The Role of Interferon Epsilon in Protection Against Chlamydial

The role of interferon epsilon in protection against

chlamydial reproductive tract infections

Jemma Rose Mayall

B. Biomed Sci (Hons)

June 2016

Discipline of Immunology and Microbiology

School of Biomedical Sciences and Pharmacy

Faculty of Health

The University of Newcastle

Newcastle, NSW, Australia

A thesis submitted in fulfilment of the requirements for the award of a Doctor of

Philosophy (Immunology and Microbiology)

1 Statement of Originality

This thesis contains no material which has been accepted for the award of any other degree or diploma in any university or other tertiary institution and, to the best of my knowledge and belief, contains no material previously published or written by another person, except where due reference has been made in the text. I give consent to the final version of my thesis being made available worldwide when deposited in the

University’s Digital Repository**, subject to the provisions of the Copyright Act 1968.

**Unless an Embargo has been approved for a determined period.

Statement of Collaboration

I hereby certify that work embodied in this thesis has been done in collaboration with other researchers and carried out in other institutions. I have included as part of the thesis a statement clearly outlining the extent of collaboration, with whom and under what auspices.

Statement of Authorship

I hereby certify that the work embodied in this thesis contains a published paper/s/scholarly work of which I am a joint author. I have included as part of the thesis a written statement, endorsed by my supervisor, attesting to my contribution to the joint publication/s/scholarly work.

X Jemma Mayall PhD Candidate

2 Acknowledgements

I would like to briefly acknowledge the people who have made the completion of this thesis possible by contributing their time and support. Firstly, I would like to thank my primary supervisor, mentor, and friend, Dr. Jay Horvat. Your guidance, encouragement, and support are what have pulled me through and for all the late nights, early mornings, and weekends you have sacrificed to provide me with these things, I am truly grateful. I also owe a debt of gratitude to my co-supervisor, Prof. Phil Hansbro, whose support has also gone beyond the call of duty. Thank you for giving me the opportunity to be a part of your team and allowing me to work on this project.

Thanks also to all my brilliant colleagues who I have had the pleasure of working with over the past several years. I truly feel very lucky to have had the opportunity of working with you all, and for all your assistance and friendship, you are some of the best people I know. Special thanks to my lab wife, partner in crime, and good friend,

Alexandra Brown, thanks for always being there for me, dude. I would also like to thank my good friends, Courtney and Elisha Buckingham, thanks for all the love, fun, and laughs. Despite my non-existent social life, you guys have stuck around, so you must be pretty special.

Finally, I would like to thank my family, especially my parents, Glenn and Dianne

Mayall, who have always supported me unconditionally and have given me endless love and encouragement, and also my partner, Tim Cox, whose very important contribution to the scientific community has been feeding and housing one scientist through her

PhD. Thank you for always believing in me, helping me through the rough times, and for all your unwavering love and support, you make me a better person every day. To these people I dedicate my thesis.

3 Table of contents

Synopsis ...... 9

Publications I have contributed to during my PhD studies ...... 14

List of figures ...... 21

List of tables ...... 26

Abbreviations ...... 29

: Introduction ...... 34

1.1 Sexually transmitted infections (STIs) ...... 34

1.1.1 Chlamydia reproductive tract infections (RTIs) ...... 34

1.1.2 Hormonal influence on infection and immunity in the female reproductive tract

(RT) 42

1.2 Innate immunity in the female RT: Importance of type interferons (IFNs), natural

killer (NK) cells, and inflammasomes in Chlamydia infection ...... 47

1.2.1 Type I IFNs ...... 48

1.2.2 IFNε ...... 54

1.2.3 NK cells ...... 63

1.2.4 Inflammasomes ...... 75

1.3 PhD Studies ...... 88

: Characterisation of Chlamydia infection and innate responses in the female RT in

IFNε-/- mice ...... 90

2.1 Abstract ...... 90

2.2 Introduction ...... 93

2.3 Methods...... 98

4 2.3.1 Ethics statement ...... 98

2.3.2 Chlamydia muridarum female RTI ...... 98

2.3.3 In vivo administration of recombinant (r)IFNε ...... 99

2.3.4 Total RNA extraction and bioanalysis ...... 100

2.3.5 Reverse transcription and real-time qPCR ...... 101

2.3.6 Chlamydia load ...... 102

2.3.7 Flow cytometry ...... 102

2.3.8 Microarray gene expression profiling ...... 104

2.3.9 Pathway analysis ...... 105

2.3.10 Statistics ...... 106

2.4 Results ...... 107

2.4.1 Expression of IFNε is regulated by hormones and protects the female RT from

Chlamydia infection ...... 107

2.4.2 IFNε deficiency alters immune cell profiles in the female RT ...... 111

2.4.3 IFNε deficiency alters gene expression profiles in the female RT ...... 114

2.4.4 Pathway analysis of dysregulated gene transcripts in IFNε-/- mice ...... 116

2.5 Discussion ...... 133

: Role of NK cells in IFNε-mediated protection against Chlamydia RTI ...... 144

3.1 Abstract ...... 144

3.2 Introduction ...... 146

3.3 Methods...... 150

3.3.1 Ethics statement ...... 150

3.3.2 C. muridarum female RTI ...... 150

5 3.3.3 In vivo NK cell depletion ...... 150

3.3.4 Flow cytometry ...... 151

3.3.5 Total RNA extraction ...... 154

3.3.6 Reverse transcription and real-time qPCR ...... 154

3.3.7 Chlamydia load ...... 155

3.3.8 Immunoblot analysis ...... 155

3.3.9 Statistics ...... 156

3.4 Results ...... 157

3.4.1 IFNε deficiency decreases NK cell responses in the female RT ...... 157

3.4.2 IFNε deficiency decreases systemic NK cell responses ...... 163

3.4.3 IFNε deficiency reduces the expression of genes associated with NK cell

responses in the female RT ...... 167

3.4.4 Depletion of systemic NK cells alters Chlamydia infection and affects NK cell

number and phenotype in the female RT ...... 173

3.5 Discussion ...... 178

: Role of inflammasomes in IFNε-mediated responses to Chlamydia RTI ...... 192

4.1 Abstract ...... 192

4.2 Introduction ...... 194

4.3 Methods...... 199

4.3.1 Ethics statement ...... 199

4.3.2 C. muridarum female RTI ...... 199

4.3.3 In vivo inhibition of the NLRP3 inflammasome ...... 199

4.3.4 Total RNA extraction ...... 200

6 4.3.5 Reverse transcription and real-time qPCR ...... 201

4.3.6 Chlamydia load ...... 202

4.3.7 Caspase-1 activity assay ...... 202

4.3.8 Flow cytometry ...... 202

4.3.9 NLRP3 immunofluorescence staining ...... 204

4.3.10 Statistics ...... 205

4.4 Results ...... 206

4.4.1 IFNε deficiency reduces the expression of IL-1β and caspase-1 in the female RT

206

4.4.2 IFNε deficiency reduces caspase-1 activation in the female RT ...... 209

4.4.3 IFNε deficiency decreases expression of NLRP3 in the female RT ...... 214

4.4.4 The NLRP3 inflammasome protects against Chlamydia infection of the female

RT 216

4.4.5 IFNε deficiency affects multiple inflammasome and caspase signalling pathways

in the female RT ...... 220

4.5 Discussion ...... 223

: General discussion and conclusions ...... 231

5.1 Using a murine model of C. muridarum-induced RTI to investigate how IFNε protects against Chlamydia infections in the female RT ...... 231

5.1.1 IFNε regulates many key innate immune and other processes in the female RT

234

5.1.2 IFNε protects against Chlamydia RTIs by promoting innate NK cell and IFNγ

responses 239

7 5.1.3 IFNε may protect against Chlamydia RTIs by promoting inflammasome-

mediated responses ...... 244

5.1.4 Potential interactions between the NK cell responses and inflammasome-

mediated pathways regulated by IFNε ...... 249

5.1.5 Differential effects of type I IFNs on Chlamydia infection in the female RT .. 251

5.2 Future directions ...... 254

5.2.1 Proof of principle studies ...... 254

5.2.2 Further investigation into the role of IFNε-regulated immune, metabolic, and cell

cycling pathways in the protection against Chlamydia RTIs ...... 255

5.2.3 Elucidating the mechanisms that underpin IFNε-mediated NK cell accumulation,

activation, and IFNγ responses ...... 256

5.2.4 Further investigation into role of inflammasome/caspase-1/IL-1β signalling

pathways in the induction of anti-Chlamydia responses ...... 260

5.2.5 Further investigation into the role of IFNε-mediated NK cell and inflammasome

responses in adaptive immunity to Chlamydia and the development of long-term

immunopathology ...... 263

5.3 Concluding remarks and significance of findings ...... 266

References ...... 268

Appendices ...... 298

Appendix A: Supplementary methods ...... 298

Appendix B: Chapter 2 supplementary data ...... 300

Appendix C: Chapter 3 supplementary data ...... 314

8 Synopsis

Chlamydia trachomatis is the most common cause of sexually transmitted bacterial infections, affecting over 131 million individuals annually worldwide. In women, infection commonly ascends from the vagina into the upper reproductive tract

(RT) and leads to a range of RT diseases such as infertility, pelvic inflammatory disease

(PID), and ectopic pregnancy. While antibiotics are a safe and effective method for treating infection, 50-90% of Chlamydia RT infections (RTIs) are asymptomatic. This means that infections often progress for some time before treatment is initiated, leading to permanent immunopathology in the upper RT tissues, which causes disease.

Significantly, there are no vaccines or immunotherapies currently available for the prevention of infection or the development of severe RT sequelae. This is largely due to the relatively limited understanding of the immunobiology of Chlamydia infections in the female RT. An improved understanding of the complex immune processes that are involved in both the clearance and immunopathology of Chlamydia infections is required in order to identify novel targets for the development of better therapeutic strategies for the prevention and treatment of Chlamydia infections and associated disease.

Previous studies indicate that levels of the female sex hormones, progesterone and oestradiol, affect the susceptibility of an individual to Chlamydia RTIs. The pioneering studies and preliminary data collected by our research group and collaborators demonstrate that interferon (IFN)ε, a novel type I IFN that is exclusively and constitutively expressed in the female RT (predominantly uterine tissue), fluctuates throughout the oestrous cycle and, therefore, may be linked to the hormone-dependent susceptibility of the female RT to infection. In this thesis, I demonstrate the role of IFNε in protecting against Chlamydia RTIs, identify the key immune processes that underpin

9 IFNε-mediated protection, and determine the potential of recombinant (r)IFNε as a therapeutic agent to prevent infection.

Using wild-type (WT) and IFNε knockout (IFNε-/-), C57BL/6 mice, I investigated the effects of IFNε deficiency and exogenous IFNε (via administration of rIFNε) on Chlamydia infection and the effects of female sex hormones on these responses (Chapter 2). I demonstrate that IFNε protects against Chlamydia infections from the earliest stages of infection (3 days post infection [dpi]) in progesterone-pre- treated mice, but that, despite hormone pre-treatment having substantial effects on the expression IFNε in the female RT, hormone-mediated effects on IFNε expression may not fully account for the effects of female sex hormones on susceptibility to Chlamydia infections in the female RT. I also show that intravaginal (IVAG) rIFNε administration may be an effective preventative therapy for the treatment of Chlamydia RTIs. In order to determine the mechanisms that underpin IFNε-mediated protective responses during these early stages of infection, I then performed flow cytometry, and microarray and subsequent bioinformatical analyses, on uterine tissues from Chlamydia- and sham- infected, WT and IFNε-/- mice at 3dpi. The findings from these analyses were used to identify the key immune cells and molecular pathways and networks affected by IFNε and informed the more focussed studies that aimed to clarify potential roles of natural killer (NK) cell (Chapter 3) and inflammasome (Chapter 4) responses in IFNε- mediated protection against Chlamydia infection.

I show, for the first time, that IFNε primes for and induces both local and systemic NK cell responses that protect against Chlamydia RTIs (Chapter 3).

Specifically, I showed that IFNε-/- mice have reduced numbers of conventional (c)NK

(CD45+ CD3- NK1.1+) and uterine (u)NK (CD45+ CD3- NK1.1- CD49b- CD122+) cells in their upper RTs during the early stages (3dpi) of Chlamydia infection. In particular, I

10 show that the numbers of activated (CD69+) and IFNγ-producing NK cells are reduced in the RTs of IFNε-/- mice. I also show that NK cells are the predominant cellular source of IFNγ in the uterus at 3dpi. Interestingly, I show that the number of systemic (splenic)

NK cells, as well as precursor and mature, but not immature, NK cells in the bone marrow, are reduced in both Chlamydia- and sham-infected IFNε-/- mice, compared to

WT controls. These responses correspond with a reduction in interleukin (IL)-15, a cytokine important for the development, activation, and homing of NK cells, and C-X-C motif chemokine ligand (CXCL)10, a potent NK cell chemoattractant, in the uterine horns of IFNε-/- mice. This shows that IFNε, produced in the female RT, primes for both local and systemic NK cell responses, potentially by increasing IL-15 and CXCL10.

Finally, by depleting NK cells in WT animals using anti-asialo ganglio-N- tetrasylceramide (ASGM1), I not only show for the first time that NK cells in the uterus are vital for restricting uterine Chlamydia growth, but that the depletion of systemic/infiltrating NK cells has little effect on reducing the number of activated NK cells in uterine tissue. These findings not only highlight the importance of IFNε in systemic NK cell mobilisation but, more importantly, also demonstrate the potent effects of IFNε in maintaining NK cell numbers and activity in the uterus in the absence of infiltrating NK cells and the importance of these responses in mediating protection against ascending Chlamydia RTI.

I also show that IFNε regulates inflammasome signalling pathways during

Chlamydia RTI and that IFNε-induced up-regulation of the nucleotide-binding oligomerisation domain (NOD)- and leucine-rich repeat (LRR)-containing receptor

(NLR) family pyrin domain-containing 3 (NLRP3) inflammasome axis plays an important role in mediating protection against infection. Specifically, I show that IFNε-/- mice have reduced expression of IL-1β prior to and caspase-1 prior to and during

11 infection, and reduced NLRP3-positive uterine epithelial cells during infection, compared to WT controls. These findings correspond with a reduction in the number of active caspase-1+ leukocytes present in their upper RTs early during Chlamydia infection (3dpi). Interestingly, a significant number of the active caspase-1+ leukocytes observed in the uterus during Chlamydia infection were NK cells. By inhibiting NLRP3 in WT animals using IVAG administration of MCC950, I show that NLRP3 inflammasome responses in the female RT play an important role in restricting uterine

Chlamydia growth during the early stages of Chlamydia RTI but may not solely be responsible for IFNε-mediated caspase-1 activation. I also show that IFNε-/- mice have reduced expression of absent in melanoma 2 (AIM2) and caspase-4 in their upper RTs, compared to WT controls. These findings highlight the potential importance of IFNε- mediated NLRP3 and other inflammasome responses in protecting against ascending

Chlamydia RTI.

The investigations conducted during my PhD studies have identified several novel mechanisms by which IFNε may protect against Chlamydia RTIs from the earliest stages of infection. I have shown that IFNε plays an important role in the induction of

NK cells responses, not only in the upper female RT but also systemically, during the early stages of Chlamydia infection and that these responses are important in protecting against infection. I also show that IFNε plays an important role in priming inflammasome-mediated responses in the upper female RT during infection and that these responses play an important role in protecting against Chlamydia infection. The findings from my thesis provide new insights into the effects of IFNε on mucosal immunology in the female RT and extend upon the current body of literature describing the immune processes that are important in mediating protection against Chlamydia infection. Significantly, these findings will now be used to guide future investigations

12 that will aim to determine how the responses I have identified affect long-term sequelae and, therefore, may help inform new therapeutic targets for the development of improved treatment and prevention strategies for Chlamydia RTIs and associated disease.

13 Publications I have contributed to during my PhD studies

Work conducted during my PhD studies was used to generate one of the four figures in a paper published in Science in 2013. This paper was the first to demonstrate that IFNε is constitutively expressed in the female RT and show the important role that

IFNε plays in protecting against Chlamydia and herpes simplex virus (HSV) infections.

Using a mouse model of Chlamydia female RTI, we showed for the first time that the absence of IFNε leads to an increase in bacterial load in the vagina and upper RT, delays the clearance of infection, and worsens clinical outcomes of Chlamydia-induced disease. Significantly, I showed that treatment with rIFNε is able to protect against

Chlamydia infection, identifying this novel type I IFN as a potential therapeutic agent for Chlamydia sexually transmitted infections (STIs). Additionally, I developed flow cytometry-based techniques on mouse uterine tissue that enabled us to show that IFNε plays an important role in orchestrating the infiltration of NK cells into the female RT during Chlamydia infection. This Science publication significantly advances our understanding of the immunology of the RT and the mechanisms of pathogenesis of

Chlamydia RTIs.

Additionally, my work has been selected for both oral and poster presentations, at national and international conferences, such as the Australasian Society for

Immunology (ASI) Annual Scientific Meeting, the Australian Chlamydia Conference, and the American Association of Immunologists (AAI) Annual Meeting.

I have also contributed to a number of other research publications throughout my studies. I contributed to the establishment of the murine models of infection-induced, severe allergic airways disease currently used by our laboratory and the findings of these studies have led to a publication in Thorax, which demonstrates the immunomodulatory capabilities of macrolides in the treatment of steroid-resistant and

14 steroid-sensitive asthma, and a publication in J Allergy Clin Immunol, which demonstrates the role of a micro (mi)RNA-21/phosphoinositide-3-kinase

(PI3K)/phosphorylated Akt/histone deacetylase 2 signalling axis in steroid-resistant asthma.

In addition to being selected to present my work both orally and in poster format at several national and international forums, I have contributed to 15 other conference presentations as a coinvestigator, which were presented at ASI, AAI, Thoracic Society of Australia and New Zealand (TSANZ), American Thoracic Society (ATS), and Lorne

Infection and Immunity conferences from 2012-2015.

Publication generated from my PhD studies:

Fung, K. Y., Mangan, N. E., Cumming, H., Horvat, J. C., Mayall, J. R., Stifter, S. A.,

De Weerd, N., Roisman, L. C., Rossjohn, J., Robertson, S. A, Schjenken, J. E., Parker,

B., Gargett, C. E., Nguyen, H. P., Carr, D. J., Hansbro, P. M., Hertzog, P. J. (2013).

Interferon-ε protects the female reproductive tract from viral and bacterial infection.

Science, 339(6123), 1088-1092. doi: 10.1126/science.1233321 (Cited=38).

Publications I have contributed to during my candidature:

Essilfie, A.-T., Horvat, J. C., Kim, R. Y., Mayall, J. R., Pinkerton, J. W., Beckett, E. L.,

Starkey, M. R., Simpson, J. L., Foster, P. S., Gibson, P. G., Hansbro, P. M. (2015).

Macrolide therapy suppresses key features of experimental steroid-sensitive and steroid- insensitive asthma. Thorax. doi: 10.1136/thoraxjnl-2014-206067 (Cited=9).

15 Kim, R. Y., Horvat, J. C., Pinkerton, J. W., Starkey, M. R., Essilfie, A.-T., Mayall, J.

R., Jones, B., Haw, T. J., Sunkara, K., Nguyen, T. H., Jarnicki, A. G., Keely, S., Mattes,

J., Adcock, I. M., Foster, P. S., Hansbro, P. M. (2016). MicroRNA-21 drives severe, steroid-insensitive experimental asthma by amplifying PI3K-mediated suppression of

HDAC2. J Allergy Clin Immunol. doi: http://dx.doi.org/10.1016/j.jaci.2016.04.038

(epub June 2016).

16 Conference presentations

First author oral presentations:

Mayall, J., Mangan, N., Chevalier, A., Starkey, M., Kim, R., Brown, A., Maltby, S.,

Foster, P., Hertzog, P., Horvat, J., Hansbro, P. IFN-ɛ-mediated local and systemic NK cell responses during Chlamydia infection. ASI Annual Scientific Meeting, Canberra,

2015.

Mayall, J., Mangan, N., Starkey, M., Kim, R., Hertzog, P., Horvat J., Hansbro, P. Role of NK cells in IFN-ɛ-mediated protection against female reproductive tract infection

(MUC2P.925). AAI Annual Meeting, New Orleans, 2015.

Mayall, J., Mangan, N., Starkey, M., Kim, R., Brown, A., Hertzog, P., Horvat, J.,

Hansbro, P. Role of NK cells in IFN-ɛ-mediated protection against female reproductive tract infection (#111). ASI Annual Scientific Meeting, Wollongong, 2014.

Mayall, J., Mangan, N., Starkey, M., Kim, R., Hertzog, P., Horvat. J., Hansbro, P. Role of NK cells in IFN-ɛ-mediated protection against female reproductive tract infection.

Australian Chlamydia Conference, Sunshine Coast, 2014.

First author poster presentations:

Mayall, J., Mangan, N., Starkey, M., Kim, R., Maltby, S., Brown, A., Hertzog, P.,

Horvat, J., Hansbro, P. Role of NK cells in IFN-ɛ-mediated protection against female reproductive tract infection (PP6). Australian Society for Medical Research (ASMR)

Satellite Meeting, Newcastle, 2015.

17 Mayall, J., Mangan, N., Starkey, M., Kim, R., Hertzog, P., Horvat. J., Hansbro, P. Role of NK cells in IFN-ɛ-mediated protection against female reproductive tract infection

(MUC2P.925). AAI Annual Meeting, New Orleans, 2015.

Presentations that I have contributed to during my candidature:

Essilfie, A.-T., Horvat, J., Kim, R., Mayall, J., Pinkerton, J., Beckett, E., Starkey,

Simpson, J., Foster, P., Gibson, P., Hansbro, P. Macrolide therapy suppresses key features of experimental steroid-sensitive and steroid-insensitive asthma (HYP2P.342).

AAI Annual Meeting, New Orleans, 2015.

Kim, R., Pinkerton, J., Starkey, M., Essilfie, A.-T., Mayall, J., Jones, B., Haw, T. J.,

Keely, S., Mattes, J., Adcock, I., Foster, P., Horvat, J., Hansbro P. MicroRNA-21 drives severe, steroid-insensitive experimental asthma by amplifying PI3K-mediated suppression of HDAC2 (HYP7P.262). AAI Annual Meeting, New Orleans, 2015.

Kim, R., Horvat, J., Pinkerton, J., Starkey, M., Essilfie, A.-T., Mayall, J., Jones, B.,

Haw, T. J., Keely, S., Mattes, J., Adcock, I., Foster, P., Hansbro P. Infection-induced microRNA-21 drives severe steroid-insensitive experimental asthma by amplifying

PI3K-mediated suppression of HDAC2 (TO 047). TSANZ Annual Scientific Meeting,

Gold Coast, 2015.

Kim, R., Pinkerton, J., Starkey, M., Essilfie, A.-T., Mayall, J., Jones, B., Haw, T. J.,

Keely, S., Mattes, J., Adcock, I., Foster, P., Horvat, J., Hansbro P. Infection-Induced microRNA-21 Drives Severe, Steroid-Insensitive Experimental Asthma by Amplifying

Phosphoinositide-3-Kinase (PI3K)-Mediated Suppression of Histone Deacetylase

(HDAC)2 (A5384). ATS International Conference, Denver, 2015.

18 Kim, R., Horvat, J., Pinkerton, J., Starkey, M., Essilfie, A.-T., Mayall, J., Jones, B.,

Haw, T. J., Keely, S., Mattes, J., Adcock, I., Foster, P., Hansbro, P. MicroRNA-21 drives severe, steroid-insensitive experimental asthma by amplifying PI3K-mediated suppression of HDAC2 (#68). ASI Annual Scientific Meeting, Wollongong, 2014.

Horvat, J., Kim, R., Mayall, J., Pinkerton, J., Starkey, M., Essilfie, A.-T., Wood, L.,

Hansbro, P. Antioxidant-based therapy for the suppression of early-life infection- induced severe asthma (TO 005). TSANZ Annual Scientific Meeting, Adelaide, 2014.

Horvat, J., Essilfie, A.-T., Kim, R., Mayall, J., Starkey, M., Foster, P., Hansbro, P.

Macrolides suppress key features of experimental steroid-sensitive and steroid-resistant asthma (P6229). AAI Annual Meeting, Honolulu, 2013.

Horvat, J., Essilfie, A.-T., Kim, R., Mayall, J., Starkey, M., Beckett, E., Foster, P.,

Hansbro, P. Efficacy of antibiotic-based therapeutic strategies for the treatment of infection-induced, steroid-resistant allergic airways disease (TO 061). TSANZ Annual

Scientific Meeting, Canberra, 2012.

Horvat, J., Essilfie, A.-T., Kim, R., Mayall, J., Starkey, M., Beckett, E., Foster, P.,

Hansbro, P. Efficacy of antibiotic-based therapeutic strategies for the treatment of infection-induced, steroid-resistant allergic airways disease. Lorne Infection and

Immunity Conference, Lorne, 2012.

Horvat, J., Kim, R., Mayall, J., Pinkerton, J., Essilfie, A.-T., Starkey, M., Wood, L.,

Hansbro, P. Antioxidant Treatment Suppresses the Progression of Early-Life Infection-

Induced Severe Asthma and Pathology in Later-Life (A1291). ATS International

Conference, San Diego, 2014.

Horvat, J., Essilfie, A.-T., Kim, R., Mayall, J., Starkey, M., Beckett, E., Foster, P.,

Hansbro, P. Immunomodulatory Effects of Macrolide Treatment on Experimental

19 Models of Steroid-Sensitive and Steroid-Resistant Asthma (A2684). ATS International

Conference, Philadelphia, 2013.

Horvat, J., Essilfie, A.-T., Kim, R., Mayall, J., Starkey, M., Beckett, E., Foster, P.,

Hansbro, P. Macrolides suppress key features of experimental steroid-sensitive & steroid-resistant asthma (P009). TSANZ Annual Scientific Meeting, Darwin, 2013.

Horvat, J., Essilfie, A.-T., Kim, R., Mayall, J., Starkey, M., Beckett, E., Foster, P.,

Hansbro, P. Efficacy of antibiotic-based therapeutic strategies for the treatment of infection-induced, steroid-resistant allergic airways disease (A2863). ATS International

Conference, San Francisco, 2012.

20 List of figures

Figure 1.1: Expression patterns of interferon (IFN)ε.

Figure 1.2: Interferon (IFN)ε expression in murine uterine tissue during stages of the oestrous cycle and pregnancy.

Figure 1.3: Interferon (IFN)ε-/- mice are more susceptible to Chlamydia reproductive tract infection (RTI).

Figure 1.4: The development of murine natural killer (NK) cells.

Figure 1.5: Activation and assembly of the canonical inflammasomes.

Figure 2.1: In vivo administration of recombinant interferon (r/IFN)ε prior to

Chlamydia muridarum female reproductive tract infection (RTI).

Figure 2.3: Interferon (IFN)ε deficiency decreases the number of natural killer (NK) cells in the upper reproductive tract (RT) during Chlamydia infection.

Figure 2.4: Number of differentially expressed genes in the upper reproductive tract

(RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls at baseline (sham-infected) and during Chlamydia infection.

21 Figure 2.6: Molecular networks associated with genes down-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls during Chlamydia infection.

Figure 2.8: Molecular networks associated with genes up-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls at baseline (sham-infected).

Figure 2.9: Molecular networks associated with genes up-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls during Chlamydia infection.

Figure 3.1: In vivo systemic natural killer (NK) cell depletion during Chlamydia muridarum female reproductive tract infection (RTI).

Figure 3.3: Interferon (IFN)ε deficiency decreases the number of IFNγ-producing natural killer (NK) cells and level of IFNγ expression in the female reproductive tract

(RT) during Chlamydia infection.

22 Figure 3.4: Interferon (IFN)ε deficiency decreases the proportion of activated and

IFNγ-producing natural killer (NK) cells in the female reproductive tract (RT) during

Chlamydia infection.

Figure 3.6: Interferon (IFN)ε deficiency decreases the production of precursor and mature, but not immature, natural killer (NK) cells in the bone marrow.

Figure 3.7: Interferon (IFN)ε deficiency differentially alters the expression of factors involved in natural killer (NK) cell responses in the female reproductive tract (RT).

Figure 3.8: Interferon (IFN)ε deficiency has no effect on the expression of classical type I IFNs but decreases expression of type I IFN receptor (IFNAR)1 during

Chlamydia infection in the female reproductive tract (RT).

Figure 3.9: Interferon (IFN)ε deficiency differentially alters the expression of factors involved in type I IFN signalling in the female reproductive tract (RT).

Figure 3.10: Interferon (IFN)ε deficiency differentially alters the expression of factors involved in IFNγ responses in the female reproductive tract (RT).

Figure 3.11: Systemic natural killer (NK) cell depletion post infection increases

Chlamydia replication and reduces inactive populations of NK cells in the upper reproductive tract (RT).

Figure 3.12: Systemic natural killer (NK) cell depletion prior to infection decreases

Chlamydia replication and increases active populations of NK cells in the upper reproductive tract (RT).

23 Figure 4.1: In vivo local inhibition of NLRP3 during Chlamydia muridarum female reproductive tract infection (RTI).

Figure 4.2: Interferon (IFN)ε deficiency alters the messenger (m)RNA expression of interleukin (IL)-1β and caspase-1 in the female reproductive tract (RT).

Figure 4.3: Interferon (IFN)ε deficiency decreases the number of active caspase-1+ natural killer (NK) cells and macrophages present in the female reproductive tract (RT) during Chlamydia infection.

Figure 4.4: Interferon (IFN)ε deficiency decreases the number of active caspase-1+ plasmacytoid dendritic cells (p/DCs) present in the female reproductive tract (RT) during Chlamydia infection.

Figure 4.5: Interferon (IFN)ε deficiency decreases the percentage of natural killer (NK) cells expressing active caspase-1 in the female reproductive tract (RT) during

Chlamydia infection.

Figure 4.6: Interferon (IFN)ε deficiency decreases NLRP3 protein expression in endometrial epithelial cells during Chlamydia infection.

Figure 4.7: Intravaginal (IVAG) NLRP3 inhibition increases Chlamydia replication but does not alter natural killer (NK) cell responses in the upper reproductive tract (RT).

Figure 4.8: Intravaginal (IVAG) NLRP3 inhibition does not alter caspase-1 activation in the upper reproductive tract (RT).

24 sFigure 2.1: Characterisation of Chlamydia infection in the upper reproductive tracts

(RTs) of progesterone- and oestradiol-pre-treated mice. sFigure 2.3: Interferon (IFN)ε deficiency does not alter Chlamydia-specific serum immunoglobulin (Ig)G1 or IgG2a levels or lymph node IFNγ production at 30 days post infection (dpi). sFigure 3.1: Systemic natural killer (NK) cell depletion post infection reduces the number of NK cells present in the spleen and bone marrow but does not affect NK cell precursors. sFigure 3.2: Systemic natural killer (NK) cell depletion prior to infection reduces the number of NK cells present in the spleen and bone marrow but does not affect NK cell precursors. sFigure 3.3: Representative flow cytometric plots of natural killer (NK) cell populations in the reproductive tracts (RTs) of wild-type (WT) and interferon (IFN)ε-/- mice during Chlamydia infection. sFigure 3.4: Interferon (IFN)ε deficiency decreases IFNγ production by natural killer

(NK) cells, T cells, and total leukocytes in the female reproductive tract (RT) during

Chlamydia infection. sFigure 3.5: Systemic natural killer (NK) cell depletion post infection reduces, while depletion prior to infection increases, the number of NK cells present in the upper reproductive tract (RT) during Chlamydia infection.

25 List of tables

Table 2.1: Staining cocktails used for flow cytometric profiling of immune cell populations.

Table 2.2: Characterisation of immune cell populations.

Table 2.3: Canonical pathways associated with down-regulated genes in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls at baseline (sham-infected).

Table 2.4: Canonical pathways associated with down-regulated genes in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls during Chlamydia infection.

Table 2.6: Canonical pathways associated with up-regulated genes in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls at baseline (sham-infected).

Table 2.7: Canonical pathways associated with up-regulated genes in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls during Chlamydia infection.

26 Table 3.1: Staining cocktails used for flow cytometric analysis of natural killer (NK) cell responses.

Table 3.2: Characterisation of immune cell populations.

Table 4.1: Staining cocktail used for flow cytometric profiling of active caspase-1+ cells.

Table 4.2: Characterisation of cell populations. sTable 1.1: Oligonucleotide sequences used for qPCR analyses. sTable 2.1: Molecular networks associated with genes down-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls at baseline (sham-infected). sTable 2.2: Molecular networks associated with genes down-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls during Chlamydia infection. sTable 2.3: Molecular networks associated with genes commonly down-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls both at baseline and during Chlamydia infection. sTable 2.4: Molecular networks associated with genes up-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls at baseline (sham-infected). sTable 2.5: Molecular networks associated with genes up-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls during Chlamydia infection.

27 sTable 2.6: Molecular networks associated with genes commonly up-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls both at baseline and during Chlamydia infection.

28 Abbreviations

AAI: American Association of Chsp60: Chlamydia 60kDa heat shock

Immunologists protein

AF: Alexa Fluor® CILP: Common innate lymphoid

AHR: Aryl hydrocarbon receptor progenitor

AIM2: Absent in melanoma 2 CLP: Common lymphoid progenitor

ANOVA: Analysis of variance C. muridarum: Chlamydia muridarum

AP1: Activator protein 1 CMV: Cytomegalovirus

ASC: Apoptosis-associated speck-like cNK: Conventional natural killer protein containing a CARD ConA: Concanavalin A

ASI: Australasian Society for COX-2: Cyclooxygenase 2

Immunology cRNA: Complementary ribonucleic

ASGM1: Asialo ganglio-N- acid tetrasylceramide C. trachomatis: Chlamydia

ATP: Adenosine triphosphate trachomatis

ATS: American Thoracic Society CX3CR: C-X3-C motif chemokine

BCA: Bicinchoninic acid receptor

BIR: Baculoviral inhibitory repeat CXCL: C-X-C motif chemokine

BSA: Bovine serum albumin ligand

BV: Brilliant Violet™ CXCR: C-X-C motif chemokine

C. albicans: Candida albicans receptor

CARD: Caspase-recruitment domain DAI: DNA-dependent activator of

CCR: C-C motif chemokine receptor IRFs

CEBPβ: CCAAT/enhancing protein β DAMP: Damage-associated molecular

pattern

DC: Dendritic cell GAS: Gamma interferon-activated site dH2O: Deionised water HBD-1: Human beta-defensin-1

DMPA: Depot medroxyprogesterone HD-5: Human defensin-5 acetate HIV: Human immunodeficiency virus

DMSO: Dimethyl sulfoxide HMG: High mobility group

DNA: Deoxyribonucleic acid HPRT: Hypoxanthine-guanine dpi: Days post infection phosphoribosyltransferase dsDNA: Double stranded HPV: Human papillomavirus deoxyribonucleic acid HSC: Haematopoietic stem cell dsRNA: Double-stranded ribonucleic HSV: Herpes simplex virus acid IDO: Indoleamine-2,3-dioxygenase

DTT: DL-Dithiothreitol IFN: Interferon

EB: Elementary body IFNAR: Type I interferon receptor

EDTA: Ethylenediaminetetraacetic IFNγR: Interferon γ receptor acid ifu: Inclusion forming units

Eomes: Eomesodermin Ig: Immunoglobulin

FACS: Flow cytometry and cell IKK: Inhibitor of NF-κB kinase sorting IL: Interleukin

FBS: Foetal bovine serum ILC: Innate lymphoid cell

Fc: Fragment, crystallisable region of IL-1R: Interleukin-1 receptor an antibody iNOS: Inducible nitric oxide synthase

FSC: Forward scatter IP: Intraperitoneal

GADD45: Growth arrest and DNA IPA®: Ingenuity® Pathway Analysis damage-inducible 45 IRF: Interferon regulatory factor

ISG: Interferon-stimulated gene mDC: Myeloid dendritic cell

ISGF3: Interferon-stimulated gene MHC: Major histocompatibility factor 3 complex

ISRE: Interferon-stimulated response MHC-I: Major histocompatibility element complex class I

IVAG: Intravaginal MHC-II: Major histocompatibility

JAK: Janus kinase complex class II

KIR: Killer-cell immunoglobulin-like MIC: Major histocompatibility receptor complex class I-related protein

Klr: Killer cell lectin-like receptor miRNA: Micro ribonucleic acid

LCMV: Lymphocytic MMP: Matrix metalloproteinases choriomeningitis virus MOMP: Major outer membrane

LILRE: Lipopolysaccharide and protein interleukin-1 response element MPO: Myeloperoxidase

L. monocytogenes: Listeria mRNA: Messenger ribonucleic acid monocytogenes NAIP: NLR family, apoptosis

LPS: Lipopolysaccharide inhibitory protein

LRR: Leucine-rich repeat NF-κB: Nuclear factor-κB

LXR: Liver X receptor NK: Natural killer

MAPK: Mitogen-activated protein NLR: NOD- and LRR-containing kinase receptor mCMV: Murine cytomegalovirus NLRC: NLR family, CARD-

MDA5: Melanoma differentiation- containing associated protein

NLRP: NLR family, pyrin domain- RB: Reticulate body containing RBC: Red blood cell

NOD: Nucleotide-binding rhIFNα2b: Recombinant human oligomerisation domain interferon α2b

OAS: 2’5’-oligoadenylate synthetase rhIFNε: Recombinant human

PAMP: Pathogen-associated interferon ε molecular pattern rIFNε: Recombinant interferon ε

PB: Persistent body RIG-I: Retinoic acid-inducible gene-I

PBMC: Peripheral blood mononuclear RIN: RNA integrity number cell RNA: Ribonucleic acid

PBS: Phosphate buffered saline ROS: Reactive oxygen species

PBS-T: Phosphate buffered saline with rRNA: Ribosomal ribonucleic acid

0.05% Tween-20 RT: Reproductive tract pDC: Plasmacytoid dendritic cell RTI: Reproductive tract infection

PGE2: Prostaglandin-E2 RXR: Retinoid X receptor

PI3K: Phosphatidylinositol-3-kinase S1P5: Sphingosine-1-phosphate

PID: Pelvic inflammatory disease receptor 5

PMA: Phorbol 12-myristate 13-acetate SC: Subcutaneous

PRE: Progesterone receptor response SEM: Standard error of the mean element SLPI: Secretory leukocyte protease

PRR: Pattern recognition receptor inhibitor qPCR: Quantitative polymerase chain SOCS: Suppressor of cytokine reaction signalling

RAG: Recombination-activating gene

SPG: Sucrose-phosphate-glutamate Th1: T helper type 1 buffer Th2: T helper type 2

SSC: Side scatter Th17: T helper type 17

STAT: Signal transducer and activator TLR: Toll-like receptor of transcription TNF: Tumour necrosis factor

STI: Sexually transmitted infection trNK: Tissue-resident natural killer

S. typhimurium: Salmonella TSANZ: The Thoracic Society of typhimurium Australia and New Zealand

TBK: Tank-binding kinase TYK2: Tyrosine kinase 2

TBS-T: Tris-buffered saline with uNK: Uterine natural killer

0.05% Tween 20 USP18: Ubiquitin-specific peptidase

TCR: T cell receptor 18

Th: T helper WT: Wild-type

33 : Introduction

1.1 Sexually transmitted infections (STIs)

Every year, it is estimated that 500 million new cases of curable STIs occur worldwide, with more than one million of these occurring in Australia and New Zealand

(World Health Organization, 2008). STIs have been shown to disproportionately affect adolescents and young adults, particularly females, and individuals of low socioeconomic status. In the USA in 2000, 48% of all new cases of STI occurred in young people aged 15-24, despite this age group only accounting for 25% of the sexually active population (Weinstock et al., 2004). Owing to the anatomy of the female

RT, women are more susceptible to infection and often suffer from more severe sequelae (Aral et al., 2006). Additionally, teenage girls and young women are more susceptible to human papillomavirus (HPV) and Chlamydia trachomatis infections owing to the immaturity of their cervixes, which provides these pathogens with greater access to the basal layer of the epithelium (Calore et al., 1998; Ho et al., 1998; Shew et al., 1994). The fact that some STIs have lethal consequences, and many are incurable and/or associated with severe RT sequelae or other chronic disease manifestations, underpins the significance of STIs as a global health problem.

1.1.1 Chlamydia reproductive tract infections (RTIs)

1.1.1.1 Epidemiology and burden of disease

34 been estimated that there are 340,000 new cases of infection annually in Australia and

New Zealand and 131 million globally (World Health Organization, 2001; World

Health Organization, 2015).

Whilst C. trachomatis initially infects the mucosa of the lower RT

(vagina/urethra), infection commonly ascends into the upper RT tissues of both males and females. Furthermore, although C. trachomatis infection causes serious inflammatory diseases of both the lower and upper RT in both males and females, sequelae are often associated with infection ascending into the upper RT and are more severe in women (Cates and Wasserheit, 1991; Cohen and Brunham, 1999).

Complications of untreated or undiagnosed C. trachomatis infections in women include pelvic inflammatory disease (PID), chronic pelvic pain, tubal factor infertility, and ectopic pregnancy. It is estimated that 40% of women with untreated C. trachomatis infections will go on to develop PID and that 25% of women with Chlamydia- associated PID will develop infertility (World Health Organization, 2007). Importantly,

C. trachomatis infection is the most common cause of infertility (2/3rds of all cases, 5% of women) and is responsible for one third of all ectopic pregnancies (0.3% of pregnancies) (Cates and Wasserheit, 1991; Chandra et al., 2005; Loxton and Lucke,

2009; Paavonen and Eggert-Kruse, 1999; Pushpakala Ajaya et al., 2009; Tiitinen et al.,

2006; Wilkowska-Trojniel et al., 2009). Ectopic pregnancy is a life threatening condition and is responsible for 10% of all maternal deaths (Corpa, 2006).

The costs associated with Chlamydia RTIs are estimated to amount to $90-160 million per annum in Australia and $1-6 billion in the US, with the majority of these costs attributable to Chlamydia-associated sequelae in females (Beagley and Timms,

2000; Chesson et al., 2004; Division, 2001).

35 Significantly, 10-28% of adults have anti-C. trachomatis antibodies, indicating that a large proportion of the population has been infected at some stage throughout their lives (Castellsague et al., 2005; Lyytikainen et al., 2008; Riska et al., 2006).

Furthermore, 50-90% of all C. trachomatis infections are asymptomatic and, therefore, may remain untreated (Nelson and Helfand, 2001; Risser et al., 2005). Untreated infections can become persistent, leading to prolonged Chlamydia-induced inflammatory responses and greater immunopathological damage to the upper RT

(Nelson and Helfand, 2001). Importantly, in women, 46%, 18%, and 6% of asymptomatic C. trachomatis infections persist for >1, 2, and 4 years, respectively

(Molano et al., 2005).

Inflammatory responses generated during Chlamydia infections not only mediate clearance of infection but also induce tissue damage which is responsible for the development of PID and infertility (Cohen and Brunham, 1999; den Hartog et al.,

2006). In females, immune responses in the RT need to be tightly regulated in order to enable embryo implantation and development. These immune responses are influenced by changes in female sex hormone levels throughout the menstrual cycle and pregnancy

(Wira et al., 2015). Significantly, studies have shown that progesterone increases the risk of establishing Chlamydia RTIs in humans (Baeten et al., 2001; Sweet et al., 1986) and rodent models of infection (Gallichan and Rosenthal, 1996; Ito et al., 1984; Kaushic et al., 2000; Morrison and Caldwell, 2002). Indeed, women on hormone-containing oral contraceptives are more susceptible to Chlamydia RTIs with the strongest effect observed in those who are on progesterone only-containing contraceptives (Baeten et al., 2001; Morrison et al., 2009).

In summary, Chlamydia RTIs are a significant global health problem and frequently cause RT sequelae in women due to their propensity to induce

36 immunopathology and tissue damage in the upper female RT. Whilst effective antimicrobial treatments are available for Chlamydia infections and are essential in preventing complications and the spread of disease, due to the tendency of C. trachomatis infections to remain asymptomatic, disease often progresses for some time before treatment is initiated, by which stage it is often too late to prevent permanent damage (Black, 1997). To date, vaccines and topical microbicides have been largely unsuccessful at preventing infection (Darville and Hiltke, 2010) and there are no immunotherapies that prevent or treat the progression of infection-induced pathology.

As such, an improved understanding of the immunobiology of Chlamydia infections in the female RT may inform targets for the development of improved therapeutic strategies to prevent Chlamydia infections and associated disease.

1.1.1.2 Microbiology of Chlamydia

C. trachomatis is an obligate intracellular bacterial pathogen, which infects the epithelial cells of mucosal surfaces of the genital tract and conjunctiva. Chlamydia are capable of differentiating into three morphologically distinct forms, the infectious, metabolically inert elementary body (EB), the larger, metabolically active reticulate body (RB), and the latent, yet viable, persistent body (PB) (Byrne and Ojcius, 2004).

The developmental cycle of Chlamydia begins with endocytosis of extracellular EBs.

Inside the host cell, EBs avoid lysosomal fusion and differentiate into RBs, which then replicate via binary fission (Byrne and Ojcius, 2004). Once the number of RBs reaches an appropriate level, they differentiate back into EBs, which are released from the cell by exocytosis or lysis in order to continue the infectious cycle (Byrne and Ojcius,

2004). The intracellular localisation of Chlamydia within non-fused endosomes protects them from exposure to antibodies and destruction by other immunological factors

37 (Brunham and Peeling, 1994). Under suboptimal environmental growth conditions, such as reduced nutrient availability, the presence of antibiotics, or increased interferon

(IFN)γ production, Chlamydia RBs may differentiate into PBs, which are capable of producing a latent infection that can be reactivated when more favourable conditions return (Beatty et al., 1993; Byrne and Ojcius, 2004; Hogan et al., 2004).

The species of C. trachomatis is divided into three biological variants or biovars: the trachoma and lymphogranuloma venereum biovars, which most commonly infect human cells, and the mouse pneumonitis biovar, also known as Chlamydia muridarum.

These biovars can be further sub-divided into several different serovars based upon serological variations in their major outer membrane protein (MOMP). Serotypes A-C

(trachoma biovar) infect the columnar epithelial cells of the conjunctiva and are responsible for chlamydial trachoma, the World’s leading cause of preventable blindness (Mabey et al., 2003). Serotypes D-K (trachoma biovar) are sexually transmitted and are primarily responsible for Chlamydia urogenital infections (Hafner et al., 2008). Although the majority of infections caused by serovars D-K are asymptomatic, these bacteria are major causes of urethritis in both sexes, epididymitis and prostatitis in men and cervicitis, endometritis, and salpingitis in women (Malhotra et al., 2013; Stanojcic et al., 1996). Importantly, these serotypes are also capable of being vertically transmitted to the neonate during childbirth and cause a number of significant diseases in infants, including inclusion conjunctivitis and pneumonia

(Schachter et al., 1986). Serotypes L1, L2, and L3 (lymphogranuloma venereum biovar) are also sexually transmitted but are much more invasive than serotypes of the trachoma biovar. These invasive Chlamydia are capable of infecting the lymph nodes which drain the RT, causing the development of lymphogranuloma venereum (Mabey and Peeling,

2002). C. muridarum was originally isolated from the lungs of asymptomatic laboratory

38 mice and was subsequently shown to be a natural etiological agent of pneumonia in members of the family Muridae (Gogolak, 1953; Nigg and Eaton, 1944). The most commonly used animal model of Chlamydia female RTI utilises inbred strains of mice and C. muridarum. Intravaginal (IVAG) infection of mice with C. muridarum replicates the kinetics and induces immune responses and pathophysiological features similar to that of C. trachomatis infection in women (Morrison et al., 1995).

1.1.1.3 Immunology and pathophysiology of Chlamydia

Much of our understanding of the in vivo immunobiology of Chlamydia RTIs has emerged from studies in these rodent models of Chlamydia RTI that are representative of human infection (Berry et al., 2004; Morrison and Caldwell, 2002).

These studies show that clearance of infection is associated with increased Chlamydia- specific immunoglobulin (Ig)A and IgG antibody responses and an early (7-14 days post infection [dpi]) and intense neutrophil influx into the mucosa, followed by macrophage, CD4+ T cell, and B cell infiltration in the later stages of infection (Berry et al., 2004; Morrison et al., 1995). Whilst much is known about a number of key immunological factors that mediate clearance and pathology, the interactions between infection and the mucosal immune environment in the female RT are highly complex, and many of the factors that promote or restrict ascending infection and persistence, versus those that drive immunopathology, are yet to be clarified.

The initial inflammatory response to C. trachomatis is mediated by host epithelial cells (Stephens, 2003), which upon infection, secrete a wide variety of chemokines and cytokines to home inflammatory cells to the site of infection and initiate/execute effector cell immune responses (Rasmussen et al., 1997). This pro- inflammatory cytokine cascade is initiated by the release of interleukin (IL)-1 from

39 endocervical epithelial cells and requires intracellular Chlamydia replication to be induced (Rasmussen et al., 1997). Epithelial cell responses also play an essential role in pathogenesis. The production of various mediators, including proteases, growth factors, and clotting factors by epithelial cells leads to tissue damage and, eventually, scarring

(Stephens, 2003). Significantly, it has been demonstrated that epithelial cell release of

IL-1 alone is sufficient to cause damage to the fallopian tubes, independent of inflammatory cell processes (Hvid et al., 2007). The acute inflammatory response elicited during Chlamydia infection of the RT is characterised by neutrophilic infiltration of the mucosae and submucosae (Morrison and Morrison, 2000). Although neutrophils are capable of killing EBs and play an important role in the clearance of infection, they too contribute to pathogenesis. Studies in mice have shown that the level of neutrophilic inflammation in the oviducts directly correlates with the development of hydrosalpinx, the accumulation of fluid in the oviducts due to tubal occlusion (Shah et al., 2005). Acute inflammatory cells cause damage to RT tissues through the activation of phagocyte oxidase and subsequent release of superoxide molecules, which damage the delicate tissues, resulting in occlusion of the oviducts and subsequent formation of hydrosalpinx and tubal factor infertility (Ramsey et al., 2001b). Neutrophil production of matrix metalloproteinases (MMPs) has also been implicated in destruction and remodelling of the oviduct during Chlamydia infection (Ramsey et al., 2005).

As infection continues, macrophages and lymphocytes accumulate in the submucosae (Morrison et al., 1995; Morrison and Morrison, 2000). Infiltrating lymphocytes include CD4+ and CD8+ T cells and B cells, however, CD4+ T cells, or T helper (Th) cells, predominate (Morrison and Morrison, 2000). CD4+ T cell-mediated immunity is essential for the resolution of infection (Perry et al., 1997; Su and Caldwell,

1995). This is demonstrated by the fact that major histocompatibility complex class II

40 (MHC/-II)-/- and T cell receptor (TCR)αβ-/- mice are unable to resolve infection

(Morrison et al., 1995; Perry et al., 1997). Conversely, mice deficient of CD8+ T cell effector function clear infection with similar kinetics to wild-type (WT) mice (Perry et al., 1999a). Th cell phenotype has also been found to influence the outcome of infection.

Low peripheral blood mononuclear cell (PBMC) IFNγ and high IL-10 responses to

Chlamydia 60kDa heat shock protein (Chsp60) are associated with an increased risk of infection and PID (Cohen et al., 2005; Debattista et al., 2002a). Additionally, high cervical cell IL-1β, IL-6, IL-8, and IL-10 responses upon re-stimulation with Chlamydia

EBs are also associated with infertility, while high IFNγ and IL-12 responses are associated with protection against fertility disorders (Agrawal et al., 2009).

Furthermore, mice deficient in IL-12, IFNγ, or the IFNγ receptor (IFNγR) are unable to eradicate infection (Cotter et al., 1997; Ito and Lyons, 1999; Johansson et al., 1997a;

Perry et al., 1997). Together, these findings suggest that a strong Th type 1 (Th1) phenotype is protective against Chlamydia infections and their sequelae.

Importantly, T cell responses may also contribute to the tissue damage induced by infection. Animal models of Chlamydia re-infection demonstrate that CD4+ and

CD8+ T cell influx is greater and more rapid during secondary infection of the oviducts, compared to that observed during primary infection, whereas neutrophilic inflammation remains the same (Rank et al., 1995). Increased T cell influx correlates with increased tissue damage, fibrosis, and oviduct dilatation, despite bacterial burden being significantly reduced in the secondary compared to the primary infection (Rank et al.,

1995). Epidemiologic studies also show an increased risk of severe sequelae with reinfection (Hillis et al., 1997; Kimani et al., 1996). However, chronic RT damage can occur independently of these responses (Morrison et al., 1995) and studies in women

41 positive for anti-C. trachomatis antibodies indicate that CD4+ T cells may be protective against severe infection-induced pathology (Agrawal et al., 2009).

1.1.2 Hormonal influence on infection and immunity in the

female reproductive tract (RT)

Immune responses in the female RT require tight regulation as they must both provide protection against the great variety of pathogens that this site may be exposed to and allow tolerance to allogenic sperm and the developing foetus (Quayle, 2002).

Changes in female sex hormone levels during the menstrual cycle and pregnancy not only play an important role in mediating the regulation of these immune responses in order to optimise conditions for sperm migration and embryo implantation and development (Mor and Cardenas, 2010), but also have a significant effect on the susceptibility of the female RT to infection. Significantly, variations in the levels of progesterone and oestrogen observed during the different stages of the menstrual cycle and associated with hormonal contraceptive use have been shown to correlate with variations in the susceptibility of the female RT to a number of infections. For example, the use of oral hormonal contraceptives that contain progesterone only or a combination of both progesterone and oestradiol, and the administration of depot medroxyprogesterone acetate (DMPA), have been shown to increase the risk of contracting Chlamydia, herpes simplex virus (HSV)-2 (Baeten et al., 2001), Candida albicans (Catterall, 1971), and human immunodeficiency virus (HIV) infections, but decrease the risk of contracting Trichomonas vaginalis (World Health Organization,

2000) and HPV (Moscicki et al., 2001) infections. Viral shedding during HSV and HIV infections is also higher in patients that are on progesterone-containing contraceptives

(Mostad et al., 2000; Wang et al., 1999a). Furthermore, the development of C.

42 trachomatis and Neisseria gonorrhoeae salpingitis occurs more frequently within the 7 days prior to menstruation, when progesterone levels are high (Sweet et al., 1986).

Some of these effects are mirrored in animal models of infection. For example, mice are more susceptible to Chlamydia and HSV-2 infections during the di-oestrous stage of their oestrous cycles (akin to the luteal/secretory phase of the menstrual cycle in humans), when progesterone levels are at their highest (Gallichan and Rosenthal, 1996;

Ito et al., 1984), and more susceptible to N. gonorrhoeae infection during pro-oestrus

(akin to the follicular/proliferative phase in humans), when oestrogen levels peak (Kita et al., 1991). Furthermore, progesterone pre-treatment has been shown to dramatically increase the susceptibility of female mice to both C. muridarum and HSV-2 RTIs

(Baker and Plotkin, 1978; Kaushic et al., 2003; Morrison and Caldwell, 2002).

However, many of the studies investigating the association between hormone levels and RTIs fail to take into account confounding factors, such as sexual behaviour, condom use, and contact with healthcare providers, which may differ between users of hormonal contraceptives, users of other methods of contraception, and those who do not use contraception (Mohllajee et al., 2006). Additionally, while some oral contraceptives and DMPA contain progesterone only, the commonly used oral contraceptive pill contains both progesterone and oestradiol, confounding the specific effects of these two hormones. Therefore, further research is required in order to ascertain the role of female sex hormones in the establishment/progression of these infections and the immunological and pathophysiological mechanisms that underpin their effects.

In order to dissect out the individual roles of progesterone and oestrogen in regulation of RT immune responses towards Chlamydia, Kaushic et al. pre-treated ovariectomised rats with progesterone, oestradiol, or a combination of both, and infected them with C. muridarum via the intrauterine route (Kaushic et al., 2000). They

43 found that oestradiol administration decreased, while progesterone administration increased, Chlamydia infection and infection-induced inflammation in the RT tissues compared to controls that did not receive either hormone (Kaushic et al., 2000).

Interestingly, the combination of progesterone and oestradiol was found to decrease inflammation but enhance Chlamydia infection, indicating that the protective effects of oestradiol on infectivity are independent of its anti-inflammatory effects (Kaushic et al.,

2000) and may be counter-regulated by progesterone.

Although the exact mechanisms underpinning hormone-mediated changes in susceptibility to and severity of infection are unknown, many immunological activities, such as innate immune responses and the expression of constitutive defence mechanisms are known to be regulated by the fluctuation in hormone levels that occurs throughout the menstrual cycle in humans and oestrous cycle in mice. The human female RT expresses the full complement of toll-like receptors (TLRs), however, the levels at which that they are expressed has been shown to vary depending on the specific tissue analysed within the RT (Nasu and Narahara, 2010) and stage of the menstrual cycle (Aflatoonian et al., 2007). For example, the expression of TLRs 2, 3, 4,

5, 6, 9, and 10 in the endometrium has been shown to be significantly higher during the secretory phase of the menstrual cycle, when progesterone levels are high, compared to during the proliferative phase, when progesterone levels are low (Aflatoonian et al.,

2007; Compton et al., 2003; Lin et al., 2009). Furthermore, endometrial tissue expression of the antimicrobial peptides, human defensin-5 (HD-5), secretory leukocyte protease inhibitor (SLPI), and human beta-defensin-1 (HBD-1), is also highest during the secretory phase (King et al., 2000; Quayle et al., 1998). However, in vaginal fluid, collected by either cervico-vaginal lavage or using tampons, SLPI and HBD-1 are

44 highest during the proliferative phase (Horne et al., 2008; Keller et al., 2007; Valore et al., 2002).

The recruitment and activity of immune cells in the female RT is also controlled by cycle-dependent hormone changes. In rat uterine tissue, granulocyte, macrophage, dendritic cell (DC), CD8+ T cell, and MHC-II+ cell numbers are elevated during oestrus, when oestrogen levels are high (Kaushic et al., 1998). In normal healthy women, peripheral blood T cells are increased during the follicular phase, while both the number and cytolytic activity of circulating conventional natural killer (c/NK) cells and the number of uterine (u)NK cells present in the RT are increased during the luteal phase

(King et al., 1991; Lee et al., 2010b). Furthermore, CD8+ T cell activity, as determined by a T cell-specific lysis assay, is only observed in human endometrium during the proliferative phase (White et al., 1997). Interestingly, oestradiol receptors have been found on CD8+ T cells, which may explain the increased presence and activity of these cells in the RT during stages of the menstrual/oestrous cycle that correspond with increased oestrogen levels (Danel et al., 1983; Stimson, 1988; White et al., 1997).

Hormonal contraceptives have also been shown to influence immune cell activity. Baker et al. demonstrated that 3 months of combined oral contraceptive use significantly decreases the activity of NK cells (Baker et al., 1989). Furthermore, exposure to oestradiol has been shown to up-regulate the production of IFNγ by concanavalin A (ConA)-stimulated splenocytes and staphylococcal enterotoxin A- stimulated PBMCs (Fox et al., 1991; Grasso and Muscettola, 1990; Karpuzoglu-Sahin et al., 2001). This effect has also been observed in vivo, as mice treated with 17β- oestradiol express higher levels of IFNγ in inflamed skin in an animal model of contact hypersensitivity (Sakazaki et al., 2006). Since strong Th1 and IFNγ responses have been shown play an important role in the clearance of Chlamydia infections, the expansion of

45 T cells and increase in IFNγ expression mediated by oestradiol may account for the increase in protection against Chlamydia infections observed during oestrogen- dominated stages of the menstrual/oestrous cycle.

46 1.2 Innate immunity in the female RT: Importance of type

interferons (IFNs), natural killer (NK) cells, and

inflammasomes in Chlamydia infection

The innate immune system is a primitive network of effector cells, cellular receptors, and soluble factors found in all classes of plant and animal life that provides immediate protection against infections. The cells of the innate immune system include phagocytes, such as macrophages, neutrophils, and DCs; γδT cells; NK cells and other innate lymphoid cells (ILCs); granulocytes, such as mast cells, eosinophils, and basophils; and epithelial cells. These cells recognise pathogens via the detection of pathogen-associated molecular patterns (PAMPs), such as lipopolysaccharide (LPS), peptidoglycan, and double-stranded (ds)RNA, which are highly conserved molecular structures broadly expressed by different classes of micro-organisms. In addition to recognising and responding to pathogens, the innate immune system is also capable of detecting signs and potential sources of tissue damage. These include: the appearance of endogenous compounds in locations usually devoid of these substances, commonly referred to as damage-associated molecular patterns (DAMPs), such as extracellular adenosine triphosphate (ATP); foreign stressors, such as phagocytosed irritants and crystalline structures; and the up-regulation of stress ligands expressed by infected or transformed cells, such as the MHC class I (MHC-I)-related proteins (MIC)A and B.

The innate immune system relies on germline-encoded pattern recognition receptors

(PRRs) to survey the extracellular environment and monitor subcellular locations for these noxious stimuli (Takeuchi and Akira, 2010). The major families of PRR include

TLRs, nucleotide-binding oligomerisation domain (NOD)- and leucine-rich repeat

(LRR)-containing receptors (NLRs), and retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs).

47 Detection of these stimuli triggers the induction of inflammatory responses, such as the recruitment of innate leukocytes and production of cytokines. These responses promote the removal for foreign substances, activate the adaptive immune system, and initiate tissue repair processes. However, inflammatory responses are also capable of causing tissue damage and have been implicated in the pathogenesis of many communicable, environmental, and autoimmune diseases. Importantly, innate immune responses play a key role in both the defence against, and pathogenesis of, Chlamydia infections in the female RT.

1.2.1 Type I IFNs

Type I IFNs are a group of functionally related cytokines that play an integral role in many innate immune processes and the maintenance of tissue homeostasis. Type

I IFNs and their receptors are expressed by nearly every cell type throughout the body and mediate a wide variety of immune activities (Stark et al., 1998). In humans, this family of IFNs is made up of 12 IFNα subtypes, IFNβ, IFNω, IFNκ, and IFNε (Flores et al., 1991; Hardy et al., 2004; Hillyer et al., 2012; LaFleur et al., 2001). Other members of the type I IFN family include IFNτ and IFNδ, which are found in ruminants and pigs, respectively. Out of all the type I IFNs, IFNα and IFNβ are the most commonly expressed across different cell types and species and the best characterised (Decker et al., 2005).

1.2.1.1 Induction of type I IFNs

The expression of type I IFNs is often induced by the activation of PRRs, upon exposure to PAMPs (Ozato et al., 2002). Membrane-bound TLR3 and the cytoplasmic

RLRs, RIG-I and melanoma differentiation-associated protein 5 (MDA5), are

48 responsible for the induction of type I IFNs in response to stimulation with dsRNA. The cytoplasmic DNA-dependent activator of IFN regulatory factors (DAI/IRFs) induces the transcription of type I IFNs upon intracellular detection of double stranded B-form

DNA (Ishii et al., 2008; Kawai and Akira, 2010). Membrane-bound TLR4 stimulates type I IFN production in response to LPS from facultative Gram-negative bacteria. Type

I IFN production has also been proposed to occur in response to cytoplasmic detection of both Gram-positive and Gram-negative intracellular bacteria, although the PRRs and pathways involved are yet to be elucidated (Monroe et al., 2010). The observation that

Chlamydia triggers IFNβ production during active cytoplasmic replication in host cells supports this hypothesis (Devitt et al., 1996). This may occur via the detection of nucleic acids from lysed bacteria (Monroe et al., 2010), the stimulation of NOD1 by muropeptide subunits of the bacterial cell wall (Pandey et al., 2009; Prantner et al.,

2010), the detection of an unknown ligand by TLR3 (Derbigny et al., 2010), or the detection of cyclic di-GMP, a bacterial second messenger, which has been shown to induce type I IFN responses independently of other known cytoplasmic receptors

(McWhirter et al., 2009).

Despite the wide range of ligands, receptors, and adaptor molecules capable of inducing type I IFN expression, stimulation of these pathways all result in the activation of IRF3 and IRF7, which initiate the transcription of type I IFN genes (Honda et al.,

2005; Taniguchi and Takaoka, 2002). IRF3 is constitutively expressed in all cells and is rapidly activated in response to PRR stimulation by tank-binding kinase (TBK)1 or inhibitor of nuclear factor-κB (NF-κB) kinase (IKK)-i (Fitzgerald et al., 2003; Sharma et al., 2003). Once activated, IRF3 dimerises and binds to NF-κB, activator protein 1

(AP1) members, and high mobility group (HMG) proteins, forming an enhanceosome that mediates the transcription of IFNβ and IFNα4 (Sato et al., 2000). The basal

49 expression levels of IRF7 are low for most cells, however, activation of the type I IFN receptor, IFNAR, and the downstream signalling molecule, IFN-stimulated gene factor

3 (ISGF3), by IFNβ or IFNα4 acts as a positive feedback loop, enhancing transcription of the IRF7 gene (Levy et al., 2003). Newly synthesised IRF7 is then available for phosphorylation and transcription of all type I IFN genes. The relative amount of each type I IFN subtype produced depends on the cell, species, and stimulus (Pestka et al.,

2004). Plasmacytoid (p)DCs are capable of producing large amounts of type I IFNs via a unique pathway involving TLRs 7 and 9 (Honda et al., 2004; Honda et al., 2005;

Kawai et al., 2004). This mechanism is efficient in rapidly producing large amounts of type I IFN due to the constitutive expression of IRF7 in these cells and lack of reliance on IKK-i and TBK1 signalling pathways (Colonna et al., 2004; Miyahira et al., 2009).

1.2.1.2 Type I IFN signalling pathways

All type I IFNs signal through the same ubiquitously expressed receptor,

IFNAR. This receptor signals through the Janus kinase/signal transducer and activator of transcription (JAK/STAT) pathway (Li et al., 1997; Li et al., 1996) and is composed of two chains, IFNAR1 and IFNAR2 (Cleary et al., 1994; Lutfalla et al., 1995), which are permanently associated with the two JAKs, tyrosine kinase 2 (TYK2) and JAK1 respectively. Activation of the receptor and phosphorylation of TYK2 and JAK1 triggers the recruitment and activation of the STAT molecules, STAT1 and STAT2

(Decker et al., 2005; Li et al., 1997; Li et al., 1996). STAT1 and STAT2 form heterodimers that associate with IRF9 in the nucleus to form ISGF3, which binds to

IFN-stimulated response elements (ISREs) in the promoter regions of IFN-stimulated genes (ISGs) to induce their transcription (Darnell et al., 1994; Decker et al., 2005; Li et al., 1997; Li et al., 1996). STAT1 homodimers are also formed in response to type I IFN

50 signalling and bind to gamma IFN-activated sites (GASs) to induce transcription

(Decker et al., 2005). Evidence suggests that some ISGs act as negative feedback mechanisms, inhibiting the transcription of other ISGs, as blocking protein synthesis in cells treated with type I IFNs has been found to prolong ISG transcription (Friedman et al., 1984; Larner et al., 1986). ISGs involved in these negative feedback pathways include suppressor of cytokine signalling (SOCS)1 and 3 and ubiquitin-specific peptidase 18 (USP18) (Schneider et al., 2014). Other signalling pathways activated by

IFNAR include the p38 mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3-kinase (PI3K) pathways (Platanias, 2005).

1.2.1.3 Key roles of type I IFNs in immune responses

Many immune processes are controlled by type I IFN signalling. These include the induction of antiviral immune responses and the antiviral state (Prchal et al., 2009); modulation of immune cell differentiation, activation and migration (Keay and

Grossberg, 1980; Mattei et al., 2010); increasing expression of MHC-I and enhancing

CD8+ T cell responses (Basham et al., 1982; Curtsinger et al., 2005; Le Bon et al.,

2003); and promotion of Th1 cell differentiation and cell-mediated immunity (Prchal et al., 2009). Interestingly, despite sharing the one receptor, the different type I IFNs vary in their antiviral and immunomodulatory capabilities (Pestka, 2000). For example, the

12 different IFNα subtypes differ in their ability to induce NK cell activity by up to 104- fold (Ortaldo et al., 1984) and IFNβ has been shown to be a more potent inducer of tumour necrosis factor (TNF), anti-proliferative pathways, and tumour apoptosis than other type I IFNs (Deonarain et al., 2003; Qin et al., 2001). It has been proposed that the various type I IFN species may induce different signal transduction pathways via unique interactions with the two IFNAR chains. This may be due to differences in the active

51 regions of various type I IFNs, such as IFN receptor recognition peptide 1, which links the A and B α-helices of the type I IFNs, since this loop structure has been found to be critical for high-affinity binding to the IFNAR2 subunit (Pestka et al., 2004).

Additionally, despite not being the primary ligand-binding chain, the deletion of a sub- domain from IFNAR1 has also been shown to prevent activation of the receptor by some type I IFNs, which further indicates different modes of activation by the different type I IFNs (Keay and Grossberg, 1980). Notably, IFNβ has recently been shown to form a stable complex with IFNAR1 and activate a unique signalling axis via the Akt pathway (de Weerd et al., 2013).

1.2.1.4 Role of type I IFN signalling in Chlamydia

infections

Although type I IFNs are mainly recognised for their antiviral activities, the production of type I IFNs is also an immediate innate immune response of epithelial, fibroblast, and haematopoietic cells to stimulation with many bacterial PAMPs (Bogdan et al., 2004). Significantly, the ability of type I IFNs to modulate the immune response, through the activation of NK cells and DCs and the production of antibodies, has been proposed to play an important role in protection against bacterial pathogens (Decker et al., 2005). Importantly, IFNβ, IRF3, and IRF7 have been found to be essential for the control of Chlamydophila pneumoniae replication in human endothelial cells (Buß et al., 2010) and a number of anti-Chlamydia factors induced by IL-1, TNF, and PRR signalling are dependent upon type I IFN signalling for successful expression. For example, during Chlamydia infection of McCoy cells, inducible nitric oxide synthase

(iNOS) expression can be blocked by the addition of anti-IFNα and anti-IFNβ antibodies (Devitt et al., 1996). As iNOS-induced production of NO is important for

52 controlling Chlamydia replication (Jayarapu et al., 2010; Mayer et al., 1993), this suggests that type I IFNs may play key a role in regulating protective responses during

Chlamydia infection. Type I IFNs have also been shown to inhibit the growth of C. trachomatis and C. psittaci in vitro by up-regulating the expression of indoleamine-2,3- dioxygenase (IDO), which catabolises tryptophan, a metabolite essential for Chlamydia growth (Carlin and Weller, 1995; Carlin et al., 1989; Shemer-Avni et al., 1989).

Additionally, constitutive low-level expression of type I IFNs has been shown to regulate signalling by increasing the expression and phosphorylation of cytokine signal transduction molecules, such as STAT1, STAT3, and STAT4, which primes cells to respond to other cytokines, such as IFNγ, IL-6, IL-12, and IL-18 (Freudenberg et al.,

2002; Gough et al., 2010; Takaoka et al., 2000). Since these cytokines play important roles in controlling Chlamydia infections, this immunomodulatory effect of type I IFNs has also been proposed to play an important role in regulating Chlamydia infection and associated diseases.

Interestingly, however, Nagarajan et al. observed that IFNAR-/- mice are more resistant C. muridarum RTI (Nagarajan et al., 2008). In this study, infected IFNAR-/- mice were shown to shed less Chlamydia, clear infection faster, and develop less oviduct pathology than infected WT controls (Nagarajan et al., 2008). This correlated with an increase in the number of Chlamydia-specific T cells in the iliac lymph nodes and enhanced trafficking of CD4+ T cells to the cervix (Nagarajan et al., 2008). Similar results were observed in a mouse model of Chlamydia respiratory tract infection (Qiu et al., 2008). Evidence suggests that this detrimental effect of IFNAR signalling on

Chlamydia infection is due to IFNβ-mediated suppression of IFNγ-induced up- regulation of MHC-II on epithelial cells and, hence, decreased presentation of

Chlamydia antigens to CD4+ T cells (Jayarapu et al., 2010; Nagarajan et al., 2008).

53 Together, these in vitro and in vivo studies demonstrate that the relationship between type I IFNs and Chlamydia infections is complex, with the various type I IFNs likely having distinct and differential effects on innate and adaptive immune responses that are critical to controlling infection at different time-points.

1.2.2 IFNε

IFNε was first described by Hardy et al. to be a novel type I IFN located at the

3’ end of the mouse type I IFN locus that consists of an open reading frame of 192 amino acids (Hardy et al., 2004). The highly conserved human orthologue is located on chromosome 9p21, in the region of conserved synteny, and encodes an open reading frame of 208 amino acids (Hardy et al., 2004). IFNε was confirmed as a protein- encoding gene by reverse-transcribing messenger (m)RNA from the human amnion epithelial cell line, WISH, and primary cultures of mouse embryonic fibroblasts and amplifying the resulting cDNA fragments using an IFNε-specific promoter (Hardy et al., 2004).

Mature human IFNε has a molecular weight of 22kDa (Peng et al., 2007) and is

15 residues longer than its murine orthologue but, excluding this region, they have 54% amino acid identity with an additional 15% amino acid similarity (Hardy et al., 2004).

The secondary and tertiary structures of IFNε are also highly conserved between the murine and human orthologues (Hardy et al., 2004). Although the tertiary structure of

IFNε is similar to that of other type I IFNs, only some of the secondary structures are conserved, indicating that IFNε may induce distinctive effects (Hardy et al., 2004).

Despite these differences, the presence of IFNε within the type I IFN locus and its tertiary structure homology with the other members of the type I IFN family support its classification as a type I IFN (Hardy et al., 2004). Out of all the type I IFNs, IFNε is

54 most closely related to IFNβ, with which it shares 38% amino acid identity (Hardy et al., 2004; Peng et al., 2007). As many functionally related genes are located in close proximity to one another to allow co-regulation via locus control regions (Loots et al.,

2000), the same may be true for the type I IFN locus (Hardy et al., 2004). However, the mechanisms by which IFNε is regulated and whether it induces distinct downstream effects compared to the other type I IFNs remain to be fully elucidated.

Preliminary studies performed by our collaborators, headed by Prof. Paul

Hertzog at Monash University and the Hudson Institute of Medical Research,

Melbourne, have shown that IFNε is expressed at high levels in uterine, ovarian and cervical tissues (Figure 1.1 A) (Fung et al., 2013), however, it has also been detected at lower levels in the brain, heart, lung, and adrenal glands of adult mice (Hardy et al.,

2004). Preliminary studies have also confirmed that IFNε is highly expressed in the human female RT (Fung et al., 2013). Significantly, basal expression of IFNε was found to be up to 1.2 x 103 times greater in the RT tissues of mice than IFNα and β (Figure

1.1 A) and subsequent studies have identified endometrial epithelial cells as the primary source of IFNε (Figure 1.1 B) (Fung et al., 2013). These expression patterns provide evidence that IFNε may play an important and specific role in RT physiology (Hardy et al., 2004).

55 A

B WT IFNε-/-

Figure 1.1: Expression patterns of interferon (IFN)ε. (A) Unlike IFNα and IFNβ, IFNε messenger (m)RNA is constitutively expressed in the tissues of the female reproductive tract (RT). Expression levels of IFNε in the adult mouse are highest in the uterus, followed by the ovaries and cervix. IFNε mRNA expression was normalised against expression of the housekeeping gene control, 18S ribosomal (r)RNA, and presented relative to IFNε expression in the kidney. All data are presented as mean±SEM. (B) IFNε protein, as detected by immunohistochemistry, is expressed by epithelial cells of the endometrium in wild-type (WT) C57BL/6 mice. Scale bars=50µm. Figure adapted from (Fung et al., 2013).

56 1.2.2.1 Regulation of IFNε

Unlike other type I IFNs, IFNε is constitutively expressed in the female RT

(Figure 1.1) and is not heavily up-regulated by PRR activation or virus infection in vitro (Fung et al., 2013; Hardy et al., 2004; Matsumiya et al., 2007). However, further research is required to determine the expression patterns of IFNε in response to infection in vivo. Several transcription factor binding sites have been identified in the

IFNε gene, such as sites for STATs and the CCAAT/enhancing protein β (CEBPβ) and progesterone receptor response elements (PREs) (Hardy et al., 2004). The presence of

PREs suggests that IFNε may be regulated by female sex hormone levels throughout the menstrual/oestrous cycle and/or during pregnancy and may be involved in maintaining

RT homeostasis (Hardy et al., 2004). Significantly, preliminary studies demonstrate that

IFNε fluctuates throughout the murine oestrous cycle, with expression found to be highest during oestrus, when progesterone levels are low, and lowest during di-oestrus and during pregnancy at the stage of embryo implantation, when progesterone levels are high (Figure 1.2) (Fung et al., 2013).

The high constitutive expression of IFNε in RT tissues suggests it may be a well-tolerated type I IFN involved in maintaining the balance between immune protection and reproductive function. Progesterone is necessary for the maintenance of pregnancy in mammals (Tamada and Ichikawa, 1980) and IFNε expression is low when levels peak at di-oestrus (Fata et al., 2001; Fung et al., 2013; Walmer et al., 1992). This suggests that progesterone may antagonise the production of IFNε in order to maintain homeostasis for embryo development. Significantly, given the important role of type I

IFNs in immune function, progesterone-mediated down-regulation of IFNε may be a potential mechanism by which hormonal contraceptive use in humans and progesterone pre-treatment of mice increases susceptibility to infections.

57 A B

Figure 1.2: Interferon (IFN)ε expression in murine uterine tissue during stages of the oestrous cycle and pregnancy. (A) IFNε messenger (m)RNA expression is highest during oestrus, when progesterone levels are low, and lowest during di-oestrus, when progesterone levels are high. (B) During pregnancy, IFNε mRNA expression is down-regulated from day 1.5 post coitus and lowest at day 4.5, the stage of embryo implantation. IFNε mRNA expression was normalised against expression of the housekeeping gene control, 18S ribosomal (r)RNA. All data are presented as mean±SEM. *=p<0.05; **=p<0.01; ***=p<0.001. Figure adapted from (Fung et al., 2013).

58 1.2.2.2 Function of IFNε

IFNε, like other type I IFNs, has been shown to have antiviral and antiproliferative activity and promote NK cell cytotoxicity (Peng et al., 2007), despite not being significantly up-regulated by viral infection (Hardy et al., 2004; Matsumiya et al.,

2007). The antiviral activity of recombinant human (rh)IFNε, generated in either

Escherichia coli or a eukaryotic system, was determined by treating WISH cells with various concentrations of rhIFNε and challenging these cells with 100 times the TCID50 of vesicular stomatitis virus (Peng et al., 2007). The antiviral activity of rhIFNε was found to be 6 x 105 IU/mg when purified from E. coli and 1.2 x 106 IU/mg when purified from a eukaryotic system, where 1 IU is the concentration required to prevent the death of 50% of the cells (Peng et al., 2007). However, these results are significantly lower than those observed for recombinant human (rh)IFNα2b, which has an antiviral activity of 2 x 108 IU/mg (Peng et al., 2007). The effects of rhIFNε and rhIFNα2b on

NK cell cytotoxicity were also assessed by measuring the amount of lactate dehydrogenase released into the supernatants of co-cultures containing NK cells and

K562 target cells treated with various concentrations of rhIFNε or rhIFNα2b (Peng et al., 2007). rhIFNε was found to be 60 times less effective than rhIFNα2b at promoting

NK cell cytotoxicity (Peng et al., 2007). In the same study, a proliferation assay was used to determine the growth suppressive effect of rhIFNε, which was found to be 60 times less than that of rhIFNα2b (Peng et al., 2007). However, the magnitude of these effects may not be universal across different cell types, as certain functions of IFNε have since been shown to be cell-specific. For example, Matsumiya et al. have uncovered an important function of IFNε in HeLa cells (Matsumiya et al., 2007). The

HeLa cervical cancer cell line is appropriate for modelling IFNε-mediated responses in the female RT in vitro as the cervix is an important site of immunological regulation in

59 the female RT (Matsumiya et al., 2007). Matsumiya et al. showed that IFNε plays an important role in TNF-mediated up-regulation of RIG-I in HeLa cells by enhancing

STAT1 expression and phosphorylation (Matsumiya et al., 2007). This only occurred in

HeLa cells and not in the breast cancer cell line, MCF-7, or embryonic kidney cell line,

HEK293 (Matsumiya et al., 2007). Matsumiya et al. also showed that TNF increases the expression levels of IFNε by stabilising IFNε mRNA transcripts (Matsumiya et al.,

2007). These results suggest that IFNε may be capable of inducing more potent anti- pathogen effects in HeLa cells or other cells of the female RT compared to other cell lines or tissues. However, the role of IFNε in defence against infection of the female RT is not fully understood and requires further investigation.

1.2.2.3 Our forerunner studies and preliminary data

Our research group has established a collaborative program with Prof. Paul

Hertzog et al. in order to determine the role of IFNε in protection against female RTIs.

His research team developed the first IFNε-/- strain of mouse in order to delineate the effects of this novel type I IFN in the maintenance of RT function and defence against

RTIs in vivo. They show that the survival, fertility, uterine histology, and B- and T cell function of naive IFNε-/- mice is unaltered compared to WT controls, and that IFNε-/- mice do not spontaneously develop disease (Fung et al., 2013). However, the basal levels of several ISGs, including 2’5’-oligoadenylate synthetase (OAS), ISG15, and

IRF7, are dramatically reduced in the RT tissues of IFNε-/- mice compared to WT controls, suggesting that IFNε may be responsible for maintaining basal expression of innate immune factors in the female RT (Fung et al., 2013). Conversely, the levels of expression of other ISGs known to be induced by type I IFN signalling, such as STAT2, are not altered in IFNε-/- mice compared to WT controls (unpublished observations).

60 This suggests that IFNε may induce distinct downstream effects compared to other type

I IFNs.

To determine if IFNε plays a role in protection against Chlamydia RTIs, we first pre-treated WT and IFNε-/- mice with progesterone in order to increase their susceptibility to infection and synchronise their oestrous cycles. We then infected these mice with 5 x 104 inclusion forming units (ifu) of C. muridarum IVAG. Significantly, we showed that IFNε-/- mice had increased Chlamydia in the vagina and worsened signs of disease from as early as 3dpi and throughout a 30 day time-course of infection compared to infected WT controls (Figure 1.3) (Fung et al., 2013).

These findings indicate that IFNε plays an important role in protecting the female RT against Chlamydia infections. However, the mechanism of IFNε-mediated protection against infection, how the protective effects of IFNε are affected by changes in the levels of female sex hormones, and whether modulation of IFNε and/or IFNε signalling can be utilised therapeutically for the treatment/prevention of Chlamydia

RTIs are yet to be determined.

61 A B

C D

Figure 1.3: Interferon (IFN)ε-/- mice are more susceptible to Chlamydia reproductive tract infection (RTI). IFNε deficiency during a murine model of Chlamydia RTI resulted in; (A) enhanced severity of clinical signs of disease (vaginal mucus, redness, and swelling, and rough coat) throughout the time- course of infection, increased Chlamydia numbers in (B) vaginal lavage fluid collected at 3 days post infection (dpi), and (C) vaginal swabs collected at 4, 7, 21, and 29dpi, and (D) increased Chlamydia 16S ribosomal (r)RNA expression in uterine horn tissue at 30dpi. Chlamydia 16S rRNA expression was normalised against expression of the housekeeping gene control, 18S rRNA. All data are presented as mean±SEM. *=p<0.05, **=p<0.01. Figure adapted from (Fung et al., 2013).

62 1.2.3 NK cells

1.2.3.1 The NK cell lineage

NK cells are large granular lymphocytes of the innate immune system that play an integral role in the first line of defence against intracellular infections and transformed cells due to their ability to rapidly mediate cellular cytotoxicity and produce pro-inflammatory cytokines. Like all other lymphocytes, NK cells arise from common lymphoid progenitor (CLP) cells in the bone marrow (Kondo et al., 1997). IL-

15 is essential for the development and survival of NK cells in the bone marrow and acquisition of the IL-2 receptor β chain (CD122), a component of the IL-15 receptor, drives the maturation of early NK cell-committed precursors by allowing them to respond to IL-15 (Kennedy et al., 2000; Mrozek et al., 1996; Puzanov et al., 1996;

Ranson et al., 2003; Rosmaraki et al., 2001; Suzuki et al., 1997; Williams et al., 1997).

Loss-of-function studies demonstrate the importance of this cytokine in NK cell development, with IL-15-/- and IL-15 receptor α chain-/- mice exhibiting defects in NK cell lineages, which includes an absence of splenic NK cells and reduced cytolytic activity of splenocytes (Kennedy et al., 2000; Lodolce et al., 1998). In mice, as NK cell precursors progress into immature NK cells in the bone marrow, they acquire expression of the pan NK cell markers, NK1.1 and NKp46 (Figure 1.4) (Fathman et al.,

2011; Kim et al., 2002; Rosmaraki et al., 2001; Williams et al., 2000). These immature

NK cells then gain expression of receptors from the Ly49 family, followed by CD49b

(integrin α2) and CD11b (integrin αM), as they reach functional maturity (Figure 1.4)

(Fathman et al., 2011; Kim et al., 2002; Rosmaraki et al., 2001; Williams et al., 2000).

Human NK cells follow a similar pattern of development, in terms of progression through stages with distinct haematopoietic potential and function, however, their

63 expression of surface markers varies, with mature NK cells instead expressing varying levels of CD56 and CD16 (Luetke-Eversloh et al., 2013).

Figure 1.4: The development of murine natural killer (NK) cells. NK cells develop from self- renewing, lineage maker- (Lin; CD3, B220, CD11b, GR1, TER-119, NK1.1) Sca-1+ CD117+ (c-Kit) haematopoietic stem cells (HSCs) in the bone marrow, increasing their cytolytic activity and potential for cytokine production as they progress through the various stages of differentiation. Following this differentiation pathway, HSCs first differentiate into common lymphoid progenitor (CLP) cells, which give rise to all lymphoid cells, including T and B cells. CLPs then differentiate into common innate lymphoid progenitor (CILP) cells, whose haematopoietic potential is restricted to NK cells and other innate lymphoid cells (ILCs). Pre-pro NK cells, the earliest NK cell committed precursors, develop from CILPs and then subsequently differentiate into precursor NK cells, characterised by expression of CD122, a component of the interleukin (IL)-15 receptor. As precursor NK cells progress into immature NK cells, they gain expression of pan-NK cell markers, such as NK1.1 and NKp46. Immature NK cells finally differentiate into mature CD49b+ CD11b+ NK cells, which can be further subdivided into distinct populations based on expression of CD27 and KLRG1. Characteristic surface marker expression is shown for each developmental stage (Artis and Spits, 2015; Fathman et al., 2011; Serafini et al., 2015; Yu et al., 2013).

Several transcription factors have been shown to mediate NK cell development by inducing the expression of key genes at distinct stages of maturation. The processes involved in terminal NK cell differentiation are controlled by the T-box transcription factors, eomesodermin (eomes) and T-bet. Eomes drives maturation and mediates

64 induction of the Ly49 receptors and CD49b, while T-bet is essential for the stability of immature NK cells and induces the expression of sphingosine-1-phosphate receptor 5

(S1P5) (Gordon et al., 2012; Jenne et al., 2009; Townsend et al., 2004).

As NK cells mature, they down-regulate their expression of the chemoattractant receptor, C-X-C motif chemokine receptor (CXCR)4, and up-regulate their expression of S1P5, which allows their egress from the bone marrow and mobilisation into the circulation via the venous sinusoids (Bernardini et al., 2008; Mayol et al., 2011; Walzer et al., 2007). The coordination of chemoattractant receptor expression throughout maturation allows NK cells to migrate to specific sites (Bernardini et al., 2008; Mayol et al., 2011; Sciumè et al., 2011; Wald et al., 2006; Walzer et al., 2007). Expression of L- selectin (CD62L) by NK cells mediates their entry into the lymph nodes via the high endothelial venules, which express L-selectin ligands (Chen et al., 2005; Frey et al.,

1998). Meanwhile, the chemokine receptors C-C motif chemokine receptor (CCR)2,

CCR5, CXCR3, and C-X3-C motif chemokine receptor (CX3CR)1 are involved in NK cell recruitment following inflammatory stimuli. Expression of CXCR3 on NK cells allows them to home to specific organs/sites in response to C-X-C motif chemokine ligand (CXCL)10 production (Bernardini et al., 2008; Sciumè et al., 2011; Wald et al.,

2006). Interestingly, CXCL10 production has been shown to mediate homing of NK cell subsets to the uterus throughout the menstrual cycle (Sentman et al., 2004).

CXCL10 is also induced by type I IFNs (Vanguri and Farber, 1990), highlighting the importance of type I IFNs in mediating NK cell responses.

While the bone marrow is thought to be the primary site of NK cell haematopoiesis (Colucci et al., 2003; Haller and Wigzell, 1977), it has recently been determined that tissue-resident (tr)NK cell populations mature independently of circulating cNK cells via the differentiation of haematopoietic precursors locally

65 (Chantakru et al., 2002; Male et al., 2010; Sojka et al., 2014; Vacca et al., 2011;

Vosshenrich et al., 2006). The uterus possesses its own unique population of trNK cells, dubbed uNK cells, which fluctuate throughout the menstrual cycle and pregnancy

(Jones et al., 1998; Pace et al., 1989) via local proliferation of early NK progenitors

(Chantakru et al., 2002; Male et al., 2010; Vacca et al., 2011). uNK cell precursors appear to reside in secondary lymphoid tissues, such as the draining lymph nodes and spleen, and are recruited to the uterus throughout the oestrous cycle and decidualisation where they differentiate into mature uNK cells upon interaction with stromal cells and exposure to IL-15 (Allen and Nilsen-Hamilton, 1998; Chantakru et al., 2002; Vacca et al., 2011; Ye et al., 1996). uNK cells are important for reproductive processes, such as tissue remodelling and angiogenesis during decidualisation and the induction of regulatory T cells to suppress maternal immune responses toward the allogenic embryo

(Hanna et al., 2006; Vacca et al., 2008; Vacca et al., 2010), however, they have also been shown to play a role in protection against certain pathogens (Mselle et al., 2009;

Siewiera et al., 2013). Significantly, the factors that mediate the development of this functionally and phenotypically distinct lineage are currently unknown, however, the diversity in trNK cells at different sites is likely dependent on the differential expression of chemoattractant receptors at different stages of development and local signals that direct differentiation.

Importantly, type I IFNs have previously been shown to promote NK cell differentiation, proliferation, and survival (Baranek et al., 2012; Lucas et al., 2007;

Nguyen et al., 2002). Guan et al. have shown that IFNAR-/- mice exhibit fewer precursor NK cells and earlier progenitors in their bone marrow (Guan et al., 2014).

However, the total number of mature NK cells in the periphery is unaltered by IFNAR deficiency, indicating that other mechanisms are able to compensate for the reduction in

66 early NK cell progenitors seen in IFNAR-/- mice (Guan et al., 2014). Significantly,

IFNα/β signalling through STAT1 induces the expression of IL-15 by DCs (Baranek et al., 2012; Lucas et al., 2007; Nguyen et al., 2002). This response has been shown to be essential for the accumulation and survival of proliferating NK cells during murine cytomegalovirus (m/CMV) infection (Baranek et al., 2012; Nguyen et al., 2002) and following TLR stimulation (Lucas et al., 2007). These data demonstrate that type I IFNs are involved the induction of NK cell responses, both at baseline and during infection, and that the role of type I IFN signalling varies, depending on the stage of NK cell development.

1.2.3.2 Role of NK cells in infection

NK cells are capable of mediating cellular cytotoxicity and modulating the immune responses required to clear infection. The importance of their cytolytic and immunomodulatory functions in protection against both viral and bacterial infections have been demonstrated (Souza-Fonseca-Guimaraes et al., 2012). Significantly, NK cells have been shown to be vitally important for protection against cytosolic bacterial infections, such as intracellular Salmonella (Griggs and Smith, 1994), Listeria (Unanue,

1997), and Chlamydia (Jiao et al., 2011; Tseng and Rank, 1998), and viral RTIs, including HSV-2 (Ashkar and Rosenthal, 2003; Thapa et al., 2007).

The cytolytic action of NK cells is mediated by the release of pore-forming proteins and proteolytic enzymes, such as perforin and granzymes, which are stored in the NK cells’ cytoplasmic granules. Upon recognition of an infected or transformed cell,

NK cells position their granules to face the target before releasing their contents via exocytosis. Perforin then inserts itself into the membrane of the target cell and oligomerises to form a transmembrane tubule. Subsequent membrane destabilisation

67 allows granzymes and other proteases to enter the target cell and mediate programmed cell death (Keefe et al., 2005; Trapani, 1995). There are five granzymes in humans and mice, with granzymes A and B being the most common (Grossman et al., 2003).

Granzyme A induces cell death pathways by triggering the release of mitochondrial reactive oxygen species (ROS) and DNase, which causes single-stranded DNA nicks

(Chowdhury et al., 2006). Granzyme B triggers apoptosis via activation of caspases and other pro-apoptotic factors (Trapani and Sutton, 2003). Granzymes have also been shown to kill intracellular bacteria within target cells by cleaving antioxidant proteins and components of the electron transport chain, which results in the generation of ROS and oxidative damage, affecting pathogen integrity (Walch et al., 2014).

The immunomodulatory functions of NK cells are mediated by the production of cytokines, including TNF, GM-CSF, and IFNγ, and chemokines, such as CXCL10

(Souza-Fonseca-Guimaraes et al., 2012). Significantly, IFNγ is the predominant cytokine produced by activated NK cells and NK cells have been identified as the primary source of IFNγ during the earliest stages of many bacterial infections

(Rottenberg et al., 2000; Souza-Fonseca-Guimaraes et al., 2012). The production of

IFNγ by NK cells has been demonstrated to play a pivotal role in protection against both intracellular bacterial infections and RTIs, including Chlamydia (Jiao et al., 2011;

Tseng and Rank, 1998) and HSV-2 (Ashkar and Rosenthal, 2003) infections.

NK cell activity and killing ability are regulated by both the tissue microenvironment and a balance of activating and inhibitory receptors on the cell surface and their cognate ligands. These receptors recognise induced-self proteins, that are up-regulated on stressed cells; MHC-I molecules, that display self- and non-self- peptides; cadherins, which are expressed in healthy tissues; and other viral- and tumour- associated factors (Pegram et al., 2011). In mice, NK cells rely on Ly49 receptors to

68 recognise both self-proteins and microbial components presented by MHC-I, while killer-cell Ig-like receptors (KIRs) serve this function in humans. The Ly49 C-type lectin receptor family, also known as the killer cell lectin-like receptor (Klr) subfamily

A, consists of both inhibitory receptors, responsible for mediating tolerance to self-

MHC-I expressing cells (Karlhofer et al., 1992; Ljunggren and Karre, 1990), and activating receptors, responsible for recognising malignantly transformed or infected cells (Desrosiers et al., 2005; Gosselin et al., 1999; Moretta et al., 1995; Ortaldo and

Young, 2005). In many cancers and viral infections, MHC-I will be down-regulated to circumvent cytotoxic T cell-mediated killing (Ljunggren and Karre, 1990). The absence of self-MHC-I on infected or transformed target cells reduces NK cell inhibitory signals and triggers NK cell cytotoxicity (Karlhofer et al., 1992; Ljunggren and Karre, 1990).

Likewise, the down-regulation of other factors normally expressed in healthy tissues, such a cadherin, which is detected by KLRG1, reduces the threshold for NK cell activation (Ito et al., 2006). Conversely, the up-regulation of certain peptide-MHC-I complexes or other stress ligands on infected or stressed cells will be recognised by activating receptors, such as Ly49H and NKG2D, on NK cells and trigger cytotoxic and immunomodulatory functions (Desrosiers et al., 2005; Moretta et al., 1995; Ortaldo and

Young, 2005).

In addition to being essential for NK cell survival and development (Kennedy et al., 2000; Mrozek et al., 1996; Puzanov et al., 1996; Ranson et al., 2003; Suzuki et al.,

1997; Williams et al., 1997), IL-15 has also been shown to contribute to NK cell recruitment, activation, and IFNγ production during infection (Allavena et al., 1997;

Elpek et al., 2010; Guo et al., 2015; Lucas et al., 2007; Nguyen et al., 2002). IL-15 recruits NK cells by promoting their adhesion to vascular endothelium (Allavena et al.,

1997) and, importantly, has been shown to contribute to their production of IFNγ during

69 HSV-2 RTIs (Ashkar and Rosenthal, 2003). Although IL-15 is required for differentiation and proliferation of developing NK cells, other factors have also been shown to mediate the expansion of NK cells during infection (Sun et al., 2009).

In addition to IL-15, the cytokines IL-2, IL-4, IL-10, IL-12, IL-18, and IL-21 have also been shown to regulate NK cell function. These cytokines are expressed by activated myeloid cells, particularly DCs, and lymphocytes and epithelial cells, which act as accessory cells to mediate NK cell responses (Souza-Fonseca-Guimaraes et al.,

2012). These cytokines often act in concert, co-stimulating and priming for NK cell proliferation, cytokine production, and cytolytic activity.

As IL-15 and IL-2 share a common receptor chain (IL-2 receptor β chain;

CD122), NK cells are also capable of responding to IL-2. IL-2 potently induces NK cell proliferation and increases NK cell responses to IL-15 and IL-12 by up-regulating the expression of their respective receptors (Murphy et al., 1992; Wang et al., 2000). IL-12 enhances IFNγ production, perforin and granzyme B mRNA expression, and cytolytic activity of NK cells (Ferlazzo et al., 2004; Hook et al., 2005; Hyodo et al., 1999).

Significantly, IL-12 is required for protective NK cell-mediated IFNγ responses during

Salmonella typhimurium infections in vivo (Mastroeni et al., 1996). IL-12 has also been shown to induce NK cell expansion, independent of IL-15, during mCMV infections

(Sun et al., 2009). Interestingly, this response is dependent on the activation of Ly49H receptors by viral proteins (Sun et al., 2009). IL-4 has also been shown to modulate NK cell responses to receptor activation. IL-4 down-regulates the expression of the activating NK cell receptor, NKG2D, reducing NKG2D-mediated cytolytic activity

(Brady et al., 2010). IL-18 also induces IFNγ secretion by NK cells and enhances their cytolytic activity. This response is amplified by co-stimulation with IL-12 (Hyodo et al.,

1999; Takeda et al., 1998) or IL-15 (IFNγ secretion only) (Strengell et al., 2003),

70 however, due to their constitutive expression of the IL-18 receptor, NK cells are capable of producing IFNγ in response to IL-18 in the absence of these cytokines (Hyodo et al.,

1999; Takeda et al., 1998), unlike T and B cells, which require IL-12 to respond to IL-

18 (Ahn et al., 1997; Yoshimoto et al., 1998). Importantly, IL-18 responses have been shown to promote NK cell cytotoxicity during intracellular bacterial infections (Maltez et al., 2015), and NK cell activation and IFNγ production during mCMV, hepatitis C, and S. typhimurium infections (Kupz et al., 2014; Rathinam et al., 2010; Serti et al.,

2014). IL-21 also increases NK cell IFNγ production and cytolytic activity, and these responses have been shown to be augmented by co-stimulation with IL-18 or IL-15

(Brady et al., 2010; Strengell et al., 2003). Taken together, these data demonstrate that both the cytokine milieu and signals from activating and inhibitory receptors converge to determine NK cell fate.

Interestingly, however, cytolytic activity induced by IL-15 is diminished by co- stimulation with some of these cytokines, such as IL-12, IL-18, and IL-4, in vitro, promoting the maturation of NK cells to a “helper” phenotype (Brady et al., 2010), and

IL-10 has been shown to have both activating and inhibitory effects (Souza-Fonseca-

Guimaraes et al., 2012). This demonstrates how a combination of cytokines acting in concert can direct specific NK cell responses based on the requirements of the local environment. The priming of NK cells by these signals allows them to respond appropriately to other stimuli and is thought to be mediated by alterations in signalling pathways, including regulation of receptor expression and activation of downstream signalling factors, such as the STATs.

Importantly, type I IFNs are also known to play a role in mediating NK cell responses during infection. The production of IFNγ and cytolytic proteins by and the cytolytic activity of NK cells following TLR stimulation or infection with Listeria

71 monocytogenes or lymphocytic choriomeningitis virus (LCMV) have been shown to be dependent on autocrine/paracrine type I IFN signalling in DCs and their subsequent production of IL-15 (Lucas et al., 2007). This may be via IL-15-mediated up-regulation of NKG2D ligands on DCs (Andoniou et al., 2005; Jinushi et al., 2003). However, during mCMV infections, NK cell cytotoxicity elicited in response to type I IFN signalling is independent of IL-15 production (Nguyen et al., 2002). Additionally, IFNγ production by NK cells during mCMV infections is independent of type I IFN signalling, instead relying on IL-12 production and STAT4 signalling (Nguyen et al.,

2002). Conversely, type I IFNs induce protective, NK cell-mediated IFNγ responses during HSV-2 infections, independent of both IL-15 and IL-12 (Gill et al., 2011). Type

I IFNs have also been shown to directly mediate protective NK cell responses during adenoviral (Zhu et al., 2008) and vaccinia viral (Martinez et al., 2008) infections. Taken together, these data suggest that the role of type I IFN signalling in mediating NK cell responses during infection may depend the pathogen and tissues involved, and crosstalk between other cells/signalling pathways. Indeed, IFNε, which signals via IFNAR and is produced at higher levels in the female RT than the other type I IFNs, may prime for specific NK cell responses in these tissues that help protect against RTIs.

1.2.3.3 Role of NK cells in Chlamydia infections

NK cells have been shown to mediate protective responses during Chlamydia infection of both the RT and lung (Jiao et al., 2011; Tseng and Rank, 1998). Using an in vivo model of Chlamydia RTI, Tseng and Rank have shown that NK cell numbers increase in the upper RT from as early as 12 hours post infection with C. muridarum, peak at 3dpi, and reach pre-infection levels again at 10dpi (Tseng and Rank, 1998).

Importantly, this study found NK cells to be the predominant source of IFNγ early

72 during infection (Tseng and Rank, 1998). NK cell depletion diminished early IFNγ responses, leading to a shift from a Th1-dominant to a Th type 2 (Th2)-dominant immune phenotype and a delay in Chlamydia clearance (Tseng and Rank, 1998).

In co-culture experiments, C. trachomatis infection has been shown to promote the production of IFNγ by NK cells via the production of IL-18 by epithelial cells and

IL-12 by DCs (Hook et al., 2005). C. trachomatis infection has also been shown to decrease the expression of MHC-I molecules and increase the expression of the NKG2D ligand, MICA, on epithelial cells, making them susceptible to NK cell-mediated killing

(Hook et al., 2004; Ibana et al., 2012). However, NK cells collected from C. trachomatis-infected individuals exhibit a reduction in lytic ability and production of cytokines, TNF and IFNγ, during co-culture with target cells, compared to NK cells collected from healthy controls (Mavoungou et al., 1999). The authors of this study suggest that this decrease in NK cell activity may be the result of anergy, however, this reduction in NK cell responses may also represent a mechanism by which Chlamydiae evade protective immune responses. Alternatively, the reduction in NK cell activity observed in these individuals may in fact be responsible for their susceptibility to infection in the first place, as a higher frequency of infection in low responders could also lead to this correlation.

The role of NK cells in Chlamydia respiratory tract infections has also been demonstrated. NK cells have been shown to accumulate and produce IFNγ in the lung during C. muridarum infection (Jiao et al., 2011; Williams et al., 1987). Importantly,

NK cell-depleted mice exhibit increases in Chlamydia burden, neutrophilic inflammation, and weight loss during C. muridarum respiratory tract infections (Jiao et al., 2011). This increase in susceptibility to infection, inflammation, and disease was shown to correlate with a decrease in the ability of DCs to prime Th1 development (Jiao

73 et al., 2011). Importantly, NK cells from C. muridarum-infected mice were shown to stimulate DCs to produce IL-12, an important cytokine for Th1 polarisation, via the secretion of IFNγ and NKG2D signalling, in ex vivo co-culture experiments (Jiao et al.,

2011). Rottenberg et al. have also demonstrated the importance of innate IFNγ responses in protection against C. pneumoniae respiratory tract infections (Rottenberg et al., 2000). Using recombination-activating gene (RAG)-1-/- mice, which are unable to produce mature T and B cells, they show that IFNγR-/-/RAG-1-/- mice have worsened infection and decreased iNOS and IDO expression, compared to RAG-1-/- controls

(Rottenberg et al., 2000). As NK cells are believed to be the primary source of IFNγ early during many bacterial infections, these data suggest that NK cell-mediated IFNγ responses may also be involved in protection against C. pneumoniae respiratory tract infections. However, they found that, while NK cell depletion reduces IFNγ expression in the lung, NK cell-depleted mice have similar levels of Chlamydia, compared to controls, at 10dpi (Rottenberg et al., 2000). The use of RAG-1-/- mice in their NK cell depletion experiments may be responsible for these counterintuitive results, as recent studies have identified a role for RAGs in NK cell function and survival during infection (Karo et al., 2014). Additionally, perforin deficiency had no effect on C. pneumoniae infection in RAG-1-/- mice, excluding a role for NK cell cytotoxicity

(Rottenberg et al., 2000). Perforin-/- mice have also been shown to clear C. muridarum

RTIs at a similar rate to WT controls (Murthy et al., 2011; Perry et al., 1999a), suggesting that the cytolytic action of NK cells does not play a major role in protection against Chlamydia infections.

Whilst one study has shown that NK cell depletion results in an increase in susceptibility to Chlamydia infection in the vagina (delay in clearance), this study did not investigate the effects of NK cells on ascending infection in the upper RT tissues.

74 Taken together, these studies highlight the need for further investigation of the role of

NK cells in Chlamydia female RTIs in order to gain a better understanding of the mechanisms that contribute to protection/susceptibility. In particular, the role that IFNε plays in mediating protective NK cell responses during Chlamydia RTIs is yet to be determined.

1.2.4 Inflammasomes

Inflammasomes are multimeric protein signalling complexes that are key components of the innate immune system. Inflammasomes are responsible for the induction of inflammatory responses and mediating inflammatory cell death. The multimeric inflammasome complex consists of an inflammasome sensor molecule, the adaptor protein, apoptosis-associated speck-like protein containing a caspase- recruitment domain (ASC/CARD), and caspase-1 (Figure 1.5) (Fernandes-Alnemri et al., 2007; Proell et al., 2013; Vajjhala et al., 2012). Activation of the sensor molecule triggers inflammasome formation and activation of caspase-1, which subsequently mediates the activation and release of pro-inflammatory cytokines, notably IL-1β and

IL-18, as well as the induction of pyroptosis (Figure 1.5) (Fernandes-Alnemri et al.,

2007; Proell et al., 2013; Vajjhala et al., 2012).

Most inflammasome sensor molecules are members of the NLR family of PRRs, which are capable of detecting PAMPs, associated with infection, and/or DAMPs, released during cellular injury (Takeuchi and Akira, 2010). NLRs are large multi- domain proteins that comprise of LRRs at their C-termini, which are responsible for the recognition of PAMPs/DAMPs, a central NOD/NACHT domain, and an N-terminal effector domain, which recruits the adaptor proteins that subsequently activate downstream signalling molecules (Figure 1.5 A-C) (Ting et al., 2008). NLR family

75 members are subcategorised by their various N-terminal domains (Ting et al., 2008).

The largest group of NLR proteins is the pyrin domain-containing subfamily, consisting of NLRPs 1-14 (Grenier et al., 2002; Stutz et al., 2009; Ting et al., 2008). Other groups include the CARD-containing NLR (NLRC) subfamily, which consists of the NOD receptors, NOD1 [NLRC1] and NOD2 [NLRC2], and NLRC4 (IPAF), and the baculoviral inhibitory repeat (BIR)-like domain-containing NLR apoptosis inhibitory protein (NAIP) subfamily (Stutz et al., 2009; Ting et al., 2008). Several NLR family members, including NLRP1, NLRP3, and NLRC4, as well as a number of non-NLR

PRRs, such as absent in melanoma 2 (AIM2) and RIG-I, are capable of forming inflammasomes (Figure 1.5). Of these inflammasomes, NLRP3 is the best described in the context of protection against infection and the pathogenesis of a wide number of human inflammatory diseases owing to its important role in mediating pro- inflammatory IL-1β responses.

76 A B C D E

Figure 1.5: Activation and assembly of the canonical inflammasomes. The canonical inflammasome complexes are made up of inflammasome sensor molecules, apoptosis-associated speck-like protein containing a caspase-recruitment domain (ASC/CARD), and caspase-1. Activation of inflammasome sensor molecules trigger oligomerisation and assembly of inflammasome complexes. (A) Assembly of the nucleotide-binding oligomerisation domain (NOD)- and leucine-rich repeat (LRR)-containing receptor (NLR) family CARD-containing subfamily member 4 (NLRC4) inflammasome, is triggered by exposure to components of the type III secretory system (T3SS) and flagellin via detection by baculoviral

77 inhibitory repeat (BIR)-like domain-containing molecules from the NLR family, apoptosis inhibitory protein (NAIP) subfamily. (B) The pyrin domain (PYD)-containing NLR subfamily member, NLRP1, is activated by anthrax lethal toxin. (C) NLRP3 is activated by a wide variety of agonists, including extracellular adenosine triphosphate (ATP), ion flux, crystalline molecules, and pore-forming bacterial toxins. (D) Absent in melanoma 2 (AIM2) is activated by cytosolic double stranded (ds)DNA, of either host or microbial origin. (E) Retinoic acid-inducible gene-I (RIG-I) is activated by dsRNA. Inflammasome activation triggers recruitment of the adaptor molecule, ASC, either via their PYDs or CARDs. ASC then recruits pro-caspase-1 via its CARD. NLRC4, NLRP1, and RIG-I are also capable of directly interacting with pro-caspase-1, via their CARDs. Inflammasome assembly brings pro-caspase-1 molecules in close proximity to one another, triggering their activation via autocatalytic cleavage into 20- kDa (p20) and 10-kDa (p10) subunits. The p20 and p10 subunits then form the tetrameric active enzyme. Active caspase-1 subsequently mediates the maturation of pro-inflammatory cytokines of the interleukin (IL)-1 family, such as IL-1β and IL-18, via proteolytic cleavage of their pro-forms, as well as the induction of pyroptosis via cleavage of proteins, such as gasdermin D. Adapted from (Dagenais et al., 2012; Man and Kanneganti, 2016; Vanaja et al., 2015).

1.2.4.1 Inflammasome activation

As inflammasomes are capable of inducing potent inflammatory responses, they require tight regulation in order to avoid unnecessary/aberrant inflammation. As such, two signals are required for inflammasome activation. During infection, PAMP:PRR binding- and pro-inflammatory cytokine signalling prime for inflammasome assembly by promoting the transcription of individual inflammasome components, such as

NLRP3 and caspase-1, and pro-forms of the IL-1 family cytokines, such as pro-IL-1β, via NF-κB activation (Bauernfeind et al., 2009; He et al., 2013; Hiscott et al., 1993;

Schindler et al., 1990). PAMP:PRR signalling also post-translationally modifies inflammasome components, such as NLRP3 and ASC, through de-ubiquitination, allowing their oligomerisation and assembly (Juliana et al., 2012; Lopez-Castejon et al.,

2013; Py et al., 2013). Once activated, IL-1β can perpetuate a self-sustaining response via IL-1 receptor (IL-1R) activation and subsequent NF-κB signalling (Bauernfeind et al., 2009; Ikejima et al., 1990). However, IL-1β requires inflammasome-mediated

78 proteolytic cleavage for its activation and release (Thornberry et al., 1992) and for this to occur, the preformed inflammasome complex requires a second activation signal.

The second step of inflammasome activation is mediated by the inflammasome sensor molecule upon recognition of PAMPs and/or DAMPs, which triggers the assembly and activation of the inflammasome complex (Sutterwala et al., 2014). Often, infection is capable of providing both signals for inflammasome activation. NLRC4 is activated by PAMPs, such as components of the type III secretory system and flagellin

(Figure 1.5 A) (Vance, 2015). AIM2 is activated by cytosolic double stranded (ds)DNA of either microbial or host origin (Figure 1.5 D) (Hornung et al., 2009). NLRP3 is activated by a variety of DAMPs, including extracellular ATP, and phagocytosed crystalline molecules (Figure 1.5 C) (Schroder and Tschopp, 2010; Sutterwala et al.,

2014). Upon activation, the NLRP3 and AIM2 inflammasomes oligomerise and recruit the adaptor molecule, ASC via their pyrin domains (Figure 1.5 C & D) (Agostini et al.,

2004; Fernandes-Alnemri et al., 2007), while the NLRP1, NLRC4, and RIG-I inflammasomes interact with caspase-1 directly via their CARD domains (Figure 1.5 A,

B, & E). Prior to stimulation, caspase-1 is present in its inactive pro-form (pro-caspase-

1). Activation and assembly of the inflammasome complex and recruitment of pro- caspase-1 by ASC/CARD brings pro-caspase-1 molecules within close proximity of one another, facilitating their autocatalytic cleavage into 20-kDa (p20) and 10-kDa (p10) subunits (Figure 1.5) (Thornberry et al., 1992). The p20 and p10 subunits then form the tetrameric active enzyme (Figure 1.5) (Wilson et al., 1994).

Active caspase-1 mediates the maturation of a number of pro-inflammatory cytokines of the IL-1 family (Gu et al., 1997; Martinon et al., 2002; Thornberry et al.,

1992). These include pro-IL-1β and pro-IL-18, which are activated, and pro-IL-33 which is inactivated, by caspase-1-mediated proteolytic cleavage into mature IL-1β, IL-

79 18 and IL-33, respectively, and subsequently released via non-classical secretion pathways, such as secretion through caspase-1-dependent pores, microvesicle shedding, and lysosome exocytosis (Bergsbaken et al., 2009; Dinarello, 2009; Gu et al., 1997;

Martinon et al., 2002).

IL-1β responses are important for the induction of a range of anti-microbial processes that control infection, however, they are also responsible for the aberrant inflammatory responses that drive pathology in both infection- and non-infection- associated diseases (Prantner et al., 2009). IL-1β is an important mediator of inflammatory responses, such as infiltration of innate immune cells from the circulation, fever, lowered pain threshold, and vasodilation (Dinarello, 2009). IL-1β signalling induces these innate processes via the up-regulation of adhesion molecules, chemokines, and effector cytokines, such as iNOS, type 2 phospholipase A, and cyclooxygenase 2 (COX-2), which mediate the synthesis of NO, platelet activating factor, and prostaglandin-E2 (PGE2), respectively (Dinarello, 2009). Unlike IL-1β, IL-

18 mRNA and pro-IL-18 are constitutively expressed (Marshall et al., 1999; Puren et al., 1999). IL-18 acts as a costimulatory factor for IL-2, IL-12, and IL-15 to induce IFNγ responses (Dinarello, 2009; Kupz et al., 2014; Okamura et al., 1995; Shibatomi et al.,

2001). Conversely, IL-33, which is inactivated by inflammasome signalling, promotes

Th2, mast cell, and ILC responses (Ali et al., 2007; Dinarello, 2009; Schmitz et al.,

2005). Therefore, the inflammasome, through its ability to modulate the activity of these cytokines, not only plays an important role in mediating early inflammatory responses induced by infection, but also in shaping the longer term immunological outcomes orchestrated by adaptive immune responses (Sims and Smith, 2010).

Active caspase-1 also mediates an inflammatory form of programmed cell death known as pyroptosis. The mechanism, characteristics, and outcome of pyroptosis are

80 distinct from those of other forms of programmed cell death (Bergsbaken and Cookson,

2007; Fink and Cookson, 2006). Pyroptosis occurs independently of pro-apoptotic caspases and is characterised by osmotic lysis, rupture of the plasma membrane, and release of pro-inflammatory intracellular contents (Fink and Cookson, 2006). Caspase-1 mediates these processes via the cleavage of gasdermin D (He et al., 2015) and formation of plasma membrane pores (Fink and Cookson, 2006). DNA cleavage, cytoskeletal destruction, and degradation of metabolic enzymes are also features of pyroptosis, however, they are not essential for cell lysis (Bergsbaken et al., 2009).

Whether or not a cell undergoes caspase-1-mediated cell death upon inflammasome activation is thought to be determined by both the type of cell and a balance between the level of inflammasome activation and the regulation of cytosolic caspase-1 activity by mechanisms such as autophagy and secretion (Gurcel et al., 2006a; Schroder and

Tschopp, 2010; Siegel, 2006). Significantly, pyroptosis has been shown to be important for the control of many intracellular infections (Case et al., 2009; Fink et al., 2008).

Importantly, caspase-1 has also been shown to be activated via a non-canonical inflammasome activation pathway. Type I IFN signalling has been shown to play a role in this activation pathway and, importantly, ASC-mediated caspase-1 activation and subsequent IL-1β secretion and pyroptosis have been shown to be dependent on type I

IFN responses during cytosolic bacterial infections (Fernandes-Alnemri et al., 2010;

Henry et al., 2007; Rathinam et al., 2010; Rathinam et al., 2012). Type I IFN signalling appears to mediate the activation of the NLRP3 inflammasome by inducing the expression of caspase-4 (previously caspase-11) (Henry et al., 2007; Malireddi and

Kanneganti, 2013), however, how caspase-4 activates caspase-1 via NLRP3 is not yet fully understood. Sollberger et al. have shown that caspase-4 is required for optimal

NLRP3 and AIM2 inflammasome activation and IL-1β secretion following UVB

81 irradiation or ATP, monosodium urate, or poly(dA:dT) stimulation in keratinocytes and that active caspase-4 is capable of either directly or indirectly processing caspase-1

(Sollberger et al., 2012). They also demonstrate that caspase-4 physically interacts with caspase-1, but not ASC, NLRP1, NLRP3, or AIM2 (Sollberger et al., 2012).

Additionally, Rathinam, et al. have shown that caspase-4 is required for the processing of caspase-1 downstream of NLRP3 inflammasome activation and assembly upon stimulation with Gram-negative bacteria (Rathinam et al., 2012). This suggests that caspase-4 acts downstream of NLRP3 to increase the efficiency of caspase-1 activation.

However, Broz et al. found that the formation of ASC foci, a measure of NLRP3/ASC complex assembly, depends on caspase-4 expression during S. typhimurium infection

(Broz et al., 2012), indicating that caspase-4 may also regulate inflammasome assembly further upstream. Caspase-4 is activated by the lipid A moiety of LPS (Hagar et al.,

2013; Kayagaki et al., 2013) and has been found to mediate a number of caspase-1- independent functions, including phago-lysosomal fusion and cell lysis (Akhter et al.,

2012; Kayagaki et al., 2011). Interestingly, activation of NLRC4 by caspase-4 has been shown to be the result of phago-lysosomal fusion (Akhter et al., 2012). Caspase-4- mediated phago-lysosomal fusion triggers the release of flagellin into the cytosol, allowing their interaction with and activation of NLRC4 (Akhter et al., 2012). As such, similar mechanisms may also be involved in type I IFN-induced caspase-4-mediated activation of NLRP3.

Conversely, type I IFNs have also been shown to suppress IL-1 expression in response to C. albicans infection via STAT1-induced IL-10 expression and inhibition of the NLRP3 inflammasome (Guarda et al., 2011). This suggests that the role of type I

IFN signalling in the inflammasome/caspase-1/IL-1β axis is complex and highlights the need for further investigation to improve our understanding of the crosstalk between

82 these pathways. Significantly, it is not known how IFNε affects inflammasome responses in the female RT.

1.2.4.2 Role of inflammasomes in Chlamydia infections

NLRP3 is the best characterised caspase-1-activating inflammasome and, importantly, activation of caspase-1 in epithelial cells (Abdul-Sater et al., 2009) and macrophages (Abdul-Sater et al., 2010; Prantner et al., 2009; Shimada et al., 2011) in response to infection with a number of Chlamydia spp. in vitro has been shown to be dependent on the NLRP3 inflammasome. NLRP3 can be activated by a wide variety of stressors, including live pathogens, pore forming bacterial toxins, extracellular ATP (via the cell surface receptor, P2X7R), hyaluronan, glucose, uric acid, amyloid-β plaques, phagocytosed crystalline molecules (monosodium urate crystals, asbestos, silica and alum), skin irritants, and UVB radiation (Schroder and Tschopp, 2010; Sutterwala et al.,

2014).

How all these dissimilar agonists activate NLRP3 is still open for debate. There is evidence that suggests NLRP3 agonists induce common downstream effects which are then sensed by NLRP3. These include potassium ion (K+) efflux, increases in intracellular calcium, generation of mitochondrial ROS, mitochondrial dysfunction, release of mitochondrial DNA and the inner mitochondrial membrane-specific lipid, cardiolipin, colocalisation of NLRP3 with the mitochondria (and ASC), and release of cathespins from the lysosome (Sutterwala et al., 2014). Importantly, previous reports have shown that K+ efflux and membrane depolarisation can lead to ROS production and activate the NLRP3 inflammasome (Abdul-Sater et al., 2009; DeCoursey et al.,

2003).

83 Several of these pathways are thought to contribute to NLRP3 inflammasome activation in response to infection. A variety of bacterial toxins can activate NLRP3 by forming pores in the plasma membrane and disrupting cellular ion balance (Gurcel et al., 2006b; Mariathasan et al., 2006). It has also been demonstrated that extracellular

ATP from microbial pathogens can trigger K+ efflux and subsequent activation of the

NLRP3 inflammasome via the P2X7 receptor (Franchi et al., 2007). Additionally, the escape of live bacteria from the lysosome, which triggers the release lysosomal enzymes into the cytosol, and the release of prokaryotic mRNA during the lysosomal degradation of bacteria have been shown to activate NLRP3 (Sander et al., 2011; Vladimer et al.,

2013). ROS production and mitochondrial dysfunction have also been demonstrated to play important roles in the activation of NLRP3 during bacterial infections (Abdul-Sater et al., 2010; Shimada et al., 2012).

Importantly, both C. trachomatis and C. muridarum have been shown to trigger activation of the NLRP3 inflammasome and IL-1β secretion in a process requiring K+ efflux and ROS production (Abdul-Sater et al., 2009; Abdul-Sater et al., 2010). How

Chlamydia induce these responses may depend on the cell type involved, as although

Chlamydia protein synthesis and the type III secretory system are required for ROS production and caspase-1 activation in response to infection in cervical epithelial cells

(Abdul-Sater et al., 2009), in macrophages, caspase-1 activation and IL-1β secretion occur independently of these processes (Prantner et al., 2009).

The precise roles of the inflammasome/caspase-1/IL-1β signalling axis in

Chlamydia infections and infection-associated pathology are currently unclear. Indeed, in loss-of-function studies, NLRP3, ASC, caspase-1, and IL-1β have been demonstrated to have contradictory effects on infection and the development of pathology.

84 IL-1β-/- mice have a significant delay in the clearance of C. muridarum from the

RT (Prantner et al., 2009). However, whilst IL-1β is important for control of Chlamydia infections, IL-1β-/- mice are also less likely to develop oviduct pathology, indicating that it may also mediate the aberrant inflammatory responses that drive pathology (Prantner et al., 2009). Nevertheless, the kinetics of these IL-1β responses may be important in determining the outcome of infection, as other studies demonstrate that early IL-1β expression is essential for protection against C. pneumoniae respiratory tract infections and, by limiting Chlamydia growth early, prevents the development of aberrant inflammatory responses and associated tissue damage later (Shimada et al., 2011).

Caspase-1 activation has also been shown to have several, seemingly conflicting effects during Chlamydia infection. Abdul-Sater et al. have demonstrated that caspase-1 activation in epithelial cells contributes to increased Chlamydia growth in vitro (Abdul-

Sater et al., 2009). The authors suggest that this is due to an increase in caspase-1- induced lipid metabolism (Abdul-Sater et al., 2009). However, caspase-1-/- mice are more susceptible to C. pneumoniae respiratory tract infections and have defective innate immune responses, including reduced iNOS and delayed IFNγ and IL-6 production

(Shimada et al., 2011). The protective effects of caspase-1 in the lung appear to be mediated by IL-1β activation, as the administration of recombinant IL-1β rescues these mice from fatal infection (Shimada et al., 2011). In contrast, Chlamydia levels in the vagina during a murine model of C. trachomatis RTI are comparable between caspase-

1-/- mice and WT controls (Cheng et al., 2008; Igietseme et al., 2013). Furthermore, both caspase-1 deficiency and the inhibition of caspase activity protect against the development of Chlamydia-induced infertility (Cheng et al., 2008; Igietseme et al.,

2013). However, these studies did not assess infection in the upper RT or the production of IL-1β (Cheng et al., 2008; Igietseme et al., 2013). Taken together, these studies

85 suggest that caspase-1 activation may have different effects on infection and pathology depending the Chlamydia species, cell types and/or tissues involved.

The NLRP3 inflammasome mediates caspase-1 activation and the production of

IL-1β by macrophages in response to infection with a number of Chlamydia spp. in vitro (Abdul-Sater et al., 2010; Prantner et al., 2009; Shimada et al., 2011). This response relies on TLR2/MyD88 signalling, which provides the primary signal for inflammasome activation (Abdul-Sater et al., 2010; Prantner et al., 2009; Shimada et al.,

2011). However, despite the requirement for NLRP3 in Chlamydia-induced macrophage

IL-1β production, NLRP3-/- and ASC-/- mice have been shown to have normal levels of

IL-1β in their genital secretions from as early as 3 days following IVAG C. muridarum infection (Nagarajan et al., 2012). Additionally, whilst ASC-/- mice display delayed clearance of C. muridarum from their RTs, they have no change in the development of pathology compared to WT controls (Nagarajan et al., 2012). These changes in clearance may be the result of reduced IL-18 responses, rather than changes in IL-1β activation (Nagarajan et al., 2012).

Together, these data highlight the need for further investigation of the inflammasome/caspase-1/IL-1β signalling axis in the induction of both protective and detrimental immune responses during Chlamydia RTIs in order to better understand the mechanisms of protection against infection and the development of pathology in the female RT. Significantly, since most of the studies on the role of inflammasome responses in Chlamydia infections have been conducted in mice that are deficient in inflammasome-associated factors throughout the entire time-course of infection, studies are required in order to delineate the protective versus pathological effects of inflammasome-mediated responses in the early versus the later stages of infection.

Furthermore, whilst a number of studies report roles for the NLRP3 inflammasome,

86 more studies are required to elucidate the potential importance of other inflammasomes

(e.g. AIM2 (Finethy et al., 2015)) during Chlamydia infections. In particular, whether

IFNε affects inflammasome-mediated IL-1β responses in the female RT and whether these responses play a role in IFNε-mediated protection against Chlamydia RTIs requires investigation.

87 1.3 PhD Studies

Chlamydia is the world’s most common bacterial STI and frequently causes serious female RT complications, including PID, infertility, and ectopic pregnancy. The socio-economic costs of these Chlamydia-associated diseases are a significant global health problem. Whilst Chlamydia infections are treatable with antibiotics, many are asymptomatic and so remain undiagnosed and untreated. This allows for the infection to persist and cause inflammation-induced damage to the delicate tissues of the upper RT, resulting in the pathogenesis of Chlamydia-associated female RT disease. Despite many promising advances, there are currently no vaccines or immune-targeted therapies available for the prevention/treatment of Chlamydia RTIs and associated immunopathology. An improved understanding of the immune processes that help mediate effective clearance of infection versus those that induce immunopathology may help inform novel therapeutic targets for the development of much needed therapies.

In pioneering studies conducted in collaboration with Prof Hertzog et al., we have demonstrated that IFNε, a novel type I IFN that is exclusively and constitutively expressed at high levels in the female RT, protects against Chlamydia RTIs from the earliest stages of infection. However, how IFNε protects against infection is not yet fully understood.

The studies conducted throughout my PhD and described hereafter in this thesis were designed to determine the innate mechanisms that underpin how IFNε mediates protection against the earliest stages (3dpi) of Chlamydia RTI using female WT and

IFNε-/- mice and a well-established murine model of C. muridarum infection. Using these models, I performed three novel studies that show that IFNε mediates a number of key innate responses in the upper female RT during the earliest stages of Chlamydia

88 infection and provide evidence that these responses play important roles in IFNε- mediated protection against Chlamydia RTIs.

In the first study, I performed a series of experiments to gain a better understanding of how oestradiol and progesterone affect IFNε expression in the female

RT and determine the effects of these hormones on Chlamydia infection in both WT and IFNε-/- mice. I also performed experiments to determine whether exogenous IFNε administration could be used therapeutically to inhibit Chlamydia infection of the female RT. Importantly, I performed preliminary flow cytometric and genome-wide gene expression microarray analyses on uterine tissue from WT and IFNε-/- mice to identify key immune cells and molecular pathways that may underpin IFNε-mediated protection against Chlamydia infection in the upper female RT (Chapter 2). Findings from these initial analyses were used to inform the investigations described in subsequent studies.

In the second study, a more comprehensive investigation of the effects of IFNε on

NK cells was conducted in order to better understand the role of IFNε-induced NK responses in mediating protection against Chlamydia RTIs (Chapter 3).

In the third study, I show that IFNε primes inflammasome/caspase-1/IL-1β responses in the female RT during Chlamydia infection and that this may play an important role in IFNε-mediated protection against Chlamydia RTIs (Chapter 4).

89 : Characterisation of Chlamydia infection

and innate responses in the female RT in IFNε-/-

mice

2.1 Abstract

C. trachomatis is a common STI that frequently causes severe female RT sequelae. However, there are currently no vaccines or immune-targeted therapies available for the prevention/treatment of Chlamydia RTIs due to the complexity of the immune processes involved in both their clearance and immunopathology. As such, an improved understanding of the immune processes that mediate clearance versus those that induce pathology is required. Interestingly, susceptibility to Chlamydia infections and their associated pathologies is regulated by the female sex hormones, oestradiol and progesterone, with increased incidence of infection and onset of Chlamydia-induced pathology observed when progesterone is dominant. In previous studies, recently published in Science (Fung et al., 2013), we showed that IFNε is constitutively expressed in the female RT, fluctuates throughout the oestrous cycle, and plays an important role in protecting against Chlamydia infections from the earliest stages of infection. To elucidate role of IFNε in hormonal regulation of the immune response, I examined the effects of IFNε deficiency on infection following either oestradiol or progesterone pre-treatment, and to identify the mechanisms of IFNε-mediated protection, I assessed the recruitment of immune cells to, and the expression patterns of genes in, the female RTs of C. muridarum- and sham-infected WT and IFNε-/- C57BL/6 mice, using quantitative polymerase chain reaction (qPCR), flow cytometric, and whole-genome microarray-based analyses.

90 I show that, although IFNε expression is up-regulated by oestradiol pre-treatment,

IFNε deficiency has no effect on resistance to infection in oestradiol-pre-treated mice, suggesting that increased IFNε does not account for the increase in protection against infection observed when oestrogen levels are high. Nevertheless, I show that both endogenous and exogenous IFNε protect against Chlamydia infections in progesterone- pre-treated mice.

I show that progesterone-pre-treated IFNε-/- mice have significantly fewer NK cells in their upper RTs early during infection, compared to Chlamydia-infected WT controls. Additionally, I show that IFNε uniquely regulates the expression of 744 genes at baseline and 802 genes during Chlamydia infection, and universally regulates the expression of 61 genes regardless of infection status. Significantly, the majority of these dysregulated transcripts are down-regulated during IFNε deficiency, particularly during infection, and pathway analysis revealed that many are involved in immune processes. I demonstrate that transcripts associated with leukocyte haematopoiesis, infiltration, and communication, including NK cell signalling pathways, are down-regulated in IFNε-/- mice at baseline. I also show that a number of pathways associated with innate immune responses, such as IRF activation and PRR signalling, are down-regulated in

Chlamydia-infected IFNε-/- mice. Significantly, IL-1β was identified as a potential key regulator of many of the transcripts dysregulated in IFNε-/- mice during infection.

Interestingly, I show that several metabolic pathways are also dysregulated by IFNε deficiency, highlighting the intimate relationship between host metabolism and defence.

The findings illustrated in this chapter demonstrate that IFNε plays an important role in protecting the female RT against Chlamydia infection during progesterone- mediated susceptibility, but oestrogen mediates protection against infection through

IFNε-independent mechanisms. Significantly, I show that IFNε plays an important role

91 in mediating NK cell accumulation as well as regulating the expression of a wide variety of genes potentially associated with IL-1β responses during Chlamydia infection in the female RT.

92 2.2 Introduction

C. trachomatis is the world’s most common sexually transmitted bacterial infection and the most common National Notifiable Disease in Australia (Newman et al., 2010; World Health Organization, 2001; World Health Organization, 2008). C. trachomatis frequently causes severe RT sequelae in women, such as PID, tubal infertility, and ectopic pregnancy. Significantly, 50-90% of all C. trachomatis infections are asymptomatic (Nelson and Helfand, 2001; Risser et al., 2005) and so, whilst curable, they often remain untreated for years, leading to prolonged Chlamydia-induced inflammatory responses and permanent immunopathological damage to the RT (Black,

1997; Nelson and Helfand, 2001). Additionally, the development of Chlamydia vaccines has been largely unsuccessful owing to the difficulty in designing those that induce immune responses that clear infection but do not lead to the tissue damage that causes disease (Darville and Hiltke, 2010). This highlights the need for an improved understanding of the factors that lead to clearance versus those that mediate immunopathology in order to facilitate the development of more effective preventative strategies.

Upon infection with Chlamydia, epithelial cells rapidly produce IL-1 which triggers an inflammatory cascade, leading to the secretion of cytokines, such as IL-6,

IL-8, and GM-CSF (Rasmussen et al., 1997). These cytokines then mediate the recruitment and activation of inflammatory cells to the RT. Clearance of infection is associated with early infiltration of large numbers of neutrophils, followed by modest numbers of macrophages, then CD4+ T cells and B cells in the later stages of infection

(Berry et al., 2004; Morrison et al., 1995). However, the release of proteases, clotting factors, and growth factors by infected epithelial cells and infiltrating inflammatory cells, which contribute to the induction of an antimicrobial state in this site, are also

93 responsible for the tissue damage that causes disease (Darville and Hiltke, 2010).

Consistent with the role of IL-1 signalling in orchestrating many of the inflammatory immune responses to Chlamydia, IL-1R-/- mice exhibit reduced neutrophilic inflammation, increased bacterial load, delayed clearance, and reduced oviduct pathology during C. muridarum RTIs (Nagarajan et al., 2012). Furthermore, increased production of the pro-inflammatory cytokines, IL-1β, IL-6, and IL-8, which are associated with the chemoattraction of neutrophils and other inflammatory cells, has been shown to correlate with an increased risk of reinfection and incidence of infertility in women (Agrawal et al., 2009), suggesting that these inflammatory cells may play a key role in pathogenesis.

Neutrophils are capable of killing accessible EBs and play an important role in the clearance of infection (Darville and Hiltke, 2010), however, they have also been shown to contribute to pathogenesis, with the level of neutrophilic inflammation in the oviducts of Chlamydia-infected mice directly correlating with the development of hydrosalpinx, and neutropenic mice exhibiting a reduced rate of oviduct pathology (Lee et al., 2010a;

Shah et al., 2005). On the other hand, CD4+ T cells and IFNγ responses have been associated with efficient clearance of Chlamydia and reduced pathology. Importantly, in mouse models, the resolution of Chlamydia RTIs has been shown to be dependent on

Th1 responses, such as IL-12 expression, CD4+ T cell influx, and IFNγ production and signalling (Cotter et al., 1997; Johansson et al., 1997a; Morrison et al., 1995; Morrison et al., 2000; Perry et al., 1997). Additionally, increased expression of IFNγ and IL-12 by cervical mucosal cells and peripheral lymphocytes in Chlamydia seropositive women correlates with reduced incidence of fertility disorders, PID, and recurrent infections

(Agrawal et al., 2009; Cohen et al., 2005; Debattista et al., 2002a). NK cells have been shown to contribute to the clearance of Chlamydia via the induction of these protective

94 responses, with NK cell-depleted mice exhibiting reduced IFNγ and Th1 responses and delayed clearance of Chlamydia RTIs (Tseng and Rank, 1998).

Classical type I IFNs have also been implicated in the induction of both protective and detrimental processes during Chlamydia infections. IFNα and β have been shown to promote the expression of iNOS (Devitt et al., 1996), which protects against Chlamydia by generating microbicidal NO, and IDO (Carlin and Weller, 1995), which limits

Chlamydia growth by catabolising tryptophan, during Chlamydia infections in vitro.

These type I IFNs also prime cells to respond to protective factors, such as IFNγ and IL-

18 (Freudenberg et al., 2002; Gough et al., 2010). However, these responses do not translate to protection against Chlamydia infections in vivo, as IFNAR-/- mice exhibit improved clearance and reduced pathology during Chlamydia RTIs, due to a reduction in IFNβ-mediated inhibition of adaptive Th1 immune response development (Jayarapu et al., 2009; Nagarajan et al., 2008). This suggests that the relationship between type I

IFNs and Chlamydia is complex and is likely dependent on the type I IFN involved and the kinetics of IFN expression.

Immune responses in the female RT are tightly regulated by changes in sex hormone levels throughout the menstrual/oestrous cycle in order to facilitate reproductive processes (Mor and Cardenas, 2010; Quayle, 2002). This also leads to changes in susceptibility to a number of infections (Gallichan and Rosenthal, 1996; Ito et al., 1984; Kita et al., 1991; Sweet et al., 1986). Studies have shown that the female sex hormone, progesterone, increases the risk of establishing Chlamydia RTIs (Baeten et al., 2001; Gallichan and Rosenthal, 1996; Ito et al., 1984; Kaushic et al., 2000;

Morrison and Caldwell, 2002; Sweet et al., 1986). Significantly, women taking hormonal contraceptives are more susceptible to Chlamydia, with the strongest effect observed in those taking progesterone only-containing contraceptives (Baeten et al.,

95 2001; Morrison et al., 2009). In preliminary studies, we show that the novel type I IFN,

IFNε, is constitutively expressed in the female RTs of both humans and mice and its expression fluctuates throughout the menstrual/oestrous cycle (Fung et al., 2013). This suggests that it may play a role in priming for immune responses to RTIs (Fung et al.,

2013). Interestingly, unlike other type I IFNs, IFNε appears to protect against

Chlamydia RTIs, with IFNε-/- mice exhibiting increased Chlamydia burden and delayed clearance of infection (Fung et al., 2013). Importantly, these changes occur from the earliest stages of infection, suggesting that IFNε mediates its protective effects through the modulation of key innate responses (Fung et al., 2013).

In this chapter, I sought to identify the role of IFNε in hormone-regulated protective responses to Chlamydia in the female RT early during infection. I also examined the effect of IFNε on immune cell profiles and gene expression patterns in the upper RT using broad flow cytometric and whole-genome microarray-based gene expression analyses in order to elucidate the potential mechanisms of IFNε-mediated protection against Chlamydia RTIs. Here, I demonstrate that IFNε expression is regulated by the hormones, progesterone and oestradiol, and confers protection against

Chlamydia infections during progesterone-mediated susceptibility. However, I also demonstrate that the high levels of IFNε expression observed during oestradiol dominance do not fully account for oestradiol-mediated resistance to infection.

Additionally, I demonstrate that recombinant (r)IFNε can be used therapeutically to inhibit Chlamydia RTI in susceptible, progesterone-pre-treated mice. Using flow cytometric and microarray-based analyses as discovery tools, I show that IFNε deficiency leads to alterations in immune cell recruitment during infection and that these changes correlate with the dysregulation of genes associated with key molecular pathways, both at baseline and during infection. Specifically, I identify potential roles

96 for NK cells and inflammasome/IL-1β signalling pathways in IFNε-mediated responses to Chlamydia. These findings were then used to inform the investigations described in

Chapters 3 and 4.

97 2.3 Methods

2.3.1 Ethics statement

All animal procedures used in this study were performed in accordance with the recommendations set out in the Australian code of practice for the care and use of animals for scientific purposes issued by the National Health and Medical Research

Council (Australia). All protocols were approved by the University of Newcastle

Animal Care and Ethics Committee.

2.3.2 Chlamydia muridarum female RTI

Adult (6-8 weeks old) female WT or IFNε-/-, C57BL/6 mice were pre-treated with 2.5mg DMPA (Depo-Provera; Pfizer, NY, USA) or 0.5mg oestradiol (Sigma-

Aldrich, Castle Hill, NSW, Australia) subcutaneously (SC) to synchronise their oestrous cycles. The induction of di-oestrus or oestrus by progesterone or oestradiol administration, respectively, was confirmed by analysing the cellular composition of vaginal lavage fluid (Wood et al., 2007). Seven days later, mice were infected IVAG with 5 x 104ifu C. muridarum (ATCC VR-123) in 10μL sucrose-phosphate-glutamate buffer (SPG; 10mM sodium phosphate [pH 7.2], 0.25M sucrose, 5mM L-glutamic acid) or sham-infected with SPG alone under ketamine:xylazine anaesthesia

(80mg/kg:5mg/kg administered intraperitoneally [IP]; Ilium Ketamil® and Ilium

Xylazil-20®; Troy Laboratories, Glendenning, NSW Australia), as described previously

(Asquith et al., 2011). Mice were sacrificed by sodium pentobarbital (Lethabarb;

Virbac, Milperra, NSW, Australia) overdose at 3dpi and tissues collected for the analysis of infection and flow cytometric and microarray analyses.

98 2.3.3 In vivo administration of recombinant (r)IFNε

In order to assess the effects of administration of rIFNε on Chlamydia infection, progesterone-pre-treated WT mice were administered 0.2, 2, or 4μg rIFNε (2.1 x 105

IU/mg; provided by Prof. Paul Hertzog, Monash University and the Hudson Institute of

Medical Research, Melbourne, Australia) in 20μL sterile phosphate buffered saline

(PBS) and WT and IFNε-/- control mice were administered PBS alone IVAG under ketamine:xylazine anaesthesia 6 hours prior to infection (Figure 2.1). Purity of rIFNε was assessed by the absence of non-IFN bands on Coomassie-stained SDS-PAGE gels and chromatography traces. Mice were sacrificed by sodium pentobarbital (Lethabarb;

Virbac) overdose at 3dpi and tissues collected for the analysis of infection and flow cytometric analyses (Fung et al., 2013).

Figure 2.1: In vivo administration of recombinant interferon (r/IFN)ε prior to Chlamydia muridarum female reproductive tract infection (RTI). C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and 6 hours prior to intravaginal (IVAG) infection with C. muridarum, treated with 0.2, 2, or 4µg rIFNε or phosphate buffered saline (PBS) vehicle control IVAG. Mice were sacrificed at 3dpi and bacterial load in vaginal lavage fluid determined via qPCR and comparison to standards of known concentrations of C. muridarum (inclusion forming units [ifu]) to assess the effects of exogenous IFNε on infection in the female reproductive tract (RT).

99 2.3.4 Total RNA extraction and bioanalysis

Uterine horn tissue was harvested from mice, immediately placed in RNAlater®

(Thermo Fisher Scientific, Scoresby, VIC, Australia) and stored at 4°C overnight, then stored at -20°C until RNA extraction performed for subsequent real-time qPCR or microarray analyses.

Total RNA was extracted from uterine tissue using TRIzol® Reagent (Thermo

Fisher Scientific) according to the manufacturer’s instructions. Briefly, uterine horn tissue was homogenised in TRIzol® using a Tissue-Tearor (BioSpec Products,

Bartlesville, OK, USA) and cleared of debris by centrifugation. Chloroform was then added and homogenates incubated at room temperature for 10 minutes. Samples were centrifuged and isopropyl alcohol added to the aqueous phase. Precipitated RNA was then washed twice with 75% ethanol and resuspended in nuclease-free deionised

(d)H2O. Concentration and purity of RNA samples were quantified using a NanoDrop™

1000 Spectrophotometer (Thermo Fisher Scientific).

The integrity of RNA samples was assessed via electrophoresis using an Agilent

2100 Bioanalyser (Agilent Technologies, Santa Clara, CA, USA) and Agilent RNA

6000 Nano LabChip Kits (Agilent Technologies) prior to microarray analysis. Prior to use, the bioanalyser was decontaminated as per the manufacturer’s instructions and reagents equilibrated to room temperature. To prime the Agilent RNA 6000 Nano

LabChips, 1μL dye concentrate was added to 65μL spin-filtered gel matrix, and 9μL of the gel-dye mixture added to each of the appropriate wells before pressurising using the chip priming station. 5μL marker buffer and 1μL denatured RNA or ladder (denatured by incubating at 70°C for 2 minutes) was added to each of the sample or ladder wells and chips vortexed. Chips were then inserted into the bioanalyser and RNA assay run

100 using Agilent 2100 Expert software (Agilent Technologies). RNA integrity numbers

(RINs) were used to select appropriate samples for microarray analysis (RIN>6).

2.3.5 Reverse transcription and real-time qPCR

1µg total RNA was treated with DNase I in a reaction volume of 10µL for 15 minutes at room temperature (Sigma-Aldrich), then the reaction was stopped via the addition of stopping solution and incubation at 65°C for 10 minutes. RNA was then reverse transcribed using BioScript™ reverse transcriptase enzyme and random hexamer primers (Bioline, Alexandria, Australia), according to the manufacturer’s instructions and as previously described (Starkey et al., 2013). Briefly, 2µL 50ng/µL random hexamer primers and 1µL 10mM dNTP mix (Bioline) were added to the RNA and incubated at 65°C for 5 minutes. 4µL 5X reaction buffer (Bioline), 1µL 0.1mM DL- dithiothreitol (DTT; Invitrogen, Mount Waverly, VIC, Australia), 1µL nuclease free

H2O, and 1µL BioScript™ (Bioline) were then added to the reaction and incubated at

25°C for 20 minutes, 42°C for 50 minutes, and 70°C for 15 minutes. DNA was then resuspended in nuclease free H2O up to a volume of 100µL and stored at -20°C until qPCR analysis.

Real-time qPCRs were performed using custom designed primers (Appendix A: sTable 1.1; IDT, Coralville, IA, USA) with SYBR Green Supermix (KAPA

Biosystems, MA, USA) in a 12.5µL reaction, or using TaqMan® Gene Expression

Assays (assay IDs: Mm00616542_s1 [IFNε], Mm00446968_m1 [HPRT]; Thermo

Fisher Scientific), on a Mastercycler® ep realplex2 system (Eppendorf, North Ryde,

NSW, Australia), as per the manufacturers’ instructions. Cycling conditions were 50°C for 2 minutes, 95°C for 2 minutes (10 minutes for TaqMan® Gene Expression Assays), and 40 cycles of 95°C for 15 seconds and 60°C for 1 minute, followed by dissociation

101 analysis (Horvat et al., 2010; Phipps et al., 2007). Expression levels of target genes relative to the housekeeping gene control, hypoxanthine-guanine phosphoribosyltransferase (HPRT), were then calculated.

2.3.6 Chlamydia load

Vaginal lavage fluid was collected by lavaging the vaginal vault with 2 x 60μL sterile PBS. Total DNA was extracted from the lavage fluid using a QIAamp DNA Mini

Kit (QIAGEN, Chadstone, VIC, Australia) according to the manufacturer’s instructions.

Chlamydia numbers (ifu/μL recovered vaginal lavage fluid) were determined via a

SYBR Green-based real-time qPCR assay using primers specific for the genomic C. muridarum MOMP sequence (Appendix A: sTable 1.1) and standards of known concentrations of C. muridarum (determined by infection of McCoy cells), as described previously (Asquith et al., 2011; Berry et al., 2004; Fung et al., 2013; Horvat et al.,

2010).

Total RNA was extracted from uterine horn tissue and Chlamydia 16S ribosomal

(r)RNA expression relative to HPRT determined via real-time qPCR as previously described (Asquith et al., 2011; Fung et al., 2013). Primers used are described in

Appendix A: sTable 1.1.

2.3.7 Flow cytometry

I developed and optimised the following methods for the characterisation of immune cells in murine uterine tissue by flow cytometry. Murine uterine tissue proved extremely difficult to process for flow cytometry and yielded few cells, necessitating the pooling of samples from several mice for analysis, however, the techniques that I have

102 optimised have proven valuable in helping better understand mucosal immune responses to Chlamydia in the murine upper female RT.

To prepare samples for flow cytometric analysis, uterine horn tissue was excised and digested by gently dissociating in 5mL HEPES buffer (10mM HEPES-NaOH

[pH7.4], 150mM NaCl, 5mM KCI, 1mM MgCl2, 1.8mM CaCl2) using C tubes and a gentleMACS™ Dissociator (Miltenyi Biotech, Macquarie Park, NSW, Australia) then incubating with 2mg/mL collagenase-D and 40U/mL DNase I (Roche, Dee Why, NSW,

Australia) at 37°C for 30 minutes. Cells were then passed through a 70μm nylon cell strainer to remove debris and incubated with red blood cell (RBC) lysis buffer (155mM

NH4Cl, 12mM NaHCO3, 0.1mM ethylenediaminetetraacetic acid [EDTA], pH 7.35) at

4°C for 5 minutes. Total cell numbers were enumerated by trypan blue exclusion using a Countess™ automated cell counter (Invitrogen) and single cell suspensions placed in a

96 well plate at 0.5-1 x 106 cells/well.

Cells were then incubated with 10ng/mL mouse fragment, crystallisable region of an antibody (Fc) receptor block (anti-mouse CD16/32; BD Biosciences, North Ryde,

NSW, Australia) in 100μL flow cytometry and cell sorting (FACS) buffer (2% foetal bovine serum [FBS], 2mM EDTA in PBS) at 4°C for 15 minutes and stained for a combination of the surface markers, CD3, CD4, CD8, B220, F4/80, CD11c, CD11b,

GR1, PDCA-1, (Biolegend, Karrinyup, WA, Australia) and NK1.1 (BD Biosciences), by incubation with fluorochrome (FITC, PE, PerCP, APC, or PE-Cy7)- or biotin- conjugated antibodies at 4°C for 20 minutes (Table 2.1). Samples incubated with biotin-conjugated antibodies were subsequently stained with streptavidin-conjugated fluorochromes (Table 2.1). Optimal concentrations for all antibodies and streptavidin- conjugated fluorochromes were determined by prior titration experiments. Stained cells were then washed, fixed in 4% paraformaldehyde, and analysed by flow cytometry

103 using a FACSCanto™ II and FACSDiva software (BD Biosciences) (Beckett et al.,

2012). The percentages and total numbers of different immune cell populations present were determined using forward scatter (FSC) and side scatter (SSC) and characteristic surface marker expression profiles (Table 2.2) (Beckett et al., 2012).

Table 2.1: Staining cocktails used for flow cytometric profiling of immune cell populations

Lymphocyte stain Monocyte/granulocyte stain CD3-APC GR1-APC CD4-FITC PDCA-1-FITC CD8-PerCP CD11b-PerCP B220-PE F4/80-PE NK1.1-Biotin CD11c-Biotin

Streptavidin-PE-Cy7 Streptavidin-PE-Cy7

Table 2.2: Characterisation of immune cell populations

Cell type Surface marker expression FSC/SSC profile CD4+ T cell CD3+ CD4+ CD8- FSClow-int SSClow CD8+ T cell CD3+ CD4- CD8+ FSClow-int SSClow B cell CD3- B220+ FSClow-int SSClow Natural killer (NK) cell CD3- NK1.1+ FSClow-int SSClow Myeloid dendritic cell (mDC) CD11c+ CD11b+ GR1- PDCA- FSClow-int SSClow-int Plasmacytoid (p)DC CD11c+ CD11b- GR1+ PDCA+ FSClow-int SSClow-int Monocyte/Macrophage F4/80+ FSCint SSCint Neutrophil F4/80- GR1+ CD11b+ FSClow-int SSCint-high NK T cell CD3+ NK1.1+ FSClow-int SSClow

2.3.8 Microarray gene expression profiling

Microarray gene expression profiling was performed by our collaborators at

Monash University and the Hudson Institute of Medical Research, Melbourne, using single-colour Agilent whole-transcriptome oligo microarray chips (Agilent

Technologies) according to the manufacturer’s instructions. Briefly, 1μg RNA was amplified and labelled with Cyanine-3 using a Low Input Quick Amp Labelling Kit

(Agilent Technologies). Labelled complementary (c)RNA was washed using an RNeasy

104 Mini Kit (QIAGEN) and dye incorporation and cRNA yield determined using a

NanoDrop™ 1000 Spectrophotometer (Thermo Fisher Scientific). 600ng cRNA was then fragmented at 60°C for 30 minutes and hybridised onto a SurePrint G3 Mouse GE

8X60K Microarray chip (Agilent Technologies) at 65°C for 17 hours in a Rotating

Microarray Hybridisation Oven (Agilent Technologies) using a Gene Expression

Hybridisation Kit (Agilent Technologies). Microarrays were washed then scanned using an Agilent DNA Microarray Scanner C (Agilent Technologies) at a resolution of 3μm.

Scanned images were analysed with Agilent Feature Extraction software 11.0.1.1

(Agilent Technologies) to obtain signal intensity data.

I then performed gene expression analysis using GeneSpring GX 11.3 software

(Agilent Technologies) to determine significant differences between Chlamydia and sham-infected, WT and IFNε-/- mice (average of n=3 biological replicates). Signals were normalised to the 75th percentile signal value of all non-control probes, baseline transformation set to median for comparisons between samples (across microarrays), and non-uniform and saturated probes filtered using the default flagging option in

GeneSpring GX11.3 (Agilent Technologies). Differential gene expression data was filtered by expression level (15-100 percentile expression) and thresholds set to fold change ≥2 and p≤0.05.

2.3.9 Pathway analysis

Pathway and network associations of dysregulated transcripts were determined using Ingenuity® Pathway Analysis (IPA®) software (QIAGEN, Redwood City, CA,

USA). Lists of differentially expressed genes and their corresponding expression values

(fold change) generated during microarray gene expression profiling were split according to regulation (up- or down-regulated) and uploaded into IPA®. Canonical

105 pathways and molecular networks were algorithmically generated and ranked according to p-value. p-values were calculated during IPA® analysis using a right-tailed Fisher’s exact test and are a measure of the likelihood that the associations between focus molecules (dysregulated transcripts identified by microarray) and the pathways and networks identified are due to chance.

2.3.10 Statistics

All data are presented as mean ± standard error of the mean (SEM). Statistical significance for comparisons between two groups was determined using unpaired t-

Tests, or the non-parametric equivalent, where appropriate. Statistical significance for comparisons between three or more groups was determined by one-way analysis of variance (ANOVA) with appropriate post-hoc test, or non-parametric equivalent, where appropriate. All statistical analyses were performed using GraphPad Prism 6 software

(San Diego, CA, USA).

106 2.4 Results

2.4.1 Expression of IFNε is regulated by hormones and

protects the female RT from Chlamydia infection

Whilst we have previously shown that IFNε-/- mice have increased Chlamydia load in their vaginas at 3dpi compared to WT controls, we did not know whether this translated into protection from an ascending infection at this early time point (Fung et al., 2013). We also conducted all prior experiments in progesterone-pre-treated mice. To ascertain the effect of both infection and the female sex hormones, progesterone and oestradiol, on expression of IFNε in the upper female RT, I measured IFNε mRNA levels in uterine horn tissue from both Chlamydia- and sham-infected WT mice, pre- treated with either progesterone or oestradiol, via real-time qPCR at 3dpi (Figure 2.2

A). This time-point was chosen as it precedes both the peaks of infection (7dpi;

Appendix B: sFigure 2.1) and inflammation (14dpi), thus allowing us to study the innate processes that underpin how IFNε mediates protection against Chlamydia RTIs from the earliest stages of infection. In initial experiments, the induction of di- oestrus/oestrus by hormone pre-treatment was confirmed prior to infection and at the endpoint by cytological examination of vaginal smears (Wood et al., 2007).

Characteristic features of vaginal smears during the di-oestrous phase include the presence of many leukocytes and stringy mucus, while, during the oestrous phase, vaginal lavage contains exclusively large cornified epithelial cells.

I show that IFNε expression in the uterus is significantly higher in mice pre- treated with oestradiol, compared to progesterone, at 3dpi (Figure 2.2 A). However, expression levels are not altered by Chlamydia infection during pre-treatment with either hormone (Figure 2.2 A).

107 To determine the role of IFNε in protection against Chlamydia in the upper RT during both progesterone-mediated susceptibility and oestradiol-mediated protection, I next measured Chlamydia 16S rRNA levels in uterine horn tissue from Chlamydia- infected WT and IFNε-/- mice pre-treated with either progesterone or oestradiol (Figure

2.2 B). Chlamydia 16S is only expressed by live, metabolically active Chlamydia RBs and its levels are proportionate to the number of replicative Chlamydia organisms present (Mathews et al., 1999). As such, Chlamydia 16S expression can be used to standardise the number of chlamydial organisms present and is a well-accepted and published method for the assessment of bacterial burden in tissue during Chlamydia infection (Asquith et al., 2011; Fung et al., 2013). Additionally, this method has several advantages over other methods of assessing Chlamydia numbers, such as analysis of

Chlamydia genomic DNA levels via qPCR or determination of ifu/mL via cell culture, as these methods cannot differentiate between dead/inactive and live/active Chlamydiae, are not as sensitive, have high false negative rates, or cannot be used on tissue homogenates.

Progesterone-pre-treated IFNε-/- mice have significantly higher Chlamydia 16S expression compared to WT controls at 3dpi (Figure 2.2 B). Interestingly, I did not detect a difference in the level of 16S expression between oestradiol-pre-treated WT and

IFNε-/- mice (Figure 2.2 B).

I next sought to determine the therapeutic potential of rIFNε in reducing susceptibility to Chlamydia infections. To do this, WT mice were pre-treated with progesterone and administered increasing doses of rIFNε IVAG prior to infection.

Progesterone-pre-treated mice were used for this experiment as, not only does progesterone increase susceptibility to infection in these mice, but IFNε does not appear to greatly effect infection in oestradiol-pre-treated mice (Figure 2.2 B). Bacterial load

108 was measured in vaginal lavage fluid via real-time qPCR for Chlamydia genomic DNA and comparison to standards of known concentrations, which allowed us to calculate bacterial numbers present (Figure 2.2 C). Analysis of Chlamydia 16S expression was not performed for this study, as uterine tissue was used for flow cytometric analysis of immune cell infiltrates (Section 2.4.2). rIFNε reduced infection in progesterone-pre- treated WT mice in a dose-dependent manner, with mice administered 4µg rIFNε exhibiting significantly reduced bacterial load in the vaginal vault at 3dpi compared to

PBS vehicle controls (Figure 2.2 C).

109 A B C * 100 0.8 *** * 8000 ** 10 NS * 0.6 6000 16S 1

0.1 0.4 4000 NS NS 0.01 Chlamydia 0.2 2000 0.001 L Vaginal LavageL Vaginal Fluid) Bacterial Recovery Bacterial µ 0.0001

Relative Expression (to HPRT) (to Expression Relative 0 (ifu/

0.0 HPRT) (to Expression Relative ε -/- -/- WT ε WT ε 0 2 4 0.2

IFN SPG Cmu SPG Cmu IFN IFN Progest. O est. Progest. O est. µ g rIF N ε

Figure 2.2: Interferon (IFN)ε expression is regulated by progesterone and oestradiol, but not Chlamydia infection, and reduces Chlamydia infection in the female reproductive tract (RT) following progesterone, but not oestradiol, pre-treatment. Wild-type (WT; A, B, & C) and IFNε-/- (B) C57BL/6 mice were pre-treated with either progesterone (A, B, & C) or oestradiol (A & B) subcutaneously (SC) at -7 days post infection (dpi) then infected intravaginally (IVAG) with Chlamydia muridarum. IFNε messenger (m)RNA expression was quantified via qPCR at 3dpi to assess the effect of hormones and infection on IFNε expression in the upper RT (A; one experiment; n≥7). Chlamydia 16S ribosomal (r)RNA expression was quantified via qPCR at 3dpi to assess the effect of IFNε deficiency on infection in the upper RT (B; one experiment; n=6). IFNε and Chlamydia 16S expression levels were normalised against expression of the housekeeping gene control, hypoxanthine-guanine phosphoribosyltransferase (HPRT). 6 hours prior to infection, mice were treated with 0.2, 2, or 4µg recombinant (r)IFNε or phosphate buffered saline (PBS) vehicle control IVAG (C; one experiment; n≥6). Bacterial load in vaginal lavage fluid was determined via qPCR and comparison to standards of known concentrations of C. muridarum (inclusion forming units [ifu]; C). All data are presented as mean±SEM. *=p<0.05; **=p<0.01; ***=p<0.001.

110 2.4.2 IFNε deficiency alters immune cell profiles in the

female RT

I next performed a series of preliminary flow cytometric analyses to quantify common leukocyte populations of the female RT (Hickey et al., 2011) in uterine tissue from Chlamydia-infected WT, IFNε-/-, and rIFNε-treated mice in order to identify the key immune cells that may underpin IFNε-mediated protection against Chlamydia in the upper female RT (Figure 2.3). To obtain enough cells for these analyses, uterine homogenate samples from 8 mice were pooled into an n of 4. Flow cytometric analyses were not conducted on sham-infected WT and IFNε-/- mice as pooled samples from ≥5 mice are required in order to obtain enough cells to perform these tests in the absence of an inflammatory response.

I show that, at 3dpi, NK cells are the most abundant immune cell in the female

RT making up 8% of all cells (Figure 2.3 A). They are ~20-fold higher than neutrophils

(Figure 2.3 H) and macrophages (Figure 2.3 G), ~55-fold higher than NK T cells

(Figure 2.3 I), and 2-fold higher than pDCs (Figure 2.3 B). Relative to these innate immune cells, the numbers of myeloid (m)DCs (Figure 2.3 C), CD4+ (Figure 2.3 D) and CD8+ (Figure 2.3 E) T cells, and B cells (Figure 2.3 F) are quite low at this time- point (<0.12% of all cells). Significantly, I show that IFNε-/- mice have ~40% fewer NK cells in their uterine tissue compared to WT controls (Figure 2.3 A). There was also a trend towards a 30% increase in the number of NK cells present in uterine homogenates from rIFNε-treated mice, compared to vehicle-treated WT controls, however this did not reach significance given the variability of the data and the low number of samples obtained. There were no significant differences in the numbers of pDCs, mDCs, CD4+ T cells, CD8+ T cells, B cells, macrophages, neutrophils, or NK T cells in IFNε-/- or rIFNε-treated mice compared to WT controls (Figure 2.3 B-I). Similar trends are

111 observed when the populations are expressed as whole tissue cell numbers (data not shown).

112 A B C 15 8 0.20

6 0.15 10 * 4 0.10 pD C s(% ) 5 (%) mDCs NK (%) Cells 2 0.05

0 0 0.00 ε ε ε -/- -/- -/- WT ε WT ε WT ε IFN IFN IFN

W T+rIFN W T+rIFN W T+rIFN

D E F 0.15 0.25 0.20

0.20 0.15 0.10 0.15 0.10 0.10 0.05 B C ells (% ) 0.05

CD4+ T Cells (%) Cells T CD4+ (%) Cells T CD8+ 0.05

0.00 0.00 0.00 ε ε ε -/- -/- -/- WT ε WT ε WT ε IFN IFN IFN

W T+rIFN W T+rIFN W T+rIFN

G H I

0.8 0.8 0.3

0.6 0.6 0.2

0.4 0.4

0.1

0.2 0.2 NK(%) T Cells Neutrophils (%) Neutrophils Macrophages (%)

0.0 0.0 0.0 ε ε ε -/- -/- -/- WT ε WT ε WT ε IFN IFN IFN

W T+rIFN W T+rIFN W T+rIFN

Figure 2.3: Interferon (IFN)ε deficiency decreases the number of natural killer (NK) cells in the upper reproductive tract (RT) during Chlamydia infection. Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum. 6 hours prior to infection, mice were treated with 4µg recombinant (r)IFNε (WT) or phosphate buffered saline (PBS) vehicle (WT and IFNε-/-) IVAG. NK cell (A), plasmacytoid dendritic cell (p/DC; B), myeloid (m)DC (C), CD4+ T cell (D), CD8+ T cell (E), B cell (F), macrophage (G), and neutrophil (H) numbers in uterine horn homogenates were quantified via flow cytometry at 3dpi and percentages (of total cells) calculated to assess the effect of IFNε deficiency and exogenous IFNε on immune cell infiltration in the upper RT during Chlamydia infection (one experiment; n=4 replicates of 8 pooled uterine homogenate samples). All data are presented as mean±SEM. *=p<0.05.

113 2.4.3 IFNε deficiency alters gene expression profiles in the

female RT

In order to characterise IFNε-regulated gene expression profiles in the female

RT, I employed whole-genome microarray-based analyses to identify transcripts with altered expression patterns in Chlamydia- and sham-infected IFNε-/- mice at 3dpi compared to WT controls. Subsequent cross-comparisons allowed us to identify genes regulated by IFNε uniquely during the steady-state (baseline) or early infection, and those that are universally regulated. 744 transcripts were dysregulated at baseline in

IFNε-/- mice, compared to sham-infected WT controls, with 326 of these being up- regulated and 418 down-regulated (Figure 2.4). Additionally, the expression levels of

802 transcripts were uniquely altered during infection in IFNε-/- mice, compared to

Chlamydia-infected WT controls, with 63 of these being up-regulated and 739 down- regulated (Figure 2.4). 61 transcripts were altered in both Chlamydia- and sham- infected IFNε-/- mice, compared to WT controls, with 13 of these being up-regulated and 48 down-regulated (Figure 2.4).

114 IFNε-/- vs. WT

SPG Cmu

744 61 802

↑326 ↓418 ↑13 ↓48 ↑63 ↓739

Figure 2.4: Number of differentially expressed genes in the upper reproductive tract (RT) of female interferon (IFN)ε-/- mice at baseline (sham-infected) and during Chlamydia infection compared to wild-type (WT) controls. WT and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum (Cmu) or sham-infected with sucrose-phosphate-glutamate buffer (SPG). Microarray gene expression profiling was performed on total RNA isolates from uterine tissue at 3dpi. Gene expression profiles from IFNε-/- mice were initially compared to age-matched WT controls to assess the effect of IFNε deficiency on the transcriptome. Data was filtered by expression level (15-100 percentile expression), fold change (≥2), and p-value (p≤0.05) and cross-comparisons were performed between infected and non-infected groups. Numbers of up- and down-regulated transcripts that are unique to baseline (SPG) or Chlamydia infection (Cmu), and those that are commonly dysregulated in IFNε-/- mice are shown (one experiment; n=3).

115 2.4.4 Pathway analysis of dysregulated gene transcripts in

IFNε-/- mice

Since I found that IFNε deficiency results in the dysregulation of a large number of transcripts, both at baseline and during infection, I next sought to elucidate the biological processes that these dysregulated transcripts may be involved in using IPA®.

This approach allowed for the systematic and unbiased identification of key pathways and biological processes regulated by IFNε signalling, and networks of potential interactions between dysregulated and predicted factors downstream of IFNε, in both the absence and presence of infection and, therefore, may help identify novel mechanisms that underpin IFNε-mediated protection against Chlamydia infection.

As down-regulated genes were over-represented in all comparisons between

IFNε-/- and WT mice (i.e. down-regulated in IFNε-/- mice compared to WT controls), the role of any down-regulated networks and pathways identified during pathway analysis may overshadow the role of the small number of up-regulated genes. To circumvent this, lists of dysregulated transcripts were split by regulation (i.e. up- or down- regulated) allowing us to delineate any potential effects of up-regulated genes and identify the processes they are involved in.

2.4.4.1 Canonical pathways associated with dysregulated

gene transcripts in IFNε-/- mice

2.4.4.1.1 Canonical pathways associated with down-regulated gene

transcripts in IFNε -/- mice

Unsurprisingly, pathway analysis of transcripts down-regulated in IFNε-/- mice at baseline (sham-infected) compared to WT controls identified significant associations

116 with canonical pathways related to immune regulation (Table 2.3). These included pathways associated with; i) non-specific leukocyte recruitment and haematopoiesis, such as Granulocyte and Agranulocyte Adhesion and Diapedesis, and Haematopoiesis from Pluripotent Stem Cells, ii) immune cell function, notably Natural Killer Cell

Signalling and Communication Between Innate and Adaptive Immune Cells, iii) innate immune signalling, such as Clathrin-mediated Endocytosis Signalling, Acute Phase

Response Signalling, the Role of Pattern Recognition Receptors in Recognition of

Bacteria and Viruses, and the Complement System, and iv) metabolic processes with roles in immune regulation, including Liver X Receptor (LXR)/Retinoid X Receptor

(RXR) Activation, Glutathione-mediated Detoxification, and Aryl Hydrocarbon

Receptor Signalling (Table 2.3).

Pathway analysis of transcripts down-regulated in Chlamydia-infected IFNε-/- mice compared to WT controls also identified a number of canonical pathways associated with immune regulation (Table 2.4). IPA® analysis identified pathways related to; i) innate immune responses, including Activation of IRF by Cytosolic Pattern

Recognition Receptors, Extrinsic and Intrinsic Prothrombin Activation Pathways, and the Role of Pattern Recognition Receptors in Recognition of Bacteria and Viruses, as well as ii) immune cell function, specifically Differential Regulation of Cytokine

Production in Macrophages and T Helper Cells by IL-17A and IL-17F, Communication

Between Innate and Adaptive Immune Cells, and TREM1, IL-8, and OX40 signalling

(Table 2.4). Interestingly, a large number of pathways with roles in; i) metabolism, including Nicotine, Melatonin, and Triacylglycerol Degradation, Oestrogen

Biosynthesis, and LXR/RXR Activation, and ii) cell cycle progression and apoptosis, such as Growth Arrest and DNA Damage-inducible 45 (GADD45) Signalling and DNA

Damage-induced 14-3-3σ Signalling, were also identified (Table 2.4).

117 Pathway analysis of transcripts that are commonly down-regulated in both

Chlamydia- and sham-infected IFNε-/- mice compared to WT controls identified only one pathway, the Role of IL-17A in Psoriasis, which was associated with the down- regulation of S100A8 and S100A9 in IFNε-/- mice (Table 2.5).

118 Table 2.3: Canonical pathways associated with down-regulated genes in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls at baseline (sham-infected). p-values were calculated during Ingenuity® Pathway Analysis (IPA®) analysis and represent the likelihood of finding the number of focus molecules (dysregulated transcripts identified by microarray) in each pathway in a set of x randomly selected molecules where x = the total number of molecules known to be associated with that pathway. # = number of focus molecules associated with pathway.

Pathway p-value Molecules # Granulocyte Adhesion and Diapedesis 2.14E-06 IL33, SELL, CLDN4, Ccl8, CXCL14, 11 CXCL17, CSF3, HRH3, CLDN22, CLDN3, IL18RAP Agranulocyte Adhesion and Diapedesis 7.41E-04 IL33, SELL, CLDN4, Ccl8, CXCL14, 8 CXCL17, CLDN22, CLDN3 LXR/RXR Activation 1.51E-03 IL33, S100A8, AGT, RBP4, APOD, 6 IL18RAP Glutathione-mediated Detoxification 2.82E-03 GSTA5, Gsta4, GSTO1 3 Clathrin-mediated Endocytosis Signalling 2.95E-03 STON2, FGF18, S100A8, ITGB6, 7 FGF1, RBP4, APOD Aryl Hydrocarbon Receptor Signalling 3.09E-03 CTSD, ALDH1A3, GSTA5, AHR, 6 GSTO1, CHEK1 Natural Killer Cell Signalling 5.25E-03 SH2D1A, KLRD1, KLRB1, Klra4 5+ (includes others), KLRC1 Complement System 6.31E-03 CFB, C6, C2 3 Basal Cell Carcinoma Signalling 6.31E-03 WNT7A, BMP5, Tcf7, WNT11 4 LPS/IL-1 Mediated Inhibition of RXR 6.92E-03 IL33, CHST4, ALDH1A3, GSTA5, 7 Function HS6ST2, GSTO1, IL18RAP Role of IL-17A in Psoriasis 7.59E-03 S100A9, S100A8 2 Acute Phase Response Signalling 7.94E-03 IL33, KLKB1, CFB, C2, AGT, RBP4 6 Regulation of the Epithelial- 1.17E-02 WNT7A, FGF18, Tcf7, WNT11, 6 Mesenchymal Transition Pathway CLDN3, FGF1 Heparan Sulphate Biosynthesis (Late 1.38E-02 CHST4, LIPE, HS6ST2 3 Stages) Communication between Innate and 1.41E-02 IL33, CD83, IGHA1, TNFRSF17 4 Adaptive Immune Cells Haematopoiesis from Pluripotent Stem 1.51E-02 IGHM, IGHA1, CSF3 3 Cells Primary Immunodeficiency Signalling 1.62E-02 IGHM, CD79A, IGHA1 3 Role of Cytokines in Mediating 1.86E-02 IL33, IL20, CSF3 3 Communication between Immune Cells Heparan Sulphate Biosynthesis 1.95E-02 CHST4, LIPE, HS6ST2 3 Role of Osteoblasts, Osteoclasts and 2.45E-02 IL33, WNT7A, BMP5, Tcf7, WNT11, 6 Chondrocytes in Rheumatoid Arthritis IL18RAP Ascorbate Recycling (Cytosolic) 3.02E-02 GSTO1 1 Methionine Salvage II (Mammalian) 3.02E-02 BHMT 1 Thyroid Hormone Biosynthesis 3.02E-02 CTSD 1 Atherosclerosis Signalling 3.63E-02 IL33, S100A8, RBP4, APOD 4 Role of Pattern Recognition Receptors in 3.98E-02 OAS1, OAS2, Oas1f, OAS3 4 Recognition of Bacteria and Viruses Arsenate Detoxification I (Glutaredoxin) 3.98E-02 GSTO1 1 FXR/RXR Activation 4.07E-02 IL33, AGT, RBP4, APOD 4 B Cell Development 4.17E-02 IGHM, CD79A 2 Ovarian Cancer Signalling 4.57E-02 GJA1, WNT7A, Tcf7, WNT11 4 Role of Wnt/GSK-3β Signalling in the 4.57E-02 WNT7A, Tcf7, WNT11 3 Pathogenesis of Influenza Human Embryo Stem Cell Pluripotency 4.79E-02 WNT7A, BMP5, Tcf7, WNT11 4

119 Table 2.4: Canonical pathways associated with down-regulated genes in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls during Chlamydia infection. p-values were calculated during Ingenuity® Pathway Analysis (IPA®) analysis and represent the likelihood of finding the number of focus molecules (dysregulated transcripts identified by microarray) in each pathway in a set of x randomly selected molecules where x = the total number of molecules known to be associated with that pathway. # = number of focus molecules associated with pathway.

Pathway p-value Molecules # Nicotine Degradation III 2.09E-04 CYP1A1, UGT3A1, UGT2A1, CYP2C9, 5 CYP2C8 Melatonin Degradation I 2.75E-04 CYP1A1, UGT3A1, UGT2A1, CYP2C9, 5 CYP2C8 Role of IL-17A in Psoriasis 3.16E-04 CXCL3, S100A9, S100A8 3 Superpathway of Melatonin 4.17E-04 CYP1A1, UGT3A1, UGT2A1, CYP2C9, 5 Degradation CYP2C8 Nicotine Degradation II 4.57E-04 CYP1A1, UGT3A1, UGT2A1, CYP2C9, 5 CYP2C8 Bupropion Degradation 2.34E-03 CYP1A1, CYP2C9, CYP2C8 3 Acetone Degradation I (to 2.95E-03 CYP1A1, CYP2C9, CYP2C8 3 Methylglyoxal) Breast Cancer Regulation by Stathmin1 4.57E-03 TUBB3, CCNE1, GNAS, ARHGEF15, 7 UHMK1, CDK1, TUBB2B Activation of IRF by Cytosolic Pattern 4.68E-03 IL10, MAPK10, PIN1, IFNA4 4 Recognition Receptors Oestrogen Biosynthesis 7.76E-03 CYP1A1, CYP2C9, CYP2C8 3 Extrinsic Prothrombin Activation 1.23E-02 F10, FGA 2 Pathway Differential Regulation of Cytokine 1.55E-02 IL10, IL1B 2 Production in Macrophages and T Helper Cells by IL-17A and IL-17F D-myo-inositol (1,4,5)-trisphosphate 1.55E-02 INPP5F, INPP5E 2 Degradation Communication between Innate and 1.66E-02 IL10, HLA-A, IL1B, IGHA1 4 Adaptive Immune Cells GADD45 Signalling 1.74E-02 CCNE1, CDK1 2 1D-myo-inositol Hexakisphosphate 1.74E-02 INPP5F, INPP5E 2 Biosynthesis II (Mammalian) D-myo-inositol (1,3,4)-trisphosphate 1.74E-02 INPP5F, INPP5E 2 Biosynthesis DNA damage-induced 14-3-3σ 1.74E-02 CCNE1, CDK1 2 Signalling Role of Cytokines in Mediating 2.09E-02 IL10, IL1B, IFNA4 3 Communication between Immune Cells Regulation of Cellular Mechanics by 2.34E-02 CCNE1, CDK1, CNGA3 3 Calpain Protease Differential Regulation of Cytokine 2.51E-02 IL10, IL1B 2 Production in Intestinal Epithelial Cells by IL-17A and IL-17F Estrogen-mediated S-phase Entry 2.69E-02 CCNE1, CDK1 2 Triacylglycerol Degradation 2.69E-02 LIPC, LIPG 2 Superpathway of D-myo-inositol (1,4,5)- 2.69E-02 INPP5F, INPP5E 2 trisphosphate Metabolism Gαs Signalling 2.95E-02 GNAS, ADORA2B, RAP1A, CNGA3 4 Intrinsic Prothrombin Activation 3.63E-02 F10, FGA 2 Pathway

120 LXR/RXR Activation 4.07E-02 APOA5, IL1B, S100A8, FGA 4 Axonal Guidance Signalling 4.37E-02 TUBB3, GNAS, SDCBP, RND1, MYL2, 9 ARHGEF15, Adam24, RAP1A, TUBB2B Allograft Rejection Signalling 4.37E-02 H2-T18, IL10, HLA-A 3 TREM1 Signalling 4.47E-02 CXCL3, IL10, IL1B 3 Role of Pattern Recognition Receptors 4.57E-02 IL10, MAPK10, IL1B, IFNA4 4 in Recognition of Bacteria and Viruses Thyroid Hormone Metabolism II (via 4.57E-02 UGT3A1, UGT2A1 2 Conjugation and/or Degradation) Retinol Biosynthesis 4.57E-02 LIPC, LIPG 2 Hepatic Fibrosis / Hepatic Stellate Cell 4.68E-02 CXCL3, MYL2, FLT1, IL10, IL1B 5 Activation FXR/RXR Activation 4.68E-02 LIPC, MAPK10, IL1B, FGA 4 IL-8 Signalling 4.68E-02 GNAS, MYL2, FLT1, MAPK10, LASP1 5 OX40 Signalling Pathway 4.79E-02 H2-T18, HLA-A, MAPK10 3

Table 2.5: Canonical pathways associated with commonly down-regulated genes in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls both at baseline and during Chlamydia infection. p-values were calculated during Ingenuity® Pathway Analysis (IPA®) analysis and represent the likelihood of finding the number of focus molecules (dysregulated transcripts identified by microarray) in each pathway in a set of x randomly selected molecules where x = the total number of molecules known to be associated with that pathway. # = number of focus molecules associated with pathway.

Pathway p-value Molecules # Role of IL-17A in Psoriasis 9.55E-05 S100A9, S100A8 2

121 2.4.4.1.2 Canonical pathways associated with up-regulated gene

transcripts in IFNε -/- mice

Conversely, pathway analysis of transcripts up-regulated in IFNε-/- mice at baseline compared to WT controls identified pathways associated with cellular organisation-related signalling, such as Ephrin B and RhoGDI Signalling, and fatty acid metabolism, specifically Stearate Biosynthesis (Table 2.6). Interestingly, Melatonin

Degradation was also identified, however, this pathway was only associated with the one up-regulated factor, myeloperoxidase (MPO; Table 2.6).

Interestingly, pathway analysis of transcripts up-regulated in Chlamydia- infected IFNε-/- mice compared to WT controls identified pathways associated with; i) the metabolism of molecules involved in respiration, such as Tetrapyrrole and Haem

Biosynthesis, ii) the metabolism of molecules involved in inflammation, specifically

Prostanoid Biosynthesis, as well as iii) Circadian Rhythm Signalling (Table 2.7).

Pathway analysis of transcripts commonly up-regulated in both Chlamydia- and sham-infected IFNε-/- mice compared to WT controls showed significant associations with pathways involved in fatty acid metabolism, such as Triacylglycerol and Stearate

Biosynthesis, and cell contact-mediated signalling, specifically Ephrin B Signalling; identifying these pathways as universally up-regulated in IFNε-/- mice (Table 2.8).

122 Table 2.6: Canonical pathways associated with up-regulated genes in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls at baseline (sham-infected). p- values were calculated during Ingenuity® Pathway Analysis (IPA®) analysis and represent the likelihood of finding the number of focus molecules (dysregulated transcripts identified by microarray) in each pathway in a set of x randomly selected molecules where x = the total number of molecules known to be associated with that pathway. # = number of focus molecules associated with pathway.

Pathway p-value Molecules # Melatonin Degradation III 7.76E-03 MPO 1 Ephrin B Signalling 1.95E-02 CAP1, GNAT2, GNG13 3 Stearate Biosynthesis I (Animals) 3.16E-02 DHCR24, ELOVL2 2 RhoGDI Signalling 4.57E-02 CDH4, GNAT2, GNG13, CDH16 4

Table 2.7: Canonical pathways associated with up-regulated genes in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls during Chlamydia infection. p-values were calculated during Ingenuity® Pathway Analysis (IPA®) analysis and represent the likelihood of finding the number of focus molecules (dysregulated transcripts identified by microarray) in each pathway in a set of x randomly selected molecules where x = the total number of molecules known to be associated with that pathway. # = number of focus molecules associated with pathway.

Pathway p-value Molecules # Circadian Rhythm Signalling 3.39E-03 PER3, NR1D1 2 Tetrapyrrole Biosynthesis II 1.29E-02 ALAD 1 Prostanoid Biosynthesis 2.34E-02 PTGDS 1 Haem Biosynthesis II 2.34E-02 ALAD 1

Table 2.8: Canonical pathways associated with commonly up-regulated genes in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls both at baseline and during Chlamydia infection. p-values were calculated during Ingenuity® Pathway Analysis (IPA®) analysis and represent the likelihood of finding the number of focus molecules (dysregulated transcripts identified by microarray) in each pathway in a set of x randomly selected molecules where x = the total number of molecules known to be associated with that pathway. # = number of focus molecules associated with pathway.

Pathway p-value Molecules # Triacylglycerol Biosynthesis 1.51E-02 ELOVL2 1 Stearate Biosynthesis I (Animals) 1.58E-02 ELOVL2 1 Ephrin B Signalling 3.16E-02 CAP1 1

123 2.4.4.2 Molecular networks associated with dysregulated

gene transcripts in IFNε-/- mice

2.4.4.2.1 Molecular networks associated with down-regulated gene

transcripts in IFNε -/- mice

IPA® also allowed us to find significant associations between sets of dysregulated transcripts and molecular networks of interacting factors that may be involved in IFNε-mediated protection. Generation of molecular networks allows the visualisation of known relationships between dysregulated factors identified by microarray (focus molecules) and other genes and gene products that have previously been shown to be either regulated by, or involved in the regulation of, these focus molecules. This allows for the identification of both factors that may be responsible for the regulation of many of the genes identified downstream of IFNε and novel factors that may also be dysregulated but were not detected during microarray analysis.

Importantly, the most significant network associated with transcripts down-regulated in

IFNε-/- mice at baseline compared to WT controls contained a number of important NK cell-related factors (Klra7/4, KLRB1, Klrk1 and EOMES; Figure 2.5) and is involved in functions such as Immune Cell Trafficking, Haematological System Development and

Function and Cell-to-Cell Signalling and Interaction (Appendix B: sTable 2.1).

Notable functions associated with other networks identified during analysis of transcripts down-regulated in sham-infected IFNε-/- mice included Lipid Metabolism,

Small Molecule Biochemistry, Inflammatory Response, Tissue Morphology, and Cell

Death and Survival, which may be related to several of the pathways identified in

Section 2.4.4.1.1 (Appendix B: sTable 2.1).

124 Interestingly, the most significant network identified during analysis of transcripts down-regulated in Chlamydia-infected IFNε-/- mice compared to WT controls highlights a potential role for the hub molecule IL-1β in IFNε-mediated responses to infection, as this factor demonstrated high interconnectivity with other factors in the network (Figure 2.6). These included factors such as S100A8, S100A9, and Saa1, which are involved in inflammatory and acute phase responses (Figure 2.6).

Networks significantly associated with transcripts down-regulated in Chlamydia- infected IFNε-/- mice are also involved in functions such as Immune Cell Trafficking,

Haematological System Development and Function, Cell-to-Cell Signalling and

Interaction, Tissue Morphology, Inflammatory Response, Cell Death and Survival, and

Lipid Metabolism (Appendix B: sTable 2.2).

The most significant network identified during analysis of transcripts universally down-regulated in IFNε-/- mice compared to WT controls, regardless of infection status, also contained NK cell-related factors (GZMK and Klra16) and encompassed noteworthy hub molecules such as STAT1, IFNAR, SOCS1, IL-12B, and TNF, which have all been shown to play a role in protection against Chlamydia infections (Figure

2.7). Networks identified during analysis of commonly down-regulated transcripts were associated with functions such as Cellular Movement, Haematological System

Development and Function, Tissue Morphology, Cancer, Organismal Injury and

Abnormalities, and Reproductive System Disease (Appendix B: sTable 2.3).

125

Direct interaction

Indirect interaction

Figure 2.5: Molecular networks associated with genes down-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls at baseline (sham- infected). WT and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and sham-infected with sucrose-phosphate-glutamate buffer (SPG) intravaginally (IVAG). Microarray gene expression profiling was performed on total RNA isolates from uterine tissue at 3dpi. Gene expression profiles from IFNε-/- mice were initially compared to age-matched WT controls to assess the effect of IFNε deficiency on the transcriptome. Data was filtered and cross- comparisons performed between infected and non-infected groups. Analysis of transcripts down-regulated in IFNε-/- mice at baseline compared to WT controls using Ingenuity® Pathway Analysis (IPA®) software identified the molecular networks that link these factors. p-scores were calculated during IPA® analysis and the highest ranking network is shown (one experiment; n=3). Focus molecules (dysregulated transcripts identified by microarray) are shown in red with darker colour indicating greater fold change. Molecules of interest and the relationships between these are outlined in dark blue and all other relationships associated with molecules of interest in light blue.

126

Direct interaction

Indirect interaction

Figure 2.6: Molecular networks associated with genes down-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls during Chlamydia infection. WT and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum. Microarray gene expression profiling was performed on total RNA isolates from uterine tissue at 3dpi. Gene expression profiles from IFNε-/- mice were initially compared to age-matched WT controls to assess the effect of IFNε deficiency on the transcriptome. Data was filtered and cross-comparisons performed between infected and non-infected groups. Analysis of transcripts down-regulated in Chlamydia-infected IFNε-/- mice compared to WT controls using Ingenuity® Pathway Analysis (IPA®) software identified the molecular networks that link these transcripts. p-scores were calculated during IPA® analysis and the highest ranking network is shown (one experiment; n=3). Focus molecules (dysregulated transcripts identified by microarray) are shown in red with darker colour indicating greater fold change. Molecules of interest and the relationships between these are outlined in dark blue and all other relationships associated with molecules of interest in light blue.

127

Direct interaction

Indirect interaction

Figure 2.7: Molecular networks associated with genes down-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls both at baseline and during Chlamydia infection. WT and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum or sham-infected with sucrose-phosphate-glutamate buffer (SPG). Microarray gene expression profiling was performed on total RNA isolates from uterine tissue at 3dpi. Gene expression profiles from IFNε-/- mice were initially compared to age-matched WT controls to assess the effect of IFNε deficiency on the transcriptome. Data was filtered and cross-comparisons performed between infected and non-infected groups. Analysis of transcripts that are universally down-regulated in IFNε-/- mice compared to WT controls regardless of infection status using Ingenuity® Pathway Analysis (IPA®) software identified the molecular networks that link these transcripts. p-scores were calculated during IPA® analysis and the highest ranking network is shown (one experiment; n=3). Focus molecules (dysregulated transcripts identified by microarray) are shown in red with darker colour indicating greater fold change. Molecules of interest and the relationships between these are outlined in dark blue and all other relationships associated with molecules of interest in light blue.

128 2.4.4.2.2 Molecular networks associated with up-regulated gene

transcripts in IFNε -/- mice

Conversely, networks associated with transcripts up-regulated in IFNε-/- mice at baseline compared to WT controls were not found to be heavily immune response- related, with the top network instead being linked to biological processes such as Cell

Morphology, Connective Tissue Disorders, and Skeletal and Muscular Disorders

(Figure 2.8 & Appendix B: sTable 2.4).

Networks identified during analysis of transcripts up-regulated in Chlamydia- infected IFNε-/- mice compared to WT controls are also involved in functions such as

Cell Morphology and Organismal Injury and Abnormalities (Appendix B: sTable 2.5).

Interestingly, IFNγ, which is vital for protection against Chlamydia infections, was identified as a hub molecule in the most significant network associated with transcripts up-regulated in Chlamydia-infected IFNε-/- mice, and further investigation of the relationships between this factor and the focus molecules contained within this network indicated that many are inversely associated with IFNγ expression (Figure 2.9).

Fewer networks were significantly associated with transcripts universally up- regulated in IFNε-/- mice compared to WT controls, regardless of infection status, however, their top functions were linked to Infectious Diseases, Lipid Metabolism, and

Molecular Transport (Appendix B: sTable 2.6). Again, notable factors were identified as hub molecules in the most significant network associated with transcripts commonly up-regulated in IFNε-/- mice, including IFNγ, STAT1, and IL-6 (Figure 2.10).

129

Direct interaction

Indirect interaction

Figure 2.8: Molecular networks associated with genes up-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls at baseline (sham-infected). WT and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and sham-infected with sucrose-phosphate-glutamate buffer (SPG) intravaginally (IVAG). Microarray gene expression profiling was performed on total RNA isolates from uterine tissue at 3dpi. Gene expression profiles from IFNε-/- mice were initially compared to age-matched WT controls to assess the effect of IFNε deficiency on the transcriptome. Data was filtered and cross-comparisons performed between infected and non-infected groups. Analysis of transcripts up-regulated in IFNε-/- mice at baseline compared to WT controls using Ingenuity® Pathway Analysis (IPA®) software identified the molecular networks that link these transcripts. p-scores were calculated during IPA® analysis and the highest ranking network is shown (one experiment; n=3). Focus molecules (dysregulated transcripts identified by microarray) are shown in red with darker colour indicating greater fold change.

130

Direct interaction

Indirect interaction

Figure 2.9: Molecular networks associated with genes up-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls during Chlamydia infection. WT and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum. Microarray gene expression profiling was performed on total RNA isolates from uterine tissue at 3dpi. Gene expression profiles from IFNε-/- mice were initially compared to age-matched WT controls to assess the effect of IFNε deficiency on the transcriptome. Data was filtered and cross-comparisons performed between infected and non-infected groups. Analysis of transcripts up-regulated in Chlamydia-infected IFNε-/- mice compared to WT controls during using Ingenuity® Pathway Analysis (IPA®) software identified the molecular networks that link these transcripts. p-scores were calculated during IPA® analysis and the highest ranking network is shown (one experiment; n=3). Focus molecules (dysregulated transcripts identified by microarray) are shown in red with darker colour indicating greater fold change. Molecules of interest and the relationships between these are outlined in dark blue and all other relationships associated with molecules of interest in light blue.

131

Direct interaction

Indirect interaction

Figure 2.10: Molecular networks associated with genes up-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls both at baseline and during Chlamydia infection. WT and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum or sham-infected with sucrose-phosphate-glutamate buffer (SPG). Microarray gene expression profiling was performed on total RNA isolates from uterine tissue at 3dpi. Gene expression profiles from IFNε-/- mice were initially compared to age-matched WT controls to assess the effect of IFNε deficiency on the transcriptome. Data was filtered and cross-comparisons performed between infected and non-infected groups. Analysis of transcripts universally up-regulated in IFNε-/- mice compared to WT controls regardless of infection status using Ingenuity® Pathway Analysis (IPA®) software identified the molecular networks that link these transcripts. p-scores were calculated during IPA® analysis and the highest ranking network is shown (one experiment; n=3). Focus molecules (dysregulated transcripts identified by microarray) are shown in red with darker colour indicating greater fold change. Molecules of interest and the relationships between these are outlined in dark blue and all other relationships associated with molecules of interest in light blue.

132 2.5 Discussion

In this study, I confirmed findings from our Science publication that showed that

IFNε is protective against Chlamydia infection in the female RT from the earliest stages of infection (3dpi) (Fung et al., 2013). Importantly, I also extended upon these findings to improve our understanding of the role of IFNε in protection against Chlamydia female RTIs. I confirmed that IFNε expression is not induced by infection in vivo but is instead regulated by female sex hormones. I show that IFNε not only reduces

Chlamydia numbers in the vagina from 3dpi, but also protects against ascending

(uterine) infection from this very early stage. Importantly, I show that IFNε has its most pronounced effects on Chlamydia infection in progesterone-pre-treated mice, which are highly susceptible to infection, with oestradiol pre-treated IFNε-/- mice found to still be highly resistant infection compared to WT and IFNε-/- mice that have been pre-treated with progesterone. In order to better understand how IFNε mediates these protective effects from the earliest stages of infection in progesterone-pre-treated mice, I assessed immune cell infiltration and profiled gene expression changes in the upper RTs of IFNε-

/- mice and WT controls at 3dpi. These techniques were employed as discovery tools to identify the potential mechanisms that may underpin IFNε-mediated protection against infection and were crucial in identifying important links between IFNε and NK cells as well as IL-1β and the inflammasome in the innate immune response to Chlamydia infections in the female RT. Importantly, the findings of these studies were pivotal in informing the directions of subsequent studies (described in Chapters 3 and 4 of this thesis).

Previous studies show that IFNε is not induced by PRR or IRF activation, but is instead constitutively expressed in uterine tissue and fluctuates throughout the menstrual cycle in humans and oestrous cycle in mice (Fung et al., 2013). Here, I

133 expand upon these findings, by showing that uterine expression of IFNε is not affected by Chlamydia infection but is instead regulated by hormones. I show that oestradiol- pre-treated mice have significantly higher expression levels of IFNε in their uterine horn tissue compared to that of progesterone-pre-treated mice at baseline and that Chlamydia infection has no effect on IFNε expression following pre-treatment with either progesterone or oestradiol (Figure 2.2 A), despite Chlamydia levels, and therefore

PAMP stimulation, being dramatically different between the two hormone pre-treatment groups (Figure 2.2 B). This increase in IFNε expression observed during oestradiol- dominance is supported by previous studies that show that the expression of IFNε by endometrial epithelial cells from women in the proliferative phase of the menstrual cycle, when oestradiol levels are high, is higher than that from both women in the secretory phase, when progesterone levels are high, and post-menopausal women, who have reduced levels of both hormones (Fung et al., 2013). However, IFNε is also up- regulated during the secretory phase of the menstrual cycle in pre-menopausal women compared to expression levels observed during post-menopause (Fung et al., 2013).

Since progesterone is dominant but oestradiol is still present at low concentrations during the secretory phase, the modulation of IFNε expression by hormone fluctuations throughout the reproductive cycles in humans and mice may be due to an up-regulation by oestradiol, rather than a down-regulation by progesterone. Further studies are required in order to determine whether low levels of oestradiol present at this stage are responsible for the increase in expression of IFNε observed or if progesterone also induces IFNε expression, albeit to a lesser extent than oestradiol. As such, these hormone pre-treatment experiments are to be repeated in ovariectomised mice in future studies.

134 Susceptibility to RTI is known to fluctuate throughout the menstrual/oestrous cycles due to regulation of immune responses by the female sex hormones, progesterone and oestradiol. Oestradiol has previously been shown to protect against both infection and inflammation in an animal model of Chlamydia female RTIs (Kaushic et al., 2000).

Additionally, cervical secretions from women in the early, oestradiol-dominant stages of the menstrual cycle have more potent anti-Chlamydia effects than those collected during the progesterone-dominant stages or menses (Mahmoud et al., 1994). In preliminary studies, I have shown that, in progesterone-pre-treated mice, Chlamydia rapidly ascends the RT and replicates in the uterus and oviducts, increasing Chlamydia burden in the upper RT until it peaks at 7dpi and is cleared in the majority of animals by

30dpi, however, in oestradiol-pre-treated mice, although infection also reaches the upper RT by 3dpi, infection levels remain low throughout the time-course (Appendix

B: sFigure 2.1).

Since oestradiol pre-treatment is associated with increased IFNε responses

(Figure 2.2 A) and since we show that IFNε protects against infection (Fung et al.,

2013), it would be assumed that oestradiol-induced IFNε responses may account for the increase in protection against infection observed in oestradiol-pre-treated mice.

However, my data show that this may not be the case.

Using IFNε-/- mice, I demonstrate that absence of IFNε leads to a 1000-fold increase in Chlamydia load in the uterine horns of progesterone-pre-treated mice at 3dpi

(Figure 2.2 B). Whilst the absence of IFNε was shown to result in an increase infection in progesterone-pre-treated mice, the levels of infection in oestradiol-pre-treated mice were unchanged by the absence of IFNε and remained low compared to that observed in both progesterone-pre-treated WT (10-15-fold lower) and IFNε-/- (10,000-15,000-fold lower) mice (Figure 2.2 B). These findings demonstrate that whilst IFNε contributes to

135 protection against infection in progesterone-pre-treated mice, the role of IFNε during oestradiol pre-treatment is largely overshadowed by the other effects induced by this hormone, which confer a high level of protection against infection (and/or reduce permissivity), regardless of IFNε expression, in the murine model of Chlamydia female

RTI we have utilised. As such, all subsequent studies were conducted in progesterone- pre-treated mice.

The observation of increased infection in the uterine tissue of progesterone-pre- treated IFNε-/- mice extends upon our previous findings, which showed that IFNε reduces Chlamydia numbers in the vagina from 3-29dpi (Fung et al., 2013). This corresponded with an increase in Chlamydia in the uterine horns of IFNε-/- mice at

30dpi compared to WT controls (Fung et al., 2013). This IFNε-mediated protection against infection in the upper female RT is likely the most crucial observation as inhibition of ascending infection is key to the prevention of Chlamydia-induced female

RT pathology (Darville and Hiltke, 2010; Maxion et al., 2004). Importantly, my findings extend upon these previous observations and demonstrate that, not only are

IFNε-/- mice more susceptible to infection in the lower female RT (vagina) from 3dpi, they are also more susceptible to an ascending (uterine) Chlamydia infection from this very early stage of infection. Interestingly, during our previous studies we did not observe any robust changes in Chlamydia-specific serum IgG1 and IgG2a levels or caudal/lumbar lymph node IFNγ release at 30dpi in IFNε-/- mice compared to WT controls (Appendix B: sFigure 2.3), which suggests that IFNε does not have a profound effect on adaptive immune responses during Chlamydia infection. These findings, in combination with the observations that show that IFNε mediates its protective effects from as early as 3dpi, suggest that the most important IFNε-mediated effects that protect against ascending infection likely involve key innate immune

136 responses that are induced during the earliest stages of Chlamydia infection. Therefore, since IFNε appears to have its most robust effects on infection on the background of progesterone-mediated susceptibility and since IFNε is likely mediating its protective effects by affecting key early innate immune responses, the remainder of my PhD studies focussed on investigating the effects of IFNε in progesterone-pre-treated mice at

3dpi.

To further reinforce the important role that IFNε plays in protecting against the earliest stages of Chlamydia infection and determine its therapeutic potential, I also treated susceptible progesterone-pre-treated WT mice with increasing doses of rIFNε locally 6 hours prior to infection and assessed its effects on infection at 3dpi. IVAG administration of rIFNε prior to infection reduced Chlamydia load in progesterone-pre- treated WT mice at 3dpi in a dose-dependent manner (Figure 2.2 C), providing further evidence for the involvement of IFNε in innate defence against Chlamydia RTIs and highlighting its potential for use in novel preventative strategies.

In order to identify how IFNε may be mediating its protective effects during the earliest stages of infection, I conducted immune cell and gene expression profiling experiments using flow cytometry and microarray-based analyses, respectively.

Importantly, these studies identified NK cell expansion/recruitment as a potential mechanism for IFNε-mediated protection. Using WT and IFNε-/- mice and rIFNε, I show that IFNε deficiency results in a reduction, and exogenous IFNε leads to a trend towards an increase, in the number of NK cells present in the upper RT during

Chlamydia infection (Figure 2.3 A). Whilst IFNε-/- mice also exhibited a trend towards a reduction in the number of neutrophils present in the upper RT at 3dpi (Figure 2.3 H), this did not reach significance and NK cells were the most abundant cell type at this time-point. This may be due to the small n used (n=4) and the kinetics of the

137 inflammatory response, as neutrophilic inflammation is known to peak at 7dpi

(Morrison and Morrison, 2000) and is important in the development of oviduct pathology later during infection (Shah et al., 2005). As such, the role of IFNε in neutrophil responses will be investigated further in future studies.

Using microarray-based techniques, I show that IFNε uniquely regulates the expression of 744 genes at baseline and 802 genes during Chlamydia infection, and universally alters the transcription of 61 genes regardless of infection status, in the female RT (Figure 2.4). In IFNε-/- mice, the vast majority of dysregulated transcripts were down-regulated, particularly during infection. This suggests that IFNε not only induces the baseline expression of a number of genes but that it also primes for the rapid induction of factors that are potentially involved in host responses to Chlamydia infection in the female RT.

IPA® analysis revealed that many of these genes are involved in immune regulatory processes. Notably, these included NK cell and innate immune signalling pathways, providing further evidence for the involvement of NK cell responses in IFNε- mediated protection (Table 2.3). Molecular networks identified via IPA® analysis also provided evidence for the induction of NK cell responses by IFNε. The most significant network (based on p-scores calculated during IPA® analysis) associated with genes down-regulated in IFNε-/- mice at baseline involved several factors related to NK cell function, development, and signalling, including Klra7, KLRB1, Klrk1, and EOMES

(Figure 2.5). Significantly, KLRB1 codes for the pan-NK cell marker, NK1.1, used to identify NK cells in our flow cytometry experiments. The Klrk1 gene encodes the activating NK cell receptor, NKG2D, which recognises induced-self proteins that are overexpressed on infected, transformed, or stressed cells and promotes their cytolytic destruction. Klra7 encodes for the NK cell receptor Ly49G which plays a role in the

138 recognition of MHC-I molecules. Additionally, the EOMES gene encodes for the T-box transcription factor, eomes, which is highly expressed in NK cells and is essential for their maturation (Gordon et al., 2012). The most significant network associated with commonly down-regulated transcripts also contained the two NK cell-related genes,

GZMK, which encodes the tryptase serine protease, granzyme K, contained in the cytolytic granules of activated NK cells and cytotoxic T cells (Shresta et al., 1997), and

Klra16, which codes for Ly49P, another MHC-I receptor important for recognising infected cells (Desrosiers et al., 2005) (Figure 2.7). Importantly, the decrease in abundance of these factors correlates with the reduction in NK cell numbers observed in

IFNε-/- mice.

Previous studies have demonstrated the protective role of NK cells in the host response to Chlamydia RTIs as well as respiratory tract infections (Jiao et al., 2011;

Tseng and Rank, 1998). NK cells are thought to protect against Chlamydia via IFNγ production early during infection and the promotion of Th1 responses and may be capable of recognising/lysing infected cells (Hook et al., 2004; Jiao et al., 2011; Tseng and Rank, 1998). Based on my findings and these previous studies, I decided to investigate the role of IFNε-mediated innate NK cell responses in protection against

Chlamydia infection in the female RT in more detail in Chapter 3.

Molecules associated with IFNγ responses were also identified via network analysis of genes universally down-regulated in IFNε-/- mice compared to WT controls

(Figure 2.7) and, intriguingly, genes up-regulated in IFNε-/- mice compared to WT controls during infection and regardless of infection status (Figure 2.9 & 2.10). SOCS1 is a hub molecule for the most significant network identified during the analysis of down-regulated genes. Investigation of the relationships between SOCS1 and the other factors contained in this network revealed that it primarily plays a role in the inhibition

139 of their activation/signalling pathways (STAT1 (Starr et al., 1997), IFNAR1 (Piganis et al., 2011), IRG1 (Carow et al., 2011)), indicating that it may be responsible for the down-regulation of these responses. SOCS1 is also known to be a potent inhibitor of

IFNγ responses via inhibition of JAK/STAT signalling (Alexander et al., 1999; Federici et al., 2002). Interestingly, IFNγ featured as a hub molecule in networks associated with genes up-regulated in IFNε-/- mice, both during infection and regardless of infection status. Again, examination of the relationships between IFNγ and the up-regulated focus molecules revealed inverse relationships, where IFNγ is known to decrease their expression (SCGB3A1 (Yamada et al., 2005), ADM (Isumi et al., 1998), FGF12

(Hamby et al., 2012)). The increase seen in these factors indicates that IFNγ may be diminished in IFNε-/- mice, providing justification for further examination of IFNγ- responses in IFNε-mediated protection. Importantly, NK cells have been shown to be the primary source of IFNγ early during Chlamydia RTIs and the production of IFNγ is thought to be the mechanism by which NK cells mediate their protective effects (Jiao et al., 2011; Murthy et al., 2011; Perry et al., 1999a; Tseng and Rank, 1998), suggesting that these changes may be linked to the decrease in NK cells observed in IFNε-/- mice.

Network analysis also allowed us to identify novel factors that may be involved in

IFNε-mediated protection. Molecules with high levels of interconnectivity with other dysregulated factors may be central to the responses downstream of IFNε that protect against Chlamydia infections. The presence of IL-1β as a hub molecule in the most significant network linked to down-regulated transcripts in Chlamydia-infected IFNε-/- mice (Figure 2.6) suggests that IFNε may also prime for IL-1β activation in response to infection. Pro-IL-1β is cleaved into its active form by caspase-1 and others have shown that Chlamydia induce this response via activation of the NLRP3 inflammasome

(Abdul-Sater et al., 2010; Prantner et al., 2009). However, the role of this signalling axis

140 in Chlamydia infections is controversial, as loss-of-function studies have demonstrated divergent effects for each of its components (Nagarajan et al., 2012). For example, caspase-1 activation and IL-1β responses have been associated with both increased

Chlamydia infection and growth in vitro (Abdul-Sater et al., 2009), and protection against infection and worsened pathology in vivo (Nagarajan et al., 2012; Prantner et al.,

2009; Shimada et al., 2011). Thus, based on these findings, I sought to investigate the role of the Chlamydia-induced NLRP3 inflammasome/caspase-1/IL-1β axis in IFNε- mediated protection in order to better understand the complex relationship between these factors and protection against Chlamydia infection (Chapter 4).

IPA® analysis of transcripts down-regulated in IFNε-/- mice at baseline also identified pathways associated with leukocyte haematopoiesis, infiltration, and signalling (Table 2.3). Pathways associated with host defence were also down-regulated in Chlamydia-infected IFNε-/- mice compared to WT controls (Table 2.4). Not surprisingly, many of these were related to innate immune processes, such as PRR signalling and IRF activation. Interestingly, several pathways associated with neutrophil, macrophage, and T cell function (IL-8, TREM1, and OX40 signalling and

Differential Regulation of Cytokine Production in Macrophages and T Helper Cells by

IL-17A and IL-17F) were also identified during analysis of transcripts down-regulated in IFNε-/- mice during infection, however, numbers of these cells were not significantly altered at this time-point. Nevertheless, future studies will determine the effect of IFNε on the function of these cells by assessing their activation in IFNε-/- mice and infiltration at later time-points. Transcripts down-regulated in IFNε-/- mice regardless of infection status were only significantly associated with the one pathway, the Role of IL-17A in

Psoriasis (Table 2.5). This association was based on the dysregulation of S100A8 and

S100A9.

141 I also show that several metabolic pathways are down-regulated during IFNε deficiency, highlighting the intimate relationship between host metabolism and defence.

At baseline, these include LXR/RXR Activation, Glutathione-mediated Detoxification, and Aryl Hydrocarbon Receptor Signalling (Table 2.3). Metabolic pathways are also highly represented in the analysis of down-regulated transcripts in IFNε-/- mice during

Chlamydia infection, most of these involving the same set of 3-5 genes (e.g. Nicotine and Melatonin Degradation and Oestrogen Biosynthesis; Table 2.4). The potential role of these pathways, in light of subsequent findings, will be discussed further in Chapter

5. Additionally, biological processes related to apoptosis and cell cycle progression were dysregulated in IFNε-/- mice during infection (Table 2.4). This may indicate that the cell death pathways that normally occur in response to infection are dysfunctional in the absence of IFNε.

Conversely, few pathways were significantly associated with the factors up- regulated in IFNε-/- mice compared to WT controls and most of those identified are not primarily involved in mediating immune processes. However, several pathways related to lipid metabolism (Triacylglycerol and Stearate Biosynthesis) were universally up- regulated in IFNε-/- mice (Table 2.8). Interestingly, Prostanoid Biosynthesis was also up-regulated in IFNε-/- mice during infection (Table 2.7). Activation of lipid metabolism by C. trachomatis has been shown to induce the biosynthesis of prostanoids

(Fukuda et al., 2005), indicating that the regulation of Prostanoid Biosynthesis by IFNε may be mediated via alterations to lipid metabolism. Pathways associated with cellular organisation-related signalling, including Ephrin B (Table 2.8) and RhoGDI (analysis of genes up-regulated at baseline; Table 2.6) Signalling, were also up-regulated during

IFNε deficiency, which could indicate dysregulation of cell-to-cell contacts in these mice. Curiously, Melatonin Degradation was also identified during analysis of genes

142 up-regulated in IFNε-/- mice at baseline (Table 2.6), however, this association was based on the dysregulation of the one factor, MPO, a lysosomal enzyme contained in neutrophil granules. As neutrophil infiltration was not significantly altered by IFNε during Chlamydia infection (Figure 2.3 H), the role of neutrophils in IFNε-mediated protection was not examined further, however, I aim to explore the effects of IFNε on neutrophil function in futures studies. Additionally, Haem and Tetrapyrrole

Biosynthesis were up-regulated in IFNε-/- mice during infection (Table 2.7), which could represent changes in the production of haemoproteins or cytochromes involved in the generation of ATP. Interestingly, MPO also contains a haem pigment which is responsible for the green colour of secretions rich in neutrophils, indicating that the dysregulation of these factors may be linked. Factors related to Circadian Rhythm

Signalling were also up-regulated in IFNε-/- mice during infection (Table 2.7). This could be due to the crosstalk between circadian and immune signalling pathways

(Fukuda et al., 2005).

Owing to time constraints, I could not explore all the pathways/networks identified during my PhD studies, however, these are being followed up as part of other ongoing research projects. The importance of, and potential future directions guided by, these findings are discussed further in Chapter 5 (General discussion and conclusions).

143 : Role of NK cells in IFNε-mediated

protection against Chlamydia RTI

3.1 Abstract

In previous studies, we demonstrated that IFNε is constitutively expressed in the female RT and protects against Chlamydia infections from the earliest stages of infection. Importantly, I have shown that Chlamydia-infected, IFNε-/- mice exhibit a decrease in the number of NK cells present in the female RT at 3dpi (Chapter 2).

Here, I examine the effects of IFNε on local and systemic NK cell responses to elucidate the role of IFNε-mediated NK cell responses in protection against Chlamydia infections in the female RT. Uterine horn, spleen, and bone marrow tissues were harvested from Chlamydia or sham-infected female WT and IFNε-/- mice and the effects of IFNε deficiency on local and systemic NK cell responses assessed. IFNε-/- mice exhibit a decrease in the number and activation (CD69+) of, and IFNγ-production by,

NK cells in the female RT during Chlamydia infection, and a reduction in the number of

NK cells present in the spleen regardless of infection status. Interestingly, I show that

IFNε-/- mice also have a reduction in the number of mature NK cells present in the bone marrow. This corresponds with a reduction in the uterine expression of a number of cytokines and chemokines that are associated with the development and/or chemoattraction of NK cells. Depletion of NK cells in WT mice had a similar effect on the number of total, but not activated, NK cells present in the female RT during

Chlamydia infection to that observed during IFNε deficiency. This reduction in NK cell numbers corresponded with an increase in Chlamydia replication, however, the level of infection in NK cell-depleted, WT mice was much lower than that observed in IFNε-/-

144 mice. This suggests that activation of NK cells by IFNε may be more important than

IFNε-mediated NK cell haematopoiesis and chemoattraction in mediating protective effects against Chlamydia.

Taken together, my findings suggest that IFNε protects against Chlamydia infection of the female RT not only by mediating NK cell haematopoiesis and recruitment but, perhaps most importantly, by also strongly promoting local NK cell activation and IFNγ production in the uterus.

145 3.2 Introduction

Chlamydia infections frequently cause severe RT sequelae in women, such as

PID, tubal infertility and ectopic pregnancy. However, the immune processes involved in the clearance versus immunopathology of Chlamydia infections are complex and require further investigation.

Robust Th1 and IFNγ responses are known to promote clearance of Chlamydia and protect against pathology. IFNγ-/-, IFNγR-/-, and IL-12-/- mice display increased

Chlamydia load and dissemination and decreased clearance of infection during both reproductive and respiratory tract Chlamydia infections (Cotter et al., 1997; Johansson et al., 1997a; Perry et al., 1997). Furthermore, increased expression of IFNγ and IL-12 by cervical mucosal cells and peripheral lymphocytes in women is associated with reduced risk of infection, fertility disorders, and PID (Agrawal et al., 2009; Cohen et al.,

2005; Debattista et al., 2002a).

The anti-Chlamydia effects of IFNγ are mediated by expression of the effector molecules, iNOS (Igietseme, 1996; Rottenberg et al., 1999; Zhang et al., 2012) and IDO

(Byrne et al., 1986; Murray et al., 1989; Rapoza et al., 1991). The expression of iNOS can be induced in a wide variety of cells, such as epithelial cells, macrophages, and fibroblasts, and results in the generation microbicidal nitric oxide (NO), which inhibits

Chlamydia growth (Igietseme, 1996; Rottenberg et al., 1999; Zhang et al., 2012).

Importantly, iNOS-/- mice exhibit delayed clearance and more severe pathology during

C. muridarum RTIs than WT controls (Ramsey et al., 2001a). IDO inhibits Chlamydia growth by catabolising tryptophan, an essential metabolite of Chlamydia (Byrne et al.,

1986; Murray et al., 1989; Rapoza et al., 1991). Rapoza et al. showed that the inhibition of C. trachomatis growth by IFNγ treatment in conjunctival epithelial cells correlates with increased IDO expression, with inhibition of infection reversed by supplementing

146 the media with exogenous tryptophan (Rapoza et al., 1991), however, the role of IDO in

IFNγ-mediated protection against Chlamydia in the murine host is open for debate

(Nelson et al., 2005). IFNγ may also protect against Chlamydia infections and their associated pathologies by regulating the Th1/Th2 balance, as IFNγ-/- mice have been shown to have increased Th2 cytokine-dependent immunopathology and fail to clear

Chlamydia during C. muridarum respiratory tract infections (Wang et al., 1999b).

Significantly, the production of IFNγ during the innate immune response has been shown to play an important role in controlling Chlamydia infections. RAG-1-/-/IFNγR-/- mice, which are both deficient in mature T and B cells and unable to respond to IFNγ, are more susceptible to C. pneumoniae respiratory tract infections than mice deficient in

RAG-1 alone, which demonstrates the importance of IFNγ production by innate cells for protection against Chlamydia infections (Rottenberg et al., 2000). Importantly, studies have shown that NK cells are the predominant source of IFNγ early during

Chlamydia RTIs, with NK cell depletion resulting in diminished IFNγ expression, a shift from a Th1-dominant to a Th2-dominant response, and delayed clearance (Tseng and Rank, 1998). NK cells have also been shown to play a role in protection against

Chlamydia respiratory tract infections, with NK cell-depleted mice having increased

Chlamydia load and more severe neutrophilic inflammation and weight loss during C. muridarum respiratory tract infections (Jiao et al., 2011). This may be due to the priming effect of innate, NK cell-mediated IFNγ production on the development of protective Th1 responses, as NK cells from C. muridarum infected mice were shown to stimulate DCs to produce IL-12 via the secretion of IFNγ and NKG2D signalling, while

DCs from NK cell-depleted mice were shown to be unable to prime Th1 development

(Jiao et al., 2011).

147 Chlamydia induces the mobilisation and activation of NK cells by stimulating the production of cytokines by immune cells and epithelial cells and modulating the expression of activating and inhibitory receptors on both host and accessory cells.

Exposure to these stimuli activates NK cells to produce cytokines and primes for their cytolytic activity. In co-culture experiments, C. trachomatis infection has been shown to promote the production of IFNγ by NK cells by triggering the production of IL-18 by epithelial cells and IL-12 by DCs (Hook et al., 2005). C. trachomatis infection has also been shown to decrease the expression of MHC-I and increase the expression of MICA on epithelial cells, making them susceptible to NK cell-mediated cytotoxicity (Hook et al., 2004; Ibana et al., 2012). However, the role of NK cell cytotoxicity in protection against Chlamydia infections is unclear, as perforin-/- mice clear C. muridarum RTIs at a similar rate to WT controls (Murthy et al., 2011; Perry et al., 1999a).

Significantly, type I IFNs have been shown to play an important role in regulating

NK cell responses via direct and indirect mechanisms. Protective NK cell responses have been shown to be dependent on type I IFN signalling during adenoviral (Zhu et al.,

2008) and vaccinia viral (Martinez et al., 2008) infections. The recruitment, proliferation, and lytic activity of, and production of IFNγ and cytolytic proteins by, NK cells upon TLR stimulation has been shown to be dependent on IFNα/β signalling and activation of STAT1, which induces the expression of IL-15 by DCs (Lucas et al.,

2007). However, type I IFN signalling has also been shown to mediate NK cell cytotoxicity and IFNγ production via IL-15-independent mechanisms, during mCMV and HSV-2 infections, respectively (Gill et al., 2011; Nguyen et al., 2002). Additionally, type I IFN signalling induces expression of the potent NK cell chemoattractant,

CXCL10, mediating the recruitment of NK cells to sites of immune response (Vanguri and Farber, 1990).

148 In Chapter 2, I demonstrate that IFNε protects against Chlamydia infection in the female RT from the earliest stages of infection, suggesting that it plays an important role in potentiating protective innate responses. The results from my flow cytometry- based immune cell and microarray-based gene expression profiling experiments suggest a potential role for NK cells in IFNε-regulated protective responses. Here, I expand on the findings described in Chapter 2 to show that IFNε augments the infiltration and activation of, as well as the production of IFNγ by, NK cells in the female RT during

Chlamydia infection. I also show that IFNε promotes the production of mature NK cells in the bone marrow and increases systemic NK cell numbers. These increased NK cell responses correspond with an increase in the expression of NK cell chemoattractants and factors involved in NK cell development in the uterus. Additionally, I show that depletion of NK cells leads to an increase in Chlamydia infection in the upper female

RT. These findings provide evidence for a strong link between IFNε and NK cell responses in host protection against Chlamydia female RTIs.

149 3.3 Methods

3.3.1 Ethics statement

Council (Australia). All protocols were approved by the University of Newcastle

Animal Care and Ethics Committee.

3.3.2 C. muridarum female RTI

Adult (6-8 weeks old) female WT or IFNε-/-, C57BL/6 mice were pre-treated with 2.5mg DMPA (Depo-Provera; Pfizer) SC to prime for infection and synchronise their oestrous cycles. Seven days later, mice were infected IVAG with 5 x 104ifu C. muridarum (ATCC VR-123) in 10μL SPG or sham-infected with SPG alone under ketamine:xylazine anaesthesia (80mg/kg:5mg/kg IP; Ilium Ketamil® and Ilium Xylazil-

20®; Troy Laboratories), as described previously (Asquith et al., 2011). Mice were sacrificed by sodium pentobarbital (Lethabarb; Virbac) overdose at 3dpi and tissues collected for the analysis of NK cell responses.

3.3.3 In vivo NK cell depletion

To deplete NK cells systemically, WT mice were administered 20μL reconstituted anti-asialo ganglio-N-tetrasylceramide (ASGM1) antiserum, and WT and

IFNε-/- controls administered 20μL normal rabbit serum (Wako Pure Chemical

Industries, Novachem, Collingwood, VIC, Australia), in 200μL RPMI 1640 media IP on days -2, 0 and 2 (depletion prior to and throughout infection) or on days 1 and 2

150 (depletion during infection only; Figure 3.1). Successful systemic depletion was confirmed via flow cytometric analysis of splenocytes and bone marrow (Appendix C: sFigure 3.1 & 3.2).

Figure 3.1: In vivo systemic natural killer (NK) cell depletion during Chlamydia muridarum female reproductive tract infection (RTI). Wild-type (WT) and interferon (IFN)ε-/- C57BL/6 mice were pre- treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with C. muridarum or sham-infected with sucrose-phosphate-glutamate buffer (SPG). Mice were administered anti-asialo GM1 (ASGM1) NK cell depleting antibody (WT only) or normal rabbit serum control intraperitoneally (IP) at -2, 0, and 2dpi, to deplete NK cells systemically prior to and throughout infection, or at 1 and 2dpi, to deplete NK cells systemically post infection. Mice were sacrificed at 3dpi to assess and compare the effects of systemic NK cell depletion and IFNε deficiency on NK cell responses and infection in the upper reproductive tract (RT).

3.3.4 Flow cytometry

Uterine horn tissue was excised and digested by gently dissociating in 5mL

HEPES buffer using C tubes and a gentleMACS™ Dissociator (Miltenyi Biotech) then incubating with 2mg/mL collagenase-D and 40U/mL DNase I (Roche) at 37°C for 30 minutes. Cells were then passed through a 70μm nylon cell strainer to remove debris and incubated with RBC lysis buffer at 4°C for 5 minutes. Total cell numbers were

151 enumerated by trypan blue exclusion using a Countess™ automated cell counter

(Invitrogen) and single cell suspensions placed in a 96 well plate at 0.5-3 x 106 cells/well, based on frequency of the target cell population.

Cells were then incubated with 10ng/mL mouse Fc receptor block (anti-mouse

CD16/32; BD Biosciences) in 100μL FACS buffer at 4°C for 15 minutes and stained for a combination of the surface markers CD45, CD3, NK1.1, CD122, CD49b, CD69,

CD11b, CD117, CD127, CD135, B220, and GR1 (Biolegend or BD Biosciences) by incubation with fluorochrome (FITC, PE, PerCP, APC, APC-Cy7, PE-Cy7, Pacific

Blue™, PE-CF594, Alexa Fluor® [AF]700, Brilliant Violet™ [BV]421, BV510,

BV605 or BV650)- or biotin-conjugated antibodies at 4°C for 20 minutes (Table 3.1).

Samples incubated with biotin-conjugated antibodies were subsequently stained with streptavidin-conjugated fluorochromes (Table 3.1). Optimal concentrations for all antibodies and streptavidin-conjugated fluorochromes were determined by prior titration experiments. Stained cells were then washed, fixed in 4% paraformaldehyde and analysed by flow cytometry using a FACSCanto™ II or FACSAria™ III, depending on laser/detector requirements, and FACSDiva software (BD Biosciences) (Beckett et al.,

2012). The percentages and total numbers of different immune cell populations present were determined using FSC and SSC and characteristic surface marker expression profiles (Table 3.2) (Beckett et al., 2012; Yadi et al., 2008).

To assess the capacity of cells from WT and IFNε-/- mice to produce the cytokine IFNγ, single cell suspensions were stimulated with 1μg/mL ionomycin and

50ng/mL phorbol 12-myristate 13-acetate (PMA), in the presence of 5μg/mL of the

Golgi complex inhibitor, Brefeldin A (Sigma-Aldrich), in 200μL supplemented RPMI

1640 media (10% FBS, 2mM L-glutamine, 2mM sodium pyruvate, 100μg/ml penicillin,

100μg/ml streptomycin, 50μM 2-mercaptoethanol; Gibco®, Thermo Fisher Scientific)

152 for 5 hours (Essilfie et al., 2012). Cells were then blocked and stained for extracellular antigens as above and fixed in 4% paraformaldehyde at 4°C for 30 minutes. Cells were then permeablised using saponin buffer (0.25% saponin in FACS buffer; 10 minutes) and stained with anti-IFNγ (Biolegend) for 30 minutes at room temperature. Anti-IFNγ stained cells were compared to pooled isotype control antibody stained samples for each group, to account for non-specific binding. Cells were washed and fixed in 4% paraformaldehyde until analysis (as above).

Table 3.1: Staining cocktails used for flow cytometric analysis of natural killer (NK) cell responses

NK cell function stain Uterine (u)NK cell Splenic NK cell NK cell progenitor stain function stain stain CD3-APC CD3-APC CD3-APC CD117-APC CD69-FITC CD49b-FITC CD49b-FITC CD49b-FITC CD45-PerCP CD45-PerCP CD45-PerCP CD11b-PerCP IFNγ-PE IFNγ-PE B220-PE & CD135-PE NK1.1-PE-Cy7 NK1.1-PE-Cy7 NK1.1-PE-Cy7 NK1.1-PE-Cy7 CD122-Biotin CD122-Biotin CD122-Biotin CD69-PE-CF594 CD127-BV605 CD3-AF700 GR1-APC-Cy7

Streptavidin-BV421 Streptavidin-BV605 Streptavidin-BV421

Table 3.2: Characterisation of immune cell populations

Cell type Surface marker expression FSC/SSC profile Leukocyte CD45+ IFNγ+/- T cell CD45+ CD3+ IFNγ+/- FSClow-int SSClow Natural killer (NK) cell CD45+ CD3- NK1.1+ IFNγ+/- CD69+/- FSClow-int SSClow Uterine (u)NK cell CD45+ CD3- NK1.1- CD49b- CD122+ FSClow-int SSClow Precursor NK cell CD45+ Lin (CD3, B220, GR1, CD11b)- CD135- CD117- FSClow SSClow /low CD127+ CD122+ NK1.1- CD49b- Immature NK cell CD45+ Lin- CD122+ NK1.1+ CD11b- FSClow-int SSClow Mature NK cell CD45+ CD3- CD122+ NK1.1+ CD11b+ FSClow-int SSClow

153 3.3.5 Total RNA extraction

Uterine horn tissue was harvested from mice, immediately snap frozen and stored at -80°C until RNA extraction performed for subsequent real-time qPCR analysis.

Total RNA was extracted from uterine tissue using TRIzol® Reagent (Thermo

Fisher Scientific) according to the manufacturer’s instructions. Briefly, uterine horn tissue was homogenised in TRIzol® using a Tissue-Tearor (BioSpec Products) and cleared of debris by centrifugation. Chloroform was then added and homogenates incubated at room temperature for 10 minutes. Samples were centrifuged and isopropyl alcohol added to the aqueous phase. Precipitated RNA was then washed twice with 75% ethanol and resuspended in nuclease-free dH2O. Concentration and purity of RNA samples were quantified using a NanoDrop™ 1000 Spectrophotometer (Thermo Fisher

Scientific).

3.3.6 Reverse transcription and real-time qPCR

1µg total RNA was treated with DNase I in a reaction volume of 10µL for 15 minutes at room temperature (Sigma-Aldrich), then the reaction was stopped via the addition of stopping solution and incubation at 65°C for 10 minutes. RNA was then reverse transcribed using BioScript™ reverse transcriptase enzyme and random hexamer primers (Bioline), according to the manufacturer’s instructions and as previously described (Starkey et al., 2013). Briefly, 2µL 50ng/µL random hexamer primers and 1µL 10mM dNTP mix (Bioline) were added to the RNA and incubated at

65°C for 5 minutes. 4µL 5X reaction buffer (Bioline), 1µL 0.1mM DTT (Invitrogen),

1µL nuclease free H2O, and 1µL BioScript™ (Bioline) were then added to the reaction and incubated at 25°C for 20 minutes, 42°C for 50 minutes, and 70°C for 15 minutes.

154 DNA was then resuspended in nuclease free H2O up to a volume of 100µL and stored at

-20°C until qPCR analysis.

Real-time qPCRs were performed using custom designed primers (Appendix A: sTable 1.1; IDT) with SYBR Green Supermix (KAPA Biosystems) in a 12.5µL reaction on a Mastercycler® ep realplex2 system (Eppendorf). Cycling conditions were

50°C for 2 minutes, 95°C for 2 minutes, and 40 cycles of 95°C for 15 seconds and 55-

65°C (based on results of prior temperature gradient experiments) for 1 minute, followed by dissociation analysis (Horvat et al., 2010; Phipps et al., 2007). Expression levels of target genes relative to the housekeeping gene control, HPRT, were then calculated.

3.3.7 Chlamydia load

Total RNA was extracted from uterine horn tissue and Chlamydia 16S rRNA expression relative to HPRT determined via real-time qPCR as previously described

(Asquith et al., 2011; Fung et al., 2013). Primers used are described in Appendix A: sTable 1.1.

3.3.8 Immunoblot analysis

Uterine horn tissue was harvested from mice and stored in radioimmunoprecipitaion assay (RIPA) buffer supplemented with cOmplete™ Mini protease inhibitors and phosSTOP phosphatase inhibitors (Sigma-Aldrich) at -80°C until protein isolation performed for subsequent immunoblot analysis.

Whole protein was isolated from uterine tissue by homogenising samples in fresh supplemented RIPA buffer and centrifuging to clear the lysate. Protein

155 concentration was determined via bicinchoninic acid (BCA) assay (Thermo Fisher

Scientific).

Protein samples (35µg) were denatured in Laemmli buffer and resolved on 4-

15% gradient Mini-PROTEAN® TGX Stain-Free™ polyacrylamide gels with Precision

Plus Protein™ WesternC™ Standards (Bio-Rad, CA, USA). Proteins were then transferred onto PVDF membranes and blocked with 5% bovine serum albumin (BSA) in Tris-buffered saline with 0.05% Tween 20 (TBS-T) overnight. Blots were incubated with primary antibodies (anti-IL-15 [ab7213; Abcam, Cambridge, MA, USA], anti-β- actin [ab70165; Abcam] antibodies) in TBS-T overnight, washed, then incubated with anti-rabbit IgG HRP secondary antibody (R&D Systems, Minneapolis, MN, USA) and

Precision Protein™ StrepTactin-HRP Conjugate (Bio-Rad) in TBS-T for 2 hours. Blots were developed with SuperSignal® West Femto Maximum Sensitivity Substrate

(Thermo Fisher Scientific) and visualised on a ChemiDoc™ MP imaging system (Bio-

Rad) (Kim et al., 2016).

3.3.9 Statistics

All data are presented as mean ± SEM. Statistical significance for comparisons between two groups was determined using unpaired t-Tests, or non-parametric equivalent, where appropriate. Statistical significance for comparisons between three or more groups was determined by one-way ANOVA with appropriate post-hoc test, or non-parametric equivalent, where appropriate. Statistical analyses were performed using

GraphPad Prism 6 software.

156 3.4 Results

3.4.1 IFNε deficiency decreases NK cell responses in the

female RT

To investigate the role of NK cells in IFNε-mediated protection against

Chlamydia infection in the female RT, I performed a more focussed series of flow cytometric analyses, expanding on those described in Chapter 2, to examine the cellular composition of uterine homogenates from Chlamydia-infected WT and IFNε-/- mice at

3dpi. These analyses allowed us not only to investigate the effects of IFNε on NK cell number, activation, and IFNγ production, but also to determine whether IFNε affects tissue-resident uNK cell responses.

My data from this focussed analysis confirmed and extend upon the preliminary findings outlined in Chapter 2. Using a more thorough classification strategy which includes the pan-leukocyte marker, CD45, and, not only NK1.1 and CD3, but also

CD122 and CD49b for the determination of both recirculating cNK cells and tissue- resident uNK cells, I show that cNK cells make up 2.5% of all cells in the uterus and are

7-fold more abundant than uNK cells in Chlamydia-infected, progesterone-pre-treated

WT mice at 3dpi (Figure 3.2). By staining for the early activation marker, CD69, I also show that, in WT mice, 35% of these cNK cells are activated (CD69+; Figure 3.2).

I show that the numbers of cNK cells present are significantly reduced, when expressed both as a percentage of viable cells (Figure 3.2 A) and as total numbers present (Figure 3.2 D), in uterine tissue from IFNε-/- mice compared to that of WT controls. This represents a reduction of approximately 40% in the total number of NK cells present in the upper RTs IFNε-/- mice (Figure 3.2 D). I also show that IFNε-/- mice have fewer uNK cells in their upper RTs compared to WT controls, both as a percentage

157 of viable cells (Figure 3.2 B) and total numbers (Figure 3.2 E). Additionally, I show that IFNε-/- mice have a significant reduction in both the percentage of viable cells

(Figure 3.2 C) and total numbers of cells (Figure 3.2 F) identified as activated CD69+

NK cells. Representative flow cytometric plots of these NK cell populations in WT and

IFNε-/- mice are provided in Appendix C: sFigure 3.3.

I also show that, in WT mice, NK cells represent 40% of all IFNγ-producing leukocytes and that IFNγ-producing NK cells are 5-fold more abundant than IFNγ- producing T cells at this time-point (Figure 3.3). Importantly, I show that the number of

IFNγ-producing NK cells, represented as both a percentage of viable cells (Figure 3.3

A) and the total number present in uterine homogenates (Figure 3.3 E), is significantly decreased in IFNε-/- mice compared to WT controls. This represents a reduction in the total number of IFNγ-producing NK cells of approximately 50% (Figure 3.3 E). As NK cells can influence T cell polarity and T cells are another important source of IFNγ during Chlamydia infection, I next sought to assess the effect of IFNε on IFNγ production by these cells. While the total number of T cells present in the upper RT was not altered between WT and IFNε-/- mice (data not shown), the number of IFNγ- producing T cells is significantly reduced in the upper RTs of IFNε-/- mice, both as a percentage of viable cells (Figure 3.3 B) and total number present (Figure 3.3 F), compared to WT controls. This decrease in IFNγ-producing NK and T cells in IFNε-/- mice correlates with a decrease in the total number of IFNγ-producing leukocytes present in the RT, as a percentage of viable cells (Figure 3.3 C) and total number

(Figure 3.3 G). Representative flow cytometric plots demonstrating IFNγ expression by these cell types in WT and IFNε-/- mice are provided in Appendix C: sFigure 3.4.

Significantly, the reduced numbers of IFNγ+ cells in IFNε-/- mice is also associated with a decrease in IFNγ expression in the uterus during infection (Figure 3.3 D).

158 To determine if the decrease in activated and IFNγ-producing NK cells observed in IFNε-/- mice is due to a preferential accumulation of a particular population of

CD69+/- IFNγ+/- NK cells (due to changes in local activation or chemoattraction of a particular population) in response to IFNε, total numbers and proportions of the two single positive, double positive, and double negative populations of NK cells in the uterine tissue of WT and IFNε-/- mice were also assessed. I show that IFNε-/- mice have fewer IFNγ+ CD69- (Figure 3.4 A & E) and IFNγ- CD69+ (Figure 3.4 B & F) single positive and IFNγ+ CD69+ double positive (Figure 3.4 C & G) NK cells in their upper

RTs. Curiously, however, there is no difference between the number of IFNγ- CD69- double negative NK cells in IFNε-/- mice compared to WT controls (Figure 3.4 D & H).

The frequency of these populations was also calculated in order to demonstrate the shift in the makeup of NK cells in the RTs of Chlamydia-infected IFNε-/- mice compared to

WT controls (Figure 3.4 I). The data show that IFNε deficiency results in a consistent reduction in the number of activated and IFNγ-producing NK cells, and an increase in the proportion of IFNγ- CD69- NK cells, present in the female RT during Chlamydia infection.

159 A B C

4 0.5 1.5

0.4 3 1.0 0.3 2 * 0.2 * 0.5 * NK (%) Cells

1 (%) Cells uNK 0.1 CD69+ (%) NK Cells

0 0.0 0.0

-/- -/- -/- WT ε WT ε WT ε IFN IFN IFN

D E F

2.0× 10 4 1.5× 10 3 6.0× 10 3

1.5× 10 4 1.0× 10 3 4.0× 10 3

4 * 1.0× 10 *

NK Cells * 2 3 uNK Cells uNK 5.0× 10 2.0× 10 5.0× 10 3 CD69+ NK Cells NK CD69+

0 0 0

-/- -/- -/- WT ε WT ε WT ε IFN IFN IFN

Figure 3.2: Interferon (IFN)ε deficiency decreases the number and activation of conventional natural killer (NK) cells and tissue-resident uterine (u)NK cells in the female reproductive tract (RT) during Chlamydia infection. Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum. Percentages (of viable cells) and total numbers of conventional NK cells (A & D), uNK cells (B & E), and CD69+ NK cells (C & F) in uterine tissues were quantified via flow cytometry at 3dpi to assess the effect of IFNε deficiency on NK cell numbers and activation in the upper RT (three experiments; n≥15 replicates of pooled uterine homogenate samples). All data are presented as mean±SEM. *=p<0.05.

160 A B C D

1.5 0.25 3 0.020

0.20 0.015 1.0 2 0.15 * 0.010 * 0.10

* +T C ells(% ) + NK Cells (%) NK Cells + 0.5 γ * 1 γ + Leukocytes (%) 0.005 γ

IFN 0.05 IFN IFN

0.0 0.00 0 HPRT) (to Expression Relative 0.000 γ

-/- -/- -/- -/- WT ε WT ε WT ε WT ε IFN IFN IFN IFN IFN

E F G

8.0× 10 3 1.5× 10 3 1.5× 10 4

6.0× 10 3 1.0× 10 3 1.0× 10 4

4.0× 10 3 * + T C ells + NK Cells + γ γ * 5.0× 10 2 + Leukocytes 5.0× 10 3 * γ × 3 IFN IFN 2.0 10 IFN

0 0 0

-/- -/- -/- WT ε WT ε WT ε IFN IFN IFN

Figure 3.3: Interferon (IFN)ε deficiency decreases the number of IFNγ-producing natural killer (NK) cells and level of IFNγ expression in the female reproductive tract (RT) during Chlamydia infection. Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum. Percentages (of viable cells) and total numbers of IFNγ+ NK cells (A & E), T cells (B & F), and total leukocytes (C & G) in uterine horn tissues were quantified via intracellular cytokine staining and flow cytometry (three experiments; n≥15 replicates of pooled uterine homogenate samples) and IFNγ messenger (m)RNA expression (D) was quantified via qPCR (one experiment; n≥5) at 3dpi to assess the effect of IFNε deficiency on IFNγ production by immune cells in the upper RT. Target gene mRNA expression was normalised against expression of the housekeeping gene control, hypoxanthine-guanine phosphoribosyltransferase (HPRT). All data are presented as mean±SEM. *=p<0.05.

161 A B C D

0.8 0.5 0.6 1.5

0.4 0.6 0.4 1.0 0.3 0.4 * * 0.2 * 0.2 0.5 0.2 - CD69- NK Cells (%) NK Cells CD69- - + CD69- NK (%) Cells - CD69+ - NK(%) Cells 0.1 + CD69+ NK (%) Cells γ γ γ γ IFN IFN IFN 0.0 0.0 IFN 0.0 0.0

-/- -/- -/- -/- WT ε WT ε WT ε WT ε IFN IFN IFN IFN

E F G H

4.0× 10 3 2.5× 10 3 2.5× 10 3 6.0× 10 3

2.0× 10 3 2.0× 10 3 3.0× 10 3 4.0× 10 3 1.5× 10 3 1.5× 10 3 2.0× 10 3 * 1.0× 10 3 ** 1.0× 10 3 * 2.0× 10 3 - CD69- NK Cells NK CD69- - - CD69+ NK Cells NK CD69+ - + CD69- NK Cells NK CD69- +

3 NK Cells CD69+ +

× γ γ γ 1.0 10 5.0× 10 2 γ 5.0× 10 2 IFN IFN IFN IFN

0 0 0 0

-/- -/- -/- -/- WT ε WT ε WT ε WT ε IFN IFN IFN IFN

I WT IFN ε -/-

IFN γ + CD69- 13.9% IFN γ - CD69+ 17.9% 15.7% 14.9% IFN γ + CD69+ 14.5% IFN γ - C D 69- 19.1%

47.2% 56.7%

Figure 3.4: Interferon (IFN)ε deficiency decreases the proportion of activated and IFNγ-producing natural killer (NK) cells in the female reproductive tract (RT) during Chlamydia infection. Wild- type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum. Percentages (of viable cells) and total numbers of IFNγ+ CD69- (A & E), IFNγ- CD69+ (B & F), IFNγ+ CD69+ (C & G), and IFNγ- CD69- (D & H) NK cells in uterine horn tissues were quantified via intracellular cytokine staining and flow cytometry at 3dpi to assess the effect of IFNε deficiency on NK cell activation and IFNγ production in the upper RT. The differential proportions IFNγ+/- CD69+/- NK cells as percentages of all NK cells in the upper RT were also determined (I; three experiments; n≥15 replicates of pooled uterine homogenate samples). All data are presented as mean±SEM. *=p<0.05; **=p<0.01.

162 3.4.2 IFNε deficiency decreases systemic NK cell responses

I next sought to determine if these IFNε-mediated effects on NK cell number, activity, and IFNγ production are specific to the female RT or whether IFNε is also involved in mediating systemic NK cell responses. To do this, I performed flow cytometric analyses on splenocytes and bone marrow cells from both Chlamydia- infected and sham-infected, WT and IFNε-/- mice at 3dpi. It was feasible to include sham-infected mice in these analyses as the yield of cells isolated from spleen and bone marrow tissues at baseline is sufficient for flow cytometric analyses without the need to pool samples, unlike uterine tissues from uninfected mice which require pooling of >5 samples for analysis.

I show that IFNε-/- mice have fewer NK cells present in the spleen, both at baseline (as a percentage of viable cells and total number) and during Chlamydia infection (total numbers only), compared to WT controls (Figure 3.5 A & D). As a percentage of viable cells, activated CD69+ NK cells are also significantly lower in sham-infected IFNε-/- mice compared to WT controls (Figure 3.5 B). Whilst the total number of CD69+ NK cells present in the spleens of sham-infected IFNε-/- mice is not altered, I show that IFNε deficiency results in a reduction in the total number of these cells present in the spleen during Chlamydia infection (Figure 3.5 E). IFNγ+ NK cells, as a percentage of viable cells, are also significantly reduced in the spleens of IFNε-/- mice compared to WT controls (Figure 3.5 C). However, no differences are observed between the total numbers of IFNγ+ NK cells present in the spleens of Chlamydia- or sham-infected, WT and IFNε-/- mice (Figure 3.5 F). While this data indicates that the numbers of activated and IFNγ-producing splenic NK cells are decreased in IFNε-/- mice, this appears to be due to an overall decrease in the total number of NK cells

163 present, as the proportions of IFNγ+/- CD69+/- NK cells are similar between WT and

IFNε-/- mice, both in the presence and absence of infection (Figure 3.5 G).

Given that IFNε deficiency results in decreased systemic NK cell responses, I next investigated the effect of IFNε deficiency on the number of early precursor, immature, and mature NK cells in the bone marrow of both Chlamydia- and sham- infected WT and IFNε-/- mice. I show that, while the numbers of immature NK cells are not altered between WT and IFNε-/- mice (Figure 3.6 B & E), there is a significant reduction in both the numbers of precursor NK cells present during infection (Figure

3.6 A & D) and mature (CD11b+) NK cells present, both at baseline and during infection (Figure 3.6 C & F), in the bone marrow of IFNε-/- mice compared to WT controls.

164 A B C

6 0.4 2.5 * *** 2.0 0.3 * 4 1.5 0.2 1.0

2 (%) NK Cells + γ NK (%) Cells 0.1 0.5 IFN CD69+ (%) NK Cells

0 0.0 0.0

SPG Cmu SPG Cmu SPG Cmu SPG Cmu SPG Cmu SPG Cmu

WT IFN ε -/- WT IFN ε -/- WT IFN ε -/-

D E F

5 6 2.5× 10 6 2.0× 10 1.5× 10 * 2.0× 10 6 * 1.5× 10 5 *** 1.0× 10 6 1.5× 10 6 1.0× 10 5 6 1.0× 10 NK Cells + γ NK Cells 5.0× 10 5 × 4 5.0 10 IFN 5.0× 10 5 Cells NK CD69+

0 0 0

SPG Cmu SPG Cmu SPG Cmu SPG Cmu SPG Cmu SPG Cmu

WT IFN ε -/- WT IFN ε -/- WT IFN ε -/-

G γ WT SPG IFN ε -/- SPG WT Cmu IFN ε -/- Cm u IFN + CD69- IFN γ - CD69+ 5.3% 5.5% 5% 2% 5.2% 2.4% 2.3% 2.1% IFN γ + CD69+ IFN γ - C D 69-

35.5% 37.5% 36.1% 34%

57.3% 54.8% 56.1% 59%

Figure 3.5: Interferon (IFN)ε deficiency decreases the total number of circulating natural killer (NK) cells but does not alter the proportion of activated and IFNγ-producing NK cells present in the spleen. Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum (Cmu) or sham-infected with sucrose-phosphate-glutamate buffer (SPG). Percentages (of viable cells) and total numbers of circulating (A & D), CD69+ (B & E), and IFNγ+ (C & F) NK cells in spleen tissues were quantified via intracellular cytokine staining and flow cytometry at 3dpi to assess the effect of IFNε deficiency on systemic NK cell numbers, activation, and IFNγ production. The differential proportions IFNγ+/- CD69+/- NK cells as percentages of all NK cells in the spleen were also determined (I; two experiments; n≥15). All data are presented as mean±SEM. *=p<0.05; ***=p<0.001.

165 A B C

0.020 0.4 0.05 * * * 0.04 0.015 0.3

0.03 0.010 0.2 0.02

0.005 0.1 0.01 ImmatureNK (%) Cells Precursor NK Cells (%) NK Precursor Cells 0.000 0.0 0.00 Mature (CD11b+) NK Cells (CD11b+) (%)NKMature Cells

SPG Cmu SPG Cmu SPG Cmu SPG Cmu SPG Cmu SPG Cmu

WT IFN ε -/- WT IFN ε -/- WT IFN ε -/-

D E F

× 3 × 4 × 3 3.0 10 * 4.0 10 6.0 10 *

3.0× 10 4 2.0× 10 3 4.0× 10 3

2.0× 10 4

1.0× 10 3 2.0× 10 3 1.0× 10 4 Im m ature N K C ells Precursor N K C ells

0 0 Mature (CD11b+) NK Cells 0

SPG Cmu SPG Cmu SPG Cmu SPG Cmu SPG Cmu SPG Cmu

WT IFN ε -/- WT IFN ε -/- WT IFN ε -/-

Figure 3.6: Interferon (IFN)ε deficiency decreases the production of precursor and mature, but not immature, natural killer (NK) cells in the bone marrow. Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum (Cmu) or sham-infected with sucrose-phosphate- glutamate buffer (SPG). Percentages (of viable cells) and total numbers of precursor (A & D), immature (B & E), and mature (CD11b+; C & F) NK cells in bone marrow tissues collected from the femur were quantified via flow cytometry at 3dpi to assess the effect of IFNε deficiency on NK cell haematopoiesis (three experiments; n≥19). All data are presented as mean±SEM. *=p<0.05.

166 3.4.3 IFNε deficiency reduces the expression of genes

associated with NK cell responses in the female RT

To elucidate how IFNε induces its effects on local and systemic NK cell responses, I assessed the uterine mRNA expression levels of a number of factors that are closely linked with NK cell chemoattraction, activation and, IFNγ responses in WT and IFNε-/- mice in both the absence and presence of infection. I show that the expression levels of both IL-15 (Figure 3.7 A) and CXCL10 (Figure 3.7 B) are significantly lower (~40% reduction) in sham-infected IFNε-/- mice compared to WT controls. I also show that there is a trend towards a decrease in IL-15 expression in

Chlamydia-infected IFNε-/- mice compared to WT controls (Figure 3.7 A), whilst no difference between the infected groups is observed for CXCL10 expression (Figure 3.7

B). Furthermore, I show that IL-12p40 expression is unaltered between either

Chlamydia- or sham-infected, WT or IFNε-/- mice (Figure 3.7 C). These findings demonstrate that the baseline expression of two factors that are important for the chemoattraction and activation of NK cell responses are reduced in IFNε-/- mice.

Reduced IL-15 expression in IFNε-/- mice was confirmed at the protein level via immunoblot analysis (Figure 3.7 D).

IFNAR signalling via the classical type I IFNs has previously been linked to detrimental effects during Chlamydia infection. To ascertain how IFNε may be selectively initiating these protective responses despite signalling through the same receptor, I assessed the expression of a variety of factors involved in the induction of type I IFN responses in the RTs of WT and IFNε-/- mice. First, I sought to determine whether IFNε affects the expression of conventional type I IFNs and their common receptor, IFNAR. I show that IFNε has no effect on the expression of classical type I

IFNs, with no differences in the relative expression levels of IFNα species (Figure 3.8

167 A) or IFNβ (Figure 3.8 B) observed between WT and IFNε-/- mice. However, IFNAR1 expression is slightly reduced in IFNε-/- mice during infection, compared to WT controls

(Figure 3.8 C).

I next sought to determine whether IFNε modifies the type I IFN response by regulating the expression of factors involved in type I IFN-related signalling pathways.

Notably, IRF3 and IRF7 expression levels are significantly reduced in Chlamydia- infected IFNε-/- mice (Figure 3.9 A & B), while STAT1 expression is decreased in

IFNε-/- mice at baseline and trending towards a reduction during infection (Figure 3.9

C), compared to WT controls. In contrast, there is no difference between the expression levels of IRF1 in IFNε-/- mice compared to WT controls (Figure 3.9 D).

I next analysed the effect of IFNε on the expression of effector cytokines and other factors involved in IFNγ responses that may play a role in IFNε-mediated protection against Chlamydia infections. I show a significant reduction in iNOS expression in Chlamydia-infected IFNε-/- mice (Figure 3.10 A) and IDO expression in both Chlamydia- and sham-infected IFNε-/- mice (Figure 3.10 B) compared to WT controls. IFNγR1 expression is also significantly lower in IFNε-/- mice during infection compared to WT controls (Figure 3.10 C). Conversely, SOCS1 expression is significantly higher in Chlamydia-infected IFNε-/- mice (Figure 3.10 D).

168 A B C

0.10 0.0660 0.3 0.04

0.08 * * 0.03 0.2 0.06 0.02 0.04 0.1 0.01 0.02

0.00 0.0 0.00

IL-15 Relative Expression (to HPRT) (to Expression Relative IL-15 SPG Cmu SPG Cmu SPG Cmu SPG Cmu SPG Cmu SPG Cmu CXCL10 Relative Expression (to HPRT) (to Expression CXCL10 Relative IL-12p40 Relative Expression (to HPRT) (to Expression Relative IL-12p40 WT IFN ε -/- WT IFN ε -/- WT IFN ε -/-

0.4

0.3

0.2

0.1

0.0 IL-15 Relative Density (to ACTB) (to Density Relative IL-15

SPG Cmu SPG Cmu WT IFN ε -/-

Figure 3.7: Interferon (IFN)ε deficiency differentially alters the expression of factors involved in natural killer (NK) cell responses in the female reproductive tract (RT). Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum (Cmu) or sham-infected with sucrose- phosphate-glutamate buffer (SPG). Interleukin (IL)-15 (A), C-X-C motif chemokine ligand (CXCL)10 (B), and IL-12p40 (C) messenger (m)RNA expression was quantified via qPCR (one experiment; n≥5). and IL-15 protein expression, relative to β-actin, was determined by immunoblot analysis and quantified by densitometry (D; one experiment; 5 pooled samples) in uterine tissue at 3dpi to assess the effect of IFNε deficiency on expression of factors associated with NK cell responses in the upper RT. Target gene mRNA expression was normalised against expression of the housekeeping gene control, hypoxanthine- guanine phosphoribosyltransferase (HPRT). All data are presented as mean±SEM. *=p<0.05; **=p<0.01.

169 A B C

0.0015 0.004 0.8

0.003 0.6 0.0010 *

0.002 0.4

0.0005

0.001 0.2 Relative Expression (to HPRT) (to Expression Relative α 0.000 HPRT) (to Expression Relative 0.0000 0.0 β

IFN SPG SPG Cmu SPG Cmu SPG Cmu Cmu SPG Cmu SPG Cmu IFNAR1 Relative Expression (to HPRT) (to Expression IFNAR1 Relative P an-IFN WT IFN ε -/- WT IFN ε -/- WT IFN ε -/-

Figure 3.8: Interferon (IFN)ε deficiency has no effect on the expression of classical type I IFNs but decreases expression of type I IFN receptor (IFNAR)1 during Chlamydia infection in the female reproductive tract (RT). Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum (Cmu) or sham-infected with sucrose-phosphate-glutamate buffer (SPG). Pan-IFNα (A), IFNβ (B), and IFNAR1 (C) messenger (m)RNA expression was quantified via qPCR at 3dpi to assess the effect of IFNε deficiency on expression of the classical type I IFNs and their common receptor in the upper RT. Target gene mRNA expression was normalised against expression of the housekeeping gene control, hypoxanthine-guanine phosphoribosyltransferase (HPRT; one experiment; n≥5). All data are presented as mean±SEM. *=p<0.05.

170 A B C D

0.15 0.15 0.5 0.20 * * 0.4 * 0.15 0.10 0.10 0.3

0.10 0.2 0.05 0.05 0.05 0.1

0.00 0.00 0.0 0.00

IRF3 Relative Expression (to HPRT) (to Expression Relative IRF3 SPG SPG Cmu HPRT) (to Expression Relative IRF7 SPG SPG Cmu SPG Cmu SPG Cmu HPRT) (to Expression Relative IRF1 SPG SPG Cmu

Cmu Cmu HPRT) (to Expression STAT1 Relative Cmu

WT IFN ε -/- WT IFN ε -/- WT IFN ε -/- WT IFN ε -/-

Figure 3.9: Interferon (IFN)ε deficiency differentially alters the expression of factors involved in type I IFN signalling in the female reproductive tract (RT). Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum (Cmu) or sham-infected with sucrose-phosphate- glutamate buffer (SPG). IFN regulatory factor (IRF)3 (A), IRF7 (B), signal transducer and activator of transcription (STAT)1 (C), and IRF1 (D) messenger (m)RNA expression was quantified via qPCR at 3dpi to assess the effect of IFNε deficiency on expression of factors associated with classical type I IFN signalling pathways in the upper RT. Target gene mRNA expression was normalised against expression of the housekeeping gene control, hypoxanthine-guanine phosphoribosyltransferase (HPRT; one experiment; n≥5). All data are presented as mean±SEM. *=p<0.05.

171 A B C D

0.8 0.020 0.010 0.004 * ** * * 0.008 0.003 * 0.6 0.015

0.006 0.002 0.4 0.010 0.004

0.001 0.2 0.005 0.002

0.000 0.000 0.0 0.000 R Relative Expression (to HPRT) (to Expression R Relative γ IDO Relative Expression (to HPRT) (to Expression IDO Relative

iNOS Relative Expression (to HPRT) (to Expression iNOS Relative SPG SPG Cmu SPG SPG Cmu SPG SPG Cmu SPG SPG Cmu Cmu Cmu IFN Cmu Cmu SOCS1 Relative Expression (to HPRT)SOCS1 (to Expression Relative WT IFN ε -/- WT IFN ε -/- WT IFN ε -/- WT IFN ε -/-

Figure 3.10: Interferon (IFN)ε deficiency differentially alters the expression of factors involved in IFNγ responses in the female reproductive tract (RT). Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum (Cmu) or sham-infected with sucrose-phosphate- glutamate buffer (SPG). Inducible nitric oxide synthase (iNOS; A), indoleamine 2, 3-dixoygenase (IDO; B), IFNγ receptor (IFNγR)1 (C), and suppressor of cytokine signalling (SOCS)1 (D) messenger (m)RNA expression was quantified via qPCR in uterine tissue at 3dpi to assess the effect of IFNε deficiency on expression of factors associated with IFNγ responses in the upper RT. Target gene mRNA expression was normalised against expression of the housekeeping gene control, hypoxanthine-guanine phosphoribosyltransferase (HPRT; one experiment; n≥5). All data are presented as mean±SEM. *=p<0.05; **=p<0.01.

172 3.4.4 Depletion of systemic NK cells alters Chlamydia

infection and affects NK cell number and phenotype in

the female RT

Since IFNε-/- mice have reduced local and systemic NK cell responses and are more susceptible to Chlamydia infection, I next sought to determine if NK cell depletion would have similar effects on Chlamydia infection in the RT as IFNε deficiency. NK cells were depleted in progesterone-pre-treated WT mice through IP administration of anti-ASGM1 rabbit serum on days 1 and 2 after Chlamydia infection.

Anti-ASGM1 was chosen to deplete NK cells in our model as it has previously been demonstrated to successfully deplete NK cells from the female RT in a study that explored the role of NK cells in protection against Chlamydia RTIs (Tseng and Rank,

1998). This treatment regime was designed to model a deficiency in NK cell mobilisation and infiltration observed following infection. The effects of NK cell depletion on infection and NK cell responses were analysed and compared with

Chlamydia-infected WT and IFNε-/- mice treated with control rabbit serum.

Unsurprisingly, I show that NK cell depletion results in a modest increase in infection in the uterus, with anti-ASGM1-treated mice having a 2-fold increase in

Chlamydia 16S expression compared to rabbit serum-treated WT controls (Figure 3.11

A). However, Chlamydia 16S expression in NK cell-depleted WT mice does not reach the levels observed in Chlamydia-infected, rabbit serum-treated, IFNε-/- mice (150-fold increase compared to rabbit serum-treated WT controls, Figure 3.11 A). Interestingly, despite the fact that the anti-ASGM1 treatment regime used is successful at almost completely depleting NK cell numbers in the spleen and mature NK cells in the bone marrow (Appendix C: sFigure 3.1), the total number of NK cells in the uterine tissue

173 of anti-ASGM1-treated mice is only reduced by ~35%, with this reduction not quite reaching statistical significance (p=0.058, Figure 3.11 B & E). Importantly, the numbers of total NK cells in the anti-ASGM1-treated group are similar to that observed in infected, IFNε-/- mice (Figure 3.11 B & E). Interestingly, whilst anti-ASGM1 treatment has similar effects on total NK cells as IFNε deficiency, I show that the phenotype of NK cells in the uterine tissue of NK cell-depleted WT mice is remarkably different to that of IFNε-/- controls. Specifically, my studies show that the uterine tissue of Chlamydia-infected, anti-ASGM1-treated WT mice exhibits a reduction in the numbers of CD69- NK cells (CD69- IFNγ+ and CD69- IFNγ-), but not CD69+ NK cell numbers (CD69+ IFNγ+ and CD69+ IFNγ-), which are the same as in rabbit serum- treated WT controls, whilst, in IFNε-/- mice, uterine tissues are mostly deficient in

CD69+, but not CD69-, NK cells (Figure 3.11 H-O).

Together, my findings demonstrate the importance of IFNε production in activation and proliferation of NK cells in the uterus during Chlamydia female RTI. I show that NK-depleted, WT mice that have reduced numbers of systemic NK cells available for mobilisation are still able to maintain a pool of activated, IFNγ-producing

NK cells in the uterus. This is most likely due to the ability of these anti-ASGM1- treated WT mice to produce IFNε that directly activates NK cells that reside in the uterus as the numbers of activated, IFNγ-producing cells are only significantly reduced

IFNε-/- mice. Significantly, my findings suggest that the activation of the NK cells in the uterus is more important than total number in helping protect against infection, given that NK cell-depleted WT mice, which have normal levels of activated, IFNγ-producing

NK cells, are still much more resistant to infection than IFNε-/- mice, which have similar numbers of total, but reduced numbers of activated, NK cells.

174 I next sought to determine if a prolonged depletion of NK cells prior to infection would be able to achieve greater reductions in total and activated NK cells in the female

RT during Chlamydia infection. Remarkably, I show that anti-ASGM1 treatment for 3 days prior to, and then once daily during, infection did not statistically affect Chlamydia

16S relative expression, (Figure 3.12 A). Indeed, my data suggest that this NK cell depletion strategy may result in a reduction in infection in the upper RT as a strong trend towards a reduction in Chlamydia 16S expression was observed. Again, I show that the anti-ASGM1 treatment regime used was successful at almost completely depleting NK cell numbers in the spleen and mature NK cells in the bone marrow

(Appendix C: sFigure 3.2). However, when I analysed the effects of systemic depletion on uterine NK cells, I found that the anti-ASGM1-treated WT mice actually had increased numbers of total, as well as CD69+ and IFNγ+, NK cells in their RT compared to rabbit serum-treated WT controls (Figure 3.12 B-N). These findings suggest that the pool of activated, IFNγ-producing NK cells observed the uterus of WT mice during Chlamydia infection are robustly maintained despite having a prolonged reduction in the number of systemic NK cells available for recruitment to the female RT during infection. Indeed, my findings suggest that the depletion of systemic NK cells for a period of time prior to infection may actually produce a compensatory effect that somehow increases the number and activation of NK cell numbers in the female RT during infection. Representative flow cytometric plots of NK cell populations in the

RTs of mice treated with anti-ASGM1 either post or prior to and throughout infection are provided in Appendix C: sFigure 3.5.

175 A B C D

1 1.5 1.5 1.0 0.0661 0.0565 0.8 0.1

16S 1.0 1.0 * 0.6 0.01 * 0.4

0.5 0.5 (%) NK Cells + γ NK (%) Cells

Chlamydia 0.001 0.2 IFN CD69+ (%) NK Cells

0.0001 0.0 0.0 0.0 Relative Expression (to HPRT) (to Expression Relative -/- -/- -/- -/- ε ε ε ε

Serum IFN Serum IFN Serum IFN Serum IFN

A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 E F G

1.5× 10 4 1.0× 10 4 8.0× 10 3

3 *** 0.0588* 8.0× 10 * 6.0× 10 3 1.0× 10 4 6.0× 10 3 4.0× 10 3 3 4.0× 10 NK Cells + γ NK Cells 5.0× 10 3 × 3 IFN 2.0 10 CD69+ NK Cells NK CD69+ 2.0× 10 3

0 0 0

-/- -/- -/- ε ε ε

Serum IFN Serum IFN Serum IFN A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 H I J K

0.20 0.5 0.8 0.15 **** * 0.4 **** 0.15 **** 0.6 * 0.10 **** 0.3 0.10 0.4 0.2 0.05 0.05 0.2 - CD69- NK Cells (%) NK Cells CD69- - + CD69- NK (%) Cells CD69+ - NK(%) Cells 0.1 + CD69+ NK (%) Cells γ γ γ γ IFN IFN IFN 0.00 0.0 IFN 0.0 0.00

-/- -/- -/- -/- ε ε ε ε

Serum IFN Serum IFN Serum IFN Serum IFN A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 L M N O

2.0× 10 3 4.0× 10 3 5.0× 10 3 1.0× 10 3 0.0604 ** **** 4.0× 10 3 8.0× 10 2 1.5× 10 3 *** 3.0× 10 3 ** ****

3.0× 10 3 6.0× 10 2 1.0× 10 3 2.0× 10 3 *** 2.0× 10 3 4.0× 10 2 - CD69- NK Cells NK CD69- - + CD69- NK Cells NK CD69- + Cells NK CD69+ -

2 3 NK Cells CD69+ +

× × γ γ 5.0 10 γ 1.0 10 γ 1.0× 10 3 2.0× 10 2 IFN IFN IFN IFN

0 0 0 0

-/- -/- -/- -/- ε ε ε ε

Serum IFN Serum IFN Serum IFN Serum IFN A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 Figure 3.11: Systemic natural killer (NK) cell depletion post infection increases Chlamydia replication and reduces inactive populations of NK cells in the upper reproductive tract (RT). Wild- type (WT) and interferon (IFN)ε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum. Mice were administered anti-asialo GM1 (ASGM1) antibody (WT) or normal rabbit serum (WT and IFNε-/-) intraperitoneally (IP) at 1 and 2dpi. Chlamydia 16S ribosomal (r)RNA expression was quantified via qPCR (A; one experiment; n≥5) and percentages (of viable cells) and total numbers of total (B & E), IFNγ+ (C & F), CD69+ (D & G), IFNγ+ CD69- (H & L), IFNγ- CD69+ (I & M), IFNγ+ CD69+ (J & N), and IFNγ- CD69- (K & O) NK cells in uterine tissues were quantified via flow cytometry (one experiment; n≥11 replicates of pooled uterine homogenate samples) at 3dpi. Chlamydia 16S expression was normalised against expression of the housekeeping gene control, HPRT. All data are presented as mean±SEM. *=p<0.05; **=p<0.01; ***=p<0.001; ****=p<0.0001.

176 A B C D

1 2.0 1.5 0.0546 0.8

0.1 1.5 0.0700 0.6

16S 1.0

0.01 1.0 0.4

0.5 (%) NK Cells + γ NK (%) Cells

Chlamydia 0.001 0.5 0.2 IFN CD69+ (%) NK Cells

0.0001 0.0 0.0 0.0 Relative Expression (to HPRT) (to Expression Relative

Serum Serum Serum Serum

A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 E F G

4 1.0× 10 1.0× 10 4 5.0× 10 3 * 3 * 8.0× 10 8.0× 10 3 * 4.0× 10 3

6.0× 10 3 6.0× 10 3 3.0× 10 3

3 3 3 4.0× 10 4.0× 10 NK Cells + 2.0× 10 NK Cells γ

3 IFN 2.0× 10 Cells NK CD69+ 2.0× 10 3 1.0× 10 3

0 0 0

Serum Serum Serum A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 H I J K

0.06 0.8 0.8 0.05 * 0.04 0.6 0.6 0.04 0.03 0.4 0.4 0.02 0.02 0.2 0.2 - CD69- NK Cells (%) NK Cells CD69- - + CD69- NK (%) Cells CD69+ - NK(%) Cells 0.01 + CD69+ NK (%) Cells γ γ γ γ IFN IFN IFN 0.00 0.0 IFN 0.0 0.00

Serum Serum Serum Serum A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 L M N O

2 3.0× 10 2 5.0× 10 3 5.0× 10 3 2.5× 10

* 2 4.0× 10 3 * 4.0× 10 3 2.0× 10 2.0× 10 2 3.0× 10 3 3.0× 10 3 1.5× 10 2

2.0× 10 3 2.0× 10 3 1.0× 10 2 1.0× 10 2 - CD69- NK Cells NK CD69- - + CD69- NK Cells NK CD69- + - CD69+ NK Cells NK CD69+ - + CD69+ NK Cells CD69+ + γ γ γ 1.0× 10 3 γ 1.0× 10 3 5.0× 10 1 IFN IFN IFN IFN

0 0 0 0

Serum Serum Serum Serum A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 Figure 3.12: Systemic natural killer (NK) cell depletion prior to infection decreases Chlamydia replication and increases active populations of NK cells in the upper reproductive tract (RT). Wild- type (WT) C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and administered anti-asialo GM1 (ASGM1) antibody or normal rabbit serum intraperitoneally (IP) at -2, 0, and 2dpi. Mice were infected intravaginally (IVAG) with Chlamydia muridarum and Chlamydia 16S ribosomal (r)RNA expression quantified via qPCR (A; one experiment; n=7) and percentage (of viable cells) and total numbers of total (B & E), interferon (IFN)γ+ (C & F), CD69+ (D & G), IFNγ+ CD69- (H & L), IFNγ- CD69+ (I & M), IFNγ+ CD69+ (J & N), and IFNγ- CD69- (K & O) NK cells in uterine tissues quantified via flow cytometry (one experiment; n=4 replicates of pooled uterine homogenate samples) at 3dpi. Chlamydia 16S expression was normalised against expression of the housekeeping gene control, HPRT. All data are presented as mean±SEM. *=p<0.05.

177 3.5 Discussion

The studies described in this chapter were based on the results of my preliminary immune cell and genome-wide gene expression profiling experiments that showed reductions in NK cells and the expression of NK cell-associated genes in the uterine tissue of Chlamydia-infected, IFNε-/- mice compared to WT controls (Chapter 2). In this chapter, I extended upon these initial findings to demonstrate an important role for

IFNε in mediating uterine and systemic NK cell responses that protect against the early stages of Chlamydia infection in the female RT.

Previous studies by me (data not shown) and others (Jiao et al., 2011) confirm

3dpi as the peak of NK cell infiltration in our murine model of C. muridarum-induced female RTI. Therefore, 3dpi is the optimal time point for examining the effects of IFNε on NK cell responses during Chlamydia infection.

The protective roles of NK cells during Chlamydia infections have previously been demonstrated (Jiao et al., 2011; Tseng and Rank, 1998). NK cells are thought to mediate protection against Chlamydia via production of IFNγ (Jiao et al., 2011; Tseng and Rank, 1998), however, they have also been shown to be capable of recognising and killing Chlamydia-infected cells (Hook et al., 2004; Ibana et al., 2012). Importantly, NK cell responses, including the production of IFNγ and cytolytic activity, are also known to be regulated by type I IFNs (Andoniou et al., 2005; Gill et al., 2011; Lucas et al.,

2007), making them a likely candidate for IFNε-mediated protection against Chlamydia.

Throughout the studies outlined in this chapter, I performed focussed analyses of

NK cell populations and responses in WT and IFNε-/- mice via flow cytometry to advance the findings of Chapter 2. Using more comprehensive NK cell staining panels and classification strategies, I show that cNK cells constitute 2.5% of all cells in the

178 uterus of WT mice at 3dpi (Figure 3.2 A). This may be lower than that observed in initial profiling experiments (Chapter 2) due to, not only the more conservative classification strategy utilised, but also differences in processing to allow for intracellular cytokine staining. For example, the addition of ex vivo stimulation and permeablisation steps, which are known to reduce the yield of viable cells obtained, could have significantly affected relative cell numbers. Nevertheless, I confirm that

IFNε-/- mice have reduced numbers of cNK cells in their upper RTs at 3dpi, compared to

WT controls (Figure 3.2 A & D).

The uterus possesses its own unique population of trNK cells, uNK cells, which fluctuate throughout pregnancy and the menstrual cycle (Jones et al., 1998; Pace et al.,

1989) via local proliferation of early NK progenitors (Chantakru et al., 2002; Male et al., 2010; Vacca et al., 2011). uNK cells are important for reproductive processes, however, they have also been shown to play a role in protection against certain pathogens (Mselle et al., 2009; Siewiera et al., 2013). As such, I also examined the effect of IFNε on uNK cell numbers during infection. I found that uNK cells were also reduced in IFNε-/- mice during infection, indicating that IFNε may potentiate their local proliferation (Figure 3.2 B & E).

NK cell activity is controlled by a balance of activating and inhibitory receptors and their cognate ligands. CD69 is an early activation marker expressed by NK cells upon stimulation of various activation pathways; importantly, these include stimulation with type I IFNs and bacteria (Athié-Morales et al., 2008). Additionally, activation of

CD69 triggers NK cell-mediated cytolytic (Moretta et al., 1991) and immunomodulatory functions (Borrego et al., 1999). Thus, I used this marker to quantify activated NK cells in the RTs and spleens of WT and IFNε-/- mice during

Chlamydia RTI in order to investigate the effects of IFNε on NK cell activation. IFNε-/-

179 mice had significantly fewer activated NK cells in their RTs at 3dpi (Figure 3.2 C &

F), indicating that IFNε promotes the activation of NK cells during infection. This

IFNε-mediated increase in CD69 expression suggests that IFNε may also promote the cytolytic activity and immunomodulatory functions, such as the production of IFNγ, of

NK cells, enhancing the clearance of Chlamydia from the RT. The role of IFNγ production by NK cells in protection against Chlamydia infections has previously been demonstrated (Jiao et al., 2011; Tseng and Rank, 1998), however, NK cell-mediated cytotoxicity is unlikely to be playing a role (Murthy et al., 2011; Perry et al., 1999a) and the role of CD69+ activated NK cells is yet to be determined. Nevertheless, this is the first time IFNε has been shown to increase NK cell activity and NK cell activity in the female RT has been associated with protection against Chlamydia infections.

Importantly, NK cells have been shown to be the predominant source of IFNγ early during Chlamydia female RTIs (Tseng and Rank, 1998). IFNγ has long been known to be an integral anti-Chlamydia cytokine (Byrne et al., 1989; Byrne and

Krueger, 1983; Cotter et al., 1997; Ito and Lyons, 1999; Johansson et al., 1997b; Li et al., 2008; Perry et al., 1997; Shemer and Sarov, 1985), and clinical studies have associated its expression with reduced risk of both infection (Cohen et al., 2005) and the development of sequelae (Cohen et al., 2000; Debattista et al., 2002b; Holland et al.,

1996). Importantly, I show for the first time that the number of IFNγ-producing NK cells in the female RT during Chlamydia infection is reduced in IFNε-/- mice, compared to WT controls (Figure 3.3 A & E).

Additionally, there were fewer IFNγ+ T cells present in the RTs of Chlamydia- infected IFNε-/- mice, compared to WT controls (Figure 3.3 B & F), although these cells accounted for a smaller percentage of total cells than NK cells. Jiao et al. have previously shown that NK cells promote the development of protective Th1 immunity

180 to Chlamydia via the modulation of DC function (Jiao et al., 2011). This response was shown to be dependent on the production of IFNγ in ex vivo co-culture experiments

(Jiao et al., 2011). Taken together, these data suggest that this IFNε-mediated IFNγ production by NK cells promotes the development of protective Th1 immunity to

Chlamydia.

The total number of IFNγ-producing leukocytes was also significantly reduced in

IFNε-/- mice (Figure 3.3 C & G). Importantly, NK cells accounted for over 40% of these IFNγ+ leukocytes. This is unsurprising, as NK cells are the most abundant cell type at this time-point and are known to be the primary source of IFNγ early during infection. Furthermore, this reduction in IFNγ-producing cells correlates with a reduction in IFNγ expression (Figure 3.3 D), suggesting that IFNε augments the amount of IFNγ produced during infection.

Additionally, I show that this IFNε-mediated increase in active and IFNγ- producing NK cells in the RT is not solely due to an increase in the total number of NK cells present, but also due an increase in their local activation, as the number and proportion of NK cells identified as single or double positive for IFNγ and CD69 is reduced in IFNε-/- mice (Figure 3.4 A-C, E-G, & I) but the number of IFNγ- CD69- double negative NK cells is not altered by IFNε deficiency (Figure 3.4 D & H).

The bone marrow is thought to be the primary site of NK cell haematopoiesis

(Colucci et al., 2003; Haller and Wigzell, 1977), with NK cells mobilising into the circulation and homing to specific organs or sites of immune response upon maturation via the modulation of their chemoattractant receptors (Bernardini et al., 2008; Mayol et al., 2011; Sciumè et al., 2011; Wald et al., 2006; Walzer et al., 2007). However, trNK cell populations in the uterus and other organs have been shown to mature independently of cNK cells via the differentiation of local haematopoietic precursors

181 (Chantakru et al., 2002; Male et al., 2010; Sojka et al., 2014; Vacca et al., 2011;

Vosshenrich et al., 2006). Additionally, mature c and trNK cells are known to expand in the periphery upon stimulation with viruses, bacterial components, target and accessory cells, and cytokines via direct and indirect mechanisms (Tsujimoto et al., 2005; Warren,

1996). Taken together, these data suggest that there are three possible mechanisms for the IFNε-mediated increase in NK cell numbers observed in the female RT; IFNε could be promoting (1) the expansion/development of c/trNK cells locally, (2) the haematopoiesis of NK cells/NK cell precursors in the bone marrow, increasing the systemic NK cell pool, and/or (3) the chemotaxis of NK cells/precursor NK cells to the

RT. Thus, I sought to determine the role of IFNε in c and trNK cell production, maintenance of the systemic NK cell pool, and NK cell chemoattraction, both in the steady state and during Chlamydia infection.

To determine the role of IFNε in maintenance of the systemic NK cell pool, I assessed the effect of IFNε deficiency on NK cell populations in the spleen. I found that the numbers of NK cells present in the spleens of both Chlamydia- and sham-infected

IFNε-/- mice are significantly lower than those observed in WT controls (Figure 3.5 D).

Additionally, IFNε deficiency reduced the proportion of splenocytes identified as

CD69+ NK cells (Figure 3.5 B) and IFNγ+ NK cells (Figure 3.5 C) in sham-infected mice, and the total number of CD69+ splenic NK cells present during infection (Figure

3.5 E), however, this appears to be due to the absolute decrease in NK cell numbers, as the proportions of NK cells positive for IFNγ and/or CD69 are similar between WT and

IFNε-/- mice (Figure 3.5 G). Taken together, these data suggest that IFNε contributes to the generation/maintenance of the systemic NK cell pool and that, although IFNε increases the number of NK cells systemically, its effects on NK cell activation and

IFNγ-production are restricted to the RT. Thus, these effects on NK cell generation and

182 activation are likely to be mediated through independent pathways. However, based on this information, it is unclear how IFNε increases systemic NK cell number. This could be mediated by either the potentiation of NK cell haematopoiesis in the bone marrow or the expansion and recirculation of NK cells from the uterus, the site of IFNε expression, as others have shown that cNK cells isolated from the spleen are capable of recirculating and repopulating all other organs (Grégoire et al., 2007). Therefore, I next examined the effects of IFNε deficiency on the production of NK cells and their progenitors in the bone marrow.

Like all other lymphocytes, NK cells arise from CLP cells in the bone marrow

(Kondo et al., 1997). Early NK cell-committed precursors acquire expression of the IL-

2 receptor β chain (CD122) (Rosmaraki et al., 2001), a component of the IL-15 receptor, which drives their maturation into NK cells by allowing them to respond to IL-

15 (Kennedy et al., 2000; Mrozek et al., 1996; Puzanov et al., 1996; Suzuki et al., 1997;

Williams et al., 1997). Precursor NK cells lack expression of the pan-NK cell markers

NK1.1, CD49b, and the Ly49 receptor family (Kim et al., 2002; Rosmaraki et al., 2001;

Williams et al., 2000). As they progress into immature NK cells, they acquire NK1.1 expression, followed by CD49b and CD11b as they reach functional maturity (Fathman et al., 2011; Kim et al., 2002; Rosmaraki et al., 2001; Williams et al., 2000). To ascertain whether IFNε contributes NK cell haematopoiesis at any of these developmental stages, I used these markers to identify NK cell progenitor populations in the bone marrow of WT and IFNε-/- mice. I show that IFNε-/- mice have significantly fewer precursor NK cells during infection (Figure 3.6 A & D) and mature NK cells, both at baseline and during infection (Figure 3.6 C & F), but no change in the number of immature NK cells (Figure 3.6 B & E) present in the bone marrow, compared to WT

183 controls. This data demonstrates that IFNε is involved in the generation of NK cells at multiple stages of their differentiation.

To strengthen the evidence for the involvement of NK cells in IFNε-mediated protection against Chlamydia RTIs, I used NK cell depleting antibodies to compare the effects of systemic NK cell depletion on Chlamydia infection and immune responses in the upper RT to those of IFNε deficiency. Here, I show that NK cell depletion post infection using anti-ASGM1 leads to a modest increase in Chlamydia 16S expression, however this does not reach the same extent observed during IFNε deficiency (Figure

3.11 A). This may be due to a selective depletion of inactive NK cells in the RT, as, while there was a significant reduction in the numbers of CD69- IFNγ- NK cells present

(Figure 3.11 K & O), no differences were observed in the numbers of CD69+ (Figure

3.11 C & F) or IFNγ+ (Figure 3.11 D & G) NK cells in uterine homogenates between the anti-ASGM1 and rabbit serum control groups. This is in contrast to IFNε-/- mice, which exhibit a pronounced deficiency in activated and IFNγ-producing populations of

NK cells, but WT levels of in inactive, non-IFNγ-producing (CD69- IFNγ-) NK cells at

3dpi (Figure 3.11). These differences in NK cell populations between IFNε-/- and anti-

ASGM1-treated mice may be responsible for the difference in Chlamydia 16S expression observed and highlight the importance of local, IFNε-mediated NK cell activation and production of IFNγ (rather than systemic NK cell number) in protection against ascending infection. Additionally, normal rabbit serum-treated controls exhibited fewer NK cells in their RTs (Figure 3.11 & 3.12) than untreated mice from previous experiments (Figure 3.2), suggesting that the control treatment may also influence immune responses in the female RT, highlighting a potential issue with these reagents. Nevertheless, this is the first time systemic NK cell depletion has been shown to increase Chlamydia load and infection of the upper RT. This adds to previous

184 research that demonstrates that NK cell depletion leads to a delay in clearance of

Chlamydia from the vagina (Tseng and Rank, 1998).

While systemic NK cell depletion post infection with Chlamydia successfully reduced certain populations of NK cells in the upper RT, anti-ASGM1 treatment prior to infection increased NK cell numbers in uterine homogenates at 3dpi (Figure 3.12 E).

Again, this appears to be due to the inability of anti-ASGM1 to deplete active NK cells in this site (Figure 3.12 C, D, F, & G). The increase in NK cell numbers observed in the upper RT may be a compensatory mechanism to replenish the systemic pool. These data highlight the difficulty in depleting the RT of NK cells.

To determine how IFNε mediates protective NK cell responses, I examined the expression of several factors involved in the regulation of NK cell function in the upper

RTs of WT and IFNε-/- mice. The cytokine IL-15 is essential for NK cell development and survival (Kennedy et al., 2000; Mrozek et al., 1996; Puzanov et al., 1996; Ranson et al., 2003; Suzuki et al., 1997; Williams et al., 1997), contributes to their recruitment, activation (including CD69 expression and IFNγ production), and expansion during infection (Allavena et al., 1997; Elpek et al., 2010; Guo et al., 2015; Lucas et al., 2007;

Nguyen et al., 2002), and has also been shown to play a critical role in the in situ maturation of uNK cells (Allen and Nilsen-Hamilton, 1998; Ye et al., 1996).

Importantly, type I IFNs have previously been shown to induce the expression of IL-15

(Baranek et al., 2012; Lucas et al., 2007). I expand upon these findings by demonstrating that IFNε deficiency results in a decrease in both the mRNA (Figure 3.7

A) and protein expression (Figure 3.7 D) of IL-15 in the female RT. NK cell trafficking is mediated by the expression of chemokines. CXCL10 is a potent chemoattractant that is induced by type I IFNs (Vanguri and Farber, 1990) and plays an important role in the mobilisation of NK cells in response to infection (Mahalingam et al., 1999; Pak-Wittel

185 et al., 2013; Yuan et al., 2009). Importantly, I show that the mRNA expression of

CXCL10 is significantly reduced in sham-infected IFNε-/- mice, compared to WT controls (Figure 3.7 B). The bounce-back seen in CXCL10 expression in Chlamydia- infected IFNε-/- mice may be due to the higher levels of infection (>900-fold compared to WT mice) present their upper RTs at this time-point. This reduction in baseline NK cell chemoattraction may contribute to the decrease in NK cell responses observed and reduce the pool of NK cells available for expansion upon infection. IL-12 is another cytokine known to be involved in the induction of NK cell and Th1 responses (Gately et al., 1998). Importantly, it has previously been demonstrated that IL-12 production by dendritic cells stimulates NK cells to secrete IFNγ (Ferlazzo et al., 2004). However, here I show that IL-12p40 mRNA expression is not altered in IFNε-/- mice compared to

WT controls (Figure 3.7 C), indicating that the IFNε-mediated production of IFNγ by

NK cells observed is induced by other mechanisms. Nevertheless, IL-12 protein expression will be explored in future studies. Taken together, my data suggest that IFNε promotes both the accumulation of, and the production of IFNγ by, NK cells in the female RT via the production of IL-15 and CXCL10, which mediate the in situ expansion and activation, and the chemoattraction of NK cells, respectively.

Although conventional type I IFNs have been shown to mediate several protective responses to Chlamydia infection in vitro (Carlin and Weller, 1995; Devitt et al., 1996;

Freudenberg et al., 2002; Gough et al., 2010), mice deficient in the common type I IFN receptor, IFNAR, are protected against Chlamydia RTIs (Nagarajan et al., 2008). This has been shown to be due to the action of IFNβ, which suppresses IFNγ-induced presentation of Chlamydia antigens by MHC-II to CD4+ T cells (Jayarapu et al., 2009;

Nagarajan et al., 2008). To determine if IFNε mediates its protective effects by altering conventional type I IFN responses, I assessed the effect of IFNε deficiency on

186 expression of the other type I IFNs, IFNAR1, and factors involved in type I IFN signalling pathways. Interestingly, I show that the expression of IFNα and β, either at baseline or early during Chlamydia infection, is unaltered by IFNε deficiency (Figure

3.8 A & B). However, there is a modest reduction in the expression of IFNAR1 in IFNε-

/- mice during infection (Figure 3.8 C). Previous studies have demonstrated that

IFNAR1 is essential for type I IFN signalling and may be responsible for the differential effects of the various type I IFNs (de Weerd et al., 2013; Hwang et al., 1995). This suggests that IFNε may instead be exerting its protective effects by altering type I IFN signalling pathways to favour the expression of protective downstream factors while minimising the expression of detrimental ones, via IFNα and β-independent pathways.

Type I IFNs signalling via IFNAR leads to the recruitment and phosphorylation of the signalling factors, STAT1 and STAT2 (Decker et al., 2005; Li et al., 1997; Li et al.,

1996). These activated STATs then form a heterodimer and translocate to the nucleus where they bind to IRF9 to form ISGF3 (Darnell et al., 1994; Decker et al., 2005; Li et al., 1997; Li et al., 1996). ISGF3 associates with ISREs in the promoter regions of genes and is the primary transcription factor for ISGs. Type I IFN signalling can also trigger the formation of STAT1 homodimers that bind to GASs in the promoter regions of

IFNγ-induced genes (Decker et al., 2005), which may explain how type I IFNs induce protective responses similar to those downstream of IFNγ during Chlamydia infection in vitro. Interestingly, I show that baseline STAT1 expression is reduced in IFNε-/- mice, compared to WT controls, and remains low during infection (Figure 3.9 C). These changes in STAT1 expression could be responsible for the IFNε-mediated induction of

ISGs, such as CXCL10 and IL-15, and may contribute to responses downstream of

IFNγ.

187 Interestingly, others have shown that the signalling molecules that lead to type I

IFN expression are capable of directly up-regulating ISGs in an IFN-independent manner (Grandvaux et al., 2002; Kessler et al., 1988; Nakaya et al., 2001; Sato et al.,

1998) and have divergent effects on Chlamydia burden and RT pathology (Prantner et al., 2011). In contrast to IFNAR-/- and IFNβ-/- mice, IRF3-/- mice have been shown to have increased Chlamydia load early during infection and develop worsened uterine horn pathology (Prantner et al., 2011). Intriguingly, this is despite augmented Th1 responses similar to that seen in IFNAR-/- mice, and correlates with delayed immune cell recruitment and a decrease in CXCL10 and IFNγ expression early during infection

(Prantner et al., 2011). Here, I show that the expression of IRF3 during infection is significantly reduced in IFNε-/- mice (Figure 3.9 A). Taken together, these data suggest that IFNε-mediated increases in IRF3 expression may also be responsible for enhancing the recruitment of IFNγ-producing cells to the RT without generating the detrimental effects observed with conventional type I IFN signalling. IRF7 can also directly bind to promoters containing ISREs to induce the expression of ISGs (Kessler et al., 1988; Sato et al., 1998) and its expression has been shown to be induced by type I IFN signalling in a positive feed forward manner (Honda et al., 2006). Interestingly, I show that expression of IRF7, which increases upon infection, is significantly reduced in IFNε-/- mice (Figure 3.9 B), indicating that IFNε may prime for its up-regulation during infection. Importantly, others have demonstrated a role for IRF7 in protection against

Chlamydophila pneumoniae infection (Buß et al., 2010). As such, IFNε-mediated IRF7 expression may also be involved in the induction of protective responses to Chlamydia

RTI.

IRF1 is another ISG that has been linked to the expression of many factors also induced by IFNε, such as CXCL10 (Harikumar et al., 2014), IL-15 (Ogasawara et al.,

188 1998), iNOS (Kleinert et al., 2004), and IDO (Ozes and Taylor, 1994). Thus, I endeavoured to determine if IRF1 is responsible for inducing the expression of these factors downstream of IFNε. IRF1 expression, however, is unaltered in IFNε-/- mice

(Figure 3.9 D), indicating that IFNε mediates the expression of these factors via other mechanisms. Nevertheless, future studies will also assess the effects of IFNε on the activation of these signalling factors.

IFNγ mediates its anti-Chlamydia effects by activating phagocytes and inducing the expression of the effector cytokines, IDO (Byrne et al., 1986; Murray et al., 1989;

Rapoza et al., 1991) and iNOS (Igietseme, 1996; Rottenberg et al., 1999; Zhang et al.,

2012). iNOS expression can be induced in a wide variety of cells via signalling pathways that lead to STAT1 and/or NK-κB activation, including type I IFN, IFNγ, and

IL-1β signalling (Kleinert et al., 2004), and leads to the generation of microbicidal NO, which inhibits Chlamydia growth (Igietseme, 1996; Rottenberg et al., 1999; Zhang et al., 2012). Here, I show that uterine expression iNOS is significantly lower in

Chlamydia-infected IFNε-/- mice, compared to WT controls (Figure 3.10 A). Although

IFNγ is the prototypic regulator of iNOS expression, the accumulation of iNOS and NO in C. pneumoniae-infected bone marrow-derived macrophages and C. trachomatis- infected fibroblasts has been shown to be induced by IFNα/β, independent of IFNγ

(Devitt et al., 1996; Rothfuchs et al., 2001). As such, IFNε may also directly induce the expression of iNOS. IDO inhibits Chlamydia growth by catabolising the essential metabolite, tryptophan (Byrne et al., 1986; Murray et al., 1989; Rapoza et al., 1991).

Importantly, I show that IDO expression is also reduced in IFNε-/- mice, both at baseline and during infection (Figure 3.10 B). However, Nelson et al. have demonstrated that

IFNγ fails to induce IDO in murine epithelial cells, and as such, the role of this pathway in IFNε-mediated responses requires further investigation. Interestingly, conventional

189 type I IFNs have also been shown to induce IDO expression in human macrophages, indicating that IFNε could be inducing the expression of IDO directly (Murray et al.,

1989).

Prior microarray-based gene expression profiling and subsequent bioinformatical analyses suggested that IFNε may regulate the expression of factors involved in IFNγ signalling (Chapter 2). Here, I show that IFNγR1 expression is reduced in IFNε-/- mice during Chlamydia infection (Figure 3.10 C). This provides further evidence for the involvement IFNγ signalling in IFNε-mediated protection. Conversely, I show that

SOCS1 expression is increased in Chlamydia-infected IFNε-/- mice, compared to WT controls (Figure 3.10 D). Importantly, SOCS1 is a potent inhibitor of IFNγ responses via the inhibition of JAK/STAT signalling (Alexander et al., 1999; Federici et al.,

2002). Interestingly, SOCS1 expression has previously been shown to increase upon infection with C. pneumoniae in vivo due to IFNα/β signalling (Yang et al., 2008). As such, the down-regulation of SOCS1 by IFNε is unique and demonstrates its ability to induce divergent responses to those of IFNα/β. The suppression of SOCS1 by IFNε may contribute to protection by enhancing the IFNγ responses that lead to clearance. Taken together, my data suggests that IFNε is importantly in, not only the induction of NK cell responses, but also in the regulation of factors involved in protective IFNγ responses downstream.

Collectively, my data demonstrate that IFNε potentiates NK cell responses in the female RT during Chlamydia infection by, not only increasing systemic NK cell numbers via the promotion of NK cell haematopoiesis in the bone marrow, but also by increasing NK cell number, activation, and IFNγ production at a local level. These

IFNε-mediated effects on NK cell responses play an important role in protecting against

Chlamydia infection. The exact direct and/or indirect mechanisms that underpin how

190 IFNε mediates its effects on NK cells are the focus of ongoing studies, however, my data suggest an important role for local IFNε-mediated IL-15 responses in these effects.

191 : Role of inflammasomes in IFNε-mediated

responses to Chlamydia RTI

4.1 Abstract

In previous studies, I showed that IFNε is constitutively expressed in the female

RT and protects against Chlamydia infection in the vagina and uterus from the earliest stages of infection, suggesting that IFNε has a strong influence on innate responses that protect against Chlamydia infection in the female RT. I then conducted microarray- based gene expression profiling and subsequent bioinformatics analyses of uterine tissue from WT and IFNε-/- mice to identify the innate factors and processes involved in

IFNε-mediated protection. Importantly, I found IL-1β to be a key hub molecule, demonstrating high levels of interconnectivity with other factors regulated by IFNε, in the most significant network associated with genes down-regulated in Chlamydia- infected IFNε-/- mice compared to WT controls. This indicates that IL-1β may play a major role in mediating responses in the female RT downstream of IFNε (Chapter 2).

IL-1β is a potent pro-inflammatory molecule that plays an important role in helping mediate the clearance of infection but is also involved in the pathogenesis of many immunopathological conditions. Importantly, whilst IL-1β is induced during inflammatory responses, it is produced in an immature form (i.e. pro-IL-1β) that needs to be cleaved in order to be activated. One of the key pathways required IL-1β activation is the inflammasome pathway that, once activated, cleaves and activates caspase-1, which, in-term, cleaves pro-IL-1β. Importantly, whilst previous studies have demonstrated that the various factors associated with the inflammasome-mediated, caspase-1/IL-1β signalling pathway affect infection and/or the development of

192 pathology during Chlamydia infections in the female RT, the findings of some of these studies appear to contradict one another.

In this study, I aimed to determine the role of the inflammasome/caspase-1/IL-1β pathway in IFNε-mediated protection against ascending Chlamydia infection in the female RT. Uterine tissues were harvested from Chlamydia or sham-infected WT or

IFNε-/- mice to assess the effects of IFNε deficiency on inflammasome, caspase-1, and

IL-1β responses. I show that IFNε-/- mice have reduced IL-1β mRNA expression in the upper RT at baseline compared to WT controls. In contrast, I show that IL-1β expression is increased in Chlamydia-infected IFNε-/- mice compared to infected WT controls. Importantly, I show that IFNε-/- mice have reduced caspase-1 expression and

NLRP3 cellular accumulation in the upper RT during infection, which suggests that inflammasome-mediated activation of IL-1β may be reduced in the absence of IFNε signalling. I also show that these decreased caspase-1 and NLRP3 responses are associated with a decrease in active caspase-1+ cells in IFNε-/- mice during Chlamydia infection compared to infected WT controls. In order to determine whether the decreased NLRP3 inflammasome activity in IFNε-/- mice contributes to the increased infection observed in this group, I treated Chlamydia-infected WT animals IVAG with the highly specific NLRP3 inhibitor, MCC950. IVAG MCC950 treatment results in a 6- fold increase in Chlamydia levels in the uterus at 3dpi compared to infected, sham- treated WT controls, which demonstrates the importance of the NLRP3 inflammasome in protecting against the early stages of infection.

Together, my findings suggest that IFNε may protect against the early stages of

Chlamydia infection in the upper female RT by promoting inflammasome-mediated responses that restrict early Chlamydia growth and ascending infection.

193 4.2 Introduction

The immune processes involved in the clearance and immunopathology of

Chlamydia RTIs are complex. Importantly, many of the immune responses that have been shown to mediate the clearance of Chlamydia infections are also responsible for the tissue damage that causes disease (Cohen and Brunham, 1999; den Hartog et al.,

2006). This highlights the need for continued research to improve our understanding of the processes that lead to clearance versus those that drive immunopathology in order to inform the best targets for improved therapeutic strategies for the prevention and treatment of not only Chlamydia infection but also infection-induced pathology.

Strong Th1 and IFNγ responses are known to be important for both protection against Chlamydia infection and pathology (Agrawal et al., 2009; Cohen et al., 2005;

Cotter et al., 1997; Debattista et al., 2002a; Johansson et al., 1997a; Perry et al., 1997), whilst increased Th2 and Th type 17 (Th17) responses and neutrophilic inflammation, particularly chronic neutrophilic inflammation in the upper regions of the female RT, have been associated with pathology (Agrawal et al., 2009; Shah et al., 2005). However, the roles of other immune factors and pathways are less clear. In particular, whilst studies have shown that the factors involved in the NLRP3 inflammasome/caspase-

1/IL-1β signalling pathway have important effects on both Chlamydia infection and the development of pathology, some studies have shown show no or opposing effects when examining the same factors. Therefore, research is required to help understand the role of inflammasome-mediated responses in the pathogenesis of Chlamydia infection.

Inflammasomes are signalling complexes that play key roles in the innate immune response to infection. The inflammasome complex consists of a sensor molecule, the adaptor molecule ASC, and caspase-1. Recognition of PAMPs/DAMPs by the sensor molecule triggers inflammasome formation and the autolytic cleavage of pro-caspase-1

194 into its active form. Active caspase-1 then mediates the activation and release of pro- inflammatory cytokines, such as IL-1β and IL-18, via proteolytic cleavage of their pro- forms, as well as the induction of pyroptosis (Fernandes-Alnemri et al., 2007; Proell et al., 2013; Vajjhala et al., 2012). Currently, there are five known inflammasomes

(NLRP1, NLRP3, NLRC4, AIM2, and RIG-I) and these have been shown to work in concert with a number of signalling processes during infection in order to induce inflammasome-mediated caspase-1 recruitment and activation and subsequent cleavage, maturation, and release of IL-1β and IL-18. The NLRP3 inflammasome is the best characterised of the inflammasomes.

Upon pathogen exposure, PAMPs induce PRR activation that not only promotes the production of pro-inflammatory cytokines (including pro-IL-1β) but also the components of the NLRP3 inflammasome, through NF-κB signalling (Bauernfeind et al., 2009; He et al., 2013; Hiscott et al., 1993; Schindler et al., 1990). The assembly and activation of the inflammasome complex, however, requires the presence of a second signal, either PAMPs or DAMPs, which, in the case of infection, are produced by pathogen-induced cell and tissue damage (Sutterwala et al., 2014). Upon activation, the

NLRP3 inflammasome oligomerises and recruits the adaptor molecule, ASC (Figure

1.5 C) (Agostini et al., 2004; Fernandes-Alnemri et al., 2007). ASC then recruits pro- caspase-1, facilitating its autocatalytic cleavage into 20-kDa (p20) and 10-kDa (p10) subunits which assemble into the tetrameric active enzyme (Figure 1.5 C) (Thornberry et al., 1992; Wilson et al., 1994). Active caspase-1 then activates pro-inflammatory cytokines of the IL-1 family, such as IL-1β and IL-18 (Figure 1.5) (Gu et al., 1997;

Martinon et al., 2002; Thornberry et al., 1992).

IL-1β responses are important for the induction of a range of anti-microbial processes that control infection, however, they are also responsible for the aberrant

195 inflammatory responses that drive pathology in both infection- and non-infection- associated diseases (Prantner et al., 2009). As such, IL-1β signalling has been shown to both protect against Chlamydia infection and contribute to the development of pathology in vivo (Nagarajan et al., 2012; Prantner et al., 2009; Shimada et al., 2011).

Both IL-1β-/- and IL-1R-/- mice have been shown to be less likely to develop oviduct pathology, but more susceptible to Chlamydia RTIs, with both strains exhibiting delayed clearance and increased shedding of Chlamydia from the vagina (Nagarajan et al., 2012; Prantner et al., 2009).

Interestingly, in in vitro studies, caspase-1 activation in epithelial cells has been shown to augment Chlamydia growth (Abdul-Sater et al., 2009). However, caspase-1-/- mice are more susceptible to respiratory tract C. pneumoniae infections and exhibit increased pathology and a higher rate of mortality due to defective innate responses, including reduced iNOS levels, and delayed IFNγ and IL-6 production (Shimada et al.,

2011). Conversely, caspase-1 deficiency protects against the development of

Chlamydia-induced infertility but has no effect on Chlamydia load in the vagina during

C. trachomatis RTI (Cheng et al., 2008; Igietseme et al., 2013). These studies did not measure IL-1β levels in the RT.

2009; Shimada et al., 2011) in response to infection with Chlamydia in vitro has been shown to be dependent on activation of the NLRP3 inflammasome. Intriguingly, however, despite the requirement for NLRP3 in Chlamydia-induced IL-1β production by macrophages, ASC-/- and NLRP3-/- mice have normal levels of IL-1β from 3dpi and

ASC-/-, but not NLRP3-/-, mice exhibit a delay the clearance of Chlamydia from the

196 vagina but no change in the development of oviduct pathology, following infection

(Nagarajan et al., 2012). This suggests, not only redundancies in IL-1β production, but also the involvement of other ASC-containing inflammasomes and protective, IL-1β- independent inflammasome responses. Indeed, recent evidence from in vitro studies indicates that the AIM2 inflammasome is also activated by Chlamydia and contributes to IL-1β and IL-18 responses during infection (Finethy et al., 2015), however the consequences of this activation on infection and pathology are not yet known.

Taken together, these studies suggest that the role of the NLRP3 inflammasome/caspase-1/IL-1β signalling axis in protection against Chlamydia infection and associated pathology is complex and the factors involved in this pathway may mediate divergent responses. Therefore, more research is required to help clarify the roles of inflammasomes, caspase-1, and IL-1β in protection against, and pathogenesis of, Chlamydia infection and associated disease in the female RT.

Importantly, type I IFN signalling has been shown to play a role in inflammasome and caspase-1 activation. Interestingly, ASC-mediated caspase-1 activation and subsequent IL-1β secretion and pyroptosis have been shown to be dependent on type I

IFN responses during cytosolic bacterial infections (Fernandes-Alnemri et al., 2010;

Henry et al., 2007; Rathinam et al., 2010). Type I IFN signalling appears to mediate activation of the NLRP3 inflammasome via induction of caspase-4 (Henry et al., 2007;

Malireddi and Kanneganti, 2013), which has been shown to be required for optimal

NLRP3 and AIM2 inflammasome activation (Sollberger et al., 2012). Caspase-4 is capable of, either directly or indirectly, processing caspase-1 and mediates a number of caspase-1-independent functions, including phago-lysosomal fusion and cell lysis

(Akhter et al., 2012; Kayagaki et al., 2011; Sollberger et al., 2012).

197 In Chapter 2, I show that IFNε protects against Chlamydia infection in the uterus from the earliest stages of infection, suggesting that it plays a role in priming innate responses that protect against ascending Chlamydia infection in the female RT. Using whole-genome microarray gene expression analyses and IPA®, I also show that IL-1β may be a key factor involved in molecular networks induced downstream of IFNε signalling. In Chapter 4, I extend upon these findings in order to investigate the relationship between protective IFNε-mediated responses and the NLRP3 inflammasome/caspase-1/IL-1β signalling pathway during the early stages of

Chlamydia female RTI.

198 4.3 Methods

4.3.1 Ethics statement

Council (Australia). All protocols were approved by the University of Newcastle

Animal Care and Ethics Committee.

4.3.2 C. muridarum female RTI

Adult (6-8 weeks old) female WT or IFNε-/-, C57BL/6 mice were pre-treated with 2.5mg DPMA (Depo-Provera; Pfizer) SC to prime for infection and synchronise their oestrous cycles. Seven days later, mice were infected IVAG with 5 x 104ifu C. muridarum (ATCC VR-123) in 10μL SPG or sham-infected with SPG alone under ketamine:xylazine anaesthesia (80mg/kg:5mg/kg IP; Ilium Ketamil® and Ilium Xylazil-

20®; Troy Laboratories) as described previously (Asquith et al., 2011). Mice were sacrificed by sodium pentobarbital (Lethabarb; Virbac) overdose at 3dpi and tissues collected for the analysis of inflammasome responses.

4.3.3 In vivo inhibition of the NLRP3 inflammasome

To determine the role of the NLRP3 inflammasome in Chlamydia RTIs, progesterone-pre-treated WT mice were administered 10mg/kg MCC950 NLRP3 inhibitor (compound provided by Prof. Matt Cooper, The University of Queensland,

Australia) in 20μL sterile saline with 4% dimethyl sulfoxide (DMSO) or vehicle alone

IVAG under isoflurane anaesthesia on days -2, -1, 0, 1, and 2 post infection. Mice were

199 sacrificed by sodium pentobarbital (Lethabarb; Virbac) overdose at 3dpi and tissues collected for the analysis of infection and immune responses.

Figure 4.1: In vivo local inhibition of NLRP3 during Chlamydia muridarum female reproductive tract infection (RTI). Wild-type (WT) C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi), administered 10mg/kg MCC950 NLRP3 inhibitor or saline vehicle intravaginally (IVAG) at -2, -1, 0, 1 and 2dpi and infected with C. muridarum IVAG. Mice were sacrificed at 3dpi to assess the effects of local NLRP3 inhibition on infection and immune responses in the upper reproductive tract (RT).

4.3.4 Total RNA extraction

Uterine horn tissue was harvested from mice, immediately snap frozen and stored at -80°C until processing for qPCR analysis.

Total RNA was extracted from uterine tissue using TRIzol® Reagent (Thermo

200 ethanol and resuspended in nuclease-free dH2O. Concentration and purity of RNA samples were quantified using a NanoDrop™ 1000 Spectrophotometer (Thermo Fisher

Scientific).

4.3.5 Reverse transcription and real-time qPCR

1µg total RNA was treated with DNase I in a reaction volume of 10µL for 15 minutes at room temperature (Sigma-Aldrich) and the reaction stopped via addition of stopping solution and incubation at 65°C for 10 minutes. RNA was then reverse transcribed using BioScript™ reverse transcriptase enzyme and random hexamer primers (Bioline), according to the manufacturer’s instructions, as previously described

(Starkey et al., 2013). Briefly, 2µL 50ng/µL random hexamer primers and 1µL 10mM dNTP mix (Bioline) were added to the RNA and incubated at 65°C for 5 minutes. 4µL

5X reaction buffer (Bioline), 1µL 0.1mM DTT (Invitrogen), 1µL nuclease free H2O, and 1µL BioScript™ (Bioline) were then added to the reaction and incubated at 25°C for 20 minutes, 42°C for 50 minutes, and 70°C for 15 minutes. DNA was then resuspended in nuclease free H2O up to a volume of 100µL and stored at -20°C until qPCR analysis.

50°C for 2 minutes, 95°C for 2 minutes, and 40 cycles of 95°C for 15 seconds and 55-

65°C (based on results of prior temperature gradient tests) for 1 minute, followed by dissociation analysis (Horvat et al., 2010; Phipps et al., 2007). Expression of target genes relative to the housekeeping gene control, HPRT, were then calculated.

201 4.3.6 Chlamydia load

Total RNA was extracted from uterine horn tissue and Chlamydia 16S rRNA expression relative to HPRT was determined via real-time qPCR as described previously (Asquith et al., 2011; Fung et al., 2013). Primers used are described in

Appendix A: sTable 1.1.

4.3.7 Caspase-1 activity assay

Uterine horn tissue was excised and digested by gently dissociating in 5mL

HEPES buffer using C tubes and a gentleMACS™ Dissociator (Miltenyi Biotech) and incubating with 2mg/mL collagenase-D and 40U/mL DNase I (Roche) at 37°C for 30 minutes. Cells were then passed through a 70μm nylon cell strainer to remove debris and incubated with RBC lysis buffer at 4°C for 5 minutes. Total cell numbers were enumerated by trypan blue exclusion using a Countess™ automated cell counter

(Invitrogen) and samples placed in a 96 well plate at 1 x 106 cells/well. Cells were resuspended in supplemented RPMI 1640 media (GIBCO, Invitrogen) and 30X FAM-

FLICA® fluorescent caspase-1 inhibitor probe solution (FAM-YVAD-FMK; Sapphire

Bioscience, Redfern, NSW) added to a volume of 200μL. Cells were then incubated at

37°C for 1 hour, washed, and stained for surface markers as below (Wree et al., 2014).

4.3.8 Flow cytometry

Uterine horn tissue was excised and digested by gently dissociating in 5mL

202 enumerated by trypan blue exclusion using a Countess™ automated cell counter

(Invitrogen) and cells placed in a 96 well plate at 0.5-1 x 106 cells/well.

Cells were incubated with 10ng/mL mouse Fc receptor block (anti-mouse

CD16/32; BD Biosciences) in 100μL FACS buffer at 4°C for 15 minutes and stained for a combination of the surface markers CD45, CD3, NK1.1, CD11b, GR1, F4/80, and

CD11c (Biolegend or BD Biosciences) by incubation with fluorochrome (PerCP, APC,

APC-Cy7, PE-Cy7, AF700, BV421, or BV605)- or biotin-conjugated antibodies at 4°C for 20 minutes (Table 4.1). Samples stained with biotin-conjugated antibodies were subsequently stained with streptavidin-conjugated fluorochromes (Table 4.1). Optimal concentrations for all antibody- and streptavidin-conjugated fluorochromes were determined by prior titration experiments. Stained cells were washed, fixed in 4% paraformaldehyde and analysed by flow cytometry using a FACSAria™ III and

FACSDiva software (BD Biosciences) (Beckett et al., 2012). The percentage and total number of different immune cell populations in the uterine tissue were determined based on FSC and SSC and characteristic surface marker expression profiles (Table

4.2) (Beckett et al., 2012; Yadi et al., 2008).

Table 4.1: Staining cocktail used for flow cytometric profiling of active caspase-1+ cells

Caspase-1 activity stain FAM-YVAD-FMK

CD3-APC CD45-PerCP CD11c-PE-Cy7 NK1.1-Biotin F4/80-BV605 CD11b-AF700 GR1-APC-Cy7

Streptavidin-BV421

203 Table 4.2: Characterisation of cell populations

Cell type Surface marker expression FSC/SSC profile Leukocyte CD45+ Structural cell CD45- T cell CD45+ CD3+ FSClow-int SSClow Natural killer (NK) cell CD45+ CD3- NK1.1+ FSClow-int SSClow Myeloid dendritic cell (mDC) CD45+ CD11c+ CD11b+ GR1- FSClow-int SSClow-int Plasmacytoid (p)DC CD45+ CD11c+ CD11b- GR1+ FSClow-int SSClow-int Monocyte/Macrophage CD45+ F4/80+ FSCint SSCint Neutrophil CD45+ F4/80- GR1+ CD11b+ FSClow-int SSCint-high

4.3.9 NLRP3 immunofluorescence staining

Uterine horn tissue was fixed in formalin, embedded in paraffin then sectioned in the transverse plane (~4μm thickness). Sections were then deparaffinised using xylene and rehydrated in ethanol/water gradients. Antigen retrieval was performed by incubating sections in 0.05% citraconic anhydride buffer (pH 7.4) for 40 minutes at

80°C. Sections were washed in PBS-Tween (PBS-T; PBS, 0.05% Tween-20), dried and blocked with Blocker™ Casein in PBS (Thermo Fisher Scientific) for 30 minutes at room temperature in a humidified chamber. Sections were incubated with primary goat anti-NLRP3 polyclonal antibody (ab4207; Abcam) in PBS-T at 4°C overnight, washed, and incubated with secondary rabbit anti-goat IgG H&L AF488 antibody (ab150145;

Abcam) in PBS-T at room temperature for 1.25 hours in a humidified chamber. For nuclear detection, sections were incubated with Hoechst 33342 Solution (Thermo Fisher

Scientific) in PBS at room temperature for 5 minutes. Stained sections were washed then mounted using FluorSave™ reagent (345789; Calbiochem® Merck Millipore,

Bayswater, VIC, Australia). Slides were analysed using an Olympus BX51 Fluorescent

Microscope with Image-Pro® Plus software (Media Cybernetics, Rockville, MD, USA).

204 4.3.10 Statistics

All data are presented as mean ±SEM. Statistical significance for comparisons between two groups determined using unpaired t-Tests, or non-parametric equivalent, where appropriate. Statistical significance for comparisons between three or more groups was determined by one-way ANOVA with appropriate post-hoc test, or non- parametric equivalent, where appropriate. Statistical analyses were performed using

GraphPad Prism 6 software.

205 4.4 Results

4.4.1 IFNε deficiency reduces the expression of IL-1β and

caspase-1 in the female RT

My previous microarray profiling studies identified IL-1β as a potential key factor involved in mediating responses downstream of IFNε signalling (Chapter 2).

Inflammasomes are key innate immune complexes play important roles in the activation of IL-1β responses. To further explore the role of inflammasome-mediated IL-1β responses in IFNε-mediated protection against Chlamydia RTIs, I initially assessed mRNA expression levels of a number of factors involved in inflammasome activation and signalling in uterine tissue from both Chlamydia- and sham-infected WT and IFNε-/- mice at 3dpi.

I show that IL-1β expression is significantly lower in sham-infected IFNε-/- mice compared to their WT controls (Figure 4.2 A), suggesting that baseline IL-1β responses are deficient in the absence of IFNε signalling. This may account for a decreased initial response to Chlamydia in IFNε-/- mice that results in increased susceptibility to infection. Interestingly, I show that during Chlamydia infection, IL-1β expression is trending towards an increase in IFNε-/- mice compared to infected WT controls (Figure

4.2 A). This is likely due to the increased Chlamydia in the uterine tissue of IFNε-/- mice

(>900-fold increase compared to WT controls) which may be resulting in increased

PAMP:PRR signalling-induced expression of IL-1β. I did not observe any differences in

IL-18 expression levels between WT and IFNε-/- mice in either the absence or presence of Chlamydia infection (Figure 4.2 B). Most significantly, I show that caspase-1 expression is significantly decreased in IFNε-/- mice, both at baseline and during

Chlamydia infection, compared to WT controls (Figure 4.2 C). This suggests that there

206 may be deficiencies in caspase-1-mediated activation of both IL-1β and IL-18 in the uterine tissue of IFNε-/- mice during infection. I also show that expression levels of

TLR2 (Figure 4.2 D), TLR4 (Figure 4.2 E) and TLR9 (Figure 4.2 F) are not significantly altered in IFNε-/-, which suggests that any changes in IL-1β and caspase-1 expression are not associated with the altered expression of key PRRs that are activated by Chlamydia infection.

207 A B C

0.03 0.0736 0.15 0.4 * *

0.3 0.02 0.10

* 0.2

0.01 0.05 0.1

Relative Expression (to HPRT) (to Expression Relative 0.00 0.00 0.0 β IL-18 Relative Expression (to HPRT) (to Expression Relative IL-18 IL-1 SPG Cmu SPG Cmu SPG Cmu SPG Cmu SPG Cmu SPG Cmu

WT IFN ε -/- WT IFN ε -/- HPRT) (to Expression Caspase-1 Relative WT IFN ε -/-

D E F

0.3 0.3 0.04 0.0660 0.0519 0.03 0.2 0.2

0.02

0.1 0.1 0.01

0.0 0.0 0.00 TLR4 Relative Expression (to HPRT) (to Expression TLR4 Relative HPRT) (to Expression TLR9 Relative TLR2 Relative Expression (to HPRT) (to Expression TLR2 Relative SPG Cmu SPG Cmu SPG Cmu SPG Cmu SPG Cmu SPG Cmu

WT IFN ε -/- WT IFN ε -/- WT IFN ε -/-

Figure 4.2: Interferon (IFN)ε deficiency alters the messenger (m)RNA expression of interleukin (IL)-1β and caspase-1 in the female reproductive tract (RT). Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum (Cmu) or sham-infected with sucrose-phosphate- glutamate buffer (SPG). IL-1β (A), IL-18 (B), caspase-1 (C), toll-like receptor (TLR)2 (D), TLR4 (E), and TLR9 (F) mRNA expression was quantified via qPCR at 3dpi to assess the effect of IFNε deficiency on expression of key inflammasome-related factors in the upper RT. Target gene mRNA expression was normalised against expression of the housekeeping gene control, hypoxanthine-guanine phosphoribosyltransferase (HPRT; one experiment; n≥5). All data are presented as mean±SEM. *=p<0.05; **=p<0.01.

208 4.4.2 IFNε deficiency reduces caspase-1 activation in the

female RT

Since I show that caspase-1 expression in the female RT is decreased in IFNε-/- mice, the next aim was to determine whether these changes were associated with a decrease in caspase-1 activation. To assess the effects of IFNε signalling on the level and cellular source of caspase-1 activation in the upper RT, I incubated uterine cells from Chlamydia-infected WT and IFNε-/- mice with the fluorescent caspase-1 inhibitor probe, FAM-YVAD-FMK. FAM-YVAD-FMK is a fluorochrome-conjugated molecule that irreversibly binds to the active site in cleaved caspase-1. I then stained these cells for key markers to allow for the identification of likely sources of IFNε-induced caspase-1 activation (Table 4.1) and performed flow cytometric analysis. This method allows for the detection and characterisation of active caspase-1+ cells (Wree et al.,

2014).

I show that, in WT mice, structural cells are the most abundant caspase-1+ cells, followed by macrophages and NK cells (Figure 4.3 & 4.4). I show that, whilst there is no difference between the numbers of active caspase-1+ structural cells in the female

RTs of WT and IFNε-/- mice during Chlamydia infection (Figure 4.3 A & E), there is a significant decrease in the number of active caspase-1+ leukocytes, represented as a percentage of viable cells, in IFNε-/- mice during infection compared to WT controls

(Figure 4.3 B). There is also a trend towards a decrease in the total number of active caspase-1+ leukocytes present in the RT (Figure 4.3 F), however, an increase in replicates may be required to achieve significance. This reduction in the percentage of active caspase-1+ leukocytes appears to be as a result of reduced numbers of active caspase-1+ NK cells, macrophages, and pDCs, rather than neutrophils, mDCs, or T-cells

(Figure 4.3 & 4.4).

209 I also calculated the frequency of active caspase-1+ cells within each cell type as a percentage of their parent population. I show that there is a strong trend towards a reduction in the percentage of leukocytes positive for active caspase-1 in Chlamydia- infected IFNε-/- mice compared to that of WT controls (Figure 4.5 B). Importantly, the percentage of NK cells positive for active caspase-1 in Chlamydia-infected IFNε-/- mice is reduced by ~60% compared to that of WT controls (Figure 4.5 C). This demonstrates that the reduction in the number of active caspase-1+ cells in these populations are due to a reduction in the frequency of active caspase-1 positivity rather than a reduction in total cell number.

210 A B C D

10 1.5 0.20 1.0

8 0.8 0.15 1.0 6 0.6 * * 0.10 4 0.4 0.5 0.05 2 ** 0.2

0 0.0 0.00 0.0

-/- -/- Caspase-1+ NK (%)Active Cells -/- -/- ε ε ε ε

WT Caspase-1+ Leukocytes (%)Active WT WT WT Active Caspase-1+ MacrophagesActive (%) IFN IFN IFN

Active Caspase-1+ Structural Cells (%) Cells Caspase-1+Active Structural IFN

E F G H

4.0× 10 4 6.0× 10 3 8.0× 10 2 4.0× 10 3

3.0× 10 4 6.0× 10 2 3.0× 10 3 4.0× 10 3 0.0802

2.0× 10 4 4.0× 10 2 2.0× 10 3

2.0× 10 3 1.0× 10 4 2.0× 10 2 * 1.0× 10 3

0 0 NK Caspase-1+ Cells Active 0 0 Active Caspase-1+ Leukocytes Caspase-1+ Active

-/- -/- -/- Caspase-1+Active Macrophages -/- ε ε ε ε

Active Caspase-1+ Structural Cells Caspase-1+ Structural Active WT WT WT WT IFN IFN IFN IFN

Figure 4.3: Interferon (IFN)ε deficiency decreases the number of active caspase-1+ natural killer (NK) cells and macrophages present in the female reproductive tract (RT) during Chlamydia infection. Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum. Active caspase-1 was detected in uterine tissue at 3dpi using FAM-YVAD-FMK fluorescent caspase-1 inhibitor reagent and percentages (of viable cells) and total numbers of active caspase-1+ structural cells (A & E), total leukocytes (B & F), NK cells (C & G), and macrophages (D & H) in the upper RT were quantified via flow cytometry to assess the effect of IFNε deficiency on active caspase-1+ cells during infection (one experiment; n=6 replicates of pooled uterine homogenate samples). All data are presented as mean±SEM. *=p<0.05; **=p<0.01.

211 A B C D

0.025 0.08 0.020 0.0015

0.020 0.06 0.015 0.0010 0.015 0.04 0.010 0.010 * 0.0005 0.02 0.005 0.005

0.000 0.00 0.000 0.0000 Active Caspase-1+Active pDCs (%) Active Caspase-1+ mDCsActive (%) Active Caspase-1+ T Cells (%) Caspase-1+ TActive Cells -/- -/- -/- -/- WT ε WT ε WT ε WT ε Active Caspase-1+ Neutrophils (%) Caspase-1+ Neutrophils Active IFN IFN IFN IFN

E F G H

1.0× 10 2 3.0× 10 2 6.0× 10 1 5.0× 10 0

8.0× 10 1 4.0× 10 0

2.0× 10 2 4.0× 10 1 6.0× 10 1 3.0× 10 0

4.0× 10 1 2.0× 10 0 1.0× 10 2 2.0× 10 1

2.0× 10 1 1.0× 10 0 Active Caspase-1+ Caspase-1+ pDCsActive Active Caspase-1+Active mDCs 0 0 0 Caspase-1+ Active T Cells 0 Active Caspase-1+ Neutrophils Caspase-1+ Active -/- -/- -/- -/- WT ε WT ε WT ε WT ε IFN IFN IFN IFN

Figure 4.4: Interferon (IFN)ε deficiency decreases the number of active caspase-1+ plasmacytoid dendritic cells (p/DCs) present in the female reproductive tract (RT) during Chlamydia infection. Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum. Active caspase- 1 was detected in uterine tissue at 3dpi using FAM-YVAD-FMK fluorescent caspase-1 inhibitor reagent and percentages (of viable cells) and total numbers of active caspase-1+ neutrophils (A & E), pDCs (B & F), myeloid (m)DCs (C & G), and T cells (D & H) in the upper RT were quantified via flow cytometry to assess the effect of IFNε deficiency on active caspase-1+ cells during infection (one experiment; n=6 replicates of pooled uterine homogenate samples). All data are presented as mean±SEM. *=p<0.05.

212 A B C D

15 50 30 100

40 80

10 0.0726 20 30 60

20 40 5 10 * (% NK Cells) NK (% (%Leukocytes)

10 (% Macrophages) 20 (% Structural Cells) (% Structural

0 0 NK Caspase-1+ Cells Active 0 0 Active Caspase-1+ Leukocytes Caspase-1+ Active

-/- -/- -/- Caspase-1+Active Macrophages -/- ε ε WT ε ε Active Caspase-1+ Structural Cells Caspase-1+ Structural Active WT WT WT IFN IFN IFN IFN E F G H

25 50 15 6

20 40

10 4 15 30 0.0609

10 20 5 2

(% Neutrophils) (% 5 10

0 0 0 0 Active Caspase-1+ Neutrophils Caspase-1+ Active -/- -/- -/- -/- WT ε WT ε WT ε WT ε Active Caspase-1+ pDCs Caspase-1+ (% pDCs)Active Active Caspase-1+ mDCsActive (% mDCs) IFN IFN IFN (% T Caspase-1+ Cells) T Cells Active IFN

Figure 4.5: Interferon (IFN)ε deficiency decreases the percentage of natural killer (NK) cells expressing active caspase-1 in the female reproductive tract (RT) during Chlamydia infection. Wild- type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum. Active caspase-1 was detected in uterine tissue at 3dpi using FAM-YVAD-FMK fluorescent caspase-1 inhibitor reagent and percentages of structural cells (A), total leukocytes (B), NK cells (C), macrophages (D), neutrophils (E), plasmacytoid dendritic cells (p/DCs; F), myeloid (m)DCs (G), and T cells (H) positive for active caspase-1 quantified via flow cytometry to assess the effect of IFNε deficiency on caspase-1 activation in immune cell populations in the upper RT during infection (one experiment; n=6 replicates of pooled uterine homogenate samples). All data are presented as mean±SEM. *=p<0.05.

213 4.4.3 IFNε deficiency decreases expression of NLRP3 in the

female RT

Activation of caspase-1 in epithelial cells (Abdul-Sater et al., 2009) and macrophages (Abdul-Sater et al., 2010; Prantner et al., 2009; Shimada et al., 2011) during in vitro infection with Chlamydia has been shown to be dependent on the

NLRP3 inflammasome. Given that I show that IFNε-/- mice exhibit decreased caspase-1 expression (Figure 4.2 C) and activation (Figure 4.3), I next sought to determine if

NLRP3 inflammasome responses are also decreased in IFNε-/- mice and if they are responsible for these IFNε-mediated changes. In order to investigate NLRP3 levels and cellular source, I conducted immunofluorescent staining for NLRP3 in uterine histology sections from Chlamydia- and sham-infected WT and IFNε-/- mice.

I show limited NLRP3 staining in the uterine tissue from WT and IFNε-/- mice at baseline (Figure 4.6). Some staining is detectable in the endometrial epithelial layer and smooth muscle cells of the myometrium (Figure 4.6), with little difference between the intensity of staining observed between the sham-infected, WT and IFNε-/- groups.

Significantly, I show that Chlamydia infection results in an increase in aggregates of intense NLRP3 staining in the endometrial epithelial layer, endometrial glands, and immune cells in the endometrial stromal tissue of WT mice, with the most intense staining observed in the cells of the endometrial glands (Figure 4.6). Importantly, the intensity of NLRP3 staining in these cells/tissues was greatly decreased in Chlamydia infected IFNε-/- mice compared to WT controls (Figure 4.6). Indeed, little-to-no staining can be seen in the endometrial glands of the infected, IFNε-/- mice.

214 WT IFNε-/-

SPG

Cmu

Figure 4.6: Interferon (IFN)ε deficiency decreases NLRP3 protein expression in endometrial epithelial cells during Chlamydia infection. Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum (Cmu) or sham-infected with sucrose-phosphate-glutamate buffer (SPG). Immunofluorescent straining for NLRP3 (green) was performed on formalin-fixed paraffin-embedded uterine tissue and samples counter stained with Hoechst 33342 for nuclear detection (blue) at 3dpi to assess the effect of IFNε deficiency on NLRP3 expression at baseline and during infection. Images are representative of results from multiple sections of 3 uterine tissue samples per experimental group.

215 4.4.4 The NLRP3 inflammasome protects against Chlamydia

infection of the female RT

I show that NLRP3, caspase-1, and IL-1β responses are all decreased in IFNε-/- mice compared to WT controls. I next sought to determine if NLRP3 inflammasome inhibition would have similar effects on Chlamydia infection in the RT as IFNε deficiency. NLRP3 inflammasome activity was inhibited in progesterone-pre-treated

WT mice through IVAG administration of MCC950 from 2 days prior to Chlamydia infection and then daily until 3dpi. The effects of NLRP3 inflammasome inhibition on infection and the number of active caspase-1+ cells in uterine tissues were analysed and compared with sham-treated, Chlamydia-infected WT mice.

I show that, compared to sham-treated controls, MCC950-treated mice have a 6- fold increase in Chlamydia 16S expression in the uterine tissue at 3dpi (Figure 4.7 A).

This significant result demonstrates, for the first time, that the NLRP3 inflammasome plays an important role in protecting against an ascending Chlamydia infection in the female RT. Similar results are observed with post infection MCC950 treatment (data not shown). Surprisingly, I did not observe any suppression in the level of active caspase-1+ cells in the uterine tissue of MCC950-treated mice compared to sham-treated controls

(Figure 4.8). This may suggest that, despite the fact that treatment has a significant effect on ascending infection, MCC950 treatment may be having its effects in the vagina and/or cervix rather than uterus or there may be other inflammasomes mediating caspase-1 activation in a redundant manner in the uterus during Chlamydia infection when NLRP3 activity is inhibited.

Since activation of the NLRP3 inflammasome has been implicated in induction of NK cell responses (Kupz et al., 2014; Serti et al., 2014) and since I, and others, show

216 the importance of these cells in protecting against infection (Chapter 3) (Jiao et al.,

2011; Tseng and Rank, 1998), I also explored the effect of NLRP3 inhibition on NK cell responses to Chlamydia infection.

Interestingly, I show that MCC950 treatment did not affect the number of NK cells or expression of factors associated with NK cell responses in the uterus of

Chlamydia-infected WT mice compared to sham-treated controls (Figure 4.7). Since I decided to stain for active caspase-1 and other cell populations in these NLRP3 inhibition studies and since the number of cells sourced from uterine tissue is limited, it was not feasible to also investigate the effects of MCC950 on NK cell activation or

IFNγ production.

217 A B C

0.1 2.0 2.5× 10 4

* 4 2.0× 10 1.5

16S 0.01 1.5× 10 4 1.0 1.0× 10 4 0.001 NK Cells NK (%) Cells

Chlamydia 0.5 5.0× 10 3

0.0001 0.0 0 Relative Expression (to HPRT) (to Expression Relative

S aline S aline S aline MCC950 MCC950 MCC950

D E F

0.008 0.20 0.10

0.08 0.006 0.15 0.0642 0.06 0.004 0.10 0.04

0.002 0.05 0.02

Relative Expression (to HPRT) (to Expression Relative 0.000 0.00 0.00 γ IFN IL-15 Relative Expression (to HPRT) (to Expression Relative IL-15 S aline S aline S aline CXCL10 Relative Expression (to HPRT) (to Expression CXCL10 Relative MCC950 MCC950 MCC950

Figure 4.7: Intravaginal (IVAG) NLRP3 inhibition increases Chlamydia replication but does not alter natural killer (NK) cell responses in the upper reproductive tract (RT). Wild-type (WT) C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi), administered 10mg/kg MCC950 NLRP3 inhibitor or saline vehicle IVAG at -2, -1, 0, 1 and 2dpi and infected IVAG with Chlamydia muridarum. Chlamydia 16S ribosomal (r)RNA expression in uterine tissue was quantified via qPCR at 3dpi to assess the effects of local NLRP3 inhibition on infection in the upper RT (A; one experiment; n=8). Percentage (of viable cells; B) and total numbers (C) of NK cells were quantified via flow cytometry (one experiment; n≥7 replicates of pooled uterine homogenate samples) and messenger (m)RNA expression of IFNγ (D), interleukin (IL)-15 (E), and C-X-C motif chemokine ligand (CXCL)10 (F) quantified via qPCR (one experiment; n=8) in uterine tissues at 3dpi to assess the effect of NLRP3 inhibition on NK responses in the upper RT. Target gene mRNA expression was normalised against expression of the housekeeping gene control, hypoxanthine-guanine phosphoribosyltransferase (HPRT). All data are presented as mean±SEM. *=p<0.05.

218 A B C

60 1.5 0.15

40 1.0 0.10

20 0.5 0.05

0 0.0 0.00 Active Caspase-1+ NK (%)Active Cells Active Caspase-1+ Leukocytes (%)Active

S aline S aline S aline Active Caspase-1+ Structural Cells (%) Cells Caspase-1+Active Structural MCC950 MCC950 MCC950

D E F

5 3 8.0× 10 1.5× 10 4 2.0× 10

6.0× 10 5 1.5× 10 3 1.0× 10 4

4.0× 10 5 1.0× 10 3

5.0× 10 3 2.0× 10 5 5.0× 10 2

0 0 NK Caspase-1+ Cells Active 0 Active Caspase-1+ Leukocytes Caspase-1+ Active Active Caspase-1+ Structural Cells Caspase-1+ Structural Active

S aline S aline S aline MCC950 MCC950 MCC950

Figure 4.8: Intravaginal (IVAG) NLRP3 inhibition does not alter caspase-1 activation in the upper reproductive tract (RT). Wild-type (WT) C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi), administered 10mg/kg MCC950 NLRP3 inhibitor or saline vehicle IVAG at -2, -1, 0, 1 and 2dpi and infected IVAG with Chlamydia muridarum. Active caspase-1 was detected in uterine tissue at 3dpi using FAM-YVAD-FMK fluorescent caspase-1 inhibitor reagent and percentages (of viable cells) and total numbers of active caspase-1+ structural cells (A & D), total leukocytes (B & E), and natural killer (NK) cells (C & F) were quantified via flow cytometry to assess the effects of IVAG MCC950 administration on active caspase-1+ cells in the upper RT during infection (one experiment; n≥7 replicates of pooled uterine homogenate samples). All data are presented as mean±SEM.

219 4.4.5 IFNε deficiency affects multiple inflammasome and

caspase signalling pathways in the female RT

Whilst I show that NLRP3 inflammasome, caspase-1, and IL-1β responses are altered in IFNε-/- mice, NLRP3 inhibition in WT mice through IVAG administration of

MCC950 does not affect the level of active caspase-1+ cells in the uterus (Figure 4.8) nor does it have the same effect on Chlamydia infection as IFNε deficiency (Figure 4.7

A). These findings suggest that MCC950 treatment may be having its effects in the vagina and/or cervix rather than uterus or that IFNε may be mediating protection against infection through pathways that are either independent or redundant to its effects on

NLRP3 inflammasome and/or caspase-1 signalling. A recent study by Finethy et al. showed that Chlamydia activates AIM2 as well as NLRP3 inflammasomes (Finethy et al., 2015). Furthermore, type I IFNs have been shown to increase caspase-4 responses that can not only activate the AIM2 inflammasome, but also interact with and mediate

NLRP3 inflammasome activation and signalling through non-canonical pathways

(Henry et al., 2007; Malireddi and Kanneganti, 2013; Sollberger et al., 2012). To further explore the role of other inflammasome signalling pathways in IFNε-mediated protection against Chlamydia RTIs, I assessed the mRNA expression levels of caspase-

4 and AIM2 in uterine tissue from both Chlamydia- and sham-infected WT and IFNε-/- mice at 3dpi.

Significantly, I show that caspase-4 expression is significantly lower in sham- infected IFNε-/- mice compared to their WT controls (Figure 4.9 A), suggesting that baseline caspase-4 levels are deficient in the absence of IFNε signalling. Furthermore, I also show that AIM2 expression increases during Chlamydia infection in WT mice, however, this increase is not observed in IFNε-/- mice (Figure 4.9 B). My results show

220 that, aside from NLRP3, capase-1, and IL-1β responses, IFNε also regulates AIM2 inflammasome and caspase-4 expression in the female RT.

221 A B

0.6 3 ** * *

0.4 2

0.2 1

0.0 0

SPG Cmu SPG Cmu HPRT) (to Expression AIM2 Relative SPG Cmu SPG Cmu

Caspase-4 Relative Expression (to HPRT) (to Expression Caspase-4 Relative WT IFN ε -/- WT IFN ε -/-

Figure 4.9: Interferon (IFN)ε deficiency decreases the messenger (m)RNA expression of caspase-4 at baseline and absent in melanoma 2 (AIM2) during Chlamydia infection in the female reproductive tract (RT). Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum (Cmu) or sham-infected with sucrose-phosphate-glutamate buffer (SPG). Caspase-4 (A) and AIM2 (B) mRNA expression were quantified via qPCR at 3dpi to assess the effect of IFNε deficiency on expression of key factors involved in alternate inflammasome-related pathways in the upper RT. Target gene mRNA expression was normalised against expression of the housekeeping gene control, hypoxanthine-guanine phosphoribosyltransferase (HPRT; one experiment; n≥5). All data are presented as mean±SEM. *=p<0.05; **=p<0.01.

222 4.5 Discussion

In this study, I show for the first time that IFNε regulates NLRP3 and AIM2 inflammasome, caspase-1 and caspase-4, and IL-1β responses in the uterus and that

NLRP3 inflammasome-mediated signalling may be contributing to IFNε-mediated protection during the earliest stages of Chlamydia infections in the female RT.

In the studies described in Chapter 2, I demonstrate that the increase in susceptibility to Chlamydia RTIs observed in IFNε-/- mice correlates with changes in both baseline and infection-induced gene expression patterns in the upper RT (Chapter

2). These studies suggested the involvement of, and highlighted a potential role for, IL-

1β in IFNε-mediated responses in the female RT and in protection during the early stages of Chlamydia infection (Section 2.4.4). In this chapter, I expand on these observations by demonstrating that IFNε deficiency suppresses the mRNA expression of IL-1β at baseline but promotes its expression during infection (Figure 4.2 A). As IL-

1β transcription is mediated by PAMP:PRR signalling, the increase observed in IL-1β mRNA expression in Chlamydia-infected IFNε-/- mice may be due to their increased

Chlamydia load (>900-fold increase in IFNε-/- mice compared to WT controls [Figure

2.2 B]). Indeed, previous studies have shown that IL-1β mRNA expression by macrophages increases with increased Chlamydia PAMP stimulation (Prantner et al.,

2009).

IL-1β responses have been implicated in both the innate processes that control infection and the aberrant inflammatory responses that drive pathology (Prantner et al.,

2009). Previous studies have shown that IL-1β-/- mice are both more susceptible to

Chlamydia RTIs and less likely to develop oviduct pathology (Prantner et al., 2009).

Early IL-1β expression is also essential for protection against C. pneumoniae respiratory tract infections, however, by limiting Chlamydia growth early, its expression reduces

223 inflammation and associated tissue damage and improves survival (Shimada et al.,

2011). Taken together, my data suggest that IFNε-mediated increases in baseline IL-1β expression may also be important in inhibiting the establishment of Chlamydia infections in the female RT. In IFNε-/- mice, this deficiency in IL-1β expression in the early stages of infection may allow for increased Chlamydia growth, leading to aberrant

IL-1β responses later during infection that are responsible for the development of pathology. The effects of IFNε on IL-1β expression, inflammation, and the development of pathology at later stages of infection will be the focus of further research in future studies. The findings presented in this chapter not only demonstrate that IFNε plays a role in regulating the expression of IL-1β, but also suggest that it may affect IL-1β activation.

The production and activation of IL-1β requires two signals. Firstly, PRR activation triggers the transcription and translation of pro-IL-1β, and, secondly, inflammasome activation signals for caspase-1-mediated cleavage of pro-IL-1β into its active form. It has previously been demonstrated that Chlamydia-induced IL-1β secretion requires the TLR2/MyD88 pathway (Abdul-Sater et al., 2010; Prantner et al.,

2009; Shimada et al., 2011). As such, the regulation of IL-1β mRNA expression by

IFNε may be mediated via changes in TLR signalling. However, neither baseline nor infection-induced expression levels of TLR2, 4, or 9, the major PRRs involved in the recognition of Chlamydia, were significantly altered in IFNε-/- mice, suggesting alternate means of regulation. The effect of IFNε on a number of signalling pathways that may directly or indirectly contribute to IL-1β transcription, such as NF-κB, PU.1, and CEBPβ signalling (see Chapter 5), will be investigated further in future studies.

Previous studies also demonstrate that the production of IL-1β by macrophages in response to in vitro infection with Chlamydia requires caspase-1 activation via the

224 NLRP3 inflammasome (Abdul-Sater et al., 2010; Prantner et al., 2009; Shimada et al.,

2011). Caspase-1 has also been associated with both protection against Chlamydia infections and the development of pathology, via IL-1β-dependent and independent pathways. Caspase-1-/- mice are more susceptible to respiratory C. pneumoniae infection and the administration of recombinant IL-1β rescues these mice from mortality, indicating that the protective effects of caspase-1 are dependent on IL-1β expression

(Shimada et al., 2011). However, others have shown that caspase-1 deficiency and the inhibition of caspase activity protects against Chlamydia-induced infertility and has no effect on vaginal shedding of C. trachomatis (Cheng et al., 2008; Igietseme et al.,

2013), although the effects of caspase-1 on infection in the upper RT was not investigated in these studies.

Here, I show that both caspase-1 expression and the number of active caspase-1+ leukocytes present in the upper RT are diminished in IFNε-/- mice. These data suggest that caspase-1 may play an important role in the induction of protective IFNε-mediated responses. Additionally, I identify the cell types involved in IFNε-mediated caspase-1 activation. Although there was a decrease in the number of active caspase-1+ macrophages (Figure 4.3 D), the predominant source of IL-1β during Chlamydia infection, the percentage of macrophages positive for active caspase-1 was unaltered in

IFNε-/- mice (Figure 4.5 D). Conversely, a deficiency in IFNε decreased both the number of active caspase-1+ NK cells in the RT (Figure 4.3 C & G) and the frequency of caspase-1 activation in NK cells (Figure 4.5 C). Little is known about the role of this pathway in NK cell function, highlighting the need for further investigation of the potential role of caspase-1 in NK cell responses.

The NLRP3 inflammasome has previously been demonstrated to mediate caspase-

1 activation in response to Chlamydia infection (Abdul-Sater et al., 2010; Prantner et

225 al., 2009). Importantly, Pothlichet et al. demonstrate that the gene for NLRP3 contains

ISREs in its promotor region and that the induction of its expression in human primary bronchial epithelial cells by H1N1 is dependent on IFNβ signalling (Pothlichet et al.,

2013). This suggests that the decrease caspase-1 activation observed in IFNε-/- mice may be the result of diminished NLRP3 expression. To determine if NLRP3 is involved in IFNε-mediated responses, I used immunofluorescent staining to determine NLRP3 levels and cellular source in uterine histology sections from Chlamydia- and sham- infected WT and IFNε-/- mice. In WT mice, NLRP3 expression was up-regulated in endometrial epithelial cells upon infection with Chlamydia, however, this increase was not observed in IFNε-/- mice (Figure 4.6), indicating that IFNε primes for the induction of NLRP3 expression in response to stimulation with Chlamydia.

To ascertain the contribution of the NLRP3 inflammasome in IFNε-mediated protection against Chlamydia infection in the female RT, I used the highly specific

NLRP3 inhibitor, MCC950, to inhibit its activity locally in WT mice. MCC950 is an

NLRP3 inflammasome-specific inhibitor that reduces caspase-1 activation and IL-1β production in macrophages stimulated with LPS and ATP, monosodium urate crystals, or nigericin (Coll et al., 2015). MCC950 does not inhibit IL-1β production in response to NLRC4 or AIM2 activation by Salmonella or dsDNA, respectively (Coll et al.,

2015). I show that, IVAG administration of MCC950 increases Chlamydia infection in the upper RTs of WT mice (Figure 4.7 A). This increase in infection (6-fold) does not reach the levels seen in IFNε-/- mice (>900-fold), however, this may be due to IFNε mediating its protective effects through a number of different pathways (e.g. NLRP3, other inflammasomes [see below], and NK cells [see Chapter 3]) to confer protection.

These results deviate from previously published findings that show that NLRP3-/- mice have a similar course of infection to WT controls as this study only measured

226 Chlamydia load in the vagina and did not assess ascending infection in the upper RT

(Nagarajan et al., 2012). Additionally, these knockout animals may have developed compensatory pathways to circumvent the deficiency in NLRP3, for example, by up- regulating the expression of other Chlamydia-activated inflammasomes, such as AIM2, as they are deficient in NLRP3 from birth. This highlights how the use of inhibitors, such as MCC950, may be more appropriate for studying the role of inflammasomes in

Chlamydia RTIs. Together, my data show for the first time that, not only does IFNε potentiate NLRP3-mediated responses, but also that IFNε-mediated NLRP3 inflammasome responses play an important role in protecting against ascending

Chlamydia infections in the female RT.

Although there is conflicting evidence regarding the role of the NLRP3 inflammasome/caspase-1/IL-1β signalling axis during Chlamydia RTIs, inflammasome activation has been shown to have effects independent of IL-1β production (Nagarajan et al., 2012). IL-18 is another member of the IL-1 family activated by caspase-1 signalling and, interestingly, IL-18 has been shown to be involved in mediating Th1 responses via its ability to induce IFNγ, either with IL-12 or IL-15 (Dinarello, 2009;

Kupz et al., 2014; Okamura et al., 1995; Shibatomi et al., 2001). Nagarajan et al. have demonstrated that activation of the NLRP3 inflammasome by Chlamydia RTIs induces

IL-18 production (Nagarajan et al., 2012). Importantly, inflammasome-driven IL-18 responses have been shown to potently promote NK cell cytotoxicity, activation, and

IFNγ production (Kupz et al., 2014; Maltez et al., 2015; Rathinam et al., 2010; Serti et al., 2014). Although IL-18 mRNA expression was not altered in IFNε-/- mice (Figure

4.2 B), IL-18 has been shown to be constitutively expressed (Marshall et al., 1999;

Puren et al., 1999) and the reduction observed in caspase-1 activation in these animals suggests that there may be a reduction in its activation. Thus, inflammasome activation

227 may also be one of the mechanisms by which IFNε induces protective NK cell responses and future studies will aim to determine the role of IL-18 activation in IFNε- mediated responses.

However, NK cell number and the expression of CXCL10 and IL-15 were not altered by NLRP3 inhibition (Figure 4.5). This suggests that IFNε-mediated NLRP3 inflammasome and NK cell responses may act independently of one another to protect against infection. Nevertheless, IFNε-mediated inflammasome responses may mediate their protective effects via the modulation of NK cell activity. Future studies will aim to determine the mechanism of NLRP3 inflammasome-mediated protection and how this contributes to IFNε-induced responses during Chlamydia RTI.

Furthermore, how NLRP3 is mediating these protective effects is unclear, as caspase-1 activation in the upper RT is unaltered in MCC950-treated mice (Figure 4.8).

This suggests either 1) that IVAG MCC950 treatment is unable to affect inflammasome activation in the upper RT and is instead exerting its detrimental effects by inhibiting

NLRP3 in the vagina/cervix, 2) that other caspase-1-activating pathways, including other inflammasomes, are activated by Chlamydia infection and compensate for the inhibition of NLRP3, or 3) that NLRP3 protects against Chlamydia via a novel, caspase-

1-independent pathway. The potential existence of NLRP3-independent pathways of

Chlamydia-mediated caspase-1 activation highlights the possibility of alternate means of increased caspase-1 activation downstream of IFNε. Interestingly, AIM2 has recently been shown to be involved in caspase-1 activation and the production of IL-1β and IL-

18 during Chlamydia infection in vitro (Finethy et al., 2015). This study first demonstrated that IFNγ-primed NLRP3-/- macrophages secrete significantly more IL-18 upon infection with C. muridarum than caspase-1-/- macrophages (Finethy et al., 2015).

As this indicates that Chlamydia may be capable of activating other inflammasomes, the

228 authors then went on to assess IL-18 production by Chlamydia-infected IFNγ-primed

NLRP1-/-, NLRP3-/-, NLRC4-/-, and AIM2-/- macrophages (Finethy et al., 2015).

Importantly, they show that only NLRP3-/- and AIM2-/- macrophages exhibit a partial reduction in IL-18 secretion, compared to WT controls, and that NLRP3-/- AIM2-/- double knockout macrophages are completely unable to produce either IL-1β or IL-18 in response to Chlamydia infection in vitro (Finethy et al., 2015). My results expand on these findings by demonstrating for the first time that AIM2 expression is up-regulated by Chlamydia infection in the female RT (Figure 4.9 A). Furthermore, I demonstrate that IFNε is required for this response, as AIM2 expression is significantly lower in

Chlamydia-infected IFNε-/- mice, compared to their WT controls (Figure 4.9 A). This suggests, not only that AIM2 may also be involved in IFNε-mediated caspase-1 responses, but that IFNε-regulated increases in the expression of AIM2 during infection may be responsible for the caspase-1 activation observed in the upper RTs of

Chlamydia-infected, MCC950-treated mice.

IFNε signalling may also contribute to inflammasome-dependent caspase-1 activation via the expression of caspase-4 and activation of the non-canonical NLRP3 inflammasome pathway (Henry et al., 2007; Malireddi and Kanneganti, 2013). Studies have shown that Gram-negative bacteria induce caspase-4 expression and subsequent caspase-1 and IL-1β activation via a TLR4/TRIF/IRF3/type I IFN/IFNAR/STAT1 signalling axis (Broz et al., 2012; Henry et al., 2007; Rathinam et al., 2010; Rathinam et al., 2012). In this chapter, I show that baseline caspase-4 expression is reduced in IFNε-/- mice, compared to WT controls (Figure 4.9 A). Caspase-4 is activated by a component of LPS, lipid A (Hagar et al., 2013; Kayagaki et al., 2013). Once activated, caspase-4 induces the caspase-1-dependent activation of IL-1β and IL-18, via activation of non- canonical inflammasome pathways, and increases phagosome-lysosome fusion and cell

229 lysis, via caspase-1-independent pathways (Akhter et al., 2012; Kayagaki et al., 2011).

As such, the deficiency in caspase-4 observed in IFNε-/- mice may be responsible for reduced caspase-1 activation in these animals and caspase-4 expression may be driving caspase-1 activation via a non-canonical inflammasome pathway in MCC950-treated mice. The role of caspase-4 in IFNε-mediated responses and caspase-1 activation during

Chlamydia infection will be investigated further in future studies.

In summary, my ground-breaking studies have shown that IFNε regulates not only the NLRP3 inflammasome/caspase-1/IL-1β signalling axis, but that IFNε may have potent effects on multiple inflammasome- and caspase-mediated pathways in the female

RT. I also show that the NLRP3 inflammasome plays a role in protecting the female RT against early ascending Chlamydia infection. These studies improve our understanding of the complex relationship between IFNε and inflammasome-associated factors in innate protection against the early stages of Chlamydia infection. Future studies will be dedicated to determining how interactions between these factors affect the pathological outcomes associated with the later stages of infection and whether these responses can be utilised in therapies.

230 : General discussion and conclusions

5.1 Using a murine model of C. muridarum-induced RTI to

investigate how IFNε protects against Chlamydia

infections in the female RT

In order to explore the mechanisms of IFNε-mediated protection against

Chlamydia RTIs, I utilised a murine model of Chlamydia female RTI, which recapitulates many of the features of Chlamydia infection and associated disease in humans.

This model employs the natural mouse pathogen, C. muridarum, which allows us to replicate natural host-pathogen interactions. The genomes of C. muridarum and C. trachomatis are highly similar and, even within regions of variation, contain orthologous virulence factor genes (Belland, 2001; Read et al., 2000), suggesting similar pathogenic mechanisms. Of the two strains, C. muridarum is the more appropriate strain to use in mice as Chlamydiae have evolved mechanisms to circumvent host defences and, as such, have developed host specificities due to their unique susceptibilities to certain protective responses, namely, those downstream of

IFNγ, including iNOS and IDO (Read et al., 2000). For example, C. trachomatis serovar

D possesses tryptophan biosynthesis genes, whereas C. muridarum does not (Read et al., 2000). This may be due to a lack of reliance on the IFNγ/IDO pathway for of control

Chlamydia infections in murine systems, meaning that C. muridarum has access to host tryptophan (Nelson et al., 2005), and may explain the processes behind host specificity, as, unlike C. trachomatis, C. muridarum is unable to mount a persistent infection in humans, who produce IDO in response to IFNγ. By using a murine pathogen, changes

231 in susceptibility detected in IFNε-/- mice should, therefore, reflect regulation of natural host protective responses.

C. muridarum RTI in mice induces immune responses and pathophysiological features similar to that of C. trachomatis infections in women (Berry et al., 2004;

Morrison and Caldwell, 2002). IVAG inoculation generates a self-limiting infection that originates in the epithelium of the vaginal vault and ascends the RT along the epithelial layer to the uterine horns and oviducts (Morrison et al., 1995). The initial inflammatory response C. muridarum RTI is characterised by intense neutrophil influx into the mucosae and submucosae, followed by the recruitment of macrophages, CD4+ and

CD8+ T cells, and B cells as infection clears (Berry et al., 2004; Morrison et al., 1995).

Tubal occlusion resulting in hydrosalpinx and infertility is a common complication of infection in humans and is also a frequently observed sequela of C. muridarum infection in mice (de la Maza et al., 1994). In contrast, the use of human serovars in murine RTI models in the literature show a mild infection of short duration upon IVAG inoculation, characterised by minimal inflammation and the relative absence of sequelae (Lyons et al., 2005; Perry et al., 1999b). Relatively large doses of C. trachomatis need to be introduced directly into the uterus or ovarian bursa of female mice in order to generate upper RT infection and associated pathology (Lyons et al., 2005; Tuffrey et al., 1990;

Tuffrey et al., 1986). However, this model of infection does not replicate the natural mode of Chlamydia transmission and ascending infection that would occur with human

Chlamydia STIs.

In the murine model of C. muridarum-induced female RTI utilised, intact mice are pre-treated with the female sex hormone, progesterone, in order to synchronise there oestrous cycles and prime for infection (Berry et al., 2004). Synchronisation of the oestrous cycle is essential, as susceptibility to infection is dependent on the reproductive

232 stage (Pal et al., 1998) and progesterone pre-treatment is required to induce susceptibility of female mice to Chlamydia RTIs, allowing for the establishment of a productive infection (Kaushic et al., 2000). Significantly, women taking progesterone- containing contraceptives are more susceptible to Chlamydia RTIs (Morrison et al.,

2009), highlighting the clinical relevance of progesterone pre-treatment in intact mice used in this model.

Using progesterone pre-treated, WT and IFNε-/- mice infected with C. muridarum,

I was able to show that IFNε plays an important role in mediating a variety of immune, metabolic, and other key processes in the female RT and likely protects against

Chlamydia infection by promoting innate NK cell- and inflammasome-mediated responses in the earliest stages of infection. I also showed that the administration of exogenous IFNε can provide protection against infection, which indicates that IFNε and/or its effects may be harnessed in a therapeutic capacity. These novel observations improve our understanding of the processes that regulate innate immunity in the female

RT and the mechanisms that underpin host defence against Chlamydia RTIs.

Additionally, our collaborators have shown that IFNε also plays a role in protection against HSV-2 infections in the female RT (Fung et al., 2013). Together, our findings suggest that IFNε may also be important for protection against other RTIs and highlight the potential of targeting IFNε in novel therapeutic strategies for the prevention of RT disease.

To determine the role of IFNε in hormone-regulated responses to Chlamydia RTI,

WT and IFNε-/- mice were also pre-treated with oestradiol prior to infection. Oestradiol is known prime for protective responses to Chlamydia (Ito et al., 1984; Kaushic et al.,

2000) and I show that mice pre-treated with oestradiol do not establish a productive infection (sFigure 2.1). Since, I and others show that IFNε expression increases quite

233 dramatically following oestradiol pre-treatment and/or during oestradiol-dominant stages of the oestrous cycle (Figure 1.2 & 2.2 A) (Fung et al., 2013), my findings would suggest that oestradiol-induced increases in the expression of protective IFNε may underpin oestradiol-mediated protection against infection. However, my data show that oestradiol-pre-treated IFNε-/- mice are still highly resistant to Chlamydia at the early stages of infection, indicating that the overriding protective effects of oestradiol are not dependent upon IFNε but rather due to other changes in the female RT. These may include oestradiol-mediated increases in IFNγ production (Fox et al., 1991; Grasso and

Muscettola, 1990; Karpuzoglu-Sahin et al., 2001) or the accumulation and activity of other immune cells, such as macrophages and CD8+ T cells (Danel et al., 1983; Kaushic et al., 1998; Stimson, 1988; White et al., 1997), or oestradiol-mediated changes in the epithelial lining of the lower female RT (changes in cell type and increases thickness in cervical and vaginal tissues) (Kaushic et al., 1998), which reduce access to appropriate host cells for replication and/or prevent infection from ascending into the uterus.

5.1.1 IFNε regulates many key innate immune and other

processes in the female RT

During my studies, I have demonstrated that IFNε significantly promotes the accumulation of NK cells, but not pDCs, mDCs, CD4+ T cells, CD8+ T cells, B cells, macrophages, neutrophils, or NK T cells, in the upper RT during the earliest stages of

Chlamydia infection. Importantly, NK cells are the most abundant cell type at this time- point, consistent with their role as key innate immune effector cells. As type I IFNs are known to regulate NK cell function, and NK cells have been shown to contribute to protective IFNγ responses during Chlamydia infections, the regulation of NK cell

234 responses by IFNε is a likely a key mechanism that underpins IFNε-mediated protection against infection.

Using microarray and IPA® analyses, I demonstrate that IFNε regulates both the basal and infection-induced expression patterns of genes associated with a variety of innate immune processes. Importantly, these included NK cell signalling pathways, and networks involved in both NK cell function and IFNγ responses, which were altered both at baseline and during infection. This provides further evidence for the involvement of NK cells in IFNε-mediated protection and suggests that IFNε may prime for NK cell and IFNγ responses during infection by increasing their accumulation in the

RT at baseline. As IFNγ responses are known to play an integral role in protection against Chlamydia infections and since NK cells are the predominant source of IFNγ during the earliest stages of infection, the roles of NK and IFNγ responses in IFNε- mediated protection were examined further in Chapter 3.

Interestingly, network analysis also identified IL-1β as a hub molecule, exhibiting high levels of interconnectivity with many of the other transcripts up- regulated by IFNε during infection, indicating that IL-1β may be a key factor downstream of IFNε. IL-1β requires activation via proteolytic cleavage in order to function and IL-1β activation upon infection with Chlamydia has been shown to be dependent on activation of the NLRP3 inflammasome and caspase-1 (Abdul-Sater et al.,

2010; Prantner et al., 2009). Taken together, these findings suggest that IFNε may also play a role in the regulation of NLRP3 inflammasome responses, priming for the activation of IL-1β in response to infection. As such, these responses were explored further in chapter 4.

My data also suggest that IFNε regulates a variety of other innate immune processes which may be involved in protection against infection. I show evidence that

235 IFNε promotes the expression of genes associated with leukocyte haematopoiesis, infiltration, and signalling at baseline, and factors associated IRF activation and PRR signalling upon infection, suggesting that these signalling pathways may play a role in mediating responses downstream of IFNε. Importantly, IRFs are responsible for initiating IFN responses and I show that IFNε promotes the up-regulation of both IRF3 and IRF7 during infection in Chapter 3. Additionally, PRRs, such as TLR2, have been shown to be essential for NLRP3 inflammasome activation during infection with cytosolic bacteria, indicating that alterations in these pathways may be the mechanism by which IFNε mediates inflammasome and IL-1β responses. Although no differences were observed in the expression of PRRs between WT and IFNε-/- mice (Chapter 4),

IFNε may regulate factors involved in PRR signalling downstream of these receptors.

The role of PRR signalling in IFNε-mediated responses will be investigated further in future studies.

Interestingly, aside from immune factors, I show that IFNε also regulates the expression of a number of genes associated with metabolic processes, such as LXR/RXR

Activation, Glutathione-mediated Detoxification, and Aryl Hydrocarbon Receptor

Signalling, and Nicotine Degradation, Melatonin Degradation, and Oestrogen

Biosynthesis, which involve the same set of 3-5 genes.

LXRs and RXRs are members of the nuclear receptor superfamily of ligand- activated transcription factors and are primarily involved in cholesterol metabolism and lipid homeostasis. However, LXR/RXR activation has also been shown to regulate immune responses (Joseph et al., 2004; Joseph et al., 2003; Kaul et al., 2006; Terasaka et al., 2005; Valledor et al., 2004), highlighting the intimate relationship between host metabolism and defence. Cross-talk between LXR/RXR and innate immune signalling pathways has previously been described by others and LXR/RXR agonists have been

236 shown to have several selective anti-inflammatory effects (Joseph et al., 2003; Kaul et al., 2006; Terasaka et al., 2005), however, gene silencing of LXR in human PBMCs was found to decrease the expression of IFNγ (Kaul et al., 2006; Wang et al., 2014). As such, IFNε-mediated increases in LXR/RXR activation may be involved in the induction of IFNγ responses in the female RT.

Glutathione-mediated processes have also been shown play a critical role in host defence. Glutathione is a thiol antioxidant that reduces ROS. As such, glutathione is essential for some functions of the immune system such as phagocytosis (Oliver et al.,

1976; Short et al., 1996), NO killing of intracellular bacteria (Venketaraman et al.,

2003; Venketaraman et al., 2005), and T cell proliferation (Hadzic et al., 2005).

Importantly, glutathione deficiency has been associated with an increase in susceptibility to infection (Ghezzi, 2011; Ristoff et al., 2001) due to impairment of these functions (Spielberg et al., 1979). Glutathione is also known to have anti-inflammatory effects (Blackwell et al., 1996) and protects against inflammatory pathologies (Ghezzi,

2011). Notably, although the effects of glutathione inhibit the expression of many inflammatory cytokines, they are required for adequate production of IFNγ by APCs,

Th1 polarisation, and optimal NK cell proliferation and cytolytic activity in response to

IL-2 (Murata et al., 2002; Peterson et al., 1998; Yamauchi and Bloom, 1993; Yamauchi and Bloom, 1997). An IFNε-mediated increase in glutathione-mediated detoxification may play a role in protection against Chlamydia infections by augmenting NK cell proliferation and IFNγ production and reducing damage caused by ROS. As such, these data suggest novel links between IFNε, glutathione, and IFNγ responses.

The aryl hydrocarbon receptor (AHR) is a ligand-regulated transcription factor that recognises a variety of dietary and environmental ligands, such as dioxin

(environmental toxin), flavonoids, and metabolites of tryptophan (kynurenine) (Esser et

237 al., 2009). Importantly, AHR has recently been identified to regulate the expression of genes involved in innate immunity (Esser et al., 2009). As AHR can be activated by kynurenine, the metabolism of tryptophan via IFNε-mediated increases in IDO expression may be responsible for the increase in AHR signalling observed. Indeed, increased expression of IDO by M. tuberculosis increases AHR nuclear translocation and expression of AHR target genes (Memari et al., 2015). Immature NK cells have also been shown express AHR (Hughes et al., 2010) and, therefore, the IFNε-mediated increase in AHR mRNA and transcripts associated with AHR signalling may also be due to an increase in the number of NK cells present in the RT. Furthermore, IL-1β has been shown to be a direct target gene of the AHR (Memari et al., 2015). Therefore, an increase in AHR signalling may be one mechanism by which IFNε increases the mRNA expression of IL-1β.

Melatonin is also a product of tryptophan utilisation and so its synthesis and subsequent degradation may represent a novel method of reducing the availability of tryptophan during Chlamydia infection. How IFNε induces factors associated with melatonin degradation, and their role in the innate response to Chlamydia infections, is yet to be determined.

I also provide evidence that factors associated with cell cycling pathways, such as GADD45, DNA Damage-induced 14-3-3σ, and Circadian Rhythm Signalling pathways are regulated by IFNε in the female RT. This indicates that IFNε may regulate cell cycle progression and promote the activation of cell death pathways in response to infection. As both GADD45 proteins and 14-3-3σ are induced by DNA damage, their signalling pathways may be induced by other pathways of cell death, such as granzyme- mediated NK cell cytotoxicity or capase-1-mediated pyroptosis during IFNε-mediated

NK cell and inflammasome responses. Furthermore, IL-1β is known to regulate clock

238 genes that control the circadian rhythm, promoting non-rapid eye movement sleep

(Cavadini et al., 2007; Fang et al., 1998), suggesting that IFNε-mediated changes to circadian rhythm signalling may be related to changes in IL-1β expression.

Interestingly, several pathways related to lipid metabolism (Triacylglycerol and

Stearate Biosynthesis) were also found to be universally down-regulated by IFNε. As an obligate intracellular pathogen, Chlamydia acquires host lipids for the de novo synthesis of its membrane constituents, and others have shown that inhibition of fatty acid, triacylglycerol, and lipid droplet metabolism in host cells impairs Chlamydia replication and maturation (Cocchiaro et al., 2008; Kumar et al., 2006; Wang et al., 2007; Yao et al., 2015). Taken together, these data suggest that by reducing the production of these metabolites, IFNε may limit Chlamydia growth.

5.1.2 IFNε protects against Chlamydia RTIs by promoting

innate NK cell and IFNγ responses

NK cells are large cytotoxic lymphocytes of the innate immune system that play an integral role in the first line of defence against both viral and cytosolic bacterial infections due to their capacity to lyse infected cells and initiate IFNγ-mediated responses during primary infections, prior to the establishment of adaptive, cell- mediated immunity. Significantly, they have been shown to be important for protection against Chlamydia infections (Jiao et al., 2011; Tseng and Rank, 1998).

The studies described in my thesis demonstrate for the first time that IFNε increases NK cell responses, including cNK cell haematopoiesis, accumulation, activation, and IFNγ production, and uNK cell accumulation, in the upper female RT during Chlamydia infection.

239 NK cell haematopoiesis primarily occurs in the bone marrow and is driven by

IL-15 (Kennedy et al., 2000; Mrozek et al., 1996; Puzanov et al., 1996; Ranson et al.,

2003; Rosmaraki et al., 2001; Suzuki et al., 1997; Williams et al., 1997). NK cells gain the ability to respond to IL-15 from the stage of the early NK cell committed progenitor, the precursor NK cell (Kennedy et al., 2000; Ranson et al., 2003; Rosmaraki et al.,

2001). IL-15 then drives the survival and differentiation of precursor NK cells, allowing them to develop into mature CD11b+ NK cells (Kennedy et al., 2000; Mrozek et al.,

1996; Puzanov et al., 1996; Ranson et al., 2003; Suzuki et al., 1997; Williams et al.,

1997). Since I show that both precursor and mature NK cells are affected by IFNε, and that IFNε increases IL-15 responses in the uterus, it is possible that the IFNε-mediated increases in IL-15 expression observed extend beyond the RT, promoting the survival of precursors and generation of mature NK cells in the bone marrow. My attempts to address the effects of IFNε on systemic IL-15 responses were not successful as I was unable to detect IL-15 protein in the serum of Chlamydia-infected WT and IFNε-/- mice via ELISA (unable to detect IL-15 in any samples, data not shown). I am currently exploring other methods to determine whether IFNε affects systemic IL-15 responses.

Type I IFN signalling has previously been shown to induce the potent NK cell chemoattractant, CXCL10 (Vanguri and Farber, 1990). Importantly, I show that IFNε increases the expression of CXCL10 in the RT, which may contribute to the IFNε- mediated accumulation of NK cells by inducing their chemoattraction. However, as

IFNγ has also been shown to induce CXCL10 expression, the IFNε-mediated increase in IFNγ responses may also contribute, and how IFNε induces the expression of

CXCL10 will need to be clarified. Furthermore, the receptor for CXCL10, CXCR3 is known to be expressed by NK cells, monocytes, DCs, and T cells. Although only differences in NK cells were observed between WT and IFNε-/- mice, CXCR3 has also

240 been shown to be preferentially expressed by Th1 T cells (Belay et al., 2002), suggesting that the induction of CXCL10 by IFNε may contribute to the development of

Th1 immunity to Chlamydia during the adaptive response. As such, the effects of IFNε- induced CXCL10 on the chemoattraction of other cells and the development of adaptive immune responses will be investigated in future studies. Intriguingly, CXCL10 has also been shown to enhance the cytolytic activity of NK cells (Taub et al., 1996; Taub et al.,

1995) and has direct antimicrobial effects (Cole et al., 2001). Although the role of these pathways in protection against Chlamydia infections is yet to be determined, they may also contribute to IFNε-mediated protective responses.

How IFNε promotes the activation of and production of IFNγ by NK cells in the uterus is yet to be determined. This may occur via direct or indirect mechanisms. NK cells possess IFNARs and are capable of responding to type I IFNs, which directly mediate certain NK cell functions, such as cytolytic activity in response to mCMV

(Nguyen et al., 2002), adenovirus (Zhu et al., 2008), and vaccinia virus (Martinez et al.,

2008) infections. However, compared to other cells, such as DCs, NK cell transcriptional activity alters very little following stimulation with type I IFNs and, as such, NK cell responses to type I IFNs are often mediated via the production of cytokines by accessory cells in response to type I IFN signalling (Baranek et al., 2012).

For example, the proliferation and survival of NK cells during mCMV infection

(Baranek et al., 2012; Nguyen et al., 2002), and the production of IFNγ by, and cytolytic activity of, NK cells following TLR stimulation or infection with certain viruses (Lucas et al., 2007), have been shown to be indirectly mediated by extrinsic type I IFN signalling in accessory cells, which produce cytokines to stimulate NK cells. Lucas, et al. show that NK cell priming in response to TLR stimulation, and NK cell effector functions, such as the production of IFNγ and the lysis of target cells, during LCMV,

241 vaccinia virus, and L. monocytogenes infections, rely on the recognition of type I IFNs by DCs. These type I IFN-stimulated DCs produce and trans-present IL-15 in complex with the surface-bound IL-15 receptor α chain to IL-15 receptors on resting NK cells recruited to the lymph nodes (Lucas et al., 2007). Importantly, Lucas et al. also demonstrate that IL-1, IL-18, and IL-12 are not required for this type I IFN-induced response (Lucas et al., 2007). Since I show that both IL-12p40 and IL-18 mRNA expression are unaltered by IFNε deficiency, these data suggest that IL-15 signalling may be responsible for the IFNε-mediated increases in NK cell accumulation and IFNγ responses observed in the RT. Interestingly, a protective role for IL-15 has been demonstrated for other STIs. Tarkowski et al. have shown that IL-15 is associated with positive outcomes during HIV infection, with monocytes from long-term non- progressors expressing significantly higher levels of IL-15 than those from patients with progressive HIV infections or healthy controls (Tarkowski et al., 2012), highlighting the potential for IFNε-mediated IL-15 responses to be involved in host defence against other STIs.

In co-culture experiments, C. trachomatis infection has been shown to promote the production of IFNγ by NK cells via the production of IL-18 by epithelial cells and

IL-12 by DCs (Hook et al., 2005). Although no differences in IL-12p40 and IL-18 mRNA expression levels were observed between WT and IFNε-/- mice in the RT, protein expression levels will need to be confirmed, and others have shown that DCs educate NK cells, priming for responses such as the production of IFNγ, by producing

IL-12 in the lymph nodes (Ferlazzo et al., 2004). As such, IFNε may mediate the activation of NK cells and their production of IFNγ by augmenting this pathway and future studies will aim to assess the role of IFNε in the recruitment of NK cells to the lymph nodes and the production of cytokines by DCs in this site. Furthermore, the

242 relative contribution of type I IFNs to the induction of protective IFNγ responses during

Chlamydia infection in vivo, and the mechanisms that underpin type I IFN-mediated induction of IFNγ remain to be elucidated. Indeed, IL-12 can only account for some of the protective effects of IFNγ during Chlamydia infection, highlighting a potential role for IFNε and other type I IFNs in the induction of protective IFNγ responses (Del Rı́o et al., 2001; Perry et al., 1999b).

The IFNε-mediated increase in accumulation of NK cells in the RT may also be influenced by the expansion of mature and precursor populations of NK cells locally. I show for the first time that systemic depletion of NK cells post infection with antibodies specific for the pan-NK cell marker, ASGM1, results in a decrease in the accumulation of NK cells and an increase in Chlamydia 16S expression in the upper RT at 3dpi.

However, I also show that systemic depletion of NK cells prior to infection leads to an increase in the number of NK cells present in the upper RT. This may be due to the prevalence of active NK cells in the RT, as anti-ASGM1 antibody treatment appears to only target inactive NK cell populations in these tissues. However, there is also the possibility that the uterus possesses a local NK cell progenitor population that lacks expression of ASGM1 and, therefore, escapes depletion and differentiates into mature/active phenotypes despite anti-ASGM1 treatment. Indeed, NK cell precursors in the bone marrow are unaffected by anti-ASGM1 treatment (Appendix C: sFigure 3.1

& 3.2 B & F). These cells may have a greater propensity to expand after NK cell depletion in order to replenish the systemic pool. Indeed, trNK cell populations present in the uterus and other organs have been shown to develop independently of cNK cells via the local maturation of early NK cell precursors that reside in the lymph nodes

(Chantakru et al., 2002; Male et al., 2010; Sojka et al., 2014; Vacca et al., 2011).

Additionally, both IL-15 and CXCL10 have been shown to play critical roles in this

243 process (Allen and Nilsen-Hamilton, 1998; Sentman et al., 2004; Ye et al., 1996). I show that IFNε increases the expansion of uNK cells during Chlamydia infection and the expression of both IL-15 and CXCL10 at baseline. Taken together, these findings suggests that IFNε may increase, not only uNK cells, but also other NK cell populations, by potentiating local development and proliferation. uNK cells have been shown to have a cytokine-producing, but immature, phenotype and are important for reproductive processes. However, they have also been shown to produce cytokines in response to TLR stimulation (indirectly via accessory cells) (Eriksson et al., 2006) and play a role in protection against certain pathogens, such as CMV, limiting their spread from uterine to foetal tissues (Mselle et al., 2009; Siewiera et al., 2013). This highlights the potential importance of IFNε-mediated regulation of uNK cells in protection against female RTIs.

5.1.3 IFNε may protect against Chlamydia RTIs by promoting

inflammasome-mediated responses

In the studies described in my thesis, I demonstrate that IFNε regulates inflammasome responses in the female RT. I show for the first time that IFNε promotes

NLRP3, AIM2, caspase-1, caspase-4, and IL-1β responses in the uterus and that NLRP3 inflammasome-mediated signalling may be contributing to IFNε-mediated protection against Chlamydia infections in the female RT.

I show that WT mice have increased IL-1β responses prior to infection, but decreased IL-1β responses during infection, compared to IFNε-/- mice (Figure 4.2 A).

How IFNε increases basal IL-1β expression, yet restricts IL-1β expression during infection, is unclear. Restricted IL-1β expression during infection in WT mice could be the result of IFNε-mediated induction of other cells/factors early during infection that

244 inhibit its transcription. Indeed, type I IFNs have previously been shown to inhibit IL-1β expression via a STAT1/IL-10/STAT3 axis (Guarda et al., 2011). Although, it is more likely the increase seen in IL-1β expression in Chlamydia-infected IFNε-/- mice, compared to WT controls, is the result of increased Chlamydia load in these mice, leading to increased PAMP:PRR signalling-induced IL-1β expression. IL-1β is an important mediator of inflammatory responses, such as the infiltration of innate immune cells, fever, lowered pain threshold, and vasodilation (Dinarello, 2009). However, as explained previously, the role of IL-1β in protection against Chlamydia RTIs is complex, as IL-1β has been implicated in the induction of both the innate processes that control infection and the aberrant inflammatory responses that drive pathology (Prantner et al., 2009). Previous studies have shown that IL-1β-/- mice are more susceptible to

Chlamydia RTIs but less likely to develop oviduct pathology (Prantner et al., 2009). By priming for IL-1β responses early but limiting its expression later, IFNε may limit

Chlamydia growth in the early stages of infection without inducing the excessive inflammation that causes disease later. What is less clear is how IFNε may be contributing to these potentially protective IL-1β responses in the absence of infection

(i.e. increased IL-1β expression in sham-infected WT, compared to IFNε-/-, mice).

Interestingly, Marecki et al. have shown that the IFN-associated transcription factors,

IRF1, IRF2, IRF4, and IRF8, are capable of synergising with the IL-1β-inducing transcription factor, PU.1, to markedly increase IL-1β expression (Marecki et al., 2001).

Although IRF1 expression was not found to be altered between WT and IFNε-/- mice, the effects of IFNε on the other IRFs are yet to be determined. Additionally, non- tyrosine phosphorylated STAT1 has been shown to contribute to IL-1β expression in response to LPS stimulation by cooperating with PU.1 and IRF8 (Unlu et al., 2007).

Non-tyrosine phosphorylated STAT1, PU.1, and IRF8 form a complex which binds to

245 the LPS and IL-1 response element (LILRE) in the promotor region of the IL-1β gene and primes for the rapid induction of IL-1β transcription following IRF8 phosphorylation (Unlu et al., 2007). As I have shown that IFNε increases the expression of STAT1 at baseline, this non-tyrosine phosphorylated STAT1/PU.1/IRF8 pathway may be responsible for the IFNε-mediated increase in basal IL-1β levels observed, with

STAT1 phosphorylation by IFNγ signalling limiting IL-1β expression during infection.

However, the role of IFNε in PU.1, IRF8, and STAT1 activation, both at baseline and during infection, is yet to be elucidated.

IL-1β is activated via caspase-1-mediated proteolytic cleavage. Caspases are cysteine proteases responsible for initiating cellular processes that lead to cell death and/or inflammatory responses. Caspase-1 is a pro-inflammatory caspase tightly regulated by inflammasome-dependent activation that mediates maturation of the IL-1 family of cytokines and pyroptosis. I show that IFNε increases both the expression and activation of caspase-1 during Chlamydia infection, suggesting that caspase-1 may play a role in regulating the IFNε-mediated responses that protect against Chlamydia RTIs.

Interestingly, however, caspase-1 deficiency and the inhibition of caspase activity has previously been shown to have no effect on bacterial load (although the authors did not investigate upper RT infection) and is protective against Chlamydia-induced infertility during C. trachomatis RTI (Cheng et al., 2008; Igietseme et al., 2013). Furthermore,

Abdul-Sater et al. have demonstrated that caspase-1 activation in epithelial cells increases the number and size of Chlamydia inclusions in vitro (Abdul-Sater et al.,

2009). The authors suggest an increase in caspase-1-induced lipid metabolism may be responsible (Abdul-Sater et al., 2009). It is possible that caspase-1 activation may have both protective and detrimental effects, depending on the kinetics of infection, cell types involved, and downstream effects. As IFNε-mediated caspase-1 activity is strongest in

246 NK cells, it may not have the same effects on Chlamydia growth, IL-1β activation, and oviduct remodelling as it would in epithelial host cells or macrophages. Little is known about the effects of IFNε-induced caspase-1 responses on the development pathology, or the role of this pathway in NK cell function, highlighting the need for further investigation.

In vitro studies have demonstrated that the NLRP3 inflammasome is required for caspase-1 activation and the production of IL-1β by macrophages in response to infection with Chlamydia (Abdul-Sater et al., 2010; Prantner et al., 2009; Shimada et al., 2011). Importantly, I show that IFNε primes for increased expression of NLRP3 in endometrial epithelial cells during Chlamydia RTI in vivo. As this is both the site of infection and IFNε production, and since NLRP3 is a proposed ISG, this suggests that

IFNε may directly regulate the pathways that lead to its expression. However, as caspase-1 activation is altered in NK cells and not structural cells, the contribution of

IFNε-up-regulated NLRP3 to these downstream responses is unclear. Interestingly,

Bajora-Mazo et al. have shown that oligomeric NLRP3 inflammasome and ASC particles can be released from macrophages and stimulate caspase-1 activation in other cells (Baroja-Mazo et al., 2014). A similar mechanism may be involved in IFNε- mediated activation of caspase-1 in NK cells. Significantly, I also demonstrate that local inhibition of NLRP3 increases infection in the upper RT, providing evidence for the involvement of NLRP3 responses in IFNε-mediated protection against Chlamydia infections. However, no difference in caspase-1 activation was observed in the upper

RT following NLRP3 inhibition. There are three possible explanations for this, either 1)

IVAG administration of MCC950 is exerting its detrimental effects by inhibiting

NLRP3-mediated caspase-1 activation in the vagina/cervix, 2) other inflammasomes are involved in the IFNε-mediated activation of caspase-1 in the upper RT, and/or 3)

247 NLRP3 protects against Chlamydia via a novel, caspase-1-independent pathway.

Interestingly, previous studies have shown that ASC-/- mice exhibit a delay in clearance but normal IL-1β levels during C. muridarum RTI (Nagarajan et al., 2012), providing evidence for protective, IL-1β-independent effects downstream of inflammasome activation. Additionally, this study showed that NLRP3-/- mice clear infection from the vagina normally (Nagarajan et al., 2012), however, the authors did not investigate the effects of NLRP3 on Chlamydia infection in the upper RT. Taken together, my data suggests that NLRP3 may play a more important role in protecting against an ascending infection. Furthermore, the differences observed in clearance between ASC-/- and

NLRP3-/- mice suggests the involvement of other inflammasomes in protection against

Chlamydia RTIs. Indeed, I show that the expression of AIM2, which has recently been shown to be activated upon infection with Chlamydia in vitro (Finethy et al., 2015), is increased by IFNε during infection. These findings suggest that the novel interactions I have identified between IFNε signalling and inflammasome-mediated caspase-1 and IL-

1β responses in the female RT, and the precise role of NLRP3 in protection against infection, are likely complex.

The role of type I IFN signalling in inflammasome and caspase-1 activation has previously been demonstrated. ASC-mediated caspase-1 activation and subsequent IL-

1β secretion and pyroptosis during cytosolic bacterial infections has been shown to be dependent on the expression of type I IFNs (Fernandes-Alnemri et al., 2010; Henry et al., 2007; Rathinam et al., 2010). Type I IFN signalling has been shown to contribute to activation of the NLRP3 inflammasome during bacterial infections by inducing the expression of caspase-4 via a TLR4/TRIF/IRF3/type I IFN/IFNAR/STAT1 signalling axis (Henry et al., 2007; Malireddi and Kanneganti, 2013). Importantly, I show that

IFNε increases the expression of caspase-4 in the female RT at baseline. Caspase-4 is

248 activated by a component of LPS called lipid A (Hagar et al., 2013; Kayagaki et al.,

2013) and mediates caspase-1 activation and caspase-1-independent functions, such as phagosome-lysosome fusion and cell lysis (Akhter et al., 2012; Kayagaki et al., 2011).

As such, the induction of caspase-4 may be the mechanism by which IFNε primes for activation of caspase-1 during Chlamydia RTIs and may have protective effects that are independent of caspase-1 signalling.

5.1.4 Potential interactions between the NK cell responses

and inflammasome-mediated pathways regulated by

IFNε

My data strongly suggest that IFNε protects against the earliest stages of

Chlamydia RTIs by promoting NK cell, IFNγ, and inflammasome/caspase-1/IL-1β responses in the female RT. These IFNε-mediated responses may interact with and/or regulate one another.

Network analysis of factors up-regulated by IFNε, regardless of infection status, highlighted the potential involvement of several NK cell-related factors in IFNε- mediated responses. These included granzyme K, a serine protease contained in the cytolytic granules of activated NK cells and cytotoxic T cells (Shresta et al., 1997).

Granzyme K induces the generation of ROS and triggers caspase-independent cell death pathways, such as Bid-mediated mitochondrial damage and cleavage of p53 (Zhao et al., 2007). Significantly, granzyme K has also been shown to induce macrophages to process and secrete IL-1β, independent of P2X7 receptor activation via a non-cytolytic process (Joeckel et al., 2011), and augment the activation of TLR4 by LPS (Wensink et al., 2014). As such, IFNε-mediated changes in NK cell responses and granzyme K expression may also contribute to PRR activation and IL-1β responses.

249 Human NK cells have been shown to express high levels of NLRP3 and stimulation with the NLRP3 agonist, E. coli RNA, increases NK cell cytotoxicity and expression of IFNγ and TNF (Fu Qiu et al., 2011). These NLRP3-induced NK cell responses may be mediated by IL-18. Activation of IL-18 by caspase-1 has been shown to promote NK cell activation and IFNγ production during mCMV, hepatitis C, and S. typhimurium infections (Kupz et al., 2014; Rathinam et al., 2010; Serti et al., 2014) and

NK cell cytotoxicity, which works in concert with pyroptosis to kill infected cells, during intracellular bacterial infections (Maltez et al., 2015). Although IL-18 mRNA expression was unaltered in IFNε-/- mice, IL-18 mRNA and pro-IL-18 have previously been shown to be constitutively expressed and, therefore, IL-18 does not require a priming signal, like IL-1β, for production (Marshall et al., 1999; Puren et al., 1999).

Additionally, IFNε increases caspase-1 activation, suggesting that IL-18 maturation may be induced. Therefore, further investigation is required in order to determine if the promotion of inflammasome responses by IFNε induces NLRP3 expression in NK cells and/or the activation of IL-18 and whether this pathway plays a role in the production of

IFNγ by NK cells during Chlamydia RTI.

I also demonstrate that IFNε increases IFNγ responses and the expression of downstream effector molecules, such as iNOS and IDO. Interestingly, inflammasome activation and IL-1β production have also been shown to play a role in the induction of these responses. IL-1β is known to induce the expression of iNOS via NF-κB signalling

(Kwon et al., 1995) and has been shown to co-stimulate the production of IFNγ by

CD56bright subsets of human NK cells (Cooper et al., 2001). Taken together, these data suggest that IFNε-mediated IL-1β responses may also be involved in the induction of

IFNε-mediated IFNγ and effector cytokine responses.

250 Interestingly, NLRP3 has also been shown to induce protective iNOS responses during Chlamydia infection, independent of IL-1 signalling. Inhibition of the NLRP3 inflammasome activators, ROS and cathespin B, in C. muridarum-infected murine macrophages reduces the expression of iNOS, leading to a decrease in Chlamydia killing, in an IL-1-independent manner (Rajaram and Nelson, 2015). Furthermore, these responses were shown to correlate with increased IFNβ production, which, when inhibited, also results in an increase in infection (Rajaram and Nelson, 2015). Taken together, these data suggest that NLRP3 inflammasome activation may protect against

Chlamydia by inducing the expression of iNOS via IL-1β-independent mechanisms, and that type I IFN signalling may contribute to this response. Together, these findings suggest that the promotion of NLRP3 inflammasome-mediated responses may be a mechanism by which IFNε induces the expression of protective iNOS in the female RT.

5.1.5 Differential effects of type I IFNs on Chlamydia

infection in the female RT

Type I IFN signalling has previously been shown to have detrimental effects during Chlamydia RTIs in vivo (Nagarajan et al., 2008). The detrimental effects of type

I IFNs on Chlamydia RTI were demonstrated using IFNAR-/- mice. However, using

IFNε-/- mice, we show that IFNε, which signals via IFNAR, is protective against

Chlamydia infection in the female RT from the earliest stages of infection (Fung et al.,

2013). This is not entirely surprising, given that the different type I IFNs have been shown to vary in their antiviral and immunomodulatory capabilities, despite sharing the same receptor (Pestka, 2000). This may be due to unique interactions between the different type I IFNs and the two chains of the IFNAR. For example, unlike IFNα, IFNβ is capable of forming a stable complex with IFNAR1 and this interaction activates a

251 unique signalling axis via the Akt pathway (de Weerd et al., 2013). A similar mechanism may be involved in IFNε:IFNAR interactions. Another possibility is that competitive binding between the different type I IFNs is responsible for the protective effects of IFNε. As IFNβ has been shown to mediate the detrimental effects associated with IFNAR signalling during Chlamydia infections (Jayarapu et al., 2010; Nagarajan et al., 2008), IFNε may protect against Chlamydia RTIs by competitively blocking the effects of IFNβ. The differential biological and immunological IFNAR-mediated effects of IFNε compared to IFNα and IFNβ are currently the focus of ongoing investigations by our collaborators at Monash University and the Hudson Institute of Medical

Research.

The studies outlined in my thesis were not designed to investigate the differential effects of IFNε versus other type I IFNs, but rather identify how IFNε may be mediating its protective effects against Chlamydia infection. Nevertheless, I have identified a number of IFN-signalling pathways and responses that are affected by IFNε that may help explain its specific protective effects compared to the other type I IFNs.

I show that the expression levels of both IFNγ and IFNγR1, the ligand binding chain of the IFNγ receptor, are increased by IFNε during infection. This suggests that

IFNε may potentiate IFNγ signalling. In contrast, the studies conducted in IFNAR-/- mice suggested that IFNβ responses increase susceptibility to infection by blocking protective IFNγ-mediated responses (Jayarapu et al., 2010; Nagarajan et al., 2008).

Taken together, these data suggest that there may be subtle differences between the downstream effects of the individual type I IFNs with IFNε potentiating, and IFNα and/or IFNβ potentially blocking, IFNγ responses.

SOCS1 is a member of the STAT-induced STAT inhibitor family of proteins that are induced by cytokines and form part of a classical negative feedback system to

252 regulate signal transduction. SOCS1 inhibits IFNγ responses by binding to and inhibiting JAK1 and JAK2-induced STAT1 activation mediated by IFNγ:IFNγR signalling (Alexander et al., 1999; Federici et al., 2002). Importantly, SOCS1 has previously been shown to limit protective immune responses to Chlamydia infections, with SOCS1-/- mice exhibiting increased bacterial clearance during C. pneumoniae infections (Yang et al., 2008). Furthermore, IFNα/β signalling has previously been shown to increase SOCS1 expression during Chlamydia infection (Yang et al., 2008). In contrast, I show that the expression of SOCS1 during Chlamydia infection is reduced in the presence of IFNε signalling. Therefore, the up-regulation of SOCS1 by conventional type I IFNs, and the down-regulation of SOCS1 by IFNε, may be responsible for the differential effects of these type I IFNs during Chlamydia infection. Specifically, the up-regulation of SOCS1 may contribute to the detrimental effects of conventional type I

IFN signalling during Chlamydia RTIs via suppression of protective IFNγ responses and IFNε-mediated down-regulation of SOCS1 may help protect against Chlamydia through enhancing protective IFNγ responses.

Future studies will be conducted to identify how the different type I IFNs differentially affect IFN-mediated signalling pathways in order to better understand the differences between IFNε- and IFNα/β-induced IFNAR signalling in the pathogenesis of Chlamydia RTI.

253 5.2 Future directions

5.2.1 Proof of principle studies

Owing to the variability of Chlamydia RTI and the requirement to pool a number of uterine samples to perform some of the assays required, some datasets require additional replicates to ensure that any lack of significance is not due Type II error. To address this, key flow cytometry and gene expression experiments assessing

NK cell and inflammasome responses will be repeated in rIFNε- and vehicle control- treated WT and IFNε-/- mice where it appears that limited numbers of replicates have precluded finding statistical differences.

In preliminary studies, we have shown that IFNε-/- mice are more susceptible to

Chlamydia RTIs from the earliest stages of infection. In this thesis, I expand on these findings by demonstrating that IFNε protects against Chlamydia by promoting key innate immune processes, such as NK cell and inflammasome responses, in the upper female RT. These studies utilised IFNε-/- mice, NK cell depleting antibodies, and specific NLRP3 inhibitors to elucidate the roles of these factors/cells in host defence against Chlamydia and the mechanisms of IFNε-mediated protection. In Chapter 2, I also show that local administration of rIFNε protects against Chlamydia RTI in WT mice. However, as the deficiencies present in knockout animals from birth can lead to the development of compensatory pathways of immune protection, I will now perform proof of principle studies to validate the mechanisms of IFNε-mediated protection by repeating key studies in rIFNε-treated WT and IFNε-/- mice. These analyses will include assessment of Chlamydia infection in the upper RT, local and systemic NK cell responses, IFNγ production and induction of downstream effector cytokines, NLRP3

254 and AIM2 inflammasome activation, and the signalling pathways involved in mediating these responses.

I utilised progesterone-pre-treated, intact mice for all the studies described in this thesis. This replicates infection during progesterone-dominated stages of the menstrual cycle or hormonal contraceptive use in fertile women and thus represents Chlamydia infection in susceptible women that have normal reproductive function. However, these studies cannot discount any confounding effects that may result from interactions between progesterone and other hormones, including oestradiol, produced by the ovaries. Therefore, future studies will aim to replicate the key experiments outlined in this thesis in ovariectomised mice in order to disentangle the roles of other female sex hormones in the regulation of IFNε and IFNε-mediated responses.

5.2.2 Further investigation into the role of IFNε-regulated

immune, metabolic, and cell cycling pathways in the

protection against Chlamydia RTIs

In Chapter 2, I demonstrate that IFNε regulates the accumulation of innate immune cells and the expression of factors involved in innate immune pathways in the female RT, both at baseline and during infection. In Chapters 3 and 4, I expand on these findings by illustrating how NK cell responses and inflammasome signalling pathways contribute to IFNε-mediated protection against Chlamydia RTIs. However, I also identified numerous other innate immune, metabolic, and cell cycling pathways and processes regulated by IFNε that I was unable to explore within the timeframe of my

PhD studies. Several of these pathways have the potential to influence host defence against Chlamydia infections and so will be the subject of further investigation in future studies. These included pathways involved in neutrophil function, glutathione-mediated

255 detoxification, LXR/RXR, AHR, GADD45, and 14-3-3σ signalling, melatonin degradation, and lipid metabolism.

To confirm the involvement of these pathways in IFNε-mediated responses, I will firstly validate the changes in expression of key factors identified by array between

WT and IFNε-/- mice, using qPCR and immunoblot analyses. I will also identify the cellular source/expression patterns of the key factors involved in these pathways using flow cytometry and/or immunofluorescent staining. To determine the role of these factors in host defence against Chlamydia infections, I will then design and perform appropriate loss/gain-of-function studies in WT and IFNε-/- mice, depending on the factors identified and tools available, in order to assess the effects of these factors/pathways on infection and immune responses during Chlamydia female RTI.

5.2.3 Elucidating the mechanisms that underpin IFNε-

mediated NK cell accumulation, activation, and IFNγ

responses

The studies outlined in Chapter 3 show that IFNε potentiates the accumulation of both c and uNK cells in the uterus, and that this correlates with an increase in the number of precursor and mature NK cells produced in the bone marrow and IL-15 and

CXCL10 expression in the uterus. I am now expanding on these studies in order to increase our understanding of the mechanisms that underpin how IFNε regulates local and systemic NK cell responses.

As NK cells were the most abundant cell type present in the upper RTs of WT mice at 3dpi, the only cell population altered by the presence/absence of IFNε (Figure

2.3), and have previously been shown by others to protect against Chlamydia by producing large amounts (and being the predominant source) of IFNγ in the early stages

256 of infection (Tseng and Rank, 1998), IFNε-mediated production of IFNγ by NK cells is likely to be the mechanism of IFNε-mediated protection against Chlamydia RTIs.

However, although the total numbers of other cell populations were not altered by IFNε,

IFNε may still affect their production of IFNγ. In order to determine if IFNε affects the production of IFNγ by other cell types, I will use flow cytometry to identify other sources of IFNε-induced IFNγ and the relative amounts of IFNγ produced by each of these cell types in WT and IFNε-/- mice.

I show that systemic depletion of NK cells during infection in WT mice leads to an increase in Chlamydia replication in the upper RT, providing evidence that IFNε- mediated NK responses may play an important role in protecting against Chlamydia.

However, Chlamydia infection in NK cell-depleted WT mice did not reach the level observed in IFNε-/- mice. This may be explained by the fact that whilst NK cell depletion reduced systemic NK cell responses, much like in IFNε deficiency, the numbers of active, IFNγ-producing NK cells in the uterus was not affected. These data suggest that local IFNε responses strongly promote the proliferation of NK cells in the uterine tissue. Furthermore, a decrease in the number of uNK cells present in the RTs of

IFNε-/- mice further supports the premise that IFNε promotes the development of NK cells locally, as these cells are known to differentiate in situ from NK cell precursors that reside in local secondary lymphoid sites. To investigate the effects of IFNε on local

NK cell generation and maturation, experiments will be conducted in Chlamydia and sham-infected, WT and IFNε-/- mice using rIFNε. NK precursor populations as well as the number and activation of mature uNK and cNK cells will be assessed in uterine and local lymphoid tissues using flow cytometry prior to and after IVAG rIFNε administration compared to sham-treated controls. We will also investigate systemic

NK cell responses, including expansion, chemoattraction, activation, and IFNγ

257 production and induction of NK cell-associated effector cytokines, in these experiments.

These future experiments will not only allow me to identify the effects of IVAG administration of rIFNε on local NK cell proliferation in WT and IFNε-/- mice, but will also help identify if the administration of rIFNε to the female RT indirectly affects systemic NK cell responses.

In order to delineate the direct versus indirect effects of IFNε on NK cell responses, I also plan on performing a series of in vitro studies. To assess the direct effects of IFNε on NK cells, I will isolate splenic NK cells from WT, IFNε-/- and

IFNAR-/- mice and stimulate them with rIFNε ex vivo. I will then assess the effects of rIFNε treatment on NK cell proliferation, IFNγ production, CD69 expression, and the expression of other homing receptors and markers of development. Additionally, others have previously demonstrated that IFNε mildly stimulates NK cell cytotoxicity (Peng et al., 2007). As perforin-/- mice have been shown to clear C. muridarum RTIs at a similar rate to WT controls (Murthy et al., 2011; Perry et al., 1999a), the cytolytic action of NK cells is unlikely to play a major role in protection against Chlamydia infections.

However, the effects of rIFNε on NK cell cytotoxicity will also be investigated in my studies as these responses may be important in the context of other RTIs. Assessing the indirect mechanisms that underpin IFNε-mediated NK cell responses will be more difficult to achieve using in vitro culture systems. These experiments will first require the identification of possible NK cell-potentiating factors that are induced by IFNε, confirmation of the accessory cells that are the source of these factors, and the design of appropriate accessory cell:NK cell co-culture systems that will allow for suitable loss/gain-of-function studies that demonstrate the role of any factors of interest in the induction of IFNε-mediated NK cell responses. One such factor that may be indirectly mediating IFNε-induced NK cell responses that I am interested in pursuing in future

258 studies is IL-15. IL-15 not only drives the development of NK cells in the bone marrow

(Kennedy et al., 2000; Mrozek et al., 1996; Puzanov et al., 1996; Ranson et al., 2003;

Rosmaraki et al., 2001; Suzuki et al., 1997; Williams et al., 1997), but has also been shown to mediate type I IFN-induced NK cell responses, including proliferation, IFNγ production, and cytolytic activity during infection and upon TLR stimulation (Baranek et al., 2012; Lucas et al., 2007; Nguyen et al., 2002). Importantly, I show that IL-15 expression is reduced in the RT of IFNε-/- mice, both at baseline and during infection, compared to WT controls (Figure 3.7 A & D), which strongly suggests that IL-15 may play an important role in the IFNε-mediated induction of NK cells responses observed.

To investigate the role of IL-15 in IFNε-mediated NK cell responses, I intend on identifying the cellular source of IFNε-induced IL-15 by performing either flow cytometry or immunofluorescent staining on tissues obtained from infected and sham- infected, WT and IFNε-/- mice. As type I IFN-induced IL-15 has previously been shown to be produced and presented to NK cells by DCs in the lymph nodes (Lucas et al.,

2007), these analyses will be performed on both uterine and RT-draining lymph node samples. Once the cellular source of IL-15 is identified, I then will design and perform in vitro co-culture experiments to assess the indirect effects of IFNε-induced IL-15 production by the cells identified on NK cell responses. Combinations of IL-15- producing cells from WT, IFNε-/-, and IFNAR-/- mice, infected with Chlamydia or sham-infected, will be co-cultured with splenic NK cells from WT and IFNAR-/- mice in the presence or absence of rIFNε. The exact nature of these co-cultures will be dependent on the cells identified. The role of IL-15 in IFNε-mediated NK cell proliferation, activation, IFNγ production, and cytotoxicity will be confirmed by adding anti-IL-15 or rIL-15 to the culture medium in these experiments.

259 I will also validate the role of IL-15 in mediating protective NK cell responses downstream of IFNε in vivo. To do this, I will treat WT mice with anti-IL-15 antibodies either IP or IVAG and assess the effects of systemic/local IL-15 depletion on

Chlamydia infection and local and systemic NK cell responses compared to sham- treated WT and IFNε-/- mice. I will also administer rIL-15 IVAG to IFNε-/- mice and assess the effects of restoring IL-15 in IFNε-deficient mice.

5.2.4 Further investigation into role of

inflammasome/caspase-1/IL-1β signalling pathways in

the induction of anti-Chlamydia responses

In Chapter 4, I demonstrate that inflammasome/caspase-1/IL-1β signalling pathways are involved in IFNε-mediated responses. I am currently expanding on these findings to elucidate the roles of factors induced downstream of NLRP3 and AIM2 activation in protection against Chlamydia RTIs and identify the mechanisms that underpin IFNε-mediated regulation of these responses.

I have shown that IFNε increases the mRNA expression of IL-1β in the upper

RT at baseline, but decreases IL-1β transcription during Chlamydia RTI and has no effect on IL-18 expression. However, I also show that IFNε increases caspase-1 expression and activation in NK cells during infection. To validate the effects of IFNε on IL-1β and IL-18 activation, I will perform immunoblot analyses to assess pro- and active-IL-1β and -IL-18 protein levels in uterine tissue from WT and IFNε-/- mice.

I have shown that a deficiency in IFNε decreases caspase-1 activation in cells of the upper RT early during Chlamydia infection. However, previous cell death due to pyroptosis may reduce the numbers of active caspase-1+ cells present in IFNε-/- mice and so the differences observed in caspase-1 activation may be due to the kinetics of the

260 immune response and timing of analysis. To confirm that the changes in observed in caspase-1 activation are not due to earlier pyroptosis of active caspase-1+ cells in IFNε-/- mice, I will assess capase-1 activation in uterine tissue from WT and IFNε-/- mice at several different time-points post infection via immunoblot analysis.

In Chapter 3, I use the specific NLRP3 inhibitor, MCC950, to demonstrate that

NLRP3 inflammasome activation may contribute to IFNε-mediated protection against

Chlamydia RTIs. However, the mechanisms that underpin NLRP3-mediated protection are yet to be determined, as caspase-1 activation in the upper RT was unaltered by

IVAG MCC950 treatment. This suggests that 1) MCC950 mediates its effects by inhibiting NLRP3 activation in the vagina/cervix but does not affect NLRP3 activity in the uterus, 2) there is a redundant pathway of caspase-1 activation that compensates for inhibition of NLRP3 signalling in the uterus, and/or 3) there is a novel, NLRP3- dependent, caspase-1-independent pathway involved in protection against Chlamydia.

To address these possibilities, I will first assess and compare the effect of IVAG

MCC950 treatment on the activation of caspase-1, IL-1β, and IL-18 in the vagina and cervix compared to the uterus during Chlamydia RTI using flow cytometric and immunoblot analyses. To confirm the mechanism of NLRP3-mediated protection, I will then perform loss-of-function studies using specific inhibitors and/or neutralising antibodies against the factors/cytokines induced downstream of NLRP3 identified.

Specifically, WT mice will be treated IVAG with the caspase-1 inhibitor, Y-VAD, or anti-IL-1β or -IL-18 antibodies and the effects of inhibiting these factors on Chlamydia infection and protective/detrimental immune responses in the RT assessed via qPCR and flow cytometry. These studies will also allow me to explore the divergent effects of each of these inflammasome-induced factors and determine whether the NLRP3

261 inflammasome is solely responsible for the IFNε-mediated increases in caspase-1 activation observed in WT mice.

If NLRP3 is found to be responsible for the IFNε-mediated increase in caspase-1 activation observed in NK cells in the experiments outlined above, I will perform further immunofluorescent analyses, co-staining for NLRP3 and NK1.1 in sections of uterine tissue from both WT and IFNε-/- mice, to determine if IFNε also regulates the expression of NLPR3 in NK cells. The role of NLRP3 expression and activation in NK cell responses will also be investigated in the in vitro NK cell experiments outlined above.

I will also assess whether the activation of other inflammasomes, such as AIM2, and non-canonical inflammasome pathways (involving caspase-4) are contributing to caspase-1 activation in the upper RT during Chlamydia infection. To do this I will infect

WT and AIM2-/- mice, either treated with MCC950 or sham-treated, and assess the relative contributions of each of these inflammasome pathways to caspase-1 activation and protection against Chlamydia infection in the upper RT. To determine the relative contributions of the AIM2 inflammasome to IFNε-mediated protection, I will then treat

AIM2-/- mice with rIFNε and assess the effect of either deficiency on Chlamydia infection and IFNε-mediated responses. To investigate the contribution of caspase-4 and non-canonical inflammasome activation to IFNε-mediated responses, similar studies will be conducted using the specific caspase-4 inhibitor, Z-LEVD-FMK.

Future studies will also aim to identify the cellular source of IL-1β, caspase-4, and AIM2 in WT and IFNε-/- mice using flow cytometry or immunofluorescent staining.

In order to gain an understanding of how IFNε up-regulates the mRNA expression of each of these factors, I will assess the activation of signalling pathways known to be involved in their transcription, such as PRR signalling pathways, in WT and IFNε-/-

262 mice. Depending upon the factors identified, in vitro and in vivo loss/gain-of-function experiments will be designed to help determine the role of the factors identified in the

IFNε-mediated induction of IL-1β, caspase-4, and AIM2.

5.2.5 Further investigation into the role of IFNε-mediated

NK cell and inflammasome responses in adaptive

immunity to Chlamydia and the development of long-

term immunopathology

The studies outlined in my thesis demonstrate that IFNε regulates innate immune responses in the female RT and that these IFNε-mediated responses protect against

Chlamydia RTIs from the earliest stages of infection. Preliminary studies show that the

IFNε-mediated reduction in Chlamydia burden leads to a reduction in clinical signs of disease throughout the time-course of infection (Fung et al., 2013). However, these studies did not assess the effects of IFNε on Chlamydia-induced pathology and long- term sequelae. Studies are currently being undertaken to determine the role of IFNε in the development of immunopathology in the female RT during Chlamydia infection as part of another student’s PhD research. These studies will assess inflammation in the upper RT, particularly neutrophilic inflammation in the oviducts as this is associated with immunopathology, in WT and IFNε-/- mice at various time-points throughout

Chlamydia RTI using conventional histology, immunohistochemistry, and flow cytometry. We will also assess hydrosalpinx and fertility in WT and IFNε-/- mice after infection with Chlamydia to determine the role of IFNε in the development of sequelae.

Changes in pathology at these time-points will be correlated with the expression of factors known to contribute to protection against, or the development of, immunopathological features of disease. The effectiveness of rIFNε in preventing long

263 term sequelae will also be investigated as part of these studies to expand upon the findings outlined in Chapter 2, which indicate that rIFNε may be an effective therapeutic agent for the prevention of Chlamydia RTIs.

In Chapter 3, I show that IFNε regulates NK cell responses during Chlamydia

RTIs. I also show that IFNε increases the number of IFNγ+ T cells present early during infection. Interestingly, Jiao et al. have shown that NK cell responses protect against C. muridarum respiratory tract infections by stimulating DCs to produce IL-12, which primes for the development of Th1 immunity (Jiao et al., 2011). Taken together, these data suggest that IFNε may also promote the development of protective adaptive immune responses to Chlamydia. However, conventional type I IFN signalling has been shown to be detrimental to the host during Chlamydia RTIs due to IFNβ-mediated inhibition of MHC-II presentation of Chlamydia antigens, which suppresses the development of the adaptive immune response. We have conducted preliminary experiments that suggest that adaptive immune responses may not be greatly affected in

IFNε-/- mice compared to WT controls (Appendix B: sFigure 2.3), however, these analyses were quite limited in their scope. As such, future studies will investigate the effects of IFNε on DC function, MHC-II expression, development of Th1/Th2/Th17 immunity, and activation of CD8+ T cell responses during Chlamydia infection using flow cytometry.

In Chapter 4, I also show that IFNε promotes the expression of IL-1β at baseline but reduces its expression during infection. Importantly, IL-1β responses have been implicated in both the innate processes that control infection and the aberrant inflammatory responses that drive pathology (Prantner et al., 2009). However, early IL-

1β expression has been shown to protect against C. pneumoniae respiratory tract infections, and associated immunopathology in the later stages of infection, by limiting

264 Chlamydia growth early (Shimada et al., 2011). This suggests that the deficiency in IL-

1β expression observed in IFNε-/- mice at baseline may allow for increased Chlamydia growth, leading to aberrant IL-1β responses later during infection that are responsible for the development of pathology. The effects of IFNε on IL-1β expression and activation at later stages of infection and the role of IFNε-regulated IL-1β responses in the development of inflammation and pathology are yet to be determined. To address this, the expression of pro- and active-IL-1β will be assessed in WT and IFNε-/- mice via immunoblot analysis and correlated with the development of pathology at various time- points post infection. Loss-of-function studies will then be performed to determine the contribution of IFNε-mediated IL-1β regulation to the development of Chlamydia- induced pathology. To do this, I will inhibit IL-1β responses, either early or during the later stages of infection, by administering anti-IL-1β antibodies to WT and IFNε-/- mice.

The timing of anti-IL-1β treatments will be informed by previous IL-1β expression profiling experiments. I will then assess the effects of these different IL-1β depletion regimes on infection and the development of pathology in the female RT. Similar studies will be conducted using administration of MCC950 to determine the effects of

NLRP3 inflammasome-mediated responses at different stages of infection.

265 5.3 Concluding remarks and significance of findings

Chlamydia RTIs are a significant global health problem, affecting an estimated

131 million people annually (World Health Organization, 2008). Infection frequently causes severe RT disease in women and is the most common cause of infertility.

Currently, there are no effective strategies that prevent infection or the development of pathology. An improved understanding of the immune processes that protect against infection may facilitate the development of more effective preventative strategies.

In the studies described in this thesis, I used a murine model of C. muridarum- induced female RTI to investigate the role of IFNε, a novel type I IFN expressed exclusively and constitutively in the female RT, in protection against Chlamydia RTIs. I have made novel observations that identify the mechanisms by which IFNε protects against Chlamydia infections. In preliminary experiments, I demonstrate that IFNε regulates pathways involved in innate immune processes and promotes NK cell accumulation and IL-1β responses in the female RT. Additionally, I show that rIFNε treatment prior to infection enhances protective responses and reduces Chlamydia load in the female RT.

I then expanded on these findings to show that IFNε promotes protective NK cell responses during Chlamydia RTI. I show for the first time that IFNε increases NK cell haematopoiesis in the bone marrow and the chemoattraction, expansion, and activation of NK cells in the upper RT during Chlamydia infection. Importantly, I also show that

IFNε increases IFNγ production by NK cells in the female RT and that this correlates with increases in the expression of the IFNγ-induced effector factors, iNOS and IDO, which are known to be important mediators of protective anti-Chlamydia responses.

266 I also make novel observations to show that IFNε regulates NLRP3 and AIM2 inflammasome, and caspase-1, caspase-4, and IL-1β responses in the female RT. I show that IFNε regulates the expression of factors involved in inflammasome pathways throughout the RT and promotes the activation of caspase-1 in NK cells. Importantly, I show that local inhibition of the NLRP3 inflammasome increases Chlamydia load in the upper RT, indicating that its regulation contributes to IFNε-mediated protection.

Together, the novel findings outlined in my thesis further our understanding of the mechanisms that underpin protection against Chlamydia infections. My studies have identified potential mechanisms that explain how IFNε regulates protective responses to

Chlamydia RTIs and, importantly, demonstrate the therapeutic potential of targeting

IFNε and downstream responses, highlighting their relevance in novel preventative strategies for protection against infection in the female RT.

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297 Appendices

Appendix A: Supplementary methods sTable 1.1: Oligonucleotide sequences used for qPCR analyses

Target Nucleotide Sequence HPRT Forward 5’-AGGCCAGACTTTGTTGGATTTGAA-3’ Reverse 5’-CAACTTGCGCTCATCTTAGGCTTT-3’ Chlamydia 16S Forward 5’-GCGGCAGAAATGTCGTTTT-3’ Reverse 5’-CGCTCGTTGCGGGACTTA-3’ Chlamydia MOMP Forward 5’-GCCGTTTTGGGTTCTGCTT-3’ (genomic) Reverse 5’-CGTCAATCATAAGGCTTGGTTCA-3’ IFNγ Forward 5’-CTGGAGGAACTGGCAAAAGG-3’ Reverse 5’-TTGCTGATGGCCTGATTGTC-3’ IL-15 Forward 5’-ACAGCTCAGAGAGGTCAG-3’ Reverse 5’-ACCAGCAAGGACCATGAAGAG-3’ CXCL10 Forward 5’-CCAAGTGCTGCCGTCATTTTC-3’ Reverse 5’-TCCCTATGGCCCTCATTCTCA-3’ iNOS Forward 5’-AGCGAGGAGCAGGTGGAAGACT-3’ Reverse 5’-CCATAGGAAAAGACTGCACCGAA-3’ IDO Forward 5’-CCTGGGTCCTTGTGGCTAGAAAT-3’ Reverse 5’-GCTCGCAGTAGGGAACAGCAATA-3’ SOCS1 Forward 5’-AGAGAACTGCGGCCGTGGCA-3’ Reverse 5’-AGGGGTGGGCCATAGCGTCC-3’ IFNγR1 Forward 5’-GCTTTGACGAGCACTGAGGA-3’ Reverse 5’-CCAGCATACGACAGGGTTCA-3’ IL-12p40 Forward 5’-CACGTCCTCATGGCTGGTGC-3’ Reverse 5’-TGCCCGAGAGTCAGGGGAACT-3’ Pan-IFNα Forward 5’-SAWCYCTCCYAGACTCMTTCTGCA-3’ Reverse 5’-TATDTCCTCACAGCCAGCAG-3’ IFNβ Forward 5’-CCCTATGGAGATGACGGAGA-3’ Reverse 5’-ACCCAGTGCTGGAGAAATTG-3’ IFNAR1 Forward 5’-CTGTGTCATGTGTGCTTCCC-3’ Reverse 5’-ATCTTTCCGTGTGCTCCTCA-3’ IRF3 Forward 5’-GCCGGACGTGTCAACCTGGA-3’ Reverse 5’-CGCGCCCCTGGAGTCACAAA-3’ IRF7 Forward 5’-CTTAGCCGGGAGCTTGGATCTACT-3’ Reverse 5’-CCCTTGTACATGATGGTCACATCC-3’ STAT1 Forward 5’-CCCGAATTTGACAGTATGATGA-3’ Reverse 5’-GAAGGAACAGTAGCAGGAAGGA-3’ IRF1 Forward 5’-ATGCCTGTCACGTTGAATGAAGAGG-3’ Reverse 5’-AGGCGGGTCTGCACACATGTTA-3’ IL-1β Forward 5’-TGGGATCCTCTCCAGCCAAGC-3’ Reverse 5’-AGCCCTTCATCTTTTGGGGTCCG-3’ IL-18 Forward 5’-TCAGACAACTTTGGCCGACT-3’ Reverse 5’-CAGTCTGGTCTGGGGTTCAC-3’ Caspase-1 Forward 5’-CGAGGGTTGGAGCTCAAGTTGACC-3’ Reverse 5’-GAAGTCTTGTGCTCTGGGCAGGC-3’ TLR2 Forward 5’-TGTAGGGGCTTCACTTCTCTGCTT-3’ Reverse 5’-AGACTCCTGAGCAGAACAGCGTTT-3’ TLR4 Forward 5’-GGAACTACCTCTATGCAGGGAT-3’ Reverse 5’-TGGTTGCAGAAAATGCCAGG-3’ TLR9 Forward 5’-GAGAGACCCTGGTGTGGAA-3’

298 Reverse 5’-CCTTCGACGGAGAACCATGT-3’ Caspase-4 Forward 5’-TCATTTTACTCTGTCAAGCTGTCT-3’ Reverse 5’-TGTCAGGGTGTTTGTTTTCAG-3’ AIM2 Forward 5’-AAATGCTGTTGTTGACCGGC-3’ Reverse 5’-GAGTGTGCTCCTGGCAATCT-3’

299 Appendix B: Chapter 2 supplementary data sTable 2.1: Molecular networks associated with genes down-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls at baseline (sham- infected). p-values were calculated during Ingenuity® Pathway Analysis (IPA®) analysis and represent the likelihood of finding the number of focus molecules (dysregulated transcripts identified by microarray) in each network in a set of x randomly selected molecules, where x = the total number of molecules in that network. p-scores=-log10(p-value).

ID Molecules in Network Score Focus Top Diseases and Molecules Functions 1 Akt, Ap1, BCR (complex), BHMT, BST1, CCK, 58 39 Cell-To-Cell CD3, CD7, CD27, CD83, CD79A, CLDN4, Signalling and CSF3, CTSG, DLK1, DSG3, EOMES, ERK, Interaction ERK1/2, FCRL5, GJA1, H60b/H60c, HS6ST2, HSPA5, IFN alpha/beta, Iga, Ige, IgG, IgG1, Haematological Igg3, IgG2a, IgG2b, IGHM, Igm, IL20, IL33, System Development IL12 (complex), IL18RAP, IL20RA, and Function Immunoglobulin, Interferon alpha, JCHAIN, Jnk, KLK11, Klra7 (includes others), KLRB1, Klrk1, Immune Cell KRT75, LDL, MHC Class II (complex), MZB1, Trafficking NFAT (complex), NFkB (complex), P38 MAPK, PDE6H, PI3K (complex), PIK3AP1, Pkc(s), POU2AF1, PTPN22, Ras, RBP4, SELL, SH2D1A, SLPI, SRC (family), STAT5a/b, TCR, Tgf beta, TNFRSF17 2 ADH7, AGPAT1, AGT, AHR, ALDH1A3, Alp, 49 35 Lipid Metabolism AMACR, APOBEC3B, C2, C6, CA2, CALB1, CALD1, CFB, Cg, CHEK1, CHI3L1, CLDN3, Small Molecule CLPS, Collagen(s), CTSD, EFNB2, EMP1, Biochemistry estrogen receptor, FGF1, G0S2, GJB3, GSTA5, H3F3A/H3F3B, Histone h3, Histone h4, HLA- Vitamin and Mineral DQA1, HOXA11, HRH3, Hsp90, Metabolism HSPA1A/HSPA1B, IFI16, Ifn, Ifnar, Igk, IRG1, ITGB6, KLRC1, KLRD1, LIPE, MREG, NET1, Nr1h, OAS1, OAS2, OAS3, PC, PCDH8, Pka, PLIN1, PNLIPRP2, PRKG2, Proinsulin, RNA polymerase II, SDSL, SLC1A1, Sos, SRA1, ST8SIA4, STAR, Tcf7, TNMD, Vegf, WNT11, WNT7A 3 ACKR2, ACSL1, ADGRE1, Akt, ALK, ANXA4, 38 29 Inflammatory AOAH, ARNTL, ATF3, BFSP2, BHMT, BMP5, Response CA2, CABIN1, CD74, Cd200r3, CEBPB, chemokine, CITED2, CLSTN2, CXCL17, Lipid Metabolism CYP1A1, CYP27B1, DGAT1, DGAT2, EP300, ESR1, GATA4, GIMAP7, GSTA5, HSD11B1, Molecular Transport HSF2BP, HYOU1, Ifi27l2a/Ifi27l2b, Ifitm6, Igha, IGHM, IL4, IL6, IRF8, IRG1, IRS, JAK3, Klrk1, KRT20, LEPR, LPAR3, LRTM1, MAPKAPK2, mir-21, Mt4, NCOA2, NPY, PILRB, PLAA, RORC, S100A8, Scd2, SGK1, SLAMF1, SLC25A37, Smok2b (includes others), STAR, TAF7L, TIGIT, TLR3, Tnp1, Tnp2, TNPO3, TP63 4 ACSL1, ADAM10, ADAM28, ADAMTS4, 36 28 Haematological Apol7e (includes others), ATF3, CABIN1, System Development

300 CARD9, CD74, CD209, CHST2, CHST4, and Function COCH, CPNE4, CXCL14, CYP4A22, DMBT1, EHD1, EMP1, ESRRB, FOXC2, G0S2, GCNT1, Tissue Morphology Gm8221, Gsta4, HSD11B1, HSPA1A/HSPA1B, IFNE, IL2, IL13, IL25, IL1RL1, IRF8, IRG1, Cell-To-Cell ITPR2, LAMTOR3, LSP1, LY6D, MAP3K8, Signalling and MAPK1, MED8, MED14, MEF2C, mir-506, Interaction NACC1, NCOA2, NETO2, NFE2L2, NFkB (complex), NFKBIB, NRN1, Olfr1508, PDCD1, PDCD11, PLA2G2D, PLIN1, PPARG, PRDX2, RARRES3, S100A8, S100A9, SDC4, SH3PXD2A, SOX2, SRA1, TICAM2, TNF, TRIM14, Usp17la (includes others), ZFP42 5 26s Proteasome, AKT1, ALDH1A1, ALDH1A3, 36 28 Tissue Morphology Alox12e, ANXA8/ANXA8L1, Ap2 alpha, APOD, AQP1, ATF3, ATP2B2, C2, Ccl8, Cell Death and CCND3, CD74, CHAC1, CP, CTNNB1, CTSE, Survival DKK3, EPHA1, FGF18, FKBP5, GDA, GPRC5B, GSE1, GSTO1, HLA-DQA1, Cellular Development HSPA1A/HSPA1B, HTT, IFNG, IGHA1, Iglv1, IL1B, IL1RL1, IL20RB, IRF8, IRG1, KDM1A, LECT2, MAP6, MCOLN2, Ms4a4b (includes others), MYBPC3, MYH3, NCOA2, NFKBIB, NRIP1, PDK1, PGR, PLA2G2D, POLR2A, POSTN, PRDX2, PROK2, PSTPIP2, RAMP1, RBP4, RRAD, Serpina3g (includes others), SLC6A6, SMAD7, SMARCA4, SPINK13, STON2, TACSTD2, TBR1, TP53, TREM1, ZNF750 6 ACACA, AGTR1, AP3B2, ATF3, B4GALT5, 21 19 Cellular Movement BACH2, CD22, CITED2, COL14A1, COL1A2, Cpla2, CRABP1, CRELD2, CRYM, DDN, Cell Death and EDN1, EFEMP1, EPHA8, ETS1, ETS2, ETV4, Survival FBLN2, GATA6, GFPT2, GJA1, GZMK, H2AFY, HAND1, HIPK2, Hist1h1a, HNRNPH1, Cellular Development HNRNPK, HSPA1A/HSPA1B, HSPH1, Igha, IL5, IL17RB, IL1RL1, IRF8, ITGA6, KLF6, Klra16, Klre1, LTB, MAPKAPK2, MCM6, MSX2, MYC, NPHS1, NPPA, NPY, PDGF BB, PDK1, PML, POU4F1, PPIA, PTBP1, RAVER1, RELB, RET, SBDS, Skor1, SLC22A4, SPARC, Stfa1 (includes others), TEX2, TMC5, UBE2QL1, VDR, VEGFA 7 GGT6, HNF4A 2 1 Cancer

Cellular Development

Cellular Growth and Proliferation 8 NUPR1, PXDC1 2 1 Cancer

Organismal Injury and Abnormalities

Reproductive System Disease 9 UPK3A, UPK3B 2 1 Molecular Transport

Renal and Urological System Development

301 and Function

Tissue Morphology 10 ADCYAP1, DGKK 2 1 Behaviour

Cancer

Cell Morphology

302 sTable 2.2: Molecular networks associated with genes down-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls during Chlamydia infection. p-values were calculated during Ingenuity® Pathway Analysis (IPA®) analysis and represent the likelihood of finding the number of focus molecules (dysregulated transcripts identified by microarray) in each network in a set of x randomly selected molecules, where x = the total number of molecules in that network. p-scores=-log10(p-value).

ID Molecules in Network Score Focus Top Diseases and Molecules Functions 1 ADORA2B, Akt, Alpha catenin, APLN, APOA5, 53 36 Cell-To-Cell Apoc3, BCR (complex), CD300A, CD300LD, Signalling and CDK1, Cg, CLEC4E, Creb, CXCL3, ERK, Interaction ERK1/2, FBXL5, FGA, FLT1, H19, HDL, HDL- cholesterol, haemoglobin, HLA-A, Iga, Ige, Igm, Haematological IL10, IL12 (complex), IL12 (family), IL1B, System Development Immunoglobulin, Interferon alpha, Jnk, KRT75, and Function LASP1, LDL, LDL-cholesterol, LILRB3, LIPC, LIPG, LYAR, MAP2K1/2, Mek, MHC Class II Immune Cell (complex), MYL2, NFkB (complex), Nr1h, P38 Trafficking MAPK, PI3K (complex), PI3K (family), PIN1, Pkc(s), RAP1A, Ras homolog, RGS16, S100A8, S100A9, Saa3, SDCBP, SLFN13, SLFN12L, SP110, SPRY4, TCR, Tlr, VCAN, Vegf, VLDL- cholesterol, ZEB2 2 4933415F23Rik, AGER, BACH2, C3, c-Src, 41 30 Haematological CBFB, CD69, CD84, CDH17, CNTFR, Cphx1 System Development (includes others), CX3CR1, CXCL3, CYP11B2, and Function DLK1, FIGLA, GEM, GNAS, GPR119, GRK5, HAMP, HIST1H2AL, IDO1, IER2, IFNA4, IgG, Tissue Morphology IgG2a, Igk, IL17RA, KLK11, KRT16, LCP1, Lh, LTB4R, MKL1, MKL2, NR1H2, NUPR1, Inflammatory OR2AK2, P2RY14, PHLDA1, Prl3b1, Prm1, Response PROCR, Proinsulin, Psg16, PTGER2, PTPN1, PTPRN2, PXDC1, RAG1, RCAN1, S100A8, Saa3, SCARF1, SPDL1, SPIB, SRF, Stfa1 (includes others), Stfa2/Stfa2l1, STXBP5L, SYT10, TBL2, TLR9, Tnp2, TP73, VEGFA, VPREB1, Wfdc17, YBX2 3 A2M, ADA, AGER, AKR1B1, ANXA3, BNIP3, 33 26 Cell Death and BTG4, CBX7, CCDC169, CDC42, CEACAM1, Survival CEP55, CLCA2, CNN2, CSTA, CTNNB1, CYP1A1, CYP2C8, Cyp2d9 (includes others), Free Radical DDIT4, DPPA2, E2F4, EHF, EPHA4, ETHE1, Scavenging F2R, GATA4, GJB3, GLRX, GPX1, HIST1H3D, HORMAD2, HSFY1/HSFY2, IGFBP2, INPP5E, Cellular Movement KIF14, MAP3K5, MAPK10, mir-101, MMP1, Mup1 (includes others), NUDT18, OGG1, PDK1, PMCH, PPARD, PRC1, PROP1, PTP4A1, RBMS3, RETN, RNF2, S100A8, SERPINA3, SERPINE2, SERPINH1, SESN1, SIN3A, Slco1a1, SMARCA4, TCF7L2, TDO2, TERC, TIMP3, TP53, TP63, TREM2, TRIM71, UBE3A, UPK2 4 ACOXL, AK4, AQP1, AR, AURKB, BAG4, 28 23 Lipid Metabolism CA4, CARM1, CASP4, CCNE1, CD69, CEACAM1, CYP2C9, Cyp2j13, CYP7A1, Small Molecule CYP8B1, DIO1, E2f, EGR1, EP300, FABP5, Biochemistry

303 FKBP5, GABRG3, GMNN, HDAC2, HIST1H4C, Histone h3, Histone h4, HNF4A, Vitamin and Mineral HNRNPU, Hsp70, IL32, Il1bos, INHBA, IRG1, Metabolism KLK2, KRTDAP, Madcam1, MAGED2, MCOLN2, MED14, MEST, mir-223, MMP1, MST1R, MTHFD2, MTTP, NOD2, NPC1, NR3C1, PA2G4, PHB, PLAA, PROC, PTGDS, Rb, RIPK2, RNA polymerase II, SCNN1A, SCRT1, SFTPA1, SLC12A5, SLC2A6, SREBF1, TERC, TERT, TNFAIP6, TSIX, USH1C, XIST 5 4933409K07Rik, ABCG1, ADAM10, AGER, 28 23 Cell-To-Cell AGTR1, ALB, APP, ARF6, ARR3, ATG16L1, Signalling and BACE1, BACH2, BECN1, C3, CD200R1, Interaction CLEC4E, CNGA3, CXCL5, DDX60, E130116L18Rik, Eotaxin, F10, FAS, GRB2, Cellular Movement GTF2IRD1, HIST1H4D, IDO1, IGHA1, IKBKG, IL13, IL-1R, IL12B, IL36A, INA, IRAK3, Haematological ITGAM, KRT17, LBP, LRRC2, MAPK1, mir-17, System Development MST1R, NCOA3, NFkB (complex), NFKBIE, and Function NHLH1, NR1H3, NUAK2, PIAS4, PTPRE, RND1, RPL13, S100A9, Sbp/Sbpl, SCN1A, SERPINC1, SMPD2, Ssty1 (includes others), TANK, TAX1BP1, TBC1D14, TICAM2, TNFRSF9, TNFRSF18, TRAF3IP2, TRIM14, TRPV4, TUBB3, TUBB2B, UHMK1 6 6330415B21Rik, ACOX1, Aldose Reductase, 26 22 Cellular Movement ANKRD42, BECN1, BSG, CABP4, CD69, CD274, CD1D, CDC42, CEACAM1, Cg, Immune Cell CLEC5A, CNTN2, COX17, CSF2, CTSC, ETS1, Trafficking GBP6, GSDMC, GZMK, HLA-DQ, HTR4, HTR7, IDO1, IFNE, IL2, IL37, IL12 (complex), Haematological IL18BP, IL1RAP, IL36A, Klra16, Krtap21-1, System Development LRRC15, LUM, MAPKAP1, MARCH3, MED8, and Function MED14, MED26, MED29, mir-21, MMP1, Ms4a4b (includes others), MTOR, MXD1, MYC, NFKBIE, NRP1, OLFM4, Orm1 (includes others), POLR2A, PRKCZ, RARRES3, RICTOR, Saa3, SFTPD, SLC25A37, SLC4A4, Snrpc, SOCS6, SYNPO, TAF4, TNF, TNFRSF18, Traj18, TREM2, TSPAN32 7 GSTP1, SMG8 2 1 Cancer

Organismal Injury and Abnormalities

Renal and Urological Disease 8 DNASE2B, Foxe3 2 1 Embryonic Development

Organ Development

Organ Morphology 9 TNNC1, TNNI3K 2 1 Cardiovascular System Development and Function

Organ Morphology

Skeletal and Muscular

304 System Development and Function 10 DMRT1, TRIM50 2 1 Cell-To-Cell Signalling and Interaction

Cellular Assembly and Organization

Cellular Development

305 sTable 2.3: Molecular networks associated with genes commonly down-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls both at baseline and during Chlamydia infection. p-values were calculated during Ingenuity® Pathway Analysis (IPA®) analysis and represent the likelihood of finding the number of focus molecules (dysregulated transcripts identified by microarray) in each network in a set of x randomly selected molecules, where x = the total number of molecules in that network. p-scores=-log10(p-value).

ID Molecules in Network Score Focus Top Diseases and Molecules Functions 1 ABCG1, ADAMTS12, ANXA4, BACE1, 40 18 Cellular Movement BECN1, BNIP3, CCND3, CHUK, CLU, CNR1, Cpla2, DLK1, ETS1, FCAR, GATA6, GJB3, Haematological GZMK, HIPK2, IFNAR1, IFNE, Iga, IgG2c, System Development IGHA1, Igk, IKBKB, IKBKE, IKBKG, IL7, and Function IL11, IL32, IL12B, IL17C, IL17RA, IRF8, IRG1, KLK5, KLK11, Klra16, MAPK1, MCOLN2, Tissue Morphology MED8, MED14, MSR1, NDN, NOD2, PDK1, PGR, Pka, PLA2G2D, PLAA, PPARG, RARRES3, RIPK2, S100A8, S100A9, SLC25A37, SOCS1, SP1, SPI1, STAT1, Stfa1 (includes others), TBK1, TCF3, TICAM1, TICAM2, TNF, Tnp2, TP53, TRIM14, VEGFA 2 NUPR1, PXDC1 3 1 Cancer

Organismal Injury and Abnormalities

Reproductive System Disease 3 Ige, KRT75 3 1 Dermatological Diseases and Conditions

Hereditary Disorder

Cancer 4 ENTPD4, miR-122-5p (miRNAs w/seed 3 1 DNA Replication, GGAGUGU) Recombination, and Repair

Nucleic Acid Metabolism

Small Molecule Biochemistry

306 sTable 2.4: Molecular networks associated with genes up-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls at baseline (sham-infected). p-values were calculated during Ingenuity® Pathway Analysis (IPA®) analysis and represent the likelihood of finding the number of focus molecules (dysregulated transcripts identified by microarray) in each network in a set of x randomly selected molecules, where x = the total number of molecules in that network. p-scores=-log10(p-value).

ID Molecules in Network Score Focus Top Diseases and Molecules Functions 1 26s Proteasome, ABCB4, Abcb1b, ACP5, 65 39 Cell Morphology AKAP7, AKR1C3, Akt, Alp, AQP5, BAG1, BCAT1, BMP3, CA4, CCL1, CDH4, CDH16, Connective Tissue CFTR, Cg, CHST8, Creb, CRP, CSF1, Cyclin A, Disorders DAXX, DHCR24, DNAH11, ELAVL2, ELL2, ERK, ERK1/2, ERN1, estrogen receptor, FCRLB, Skeletal and Muscular FKBP5, FSH, G6PC, GABBR2, GCM1, GDF15, Disorders Histone h3, IER3, IgG, IgG1, IL12 (complex), Jnk, KCNMA1, KSR2, Lh, LRAT, NFkB (complex), P38 MAPK, PIK3CB, Pka, POLE, Proinsulin, PTN, RABGEF1, RFX3, RNF13, RXFP3, SCG5, SCGB3A1, SLC39A12, SQSTM1, TCR, TGFB2, Tgtp1/Tgtp2, TSHR, VDR, Vegf 2 ADCYAP1, AJAP1, AK3, ALDOC, APP, AQP8, 37 26 Gene Expression AR, B3GAT1, BAG1, BASP1, BHLHA15, CALY, CCNT1, CDK9, Ces2a, CHKA, CLDN3, Cancer CLTA, CRYBB1, DACH1, DAPL1, DAXX, ELOVL2, ENTPD7, EP300, ESR1, FBLN1, Organismal Injury and FOLR1, GABRB2, GAPDH, HIF1A, HIF3A, Abnormalities HNF4A, HSF1, Hsp27, Hsp70, ISL1, KISS1, KLK3, MPO, Mucl1/Spt1, NAP1L1, NFAT5, NKX3-1, NOVA1, NSDHL, PELP1, PIK3CB, PIP5K1B, POR, PPID, PROM2, Rbfox3, SCUBE2, SLC10A1, SOX9, SP1, SULT1C2, SUMO1, SYCE1, TAL1, TERT, thymidine kinase, Timd2, TMPRSS6, TRPM1, trypsin, TTC3, WDFY1, XBP1 3 ABCB4, ABCC6, ALDOC, APOE, AQP2, 35 25 Cell Death and BAG1, BASP1, C4bp, CALCR, CAMK2B, Survival CAP1, CDK1, CHRM2, CLTA, Collagen(s), CREM, cytochrome C, DAXX, DNASE1, ELF4, Hereditary Disorder FABP3, FKBP5, GAPDH, GNAT2, GNB1, GNB3, GNG13, GSN, GUCA2B, GUCY2D, Neurological Disease GUCY2F, Hsp27, Hsp70, HTT, KCTD11, LHX1, LRP8, MAPK14, MAPKAPK3, MAPT, MID1, NAPSA, Oxct2a/Oxct2b, PER1, PKD1, PLA2G4E, Pmca, PMEPA1, POU2F1, PSEN1, RAB17, RGS6, RGS9, RGS7BP, RPS6KA1, SERPINC1, SLC2A9, SLC35G1, SLC47A1, SLC5A8, SOD1, SPON1, STIM1, STX1A, TMEM59L, TP53, TPI1, TPT1, TTBK1, UBQLN1 4 Actin, AGMAT, CADM3, CCL28, CCND3, 31 23 Cellular Development CDK9, CLCF1, CLDN3, Cmya5, CNTFR, CPB2, CPN1, CRLF1, DAXX, ELF3, EPG5, ESR2, Cellular Growth and EVC, FKBP5, GAPDH, GLI1, GLI2, GSTM2, Proliferation HACD4, HGFAC, HNF1A, IL6, IL36RN, KAT5,

307 KIF12, KISS1, KLK3, LMO7, LRRC4C, Gene Expression MAPK13, MARK4, MLPH, MYF5, MYH3, NAP1L2, NGF, NKX3-1, NR3C2, NTNG1, OSCP1, PAX7, PDLIM2, PELP1, PHB, PLCH1, PMEPA1, PNMA2, POU2F1, PXYLP1, RCHY1, SEL1L3, SIN3A, SLC10A1, Slco1a1, SMARCA2, SMARCA4, SMO, SOX9, SRF, TERT, TFEC, TP63, UGT2B15, UGT2B17, WNT3A 5 Egfbp2, HOXA10 2 1 Cancer

Developmental Disorder

Endocrine System Disorders 6 BCL11B, Vmn1r172 (includes others) 2 1 Cellular Development

Cellular Growth and Proliferation

Embryonic Development 7 RTN4, TAGLN3 2 1 Cell Death and Survival

Cell Morphology

Cellular Assembly and Organization 8 KRT84, MSX2 2 1 Cell Death and Survival

Cellular Compromise

Cellular Development 9 CYS1, UNC119 2 1 Haematological Disease

Immunological Disease

Cell-To-Cell Signalling and Interaction 10 EZH2, LYPD6B 2 1 Cancer

Cell Death and Survival

Cell Morphology

308 sTable 2.5: Molecular networks associated with genes up-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls during Chlamydia infection. p-values were calculated during Ingenuity® Pathway Analysis (IPA®) analysis and represent the likelihood of finding the number of focus molecules (dysregulated transcripts identified by microarray) in each network in a set of x randomly selected molecules, where x = the total number of molecules in that network. p-scores=-log10(p-value).

ID Molecules in Network Score Focus Top Diseases and Molecules Functions 1 ACSL5, ADM, AJAP1, ALAD, APP, AR, 41 22 Cell Morphology ARNTL, ASAH1, ATG5, ATP4A, BECN1, BNIP3, BSG, BTNL2, CA8, CALCR, Cellular Function and Calmodulin, CRY1, CRY2, CSNK1E, CTSV, Maintenance DAPL1, DOC2B, DSCAM, DUSP4, EGLN1, ELOVL2, ENPP2, FAIM2, FAS, FGF12, GAST, Behaviour GPR83, GPR182, HSF1, IFNG, IL6, INSR, KCNIP4, KDM3A, LRRC4C, Mapk, MAPK8, MARCO, mir-133, MMP3, NAMPT, NPC2, NR1D2, NR4A2, NTNG1, NUPR1, PDGF BB, PENK, PER3, POU4F1, Rbfox3, SCGB3A1, SLC6A15, SLCO1A2, SMARCA4, SMARCB1, STK11, STXBP3, SYT9, TAC1, TIMP3, TMEM117, TRIM28, ZNF217 2 ACSL5, ADGRB3, AKT2, Ap2 alpha, AQP2, 29 17 Organismal Injury and ARNTL, BMP7, BNIP3, CAP1, CIDEA, Abnormalities Collagen(s), CTSV, DBP, DUSP4, EFCAB7, ENPP2, ESRRA, FGF21, FST, GALNT13, Cancer GATA2, H2AFY, HACD4, HGF, Histone h3, HOXA10, HSF1, ID1, KLC3, KRT23, let-7, Gastrointestinal MAFB, Marcks, Meis1, mir-1, mir-17, mir-22, Disease mir-26, mir-30, mir-130, mir-192, mir-378, miR- 125b-5p (and other miRNAs w/seed CCCUGAG), NAMPT, NQO1, NR1D1, NRIP1, PAX7, PDLIM2, POSTN, PPARA, PRKDC, PTGDS, REM1, RHO, SAMD4A, SCNN1A, SCX, SGCG, SIRT1, SOX5, SPAG6, SYCE1, TERC, TGFBR1, TIMP3, TP53, TRDN, ULK1, YWHAG 3 KCNE4, PELP1 2 1 Cancer

Organismal Injury and Abnormalities

Reproductive System Disease 4 RBP4,Stra6l 2 1 Lipid Metabolism

Molecular Transport

Small Molecule Biochemistry 5 FOLR1, WDFY1 2 1 Auditory and Vestibular System Development and Function

DNA Replication,

309 Recombination, and Repair

Drug Metabolism

310 sTable 2.6: Molecular networks associated with genes commonly up-regulated in the reproductive tract (RT) of female interferon (IFN)ε-/- mice compared to wild-type (WT) controls both at baseline and during Chlamydia infection. p-values were calculated during Ingenuity® Pathway Analysis (IPA®) analysis and represent the likelihood of finding the number of focus molecules (dysregulated transcripts identified by microarray) in each network in a set of x randomly selected molecules, where x = the total number of molecules in that network. p-scores=-log10(p-value).

ID Molecules in Network Score Focus Top Diseases and Molecules Functions 1 2' 5' oas, ABCG2, ACTN2, AIF1, Akt, APP, AR, 13 6 Infectious Diseases ATP1A3, ATP4A, BTNL2, C3, Calbindin, CAP1, Chil3/Chil4, CST3, CYP2C8, DAPL1, DHCR24, Lipid Metabolism DYRK1A, ELOVL2, ENO2, ESR2, FASN, HNF1A, HNRNPA2B1, HSF1, HSPE1, HTT, Molecular Transport IFNG, IL4, IL6, IL13, IL17D, IL9R, LAMA5, LBP, LRRC4C, LY96, MAPT, MARCO, MGLL, MME, PDLIM2, POR, PRKAA1, PRKAA2, PSEN1, PSEN2, PSMB10, PTK2, RB1, Rbfox3, S1PR3, SCAVENGER receptor CLASS A, SCD, SCGB3A1, SGPL1, SLC40A1, SLC7A11, SP110, SREBF1, STAT1, STAT6, STK11, TNK1, TP53, TRAFD1, TTR, Wfdc17, WIPF1 2 DPPA2, HSF1, SYCE1 3 1 Cancer

Cell Cycle

Cellular Assembly and Organization 3 HACD4, PDLIM2, TCOF1 3 1 Auditory and Vestibular System Development and Function

Cellular Development

Cellular Growth and Proliferation

311 10000 ** Progesterone Uterine Horn 1000 0.0541 100 ** ** Progesterone Oviduct/Ovary 10 * Oestradiol Uterine Horn

16S ** 1 * Oestradiol Oviduct/Ovary 0.1 0.01 0.001 Chlamydia 0.0001 * 0.00001 0.000001

Relative Expression (to HPRT) (to Expression Relative 3 7 14 21 30 42 Days Post Infection

sFigure 2.1: Characterisation of Chlamydia infection in the upper reproductive tracts (RTs) of progesterone- and oestradiol-pre-treated mice. Wild-type (WT) C57BL/6 mice were pre-treated with progesterone or oestradiol subcutaneously (SC) at -7 days post infection (dpi) then infected intravaginally (IVAG) with Chlamydia muridarum. Chlamydia 16S ribosomal (r)RNA expression was quantified in uterine and ovary/oviduct tissues via qPCR at 3, 7, 14, 21, 30, and 42dpi to characterise the kinetics of infection in the upper RT during progesterone and oestradiol dominance. Chlamydia 16S expression was normalised against expression of the housekeeping gene control, hypoxanthine-guanine phosphoribosyltransferase (HPRT). All data are presented as mean±SEM. *=p<0.05, **=p<0.01.

312 A B C

2.5× 10 3 1.5× 10 7 0.6

2.0× 10 3

1.0× 10 7 0.4 1.5× 10 3 (ng/mL)

1.0× 10 3 γ 5.0× 10 6 0.2 IFN 5.0× 10 2 IgG1 (ELISA Units) (ELISA IgG1 IgG 2a (ELISA U nits)

0 0 0.0

-/- -/- -/- WT ε WT ε WT ε IFN IFN IFN sFigure 2.3: Interferon (IFN)ε deficiency does not alter Chlamydia-specific serum immunoglobulin (Ig)G1 or IgG2a levels or lymph node IFNγ production at 30 days post infection (dpi). Wild-type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7dpi then infected intravaginally (IVAG) with Chlamydia muridarum. Chlamydia-specific serum IgG1 (A) and IgG2a (B) levels and caudal/lumbar lymph node IFNγ release upon restimulation with Chlamydia major outer membrane protein (MOMP; C) was quantified via ELISA at 30dpi to assess the effect of IFNε deficiency on Chlamydia-specific adaptive immune responses. All data are presented as mean±SEM.

313 Appendix C: Chapter 3 supplementary data

A B C D

6 *** 0.020 0.4 0.15 *** *** ** 0.015 0.3 **** **** 4 0.10

0.010 0.2 ***

2 0.05 NK (%) Cells 0.005 0.1 ImmatureNK (%) Cells Precursor NK Cells (%) NK Precursor Cells 0 0.000 0.0 0.00 Mature (CD11b+) NK Cells (CD11b+) (%)NKMature Cells -/- -/- -/- -/- ε ε ε ε

Serum IFN Serum IFN Serum IFN Serum IFN

A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1

E F G H

2 * 2.5× 10 6 8.0× 10 0.0648 2.0× 10 4 6.0× 10 3 ** ** **** 6 2.0× 10 **** 2 × 4 6.0 10 1.5× 10 *** 4.0× 10 3 1.5× 10 6 ** 2 4.0× 10 1.0× 10 4 1.0× 10 6 ***

NK Cells *** 2.0× 10 3 2 2.0× 10 5.0× 10 3 5.0× 10 5 Im m ature N K C ells Precursor N K C ells

0 0 0 Mature (CD11b+) NK Cells 0

-/- -/- -/- -/- ε ε ε ε

Serum IFN Serum IFN Serum IFN Serum IFN

A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1

sFigure 3.1: Systemic natural killer (NK) cell depletion post infection reduces the number of NK cells present in the spleen and bone marrow but does not affect NK cell precursors. Wild-type (WT) and interferon (IFN)ε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and administered anti-asialo GM1 (ASGM1) antibody (WT only) or normal rabbit serum (WT and IFNε-/-) intraperitoneally (IP) at 1 and 2dpi. Mice were infected intravaginally (IVAG) with Chlamydia muridarum. Percentages (of viable cells) and total numbers of circulating NK cells in spleen homogenates (A & E) and precursor (B & F), immature (C & G), and mature (D & H) NK cells in bone marrow from the femur were quantified via flow cytometry at 3dpi to compare the effects of systemic NK cell depletion and IFNε deficiency on the different populations of NK cells systemically. All data are presented as mean±SEM. *=p<0.05; **=p<0.01; ***=p<0.001; ****=p<0.0001.

314 A B C D

8 0.010 0.20 0.08

0.008 6 0.15 0.06

0.006 4 0.10 0.04 **** 0.004 **** NK (%) Cells 2 0.05 0.02 0.002 ImmatureNK (%) Cells Precursor NK Cells (%) NK Precursor Cells 0 0.000 0.00 0.00 **** Mature (CD11b+) NK Cells (CD11b+) (%)NKMature Cells

Serum Serum Serum Serum A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1

E F G H

2.0× 10 6 800 10000 4000

8000 1.5× 10 6 600 3000

6000 1.0× 10 6 400 *** 2000 4000 NK Cells **** 5.0× 10 5 200 1000 2000 Im m ature N K C ells Precursor N K C ells

0 0 0 Mature (CD11b+) NK Cells 0 ****

Serum Serum Serum Serum A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 A nti-A SG M 1 sFigure 3.2: Systemic natural killer (NK) cell depletion prior to infection reduces the number of NK cells present in the spleen and bone marrow but does not affect NK cell precursors. Wild-type (WT) C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and administered anti-asialo GM1 (ASGM1) antibody or normal rabbit serum intraperitoneally (IP) at -2, 0 and 2dpi. Mice were infected intravaginally (IVAG) with Chlamydia muridarum. Percentages (of viable cells) and total numbers of circulating NK cells in spleen homogenates (A & E) and precursor (B & F), immature (C & G), and mature (D & H) NK cells in bone marrow from the femur were quantified via flow cytometry at 3dpi to assess the effects of systemic NK cell depletion on the different populations of NK cells systemically. All data are presented as mean±SEM. ***=p<0.001; ****=p<0.0001.

315 WT IFNε-/- A B

C D

E F

sFigure 3.3: Representative flow cytometric plots of natural killer (NK) cell populations in the reproductive tracts (RTs) of wild-type (WT) and interferon (IFN)ε-/- mice during Chlamydia infection. WT and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum. The numbers of conventional NK cells (FSClow-int SSClow CD45+ CD3- NK1.1+; A & B), uterine (u)NK cells (FSClow-int SSClow CD45+ CD3- NK1.1- CD49b- CD122+; C & D), and IFNγ+/- CD69+/- NK cells (E & F) present in uterine tissues were quantified via flow cytometry at 3dpi to assess the effect of IFNε deficiency on NK cell numbers and activation in the upper RT. Images are representative of results from three experiments, n≥15 replicates of pooled uterine homogenate samples.

316 A B

WT NK cells WT T cells IFNε-/- NK cells IFNε-/- T cells

C WT Leukocytes IFNε-/- Leukocytes

sFigure 3.4: Interferon (IFN)ε deficiency decreases IFNγ production by natural killer (NK) cells, T cells, and total leukocytes in the female reproductive tract (RT) during Chlamydia infection. Wild- type (WT) and IFNε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum. Expression of IFNγ by NK cells (A), T cells (B), and total leukocytes (C) in uterine tissues was assessed via intracellular cytokine staining and flow cytometry at 3dpi to determine the effect of IFNε deficiency on IFNγ production by immune cells in the upper RT. Blue histograms represent raw counts of each cell type from WT mice and green histograms represent raw counts of each cell type from IFNε-/- mice. Images are representative of results from three experiments, n≥15 replicates of pooled uterine homogenate samples.

317 Serum Anti-ASGM1 IFNε-/- A B C

D E

sFigure 3.5: Systemic natural killer (NK) cell depletion post infection reduces, while depletion prior to infection increases, the number of NK cells present in the upper reproductive tract (RT) during Chlamydia infection. Wild-type (WT) and interferon (IFN)ε-/- C57BL/6 mice were pre-treated with progesterone subcutaneously (SC) at -7 days post infection (dpi) and infected intravaginally (IVAG) with Chlamydia muridarum. Mice were administered anti-asialo GM1 (ASGM1) antibody (WT only; B & E) or normal rabbit serum (WT and IFNε-/-; A, D, & C) intraperitoneally (IP) at 1 and 2dpi (depletion post infection; A-C) or -2, 0, and 2dpi (depletion prior to and throughout infection; D & E). The numbers of conventional NK cells (FSClow-int SSClow CD45+ CD3- NK1.1+) present in uterine tissues were quantified via flow cytometry at 3dpi to compare the effects of different regimes of systemic NK cell depletion on NK cell populations in the upper RT with those of IFNε deficiency. Images are representative of results from one experiments, n≥4 replicates of pooled uterine homogenate samples.

318