mattick, 2008, Long noncoding RNAs in mouse embryonic stem cell pluripotency and differentiation: Genome Res, v. 18, p. 1433-45. Dolmetsch, R. E., R. S. Lewis, C. C. Goodnow, and J. I. Healy, 1997, Differential activation of transcription factors induced by Ca2+ response amplitude and duration: Nature, v. 386, p. 855-8. Domingo, P., E. Muñiz-Diaz, M. A. Baraldès, M. Arilla, N. Barquet, R. Pericas, C. Juárez, P. Madoz, and G. Vázquez, 2002, Associations between Fc gamma receptor IIA polymorphisms and the risk and prognosis of meningococcal disease: Am J Med, v. 112, p. 19-25. Edwards, E. A., L. F. Devine, G. H. Sengbusch, and H. W. Ward, 1977, Immunological investigations of meningococcal disease. III. Brevity of group C acquisition prior to disease occurrence: Scand J Infect Dis, v. 9, p. 105-10. Elsbach, P., and J. Weiss, 1998, Role of the bactericidal/permeability-increasing protein in host defence: Curr Opin Immunol, v. 10, p. 45-9. Emonts, M., J. A. Hazelzet, R. de Groot, and P. W. Hermans, 2003, Host genetic determinants of Neisseria meningitidis infections: Lancet Infect Dis, v. 3, p. 565-77. Emonts, M., C. L. Vermont, J. J. Houwing-Duistermaat, E. Haralambous, C. E. Gaast-de Jongh, J. A. Hazelzet, S. N. Faust, H. Betts, P. W. Hermans, M. Levin, R. de Groot, and S. M. s.-I. C. a. E. M.-S. C. s. H. M. R. Groups, 2010, Polymorphisms in PARP, IL1B, IL4, IL10, C1INH, DEFB1, and DEFA4 in meningococcal disease in three populations: Shock, v. 34, p. 17-22. Exley, R. M., R. Sim, L. Goodwin, M. Winterbotham, M. C. Schneider, R. C. Read, and C. M. Tang, 2009, Identification of meningococcal genes necessary for colonization of human upper airway tissue: Infect Immun, v. 77, p. 45-51. Faber, J., T. Schuessler, A. Finn, C. Murdoch, W. Zenz, P. Habermehl, C. U. Meyer, B. U. Zabel, H. Schmitt, F. Zepp, and M. Knuf, 2007, Age-dependent association of human mannose-binding lectin mutations with susceptibility to invasive meningococcal disease in childhood: Pediatr Infect Dis J, v. 26, p. 243-6. Faur, Y. C., M. H. Weisburd, and M. E. Wilson, 1975, Isolation of Neisseria meningitidis from the Genito-Urinary Tract and Anal Canal. Fenton, M. J., and D. T. Golenbock, 1998, LPS-binding proteins and receptors: J Leukoc Biol, v. 64, p. 25-32. Figueroa, J. E., and P. Densen, 1991, Infectious diseases associated with complement deficiencies: Clin Microbiol Rev, v. 4, p. 359-95. Fijen, C. A., E. J. Kuijper, M. T. te Bulte, M. R. Daha, and J. Dankert, 1999, Assessment of complement deficiency in patients with meningococcal disease in The Netherlands: Clin Infect Dis, v. 28, p. 98-105.

References - 177 -

Findlow, H., R. Borrow, P. Hardelid, E. Newton, S. Frankland, S. Naylor, E. Miller, E. Kaczmarski, and R. C. Read, 2011, Serum antibody kinetics following nasal or parenteral challenge with meningococcal polysaccharide in healthy adults: Clin Vaccine Immunol, v. 18, p. 424-9. Fogel, B. L., H. Lee, J. L. Deignan, S. P. Strom, S. Kantarci, X. Wang, F. Quintero- Rivera, E. Vilain, W. W. Grody, S. Perlman, D. H. Geschwind, and S. F. Nelson, 2014, Exome sequencing in the clinical diagnosis of sporadic or familial cerebellar ataxia: JAMA Neurol, v. 71, p. 1237-46. Fredrikson, G. N., J. Westberg, E. J. Kuijper, C. C. Tijssen, A. G. Sjöholm, M. Uhlén, and L. Truedsson, 1996, Molecular characterization of properdin deficiency type III: dysfunction produced by a single point mutation in exon 9 of the structural gene causing a tyrosine to aspartic acid interchange: J Immunol, v. 157, p. 3666-71. Gakhar, L., J. A. Bartlett, J. Penterman, D. Mizrachi, P. K. Singh, R. K. Mallampalli, S. Ramaswamy, and P. B. McCray, 2010, PLUNC is a novel airway surfactant protein with anti-biofilm activity: PLoS One, v. 5, p. e9098. Gally, F., Y. P. Di, S. K. Smith, M. N. Minor, Y. Liu, D. L. Bratton, S. C. Frasch, N. M. Michels, S. R. Case, and H. W. Chu, 2011, SPLUNC1 promotes lung innate defense against Mycoplasma pneumoniae infection in mice: Am J Pathol, v. 178, p. 2159-67. Ganz, T., and J. Weiss, 1997, Antimicrobial peptides of phagocytes and epithelia: Semin Hematol, v. 34, p. 343-54. Garcia-Caballero, A., J. E. Rasmussen, E. Gaillard, M. J. Watson, J. C. Olsen, S. H. Donaldson, M. J. Stutts, and R. Tarran, 2009, SPLUNC1 regulates airway surface liquid volume by protecting ENaC from proteolytic cleavage: Proc Natl Acad Sci U S A, v. 106, p. 11412-7. Garland, A. L., W. G. Walton, R. D. Coakley, C. D. Tan, R. C. Gilmore, C. A. Hobbs, A. Tripathy, L. A. Clunes, S. Bencharit, M. J. Stutts, L. Betts, M. R. Redinbo, and R. Tarran, 2013, Molecular basis for pH-dependent mucosal dehydration in cystic fibrosis airways: Proc Natl Acad Sci U S A, v. 110, p. 15973-8. Gasparini, R., D. Panatto, N. L. Bragazzi, P. L. Lai, A. Bechini, M. Levi, P. Durando, and D. Amicizia, 2015, How the Knowledge of Interactions between Meningococcus and the Human Immune System Has Been Used to Prepare Effective Neisseria meningitidis Vaccines: J Immunol Res, v. 2015, p. 189153. Geishofer, G., A. Binder, M. Müller, B. Zöhrer, B. Resch, W. Müller, J. Faber, A. Finn, G. Endler, C. Mannhalter, W. Zenz, and C. E. M. G. S. Group, 2005, 4G/5G promoter polymorphism in the plasminogen-activator-inhibitor-1 gene in children with systemic meningococcaemia: Eur J Pediatr, v. 164, p. 486-90. Gekara, N. O., K. Westphal, B. Ma, M. Rohde, L. Groebe, and S. Weiss, 2007, The multiple mechanisms of Ca2+ signalling by listeriolysin O, the cholesterol- dependent cytolysin of Listeria monocytogenes: Cell Microbiol, v. 9, p. 2008- 21.

References - 178 -

Gewirtz, A. T., A. S. Rao, P. O. Simon, D. Merlin, D. Carnes, J. L. Madara, and A. S. Neish, 2000, Salmonella typhimurium induces epithelial IL-8 expression via Ca(2+)-mediated activation of the NF-kappaB pathway: J Clin Invest, v. 105, p. 79-92. Ghafouri, B., K. Irander, J. Lindbom, C. Tagesson, and M. Lindahl, 2006, Comparative proteomics of nasal fluid in seasonal allergic rhinitis: J Proteome Res, v. 5, p. 330-8. Ghafouri, B., E. Kihlström, C. Tagesson, and M. Lindahl, 2004, PLUNC in human nasal lavage fluid: multiple isoforms that bind to lipopolysaccharide: Biochim Biophys Acta, v. 1699, p. 57-63. Ghafouri, B., B. Ståhlbom, C. Tagesson, and M. Lindahl, 2002, Newly identified proteins in human nasal lavage fluid from non-smokers and smokers using two-dimensional gel electrophoresis and peptide mass fingerprinting: Proteomics, v. 2, p. 112-20. Goldschneider, I., E. C. Gotschlich, and M. S. Artenstein, 1969a, Human immunity to the meningococcus. I. The role of humoral antibodies: J Exp Med, v. 129, p. 1307-26. Goldschneider, I., E. C. Gotschlich, and M. S. Artenstein, 1969b, Human immunity to the meningococcus. II. Development of natural immunity: J Exp Med, v. 129, p. 1327-48. Gonzaga-Jauregui, C., T. Harel, T. Gambin, M. Kousi, L. B. Griffin, L. Francescatto, B. Ozes, E. Karaca, S. N. Jhangiani, M. N. Bainbridge, K. S. Lawson, D. Pehlivan, Y. Okamoto, M. Withers, P. Mancias, A. Slavotinek, P. J. Reitnauer, M. T. Goksungur, M. Shy, T. O. Crawford, M. Koenig, J. Willer, B. N. Flores, I. Pediaditrakis, O. Us, W. Wiszniewski, Y. Parman, A. Antonellis, D. M. Muzny, N. Katsanis, E. Battaloglu, E. Boerwinkle, R. A. Gibbs, J. R. Lupski, and B.-H. C. f. M. Genomics, 2015, Exome Sequence Analysis Suggests that Genetic Burden Contributes to Phenotypic Variability and Complex Neuropathy: Cell Rep, v. 12, p. 1169-83. Gotschlich, E. C., I. Golschneider, and M. S. Arstenstein, 1969, Human immunity to the meningococcus. IV. Immunogenicity of group A and group C meningococcal polysaccharides in human volunteers: J. Expt. Med, v. 129, p. 1367 - 1384. Greene, C. M., T. P. Carroll, S. G. Smith, C. C. Taggart, J. Devaney, S. Griffin, S. J. O'neill, and N. G. McElvaney, 2005, TLR-induced inflammation in cystic fibrosis and non-cystic fibrosis airway epithelial cells: J Immunol, v. 174, p. 1638-46. Grifantini, R., E. Bartolini, A. Muzzi, M. Draghi, E. Frigimelica, J. Berger, G. Ratti, R. Petracca, G. Galli, M. Agnusdei, M. M. Giuliani, L. Santini, B. Brunelli, H. Tettelin, R. Rappuoli, F. Randazzo, and G. Grandi, 2002, Previously unrecognized vaccine candidates against group B meningococcus identified by DNA microarrays: Nat Biotechnol, v. 20, p. 914-21.

References - 179 -

Griffiss, J. M., B. L. Brandt, P. L. Altieri, G. B. Pier, and S. L. Berman, 1981, Safety and immunogenicity of group Y and group W135 meningococcal capsular polysaccharide vaccines in adults: Infect Immun, v. 34, p. 725-32. Haralambous, E., S. O. Dolly, M. L. Hibberd, D. J. Litt, I. A. Udalova, C. O'dwyer, P. R. Langford, J. Simon Kroll, and M. Levin, 2006, Factor H, a regulator of complement activity, is a major determinant of meningococcal disease susceptibility in UK Caucasian patients: Scand J Infect Dis, v. 38, p. 764-71. Haralambous, E., H. A. Weiss, A. Radalowicz, M. L. Hibberd, R. Booy, and M. Levin, 2003, Sibling familial risk ratio of meningococcal disease in UK Caucasians: Epidemiol Infect, v. 130, p. 413-8. Hellwig, S., and B. L. Bass, 2008, A starvation-induced noncoding RNA modulates expression of Dicer-regulated genes: Proc Natl Acad Sci U S A, v. 105, p. 12897-902. Hey, A., M. S. Li, M. J. Hudson, P. R. Langford, and J. S. Kroll, 2013, Transcriptional profiling of Neisseria meningitidis interacting with human epithelial cells in a long-term in vitro colonization model: Infect Immun, v. 81, p. 4149-59. Hibberd, M., J. Summerfield, and M. Levin, 2001, Variation in the Mannose Binding Lectin (MBL) Gene and Susceptibility to Sepsis, p. 201-207. Hibberd, M. L., M. Sumiya, J. A. Summerfield, R. Booy, and M. Levin, 1999, Association of variants of the gene for mannose-binding lectin with susceptibility to meningococcal disease. Meningococcal Research Group: Lancet, v. 353, p. 1049-53. Hill, A. V., 2006, Aspects of genetic susceptibility to human infectious diseases: Annu Rev Genet, v. 40, p. 469-86. Hirschhorn, J. N., and M. J. Daly, 2005, Genome-wide association studies for common diseases and complex traits: Nat Rev Genet, v. 6, p. 95-108. Hoischen, A., B. W. van Bon, C. Gilissen, P. Arts, B. van Lier, M. Steehouwer, P. de Vries, R. de Reuver, N. Wieskamp, G. Mortier, K. Devriendt, M. Z. Amorim, N. Revencu, A. Kidd, M. Barbosa, A. Turner, J. Smith, C. Oley, A. Henderson, I. M. Hayes, E. M. Thompson, H. G. Brunner, B. B. de Vries, and J. A. Veltman, 2010, De novo mutations of SETBP1 cause Schinzel-Giedion syndrome: Nat Genet, v. 42, p. 483-5. Ingalls, R. R., E. Lien, and D. T. Golenbock, 2001, Membrane-associated proteins of a lipopolysaccharide-deficient mutant of Neisseria meningitidis activate the inflammatory response through toll-like receptor 2: Infect Immun, v. 69, p. 2230-6. Israel, L., Y. Wang, K. Bulek, E. Della Mina, Z. Zhang, V. Pedergnana, M. Chrabieh, N. A. Lemmens, V. Sancho-Shimizu, M. Descatoire, T. Lasseau, E. Israelsson, L. Lorenzo, L. Yun, A. Belkadi, A. Moran, L. E. Weisman, F. Vandenesch, F. Batteux, S. Weller, M. Levin, J. Herberg, A. Abhyankar, C. Prando, Y. Itan, W. J. van Wamel, C. Picard, L. Abel, D. Chaussabel, X. Li, B. Beutler, P. D. Arkwright, J. L. Casanova, and A. Puel, 2017, Human Adaptive

References - 180 -

Immunity Rescues an Inborn Error of Innate Immunity: Cell, v. 168, p. 789- 800.e10. Itan, Y., L. Shang, B. Boisson, E. Patin, A. Bolze, M. Moncada-Vélez, E. Scott, M. J. Ciancanelli, F. G. Lafaille, J. G. Markle, R. Martinez-Barricarte, S. J. de Jong, X. F. Kong, P. Nitschke, A. Belkadi, J. Bustamante, A. Puel, S. Boisson- Dupuis, P. D. Stenson, J. G. Gleeson, D. N. Cooper, L. Quintana-Murci, J. M. Claverie, S. Y. Zhang, L. Abel, and J. L. Casanova, 2015, The human gene damage index as a gene-level approach to prioritizing exome variants: Proc Natl Acad Sci U S A, v. 112, p. 13615-20. Iyer, M. K., Y. S. Niknafs, R. Malik, U. Singhal, A. Sahu, Y. Hosono, T. R. Barrette, J. R. Prensner, J. R. Evans, S. Zhao, A. Poliakov, X. Cao, S. M. Dhanasekaran, Y. M. Wu, D. R. Robinson, D. G. Beer, F. Y. Feng, H. K. Iyer, and A. M. Chinnaiyan, 2015, The landscape of long noncoding RNAs in the human transcriptome: Nat Genet, v. 47, p. 199-208. Jack, D. L., J. Cole, S. C. Naylor, R. Borrow, E. B. Kaczmarski, N. J. Klein, and R. C. Read, 2006, Genetic polymorphism of the binding domain of surfactant protein-A2 increases susceptibility to meningococcal disease: Clin Infect Dis, v. 43, p. 1426-33. Jacquier, A., 2009, The complex eukaryotic transcriptome: unexpected pervasive transcription and novel small RNAs: Nat Rev Genet, v. 10, p. 833-44. James, S. P., W. D. Nicol, and P. G. Shute, 1932, A Study of Induced Malignant Tertian Malaria: Proc R Soc Med, v. 25, p. 1153-86. Johansson, L., A. Rytkonen, P. Bergman, B. Albiger, H. Källström, T. Hökfelt, B. Agerberth, R. Cattaneo, and A. B. Jonsson, 2003, CD46 in meningococcal disease: Science, v. 301, p. 373-5. Jones, G. R., M. Christodoulides, J. L. Brooks, A. R. Miller, K. A. Cartwright, and J. E. Heckels, 1998, Dynamics of carriage of Neisseria meningitidis in a group of military recruits: subtype stability and specificity of the immune response following colonization: J Infect Dis, v. 178, p. 451-9. Jouanguy, E., F. Altare, S. Lamhamedi, P. Revy, J. F. Emile, M. Newport, M. Levin, S. Blanche, E. Seboun, A. Fischer, and J. L. Casanova, 1996, Interferon- gamma-receptor deficiency in an infant with fatal bacille Calmette-Guérin infection: N Engl J Med, v. 335, p. 1956-61. Kaplan, J. B., and D. H. Fine, 2002, Biofilm dispersal of Neisseria subflava and other phylogenetically diverse oral bacteria: Appl Environ Microbiol, v. 68, p. 4943- 50. Kim, T. K., and J. H. Eberwine, 2010, Mammalian cell transfection: the present and the future: Anal Bioanal Chem, v. 397, p. 3173-8. Kinniment, S. L., J. W. Wimpenny, D. Adams, and P. D. Marsh, 1996, Development of a steady-state oral microbial biofilm community using the constant-depth film fermenter: Microbiology, v. 142 ( Pt 3), p. 631-8.

References - 181 -

Ku, C. L., H. von Bernuth, C. Picard, S. Y. Zhang, H. H. Chang, K. Yang, M. Chrabieh, A. C. Issekutz, C. K. Cunningham, J. Gallin, S. M. Holland, C. Roifman, S. Ehl, J. Smart, M. Tang, F. J. Barrat, O. Levy, D. McDonald, N. K. Day-Good, R. Miller, H. Takada, T. Hara, S. Al-Hajjar, A. Al-Ghonaium, D. Speert, D. Sanlaville, X. Li, F. Geissmann, E. Vivier, L. Maródi, B. Z. Garty, H. Chapel, C. Rodriguez-Gallego, X. Bossuyt, L. Abel, A. Puel, and J. L. Casanova, 2007, Selective predisposition to bacterial infections in IRAK-4- deficient children: IRAK-4-dependent TLRs are otherwise redundant in protective immunity: J Exp Med, v. 204, p. 2407-22. Ku, C. S., D. N. Cooper, C. Polychronakos, N. Naidoo, M. Wu, and R. Soong, 2012, Exome sequencing: dual role as a discovery and diagnostic tool: Ann Neurol, v. 71, p. 5-14. Kvalsvig, A. J., and D. J. Unsworth, 2003, The immunopathogenesis of meningococcal disease: J Clin Pathol, v. 56, p. 417-22. LaForce, F. M., and J. Okwo-Bele, 2011, Eliminating epidemic Group A meningococcal meningitis in Africa through a new vaccine. Lappann, M., H. Claus, T. van Alen, M. Harmsen, J. Elias, S. Molin, and U. Vogel, 2010, A dual role of extracellular DNA during biofilm formation of Neisseria meningitidis: Mol Microbiol, v. 75, p. 1355-71. Lappann, M., S. Danhof, F. Guenther, S. Olivares-Florez, I. L. Mordhorst, and U. Vogel, 2013, In vitro resistance mechanisms of Neisseria meningitidis against neutrophil extracellular traps: Mol Microbiol, v. 89, p. 433-49. Lappann, M., J. A. Haagensen, H. Claus, U. Vogel, and S. Molin, 2006, Meningococcal biofilm formation: structure, development and phenotypes in a standardized continuous flow system: Mol Microbiol, v. 62, p. 1292-309. Laver, J. R., S. E. Hughes, and R. C. Read, 2015, Neisserial Molecular Adaptations to the Nasopharyngeal Niche: Adv Microb Physiol, v. 66, p. 323-55. Lederberg, J., 1999, J. B. S. Haldane (1949) on infectious disease and evolution: Genetics, v. 153, p. 1-3. Lee, W., Y. Zhang, K. Mukhyala, R. A. Lazarus, and Z. Zhang, 2009, Bi-directional SIFT predicts a subset of activating mutations: PLoS One, v. 4, p. e8311. Leonhardt, A., J. Olsson, and G. Dahlén, 1995, Bacterial colonization on titanium, hydroxyapatite, and amalgam surfaces in vivo: J Dent Res, v. 74, p. 1607-12. Liu, Y., J. A. Bartlett, M. E. Di, J. M. Bomberger, Y. R. Chan, L. Gakhar, R. K. Mallampalli, P. B. McCray, and Y. P. Di, 2013a, SPLUNC1/BPIFA1 contributes to pulmonary host defense against Klebsiella pneumoniae respiratory infection: Am J Pathol, v. 182, p. 1519-31. Liu, Y., M. Di, H. W. Chu, X. Liu, L. Wang, S. Wenzel, and P. Di, 2013b, Increased Susceptibility to Pulmonary Pseudomonas Infection in Splunc1 Knockout Mice.

References - 182 -

Liu, Y., M. Di, H. W. Chu, X. Liu, L. Wang, S. Wenzel, and P. Di, 2013c, Increased Susceptibility to Pulmonary Pseudomonas Infection in Splunc1 Knockout Mice. Liu, Y., M. E. Di, H. W. Chu, X. Liu, L. Wang, S. Wenzel, and Y. P. Di, 2013d, Increased susceptibility to pulmonary Pseudomonas infection in Splunc1 knockout mice: J Immunol, v. 191, p. 4259-68. Lo, H., C. M. Tang, and R. M. Exley, 2009, Mechanisms of avoidance of host immunity by Neisseria meningitidis and its effect on vaccine development: Lancet Infect Dis, v. 9, p. 418-27. Lukinskiene, L., Y. Liu, S. D. Reynolds, C. Steele, B. R. Stripp, G. D. Leikauf, J. K. Kolls, and Y. P. Di, 2011, Antimicrobial activity of PLUNC protects against Pseudomonas aeruginosa infection: J Immunol, v. 187, p. 382-90. MacLennan, J., G. Kafatos, K. Neal, N. Andrews, J. C. Cameron, R. Roberts, M. R. Evans, K. Cann, D. N. Baxter, M. C. Maiden, J. M. Stuart, and U. K. M. C. Group, 2006, Social behavior and meningococcal carriage in British teenagers: Emerg Infect Dis, v. 12, p. 950-7. Macneil, C., 2011, Chapter 8: Meningococcal disease. VPD surveillance manual, Atlanta, GA, Centers for Disease Control and Prevention. Mamanova, L., A. J. Coffey, C. E. Scott, I. Kozarewa, E. H. Turner, A. Kumar, E. Howard, J. Shendure, and D. J. Turner, 2010, Target-enrichment strategies for next-generation sequencing: Nat Methods, v. 7, p. 111-8. Mantis, N. J., N. Rol, and B. Corthésy, 2011, Secretory IgA's complex roles in immunity and mucosal homeostasis in the gut: Mucosal Immunol, v. 4, p. 603- 11. Mariner, P. D., R. D. Walters, C. A. Espinoza, L. F. Drullinger, S. D. Wagner, J. F. Kugel, and J. A. Goodrich, 2008, Human Alu RNA is a modular transacting repressor of mRNA transcription during heat shock: Mol Cell, v. 29, p. 499- 509. Martinón-Torres, F., E. Png, C. C. Khor, S. Davila, V. J. Wright, K. S. Sim, A. Vega, L. Fachal, D. Inwald, S. Nadel, E. D. Carrol, N. Martinón-Torres, S. M. Alonso, A. Carracedo, E. Morteruel, J. López-Bayón, A. C. Torre, C. C. Monge, P. A. de Aguilar, E. E. Torné, M. D. Martínez-Padilla, J. M. Martinón-Sánchez, M. Levin, M. L. Hibberd, A. Salas, E. network, E. m. c. UK, and E. c. m.-I. C. L. (www.euclids-project.eu), 2016, Natural resistance to Meningococcal Disease related to CFH loci: Meta-analysis of genome-wide association studies: Sci Rep, v. 6, p. 35842. McGillivary, G., and L. O. Bakaletz, 2010, The multifunctional host defense peptide SPLUNC1 is critical for homeostasis of the mammalian upper airway: PLoS One, v. 5, p. e13224. Medvedev, A. E., A. Lentschat, D. B. Kuhns, J. C. Blanco, C. Salkowski, S. Zhang, M. Arditi, J. I. Gallin, and S. N. Vogel, 2003, Distinct mutations in IRAK-4

References - 183 -

confer hyporesponsiveness to lipopolysaccharide and interleukin-1 in a patient with recurrent bacterial infections: J Exp Med, v. 198, p. 521-31. Medzhitov, R., 2013, Pattern recognition theory and the launch of modern innate immunity: J Immunol, v. 191, p. 4473-4. Mercer, T. R., M. E. Dinger, S. M. Sunkin, M. F. Mehler, and J. S. Mattick, 2008, Specific expression of long noncoding RNAs in the mouse brain: Proc Natl Acad Sci U S A, v. 105, p. 716-21. Misch, E. A., W. R. Berrington, J. C. Vary, and T. R. Hawn, 2010, Leprosy and the human genome: Microbiol Mol Biol Rev, v. 74, p. 589-620. Mogensen, T. H., S. R. Paludan, M. Kilian, and L. Ostergaard, 2006, Live Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis activate the inflammatory response through Toll-like receptors 2, 4, and 9 in species-specific patterns: J Leukoc Biol, v. 80, p. 267-77. Morgan, B. P., K. J. Marchbank, M. P. Longhi, C. L. Harris, and A. M. Gallimore, 2005, Complement: central to innate immunity and bridging to adaptive responses: Immunol Lett, v. 97, p. 171-9. Murphy, P. M., 1993, Molecular mimicry and the generation of host defense protein diversity: Cell, v. 72, p. 823-6. Musa, M., K. Wilson, L. Sun, A. Mulay, L. Bingle, H. M. Marriott, E. E. LeClair, and C. D. Bingle, 2012, Differential localisation of BPIFA1 (SPLUNC1) and BPIFB1 (LPLUNC1) in the nasal and oral cavities of mice: Cell Tissue Res, v. 350, p. 455-64. Nadel, S., 2016, Treatment of Meningococcal Disease: Journal of Adolescent Health, v. 59, p. S21-S28. Nadel, S., M. J. Newport, R. Booy, and M. Levin, 1996, Variation in the tumor necrosis factor-alpha gene promoter region may be associated with death from meningococcal disease: J Infect Dis, v. 174, p. 878-80. Neal, K. R., J. S. Nguyen-van-Tam, R. C. Slack, E. B. Kaczmarski, A. White, and D. A. Ala'Aldeen, 1999, Seven-week interval between acquisition of a meningococcus and the onset of invasive disease. A case report: Epidemiol Infect, v. 123, p. 507-9. Neil, R. B., and M. A. Apicella, 2009, Clinical and laboratory evidence for Neisseria meningitidis biofilms: Future Microbiol, v. 4, p. 555-63. Neil, R. B., J. Q. Shao, and M. A. Apicella, 2009, Biofilm formation on human airway epithelia by encapsulated Neisseria meningitidis serogroup B: Microbes Infect, v. 11, p. 281-7. Newport, M. J., C. M. Huxley, S. Huston, C. M. Hawrylowicz, B. A. Oostra, R. Williamson, and M. Levin, 1996, A mutation in the interferon-gamma-receptor gene and susceptibility to mycobacterial infection: N Engl J Med, v. 335, p. 1941-9.

References - 184 -

Ng, S. B., K. J. Buckingham, C. Lee, A. W. Bigham, H. K. Tabor, K. M. Dent, C. D. Huff, P. T. Shannon, E. W. Jabs, D. A. Nickerson, J. Shendure, and M. J. Bamshad, 2010, Exome sequencing identifies the cause of a mendelian disorder: Nat Genet, v. 42, p. 30-5. Nolte, O., A. Rickert, I. Ehrhard, S. Ledig, and H. G. Sonntag, 2002, A modified ex vivo human whole blood model of infection for studying the pathogenesis of Neisseria meningitidis during septicemia: FEMS Immunol Med Microbiol, v. 32, p. 91-5. Nägele, V., J. Heesemann, S. Schielke, L. F. Jiménez-Soto, O. Kurzai, and N. Ackermann, 2011, Neisseria meningitidis adhesin NadA targets beta1 integrins: functional similarity to Yersinia invasin: J Biol Chem, v. 286, p. 20536-46. O'Connell, J., D. Gurdasani, O. Delaneau, N. Pirastu, S. Ulivi, M. Cocca, M. Traglia, J. Huang, J. E. Huffman, I. Rudan, R. McQuillan, R. M. Fraser, H. Campbell, O. Polasek, G. Asiki, K. Ekoru, C. Hayward, A. F. Wright, V. Vitart, P. Navarro, J. F. Zagury, J. F. Wilson, D. Toniolo, P. Gasparini, N. Soranzo, M. S. Sandhu, and J. Marchini, 2014, A general approach for haplotype phasing across the full spectrum of relatedness: PLoS Genet, v. 10, p. e1004234. O'Dwyer, C. A., M. S. Li, P. R. Langford, and J. S. Kroll, 2009, Meningococcal biofilm growth on an abiotic surface - a model for epithelial colonization?: Microbiology, v. 155, p. 1940-52. O'Toole, G. A., L. A. Pratt, P. I. Watnick, D. K. Newman, V. B. Weaver, and R. Kolter, 1999, Genetic approaches to study of biofilms: Methods Enzymol, v. 310, p. 91-109. Okada, S., A. Puel, J. L. Casanova, and M. Kobayashi, 2016, Chronic mucocutaneous candidiasis disease associated with inborn errors of IL-17 immunity: Clin Transl Immunology, v. 5, p. e114. Olea, A., I. Matute, C. González, I. Delgado, L. Poffald, E. Pedroni, T. Alfaro, M. Hirmas, M. Nájera, A. Gormaz, D. López, S. Loayza, C. Ferreccio, D. Gallegos, R. Fuentes, P. Vial, and X. Aguilera, 2017, Case-Control Study of Risk Factors for Meningococcal Disease in Chile: Emerg Infect Dis, v. 23, p. 1070-1078. Opitz, D., M. Clausen, and B. Maier, 2009, Dynamics of gonococcal type IV pili during infection: Chemphyschem, v. 10, p. 1614-8. Orren, A., E. P. Owen, H. E. Henderson, L. van der Merwe, F. Leisegang, C. Stassen, and P. C. Potter, 2012, Complete deficiency of the sixth complement component (C6Q0), susceptibility to Neisseria meningitidis infections and analysis of the frequencies of C6Q0 gene defects in South Africans: Clin Exp Immunol, v. 167, p. 459-71. Pace, D., and A. J. Pollard, 2012, Meningococcal disease: clinical presentation and sequelae: Vaccine, v. 30 Suppl 2, p. B3-9.

References - 185 -

Panagiotou, O. A., J. P. A. Ioannidis, and f. t. G.-W. S. Project, 2012, What should the genome-wide significance threshold be? Empirical replication of borderline genetic associations. What should the genome-wide significance threshold be? Empirical replication of borderline genetic associations. : International Journal of EpidemiologyInternational Journal of Epidemiology, v. 41, p. 273-286. Parikh, S. R., N. J. Andrews, K. Beebeejaun, H. Campbell, S. Ribeiro, C. Ward, J. M. White, R. Borrow, M. E. Ramsay, and S. N. Ladhani, 2016, Effectiveness and impact of a reduced infant schedule of 4CMenB vaccine against group B meningococcal disease in England: a national observational cohort study: Lancet, v. 388, p. 2775-2782. Pathan, N., S. N. Faust, and M. Levin, 2003, Pathophysiology of meningococcal meningitis and septicaemia: Arch Dis Child, v. 88, p. 601-7. Pathan, N., C. A. Hemingway, A. A. Alizadeh, A. C. Stephens, J. C. Boldrick, E. E. Oragui, C. McCabe, S. B. Welch, A. Whitney, P. O'Gara, S. Nadel, D. A. Relman, S. E. Harding, and M. Levin, 2004, Role of interleukin 6 in myocardial dysfunction of meningococcal septic shock: Lancet, v. 363, p. 203-9. Pelton, S. I., 2016, The Global Evolution of Meningococcal Epidemiology Following the Introduction of Meningococcal Vaccines: J Adolesc Health, v. 59, p. S3- S11. Petersen, L., G. G. Nielsen, P. K. Andersen, and T. I. Sørensen, 2002, Case-control study of genetic and environmental influences on premature death of adult adoptees: Genet Epidemiol, v. 23, p. 123-32. Picard, C., J. L. Casanova, and L. Abel, 2006, Mendelian traits that confer predisposition or resistance to specific infections in humans: Curr Opin Immunol, v. 18, p. 383-90. Platonov, A. E., G. A. Shipulin, I. V. Vershinina, J. Dankert, J. G. van de Winkel, and E. J. Kuijper, 1998, Association of human Fc gamma RIIa (CD32) polymorphism with susceptibility to and severity of meningococcal disease: Clin Infect Dis, v. 27, p. 746-50. Pollard, A. J., R. Galassini, E. M. Rouppe van der Voort, M. Hibberd, R. Booy, P. Langford, S. Nadel, C. Ison, J. S. Kroll, J. Poolman, and M. Levin, 1999, Cellular immune responses to Neisseria meningitidis in children: Infect Immun, v. 67, p. 2452-63. Pope, B., and H. M. Kent, 1996, High efficiency 5 min transformation of Escherichia coli: Nucleic Acids Res, v. 24, p. 536-7. Prasanth, K. V., and D. L. Spector, 2007, Eukaryotic regulatory RNAs: an answer to the 'genome complexity' conundrum: Genes Dev, v. 21, p. 11-42. Rabbani, B., N. Mahdieh, K. Hosomichi, H. Nakaoka, and I. Inoue, 2012, Next- generation sequencing: impact of exome sequencing in characterizing Mendelian disorders: J Hum Genet, v. 57, p. 621-32.

References - 186 -

Rayner, C. F., A. Dewar, E. R. Moxon, M. Virji, and R. Wilson, 1995, The effect of variations in the expression of pili on the interaction of Neisseria meningitidis with human nasopharyngeal epithelium: J Infect Dis, v. 171, p. 113-21. Read, R. C., N. J. Camp, F. S. di Giovine, R. Borrow, E. B. Kaczmarski, A. G. Chaudhary, A. J. Fox, and G. W. Duff, 2000, An interleukin-1 genotype is associated with fatal outcome of meningococcal disease: J Infect Dis, v. 182, p. 1557-60. Read, R. C., A. Fox, K. Miller, T. Gray, N. Jones, R. Borrows, D. M. Jones, and R. G. Finch, 1995, Experimental infection of human nasal mucosal explants with Neisseria meningitidis: J Med Microbiol, v. 42, p. 353-61. Read, R. C., R. Wilson, A. Rutman, V. Lund, H. C. Todd, A. P. Brain, P. K. Jeffery, and P. J. Cole, 1991, Interaction of nontypable Haemophilus influenzae with human respiratory mucosa in vitro: J Infect Dis, v. 163, p. 549-58. Reuschl, A. K., M. R. Edwards, R. Parker, D. W. Connell, L. Hoang, A. Halliday, H. Jarvis, N. Siddiqui, C. Wright, S. Bremang, S. M. Newton, P. Beverley, R. J. Shattock, O. M. Kon, and A. Lalvani, 2017, Innate activation of human primary epithelial cells broadens the host response to Mycobacterium tuberculosis in the airways: PLoS Pathog, v. 13, p. e1006577. Robinson, K., K. R. Neal, C. Howard, J. Stockton, K. Atkinson, E. Scarth, J. Moran, A. Robins, I. Todd, E. Kaczmarski, S. Gray, I. Muscat, R. Slack, and D. A. Ala'Aldeen, 2002, Characterization of humoral and cellular immune responses elicited by meningococcal carriage: Infect Immun, v. 70, p. 1301-9. Rosano, G. L., and E. A. Ceccarelli, 2014, Recombinant protein expression in Escherichia coli: advances and challenges: Front Microbiol, v. 5, p. 172. Räth, S., S. Ziesemer, A. Witte, A. Konkel, C. Müller, P. Hildebrandt, U. Völker, and J.-P. Hildebrandt, 2013, S. aureus haemolysin A-induced IL-8 and IL-6 release from human airway epithelial cells is mediated by activation of p38- and Erk-MAP kinases and additional, cell type-specific signalling mechanisms: Cellular microbiology, v. 15, p. 1253-1265. Sanders, M. S., G. T. van Well, S. Ouburg, P. S. Lundberg, A. M. van Furth, and S. A. Morré, 2011a, Single nucleotide polymorphisms in TLR9 are highly associated with susceptibility to bacterial meningitis in children: Clin Infect Dis, v. 52, p. 475-80. Sanders, M. S., G. T. van Well, S. Ouburg, S. A. Morré, and A. M. van Furth, 2011b, Genetic variation of innate immune response genes in invasive pneumococcal and meningococcal disease applied to the pathogenesis of meningitis: Genes Immun, v. 12, p. 321-34. Sasaki, Y. T., T. Ideue, M. Sano, T. Mituyama, and T. Hirose, 2009, MENepsilon/beta noncoding RNAs are essential for structural integrity of nuclear paraspeckles: Proc Natl Acad Sci U S A, v. 106, p. 2525-30.

References - 187 -

Saunders, K. A., and J. Greenman, 2000, The formation of mixed culture biofilms of oral species along a gradient of shear stress: J Appl Microbiol, v. 89, p. 564- 72. Sayeed, S., L. Nistico, C. St Croix, and Y. P. Di, 2013, Multifunctional role of human SPLUNC1 in Pseudomonas aeruginosa infection: Infect Immun, v. 81, p. 285- 91. Schicht, M., S. Knipping, R. Hirt, S. Beileke, S. Sel, F. Paulsen, and L. Bräuer, 2013, Detection of surfactant proteins A, B, C, and D in human nasal mucosa and their regulation in chronic rhinosinusitis with polyps: Am J Rhinol Allergy, v. 27, p. 24-9. Schneider, M. C., R. M. Exley, S. Ram, R. B. Sim, and C. M. Tang, 2007, Interactions between Neisseria meningitidis and the complement system: Trends Microbiol, v. 15, p. 233-40. Schröder, N. W., and R. R. Schumann, 2005, Single nucleotide polymorphisms of Toll-like receptors and susceptibility to infectious disease: Lancet Infect Dis, v. 5, p. 156-64. Schultz, H., and J. P. Weiss, 2007, The bactericidal/permeability-increasing protein (BPI) in infection and inflammatory disease: Clin Chim Acta, v. 384, p. 12-23. Serruto, D., M. J. Bottomley, S. Ram, M. M. Giuliani, and R. Rappuoli, 2012, The new multicomponent vaccine against meningococcal serogroup B, 4CMenB: immunological, functional and structural characterization of the antigens: Vaccine, v. 30 Suppl 2, p. B87-97. Sezonov, G., D. Joseleau-Petit, and R. D'Ari, 2007, Escherichia coli physiology in Luria-Bertani broth: J Bacteriol, v. 189, p. 8746-9. Shamovsky, I., M. Ivannikov, E. S. Kandel, D. Gershon, and E. Nudler, 2006, RNA- mediated response to heat shock in mammalian cells: Nature, v. 440, p. 556- 60. Sherry, S. T., M. H. Ward, M. Kholodov, J. Baker, L. Phan, E. M. Smigielski, and K. Sirotkin, 2001, dbSNP: the NCBI database of genetic variation: Nucleic Acids Res, v. 29, p. 308-11. Shiloach, J., and R. Fass, 2005, Growing E. coli to high cell density--a historical perspective on method development: Biotechnol Adv, v. 23, p. 345-57. Sim, R. J., M. M. Harrison, E. R. Moxon, and C. M. Tang, 2000, Underestimation of meningococci in tonsillar tissue by nasopharyngeal swabbing: Lancet, v. 356, p. 1653-4. Sjöholm, A. G., E. J. Kuijper, C. C. Tijssen, A. Jansz, P. Bol, L. Spanjaard, and H. C. Zanen, 1988, Dysfunctional properdin in a Dutch family with meningococcal disease: N Engl J Med, v. 319, p. 33-7. Smirnova, I., N. Mann, A. Dols, H. H. Derkx, M. L. Hibberd, M. Levin, and B. Beutler, 2003, Assay of locus-specific genetic load implicates rare Toll-like receptor 4

References - 188 -

mutations in meningococcal susceptibility: Proc Natl Acad Sci U S A, v. 100, p. 6075-80. Sprong, T., D. Roos, C. Weemaes, C. Neeleman, C. L. Geesing, T. E. Mollnes, and M. van Deuren, 2006, Deficient alternative complement pathway activation due to factor D deficiency by 2 novel mutations in the complement factor D gene in a family with meningococcal infections: Blood, v. 107, p. 4865-70. Sprong, T., N. Stikkelbroeck, P. van der Ley, L. Steeghs, L. van Alphen, N. Klein, M. G. Netea, J. W. van der Meer, and M. van Deuren, 2001, Contributions of Neisseria meningitidis LPS and non-LPS to proinflammatory cytokine response: J Leukoc Biol, v. 70, p. 283-8. Steeghs, L., S. J. van Vliet, H. Uronen-Hansson, A. van Mourik, A. Engering, M. Sanchez-Hernandez, N. Klein, R. Callard, J. P. van Putten, P. van der Ley, Y. van Kooyk, and J. G. van de Winkel, 2006, Neisseria meningitidis expressing lgtB lipopolysaccharide targets DC-SIGN and modulates dendritic cell function: Cell Microbiol, v. 8, p. 316-25. Stephens, D. S., 1989, Gonococcal and meningococcal pathogenesis as defined by human cell, cell culture, and organ culture assays: Clin Microbiol Rev, v. 2 Suppl, p. S104-11. Stephens, D. S., 2009, Biology and pathogenesis of the evolutionarily successful, obligate human bacterium Neisseria meningitidis: Vaccine, v. 27 Suppl 2, p. B71-7. Sung, Y. K., C. Moon, J. Y. Yoo, D. Pearse, J. Pevsner, and G. V. Ronnett, 2002, Plunc, a member of the secretory gland protein family, is up-regulated in nasal respiratory epithelium after olfactory bulbectomy: J Biol Chem, v. 277, p. 12762-9. Sutherland, T. C., P. Quattroni, R. M. Exley, and C. M. Tang, 2010, Transcellular passage of Neisseria meningitidis across a polarized respiratory epithelium: Infect Immun, v. 78, p. 3832-47. Sørensen, T. I., G. G. Nielsen, P. K. Andersen, and T. W. Teasdale, 1988, Genetic and environmental influences on premature death in adult adoptees: N Engl J Med, v. 318, p. 727-32. Tam, O. H., A. A. Aravin, P. Stein, A. Girard, E. P. Murchison, S. Cheloufi, E. Hodges, M. Anger, R. Sachidanandam, R. M. Schultz, and G. J. Hannon, 2008, Pseudogene-derived small interfering RNAs regulate gene expression in mouse oocytes: Nature, v. 453, p. 534-8. Taylor, P. W., 1983, Bactericidal and bacteriolytic activity of serum against gram- negative bacteria: Microbiol Rev, v. 47, p. 46-83. Tecle, T., S. Tripathi, and K. L. Hartshorn, 2010, Review: Defensins and cathelicidins in lung immunity: Innate Immun, v. 16, p. 151-9.

References - 189 -

Thaikoottathil, J. V., R. J. Martin, P. Y. Di, M. Minor, S. Case, B. Zhang, G. Zhang, H. Huang, and H. W. Chu, 2012, SPLUNC1 deficiency enhances airway eosinophilic inflammation in mice: Am J Respir Cell Mol Biol, v. 47, p. 253-60. Thompson, M. J., N. Ninis, R. Perera, R. Mayon-White, C. Phillips, L. Bailey, A. Harnden, D. Mant, and M. Levin, 2006, Clinical recognition of meningococcal disease in children and adolescents: Lancet, v. 367, p. 397-403. Townsend, R., L. Goodwin, T. M. Stevanin, P. B. Silcocks, A. Parker, M. C. Maiden, and R. C. Read, 2002, Invasion by Neisseria meningitidis varies widely between clones and among nasopharyngeal mucosae derived from adult human hosts: Microbiology, v. 148, p. 1467-74. TranVan Nhieu, G., C. Clair, G. Grompone, and P. Sansonetti, 2004, Calcium signalling during cell interactions with bacterial pathogens: Biol Cell, v. 96, p. 93-101. Trivedi, K., C. M. Tang, and R. M. Exley, 2011, Mechanisms of meningococcal colonisation: Trends Microbiol, v. 19, p. 456-63. Trotter, C. L., N. J. Andrews, E. B. Kaczmarski, E. Miller, and M. E. Ramsay, 2004, Effectiveness of meningococcal serogroup C conjugate vaccine 4 years after introduction: Lancet, v. 364, p. 365-7. Turner, M., A. Galloway, and E. Vigorito, 2014, Noncoding RNA and its associated proteins as regulatory elements of the immune system: Nat Immunol, v. 15, p. 484-91. Tzeng, Y. L., and D. S. Stephens, 2015, Antimicrobial peptide resistance in Neisseria meningitidis: Biochim Biophys Acta, v. 1848, p. 3026-31. van der Ley, P., and L. Steeghs, 2003, Lessons from an LPS-deficient Neisseria meningitidis mutant: J Endotoxin Res, v. 9, p. 124-8. van Deuren, M., P. Brandtzaeg, and J. W. van der Meer, 2000, Update on meningococcal disease with emphasis on pathogenesis and clinical management: Clin Microbiol Rev, v. 13, p. 144-66, table of contents. Van Zele, T., F. Coppieters, P. Gevaert, G. Holtappels, P. Van Cauwenberge, and C. Bachert, 2009, Local complement activation in nasal polyposis: Laryngoscope, v. 119, p. 1753-8. Vig, M., and J. P. Kinet, 2009, Calcium signaling in immune cells: Nat Immunol, v. 10, p. 21-7. Vipond, C., R. Care, and I. M. Feavers, 2012, History of meningococcal vaccines and their serological correlates of protection: Vaccine, v. 30 Suppl 2, p. B10-7. Virji, M., 2009, Pathogenic neisseriae: surface modulation, pathogenesis and infection control: Nat Rev Microbiol, v. 7, p. 274-86. Virji, M., J. R. Saunders, G. Sims, K. Makepeace, D. Maskell, and D. J. Ferguson, 1993, Pilus-facilitated adherence of Neisseria meningitidis to human epithelial and endothelial cells: modulation of adherence phenotype occurs concurrently

References - 190 -

with changes in primary amino acid sequence and the glycosylation status of pilin: Mol Microbiol, v. 10, p. 1013-28. von Bernuth, H., C. Picard, Z. Jin, R. Pankla, H. Xiao, C. L. Ku, M. Chrabieh, I. B. Mustapha, P. Ghandil, Y. Camcioglu, J. Vasconcelos, N. Sirvent, M. Guedes, A. B. Vitor, M. J. Herrero-Mata, J. I. Aróstegui, C. Rodrigo, L. Alsina, E. Ruiz- Ortiz, M. Juan, C. Fortuny, J. Yagüe, J. Antón, M. Pascal, H. H. Chang, L. Janniere, Y. Rose, B. Z. Garty, H. Chapel, A. Issekutz, L. Maródi, C. Rodriguez-Gallego, J. Banchereau, L. Abel, X. Li, D. Chaussabel, A. Puel, and J. L. Casanova, 2008, Pyogenic bacterial infections in humans with MyD88 deficiency: Science, v. 321, p. 691-6. Waage, A., P. Brandtzaeg, A. Halstensen, P. Kierulf, and T. Espevik, 1989, The complex pattern of cytokines in serum from patients with meningococcal septic shock. Association between interleukin 6, interleukin 1, and fatal outcome: J Exp Med, v. 169, p. 333-8. Walport, M. J., 2001, Complement. First of two parts: N Engl J Med, v. 344, p. 1058- 66. Walton, W. G., S. Ahmad, M. S. Little, C. S. Kim, J. Tyrrell, Q. Lin, Y. P. Di, R. Tarran, and M. R. Redinbo, 2016, Structural Features Essential to the Antimicrobial Functions of Human SPLUNC1: Biochemistry, v. 55, p. 2979-91. Wang, K., M. Li, and M. Bucan, 2007, Pathway-based approaches for analysis of genomewide association studies: Am J Hum Genet, v. 81, p. 1278-83. Wang, W. Y., B. J. Barratt, D. G. Clayton, and J. A. Todd, 2005, Genome-wide association studies: theoretical and practical concerns: Nat Rev Genet, v. 6, p. 109-18. Weischenfeldt, J., O. Symmons, F. Spitz, and J. O. Korbel, 2013, Phenotypic impact of genomic structural variation: insights from and for human disease: Nat Rev Genet, v. 14, p. 125-38. Weiss, J., 2003, Bactericidal/permeability-increasing protein (BPI) and lipopolysaccharide-binding protein (LBP): structure, function and regulation in host defence against Gram-negative bacteria: Biochem Soc Trans, v. 31, p. 785-90. Weston, W. M., E. E. LeClair, W. Trzyna, K. M. McHugh, P. Nugent, C. M. Lafferty, L. Ma, R. S. Tuan, and R. M. Greene, 1999, Differential display identification of plunc, a novel gene expressed in embryonic palate, nasal epithelium, and adult lung: J Biol Chem, v. 274, p. 13698-703. Whittaker, R., 2007, European Centre for Disease Prevention and Control. Surveillance of invasive bacterial diseases in Europe. WHO, 2018, The top 10 causes of death. Willingham, A. T., A. P. Orth, S. Batalov, E. C. Peters, B. G. Wen, P. Aza-Blanc, J. B. Hogenesch, and P. G. Schultz, 2005, A strategy for probing the function of noncoding RNAs finds a repressor of NFAT: Science, v. 309, p. 1570-3.

References - 191 -

Wilusz, J. E., S. M. Freier, and D. L. Spector, 2008, 3' end processing of a long nuclear-retained noncoding RNA yields a tRNA-like cytoplasmic RNA: Cell, v. 135, p. 919-32. Wilusz, J. E., H. Sunwoo, and D. L. Spector, 2009, Long noncoding RNAs: functional surprises from the RNA world: Genes Dev, v. 23, p. 1494-504. Wiszniewski, L., L. Jornot, T. Dudez, A. Pagano, T. Rochat, J. S. Lacroix, S. Suter, and M. Chanson, 2006, Long-term cultures of polarized airway epithelial cells from patients with cystic fibrosis: Am J Respir Cell Mol Biol, v. 34, p. 39-48. Wright, V., M. Hibberd, and M. Levin, 2009, Genetic polymorphisms in host response to meningococcal infection: the role of susceptibility and severity genes: Vaccine, v. 27, p. B90-102. Würzner, R., A. Orren, and P. J. Lachmann, 1992, Inherited deficiencies of the terminal components of human complement: Immunodefic Rev, v. 3, p. 123- 47. Xavier, R. J. d., and J. D. Rioux, 2008, Genome-wide association studies: a new window into immunemediated diseases: Nat Rev Immunol, v. 8, p. 631 - 643. Yazdankhah, S. P., and D. A. Caugant, 2004, Neisseria meningitidis: an overview of the carriage state: J Med Microbiol, v. 53, p. 821-32. Yi, K., A. W. Rasmussen, S. K. Gudlavalleti, D. S. Stephens, and I. Stojiljkovic, 2004, Biofilm formation by Neisseria meningitidis: Infect Immun, v. 72, p. 6132-8. Zhou, H. D., X. L. Li, G. Y. Li, M. Zhou, H. Y. Liu, Y. X. Yang, T. Deng, J. Ma, and S. R. Sheng, 2008, Effect of SPLUNC1 protein on the Pseudomonas aeruginosa and Epstein-Barr virus: Mol Cell Biochem, v. 309, p. 191-7.