The Role of Nuclear (PGR) in Regulating Expression, Morphology and Function in the and Oviduct during the Periovulatory Period

Lisa Kathleen Akison

Research Centre for Reproductive Health Robinson Institute Discipline of Obstetrics & Gynaecology School of Paediatrics & Reproductive Health University of Adelaide Adelaide, Australia

Thesis submitted to the University of Adelaide in fulfilment of the requirements for admission to the degree of Doctor of Philosophy October, 2012

“The mystery of nature in the wonderful operation of animal reproduction has from the earliest period courted the attention of physiologists, and though experiment and imagination have toiled and fancied through all the ages, and opinions have been various and ingenious, the present day still finds the subject unconcluded.”

Pulley, J. (1801). An essay on the proximate cause of animal impregnation; being the substance of a paper read and discussed in the medical society at Guy’s Hospital, in October 1799. London

More than 200 years later...

“The overwhelming impression is that the molecular events of ovulation are far more complex...than originally imagined.”

Espey, L. L. & Richards, J. S. (2002). Temporal and spatial patterns of ovarian gene transcription following an ovulatory dose of gonadotropin in the rat. Biology of Reproduction 67:1667.

i Table of Contents

Abstract ...... v

Thesis declaration:...... vii

Acknowledgements...... viii

List of Figures ...... ix

List of Tables ...... xi

List of Appendices ...... xii

Abbreviations ...... xiii

Chapter 1 – Literature review & introduction to thesis ...... 1 1.1 Introduction ...... 1 1.2 Structure and function of the ovary...... 1 1.2.1 Physiological events in the ovulating follicle ...... 2 1.2.2 Regulators of ovulation ...... 7 1.3 Structure and function of the oviduct ...... 24 1.3.1 Structure of the mammalian oviduct ...... 24 1.3.2 Functions of the oviduct...... 28 1.3.3 Paracrine communication by COCs and embryos with the oviduct ...... 37 1.3.4 Oviductal structure and function – remaining questions ...... 38 1.4 Progesterone & (PGR) ...... 40 1.4.1 PGR knockout mouse models ...... 43 1.5 PGR in the ovary ...... 44 1.5.1 Hormonally regulated expression of PGR in the ovary ...... 44 1.5.2 PGR expression in the rodent ovary ...... 45 1.5.3 PGR expression in primate and ovary ...... 47 1.5.4 Functional roles of PGR in the ovary ...... 47 1.5.5 Peri-ovulatory regulated by PGR ...... 53 1.6 PGR in the oviduct ...... 59 1.6.1 PGR expression in the oviduct ...... 60 1.6.2 The role of PGR in regulating oviductal function ...... 62 1.7 Hypotheses & aims of project ...... 65 1.7.1 Main hypothesis ...... 65 1.7.2 Specific hypotheses & aims ...... 65

Lisa Akison 2012 ii Chapter 2 – Materials & Methods ...... 70 2.1 Animals, treatments & tissue collection ...... 70 2.1.1 Animal strains and housing ...... 70 2.1.2 Hormone treatments ...... 70 2.1.3 PRlacZ transgenic mouse genotyping ...... 73 2.1.4 Preliminary verification of the PRKO phenotype...... 73 2.1.5 Isolation of COCs, granulosa cells and whole tissue collection ...... 76 2.2 Gel electrophoresis ...... 76 2.3 RNA extraction & purification ...... 79 2.4 Real time RT-PCR...... 79 2.5 Microarray ...... 81 2.5.1 Microarray sample preparation, hybridisation and scanning ...... 81 2.5.2 Microarray data analysis...... 82 2.6 Histology ...... 83 2.6.1 Tissue preparation and sectioning ...... 83 2.6.2 H & E staining and image capture ...... 83 2.7 Immunohistochemistry ...... 84 2.8 Real-time cell adhesion assays ...... 84 2.9 Real-time cell migration and invasion assays ...... 85 2.10 Statistical analyses ...... 85 2.11 Solutions ...... 86

Chapter 3 – Phenotype of the PRKO ovary at the time of ovulation ...... 88 3.1 Introduction ...... 88 3.2 Materials & Methods...... 91 3.2.1 Tissue collection & histology ...... 91 3.2.2 Ovarian transplants ...... 91 3.3 Results ...... 94 3.3.1 Ovarian histology ...... 94 3.3.2 Cumulus expansion in PRKO COCs ...... 100 3.3.3 Ovarian transplants ...... 100 3.4 Discussion ...... 108

Chapter 4 – PGR-regulated immune genes in the ovary ...... 112 4.1 Introduction ...... 112 4.2 Materials & Methods...... 118 4.2.1 Animals, tissue collection and RNA extraction ...... 118 4.2.2 Taqman Low Density Arrays ...... 119

Lisa Akison 2012 iii 4.2.3 Real-time PCR ...... 120 4.2.4 Immunohistochemistry...... 120 4.2.5 Statistical analyses ...... 121 4.3 Results ...... 121 4.3.1 Taqman Low Density Immune Arrays ...... 121 4.3.2 Ptgs2 mRNA expression ...... 125 4.3.3 PTGS2 immunohistochemistry ...... 125 4.4 Discussion ...... 130

Chapter 5 – PGR-regulated genes in granulosa cells of periovulatory follicles...... 139 5.1 Introduction ...... 139 5.1.1 The CXCL12/CXCR4 chemotactic signalling axis ...... 140 5.2 Materials & Methods...... 142 5.2.1 Tissue collection, RNA extraction and quality control ...... 142 5.2.2 Microarray sample preparation, array hybridisation, scanning and analysis ...... 142 5.2.3 Real-time PCR ...... 143 5.2.4 Immunohistochemistry...... 144 5.2.5 In vivo inhibition of CXCR4 by AMD3100 ...... 144 5.2.6 Statistical analyses ...... 144 5.3 Results ...... 145 5.3.1 Granulosa Cell Microarray ...... 145 5.3.2 Cxcr4 mRNA expression ...... 154 5.3.3 CXCR4 immunohistochemistry ...... 154 5.3.4 CXCR4 inhibitor, AMD3100, does not block ovulation in vivo ...... 161 5.4 Discussion ...... 161

Chapter 6 – Characterisation of the periovulatory cumulus oocyte complex and impact of PGR on structure and function ...... 171 6.1 Introduction ...... 171 6.2 Materials & Methods...... 174 6.2.1 Animals, hormonal stimulation and tissue collection ...... 174 6.2.2 Breast cell lines...... 174 6.2.3 RNA extraction and microarray analysis ...... 175 6.2.4 In vitro real-time cell adhesion, migration and invasion assays ...... 175

6.2.5 Prostaglandin E2 assay as a measure of cumulus matrix integrity...... 176 6.2.6 JC-1 staining of oocytes as a measure of mitochondrial membrane potential ...... 177 6.2.7 Statistical analyses ...... 178 6.3 Results ...... 178 6.3.1 COC Adhesion to ECM ...... 178 Lisa Akison 2012 iv 6.3.2 Migratory phenotype of COCs ...... 180 6.3.3 Invasion of preovulatory COCs through an ECM ...... 180 6.3.4 Cumulus Cell Microarray ...... 184 6.3.5 Is adhesion, migration, and invasion by PRKO pre-ovulatory COCs defective? ...... 188

6.3.6 Integrity of the matrix in PRKO COCs may be perturbed: a bioassay using PGE2 production . 190 6.3.7 Mitochondrial membrane potential is altered in PRKO oocytes ...... 194 6.4 Discussion ...... 194

Chapter 7 – PGR regulation of oviduct structure and function ...... 203 7.1 Introduction ...... 203 7.2 Materials & Methods...... 204 7.2.1 Animals and tissue collection ...... 204 7.2.2 Histology ...... 205 7.2.3 RNA extraction and quality control ...... 205 7.2.4 Microarray sample preparation, array hybridisation, scanning and analysis ...... 205 7.2.5 Real-time PCR ...... 206 7.3 Results ...... 207 7.3.1 PGR mRNA expression in the oviduct during the periovulatory period ...... 207 7.3.2 Oviductal histology ...... 207 7.3.3 Oviduct microarray ...... 207 7.3.4 Validation of PGR target genes in the oviduct ...... 219 7.4 Discussion ...... 227

Chapter 8 – Conclusions & future research directions ...... 234 8.1 Introduction ...... 234 8.2 Thesis conclusions ...... 235 8.2.1 PGR regulation of ovarian structure and function ...... 235 8.2.2 PGR regulation of oviductal structure and function ...... 238 8.3 Future research directions ...... 239 8.4 Significance of results ...... 242

Appendices ...... 244

References ...... 275

Lisa Akison 2012 v Abstract

Ovulation requires sequential molecular events and structural remodelling in the for the successful release of a mature oocyte into the oviduct. Critical to this process is progesterone receptor (PGR), a highly yet transiently expressed in granulosa cells (GC) of preovulatory follicles and abundant in the oviduct. Progesterone receptor knockout (PRKO) mice are anovulatory, with a specific and complete defect in follicle rupture. Therefore, this model was used to examine the critical molecular and biochemical mechanisms necessary for successful ovulation. Progesterone is known to affect oviductal cells in vitro, but how PGR regulates oviductal structure and function is poorly understood. A systematic evaluation of ovarian and oviductal morphology during the periovulatory period revealed no structural defects in PRKO mice relative to heterozygous (PR+/-) littermates. However, in response to the LH surge/hCG treatment, ovulation only occurred in PR+/- , with numerous corpora lutea observed and cumulus oocyte complexes (COCs) in oviducts, while PRKO ovaries did not ovulate and showed entrapped COCs within large, luteinising follicles. Transplantation of PRKO ovaries into wild-type mice (PRWT) did not rescue the infertility phenotype. Therefore, although PGR is expressed in other tissues, ovarian PGR is essential for ovulation.

Further experiments identified PGR-regulated processes at multiple levels. In whole ovaries 10 h post- hCG, inflammatory genes were disrupted in PRKO mice, including cytokines, endothelial adhesion factors, vasoconstrictors, T-cell antigens, and the prostaglandin synthase, Ptgs2. In GCs and COCs isolated 8 h post-hCG, microarray analyses identified 296 and 44 differentially expressed genes respectively between PRKO and PR+/- samples. analysis revealed associations with the processes of proteolysis, vascular remodelling/angiogenesis, inflammatory responses, cell adhesion, migration and invasion. The latter three processes were characterised in periovulatory COCs using in vitro assays and were shown to be transiently activated, peaking at ovulation then declining dramatically in COCs collected from the oviduct immediately post-ovulation. However, periovulatory PRKO and PR+/- COCs showed similar rates of adhesion, migration and invasion in the presence of collagen I. Upregulation of the chemokine receptor, Cxcr4, by LH/hCG via PGR in both GCs and COCs was validated by RT-PCR and immunohistochemistry. Mitochondrial membrane potential was altered in PRKO oocytes compared to PR+/- and therefore their developmental potential may be reduced.

Further, a bioassay measuring retention of prostaglandin (PGE2) within the matrix of expanded COCs suggested that the matrix integrity of PRKO COCs may be compromised. Therefore, PGR in granulosa cells appears to have down-stream impacts on COCs.

In oviducts, microarray analysis comparing in PRKO and PR+/- mice 8 h post-hCG, when P4 levels are high, identified 1003 PGR-regulated genes. Gene ontology analysis identified

Lisa Akison 2012 vi significant associations with the functions of cell adhesion, migration, invasion, chemotaxis, muscle contraction and vasoconstriction. Several genes were confirmed to be PGR-regulated by RT-PCR (Adamts1, Itga8 and Edn3) and were induced by LH/hCG.

Therefore, the identification of novel gene targets for PGR regulation in the ovary and oviduct exposes several new, down-stream influences of PGR on , the COC and oviductal function, highlighting the essential role of PGR as master regulator in the ovary and oviduct during the periovulatory period.

Lisa Akison 2012 vii Thesis declaration:

I certify that this work 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. In addition, I certify that no part of this work will, in the future, be used in a submission for any other degree or diploma in any university or other tertiary institution without the prior approval of the University of Adelaide and where applicable, any partner institution responsible for the joint-award of this degree.

I give consent to this copy of my thesis, when deposited in the University Library, being made available for loan and photocopying, subject to the provisions of the Copyright Act, 1968. I also give permission for the digital version of my thesis to be made available on the web via the University’s digital research repository, the Library catalogue, the Australasian Digital Theses Program (ADTP) and also through web search engines, unless permission has been granted by the University to restrict access for a period of time.

The author acknowledges that copyright of published works contained within this thesis (as listed below) resides with the copyright holder(s) of those works. The following papers have been published from this work:

Robker, R.L., Akison, L.K. & Russell, D.L. (2009). Control of oocyte release by Progesterone Receptor-regulated gene expression. Signaling 7, 1-12.

Akison, L.K.*, Alvino, E.*, Dunning, K.R. Robker, R.L. & Russell, D.L. (2012). Transient invasive migration in mouse cumulus oocyte complexes induced at ovulation by luteinizing hormone. Biology of Reproduction 86 (4), 125, 1-8. * Both authors contributed equally to this work.

Akison, L.K. & Robker, R.L. (2012). The critical roles of progesterone receptor (PGR) in ovulation, oocyte developmental competence and oviductal transport in mammalian reproduction. Reproduction in Domestic Animals 47 (Supplement 4), 288-296.

 Lisa K. Akison October, 2012

Lisa Akison 2012 viii Acknowledgements

There are many people to thank for all their help and support during such a mammoth undertaking as a PhD! First, I would like to thank my primary supervisor, Becky Robker, for her expertise, patience, drive and friendship. You are the most accomplished multi-tasker I know and amazingly good at making my rising panic subside! Massive thanks also to Darryl Russell for your constructive criticism, your technical expertise and your desire for great cutting-edge equipment! Both Becky and Darryl were incredibly encouraging and patient during the ‘write-up’ phase and I will always be grateful for that. Thanks also go to Rob Norman for his support, encouragement and faith in my abilities.

Thank you also to the many people who provided technical assistance/expertise: Sandie Piltz for assistance with ovarian transplant surgeries; Emily Alvino, Kylie Dunning, Brenton Bennett, Kara Cashman, Laura Watson, Becky and Darryl for assistance with collection of cells and tissues for time series and migration/adhesion/invasion assays, often at odd hours; Kate Frewin, Brenton and Laura for Nanozooming slides; Kate for teaching me how to set up plates for the RTCA and for assistance with cancer cell lines, Low Density Arrays and tissue processing; Laura for advice on immuno, Ptgs2 primer design and tissue processing; Katja Hummitzsch for instructions on taking high power images of the oviducts; and Kylie for assistance with JC-1 staining (with Linda Wu), the PGE2 ELISA, and general excellent advice on all lab stuff. Laboratory Animal Services staff – primarily Pacita Wissell, Sarah Fisher and Faye Gardner – supplied C57Bl/6 and CBAF1 mice and maintained the PRlacZ mouse colony. Adelaide Microarray Centre staff, Mark van der Hoek and Rosalie Kenyon, processed the arrays and conducted the initial analysis of raw data. Chris Leigh & Gail Hermanis from Histology Services, Discipline of Anatomy and Pathology, processed, embedded, sectioned and stained much of the tissue used in the morphological analysis.

Thank you to the following members of the Ovarian Cell Biology Lab, past and present, for your friendship and support during the past four years – Kylie, Laura, Jamie, Linda, Brenton, Emily, Kate, Xing, Nok and Kara.

Funding support was provided by the National Health and Medical Research Council (NHMRC), Healthy Development Adelaide (HDA), The Research Centre for Reproductive Health and the Robinson Institute.

Finally, thank you to my friends and family for your encouragement and support and apologies for my absence and preoccupation. In particular, my husband, Adrian, and my children, Mia, Xander and Sasha – I thank you for your love, support and total belief in me and I dedicate this thesis to you.

Lisa Akison 2012 ix List of Figures

Figure 1.1 Follicle growth and maturation in the ovary...... 4 Figure 1.2 Steroid production in somatic cells of ovarian follicles...... 6 Figure 1.3 Major processes involved in ovulation...... 10 Figure 1.4 Periovulatory regulation of gene transcription in granulosa cells...... 11 Figure 1.5 Follicle wall structural changes immediately prior to ovulation...... 13 Figure 1.6 Preliminary report of adhesion, migration & invasion by cumulus cells...... 19 Figure 1.7 The structure of the oviduct in the mouse...... 25 Figure 1.8 Cellular structure of the oviduct...... 26 Figure 1.9 Putative factors involved in fertilisation and oviductal transport...... 39 Figure 1.10 The structure of the two PGR isoforms – PGR-A and PGR-B...... 41 Figure 1.11 PGR is highly expressed in the ovary during the preovulatory period...... 46 Figure 1.12 The ovarian phenotype of the PGR knockout (PRKO) mouse...... 49 Figure 1.13 Genes regulated by PGR in the ovary which are known to be important for ovulation. . 55 Figure 1.14 PGR expression in the oviduct luminal epithelium...... 61 Figure 2.1 Creation of the PRlacZ mouse and targeted disruption of the mouse PGR gene...... 71 Figure 2.2 Timing of ovulation in eCG + hCG stimulated CBA X C57Bl/6 (F1) female mice...... 72 Figure 2.3 PCR products for genotyping PGR transgenic mice...... 74 Figure 2.4 Histology of PRKO and PR+/- mouse ovaries at 24 h post-hCG...... 75 Figure 2.5 Breeding performance of PRKO and PR+/- mice...... 77 Figure 2.6 Morphology of COCs following exposure to hCG in vivo...... 78 Figure 3.1 Ovarian transplant surgical protocol and experimental design...... 93 Figure 3.2 Ovarian histology appears normal in PRKO mice until 12 h post-hCG...... 99 Figure 3.3 Basal invagination occurs in PRKO follicles at 12 h post-hCG...... 101 Figure 3.4 PRKO and PR+/- COCs show the same degree of expansion at 10 h post-hCG...... 102 Figure 3.5 Recipient female with transplanted ovary in situ...... 103 Figure 3.6 PRKO ovaries transplanted into PRWT females remain anovulatory...... 104 Figure 3.7 PRKO transplant ovaries had more anovulatory follicles than PRWT...... 106 Figure 3.8 Function was not restored to PRKO ovaries transplanted into PRWT females...... 107 Figure 4.1 Ovulation is likened to an inflammatory reaction...... 113 Figure 4.2 Fewer neutrophils are present in PRKO ovaries...... 115 Figure 4.3 Endogenous control gene expression in 10 h post-hCG ovary samples...... 122 Figure 4.4 PGR regulates immune genes in the periovulatory ovary...... 124 Figure 4.5 Ptgs2 expression in PR+/- and PRKO ovaries, COCs and granulosa cells...... 126

Lisa Akison 2012 x Figure 4.6 PTGS2 protein localisation is similar in PRKO and PR+/- ovaries...... 129 Figure 4.7 PGR regulation of immune genes in the periovulatory ovary...... 131 Figure 5.1 Principle Component Analysis plots for granulosa cell microarray samples...... 146 Figure 5.2 Volcano plot of granulosa cell microarray data...... 147 Figure 5.3 Cxcr4 mRNA is induced by hCG in COCs and granulosa cells...... 155 Figure 5.4 Cxcr4 is down-regulated in PRKO GCs and COCs during the periovulatory period. ... 156 Figure 5.5 CXCR4 protein is detected in ovaries and oviducts from PR+/- mice...... 160 Figure 5.6 The CXCR4 inhibitor, AMD3100, does not reduce ovulation rate in vivo...... 162 Figure 6.1 Adhesion of COCs to ECM substrates is dynamic across the periovulatory window. .. 179 Figure 6.2 The migratory phenotype of COCs is temporally regulated...... 181 Figure 6.3 Preovulatory expanded COCs are as invasive as two known invasive cell lines...... 183 Figure 6.4 Principle Component Analysis plots for COC microarray samples...... 185 Figure 6.5 Volcano plot of COC microarray data...... 186 Figure 6.6 PRKO COCs show migratory capacity comparable to PR+/- COCs...... 189 Figure 6.7 PRKO COCs are as adhesive to collagen I as PR+/- COCs...... 191 Figure 6.8 PRKO COCs are as invasive through collagen I as PR+/- COCs...... 192

Figure 6.9 PRKO COCs lose more PGE2 to the media than PR+/- COCs...... 193 Figure 6.10 Oocyte mitochondrial membrane potential is altered in PRKO COCs...... 195 Figure 7.1 Pgr mRNA is stably expressed in the oviduct during the periovulatory period...... 208 Figure 7.2 Oviductal histology appears normal in PRKO mice...... 213 Figure 7.3 Cells of the luminal epithelium appear normal in PRKO oviducts...... 216 Figure 7.4 Principle Components Analysis plots for oviduct microarray samples...... 217 Figure 7.5 Volcano plot of oviduct microarray data...... 218 Figure 7.6 RT-PCR validation of putative PGR-regulated genes in the oviduct...... 225 Figure 7.7 A subset of PGR-regulated genes in the oviduct are also induced by hCG...... 226 Figure 7.8 PGR regulation of gene pathways potentially involved in oviductal transport...... 233 Figure 8.1 PGR regulates multiple processes in periovulatory ovaries and oviducts...... 236

Lisa Akison 2012 xi List of Tables

Table 1.1 Major products present, expressed and/or secreted by the mammalian oviduct...... 33 Table 1.2 PGR-regulated genes in the ovary...... 54 Table 2.1 Progesterone receptor transgenic mouse genotyping PCR reaction...... 74 Table 2.2 Primers used throughout thesis for real-time PCR validation of gene expression...... 80 Table 4.1 Differentially expressed immune genes in whole ovaries at 10 h post-hCG...... 132 Table 5.1 Differentially expressed genes in PRKO granulosa cells associated with cell migration/movement, chemotaxis or cell invasion...... 148 Table 5.2 Differentially expressed genes in PRKO granulosa cells associated with adhesion, cell-to- cell contact and cell binding...... 150 Table 5.3 Differentially expressed genes in PRKO granulosa cells associated with immune responses and immune cell trafficking...... 151 Table 5.4 Differentially expressed genes in PRKO granulosa cells associated with vascular remodelling, angiogenesis or formation of blood vessels...... 152 Table 5.5 Differentially expressed proteases in PRKO granulosa cells...... 153 Table 6.1 Genes differentially expressed in PRKO and PR+/- COCs from microarray analysis...... 187 Table 7.1 50 most differentially expressed genes in PRKO versus PR+/- oviducts...... 220 Table 7.2 Differentially expressed genes in PRKO oviducts associated with the functions of adhesion, attachment or binding of cells...... 221 Table 7.3 Differentially expressed genes in PRKO oviducts associated with the functions of cell movement, migration, chemotaxis or invasion...... 222 Table 7.4 Differentially expressed genes in PRKO oviducts associated with the functions of vasoconstriction and/or muscle contraction...... 223

Lisa Akison 2012 xii List of Appendices

Appendix 1 Complete gene information for the Taqman Low Density Immune Array (Mouse)...... 244 Appendix 2 Samples used for the microarray analyses...... 247 Appendix 3 List of differentially expressed genes (P<0.05) from the granulosa cell microarray. .... 250 Appendix 4 Housekeeper gene expression across samples used in RT-PCR time series...... 259 Appendix 5 Experiments testing the potential role of the oviduct in stimulating COC migration. .... 261 Appendix 6 List of differentially expressed genes (P<0.01 only) from the oviduct microarray...... 267

Lisa Akison 2012 xiii Abbreviations

m: mitochondrial membrane potential AC: adenylate cyclise ACTB: actin, beta ACTG2: actin, gamma 2, smooth muscle, enteric ADAMTS1: ADAM metallopeptidase with thrombospondin type 1 motif, 1 AGTII: angiotension II AGTR: angiotensin II receptor AMH: anti-Mullerian hormone MEM: minimum essential medium, alpha ANGPT: angiopoietin ANOVA: analysis of variance AREG: amphiregulin BAX: BCL2-associated X protein bp: base pairs BSA: bovine serum albumin C3, C7: complement 3 and 7 cAMP: cyclic monophosphate CBF: cilia beat frequency CC: cumulus cells CCR4: chemokine (C-C motif) receptor 4 cDNA: complementary DNA C/EBPβ: CCAAT enhancer binding protein β CL: COC: cumulus oocyte complex Coll: collagen CREB: cAMP response element binding protein CT: cycle threshold CXCL12: chemokine (C-X-C motif) ligand 12 (previously known as SDF1) CXCR4: chemokine (C-X-C motif) receptor 4 DES: desmin DNA: deoxyribonucleic acid dNTP: deoxyribonucleotide E2: estradiol

Lisa Akison 2012 xiv ECE1: endothelin converting 1 eCG: equine chorionic gonadotrophin ECM: extracellular matrix EDN: endothelin EFNB2: ephrin B2 EGF: epidermal EGF-L: -like EPAS1: endothelial PAS domain protein 1 (previously known as HIF2) EREG: epiregulin ERK: extracellular signal-regulated kinase EtOH: ethanol F1: first filial FCS: fetal calf serum FSH: follicle stimulating hormone FN: fibronectin GC: granulosa cell GVBD: germinal vesicle breakdown GM-CSF: colony stimulating factor 2 (granulocyte-macrophage) h: hour HA: hyaluronan hCG: human chorionic gonadotropin H & E: haematoxylin and eosin HIF: hypoxia inducible factor HMOX1: heme oxygenase (decycling) 1 IL: interleukin ILCL: interstitial Cajal-like cells IFN: interferon i.p.: intraperitoneal IPA: Ingenuity Pathway Analysis ITG: integrin IU: international units IVF: in vitro fertilisation IVM: in vitro maturation KO: knockout Lam: laminin LH: luteinising hormone Lisa Akison 2012 xv LHCGR: luteinising hormone/choriogonadotrophin receptor MAPK: mitogen-activated protein kinase min: minute MMP: matrix metalloproteinase mPR: membrane progestin receptor mRNA: messenger ribonucleic acid MYOCD: myocardin NFKB2: nuclear factor of kappa polypeptide gene enhancer in B-cells 2 NO: nitric oxide OSF: oocyte secreted factor OVGP1: oviductal 1 (previously known as MUC9) P4: progesterone PA: plasminogen activator PAF: activating factor PAPPA: pregnancy-associated plasma protein A PBS: phosphate buffered saline PBST: phosphate buffered saline + Tween-20 PCA: principal component analysis PCR: polymerase chain reaction PG: prostaglandin PKA: protein kinase A PPARγ: peroxisome proliferator-activated receptor gamma PGR: progesterone receptor PGRMC1: progesterone receptor membrane component 1 PRE: progesterone response element PRKO: progesterone receptor knockout PRLR: prolactin receptor PRWT: progesterone receptor wild-type PTGS2: prostaglandin-endoperoxide synthase 2 (previously known as COX2) RGMB: RGM domain family, member B RNA: ribonucleic acid RIN: RNA integrity number RPL19: ribosomal protein L19 RTCA: real time cell analysis RT-PCR: reverse transcription polymerase chain reaction RUNX1/2: runt related transcription factor 1 & 2 Lisa Akison 2012 xvi SE: standard error SELE: E SFM: serum free medium SMC: smooth muscle cell SOCS: suppressor of cytokine signaling SP1/3: specificity protein 1/3 SPHK1: sphingosine kinase 1 STAT: signal transducer and activator of transcription TBE: tris borate EDTA TGF: transforming growth factor TN: tenascin VCAN: versican VEGF: vascular endothelial growth factor VN: vitronectin ZBTB16: and BTB domain containing 16 (previously known as PLZF)

Lisa Akison 2012 1 Chapter 1 – Literature review & introduction to thesis

1.1 Introduction

Despite the ubiquity and fundamental necessity of reproduction, many of the critical biological processes required for its success are still not entirely understood. To successfully manage fertility requires a thorough understanding of these processes and the mechanisms underlying them. Fertility management includes optimising reproductive success of commercially desirable or threatened species; preventing reproduction using contraceptive methods; or treatment for infertility. In , infertility affects 1 in 6 couples [Hull et al., 1985] and anovulation has been identified as a major cause of this infertility [Overbeek and Lambalk, 2009]. In a recent study on an Australian cohort of 657 women aged 30-32 years who sought pregnancy, 24% reported difficulty becoming pregnant and of these, 16% were due to anovulation [Marino et al., 2011]. Perhaps ironically, there is also an urgent need for the development of safe, effective and reversible contraceptives with more than 100 million women reliant on current hormonal contraceptives to control or prevent ovulation [Trussell, 2007]. Thus, given the challenges for successful fertility management, an understanding of the processes regulating ovulation and subsequent early embryo development and transport is imperative.

Thus, the over-arching goal of this thesis is to develop a greater understanding of the molecular processes regulating successful mammalian ovulation and subsequent transport of the oocyte and early embryo.

The ovaries and oviducts or Fallopian tubes are the pivotal organs involved at this early stage of female reproduction and fertility. They are inextricably linked due to their close physical proximity, particularly in the mouse where they are connected by the bursal membrane that encases the ovary and the infundibula opening to the oviduct. However, common to all mammalian species, their functional reliance on each other is profound. The following sections describe the structure and function of both the ovary and oviduct in mammals, with particular emphasis on humans and rodents.

1.2 Structure and function of the ovary

The two main functions of the ovary are the production of reproductive that synchronise the reproductive cycle and the growth and nourishment of oocytes capable of fertilisation and development into live offspring. Both processes occur within ovarian follicles. Lisa Akison 2012 2

1.2.1 Physiological events in the ovulating follicle

Ovarian follicle development occurs as a highly orchestrated series of developmental stages referred to as , which culminates in the release of a mature and developmentally competent oocyte at ovulation (Figure 1.1). The physiological events characterising folliculogenesis have been well characterised (see [Edson et al., 2009; Greenwald and Roy, 1994; Hunter, 2003; Johnson, 2007] for detailed descriptions from which much of the following summary has been adapted).

Primordial follicles are formed in the neonatal ovary and are composed of an immature oocyte surrounded by a single layer of squamous somatic cells, or pre-granulosa cells, and segregated from the ovarian environment by the basal lamina. Primordial follicles are recruited and activated to grow in response to signals that are still being elucidated but are likely to include anti-Mullerian hormone (AMH) and a number of pleiotrophic cytokines and growth factors (see [McLaughlin and McIver, 2009] for review).

The squamous pre-granulosa cells of primordial follicles change to the cuboidal structure of fully developed granulosa cells, marking the transition of the follicle stage from a primordial to a primary follicle (Figure 1.1). At this point, the also forms around the oocyte, separating it from the surrounding granulosa cells. Once activated, follicle growth and development are controlled first by paracrine growth factors and from the secondary stage, by the gonadotrophins follicle stimulating hormone (FSH) and luteinising hormone (LH), which are released from the anterior pituitary. Alternatively, follicle growth can be exogenously controlled by treatment with equine chorionic gonadotrophin (eCG). Theca cells are formed from stromal cells and surround the follicle’s basal lamina. This theca cell layer develops a network of capillary vessels that supplies factors from the blood supply to the growing follicle. As they acquire FSH responsiveness, follicles form a fluid-filled cavity or antrum adjacent to the oocyte, designating the antral stage of follicle development (Figure 1.1).

With antral formation, two distinct populations of granulosa cells diverge; cumulus cells that encase the oocyte, forming the cumulus oocyte complex (COC) and mural granulosa cells which line the follicle wall (Figure 1.1). The cumulus cells form a compact layer of between 1000 and 3000 cells [Salustri et al., 1992] which are connected to each other and the oocyte by gap junctions to allow bi-directional communication. Cumulus cell differentiation is driven by factors secreted by the oocyte (oocyte secreted factors or OSFs; see [Gilchrist et al., 2008] for review), to the surrounding granulosa cells. Bi- directional transport of regulatory molecules between the oocyte and cumulus cells is also critical for appropriate maturation of the oocyte prior to ovulation (see below).

Lisa Akison 2012

4

Figure 1.1 Follicle growth and maturation in the ovary. A) Primordial follicles are activated and under the control of paracrine factors (primary follicles) and basal levels of FSH and LH (secondary and pre-antral follicles) continue to grow and differentiate up to the antral stage. At this point, steroid production begins, producing an increase in estradiol that results in a surge of LH. This surge of LH acts on granulosa cells to initiate cumulus expansion in the COC, resumption of meiosis and acquisition of developmental competence by the oocyte, and culminates in the eventual release of the mature, expanded cumulus oocyte complex (COC) in a process termed ovulation. B) Structure of a preovulatory follicle.

Lisa Akison 2012 5 In antral follicles, steroid production begins in specific somatic cells (Figure 1.2). The theca cells are the first cells of the follicle to express LH receptors and respond to LH by synthesising androgens, supplying androstenedione to granulosa cells which, in the presence of FSH, express aromatase (CYP19), to convert androgen to estrogen (estradiol) [Liu and Hsueh, 1986; Moon et al., 1978]. This relationship between granulosa cells, theca cells, FSH and LH is known as the two-cell two- gonadotrophin hypothesis [Moon et al., 1978] (Figure 1.2). Granulosa cells in these antral follicles are acutely FSH and estrogen responsive [Richards, 1975, 1980] and thus in the presence of these hormones, rapid granulosa cell proliferation occurs [Rao et al., 1978; Robker and Richards, 1998a, b; Sicinski et al., 1996]. This causes a positive feedback which further enhances granulosa cell proliferation and results in a surge of estradiol (E2) towards the end of antral expansion. In response to rising E2 levels, the frequency and amplitude of LH pulses from the pituitary increases, producing a surge in circulating LH levels [Goodman and Karsch, 1980; Karsch, 1987]. This surge is required to initiate ovulation. E2 also acts on the pituitary to suppress FSH production late in the of the cycle. Therefore, follicles expressing high levels of E2 become FSH independent while less developed follicles become FSH-starved and die, thus providing a mechanism for the development of follicle dominance.

FSH stimulates the appearance of LH receptors (LHCGR), on mural granulosa cells [Eppig et al., 1997; Peng et al., 1991]. The mural cells then respond to the ovulatory LH surge (or treatment with human chorionic gonadotrophin or hCG) by ceasing proliferation and undergoing a process termed ‘luteinisation’ [Murphy, 2004; Richards, 1994; Richards et al., 1986]. This is a terminal differentiation whereby the cells become highly steroidogenic, synthesizing elevated progesterone (P4). Progesterone is widely recognized to be required for pregnancy maintenance but is also critical for successful ovulation. Granulosa cells produce a pulse of P4 immediately after the LH surge which is essential for ovulation. At the same time, the LH surge induces a cohort of EGF-like ligands in granulosa cells which act on the cumulus cells to initiate COC expansion and resumption of meiosis in the oocyte [Park et al., 2004]. It is only the fully mature oocyte that is capable of subsequent fertilisation (defined as oocyte developmental competence; see [Sun et al., 2009] for review). Once ovulation has occurred, luteinisation of the granulosa and theca cells continues and vascular invasion occurs to form a corpus luteum (Figure 1.1). This is a highly steroidogenic structure that is responsible for preparing the for embryo implantation and maintaining pregnancy.

In the unexpanded COC, the cumulus cells and the oocyte are intimately associated, with bi-directional communication occurring between these follicular compartments. Specific products synthesised in the cumulus cells, such as cyclic AMP and EGF-like peptides, transfer to the oocyte via gap junctions or

Lisa Akison 2012 6

Figure 1.2 Steroid production in somatic cells of ovarian follicles. Also known as the two-cell two-gonadotrophin hypothesis. (a) Theca cells in late preantral/early antral follicles produce androstenedione which is supplied to granulosa cells for conversion to estrogen (estradiol) in the presence of FSH and aromatase. Estrogen promotes granulosa cell proliferation, causing a surge in estrogens in the blood. (b) In preovulatory follicles, high estrogen levels combined with FSH cause LH receptors to appear on granulosa cells of pre-ovulatory follicles, allowing production of progesterone. Progesterone is critical for ovulation, as well as for pregnancy maintenance via the continued production of progesterone by the corpus luteum. Adapted from [Johnson, 2007].

Lisa Akison 2012 7 paracrine signalling and contribute to oocyte growth and maturation. At the same time, factors secreted from the oocyte (OSFs), such as growth differentiation factor 9 (GDF9) and bone morphogenetic protein 15 (BMP15), transfer to the surrounding cumulus cells via gap junctions, thus rendering them distinct from mural granulosa cells in function and structure (see [Gilchrist, 2011] for review of oocyte-somatic cell interactions). In the unexpanded COC, meiotic arrest is maintained in the oocyte via high levels of the gonadotrophin second messenger, cyclic (cAMP) [Bornslaeger et al., 1986; Schultz et al., 1983] which is produced directly in the oocyte [Mehlmann et al., 2002] but is also synthesised by the surrounding cumulus cells and is supplied to the oocyte via gap junctions [Anderson and Albertini, 1976; Webb et al., 2002]. The cumulus cells also supply cyclic GMP (cGMP) to the oocyte [Tornell et al., 1991] which inhibits phosphodiesterase (PDE) activity, the enzyme that degrades cAMP, and thus cGMP is also believed to contribute to the maintenance of meiotic arrest [Norris et al., 2009; Vaccari et al., 2009].

Cumulus expansion involves cumulus cell production of a hyaluronan-rich extracellular matrix as a secondary response to EGF-like ligands released by granulosa cells responding to LH [Park et al., 2004]. This unique extracellular matrix envelops the cumulus cells and oocyte, and its formation is dependent on the induction of specific genes [Richards, 2005; Richards et al., 2002b; Robker et al., 2000; Russell and Robker, 2007]. The cumulus cells lose their connection with the oocyte and each other due to entrapment in this extracellular matrix and physical breakdown of gap junctions. Cumulus expansion is required for normal oocyte maturation and ovulation [Russell and Robker, 2007]. This breakdown in communication between the oocyte and surrounding cumulus cells results in declining levels of cAMP and cGMP within the oocyte and subsequent resumption of meiosis [Dekel et al., 1981; Norris et al., 2009; Vaccari et al., 2009]. Nuclear and cytoplasmic maturation of the oocyte occurs, with the nuclear membrane (or germinal vesicle) breaking down (GVBD) [Calarco et al., 1972], formation of the meiotic spindle and extrusion of the first polar body containing half of the oocyte’s [Maro et al., 1986]. These are critical steps in the maturation of the oocyte and are required to achieve ‘developmental competence’, or the ability to be fertilised and develop into a viable offspring.

1.2.2 Regulators of ovulation

Perhaps surprisingly, the mechanisms controlling ovulation, or the release of a developmentally competent oocyte capable of fertilisation, are not entirely understood. As ovulation is crucial to reproductive success, there may be a number of redundant mechanisms which ensure weakening of the follicle apex and the eventual release of the COC (Figure 1.3). These include structural and molecular changes, with the exact nature of these changes intensely debated for several decades. However, it is widely accepted that following the LH surge, there is a cascade of regulated gene Lisa Akison 2012 8 expression in both granulosa and cumulus cells that results in cumulus expansion and rupture of the follicle wall at the apex [Espey, 1999]. It is also widely acknowledged that progesterone receptor (PGR) plays a pivotal role in this regulated gene expression and is required for ovulation. PGR regulation of specific gene networks required for ovulation will be discussed later in Chapter 1.

Researchers have proposed several contributing processes to ovulatory success (Figure 1.3). These include:  changes to the components and thickness of the follicle wall;  the action of proteases in remodelling of extracellular matrix in the follicle wall and in the cumulus oocyte complex;  cumulus ‘activation’, including the formation of an extracellular matrix and acquisition of migratory, invasive and adhesive properties;  vascular changes such as increased blood vessel permeability, vasoconstriction and vasodilation;  smooth muscle contraction causing the follicle to protrude beyond the ovarian surface; and  an inflammatory reaction involving a variety of inflammatory mediators and immune cells. All of these mechanisms, with the exception of the contribution of an inflammatory response, are discussed in more detail below. The evidence for immune cells and cytokines playing a critical role will be discussed separately in Chapter 4. In addition, LH-induced regulation of gene transcription in granulosa cells, which is the necessary precursor to the cascade of ovulatory genes, will be briefly presented.

Much of our understanding of the molecular mechanisms of ovulation come from studies on rodents, particularly transgenic strains of mice (e.g. [Conneely et al., 2002]). Although mice are a polyovular species, unlike humans which are typically monovular, both species respond similarly to gonadotrophin stimulation and display similar processes during ovulation. Thus, mouse transgenic knockout models provide a practical and informative resource to investigate molecular aspects of human reproduction.

1.2.2.1 Periovulatory regulation of granulosa gene transcription The LH surge transiently modifies the transcriptional machinery of mural granulosa cells to initiate the well-described ovulatory cascade of a cohort of genes in granulosa cells and cumulus cells with known roles in ovulation (Figure 1.4 and see [Russell and Robker, 2007] for review). LH binds to the LH receptor on granulosa cells, activates adenylate cyclase (AC), thus stimulating intracellular cAMP production and activation of protein kinase A (PKA). PKA activates mitogen activated protein kinases (MAPK/ERK) which phosphorylate transcription factors including cAMP response element binding protein (CREB) and stimulatory proteins 1 and 3 (SP1/SP3). SP1 and SP3 are constitutively present in

Lisa Akison 2012

10

Figure 1.3 Major processes involved in ovulation. The ovulatory surge in luteinising hormone (LH), or injection with the LH-analogue hCG, initiates a cascade of regulated gene expression in granulosa and cumulus cells that initiates and controls several molecular and structural processes believed to contribute to successful ovulation of the oocyte. There are potentially complex interactions and redundancies between these processes and the exact nature of their involvement in ovulation is unknown.

Lisa Akison 2012 11

Figure 1.4 Periovulatory regulation of gene transcription in granulosa cells. A) Luteinising hormone (LH) interacts with its receptor on granulosa cells activating adenylate cyclase (AC) and thus initiating, amongst other things, intracellular production of cyclic AMP (cAMP). This then activates protein kinase A (PKA) and the mitogen activated protein kinases (MAPK/ERK) which phosphorylate transcription factors including cAMP response element binding protein (CREB) and stimulatory proteins 1 and 3 (SP1/SP3). B) Phosphorylated SP1/SP3 and CREB recruit additional transcription factors, including enhancer binding protein (C/EBPβ) and progesterone receptor (PGR), which induce a cohort of essential genes required for ovulation. PGR is specifically involved in regulating ovulatory genes. Adapted from Russell & Robker [2007].

Lisa Akison 2012 12 granulosa cells but exhibit sequence-specific, LH-regulated binding to gene promoters [Russell et al., 2003a]. Activity of SP1/SP3 complexes and phosphorylated CREB (P-CREB) causes induction and recruitment of additional transcription factors that further contribute to a cascade of ovulatory gene expression (Figure 1.4 and see [Russell and Robker, 2007] for review). These include early growth response 1 (EGR1), CCAAT enhancer binding protein β (C/EBPβ) and progesterone receptor (PGR). These transcription factors are pivotal to the induction of down-stream ovulatory target genes, many of which will be described further in the following sections. Importantly, PGR is the only transcription factor which is known to have specific effects on genes required for ovulation, as opposed to additional roles in steroidogenesis, LH secretion or luteinisation (as per EGR1 and C/EBPβ) [Lee et al., 1996; Sterneck et al., 1997; Topilko et al., 1998; Yoshino et al., 2002], hence our interest in PGR regulation of ovulatory genes and ovulatory mechanisms. The specifics of PGR in the ovary and known PGR- regulated gene networks in the ovary will be discussed in Section 1.5.

1.2.2.2 Follicle wall structural changes Ovulation primarily requires that the ovarian and follicle wall is ruptured to allow passage of the oocyte into the oviduct/, yet no specific mechanism for the degradation of the ovarian wall has been identified. Novel imaging techniques have demonstrated that follicle wall rupture and COC release occurs rapidly, with the first signs being leakage of , followed by extrusion of follicular somatic cells and extracellular matrix (ECM) followed by release of the whole COC within 2-12 mins [Dahm-Kahler et al., 2006; Zackrisson et al., 2011]. The initial escape of follicular cells appears to result in partial degradation of the follicular apex [Zackrisson et al., 2011]. Thinning of the apical follicular wall, and in particular of the granulosa cell layers, is known to immediately precede ovulation [Espey, 1999] and may be a critical preliminary step (Figure 1.5). In a mature, preovulatory follicle, there are five different layers of cells containing a variety of ECM proteins that provide structural support (Figure 1.5A). The outermost layer is the ovarian surface epithelium, which is a single layer of cells. The second layer is the tunica albuginea, consisting of fibroblasts and collagen that form a tenacious sheath around the entire ovary. The third layer is the , the follicle’s own capsule of collagenous connective tissue which delineates its boundary and is very similar to the tunica albuginea. The fourth layer consists of the secretory cells of the , a highly differentiated tissue that is supplied by large capillaries that make up most of the ovarian circulation. This layer also contains collagen, and both thecal layers contain abundant laminin and secreted fibronectin. The fifth and innermost layer is the stratum granulosum or granulosa cell layer, which is separated from the theca by a basal lamina that is rich in laminin, collagen IV and heparin sulphate proteoglycan [Palotie et al., 1984] and is thought to be synthesised primarily by the underlying granulosa cells (see [Rodgers and Irving Rodgers, 2002] for review). In the ovary, the follicular basal lamina is believed to play a role

Lisa Akison 2012 13

A) B)

Figure 1.5 Follicle wall structural changes immediately prior to ovulation. A) Preovulatory follicle, prior to the LH surge. The follicle wall is composed of distinct cellular layers, each containing different extracellular matrix components. The inner layer is the mural granulosa cells that line the antral cavity. This is surrounded by the basal lamina, theca cell layers, the tunica albuginea and finally the outer ovarian surface epithelium. B) Periovulatory follicle immediately prior to ovulation. All layers, particularly the granulosa cell layer, become significantly thinner in the minutes just prior to ovulation, allowing the cumulus oocyte complex direct access to exposed extracellular matrix proteins. Figure adapted from photomicrographs contained in Espey [1999].

Lisa Akison 2012 14 in influencing granulosa cell proliferation and differentiation by maintaining the polarity and degree of specialisation of granulosa cells immediately adjacent to it [Rodgers and Irving Rodgers, 2002]. It also excludes capillaries, immune cells and nerve processes from the granulosa layer until ovulation [Rodgers and Irving Rodgers, 2002]. In comparison, the structure of the follicle wall at the apex a few minutes before ovulation is markedly different (Figure 1.5B). The surface epithelium has sloughed away or been stretched apart [Schroeder and Talbot, 1982] and is almost absent, and all the other layers of the wall have thinned, particularly the granulosa cell layer (Figure 1.5B). I propose that this thinning of the granulosa layers may expose the extracellular matrix proteins abundant in the ovarian wall (Figure 1.5). These include collagens, specifically types I, III and IV, fibronectin and laminin, which have all been localised to the follicle wall in a range of mammalian species, including humans [Berkholtz et al., 2006a; Figueiredo et al., 1995; Frojdman et al., 1998; Lind et al., 2006a; Rodgers and Irving Rodgers, 2002; van Wezel et al., 1998; Yamada et al., 1999; Zhao and Luck, 1995]. In the mouse, collagen I is found in granulosa and theca cell layers of antral follicles and is present at very high levels in ovarian surface epithelium; collagen IV is highly expressed in the theca; fibronectin is present at high levels in follicular fluid and to a lesser extent in granulosa and theca cells; and laminin is predominately localised to the theca and basal lamina surrounding the follicle [Berkholtz et al., 2006a]. Extensive remodelling occurs in the follicle ECM during the periovulatory period and the prevailing paradigm is that proteases are essential for this. The following section describes some of the key proteases believed to be essential for ovulation.

1.2.2.3 Proteases Proteases are a structurally and functionally diverse group of that cleave specific protein substrates and are critical for many biological processes. For example, they are involved in remodelling of extracellular matrix (ECM) proteins and regulate signalling pathways by controlling the bio-availability of many cytokines/receptors and their ligands. In the ovary, proteases are believed to be important for the extensive ECM remodelling that is required for follicle rupture and successful ovulation. They are involved in matrix remodelling required for the expansion of cumulus cells in the preovulatory COC, degradation of the basal lamina to allow invagination of the thecal layers and breakdown of the apical follicle wall (reviewed by [Ohnishi et al., 2005]). Several proteases have been identified as potentially important for ovulation, with all induced by the LH surge. These include matrix metalloproteinases, plasminogen activators/plasmin, cathepsin L and ADAM metallopeptidase with thrombospondin type 1 motif, 1 (ADAMTS1). Some of these will be described in more detail below.

Matrix metalloproteinases (MMPs) are either secreted or membrane-bound proteins, and are able to degrade almost all ECM components, including collagens, elastins, proteoglycans and (reviewed by [Egeblad and Werb, 2002]). MMPs are synthesised as inactive zymogens that require activation by proteolytic cleavage [Sternlicht and Werb, 2001] and their activity is regulated by Lisa Akison 2012 15 endogenous inhibitors, such as tissue inhibitors of metalloproteinases (TIMPS) [Baker et al., 2002]. They have been implicated to play a role in ovulation due to their ability to degrade a broad range of ECMs, particularly at the apical follicle wall [Murdoch and McCormick, 1992], thus reducing the structural integrity and facilitating breakdown of the follicle and oocyte release (see [Curry and Osteen, 2003] for review). In the mouse, MMP19 mRNA [Hagglund et al., 1999] and MMP9 activity [Robker et al., 2000] have been shown to be induced in the ovary following an ovulatory dose of hCG, and the cellular localisation of MT1-MMP (MMP14) changed in preovulatory follicles, with a decrease in GCs and a concomitant increase in thecal cells [Hagglund et al., 1999]. Broad-spectrum metalloproteinase inhibitors such as GM6001 [Peluffo et al., 2011] and galardin [Liu et al., 2006a] reduce or block oocyte release, providing further evidence that MMPs are important in follicle rupture.

The plasminogen activator (PA)/plasmin system has been implicated in follicle rupture and degradation of matrix in the expanded COC. PAs are serine proteases that cleave the inactive zymogen plasminogen to form the active protease plasmin. Plasmin primarily degrades fibrinogen and fibrin, but also cleaves a wide variety of substrates including ECM proteins and growth factors [Myohanen and Vaheri, 2004]. Evidence for a role of this system in follicle rupture includes the presence of plasminogen in follicular fluid and the ability of plasmin to weaken the follicle wall in vitro [Beers, 1975]; induction of PA expression and secretion by gonadotrophins in a spatially and temporally restricted manner in granulosa, theca and epithelial cells on the ovarian surface [Peng et al., 1993]; and demonstration that administration of PA/plasmin inhibitors or antisera suppresses ovulation in the rat and ewe [Colgin and Murdoch, 1997; Murdoch, 1998; Tsafriri et al., 1989]. Interestingly, vascular endothelial growth factor (VEGF) induces PA expression in endothelial cells [Mandriota et al., 1995; Pepper et al., 1991]. VEGF will be discussed in more detail below in the section on vascular changes in the ovary. In addition to PA expression in granulosa and theca cells, COCs from preovulatory follicles also express PAs [D'Alessandris et al., 2001; Liu et al., 1986]. Both the oocyte and cumulus cells secrete PAs, dramatically increasing secretion after expansion, presumably to assist in matrix degradation after ovulation [D'Alessandris et al., 2001].

However, knockout mouse models which lack individual genes encoding specific proteases still ovulate, reflecting redundancies and overlapping functions of the various proteolytic pathways [Curry, 2010]. The exception is ADAMTS1, the only protease which has been convincingly shown from knockout mouse studies to play a role in ovulation.

The ADAMTS family are members of the metzincin protease family with several protein domains involved in ECM binding [Porter et al., 2005]. In the ovary, ADAMTS1 breaks down versican, a key component of the ECM found in the COC and the follicle wall [Brown et al., 2010a]. Mouse studies have shown that ADAMTS1 is induced by LH in the granulosa cells of preovulatory follicles and

Lisa Akison 2012 16 becomes associated with the ECM of COCs during cumulus expansion [Brown et al., 2010a; Russell et al., 2003b]. ADAMTS1 has also been localised by immunohistochemical staining to the ovulatory stigma [Richards et al., 2005]. Female mice null for ADAMTS1 are subfertile, with ovulation rate reduced by 77% compared to their normal littermates and fertilisation rates reduced by 63% [Brown et al., 2010a]. This appears to be due to an inability to cleave the proteoglycan versican, resulting in abnormal matrix formation and cumulus cell aggregation in periovulatory COCs, defective catabolism of the cumulus matrix in postovulatory COCs resulting in abnormal retention of cumulus cells around the oocyte, and a lack of follicle wall remodelling required for thecal-cell invagination in the basal region of the follicle [Brown et al., 2010a]. Thus, ADAMTS1 is critical for appropriate cumulus matrix formation and catabolism, and remodelling of ECM in the follicle wall. These appear to be important processes for follicular rupture and subsequent ovulation, as ADAMTS1 null mice show entrapped oocytes within preovulatory follicles at 16 h post-hCG [Mittaz et al., 2004]. ADAMTS1, along with several other ADAMTS proteins, has also recently been implicated to play a role in ovulation in primates [Peluffo et al., 2011], specifically stigmata formation and follicle rupture.

1.2.2.4 Cumulus oocyte complex activation The preovulatory LH surge initiates a cascade of regulated gene expression via interaction with its receptor (LHCGR) on mural granulosa cells, inducing a suite of effector genes that activate cumulus cells resulting in dramatic structural and functional changes in the COC (see [Russell and Robker, 2007] for review). These changes constitute a phase of cumulus ‘activation’, which includes the process of cumulus expansion or mucification that involves the production of a hyaluronan-rich extracellular matrix, resumption of meiosis in the oocyte and transition to a migratory, adhesive and invasive phenotype. Each of these features of the ‘activated’, periovulatory COC will be described below.

The creation of a correctly assembled extracellular matrix around the oocyte is essential for ovulation. The LH surge induces the rapid expression of the EGF-like ligands amphiregulin (AREG), epiregulin (EREG), betacellulin (BTC) and neuregulin-1 (NRG1) in granulosa cells that act on their cognate receptors, EGF receptor (EGFR) and human epidermal growth factor receptors 2 & 3 (ERBB2/3) on granulosa and cumulus cells [Noma et al., 2010; Park et al., 2004; Shimada et al., 2006b]. Thus, these ligands function as secondary signals following the ovulatory LH surge between the granulosa and cumulus cells. The EGF-like ligands promote cumulus cell gene expression via activation of the extracellular signal-regulated kinase 1 & 2 (ERK1/2) signalling pathway [Kansra et al., 2004]. Importantly, although Areg-/- mice ovulate normally, Ereg-/- and EGFR hypomorph mutant mice show severely reduced ovulation rates, indicating their essential roles in this process [Hsieh et al., 2007]. The LH surge also stimulates the expression of prostaglandin-endoperoxide synthase 2 (PTGS2) in cumulus cells, resulting in prostaglandin E2 (PGE2) production. PGE2 acts in an autocrine manner via Lisa Akison 2012 17 its receptors, EP2 & EP4, to regulate cumulus cell gene expression of EGF-like factors and maintain cumulus expansion [Hizaki et al., 1999; Segi et al., 2003; Shimada et al., 2006b; Takahashi et al., 2006]. The importance of PTGS2 to the process of cumulus expansion, and ultimately to ovulation, is highlighted by the EP2 receptor knockout mouse model, which has defective cumulus expansion and reduced ovulation rate [Hizaki et al., 1999]. The EGF-like ligands, regulated by PGE2, stimulate cumulus cells to produce hyaluronan (HA) via induction of hyaluronan synthase 2 (HAS2) [Ashkenazi et al., 2005; Russell and Salustri, 2006]. HA is a non-sulfated, gylcosaminoglycan and is the primary component of the viscous extracellular matrix that envelops the oocyte and cumulus cells during the process of cumulus expansion [Russell and Salustri, 2006]. HA is believed to be tethered to cumulus cells by the HA receptor, CD44, which is expressed on cumulus cells in response to the LH surge in many species, including humans [Okada et al., 2003; Rodriguez Hurtado et al., 2011; Schoenfelder and Einspanier, 2003; Yokoo et al., 2002]. However, CD44-null mice show normal fertility [Protin et al., 1999], suggesting that either HA tethering is not critical for ovulation, or other HA receptors may also be involved in anchoring HA, such as hyaluronan-mediated motility receptor (HMMR, also known as RHAMM) which has been identified in bovine COCs [Schoenfelder and Einspanier, 2003]. Along with HA, the cumulus cells also produce several matrix stabilising proteins that impart organisation and structure. These include tumour necrosis factor alpha-induced protein 6 (TNFAIP6, also known as TSG6) which binds directly to HA [Carrette et al., 2001; Mukhopadhyay et al., 2001] and the anti- inflammatory protein, pentraxin 3 (PTX3), which associates with TNFAIP6 molecules forming anchoring complexes that cross-link multiple HA strands [Salustri et al., 2004]. Knockout mouse models with null mutations in these genes show defective cumulus cell mucification and sub-fertility [Fulop et al., 2003; Ochsner et al., 2003; Varani et al., 2002], demonstrating the important role of COC expansion for ovulation. In addition, the granulosa cell-produced protein, versican, the primary for ADAMTS1, also binds directly to HA in the cumulus matrix [Russell et al., 2003c]. As mentioned earlier, ADAMTS1 null mice are sub-fertile, and have an inability to cleave versican which results in abnormal matrix formation [Brown et al., 2010a]. The final important components of the cumulus matrix are the heavy chains of inter-alpha trypsin inhibitor (II) [Chen et al., 1992; Hess et al., 1999] which are present in serum and reach the follicle via the increased vascular permeability that occurs during ovulation (see below). These proteins, also known as SHAPS (serum-derived hyaluronan associated proteins), form a covalent bond with HA, an interaction that is catalysed by TNFAIP6 [Chen et al., 1996; Fulop et al., 2003]. The importance of serum-derived components, such as II, in the assembly of the cumulus matrix during COC expansion has been demonstrated in vitro, with expansion only occurring in cultured mouse COCs when the media is supplemented with serum [Chen et al., 1992; Salustri et al., 1989]. The light chain of II, bikunin, is essential in the formation of the SHAP-HA complex and has also been shown to be important in ovulation and COC integrity. Bikunin knockout mouse models show severely reduced ovulation rate, disorganised corona radiata, and defective matrix formation in Lisa Akison 2012 18 preovulatory and postovulatory COCs [Sato et al., 2001; Zhuo et al., 2001]. Thus, vascular remodelling impacts ovulation at least partly by supplying important factors from serum to the preovulatory follicle to support cumulus expansion.

At the commencement of this project, there was emerging, compelling evidence from our laboratory that the COC adopts a migratory, invasive and adhesive phenotype in response to LH-induced expansion [Alvino, 2010]. This study showed that dissociated cumulus cells from preovulatory, expanded COCs (i.e. 10 h post-hCG) adhered to various extracellular matrix proteins with greater affinity than cumulus cells from immature, unexpanded COCs (Figure 1.6A). Cell adhesion was greatest to ECM proteins found in the follicle wall (e.g. collagens and laminin, as described above). This study also used Boyden-chamber migration assays to show that expanded, preovulatory COCs display a significantly greater migratory ability than unexpanded, immature COCs (Figure 1.6B). This migratory capacity was specific to COCs, as granulosa cells isolated at the same time from preovulatory follicles showed minimal migration (Figure 1.6C). Cumulus cells from expanded COCs had an elongated shape, lamellipodial projections typical of migratory cells [Small et al., 2002] and were some distance from the micropores (Figure 1.6E, middle panel). In contrast, cumulus cells from unexpanded COCs that were counted on the underside of filters were almost exclusively contained within the pores of the filter, had a rounded morphology and rarely had migrated onto the membrane surface (Figure 1.6E, left panel). Granulosa cell morphology was similar to that observed for unexpanded COCs (Figure 1.6E, right panel). Finally, this study demonstrated that pre-ovulatory COCs invaded through Matrigel™ as readily as a highly invasive cancer cell line (MD-MB231 cells) and significantly greater than a non-invasive cancer cell line (MCF-7) using the same Boyden-chamber end-point assay (Figure 1.6D). Together, these results suggested that cell adhesion, migration and invasion were induced with COC expansion. Thus, it is possible to hypothesise that the COC may be capable of playing an active role in facilitating its own release from the follicle via the processes of matrix production leading to cumulus expansion, adhesion to ECM components of the follicle wall and invasive migration.

1.2.2.5 Vascular changes Female reproductive tissues, particularly the ovary and uterus, are unique adult organs in that they periodically undergo rapid remodelling and angiogenesis as part of their normal cyclic functions. In the ovary, each reproductive cycle requires tissue remodelling and vascular changes to sustain each new wave of growing follicles during folliculogenesis. Primordial and primary follicles are supplied with nutrients and oxygen via passive diffusion from stromal blood vessels, but for growth beyond these stages, formation of a capillary network around each individual follicle is required [Robinson et al., 2009]. This network is confined to the theca layer, which is separated from the underlying avascular granulosa layer by the basement membrane throughout folliculogenesis [Tamanini and De Ambrogi,

2004]. The levels of angiogenesis and blood flow reach their peak at the time of ovulation and Lisa Akison 2012 19

A) 2500 a cumulus cells from unexpanded COCs cumulus cells from expanded COCs 2000 a

1500 ab ab ab 1000 bc Adherent Cells Adherent abc 500 c c c c c c c c c 0 Coll I Coll II Coll IV FN Lam TN VN BSA B) C) D)

1.2 *** 1.4 * 60 a ab 1.0 1.2 50 1.0 0.8 40 0.8 0.6 30 0.6 0.4 20 0.4 b

0.2 0.2 (%) Index Invasion 10 Relative Migration Index Migration Relative Relative Migration Index Migration Relative 0.0 0.0 0 Unexpanded Expanded Granulosa Cells COCs COCs MB-231 MCF-7 E)

Figure 1.6 Preliminary report of adhesion, migration & invasion by cumulus cells. Adhesion, migration and invasion assessed using Boyden chamber transwell assays. A) Dissociated cumulus cells adhere to extracellular matrices in vitro. B) Cumulus cells from mice treated with eCG alone (unexpanded COCs) showed low capacity to migrate when compared with cumulus cells from mice treated with eCG and an ovulatory dose of hCG (expanded COCs). C) Granulosa cells from preovulatory follicles did not migrate. D) Cumulus cells could penetrate an extracellular matrix (Matrigel) barrier with invasive capacity comparable to that of the highly invasive breast cancer cell line, MDA-MB-231. MCF-7 breast cancer cells are a well- characterised, non-invasive cell line. E) Photomicrographs of representative filters showing cumulus cells from unexpanded COCs (left panel), cumulus cells from expanded COCs (middle panel) and granulosa cells (right panel). Red arrows indicate cumulus cells and granulosa cells remaining in filter pores. Black arrows indicate cumulus cells with morphology typical of motile cells. Pore size is 12 μm. Different letters denote significantly different by two-way ANOVA; * = P<0.05; *** = P<0.001. (Adapted from [Akison et al., 2012]).

Lisa Akison 2012 20 luteinisation, and have been likened to the levels observed in aggressive tumours [Reynolds et al., 1992]. Also during the preovulatory period, vascular permeability is enhanced facilitating the movement of blood components into follicular cells [Ko et al., 2006; Shin et al., 2005; Stouffer et al., 2007].

One of the key factors involved in this increased vascularisation and permeability is vascular endothelial growth factor a (VEGF-A or VEGF) and its receptor VEGF receptor 2 (VEGFR-2). In the preovulatory follicle, expression of both VEGF-A and VEGFR-2 are upregulated, predominantly in granulosa cells, but also in theca and stroma, across several species [Berisha et al., 2000; Hazzard et al., 1999; Reynolds et al., 1992; Stouffer et al., 2007]. The pivotal contribution of this axis to ovulatory success has been demonstrated by inhibitor/antagonist studies in rodents and primates targeting the receptor and/or the ligand [Fraser and Duncan, 2009; Stouffer et al., 2007; Wulff et al., 2002; Zimmermann et al., 2003]. In these studies, ovarian histology revealed that in treated animals, proliferation of thecal endothelial cells was dramatically reduced in preovulatory follicles (up to 92%), resulting in a poorly developed thecal layer, a lack of thecal microvasculature, impaired antrum formation and a lack of ovulatory stigma. The factors regulating VEGF/VEGF-R are still being elucidated. A recent in vitro study using a human granulosa cell line (KGN cells) suggests that EGF-like growth factors, such as AREG, may induce VEGF production [Karakida et al., 2011] and an in vitro study using mouse ovaries found an upregulation in VEGF mRNA following treatment with IL-6 [Shin et al., 2005]. Also, a study in humans found a correlation between follicle size and concentrations of VEGF in follicular fluid [Nishigaki et al., 2011].

While VEGF is the prime initiator of angiogenesis and vascular permeability in the ovary, there are other molecular factors thought to modulate vascular changes and blood flow in the ovary prior to ovulation; angiotensin II (AGTII) and angiopoietins. Administration of antagonists for the angiotensin receptors, AGTR1 and AGTR2, using an in vitro perfused rat ovary model inhibited ovulation [Mitsube et al., 2003] and in vivo experiments using intrabursal injections of AGTII and/or the receptor antagonists indicated that AGTII negatively affects ovarian blood flow (i.e. is vasoconstrictive), mainly via its interaction with AGTR2 [Mitsube et al., 2003]. Finally, expression of the angiopoietins (ANGPT- 1, ANGPT-2) and their receptors suggests that they can promote destabilisation of existing vascular networks in the preovulatory follicle (via ANGTP2) as well as enhance the maturation and stability of newly formed blood vessels (via ANGTP1) [Fraser, 2006; Hazzard et al., 1999; Shimizu et al., 2007], with both processes required for vascular remodelling [Robinson et al., 2009]. Additionally, antagonist studies using high doses of ANGPT2 suppress ovulation and luteinisation in primates [Stouffer et al., 2007; Xu and Stouffer, 2005]. However, the exact details of how these factors regulate preovulatory vascular remodelling, particularly in the human, are yet to be determined.

Lisa Akison 2012 21 As mentioned earlier, the vascular network in the theca layer surrounding the follicle is separated from the granulosa cell layer by the basement membrane throughout most of the follicle’s growth and development. However, a key feature of the structure of periovulatory follicles is the eventual breakdown of the basement membrane and invagination of the thecal layer with its associated vasculature into the basal region of the follicle. This substantial remodelling of the ECM surrounding the follicle is required to supply important factors from the blood (such as II, mentioned above) into the follicle to facilitate cumulus expansion, ovulation and subsequent formation of the corpus luteum [Hunter, 2003; Smith et al., 1994]. One of the key elements to this process is the involvement of the protease ADAMTS1, which cleaves the ECM proteoglycan versican in the basal region during thecal invagination [Brown et al., 2010a]. Cleaved versican has been found to reduce cell-to-cell adhesion and weaken tissue structure in other tissues [Wysoczynski et al., 2005]. In ADAMTS1 null mice, there is abnormal morphogenesis in this basal region, no detectable cleaved versican and a 77% reduction in ovulation rate [Brown et al., 2010a; Brown et al., 2006].

Interestingly, the vascular changes occurring at the apical region of the follicle are equally dramatic but quite different to those occurring elsewhere in the follicle. Novel studies using intravital microscopy and imaging of the periovulatory ovary in vivo in the rabbit [Dahm-Kahler et al., 2006] and in the rat [Zackrisson et al., 2011] revealed that after an initial period of hyperaemia in response to hCG administration, microcirculatory alterations resulted in a gradual decline in apical blood flow and the formation of an apical avascular area at the stigma. This was in stark contrast to the high density of blood vessels in the lateral and basal parts of the follicle. The cause of this vascular change in the apical region of the follicle is currently unknown, but could be induced by vasoactive substances, such as endothelins or angiotensin II, which are known to decrease blood flow in the ovary [Levy et al., 2003; Mitsube et al., 2003]. These factors may contribute to re-direction of blood flow from the apex to the base of the follicle [Brannstrom et al., 1998]. Why this avascular zone develops is also unknown, although it has been proposed that it might facilitate necrosis and subsequent tissue degradation to enable rupture or it may simply be to minimise blood loss during ovulation [Dahm-Kahler et al., 2006]. The creation of an avascular zone at the apex and a concomitant increase in blood flow in the basal region of the follicle corresponds to Doppler flow measurements in the human follicle [Brannstrom et al., 1998] but is in stark contrast to recent in vivo images of a follicular stigma in the human suggesting the formation of a highly vascularised blister [Das et al., 2011; Lousse and Donnez, 2008]. Thus, a closer examination of vascular changes at the apex of the follicle during ovulation in the human is required.

Vasomotion activity, or spontaneous variation in a vessel’s diameter that contributes to blood flow, has also been demonstrated in the ovarian microcirculation [Zackrisson et al., 2011], and is believed to facilitate fluid exchange, as it does in other organs [Intaglietta, 1991]. Thus, lower vasomotion activity

Lisa Akison 2012 22 during the early stages of ovulation has been proposed as an important factor driving the ovarian oedema characteristic at ovulation [Bjersing and Cajander, 1974; Hunter, 2003].

In summary, the processes of angiogenesis, increased vascular permeability, basal invagination, apical avascularity and vasomotion all contribute to dramatic vascular changes required to induce and facilitate ovulation.

1.2.2.6 Smooth muscle contraction and intrafollicular pressure It is clear from Section 1.2.2.2 that dramatic changes occur to the apical follicle wall just prior to ovulation, with loss of the ovarian surface epithelium and thinning of the follicle wall layers preceding follicular rupture. One mechanism proposed for this structural change is that contraction of smooth muscle cells (SMC) in the basal region causes protrusion of the antral follicle beyond the surface of the ovary, thus SMC are present in the basal theca layer during the periovulatory period in rodents [Doss et al., 1984; Ko et al., 2006; Martin and Talbot, 1981b; Palanisamy et al., 2006; Ren et al., 2009] but are conspicuously lacking from the apex of the follicle [Ko et al., 2006; Martin and Talbot, 1981b]. A recent study has also confirmed the presence of smooth muscle cells in the theca externa of human preovulatory follicles [Choi et al., 2011]. Moreover, intravital microscopy of the rabbit ovary to observe real-time changes during ovulation in vivo demonstrated the protruding nature of the ovarian surface 1- 3 h prior to rupture [Dahm-Kahler et al., 2006] and apical wall tension was found to significantly increase from the preovulatory phase to the late ovulatory phase in an in vivo rat model [Matousek et al., 2001].

Initial studies in hamsters provided evidence for a link between SMC contraction and ovulatory success. When SMC contracted, as confirmed by electron microscopy, a V-shaped constriction was formed in the base of the follicle and this morphological feature coincided with ovulation in the majority of these follicles [Talbot and Chacon, 1982]. Ovaries removed from hamsters at 12 h post-hCG and cultured in vitro did not show these morphological features and did not ovulate. However, ovaries removed at 12.5 and 13 h post-hCG, which had begun SMC contractions in vivo before removal, did have ovulating follicles when cultured in vitro [Talbot and Chacon, 1982]. Studies in vivo showed that ovulation could be reduced by injection into the bursal cavity with compounds that antagonise smooth muscle contraction in other tissues, including calcium inhibitors and local anaesthetics [Martin and Talbot, 1981a]. Electron microscopy confirmed the effect of these inhibitors on SMC contraction.

The vasoactive peptide, endothelin 2 (EDN2), has been proposed to play a role in inducing smooth muscle contractility and follicular constriction during the periovulatory period [Bridges et al., 2011; Bridges et al., 2010]. It is specifically induced in granulosa cells following hCG administration in rodents and can induce rapid and sustained contractions of ovarian strips in vitro which can be reversed by the addition of a dual endothelin receptor antagonist [Ko et al., 2006]. Further, in vivo treatment of rats with Lisa Akison 2012 23 the same receptor antagonist resulted in fewer ovulations than saline-injected controls in a dose- dependent manner [Ko et al., 2006]. EDN2 is believed to induce follicular constriction in vivo by crossing the basement membrane from the granulosa cells to stimulate contraction of smooth muscle cells in the theca externa [Bridges et al., 2011]. There are conflicting reports of which receptor is involved. Studies in rats have shown by isometric tension analysis that the contractile effect of EDN2 was mediated by EDNRA but not EDNRB [Al-Alem et al., 2007; Bridges et al., 2010], but treatment with antagonists against either of these receptors had no effect on ovulation rate [Bridges et al., 2010]. However, a study in mice showed that treatment with a specific EDNRB antagonist produced a dramatic (>85%) reduction in ovulations and abundant unruptured follicles [Palanisamy et al., 2006]. Treatment with an EDNRA antagonist also reduced ovulation rate, albeit to a lesser extent. These differences could be due to the different animal models used and further studies are required to definitively characterise endothelin receptor signalling during ovulation. Recent data in the human, however, supports the general model of endothelin regulation of smooth muscle contraction, as endothelin system components have been localised in the human preovulatory ovary and receptor expression was indeed coincident with smooth muscle cells in the theca [Choi et al., 2011]. Interestingly, strong expression of EDNRB has also been identified in cumulus cells of preovulatory follicles in both mice [Palanisamy et al., 2006] and humans [Choi et al., 2011].

In addition to smooth muscle contraction in the basal region and an increase in follicle wall tension in the apical region, intrafollicular pressure has also been widely debated to be a contributing factor to eventual rupture at the follicle apex. Intrafollicular pressure resulting in follicle rupture was the prevailing paradigm up until the mid-1960’s, with the increase in pressure attributed to an accumulation of follicular fluid or transudates from the blood circulation (see [Hunter, 2003] for a historical review). However, later studies demonstrated no link between an increase in intrafollicular pressure and follicle rupture [Espey and Lipner, 1963] and artificially increased intrafollicular pressure by injection of saline into rabbit follicles did not result in rupture [Rondell, 1964]. However, a relatively recent study in the rat did detect an increase in intrafollicular pressure from early to late ovulatory follicles in vivo, albeit moderate, using a sensitive servo-null micropipette system [Matousek et al., 2001]. This increase coincided with follicle wall contraction and thus provides some evidence that changes in pressure may contribute to eventual follicle rupture. However, to-date, there is no evidence that intrafollicular pressure alone can cause follicle rupture.

1.2.2.7 Summary and beyond ovulation Thus ovulation is a highly regulated and complex event, involving the interaction of multiple structural, molecular and biochemical events. This review highlights that after decades of research, there is much known about this process. However, the exact nature of the critical causative events, particularly in the human, still eludes us. Lisa Akison 2012 24 Of course, once ovulation occurs, this is not the end of the story for the COC. The adaptation of internal reproduction in mammals requires mechanisms and structures for pick-up of the oocyte after release from the ovary, transport of the oocyte to the site of fertilisation and further transport and nourishment of the early embryo until it reaches the site of implantation in the uterus where it will undergo all of its growth and development before birth. The uterine tubes, Fallopian tubes or oviducts (hereafter referred to as oviducts), which link the ovaries and uterus, play an essential role in this process. However, far from being simple tubes, they play a critical, active and multi-faceted role in mammalian reproduction. The next section will summarise this role, with particular emphasis on regulation of oocyte and embryo transport.

1.3 Structure and function of the oviduct

The oviduct’s structural characteristics and ability to function are inextricably linked to the cycling ovary. Ovarian steroids and prostaglandins influence oviducts via the systemic blood circulation, as well as locally via the ovarian vein and the oviduct branch of the ovarian artery [Hunter, 2011]. The concentration of these products is greatest at the time of ovulation. Further, both the oviductal environment and development of the early embryo are influenced by paracrine activity from the cumulus cells released with the COC at ovulation. Ovarian steroid hormones, including progesterone, impact on the oviduct by influencing the morphology of the oviduct luminal epithelium, regulating muscular and nerve function, and regulating the volume and composition of fluids in the lumen (see [Hunter, 2011] for review). This section will provide a description of the structure of the mammalian oviduct, a summary of the main secreted/expressed products that contribute to the oviductal milieu and the major functions of the oviduct, specifically oocyte/embryo transport and support. Much of this information has been taken from the excellent reviews by [Croxatto, 2002; Hershlag et al., 1989; Hunter, 2011; Talbot and Riveles, 2005]. Later in this Chapter, further details on the role of progesterone, and specifically PGR, in the oviduct will be discussed.

1.3.1 Structure of the mammalian oviduct

The mammalian oviduct can be divided into three anatomically and functionally distinct regions: the fimbriated infundibulum, the ampulla and the isthmus (Figure 1.7). In cross section, all of these regions have the same basic cellular structure (Figure 1.8A), but the relative proportion of the cell layers varies with the section being examined (Figure 1.7). The outermost layer or serosa is made up of loose connective tissue, blood vessels, lymphatics and nerves and is surrounded by a simple, squamous layer of mesothelial cells. Underlying this is the muscularis layer, which is composed of inner circular Lisa Akison 2012 25

A NOTE: This figure/table/image has been removed to comply with copyright regulations. It is included in the print copy of the thesis held by the University of Adelaide Library.

Figure 1.7 The structure of the oviduct in the mouse. The oviduct can be divided into three anatomically and functionally distinct regions: the fimbriated infundibulum, which captures and propels the newly ovulated oocytes into the oviduct; the ampulla, where fertilisation and early embryonic cleavage occurs; and the isthmus, which regulates the transport of sperm to the ampulla as well as passage of the early embryo to the uterus. The oviductal wall in the infundibulum and ampulla shows a highly folded mucosal epithelial layer, reflecting the importance of ciliary transport in these regions. In contrast, the wall of the isthmus shows a highly developed muscular layer. In some species, including the mouse and hamster, the infundibulum is enclosed within an ovarian bursal membrane; however, in others, including the human, the infundibulum opens directly into the peritoneal cavity. Adapted from [Nagy et al., 2003a].

Lisa Akison 2012 26

A)

B)

A NOTE: This figure/table/image has been removed to comply with copyright regulations. It is included in the print copy of the thesis

held by the University of Adelaide Library.

Figure 1.8 Cellular structure of the oviduct. A) Cross-sectional view of the oviduct. The tunica mucosa is the epithelial cell layer that lines the lumen. Underlying this is the tunica submucosa followed by the tunica muscularis, which contains numerous, circular and longitudinal smooth muscle cells. The final layer is the tunica serosa. This section is from the isthmus region of the oviduct which has a well- developed muscularis region. B) Detail showing the cells of the tunica mucosa, which is composed of a single layer of columnar epithelial cells, both ciliated cells and secretory ‘peg’ cells, with an underlying layer of loose connective tissue called the lamina propria. This view of the mucosa is taken from the ampulla region, as evidenced by the high degree of folding and less pronounced tunica muscularis. From University of New England Histology (http://faculty.une.edu/com/abell/histo/histolab3f.htm ).

Lisa Akison 2012 27 and outer longitudinal layers of smooth muscle cells. The next layer is the submucosa, which is loose connective tissue that connects the muscle layer to the innermost layer, the luminal mucosal layer. The mucosal layer includes a single layer of epithelial cells varying from tall, columnar to almost cuboidal and contains two types of cells: ciliated and secretory ‘peg’ cells (Figure 1.8B). The secretory cells have large nuclei and they tend to protrude into the adjacent lumen. Lying immediately beneath the epithelial layer is the lamina propria, a thin layer of connective tissue which, together with the epithelial layer, constitutes the mucosa. The mucosal layer can be highly folded, giving it a glandular appearance in cross-section.

The infundibulum is important for capturing COCs expelled from ruptured follicles and, in mono- ovulatory species including humans, the fimbriae have been observed to move in order to cover the surface of the ovary at ovulation [Piňon, 2002]. This region is the most highly ciliated, presumably to facilitate oocyte pick up and transport through the ostium or small opening into the oviduct. In some species, including rodents, the infundibulum is encased inside the ovarian bursa, a sack-like membrane derived from the and (Figure 1.7). The next region is the ampulla, which constitutes approximately half the length of the oviduct, and is the site of fertilisation and early embryonic cleavage. This region is characterised by a highly folded and extensive mucosal epithelial layer and a relatively thin muscular layer (Figure 1.7 and Figure 1.8B), with ciliary movement and oviductal secretions contributing to the function of the ampulla. The region closest to the uterus is the isthmus, which makes up the other half of the oviduct’s length, and compared to the ampulla, has a more developed muscular layer than mucosal layer, particularly the outer longitudinal layer of smooth muscle cells (Figure 1.7 and Figure 1.8A). The isthmus plays an important role in regulating sperm transport via the formation of a holding reservoir which binds ejaculated sperm to the epithelium [Suarez, 2002]. This allows sperm to complete capacitation and to precisely time sperm transport with the arrival of a mature oocyte in the ampulla (see [Suarez, 2008] for review). This region also supports early embryonic development and regulates transport of the embryo to the uterus via muscular contractions [Pulkkinen, 1995].

The morphology of the oviduct varies across the oestrous/menstrual cycle, with changes particularly evident leading up to ovulation. Tissues become progressively more tonic, due to oedema in the mucosa and vascular congestion [Hunter, 2011]. This causes the luminal mucosal epithelium to become highly folded, with prominent ridges and folds, and the cilia to become erect and beat in a synchronised manner [Hunter, 2011]. In the isthmic region, this underlying swelling reduces the diameter of the lumen, thus restricting movement along the duct. Changes to the myosalpinx or muscular layer also occur across the cycle, with increasing muscular tone a feature of the follicular phase or periovulatory phase and relaxation typical in the luteal or postovulatory phase. Non-ciliated secretory cells are also abundant and their size and secretory activity peak at ovulation [Hunter, 2011]. Lisa Akison 2012 28 The distribution of both ciliated and non-ciliated or secretory cells changes depending on the region of the oviduct and the stage of the cycle. The proportion of ciliated cells decreases from over 50% in the fimbria to less than 35% in the isthmus [Amso et al., 1994; Crow et al., 1994]. Ciliation and deciliation is a continuous process throughout the cycle, with ciliation maximal during the periovulatory period, particularly in the fimbria [Donnez et al., 1985; Verhage et al., 1979]. E2 enhances ciliation and secretion, whereas high levels of P4 are associated with atrophy and deciliation [Donnez et al., 1985; Verhage et al., 1979].

It has been proposed that the waves of oviduct smooth muscle contractility are possibly regulated by pace-maker cells called interstitial Cajal-like cells (ICLC), which have only been identified in the oviduct relatively recently by electron microscopy [Popescu et al., 2007; Popescu et al., 2005]. These tiny cells resemble interstitial Cajal cells (ICC) which were first identified in the gastrointestinal tract where they regulate peristalsis [Sanders, 1996]. ICLC are in close contact with epithelial cells and are connected to smooth muscle cells and each other by gap junctions. They also express PGR (see Section 1.6.1) and thus may contribute to the regulatory effect of P4 on muscular contractility. However, direct evidence for their involvement in tubal motility is lacking.

1.3.2 Functions of the oviduct

The major functions of the oviduct are:  Capture of the newly ovulated oocyte by the infundibulum;  Transport of sperm and oocyte(s) to the site of fertilisation;  Storage and capacitiation of sperm;  Facilitation of fertilisation;  Support of early embryonic development; and  Transport of the early embryo to the uterus.

There is considerable coverage in the literature on the role of the oviduct in sperm storage, transport and capacitation [Hunter, 2010; Rodriguez-Martinez et al., 2001; Suarez, 2008; Tienthai et al., 2004; Topfer-Petersen et al., 2008], as well as the ability of sperm to alter the oviductal environment [Fazeli et al., 2004; Georgiou et al., 2007; Jiwakanon et al., 2010]. However, this review will focus specifically on the role of the oviduct in oocyte pick-up and transport, fertilisation and embryo transport and support. Interestingly, in contrast to studies of ovarian function, there are fewer studies of oviductal function in rodents, with many conducted in domestic species, presumably due to practicalities of scale.

At ovulation, COC transport to the site of fertilisation at the ampulla is rapid, occurring in a matter of minutes. In contrast to this rapid initial phase of oocyte transport, the newly-formed embryo then Lisa Akison 2012 29 progresses slowly through the isthmic region to the uterus over a period of days. A recent study reported that measurements of particle transport speed (PTS) conducted on mouse ampulla and isthmus oviductal sections in vitro showed no effective particle transport in the isthmus and a PTS of ~70 μm/s in the ampulla, more than 3-fold higher than for trachea sections [Noreikat et al., 2012]. Interestingly, in the cow, the embryo was shown to be able to locally down-regulate PTS and thus regulate its own transport [Kolle et al., 2009]. Ciliary beating, muscular contractions and oviduct fluid contribute to oocyte and embryo transport, coordinated by the ovarian steroid hormones estradiol and progesterone. Each of these components and their contributions to oviductal function will be discussed below.

1.3.2.1 Oviduct cilia The presence of a correctly assembled cumulus matrix is required for ovulation (see Section 1.2.2.4) and adhesion of this matrix to cilia on the fimbria and infundibulum is required for pick-up of the ovulated oocyte and transfer through the ostium [Talbot et al., 2003]. The adhesive attraction between the COC and oviductal cilia increases dramatically at the ostium or opening to the oviduct (e.g. 10- to 40-fold as measured in hamsters), but after compaction of the cumulus mass in the ostium, the adhesive strength is rapidly reduced, presumably to facilitate the movement of the COC further into the oviductal lumen toward the ampulla [Lam et al., 2000]. In an in vitro assay examining pick-up of hamster COCs, unexpanded COCs failed to adhere to the infundibulum and were not transferred through the ostium [Lam et al., 2000]. However, the specific molecules involved in adhering cumulus matrix to the ciliary crowns have yet to be identified. Fibronectin, tenascin-c and laminin are produced by cumulus cells in the mature COC and show a heterogeneous distribution, suggestive of specific roles in promoting adhesion [Familiari et al., 1996]. Interestingly, although the cumulus matrix is undoubtedly important for oocyte pick-up in eutherian mammals, a cumulus oophorous does not surround the ovulated oocyte in marsupial mammals [Bedford, 1996; Breed, 1994; Taggart, 1994]. The diameter of the lumen of the oviduct matches the different ovulatory products, with the large, expanded cumulus mass surrounding the oocyte in eutherians filling the relatively large luminal cavity of the ampulla and marsupials having a comparatively narrow ampullary cavity to accommodate the ovulated oocyte devoid of cumulus [Bedford, 1996; Breed, 1994].

Cilia on luminal epithelial cells are responsible for the pick-up of ova by the fimbrial ostium and movement through the ampulla, as well as the distribution of the tubal fluid which supports gamete maturation and fertilisation and facilitates gamete and embryo transport. Ab-ovarian waves of muscular contraction also contribute, but appear to be most important in the transport of the early embryo through the isthmus (see below) [Kolle et al., 2009; Lyons et al., 2006b]. The importance of ciliary activity is affirmed by the tubal dysfunction seen in association with the deciliation of salpingitis [Patton et al., 1989]. However, women suffering from Kartagener's syndrome, which is the immotile cilia syndrome, Lisa Akison 2012 30 are sometimes still fertile, although these women often still have a small proportion of functional cilia [Halbert et al., 1997; McComb et al., 1986]. In addition, blocking smooth muscle contractility with isoproterenol in rabbits [Halbert et al., 1976] and rats [Halbert et al., 1989] did not impact on oocyte transport in the ampulla, providing further evidence for the crucial role of cilia for oocyte transport.

Cilia beat frequency (CBF) changes throughout the ovarian cycle and substances produced locally by oviductal cells or embryos can affect CBF in vitro and, presumably, in vivo [Croxatto, 2002]. These include prostaglandins, specifically PGE1, PGE2 and PGF2 [Verdugo et al., 1980], and platelet activating factor (PAF) (see below), which can increase CBF. E2 and P4 modulate the ciliated cell response to these agents, with P4 appearing to decrease and E2 increase CBF. One study showed that the CBF of human Fallopian tube segments incubated with P4 was decreased in a concentration- dependent manner and that E2, on its own, had no effect but in combination with P4, prevented the reduction in CBF seen with P4 alone [Mahmood et al., 1998]. A comparison of CBF between the secretory and proliferative phases of the menstrual cycle in women found that CBF was greatest during the secretory stage but this was only evident in the fimbrial region [Lyons et al., 2002]. The cause of the increase was believed to be due to secretory-stage follicular fluid, which would be released at ovulation [Lyons et al., 2006a]. Further, in vitro studies showed that secretory-stage follicular fluid, which is known to be high in E2, P4 and prostaglandins [McNatty et al., 1979; Seibel et al., 1984], increased CBF compared to peritoneal fluid [Lyons 2006a]. This suggests that E2 and prostaglandins must counteract the reported inhibitory effect of P4 on CBF [Lyons et al., 2006b]. Thus, these studies suggest that steroid hormones and prostaglandins together regulate CBF, and potentially oocyte transport, in vivo.

1.3.2.2 Oviduct motility – the role of muscular contraction Peristaltic contraction and relaxation of the smooth muscle fibres in the tunica muscularis facilitates gamete transport to the normal site of fertilisation in the ampulla, as well as transport of the early embryo to the uterus [Croxatto, 2002; Hunter, 2011]. This movement is primarily regulated by fluctuations in the hormonal balance of E2 and progesterone P4, the adrenergic-noradrenergic system and the action of prostaglandins. Muscular contractility changes across the estrous cycle, as shown by studies in vitro of human Fallopian tube sections collected at different stages of the cycle [Helm et al., 1982]. During the preovulatory period, muscular contractions are mild. However, contractions become vigorous at ovulation when E2 levels are high. This is believed to facilitate the fimbria coming in direct contact with the ovary to facilitate pick-up of the oocyte [Okamura et al., 1977].

Following fertilisation in the ampulla, the zygote typically pauses at the ampullary-isthmic junction before resuming transport towards the uterus [Halbert et al., 1988]. This delay is believed to be important for exposing the embryo to specific factors in the oviductal fluid required for development

Lisa Akison 2012 31 [Lyons et al., 2006b]. Resumption of transport coincides with a decrease in the amplitude of muscular contractions in the isthmus and a concomitant increase in levels of P4, at least in the rabbit where this has been directly measured in vivo [Spilman et al., 1978]. Therefore, strong muscular contractions that occur during estrous and the periovulatory period possibly contribute to halting embryo transport at the ampullary-isthmic junction, whereas muscular relaxation, which characterises the luteal phase, may enable transport to resume and the embryo to enter the isthmus. Adrenergic innervations occur along the length of the oviduct but are most pronounced in the circular muscle layers of the isthmus [Brundin, 1965], resulting in physiological constriction of the utero-tubal junction. As P4 levels rise post-ovulation and post-fertilisation, tubal motility is inhibited, leading to relaxation of the tubal musculature and widening of the isthmic luminal diameter to allow passage of the early embryo into the uterus.

Putative myotropic agents in the oviduct include neuropeptides (e.g. noradrenaline, neuropeptide Y, vasoactive intestinal peptide, substance P), prostaglandins, endothelins and nitric oxide (NO) [Croxatto, 2002]. These agents may regulate both tonic and episodic muscular contractions but their effects are complex, as circular and longitudinal muscle fibres often respond differently to the same agent [Croxatto, 2002]. Although P4 and E2 have been shown to modulate oviductal motility, and their receptors have been localised to smooth muscle cells in the oviduct (e.g. [Ulbrich et al., 2003; Valle et al., 2007] and see Section 1.6.1), they do not themselves cause contraction or relaxation but instead regulate the response of the muscle cells to myotropic agents [Croxatto, 2002].

The role of prostaglandins in the regulation of spontaneous tubal motility is contradictory. One study found that muscular contractions were increased in human oviductal explants, specifically the ampulla- isthmic junction, after treatment with PGE2 and PGF2 in vitro [Wanggren et al., 2008]. However, earlier studies measuring oviductal motility in the isthmus of rabbits in vivo, found that only PGF2 stimulates muscular contractions, while PGE1 and PGE2 inhibited motility [Spilman and Harper, 1974]. These differences likely reflect the varying species, oviductal regions and experimental models examined. For instance, it has been shown that the contractile response to prostaglandins varies depending on the stage of the cycle and hormone levels [Maia et al., 1977].

It is important to note that even when the above myotropic agents increase the frequency and/or intensity of muscular contractions in vitro, this does not necessarily result in increased transport of the embryo to the uterus. In this regard, functional studies are critical to determine biologically relevant factors regulating oviduct motility.

1.3.2.3 Oviduct fluid and secreted products Oviductal fluid is abundant mid-cycle when gametes or embryos are present and is believed to play a role during fertilisation and early cleavage. Tubal fluid is rich in many substances, including mucoproteins, hormones, growth factors and enzymes (see Table 1.1 for a comprehensive list adapted Lisa Akison 2012 32 from [Aviles et al., 2010]). The complex composition of this fluid reflects changing secretions by the mucosal epithelial cells as well as selective transudate from blood vessels [Leese, 1988; Leese et al., 2001]. Interspersed between the ciliated cells of the luminal epithelium are the secretory ‘peg’ cells which contain apical granules and contribute to the oviductal fluid. As per the ciliated cells, the abundance, morphology and secretory activity of peg cells is highly plastic and depends on the stage of the cycle and the region of the duct. Concentrations of nutrients in oviductal fluid is generally less than in plasma, suggesting that diffusion is the primary method of transport [Leese and Gray, 1985]. Many components such as ions, albumin, immunoglobulins, glucose and pyruvate are transferred from blood (see [Aguilar and Reyley, 2005] for review). There are also believed to be some inputs of follicle fluid at ovulation (although there are contradictory reports of this) as well as peritoneal fluid [Hunter, 2011; Hunter et al., 2007].

The volume of fluid in the oviductal lumen also changes cyclically, with fluid accumulation most pronounced during the follicular phase, and this again is influenced by ovarian steroid hormones, particularly oestradiol. This may be due to the action of aquaporins, particularly AQP1, 5 and 9, which have been suggested as potential regulators of fluid content within the oviduct [Skowronski et al., 2009; Skowronski et al., 2011] and have been demonstrated to be regulated by E2 [Branes et al., 2005]. Although most proteins in oviductal fluid are found in other tissues, one protein, oviductal glycoprotein 1 (OVGP1), appears to be produced exclusively by oviductal secretory cells. OVGP1 binds to the zona pellucida of oocytes and pre-implantation embryos [Buhi et al., 2000], as well as the acrosome region of sperm in some species [Boatman and Magnoni, 1995]. It is a highly conserved protein that has been identified in a diverse range of mammals, including humans (see Table 1.1). This mucoid protein is induced by E2, is present in the oviduct around ovulation and is believed to be important for regulating sperm binding, reducing polyspermy and increasing fertilisation rate, at least from in vitro evidence [Buhi, 2002; McCauley et al., 2003]. Its expression was also found to be up-regulated in the pig oviduct in the presence of sperm [Georgiou et al., 2007]. However, mice null for the Ovgp1 gene show normal fertility [Araki et al., 2003], indicating that, at least in mice, it is not essential for successful fertilisation.

The composition of oviduct fluids also varies along the duct, with regional differences between the ampulla and isthmus. This is believed to reflect differences in the type of secretory granules along the duct, as demonstrated in the mare [Desantis et al., 2011], resulting in different microenvironments with varying functions. That these microenvironments would exist is surprising given the vigorous muscular contractions that occur, particularly during ovulation, which would seem to result in mixing of fluids and a more homogeneous composition along the duct [Hunter, 2011]. However, the complex folding of the luminal epithelium in the ampulla probably helps to stabilise differences in regional fluids [Yaniz et al., 2000].

Lisa Akison 2012 33 Table 1.1 Major products present, expressed and/or secreted by the mammalian oviduct. Adapted from Aviles et al. [2010]. Note that these are major factors of the oviductal fluid or components expressed in the luminal epithelium of non-diseased tissue.

Products Abbreviations Species Reported References Growth factors, cytokines & their receptors Epidermal growth factor EGF, EGFR, AREG, Mouse, Human, Pig 1, 2, 5-9, 14, 15 superfamily & receptors TGF, HBEGF, HBEGFR Fibroblast growth factor & FGF, FGFR Cow, Pig 8, 10 receptor Colony stimulating factor 2, CSF2 Human, Mouse, Cow 6, 11-13 granulocyte macrophage -like growth factors, IGF1, IGF2, IGF1R, Human, Cow, Mouse, 15-26 receptors & binding proteins IGFBP1-6 Rat, Sheep Transforming growth factor β TGFβ1-3, TGFβR1-3, Human, Cow, Mouse, 1, 5-7, 15, 28, 29, superfamily & receptors (includes INHBA, INHBB, ACVR1A, Pig, Rat 35, 36, 40-42, 167 inhibins & activin receptors) ACVR1B, ACVR2A, ACVR2B Tumor necrosis factor-alpha TNF Human, Mouse 6, 27, 37 Vascular endothelial growth VEGF, VEGFR1 (FLT1), Cow, Human, Pig 8, 38, 39, 171 factor & receptors VEGFR2 (KDR) Hormones, hormone-like proteins & their receptors Adrenomedullin & receptors AM, CRLR, RAMP1-3 Mouse, Rat 43, 44 Angiotensin 2 & receptor AGT2, AGT2R Cow, Human 45-47, 74 Atrial natriuretic peptide & ANP, NPR-A Cow, Horse, Pig, Rat, 45, 48-51 receptor Rabbit Endothelins & receptors EDN1-3, EDNRA, Cow, Mouse, Rat 45, 52-57, 166 EDNRB Estrogen (estradiol) & estrogen E2, ER, ERβ Cow, Rabbit, Human, 18, 36, 58-61 receptors Mouse, Rat Gonadotrophin-releasing hormone GNRH, GNRHR Rat, Human, Cow 62-64 & receptor Adiponectin; leptin & receptor ADIPOQ, LEP, LEPR Mouse, Pig, Rat, Rabbit 65-68 Luteinising hormone receptor LHCGR Rat, Cow 36, 69 Nitric oxide synthase NOS Cow, Rabbit, Rat 68, 70-72 Progesterone & progesterone P4, PGR Cow, Hamster, Rabbit, 58- 61 + see refs receptor Human, Mouse, Rat, later in Chapter 1 Primates

Prostaglandins, synthesising PGE2, PGF2, PTGS1, Cow, Hamster, Human, 19, 34, 45, 53, 61, enzymes & receptors PTGS2, PTGER1/EP1, Pig, Rabbit, Sheep, 75-82, 98, 99, 118 PTGER2/EP2 Mouse Prolactin receptor PRLR Human, Mouse 73 Proteases & inhibitors Matrix metalloproteinases & tissue MMP1, MMP2, MMP7, Cow, Human, Pig 29, 83-86 inhibitors of metalloproteinase TIMP1 Plasminogen activators & PLAT, PLAU, Cow, Hamster, Pig, Rat 84, 87-90 inhibitors SERPINE1/PAI1 Anti-oxidants Catalase CAT Cow, Human, Mouse, 91-93, 96 Pig Superoxide dismutases SOD1, SOD2 Cow, Mouse Human 92-94, 96 Glutathione, glutathione GSH, GPX1-4, GSR Cow, Mouse, Rat 92, 93, 95-97 peroxidase, glutathione reductase

Lisa Akison 2012 34 Table 1.1 Continued Products Abbreviations Species Reported References Immunological components Complement system proteins/ CD46, CD55, CD59, C2- Human, Cow, Mouse, 3, 4, 100-107 Embryotrophic factor-3 4, iC3b Pig Defensins DEFB1, DEFA5 Human, Cow 109-111 Haptoglobin HP Cow, Rabbit 112-114 Interleukins IL-1, IL-6, IL-8, IL-10, IL- Human, Mouse, Pig 6, 15, 27, 28 12 Immunoglobulins IgA, IgG Cow, Human, Mouse, 101, 106, 115-117 Pig, Rabbit Surfactant proteins SPA, SPD Human, Horse, Mouse 119-121 Toll-like receptors TLR2-4, TLR7-10 Human 122-124 Lipids & lipases Cholesterol/high density CHOL, HDL Cow 125-127 lipoproteins Platelet activating factor & PAF, PAFR Human, Cow, Hamster, 30-34 receptor Mouse Other phospholipids various Buffalo, Cow 125, 126, 128 Phospholipase A2 PLA2 Cow, Rabbit 126, 129 Other enzymes & proteins Glycosidases & amylase, lysozyme, β-D- Human, Cow, Hamster, 118, 130-134 glycosyltransferases glactosidase, -L- Pig fucosidase, others Hyaluronidase SPAM1 (HYAL1) Mouse 135, 136 Chaperones & heat shock HSP40, HSPA8, HSP60, Cow, Pig, Human, Cow 104, 137-141 proteins GRP58, GRP78, GP96, HSP90 Albumin ALB Cow, Human, Monkey, 115, 142-144 Rabbit Oviductal glycoprotein 1/oviductin OVGP1 (MUC9) Babboon, Cow, Goat, 50, 104, 138, 145- Rabbit, Hamster, 154 Mouse, Pig, Sheep Progestagen-associated PAEP (aka PP14) Human 85, 155-157 endometrial protein (Glycodelin) Hypoxia up-regulated protein 1 HYOU1 (ORP150) Cow, Pig 104, 138 Secreted phosphoprotein 1 SPP1 Cow, Human, Horse 50, 158-160 (osteopontin) Integrins ITG1, ITG3, ITG4, Cow, Human, Mouse 84, 158, 160-162, ITG5, ITGV, ITG9, 168 ITGβ1, ITGβ3, ITG2β1 Proteoglycans, synthases & HA, CD44, SDC1, SDC2, Cow, Pig 163-165, 169 receptors HAS2,3, RHAMM, HARE Fibronectin, Laminin, Collagen FN, Laminin 12 Human, Horse 168, 170, 172-174 (α2β1γ3), Coll Type I, III

Lisa Akison 2012 35 Table 1.1 Continued References 1 [Kennedy et al., 1994]; 2 [Lee et al., 2006]; 3 [Liu et al., 1998]; 4 [Xu et al., 2004]; 5 [Lei and Rao, 1992]; 6 [Strandell et al., 2004]; 7 [Chegini et al., 1994]; 8 [Wollenhaupt et al., 2004]; 9 [Steffl et al., 2005]; 10 [Gabler et al., 1997]; 11 [Zhao and Chegini, 1994]; 12 [Loureiro et al., 2009]; 13 [de Moraes et al., 1999]; 14 [Sun et al., 2006]; 15 [Dalton et al., 1994]; 16 [Carlsson et al., 1993]; 17 [Zhang et al., 1994]; 18 [Shao et al., 2007]; 19 [Makarevich and Sirotkin, 1997]; 20 [Schmidt et al., 1994]; 21 [Pushpakumara et al., 2002]; 22 [Stevenson and Wathes, 1996]; 23 [Pfeifer and Chegini, 1994]; 24 [Fenwick et al., 2008]; 25 [Lighten et al., 1998]; 26 [Lai et al., 1996]; 27 [Bedaiwy et al., 2005]; 28 [Jiwakanon et al., 2010]; 29 [Gabler et al., 2008]; 30 [Tiemann et al., 2001]; 31 [Lash and Legge, 2001]; 32 [Velasquez et al., 1997]; 33 [Velasquez et al., 2001]; 34 [Hermoso et al., 2001]; 35 [Zhao et al., 1994]; 36 [Kubota et al., 2009]; 37 [Hunt, 1993]; 38 [Itoh et al., 2007]; 39 [Wijayagunawardane et al., 2005]; 40 [Gandolfi et al., 1995]; 41 [Jones et al., 2006b]; 42 [Lu et al., 1993]; 43 [Li et al., 2008]; 44 [Fazeli et al., 2004]; 45 [Wijayagunawardane et al., 2001a]; 46 [Mahmood et al., 2002]; 47 [Saridogan et al., 1996]; 48 [Zhang et al., 2006]; 49 [Kim et al., 1997]; 50 [Mugnier et al., 2009]; 51 [Russinova et al., 2002]; 52 [Rosselli et al., 1994]; 53 [Wijayagunawardane et al., 1999]; 54 [Jeoung et al., 2010]; 55 [Priyadarsana et al., 2004]; 56 [Sakamoto et al., 2001]; 57 [Bridges et al., 2011]; 58 [Amso et al., 1994]; 59 [Coppens et al., 1993]; 60 [Richardson and Oliphant, 1981]; 61 [Wijayagunawardane et al., 1998]; 62 [Sengupta and Sridaran, 2008]; 63 [Singh et al., 2008]; 64 [Casan et al., 2000]; 65 [Kawamura et al., 2002]; 66 [Archanco et al., 2007]; 67 [Craig et al., 2005]; 68 [Zerani et al., 2005]; 69 [Sun et al., 1997]; 70 [Lapointe et al., 2006]; 71 [Perez Martinez et al., 1998]; 72 [Ulbrich et al., 2006]; 73 [Shao et al., 2008]; 74 [Wijayagunawardane et al., 2009]; 75 [Huang et al., 2002]; 76 [Siemieniuch et al., 2009]; 77 [Ogra et al., 1974]; 78 [Warnes et al., 1978]; 79 [Rodriguez-Martinez et al., 1983]; 80 [McComb and Moon, 1985]; 81 [Verdugo et al., 1980]; 82 [Wanggren et al., 2006]; 83 [Chegini et al., 2001]; 84 [Gabler et al., 2001]; 85 [Amir et al., 2009]; 86 [Buhi et al., 1997]; 87 [Tsantarliotou et al., 2005]; 88 [Roldan-Olarte et al., 2005]; 89 [Jimenez Diaz et al., 2000]; 90 [Kouba et al., 2000]; 91 [Lapointe et al., 1998]; 92 [Harvey et al., 1995]; 93 [El Mouatassim et al., 2000]; 94 [Roy et al., 2008]; 95 [Salmen et al., 2005]; 96 [Lapointe and Bilodeau, 2003]; 97 [Lapointe et al., 2005]; 98 [Odau et al., 2006]; 99 [Han et al., 1996]; 100 [Jensen et al., 1995]; 101 [Tauber et al., 1985]; 102 [Lee et al., 2004]; 103 [Lee et al., 2009]; 104 [Bauersachs et al., 2004]; 105 [Buhi et al., 2000]; 106 [Buhi and Alvarez, 2003]; 107 [Georgiou et al., 2007]; 108 [Tse et al., 2008]; 109 [Quayle et al., 1998]; 110 [Valore et al., 1998]; 111 [Aono et al., 2006]; 112 [Lavery et al., 2003]; 113 [Lavery et al., 2004]; 114 [Herrler et al., 2004]; 115 [Stanke et al., 1974]; 116 [Parr and Parr, 1986]; 117 [Oliphant et al., 1978]; 118 [Gauvreau et al., 2010]; 119 Kankavi ; 120 [Leth-Larsen et al., 2004]; 121 [Oberley et al., 2007]; 122 [Pioli et al., 2004]; 123 [Hart et al., 2009]; 124 [Nasu et al., 2007]; 125 [Killian et al., 1989]; 126 [Grippo et al., 1994]; 127 [Grippo et al., 1994]; 128 [Vecchio et al., 2009]; 129 [Morishita et al., 1992]; 130 [Hochberg, 1974]; 131 [Marquez et al., 2005]; 132 [Carrasco et al., 2008a]; 133 [Carrasco et al., 2008b]; 134 [Tulsiani et al., 1996]; 135 [Zhang and Martin-DeLeon, 2003]; 136 [Griffiths et al., 2008]; 137 [Elliott et al., 2009]; 138 [Topfer-Petersen et al., 2008]; 139 [Lachance et al., 2007]; 140 [Marin-Briggiler et al., 2009]; 141 [Boilard et al., 2004]; 142 [Shapiro et al., 1971]; 143 [Marcus and Saravis, 1965]; 144 [Moghissi, 1970]; 145 [Buhi et al., 1996]; 146 [Donnelly et al., 1991]; 147 [Sendai et al., 1994]; 148 [Sendai et al., 1995]; 149 [DeSouza and Murray, 1995]; 150 [Suzuki et al., 1995]; 151 [Gandolfi et al., 1993]; 152 [Sutton et al., 1984]; 153 [Abe et al., 1995]; 154 [Arias et al., 1994]; 155 [Laird et al., 1995]; 156 [Saridogan et al., 1997]; 157 [Julkunen et al., 1986]; 158 [Gabler et al., 2003]; 159 [Brown et al., 1992]; 160 [Brown et al., 2012]; 161 [Tomczuk et al., 2003]; 162 [Sulz et al., 1998]; 163 [Tienthai et al., 2000]; 164 [Lee and Ax, 1984]; 165 [Bergqvist and Rodriguez-Martinez, 2006]; 166 [Ko et al., 2006]; 167 [Refaat and Ledger, 2011]; 168 [Inan et al., 2004]; 169 [Ulbrich et al., 2004]; 170 [Makrigiannakis et al., 2009]; 171 [Lam et al., 2004]; 172 [Koch et al., 1999]; 173 [Lantz et al., 1998], 174 [Schultka et al., 1989]

Lisa Akison 2012 36 Many studies have examined the composition of oviductal fluids using a variety of in situ and in vitro collection methods (see reviews mentioned above), but little is known about the mechanisms underlying their formation. Leese et al (2008) put forward the hypothesis of the epithelial cells lining the endosalpinx of the oviduct and the of the uterus, being the ‘gatekeepers’ to nutrients from the maternal diet to uptake by the developing embryo. Therefore, reproductive tract fluids may play a key role in the ‘Developmental Origins of Health and Disease’ (DOHaD) concept, and the composition of oviduct fluid in particular may impact on the long-term potential of the preimplantation embryo [Leese et al., 2008].

Components from oviductal fluid are potentially important for embryonic development, a consideration for assisted reproductive technology (ART). Bovine oocytes pre-incubated in ampullary oviductal fluid show greater fertilisation rates than controls [Way et al., 1997], and similarly for ovine oocytes incubated in heat-inactivated tubal fluid during the final maturation period, there was an increase in the percentage developing to live offspring after embryo transfer [Libik et al., 2002]. Therefore, at least for domestic species, the oviduct appears to play a critical, but subtle, role in the development of the zygote and during early cleavage [Hunter, 2011]. There is interest in the development of new in vitro media for these species, which mimic the nutrient composition of oviduct fluids, to potentially improve embryo development rates. Studies have shown that a synthetic oviduct fluid, created using bovine epithelial cell co-culture, alters gene expression of in vitro generated bovine embryos to more closely resemble in vivo-generated embryos compared with standard culture media [Wrenzycki et al., 2001]. However, effects on developmental competence have been minimal [Pedersen et al., 2005]. It is still not known which specific components may confer subsequent viability, but there is no doubt that interactions of diverse oviductal factors are required.

There is evidence to suggest that the oviductal epithelium alters its secretory protein profile during the periovulatory period in response to the presence of sperm or oocytes [Georgiou et al., 2007]. For example, the cytokine complement component C3 (or C3 protein) was up-regulated in the presence of sperm and down-regulated in the presence of oocytes [Georgiou et al., 2007]. C3 protein expression levels have also been found to vary in the oviduct at the time of sperm-oocyte binding [Anderson et al., 1993] and during early embryonic development [Lee et al., 2004; Li et al., 2004]. The previously identified embryotrophic factor 3 (ETF-3), which was demonstrated to promote proliferation and inhibit apoptosis in pre-implantation embryos [Xu et al., 2004], has recently been found to be composed of C3 and iC3b [Tse et al., 2008].

Lisa Akison 2012 37 1.3.3 Paracrine communication by COCs and embryos with the oviduct

Both the oviduct milieu and embryonic development are influenced by paracrine activity of cumulus and granulosa cells released with the oocyte at ovulation and remaining in the vicinity of the oocyte or embryo [Hunter, 2011]. After detachment from the zona pellucida during fertilisation, these cells do not necessarily degenerate and die. They have been shown to remain viable, phagocytosing sperm and secreting hormones and other peptides [Familiari et al., 1998; Motta et al., 1995; Nottola et al., 1991]. In particular, these ovulated follicular cells gradually establish and maintain luteal properties reminiscent of luteinising granulosa cells in the postovulatory follicle, and thus remain a source of locally- synthesised P4 particularly during and shortly after fertilisation. Thus, they are proposed to exert a local influence on the oviduct mucosal epithelium and on developing embryos [Hunter, 2011]. These cells may amplify early pregnancy signals from a zygote or developing embryo to the luminal mucosal epithelium, with potential signalling via vascular counter-current transfer from the oviduct to the ipsilateral ovary to influence the pattern of ovarian steroid secretion [Hunter et al., 2005]. However, direct experimental evidence for this hypothesis is lacking. P4 produced by cumulus cells of ovulated COCs also appears to have a chemoattractive effect for sperm, as demonstrated in the rabbit, as sperm express a P4 receptor (as yet uncharacterised) on the surface of the acrosome and have been demonstrated to be chemotactically attracted to gradients of P4 in vitro [Guidobaldi et al., 2008]. Interestingly, a study in the cow found that once the COC reaches the ampulla, it attached to the luminal epithelium to await fertilisation, and that this attachment was mediated by the cumulus cells as denuded oocytes did not attach [Kolle et al., 2009]. In addition, COCs with degenerated oocytes also did not attach, suggesting a potential selective mechanism for viable oocytes by the oviduct [Kolle et al., 2009].

In most mammals studied to date, fertilised eggs (embryos) and unfertilised eggs are transported to the uterus at approximately the same time [Hunter, 2011]. However, several species do display differential timing in oocyte/embryo transport. For example, in the mare, unfertilised oocytes can remain in the duct for several estrous cycles before degenerating while embryos pass into the uterus within 5-6 days after ovulation [Betteridge et al., 1982; Betteridge and Mitchell, 1974]. Similarly, in rats and hamsters, fertilised oocytes reached the uterus earlier than unfertilised oocytes, even in contralateral sides of the same animal, and therefore transport is regulated by some factor independent of plasma progesterone levels [Ortiz et al., 1986; Villalon et al., 1982]. This indicates that the early embryo interacts with the mucosal epithelium differently to unfertilised oocytes, and suggests that embryos may initiate signalling pathways that modulate its transport to the uterus.

Several studies indicate that prostaglandins and platelet activating factor (PAF) are important factors mediating the communication between embryos and the oviductal epithelium. In the case of the mare,

Lisa Akison 2012 38 the arrival of embryos into the uterus is believed to be facilitated by the production of PGE2 by the embryo at days 5-6 post-ovulation, with no PGE2 production measured in embryos at earlier time points

[Weber et al., 1991b]. The secretion of PGE2 was believed to hasten embryo transport to the uterus, just as exogenous PGE2 infused into the oviduct hastened the transport of both embryos and oocytes [Weber et al., 1991a]. Hamster [Velasquez et al., 1995], mouse [Ammit and O'Neill, 1997] and human [O'Neill et al., 1985] oviductal stage embryos have been reported to secrete PAF. This phospholipid ligand, when bound to its G-protein coupled receptor, PAFR, is known to have multiple roles in many different tissues, including the uterus and ovary (see [Harper, 1989] for review). PAFR has been found to be expressed in mucosal epithelial cells of human Fallopian tubes [Velasquez et al., 2001], hamster oviducts [Velasquez et al., 1997] and mouse oviducts [Lash and Legge, 2001] coincident with peak times of PAF synthesis by embryos. Further studies in the hamster showed that inhibition of PAF in vivo caused a significant delay in oviductal transport of embryos but not oocytes [Velasquez et al., 1995] that was believed to be due to interrupted paracrine signalling from the embryo to the oviduct, impacting on cilia action or smooth muscle contractility. A later study confirmed that PAF regulates

CBF in oviductal ciliated cell cultures via induction of PTGS2 and PGE2 production [Hermoso et al.,

2001]. Potentially, PAF could also be involved in the up-regulation of PGE2 seen during embryo transport in the mare. Thus, PAF is believed to play a role in regulating embryo transport in the hamster, human and rodent. More recently, studies in which COCs were co-cultured with bovine oviductal epithelial cells have revealed up-regulation of genes involved in ECM formation, such as MMP1, MMP2 and TGFβ3 in the oviductal cells [Gabler et al., 2008]. Thus, paracrine signalling by the COC and embryo appears capable of inducing oviduct-secreted products and, ultimately, mediating oviductal function.

1.3.4 Oviductal structure and function – remaining questions

Endocrine and paracrine signalling pathways are required for appropriate oocyte/embryo transport, but the exact nature of these pathways is still being elucidated and undoubtedly varies between species. Figure 1.9 summarises many of the key molecules and oviductal functions discussed in this review. In summary, distinctive morphological features in the different regions of the duct suggest that cilia may be more important for transport of the newly-ovulated oocyte to the site of fertilisation, while muscle contractions appear more important for regulating transport of the early embryo to the uterus. However, in reality, oviductal transport is a far more complicated process, with movement of gametes and embryos achieved via complex interactions between smooth muscle contractions, ciliary activity and tubal secretions.

Lisa Akison 2012 39

Figure 1.9 Putative factors involved in fertilisation and oviductal transport. A) During the periovulatory period, high levels of E2 and increasing levels of P4 regulate cilia beat frequency (CBF) and muscular contractions, particularly in the infundibulum and ampulla, to facilitate pick-up of the COC at ovulation and rapid transport to the site of fertilisation in the ampulla. Prostaglandins act on cilia and/or smooth muscle cells to facilitate these changes, but the exact molecules/receptors involved may be species-specific. Oviductal secretions, in particular the mucoid protein OVGP1, facilitate successful fertilisation of the oocyte and EDN3 may regulate secretory cell activity. Local production of P4 by ovulated cumulus cells appears important as a chemoattractant to sperm and may also modulate epithelial cell secretions or function. The newly cleaved embryo halts transport at the ampullary-isthmic junction, passing through into the isthmus when P4 levels rise, oedema subsides and smooth muscle cells relax. B) Once the embryo enters the isthmus, transport is slowed by high P4 levels which reduce CBF and induce smooth muscle relaxation. Endothelins and prostaglandins mediate changes to muscular contractility. The embryo also appears capable of modulating the oviductal environment via production of PAF and PGE2, which act on the epithelium to increase CBF and possibly also regulates muscular contractions. Thus, paracrine signalling by the embryo enhances embryo transport and facilitates entry into the uterus via the utero-tubal junction.

Lisa Akison 2012 40 Despite abundant evidence, often from in vitro studies, that the oviduct luminal epithelium is sensitive to local regulation by gametes, ovarian follicular cells, ovarian follicular fluid, zygotes and more advanced embryos, it is not always clear exactly how the up- or down-regulation of specific oviductal factors impacts on fertilisation or early embryo development/transport in vivo. Moreover, the molecular mechanisms underlying the regulation of oviductal factors are often unknown. Ovarian steroids, including progesterone, are indisputably critical and thus progesterone receptor must also play some role.

The important role of progesterone production and action is evident from the previous sections describing ovarian and oviductal structure and function. The following section provides a review of current knowledge on the role of progesterone and, specifically, of its receptor, in the ovary and oviduct.

1.4 Progesterone & Progesterone Receptor (PGR)

The ovarian steroid, progesterone (P4), is commonly allied to pregnancy establishment and maintenance (hence ‘pro-gestation’) but it also plays critical roles in other tissues including the ovary and oviduct/Fallopian tube. Ovarian granulosa-lutein cells are the major sites of P4 production in response to the preovulatory LH surge and ovary-derived P4 is involved in autocrine regulation of ovarian function and ovulation. Similarly, P4 is involved in modulating the morphology and physiology of the oviduct, providing an optimal environment for oocyte maturation, sperm capacitation, fertilisation, and bi-directional transport of gametes and embryos [Hunter, 1998; Murray et al., 1995]. The ‘classical’ mode of progesterone action is mediated by progesterone receptor (PGR), a ligand-activated, nuclear transcription factor also known as NR3C3 (nuclear receptor subfamily 3, group C, member 3) [Evans, 1988; Schrader and O'Malley, 1972; Tsai and O'Malley, 1994]. Just like other nuclear receptors, PGR contains three functional domains, the N-terminus, the DNA-binding domain (DBD) and the C-terminal ligand-binding domain (LBD) (Figure 1.10). Newly formed cytoplasmic PGR is assembled in an inactive multi-protein chaperone complex that dissociates from heat shock proteins once bound by its ligand, hence activating the receptor [Evans, 1988; Tsai and O'Malley, 1994; Weigel, 1996]. The binding of P4 to the LBD domain of PGR induces a conformational change and dimerisation of the receptor, resulting in association of the ligand-bound PGR dimer with specific coactivators (see [Rowan and O'Malley, 2000] for review) and general transcription factors [Weigel, 1996]. The activated complex binds to progesterone response elements (PREs) in the promoters of target genes, resulting in regulation of transcription in those genes (see [McKenna and O'Malley, 2002; Tsai and O'Malley, 1994] for review). Interestingly, PGR-regulated genes identified in the ovary to date do not have PREs in their promotors, so the mechanism of the transcriptional regulation is not fully understood in this organ and PGR- regulation of gene transcription has not been studied extensively in the oviduct (see next sections). Lisa Akison 2012 41

Figure 1.10 The structure of the two PGR isoforms – PGR-A and PGR-B. Initiation of translation occurs at ATG1 codon for PGR-B and ATG2 codon (165 amino acids downstream of ATG1) for PGR-A. Mutation at either of these ATG codons results in selective ablation of PGR-B (ATG1) and PGR-A (ATG2) in mouse knockout models. AF1, 2, 3 correspond to activation functions 1, 2, or 3. Note that AF3 is only present in the PGR-B isoform. DBD, Hinge, and LBD indicate the DNA binding domain, hinge region, and ligand (hormone) binding domains respectively. NLS indicates location of the nuclear localisation signals, both constitutive and hormone-dependent (adapted from [Hager et al., 2000].

Lisa Akison 2012 42 As well as triggering PGR DNA binding, non-genomic modes of P4 action have been identified which involve PGR-mediated activation of cytoplasmic phosphorylation cascades [Ballare et al., 2003; Boonyaratanakornkit et al., 2008; Boonyaratanakornkit et al., 2001] and interaction with specific membrane-bound receptors [Gellersen et al., 2009; Peluso, 2006]. However, it is only relatively recently that putative membrane receptors have been identified and their direct role in non-genomic P4 action is still being elucidated (see [Gellersen et al., 2009] for review). To date, progesterone receptor membrane component 1 (PGRMC1) and the membrane progestin receptors , β, and γ (mPR, β, and γ) have been identified as possible candidates [Gellersen et al., 2009], although the physiological relevance of mPRs to P4 function is unclear (see [Fernandes et al., 2008] for review). PGRMC1 mRNA and/or protein have been identified in ovaries of the rat [Peluso et al., 2006], mouse [McRae et al., 2005], human [Engmann et al., 2006], pig [Jiang et al., 2004] and cow [Luciano et al., 2011] and in the cow oviduct [Luciano et al., 2011]. In the ovary, it has been suggested that PGRMC1 plays a role in mediating the anti-apoptotic action of P4 and in the oviduct, it may play a role in inducing rapid changes in ciliary beat frequency of oviductal epithelial cells [Wessel et al., 2004]. To date, there has been no evidence that membrane progesterone receptors play a role in ovulation. Therefore, this thesis focuses on elucidating the role of nuclear PGR in ovarian and oviductal function. However, studies on membrane-bound PGRs will be included briefly where appropriate as discussion points, particularly with respect to oviduct function.

In mammals, the PGR gene gives rise to two functionally distinct protein isoforms, PGR-A (72-94 kDA) and PGR-B (108-120 kDA) [Kastner et al., 1990; Saqui-Salces et al., 2008; Schrader and O'Malley, 1972]. These isoforms arise as a result of translation from alternative initiation sites in the same PGR gene [Conneely et al., 1989; Conneely et al., 1987; Graham and Clarke, 2002; Kastner et al., 1990] to produce two distinct transcripts (Figure 1.10). The structure of these isoforms is identical, with the exception of an additional 165 amino acids at the N-terminus of PGR-B containing one of three activation function (AF) domains ([Kastner et al., 1990; Sartorius et al., 1994; Wen et al., 1994] and Figure 1.10). These AF domains associate with various co-regulators which enhance transcriptional activation by PGR of downstream target genes (see [McKenna and O'Malley, 2002] for review). PGR-A is found predominantly in the nucleus in the absence of ligand, while PGR-B resides primarily in the cytoplasm of hormone-free cells [Lim et al., 1999] and has been implicated as the predominant isoform associated with non-genomic actions of P4 [Boonyaratanakornkit et al., 2008; Boonyaratanakornkit et al., 2001].

PGR exerts pleiotrophic control over many reproductive processes [Lydon et al., 1995]. In particular, there is evidence from antagonist studies and knockout mouse studies that PGR is involved in neuroendocrine gonadotrophin regulation [Chappell et al., 1997; Chappell et al., 1999]; uterine decidualisation [Lydon et al., 1995]; mammary gland ductal morphogenesis and lobuloalveolar Lisa Akison 2012 43 differentiation [Lydon et al., 1995]; initiating the lordosis response or sexual receptiveness in females [Lydon et al., 1995; Mani et al., 1996]; and ovulation [Lydon et al., 1995; Robker et al., 2000]. Perhaps the most compelling evidence for the critical role of PGR in reproductive function comes from the various knockout mouse models with targeted deletion of the PGR gene. This is the primary, experimental model used in this thesis and is an indispensable tool for examining the molecular regulation of ovarian and oviductal function. The following section will briefly describe the various PGR- null mouse models whose phenotypes have been reported in the literature. However, the ovarian phenotypes of these mice will be described in more detail in Section 1.5 and a brief description and validation of the particular transgenic strain used in this study will be presented in Section 2.1.

1.4.1 PGR knockout mouse models

Targeted deletion of the promoter region in exon 1 of the Pgr gene in mice, the progesterone receptor knockout model (PRKO), defined the specific role of PGR in female fertility [Lydon et al., 1995]. PRKO homozygous females develop normally to adulthood but the ovaries, uterus, mammary gland and brain exhibit altered phenotypes demonstrating that PGR exerts pleiotrophic control over reproductive tissues [Lydon et al., 1996; Lydon et al., 1995]. Further, a lacZ reporter knock-in strain (PRlacZ), in which the endogenous Pgr promoter directly regulated lacZ (β-galactosidase) expression, provided a visual demonstration, via X-gal staining, of the distinctive expression profile of Pgr in multiple reproductive organs [Ismail et al., 2002]. Mice heterozygous for the lacZ insertion were a phenocopy of the wild-type (and were the subject of the study by Ismail et al. [2002]) while mice homozygous for the lacZ insertion were a phenocopy of the PRKO strain described by Lydon et al. [1995]. Both PRKO strains resulted in full ablation of the PGR gene. Since then, isoform-specific knockouts have been produced using CRE- loxP gene targeting to introduce mutations at the initiating ATG codon for PGR-B (PGRBKO, [Mulac- Jericevic et al., 2003]) or the initiating ATG codon for PGR-A (PRAKO, [Mulac-Jericevic et al., 2000]) (see Figure 1.10). These isoform-specific knockouts have revealed different phenotypes, demonstrating tissue-specific functions for each isoform. More recently, a Pgr conditional excision allele, in which loxP sites flank the entire exon 1 region of the Pgr gene, has been generated [Hashimoto-Partyka et al., 2006] which would allow a conditional, but complete, PGR knockout to be created in specific cell types. Finally, transgenic mice in which the PGR-A [Shyamala et al., 1998] or PGR-B [Shyamala et al., 2000] isoform was selectively over-expressed have been engineered, specifically to examine the roles of each isoform in mammary gland development.

The following sections will review the available information on PGR expression in the ovary and oviduct and its role in regulating gene expression and specific functions in these organs. Due to the sheer

Lisa Akison 2012 44 number of studies there will be an emphasis on studies in rodents, particularly knockout mouse models, but where possible information in the human and other species will also be presented.

1.5 PGR in the ovary

Progesterone, via its interaction with PGR, plays a key role in the function of ovarian cells and is one of the essential molecular drivers of successful ovulation. It is also believed, at least in some species, to regulate the acquisition of oocyte developmental competence which is required for successful fertilisation. PGR is highly but transiently expressed in the ovary, specifically in granulosa cells of preovulatory follicles in response to the pre-ovulatory LH surge that occurs just prior to ovulation. It plays a pivotal role in regulating the expression of downstream target genes that are essential for many processes required for successful oocyte release. This review summarises the expression dynamics of PGR in the ovary, the role of nuclear PGR specifically in ovulation and oocyte developmental competence and the specific genes that it regulates. Its role in ovulation, particularly in rodents and humans, has been well studied. However, studies on the effect of PGR on oocyte developmental competence show conflicting results between species.

1.5.1 Hormonally regulated expression of PGR in the ovary

In the ovary, activation of the G-protein coupled LH receptor (LHCGR) on mural granulosa cells in response to the LH surge increases intracellular cAMP, thereby activating PKA and MAPK/ERK signalling and inducing expression of PGR (refer to Figure 1.4 and Section 1.2.2.1). This induction can be prevented by blockade of the LH surge with pentobarbital in vivo [Park and Mayo, 1991] or mimicked by using cell permeable cAMP or by activating adenylate cyclase with high doses of FSH or forskolin in rat granulosa cell cultures in vitro [Park-Sarge and Mayo, 1994]. In addition, mice null for ERK1/2 in granulosa cells fail to express Pgr mRNA in response to ovulatory hCG [Fan et al., 2009]. Surge levels of LH also activate protein kinase C (PKC) and inclusion of the PKC activator, PMA, with forskolin causes a synergistic induction of PGR in mouse granulosa cells in culture [Sriraman et al., 2003].

PGR expression in response to LH or forskolin only occurs in granulosa cells of preovulatory follicles [Park-Sarge and Mayo, 1994] or those that have been differentiated in FSH plus testosterone or estradiol [Clemens et al., 1998]. Intriguingly, unlike other cell types such as breast and uterine, in which PGR induction has been well characterised, the multiple estrogen response elements (ERE) present in both proximal and distal regions of the gene [Boney-Montoya et al., 2010] do not bind to estradiol (E2) in the ovary and thus the effect of E2 on PGR in granulosa cells appears to be via its induction of Lisa Akison 2012 45 differentiation in granulosa cells [Clemens et al., 1998]. The as yet unidentified factor(s) that bind to the putative ERE-like region (ERE3) of the proximal PGR promoter appear to interact synergistically with the GC-rich distal promoter [Clemens et al., 1998], with both regions retaining constitutively bound Sp1/Sp3 proteins, but not C/EBPβ protein, which are required for induction of PGR mRNA expression in response to the LH surge [Clemens et al., 1998; Sriraman et al., 2003]. The molecular mechanism by which Sp1/Sp3 control transactivation of the PGR gene is not known but is thought to recruit additional, as yet unidentified, transcriptional regulators to the PGR promoter. Further, how the kinases which are essential for PGR induction modify the transcriptional complex is not known.

1.5.2 PGR expression in the rodent ovary

In the ovary, PGR mRNA and protein isoforms are expressed in a temporally and cell-type restricted manner. In rodents, Pgr mRNA is rapidly, yet transiently, induced in response to the LH surge or an ovulatory dose of hCG, specifically in mural granulosa cells. This has been shown in vivo in the rat [Park and Mayo, 1991] and in primary cultures of rat granulosa cells, peaking after 4-8 h in response to LH/hCG [Clemens et al., 1998; Jo and Curry, 2006; Natraj and Richards, 1993]. Pgr mRNA expression has not been directly analysed in the mouse but the PRlacZ reporter mouse model (see Section 1.4.1) demonstrates that Pgr is detectable within 4 hours of the LH surge, specifically in mural granulosa cells, peaks at 8 h post-hCG but is undetectable by 12 h post-hCG (Figure 1.11, [Ismail et al., 2002]). PGR protein has also been localised to granulosa cells of preovulatory follicles, transiently up-regulated at 4 h and 8 h post-hCG then undetectable by 12 h [Robker et al., 2000; Teilmann et al., 2006]. Consistent with LHCGR expression, PGR is expressed at dramatically higher levels in mural granulosa cells than in cumulus cells or oocytes [Ismail et al., 2002; Robker et al., 2000; Teilmann et al., 2006] (Figure 1.11). Expression is localised to nuclei and cytosol and is not present in primary cilia of granulosa cells (Figure 1.11F, [Teilmann et al., 2006]).

Of the two isoforms, PGR-A predominates in granulosa cells of preovulatory follicles in mice, although PGR-B is co-expressed but at a much lower level [Conneely et al., 2003; Gava et al., 2004; Natraj and Richards, 1993; Park and Mayo, 1991; Shao et al., 2003; Teilmann et al., 2006]. Immunohistochemistry of mouse ovary using a PGR-A specific antibody showed highest expression in granulosa cells of preovulatory follicles and the corpus luteum on the morning of estrus, consistent with other reports but also in the theca of preantral and antral follicles [Gava et al., 2004]. Intriguingly, an antibody validated to bind PGR-B specifically [Mote et al., 2001] detected expression throughout the ovary, in both granulosa and theca cells of follicles from the primary to preovulatory stage [Gava et al., 2004]. PGR-B was also expressed in corpora lutea (CL), including those from previous cycles, and was

Lisa Akison 2012 46

Figure 1.11 PGR is highly expressed in the ovary during the preovulatory period. Pgr mRNA expression is demonstrated by the PRlacZ reporter mouse which expresses lacZ under the control of the endogenous Pgr promoter. The dark blue X-Gal staining clearly demonstrates that Pgr is transiently expressed in preovulatory follicles in response to LH. A) Ovaries from mice treated with eCG only do not express PGR. Scale bar in whole mount corresponds to 1 mm; scale bar in section represents 500 μm. B-C) In response to hCG, lacZ staining is detected within 4 h and is still present at 8 h post-hCG, specifically in the granulosa cells of preovulatory follicles. Scale as per A) for whole mounts; scale bar for sections represents 500 μm. D) By 24 h post–hCG, 12 h after ovulation has occurred, there is no detectable lacZ staining in the ovary. Scales as for panels B-C. CL = corpus luteum. E) Higher power magnification of preovulatory follicle shows that lacZ is detected specifically in mural granulosa cells (GCs) but not in the oocyte-associated cumulus cells (CCs) or in the oocyte (O). Scale bar represents 200 μm. F) Immunolocalisation of PGR protein detected using a monoclonal anti-PGR antibody (Clone SP2, stains green [Teilmann et al., 2006]) 6 h post-hCG in a pre-pubertal C57Bl/6 mouse. Nuclei are detected with propidium iodide (red stain). Arrows indicate granulosa cells and asterisks cumulus cells. Green staining of the oocyte is an artefact of the antibody and is not indicative of PGR expression. Scale bar represents 50 μm. Left insert is high power image of granulosa cells. Right insert is a high power image of a single granulosa cell showing the primary cilium stained red with anti-acteylated -tubulin (arrow head), nucleus stained blue with TO-PRO, and PGR stained green. Adapted from [Ismail et al., 2002] and [Teilmann et al., 2006].

Lisa Akison 2012 47 uniquely detected in the germinal vesicle of oocytes in primordial, primary and preantral follicles [Gava et al., 2004]. This expression of PGR-B is distinct from all other reports of PGR mRNA and protein but the detection of PGR-A is consistent with other observations. In cultured granulosa cells, PGR-A is clearly the more prevalent translated in the rat [Natraj and Richards, 1993] and mouse [Shao et al., 2003; Teilmann et al., 2006] following the LH surge. Thus, as consistently demonstrated in multiple rodent models, PGR displays temporal and cell-type specificity in its ovarian expression.

1.5.3 PGR expression in primate and human ovary

Unlike the very transient pattern of PGR expression observed in rodents and bovine, primates, including humans, display more prolonged expression of PGR in the ovary, probably due to the extended luteal phase in these species. In rhesus and cynomolgus monkeys, PGR protein has been localised to granulosa cells in primordial and primary follicles while the highest levels have been observed in luteinising granulosa cells of follicles that had responded to the LH surge and in theca cells of follicles at all stages [Hild-Petito et al., 1988]. Corpora lutea (CL) from the early and mid-luteal phases expressed PGR protein but late-luteal and regressing CLs did not [Duffy and Stouffer, 1997; Hild-Petito et al., 1988].

In humans, there are very few reports of PGR protein localisation in the ovary. Consistent with other species examined, PGR is expressed in the dominant follicle at the time of the LH surge [Iwai et al., 1990] and similar to other primates, PGR expression is maintained in the active CL but not in the late CL [Iwai et al., 1990; Revelli et al., 1996; Suzuki et al., 1994]. PGR is also consistently observed in the theca of some follicles and the stroma [Iwai et al., 1990; Revelli et al., 1996; Suzuki et al., 1994] and interestingly, was detected in a small proportion of primordial follicles and preantral follicles [Revelli et al., 1996]. However, a recent study, which focussed specifically on granulosa cells collected from IVF patients before, during and after the LH surge, reported transient expression of both PGR-A and PGR-B mRNA and PGR-A protein [Garcia et al., 2012], which is more reminiscent of the expression profile in rodents. Further work is required to clarify the expression patterns of PGR isoforms in the human ovary, particularly in granulosa cells during the periovulatory period.

1.5.4 Functional roles of PGR in the ovary

Antagonists of PGR and genetically modified mouse models have been used to delineate the role of progesterone and its in ovarian function. Studies in many species including humans have consistently demonstrated that PGR is essential for release of the oocyte at ovulation.

Lisa Akison 2012 48 However, PGR is likely to have multiple roles in the ovary, including modulation of granulosa-lutein cell survival and steroidogenesis, cumulus expansion and oocyte quality depending on the species. The following sections will present current evidence for the role of PGR in each of these areas of ovarian function.

1.5.4.1 Ovulation PGR antagonist studies in both humans and rodents, as well as knockout mouse studies, have demonstrated the critical role of PGR in ovulation. RU486, or , is a mixed PGR agonist/antagonist [Chabbert-Buffet et al., 2005] which has been used extensively to experimentally demonstrate the function of PGR both in vitro and in vivo. Administration of RU486 to cycling female mice [Loutradis et al., 1991] or rats [Gaytan et al., 2003a; Sanchez-Criado et al., 1990; van der Schoot et al., 1987] prevented or reduced follicle rupture. Similar results occur with more specific, unambiguous anti-progestagens; ZK28299 () inhibited ovulation in rats [Uilenbroek, 1991] and Org31710 inhibited ovulation in an in vitro-perfused rat ovary model [Pall et al., 2000]. CDB-2914, which exhibits improved specificity and efficacy as an anti-progestin compared to RU486 due to reduced anti-glucocorticoid activity [Attardi et al., 2004; Attardi et al., 2002; Hild et al., 2000], blocked ovulation in rats [Reel et al., 1998] and severely impaired ovulation in mice [Palanisamy et al., 2006]. These PGR antagonist treatments were effective when delivered 5 h [Gaytan et al., 2003a] or 1 h [Palanisamy et al., 2006] prior to hCG administration, concurrent with the LH surge/hCG administration [Loutradis et al., 1991; Pall et al., 2000] or 3.5 h post-hCG administration [Pall et al., 2000], but not at 4 h [Loutradis et al., 1991], 7 h or 9 h post-hCG [Pall et al., 2000]. This indicates that PGR is important early in the ovulatory process, setting in motion a cascade of activity which subsequently triggers follicle rupture.

PGR antagonists also exhibit anti-ovulatory activity in women. Follicular phase administration of RU486 [Liu et al., 1987; Shoupe et al., 1987; Spitz et al., 1993] or CDB-2914 [Stratton et al., 2000] blocked or delayed ovulation in a dose-dependent manner. Moreover, women who received 100 mg of CDB-2914 in the mid-follicular phase exhibited a significant incidence of luteinized unruptured follicles [Stratton et al., 2000].

These PGR antagonist studies provided compelling evidence of the involvement of PGR in ovulation, but studies using PGR knockout mouse models demonstrated the absolute requirement of the PGR gene product for oocyte release. PRKO mice (as described in Section 1.4.1) have a profound and complete anovulatory phenotype, even when hyperstimulated with exogenous gonadotrophins, resulting in oocytes entrapped within follicles ([Lydon et al., 1995; Robker et al., 2000] and Figure 1.12). This has been observed at 13, 24 and 48 h post-hCG [Lydon et al., 1995; Robker and Richards, 2000; Robker et al., 2000]. This is despite apparently normal growth and development of follicles and oocytes

Lisa Akison 2012 49

eCG only

48 h post-hCG

Figure 1.12 The ovarian phenotype of the PGR knockout (PRKO) mouse. In the top two panels, both PGR heterozygous (PR+/-) and PRKO mice show large, expanded preovulatory follicles in response to eCG. The bottom panels show that in normal PR+/- mice, the follicle ruptured, expelled the oocyte and formed a corpus luteum by 48 h post-hCG. However, in the PRKO mice, the oocytes are still trapped within the luteinising follicle at the same time point (indicated by the arrow head). Adapted from [Robker et al., 2000].

Lisa Akison 2012 50 up to the antral stage (Figure 1.12). Granulosa cells in preovulatory follicles of PRKO mice respond to the LH surge as demonstrated by the presence of cumulus expansion [Lydon et al., 1995]; undergo normal LH-induced up-regulation of PTGS2 which is essential for ovulation [Robker et al., 2000]; and undergo normal luteinisation as demonstrated by the expression of the luteal marker P450 side-chain cleavage enzyme [Robker et al., 2000]. Therefore, PGR is not required for follicle growth and development or granulosa cell differentiation or luteinisation, but is specifically and absolutely required for LH-induced rupture of the preovulatory follicle and ovulation. Interestingly, the isoform-specific knockout mouse models have different phenotypes, with only PRAKO mice showing severely reduced (~75%) ovulation rates and implantation defects suggesting an obligatory role for PGR-A in mouse female fertility [Mulac-Jericevic et al., 2000]. Histology of PRAKO mouse ovaries is similar to PRKO mice, with numerous mature anovulatory follicles containing an intact oocyte [Mulac-Jericevic et al., 2000]. Stimulation of immature PRAKO mice with exogenous gonadotrophins further demonstrated a severe impairment in ovulation compared to WT mice, but not as complete as in PRKO mice where both isoforms were ablated [Conneely et al., 2002; Mulac-Jericevic et al., 2000]. Superovulation was unaffected in PRBKO mice which only express the PGR-A protein [Mulac-Jericevic et al., 2003]. Thus, PRKO mouse models clearly demonstrate the critical importance of the PGR-A isoform in ovulation. Furthermore, the fact that PGR-B alone is capable of supporting ovulation indicates that synergy between PGR-A and PGR-B proteins are not required for regulation of essential P4-responsive genes associated with ovulation. An area ripe for investigation is the utilisation of microarray techniques to examine differentially expressed genes in PRAKO and PRBKO mice, which would allow PGR-A– selective target genes essential for ovulation to be identified.

1.5.4.2 Oocyte developmental competence While the role for PGR in ovulation is clear, the possible influence of PGR on oocyte developmental competence, that is, the ability of the oocyte to produce a viable embryo following fertilisation, is not entirely resolved. The increase in P4 production by preovulatory follicles, concomitant with resumption of meiosis and maturation of the oocyte, might suggest a role for P4 and/or PGR in this process; however the low expression of PGR in cumulus cells relative to granulosa cells may similarly indicate it is not involved in COC maturation or oocyte viability. In support of this, oocytes isolated from PRKO follicles can be successfully matured and fertilised in vitro and exhibit normal blastocyst development rates and produce pups following uterine transfer [Robker and Richards, 2000]. Further, in vitro application of steroid antagonists, including the PGR antagonists RU486 and Org 31710, prevented neither LH-triggered germinal vesicle breakdown (GVBD) of rat or mouse follicle-enclosed oocytes nor the spontaneous maturation of COCs [Motola et al., 2007]. Similarly in vivo, two PGR antagonists (RU486 and ZK98734) injected into mice subcutaneously for the first 3 days of pregnancy, did not impair pre-implantation development in embryos flushed from the oviducts and uterus [Vinijsanun and

Lisa Akison 2012 51 Martin, 1990]. However, other studies are indicative of a role for P4 in oocyte maturation and developmental competence. A recent study has demonstrated that oocytes from follicles isolated from PRKO mice do not mature in response to exogenous progestin in vitro, with only 20% undergoing GVBD, while those from heterozygous mice showed >80% GVBD [Deng et al., 2009]. An early study also showed that treatment of mice with RU486 24 h after eCG resulted in a 50% decrease in the number of two-cell embryos that progressed to the blastocyst stage [Loutradis et al., 1991]. Further, in vitro work demonstrated that culture of either mouse preovulatory follicles or isolated COCs with P4 did not affect cumulus expansion but promoted oocyte maturation, assessed as GVBD, an effect that was inhibited by mifepristone [Jamnongjit et al., 2005; Ning et al., 2008]. Another study found that addition of P4 alone did not promote oocyte maturation in cultured mouse follicles but that treatment with RU486 reduced the percentage of oocytes that underwent polar body extrusion [Romero and Smitz, 2009].

In the pig, unlike the mouse, PGR is abundantly expressed in cumulus cells in response to FSH and LH and treatment with RU486 significantly impairs cumulus expansion in vitro [Shimada et al., 2004a; Shimada et al., 2004b]. Treatment with RU486 also blocks porcine oocyte progression to MII and blastocyst development [Shimada et al., 2004b].

In the bovine COC, PGR-A is present in both the cumulus cells and oocyte while PGR-B is induced in cumulus cells during oocyte maturation to MII [Aparicio et al., 2011]. Interestingly, multiple non- genomic progesterone receptors were also identified in bovine oocytes and cumulus cells, and inhibition of P4 production by the cumulus cells using trilostane impaired cumulus expansion and reduced blastocyst development rates, an effect reversed by the addition of exogenous P4 [Aparicio et al., 2011]. Treatment with RU486 during in vitro maturation (IVM) also impaired bovine cumulus expansion and reduced blastocyst development [Aparicio et al., 2011] indicating an important role for PGR in COC maturation and oocyte quality. In contrast, a previous study reported that treatment of bovine COCs with P4 during oocyte IVM reduced the proportion of blastocyst-stage embryos developing, an effect partially reversed by the addition of RU486 [Silva and Knight, 2000]. Although these studies are seemingly contradictory with respect to the effects of P4, overall they may indicate a role for P4 and PGR in determining oocyte quality in this species.

The role of P4 and specifically PGR in the regulation of cumulus expansion in humans has not been adequately examined. In a single study, analysis of 135 cumulus cell populations collected from 44 IVF patients at the time of oocyte collection found no relationship between PGR expression and oocyte fertilisation or cleavage rate [Hasegawa et al., 2005]. However, low expression levels of PGR mRNA, regardless of follicular fluid P4 levels, were correlated with subsequent good embryo quality, defined as embryos with ≥7 blastomeres and ≤ 5% fragmentation [Hasegawa et al., 2005]. In primates, in vitro

Lisa Akison 2012 52 culture of oocytes with progestin/P4 has been shown to improve blastocyst rates compared to vehicle- treated controls [Borman et al., 2004; Zheng et al., 2003].

Cumulatively, these studies indicate that a better understanding of the role of PGR in the peri- conception COC and its impact on oocyte developmental competence is needed as its regulatory effects may in fact be species-specific, given its varied expression profiles in preovulatory COCs.

1.5.4.3 Granulosa cell survival and steroidogenesis The majority of ovarian follicles undergo atresia during follicular development and yet this process does not occur amongst preovulatory follicles responding to the LH surge, as the number of corpora lutea are approximately equivalent in number to preovulatory follicles [Svensson et al., 2000]. Apoptosis is the cellular mechanism behind follicle and luteal cell atresia in the ovary, which suggests a change in granulosa cell susceptibility to apoptosis during the periovulatory period. Steroid hormones, including progesterone, are important regulators of follicular cell survival and apoptosis and PGR plays a role in preventing granulosa cell apoptosis during luteinisation. Mice treated with RU486 prior to ovulatory hCG have increased active caspase 3 (CASP3), a protease indicative of cellular apoptosis, in granulosa cells of preovulatory follicles [Shao et al., 2003] and culture of periovulatory mouse [Shao et al., 2003], rat [Svensson et al., 2000] or human [Rung et al., 2005] granulosa cells with RU486 or Org31710 increases DNA laddering indicative of cellular apoptosis. Similarly, CASP3 activity [Svensson et al., 2001] and TUNEL positivity [Makrigiannakis et al., 2000] have been reported in human luteinising granulosa cells in response to either RU486 or Org31710 treatment in vitro.

Cholesterol synthesis by rat and human periovulatory granulosa cells in vitro is inhibited by RU486 or Org 31710 [Rung et al., 2005; Shao et al., 2003; Svensson et al., 2000], suggesting a role for PGR in steroid synthesis during luteinisation. In PRKO mice, basal progesterone levels are not different to normal littermates [Chappell et al., 1997], however steroidogenesis and luteal function have not been closely examined in any of the PGR null mouse models. In non-human primates and humans, species with long luteal cycles, it is clear that PGR regulates steroidogenesis in the early corpus luteum (reviewed in [Park and Mayo, 1991; Stouffer, 2003; Stouffer et al., 2007]). Furthermore, based on expression patterns, it is likely that PGR-B in particular regulates luteinisation while PGR-A controls ovulation [Stouffer et al., 2007]. Although PGR has a role in periovulatory granulosa cell survival and steroidogenesis, in primates at least, there is no evidence at present to suggest that these functions contribute to its critical role in follicular rupture.

Lisa Akison 2012 53 1.5.5 Peri-ovulatory genes regulated by PGR

The profound infertility of female PRKO mice has led to intense interest in the identification of PGR- regulated genes. From genomic approaches, PGR has been identified as an important regulator of gene transcription during the periovulatory period, specifically of genes found to be necessary for successful oocyte release from the preovulatory follicle [Kim et al., 2009a; Robker et al., 2009; Sriraman et al., 2010]. This has been demonstrated using microarray analysis of transcripts from ovarian cells and cultured follicles of PRKO mice compared to heterozygotes, or from isolated granulosa cells cultured in the presence/absence of PGR antagonists such as RU486 or CDB-2914. Those currently identified from in vivo studies include genes coding for proteases, growth factors, signal transduction components and transcription factors, but few have been demonstrated to play a direct role in ovulation (Table 1.2 and Figure 1.13). Many of these genes may in fact be more important for luteinisation and/or luteal cell survival. Interestingly, the mechanism by which PGR regulates many of these genes remains to be determined as progesterone response elements (PREs) have not been identified.

1.5.5.1 Proteases As mentioned earlier in this chapter, ovulation requires the action of proteases to facilitate release of the oocyte from within the follicular structure and lack of proteolytic tissue remodelling has been hypothesized to contribute to the anovulatory phenotype of the PRKO mouse [Robker et al., 2000]. At least five proteases (ADAMTS1, cathepsin L, ADAM8, PRSS35 and MMP10) appear to be directly or indirectly regulated by progesterone receptor as they are selectively induced in large ovulatory follicles and are absent in follicles from PRKO mice [Robker et al., 2000; Sriraman et al., 2008] or mice treated with the progesterone synthesis inhibitor trilostane [Miyakoshi et al., 2006] or RU486 [Peluffo et al., 2011] (Table 1.2). However to date, the extracellular matrix protease, ADAMTS1, is the only protease unequivocally linked to ovulatory success. This gene is selectively induced by the LH surge in preovulatory follicles [Espey et al., 2000; Russell et al., 2003b] and is activated via PGR stimulation of promoter activity in vitro [Doyle et al., 2004]. However, it is not induced when P4 synthesis or PGR expression is inhibited or lost [Espey et al., 2000; Robker et al., 2000; Russell et al., 2003b; Sriraman et al., 2008]. In addition, both the pro-form and the proteolytically active form of ADAMTS1 protein is deficient in PRKO mice, resulting in reduced cleavage of its main substrate, versican, within the COC [Russell et al., 2003b]. Importantly, ADAMTS1 null mice also exhibit altered matrix structure as a result of the impaired processing of versican in the COC, and thus in vivo fertilisation rate is reduced by 63% in these mice [Brown et al., 2010a], a defect not yet fully investigated in the PRKO mouse model. Interestingly, ovarian histology of ADAMTS1 knockout mice is reminiscent of that of PRKOS, including

Lisa Akison 2012

Table 1.2 PGR-regulated genes in the ovary. Evidence for PGR regulation includes reduced (↓) expression in PRKO mouse models and inhibition () using various agents which block PGR activity or progesterone synthesis. Only those genes demonstrated to be regulated by PGR in vivo have been included.  = critical for ovulation. GC = granulosa cells. KO = knockout. Gene Function Evidence for PGR regulation Critical for ovulation?

 by epostane in rat GC in vivo [Espey et al., 2000] ADAMTS1KO mice have reduced (71-77%) ovulation rate compared to Adamts1+/- Adamts1 secreted ECM protease ↓ in PRKO GC [Robker et al., 2000; Russell et al., 2003b] [Brown et al., 2010a; Mittaz et al., 2004] lysosomal cysteine ↓ in PRKO GC [Robker et al., 2000] Ctsl (Cathepsin L) No – null mice have normal fertility [Potts et al., 2004] protease  by RU486 in human GC in vitro [Garcia et al., 2012] transmembrane ↓ in PRKO GC [Robker et al., 2000] Adam8 No - ovulation normal in null mice [Kelly et al., 2005] metzincin protease  by RU486 in mouse follicles in vitro [Sriraman et al., 2008] Prss35 serine protease  by trilostane in mice in vivo [Miyakoshi et al., 2006] Unknown  by RU486 and trilostane in vivo in rats (IH and PGE2 Ptgs2(Cox2) prostaglandin synthesis PTGS2 KO has reduced ovulation rate [Davis et al., 1999; Lim et al., 1997]  production) [Mori et al., 2011] Edn1  by RU486; ↓ in PRKO ovaries [Sriraman et al., 2010] vasoconstrictive EDN1 – No Edn1, Edn2 Edn2  by CDB-2914 in vivo/in vitro [Palanisamy et al., 2006] peptides EDN2 - Receptor antagonists block ovulation [Ko et al., 2006; Palanisamy et al., 2006] ↓ in PRKO GC [Palanisamy et al., 2006] Apoa1 lipid metabolism  by RU486 in vitro; ↓ in PRKO ovaries [Sriraman et al., 2010] No – null mice have normal fertility [Miettinen et al., 2001] Cited1 angiogenesis  by RU486 in vitro; ↓ in PRKO ovaries [Sriraman et al., 2010] Unknown Likely – EGFR antagonist reduced ovulation in vivo [Ashkenazi et al., 2005]; EREG and Areg, Ereg EGF-like growth factors ↓ in PRKO GC [Shimada et al., 2006] EGFR mutant mice have reduced ovulation [Hsieh et al., 2007]  Likely - mice null for IL6R GP130 have reduced ovulation [Molyneaux, Schaible et al. Il6 cytokine ↓ in PRKO GC [Kim et al., 2008] 2003]  component of SNARE ↓ in PRKO GC Possibly – involved in secretion of IL6 [Shimada et al., 2007], however null mice Snap25 exocytosis complex  by RU486 in vitro [Shimada et al., 2007] embryonic lethal cyclic GMP-dependent ↓ in PRKO GC [Kim et al., 2008; Sriraman et al., 2006] Prkg2 (cGKII) Unknown protein kinase II  by CDB-2914 in vitro [Palanisamy et al., 2006] ubiquitin-related Sumo1  by RU486/ Org31710 in vivo/ in vitro [Shao et al., 2004] Unknown modifier  by ZK98299 in rat GC in vitro [Ko et al., 1999] Adcyap1 (Pacap) growth factor No - ovulation normal in null mice [Isaac and Sherwood, 2008]  by RU486/epostane in rat GC in vivo [Park et al, 2000] Ctgf transcription factor ↓ in PRKO GC [Nagashima et al., 2011] CTG conditional KO has 50% reduced ovulation [Nagashima et al., 2011]  Pparγ transcription factor ↓ in PRKO GC [Kim et al., 2008] PPARγ conditional KO has 75% reduced ovulation [Kim et al., 2008]  Hif1α, Hif2α, transcription factors ↓ in PRKO GC [Kim et al., 2009] Inhibition of HIF DNA-binding reduces (>90%) ovulation [Kim et al., 2009]  Hif1β

55

Figure 1.13 Genes regulated by PGR in the ovary which are known to be important for ovulation. The expression of PGR and its downstream effectors are all within granulosa cells of large, preovulatory follicles following the LH surge. The EGF-like growth factors EREG and AREG are required for cumulus expansion which is critical for ovulation. The extracellular matrix protease ADAMTS1 is also known to be important for cumulus expansion but can itself impact on follicle rupture at ovulation due to its role in breakdown of the follicle wall. Hypoxia-inducible factors (HIFs) have been shown to regulate expression of ADAMTS1 and the vasocontrictive peptide EDN2. PPARγ is responsible for the induction of other genes such as EDN2 and IL6, which were originally thought to be directly PGR-regulated. RUNX1 regulates important cumulus matrix genes such as PTGS2 and HAPLN1 (not shown) and is itself also regulated by binding of AREG to EGFR. Finally, CTGF has recently been identified as a PGR-regulated transcription factor which can induce ADAMTS1. PGR regulation of immune-related genes will be discussed in Chapter 4. Bold white lines indicate regulation; fine white lines indicate production; and black lines indicate binding of ligand to the receptor. Genes in yellow are transcription factors down-stream of PGR.

Lisa Akison 2012 56 luteinized follicles which express P450scc normally but contain entrapped oocytes [Brown et al., 2010a; Mittaz et al., 2004].

1.5.5.2 Growth factors and signal transduction components A large number of cellular signalling genes have been identified as being PGR-regulated; however for the majority of these genes, their role in ovulation is unclear (Table 1.2). One gene that is known to be critical for ovulation is Ptgs2 (see Section 1.2.2.4), but its regulation by PGR is contentious. In vitro studies using PGR inhibitors in rat preovulatory follicle culture [Hedin and Eriksson, 1997], perfused rat ovaries [Pall et al., 2000], bovine granulosa cells [Bridges et al., 2006] and human granulosa luteal cells

[Tsai et al., 2008] have reported attenuation or inhibition of PTGS2 protein expression and/or PGE2 production. However, in vivo studies did not detect a reduction in PTGS2 expression in PRKO mice compared to normal littermates [Kim et al., 2008; Robker et al., 2000] or in cows with intrafollicular treatment with trilostane [Li et al., 2007]. However, a recent in vivo study in rats treated with either RU486 or trilostane did detect a reduction in PTGS2 protein in granulosa cells of preovulatory follicles at 8 h post-hCG by immunohistochemistry and, in the case of RU486, reduced PGE2 production [Mori et al., 2011]. Further, knockdown of the PGR-regulated transcription factor, runt related transcription factor 1 (RUNX1) (discussed below) also resulted in reduced expression of PTGS2 [Liu et al., 2009a]. Thus, it appears that PGR, via RUNX1, may in fact regulate PTGS2 during the periovulatory period. Why there are discrepancies amongst in vivo studies is unknown, but may relate to differences in the mechanism of PGR knockdown.

Several genes known to regulate angiogenesis and vascular function, namely Edn2, Edn1, Cited1 and Apoa1, have been identified as PGR-regulated genes (Table 1.2). However, the only gene which has been demonstrated to play a role in ovulation is the potent vasoconstrictive peptide EDN2 (see Section 1.2.2.6). EDN2 is expressed specifically in granulosa cells, peaking at 12 h post-hCG and then rapidly (within 1 h) down-regulated. It is undetectable in ovaries from gonadotrophin-stimulated PRKO mice, and treatment with a specific endothelin receptor antagonist (against EDNRB) dramatically decreases ovulation rate and results in unruptured preovulatory follicles [Ko et al., 2006; Palanisamy et al., 2006]. Endothelin 1 (Edn1), Cbp/p300-interacting transactivator 1 (Cited1) and apolipoprotein 1 (Apoa1) have all been found to be specifically induced by PGR-A in granulosa cells in vitro in the absence of LH [Sriraman et al., 2010], and were significantly reduced in granulosa cell cultures treated with RU486 or in hormonally-primed PRKO mice [Sriraman et al., 2010]. However, these genes have not been demonstrated to play definitive roles in ovulation. EDN1 appears to be involved in follicular development & steroidogenesis, the control of premature luteinisation in granulosa cells (via its regulation of gonadotrophin-stimulated P4 secretion) and luteolysis in the corpus luteum (see [Bridges et al., 2011] for review). CITED1 has been shown to be regulated by EDN1, interacts with various transcription factors and regulates several genes, including Areg, to mediate angiogenesis during Lisa Akison 2012 57 placentation and mammary gland ductal development [Howlin et al., 2006; Rodriguez et al., 2004]. APOA1 is the primary protein constituent of high-density lipoprotein (HDL), which has been shown to regulate angiogenesis in the ovary via levels in follicular fluid [von Otte et al., 2006]. Further, it may affect oocyte maturation and fertility potential [Von Wald et al., 2009]. APOA1 null mice are fertile however [Miettinen et al., 2001].

Other PGR-regulated genes also have known or suspected roles in ovulation. EGF-like ligands amphiregulin (AREG) and epiregulin (EREG) are dysregulated in PRKO granulosa cells [Shimada et al., 2006b] and these ligands normally play key roles in triggering cumulus expansion and meiotic resumption in response to ovulatory LH [Ashkenazi et al., 2005; Park et al., 2004]. Mice with mutations in Ereg or epidermal growth factor receptor (Egfr) have severely reduced ovulation rates [Hsieh et al., 2007] and inhibition of EGFR in the rat using intrabursal injections of the antagonist, AG1478, reduced ovulation rate in a dose-dependent manner [Ashkenazi et al., 2005]. Interestingly, COCs that did ovulate in these models had defective cumulus expansion, similar to mice treated with EDNRB antagonists [Ko et al., 2006; Palanisamy et al., 2006] but unlike PRKO mice in which cumulus expansion appears morphologically normal [Robker et al., 2000]. However, PGR regulation of AREG, EREG or EDN2 may impact functional aspects of cumulus expansion which influence follicular rupture.

The cytokine IL6 is reduced in PRKO mice [Kim et al., 2008] as is synaptosomal-associated protein-25 (SNAP25), a component of the SNARE exocytosis complex that promotes cytokine secretion (including IL6) by both the COC and granulosa cells [Shimada et al., 2007]. A study in which the Cre-loxP system was used to inactivate the IL6 receptor component GP130 specifically in germ cells resulted in a defect in ovulation, suggesting that IL6 is important for ovulation [Molyneaux et al., 2003a], and possibly SNAP25 is involved in regulating its release. Thus, via regulation of both cytokine production and secretion, PGR may play a role in the inflammatory reaction that is associated with the process of ovulation. This will be explored further in Chapter 4.

In the case of other putative PGR-regulated signalling molecules, such as PRKG2 (cGKII) and SUMO1, their roles in ovulation are not clear, or they may be involved in the terminal differentiation of granulosa cells rather than follicular rupture. Both pituitary adenylate cyclase activating polypeptide (PACAP, also known as ADCYAP1) and its receptor, PAC1 (also known as ADCYAP1R1), are transiently induced in granulosa cells of preovulatory follicles via LH- and PGR-mediated mechanisms [Barberi et al., 2007; Ko et al., 1999; Ko and Park-Sarge, 2000; Park et al., 2000]. PACAP null female mice have normal rates of ovulation and fertilisation. However, only a small percentage of females have successful implantation, a defect thought to be due to their reduced prolactin and progesterone levels [Isaac and Sherwood, 2008]. Similarly, female PAC1 null mice also exhibit reduced pregnancy rates [Jamen et al.,

Lisa Akison 2012 58 2000] but ovulation rate was not examined. Thus PGR-mediated induction of the PACAP-PAC1 pathway appears to be more important for the establishment of luteinisation rather than ovulation.

1.5.5.3 Transcription factors Runt-related transcription factor 1 (RUNX1, previously known as AML1), is a nuclear transcription factor essential for hematopoietic cell survival that is also transiently induced in granulosa cells of preovulatory follicles in response to ovulatory hCG [Jo and Curry, 2006]. Treatment of rat granulosa cells in vitro with the PGR antagonist, ZK98299, inhibited hCG-induced expression of RUNX1 [Jo and Curry, 2006]. Knockdown of RUNX1 expression in rat granulosa cells using siRNA down-regulated the expression of CYP11a and consequently resulted in reduced P4 production [Jo and Curry, 2006]. Importantly, knockdown of RUNX1 also resulted in reduced LH/hCG-induced expression of PTGS2 [Liu et al., 2009a] and HAPLN1 [Jo and Curry, 2006; Liu et al., 2010], both genes demonstrated to be important for cumulus expansion which is necessary for ovulation (see Section 1.2.2). Chromatin immunoprecipitation assays (ChIP assays) have confirmed in vivo binding of endogenous RUNX1 to the Ptgs2 [Liu et al., 2009a] and Hapln1 [Liu et al., 2010] promoter regions, confirming direct regulation of these genes. Thus, the hormonally regulated expression of RUNX1 in preovulatory follicles, its involvement in P4 production, and its regulation of ovulatory genes such as Hapln1 and Ptgs2 suggests a likely role in ovulation.

PPARγ (peroxisome proliferator-activated receptor gamma) has been identified as a molecular target of PGR, as it failed to be induced by hCG in ovaries of PRKO mice relative to age-matched PRWT controls by 5 h post-hCG [Kim et al., 2008]. Its role in ovulation was tested using transgenic PR-Cre and PPARγ-flox mice to delete PPARγ specifically in cells which express PGR, resulting in PPARγ deletion specifically in mural granulosa cells but not cumulus cells of preovulatory follicles [Kim et al., 2008]. Follicular development was unaffected; however PPARγfl/fl PRCre/+ females had severely reduced ovulation rate with histological analysis of the ovaries showing an absence of CLs and abundant unruptured follicles [Kim et al., 2008]. Importantly, PPARγ appears to be responsible for the induction of other genes previously acknowledged as PGR-regulated genes, since Edn2, Prkg2 and Il6 mRNA, each of which are disrupted in PRKO ovaries, were also decreased in PPARγfl/fl PRCre/+ ovaries [Kim et al., 2008]. However, expression of the PGR-regulated gene Adamts1 was not altered in PPARγflox/flox PRCre/+ ovaries [Kim et al., 2008], indicating PPARγ only regulates a subset of PGR- regulated genes. Activating ligands of PPARγ include ligands produced by PTGS2, possibly PGJ2, as blocking prostaglandin synthesis with indomethacin or the more specific PTGS2 inhibitor, NS-398, blocks the induction of PPARγ-regulated genes (Edn2, Prkg2 and Il6) in cultured mouse granulosa cells [Kim et al., 2008]. Thus it appears that through the induction of PPARγ by PGR and ligands produced by PTGS2, these signalling pathways converge to promote ovulatory induction of EDN2, PRKG2 and IL6. Lisa Akison 2012 59 Hypoxia-inducible factor (HIF) transcription factors HIF1, HIF2 (EPAS1) and HIF1β have been identified as transcriptionally-regulated PGR-dependent genes [Kim et al., 2009b]. HIF activity is likely to be important for follicular rupture since treatment of mice with echinomycin, which blocks HIF DNA binding, blocked follicle rupture [Kim et al., 2009b]. Echinomycin treatment in vivo also blocked the hCG-stimulated induction of PGR-target genes ADAMTS1 and EDN2 but not HIF1 or ADAM8 [Kim et al., 2009b] suggesting that HIF transcription factors are also essential mediators of expression for a subset of PGR-regulated genes (Figure 1.13).

Most recently, connective tissue growth factor (CTGF) has been identified as a transcription factor acting down-stream of PGR signalling. This was done using a CTGFfl/fl PRCre/+ conditional knockout mouse which showed normal cumulus expansion but a 50% reduction in ovulation rate in hormonally- primed adult mice, entrapped oocytes in luteinised follicles and reduced expression of ADAMTS1 [Nagashima et al., 2011]. In addition, this study showed a significant reduction in Ctgf mRNA expression at 6 h post-hCG in PRKO mice compared to heterozygous littermates. Thus, transcription factors induced downstream of PGR, such as RUNX1, PPARγ, HIFs and CTGF, also influence expression of what are considered PGR-regulated genes.

In contrast to all that is known about PGR-regulation of transcription in other reproductive tissues, it is not known how PGR regulates the transcription of its periovulatory gene cohort in granulosa cells. Only ADAMTS1 has been shown to be activated via PGR stimulation of promoter activity in vitro [Doyle et al., 2004]. However, like other PGR-regulated genes in granulosa cells, ADAMTS1 lacks classical PGR binding response elements (PRE). Therefore, unique transcriptional mechanisms are believed to play a role, either interacting directly with PGR or acting as transcriptional co-activators to regulate a distinct gene expression signature (see Robker et al, 2009, for review). Alternatively, by inducing the expression of additional transcription factors, PGR could trigger the ovulatory cascade of gene expression.

Thus, through sequential cascades of genes initiated by PGR, biomechanical events including protease activation, cumulus expansion, smooth muscle contraction, vascular permeability and angiogenesis may all contribute to follicle rupture and oocyte release.

1.6 PGR in the oviduct

Progesterone receptor is highly expressed in the oviduct, predominantly in luminal epithelial cells but also muscle cells. Although much is known about the expression characteristics of PGR in oviductal cells, there is still much to unravel about how PGR may regulate many of the important reproductive

Lisa Akison 2012 60 processes that occur in the oviduct. For example, the role of PGR in oocyte and embryo transport has been relatively neglected compared to comprehensive studies examining its essential roles in implantation in the uterus. The following review summarises studies examining the expression of PGR in the oviduct and the potential role that PGR may play in regulating the specific function of oviductal transport of COCs and embryos.

1.6.1 PGR expression in the oviduct

In the oviducts of mice, PGR is highly expressed in both ciliated and non-ciliated columnar epithelial cells that line the lumen [Ismail et al., 2002; Teilmann et al., 2006], as well as some expression in smooth muscle cells in the oviductal wall [Ismail et al., 2002] (Figure 1.14). Both isoforms of PGR are expressed in the oviduct, although PGR-A predominates and PGR-B is restricted to luminal epithelial cells [Gava et al., 2004; Teilmann et al., 2006]. In ciliated cells, PGR is specifically localised to the lower half of motile cilia, with adjacent secretory cells displaying PGR staining confined to the nuclei [Teilmann et al., 2006] (Figure 1.14). Constitutive expression of Pgr in the oviduct across the oestrous cycle has been suggested by a lacZ-reporter study in mice [Ismail et al., 2002] (see also images of whole mounts in Figure 1.11) and has also been reported in human Fallopian tubes [Amso et al., 1994]. However, another study has shown that PGR can be induced in the oviduct by an ovulatory dose of hCG in pubertal mice, particularly in ciliated cells [Teilmann et al., 2006], with immunohistochemical staining showing up-regulated expression of PGR protein at 6 h post-hCG that was sustained until 16 h post-hCG (post-ovulation) (Figure 1.14). An earlier in vitro study of human Fallopian tube supports this, with highest concentrations of PGR during the proliferative phase of the cycle [Pollow et al., 1981]. In contrast, another study in the mouse found that both isoforms of PGR peaked at 48 h post-eCG treatment and subsequent administration with hCG gradually decreased PGR protein in parallel with increasing levels of P4 [Shao et al., 2006].

In addition to PGR expression in luminal epithelial cells and smooth muscle cells, a relatively recent study has also identified PGR expression in interstitial Cajal-like cells (ICLC) in human Fallopian tube [Cretoiu et al., 2009]. In particular, PGR-A was identified by immunohistochemical staining in stromal ICLC in situ, as well as ICLC among smooth muscle cells in culture.

In the bovine oviduct, strong PGR staining has been localised to ciliated and secretory cells of the luminal epithelium and smooth muscle cells, although unlike the predominance of staining to cilia as mentioned above, staining was restricted to nuclei [Saruhan et al., 2011; Ulbrich et al., 2003; Valle et al., 2007]. Several studies have demonstrated cell-type and region-specific differences in staining

Lisa Akison 2012 61

Figure 1.14 PGR expression in the oviduct luminal epithelium. PGR protein (A-E) and mRNA (F) expression in cells of the oviduct luminal epithelium. A) Immunolocalisation of PGR (green) in oviduct sections from pre-pubertal females before gonadotrophin stimulation and B) 48 h eCG + 6 h hCG. Scales bars for A & B are 25 μm. C) Immunolocalisation of PGR (green) in a 3 month old C57Bl/6 estrous female. Scale bar is 50 μm. Insert shows a higher power image of the oviduct epithelium showing ciliated and secretory cells. Cilia are marked with an arrow head. Scale bar is 10 μm. D) PGR expression (green) in the oviduct at 48 h eCG + 16 h hCG (i.e. post-ovulation). Asterisks indicate cumulus cells from an ovulated COC. Scale bar is 25 μm. E) Ciliary immunolocalisation of PGR (green) in a tissue section (upper row, scale bar is 5 μm) and in an isolated ciliated epithelial cell (lower row). Cilia are stained red with anti-acetylated -tubulin and marked with arrowheads. Nuclei are stained blue with TO-PRO. Nuclear localisation of anti-PGR is indicated with asterisks. F) Blue X-gal staining indicates that the majority of PRlacZ mRNA expression is localised to the luminal epithelial cells (grey arrowhead), with a small number of smooth muscle cells also showing expression (black arrowhead). Scale bar represents 200 μm. Protein expression was detected using a monocolonal anti-PGR antibody (Clone SP2, stains green in A-E [Teilmann et al., 2006]). Pgr mRNA expression was demonstrated by the PRlacZ reporter mouse which expresses lacZ under the control of the endogenous Pgr promoter which is visualised by dark blue X-Gal staining (F, [Ismail et al., 2002]). For A-D, nuclei are stained with propidium idodide (red) and cilia are indicated with arrow heads. Adapted from [Teilmann et al., 2006] and [Ismail et al., 2002].

Lisa Akison 2012 62 intensity across the bovine reproductive cycle [Kenngott et al., 2011; Ulbrich et al., 2003; Valle et al., 2007], with studies generally reporting increased PGR expression in the epithelium during the follicular phase. However, a recent immunohistochemical study of PGR-B expression found no difference in the intensity of staining between the follicular and luteal phases or in the different regions of the oviduct [Saruhan et al., 2011]. Therefore, whether PGR isoforms are indeed induced by the LH surge in the oviduct remains to be clarified, and may indeed, as in the ovary, be species-specific.

1.6.2 The role of PGR in regulating oviductal function

While the function of PGR in the ovary, uterus and mammary gland has been well studied, its role and mode of action in the oviduct has not been definitively defined. Ovarian steroid hormones, including P4, have an impact on the oviduct by influencing the morphology and function of oviduct luminal epithelium, regulating muscular and nerve function, and regulating the volume and composition of fluids in the lumen (see [Hunter, 2011] for review). All of these influence and optimise oviductal transport of the newly ovulated COC, as well as transport and nourish the early embryo, to maximise the chance for successful implantation in the uterus. The role of PGR in many of these processes is implied, but is often not explicitly known. This section reviews what is known about P4/PGR regulation of ciliary function, muscular contraction and luminal fluids in the oviduct.

Reports of LH-induced expression of PGR in ciliated cells of the oviduct luminal epithelium suggest a regulatory role for P4 on ciliary beat frequency (CBF), and potentially oocyte and embryo transport. Cyclic changes in CBF are controlled by E2 and P4 levels which fluctuate throughout the cycle [Nishimura et al., 2010], as does expression of their cognate receptors in oviductal epithelial cells [Amso et al., 1994; Pollow et al., 1981; Teilmann et al., 2006]. These steroids have been shown to have opposing effects on oviduct cell CBF in vitro, with E2 accelerating and P4 decelerating movement [Mahmood et al., 1998; Nakahari et al., 2011]. Administration of mifepristone in vitro prevents the P4- induced reduction in CBF in human oviductal explants [Mahmood et al., 1998] and in vivo, at least in rodents, increases the transport of embryos through the oviduct resulting in their premature arrival into the uterus [Fuentealba et al., 1987; Vinijsanun and Martin, 1990]. Molecular targets of PGR involved in CBF are not known, but might include prostaglandins [Hermoso et al., 2001; Verdugo et al., 1980] or angiotensin II [Saridogan et al., 1996] and/or their cognate receptors, which are known to be produced by the oviduct and can regulate CBF in vitro. Similarly, Ca2+-activated transient receptor potential ion channels are up-regulated in ciliated oviductal epithelial cells following hCG stimulation [Teilmann et al., 2005] and may be a mechanism by which P4 elicits its well known rapid responses in ciliated cells. Both genomic and non-genomic progesterone receptors may be involved. For example, PGRMC1 has been localised to the luminal epithelia and muscle cells of the bovine oviduct, although it remains at Lisa Akison 2012 63 similar levels across the estrous cycle [Luciano et al., 2011]. Also, the newly described membrane progestin receptors β and γ (mPRβ, and γ) have been found to be exclusively expressed in ciliated cells of the oviduct and to be hormonally regulated [Nutu et al., 2009]. Several studies have suggested that P4 may be acting in the oviduct via these non-genomic pathways [Luconi et al., 2004; Peluso, 2006; Wessel et al., 2004]. For example, Wessel et al. [2004] showed that CBF was inhibited in bovine oviductal explants as soon as 15 minutes after treatment with P4, but pre-treatment with mifepristone did not affect this result in the short-term but nonetheless prevented the inhibitory influence of P4 after 24 h. The co-expression of classical PGR and membrane receptors in oviductal cells provides the possibility of a co-operative relationship in mediating cilia function.

Ab-ovarian waves of smooth muscle contraction in the oviductal wall are also believed to contribute to oviductal transport of the COC toward the ampulla and the embryo through the isthmus towards the uterus [Croxatto, 2002; Hunter, 2011]. Changes to the myosalpinx or muscular layer occur across the cycle, with increasing muscular tone a feature of the follicular phase or preovulatory phase and relaxation typical in the luteal phase. These changes are coordinated by ovarian steroids, with E2 resulting in muscular contraction and high levels of P4 or progestagens promoting relaxation [Helm et al., 1982; Wanggren et al., 2006; Wanggren et al., 2008]. Prostaglandin E2 and F2 (PGE2 and PGF2) receptors are expressed in luminal epithelial cells, muscle wall and vessels in the human Fallopian tube [Wanggren et al., 2006] and a subset of these receptors (specifically PTGER1, PTGER2 and PTGFR) was down-regulated in these cells and tissues after treatment with RU486 [Wanggren et al., 2006].

Muscular contractions were increased after treatment with PGE2 and PGF2 [Wanggren et al., 2008], and thus muscular contractility in the oviduct appears to be induced by prostaglandins and regulated by P4 and PGR. Endothelins (EDNs) have also been reported to play a role in both oviductal muscular contraction (by EDN1 and EDN2) as well as epithelial cell secretions (by EDN3) (see [Bridges et al., 2011] for review). Both EDN1 and EDN3 are locally produced by epithelial cells in the oviduct [Rosselli et al., 1994; Sakamoto et al., 2001] and the endothelin receptor isoform EDNRA has been specifically localised to the muscle layer while EDNRB is localised to the luminal epithelial cells [Jeoung et al., 2010; Sakamoto et al., 2001]. E2 but not P4 has been shown to stimulate production of EDN1 in vitro [Wijayagunawardane et al., 1999], but studies examining P4/PGR regulation of endothelin isoforms and their receptors in the oviduct are currently lacking. PGR in smooth muscle cells may also modulate the response by these cells to other myotropic agents, such as neurotransmitters produced distally (e.g. noradrenaline) or locally (e.g. neuropeptide Y, vasoactive intestinal polypeptide and substance P) [Croxatto, 2002], but regulation of these factors or their receptors by PGR in the oviduct has not been examined. In addition, the identification of PGR expression in interstitial Cajal-like cells (ICLC) in the oviduct [Cretoiu et al., 2009], which are connected to smooth muscle cells [Popescu et al., 2005], suggests these cells may also contribute to the regulatory effect of P4 on muscle contractility.

Lisa Akison 2012 64 The volume and composition of oviductal fluids change across the oestrous cycle. Fluid accumulation occurs during the follicular phase and the relative contributions of transudate from capillaries and active secretions by the luminal epithelium differs according to the stage of the cycle and the region of the duct [Hunter, 2011]. The regulation of oviductal fluid accumulation by ovarian steroids has been demonstrated in ovariectomised animals [McDonald and Bellve, 1969], but the relative contributions of E2 and P4 and the role that PGR may play in this regulation has not been addressed. Also, although the composition of oviductal fluid has been examined in detail [Aviles et al., 2010; Leese et al., 2008] (see also Table 1.1) and secretory products are known to vary across the reproductive cycle, the specific roles that P4 and PGR play in regulating these secretions has not been adequately addressed.

A recent review [Aviles et al., 2010] compiled a comprehensive list of molecules expressed and/or secreted by the oviduct across several mammalian species (see also Table 1.1). Many of these constituents, like the well known oviduct-specific glycoproteins, are probably E2-dependent [Buhi et al., 2000]; however, P4 may also play a role, as many of these products are at high concentrations during the periovulatory period and during the first days of pregnancy. Very few studies have examined PGR regulation of these products in the oviduct. One study, examining the regulation of cytokine expression in the human Fallopian tube after administration of mifepristone 2 days after the ovulatory LH surge [Li et al., 2004], measured IL8, TNF, TGFβ and LIF in the ampulla and isthmus regions using immunohistochemistry. Mifepristone had no effect on expression of TGFβ or LIF, but increased expression of TNF in the epithelial cells of the isthmus and decreased expression of IL8 in the epithelium of the ampulla. However, this study had small sample sizes (n = 7 per group) and used a simple scoring system for staining intensity which is difficult to analyse statistically. Other studies have examined the actions of P4 on oviductal genes and products, but not the role of PGR per se. For example, exogenous P4 regulated complement component 3 (C3) mRNA and protein expression in oviducts of ovariectomised mice but not in human oviductal epithelial cells from intact women in vitro [Lee et al., 2009]. The expression of C3 mRNA was highest in oviductal cells of pregnant mice at day 2 of pregnancy [Lee et al., 2009]. C3 is converted into the embryotrophic derivatives iC3b and C3b in the presence of embryos and oviductal cells [Tse et al., 2008]. Similarly, both plasminogen activator inhibitor 1 (PAI1) [Kouba et al., 2000] and tissue inhibitor of metalloproteinase 1 (TIMP1) [Buhi et al., 1997] were shown to be stimulated in oviductal cells by exogenous P4 in ovariectomised gilts and were highest at day 2 of pregnancy. PAI1 is hypothesised to play a role in protecting the oocyte/embryo from enzymatic degradation while the role for TIMP1 is unknown. Thus, there is some evidence that P4 regulates production of oviductal secretory products; however additional studies are needed, for instance in mouse models lacking PGR, to identify any direct regulatory roles that PGR may play in the expression/secretion and function of oviductal molecules in the luminal milieu during the earliest stages of embryogenesis.

Lisa Akison 2012 65 Thus, unlike the ovary, very little is known about PGR-regulated genes in the oviduct. To the best of our knowledge, the only putative targets identified so far, as demonstrated by PGR antagonist studies, are prostaglandin receptors (specifically PTGER1, PTGER2 and PTGFR) [Wanggren et al., 2006] and cytokines (specifically TNF and IL8) [Li et al., 2004].

1.7 Hypotheses & aims of project

1.7.1 Main hypothesis

The main hypothesis of the thesis is that:

Progesterone receptor regulates molecular processes in the ovary and oviduct required for successful ovulation, COC structure and function, and transport of the oocyte and early embryo.

Although there is a substantial knowledge base demonstrating many aspects of PGR regulation of ovulatory genes in the ovary and its critical requirement for ovulation, the specific mechanisms that are required for the expulsion of the COC from the periovulatory follicle following the LH surge, and the role that PGR plays in facilitating COC maturation and release have not been definitively identified. Further, the potential role of PGR in the oviduct during the periovulatory period and the specific molecular pathways and cellular functions that it regulates have not been adequately addressed. This study uses a diverse suite of molecular, surgical and cell biology techniques to interrogate the PRKO transgenic mouse model during the periovulatory period and thus examine why these mice have such a profound anovulatory phenotype.

1.7.2 Specific hypotheses & aims

Hypothesis 1: PGR affects the structure of preovulatory follicles in the ovary and the structure of the oviduct during the periovulatory period.

Specific structural characteristics typify the periovulatory ovary. However, no studies have systematically examined the structure of the PRKO preovulatory follicle during the periovulatory period, in the absence of functional PGR expression, to determine if there are any structural defects which may contribute to the observed anovulatory phenotype. In addition, the structure of the periovulatory PRKO oviduct has not been examined.

Lisa Akison 2012 66 Therefore, to address this hypothesis, the aims were to:

 Histologically compare preovulatory follicles of PRKO and PR+/- mice across the periovulatory window using ovarian sections. In particular, vascularity, COC expansion, granulosa cell and follicle wall thinning at the apex of the follicle, and basal invagination of the follicle wall were examined. Results for this aim are presented in Chapter 3.

 Compare the structure of the oviducts of PRKO and PR+/- mice across the periovulatory window using histological sections. In particular, muscle layer thickness and the distribution and abundance of ciliated and secretory cells in the epithelial layer were examined, specifically in the ampulla. Results for this aim are presented in Chapter 7.

Hypothesis 2: The anovulatory defect is intrinsic to the PRKO ovary.

As PGR is expressed in many non-reproductive and reproductive tissues, the systemic environment of the PRKO mouse may impact on ovarian function and contribute to the observed anovulatory phenotype. Thus, to address this hypothesis, the aims were to:

 Surgically transplant PRKO ovaries into normal (PRWT genotype), ovariectomised mice. Transplants of PRWT ovaries into PRWT, ovariectomised mice acted as surgical controls.

 Characterise and compare the structure of PRKO and PRWT transplanted ovaries by histological examination.

 Compare the function of PRKO and PRWT transplanted ovaries via a breeding study.

The experiments addressing this hypothesis are presented in Chapter 3.

Hypothesis 3: Inflammatory events are altered in the periovulatory PRKO ovary.

The process of ovulation shares many similarities with inflammation. This includes production of prostaglandins which are involved in the both the onset and resolution of inflammation, vasoconstriction and immune responses. One of the enzymes required for prostaglandin production, prostaglandin synthase 2 (PTGS2), is known to be required for ovulation. Thus the anovulatory phenotype of PRKO ovaries may be due to an altered immunological or inflammatory profile and/or altered expression of PTGS2 during the period immediately preceding ovulation. Further, there is evidence that immune cells are directly involved in follicle rupture. To address this hypothesis, the aims were to:

 Measure the expression of a suite of inflammatory genes in PRKO and PR+/- whole ovaries immediately prior to ovulation using Taqman Immune Arrays. This array included Ptgs2 as one of the genes of interest.

Lisa Akison 2012 67  Fully characterise the mRNA and protein expression of PTGS2 in whole ovaries, granulosa cells and COCs, specifically its induction by LH and regulation by PGR.

The experiments addressing this hypothesis are presented in Chapter 4.

Hypothesis 4: PGR regulates genes in granulosa cells which are necessary for follicle rupture and oocyte release during the periovulatory period.

As PGR is a nuclear transcription factor, much attention has been focussed on its down-stream target genes. However, no studies have examined PGR gene regulation specifically in granulosa cells at the time of peak PGR gene expression in the ovary (8 h post-hCG) during the periovulatory period. To address this hypothesis, the aims were to:

 Use microarray assays to conduct genome-wide investigations of PGR-regulated genes in granulosa cells isolated from PRKO and PR+/- ovaries at 8 h post-hCG.

 Identify differentially expressed genes associated with specific functions related to follicle rupture and oocyte release using Ingenuity Pathway Analysis.

 Validate a gene target and determine if it is induced by the ovulatory LH surge, specifically one not previously described in detail as PGR- and/or LH-regulated in the ovary. The gene chosen for this validation was the chemokine receptor, CXCR4.

 Determine whether the gene product is required for successful ovulation in mice using an in vivo inhibitor study.

The experiments addressing this hypothesis are presented in Chapter 5.

Hypothesis 5: The ovulatory LH surge and/or PGR regulate the migratory, invasive and adhesive properties of the cumulus oocyte complex (COC) during the periovulatory period.

Preliminary evidence suggests that cumulus cells adopt a migratory phenotype around the time of ovulation and thus may be able to adhere to and invade through extracellular matrix (ECM) proteins specifically found in the ovarian follicle wall. To address this hypothesis, the aims were to:

 Demonstrate the migratory, invasive and adhesive properties of the COC at various times after the ovulatory LH surge, including immediately post-ovulation, to determine the optimal conditions for this phenotype.

 Determine if preovulatory COCs from PRKO mice are defective in their ability to migrate and adhere to or invade through a specific ECM protein found in the follicle wall.

Lisa Akison 2012 68 The results of these experiments are presented in Chapter 6.

Hypothesis 6: Periovulatory COCs from PRKO mice have dysregulated gene expression.

This hypothesis tests whether the absence of PGR expression in granulosa cells results in down- stream alterations in gene expression in COCs isolated from PRKO ovaries. The aim used to address this hypothesis was to:

 Use microarray assays to conduct genome-wide investigations of PGR-regulated genes in COCs isolated from PRKO and PR+/- ovaries at 8 h post-hCG.

The results for this hypothesis are presented in Chapter 6.

Hypothesis 7: Periovulatory COCs from PRKO mice show altered matrix integrity and/or defects in the oocyte.

PGR is known to regulate ADAMTS1 expression in granulosa cells and ADAMTS1 is critical for formation of the extracellular matrix in the expanded cumulus oocyte complex. The extent of cumulus expansion in PRKO COCs was examined for Hypothesis 1. This hypothesis tests whether other aspects of the cumulus matrix, or the oocyte itself, are affected by the ablation of PGR in the periovulatory follicle. The aims used to address this hypothesis were to:

 Assess matrix integrity using a bio-assay to measure retention or loss of a secreted product,

prostaglandin E2 (PGE2), from the cumulus oocyte complex.

 Assess mitochondrial membrane potential in the oocyte, which has been linked to developmental competence.

The results for this hypothesis are presented in Chapter 6.

Hypothesis 8: PGR regulates genes in the oviduct during the periovulatory period required for COC and embryo transport.

PGR is highly expressed in the oviduct but its down-stream targets during the periovulatory period are not known. The aims were to:

 Use microarray assays to conduct genome-wide investigations of PGR-regulated genes in whole oviducts isolated from PRKO and PR+/- mice at 8 h post-hCG.

 Characterise the expression profile of PGR in mouse oviducts in response to the ovulatory LH surge.

Lisa Akison 2012 69  Identify differentially expressed genes associated with specific functions related to COC and embryo transport using Ingenuity Pathway Analysis.

 Validate specific gene targets and determine if they are induced by the ovulatory LH surge using real-time PCR.

The results for these experiments are presented in Chapter 7.

Lisa Akison 2012 70 Chapter 2 – Materials & Methods

2.1 Animals, hormone treatments & tissue collection

2.1.1 Animal strains and housing

The transgenic mouse strain used in this thesis was the PRlacZ knock-in mouse originally described by [Ismail et al., 2002]. These are a targeted (reporter) strain with the Jackson Laboratory designation Pgrtm1Lyd (targeted mutation 1, J.P. Lydon). See Figure 2.1 for how the gene is disrupted following insertion of neomycin and lacZ. The genetic background for this strain is 129S7 x C57BL/6. The full designation for the 129 strain is 129S7/SvEvBrd-HPrt1b-m2 [Festing et al., 1999]. These mice originated from the Baylor College of Medicine and their anovulatory phenotype, both in immature primed females and older mated females, was confirmed prior to use in experiments (see Section 2.1.3). Mice null for PGR are hereafter referred to as PRKO, heterozygous mice are referred to as PR+/- and wild-type mice are referred to as PRWT.

In addition, female CBA × C57BL/6 first filial generation (F1) hybrid mice (hereafter referred to as CBAF1) and C57Bl/6 mice were obtained from Laboratory Animal Services (University of Adelaide, Australia) and the Australian Research Council Animal Facility (Perth, Australia) at weaning (21 days old).

All mice were housed at the University of Adelaide Medical School Animal Facility and maintained on a 12 h light:12 h dark cycle with rodent chow and water provided ad libitum. All experiments were conducted in accordance with the National Health and Medical Research Council (NHMRC) Australian Code of Practice for the Care and Use of Animals for Scientific Purposes and were approved by the University of Adelaide Animal Ethics Committee.

2.1.2 Hormone treatments

To initiate follicle growth, mice were injected intraperitoneally (i.p.) at 21-23 days old with 5 IU of equine chorionic gonadotrophin (eCG; Calbiochem, Merck Pty Ltd, Kilsyth, VIC, AU) in 0.1 mL sterile saline. Ovulation was induced 44-48h later by injecting with 5 IU i.p. of human chorionic gonadotrophin (hCG; Calbiochem, Merck Pty Ltd, Kilsyth, VIC, AU) in 0.1 mL sterile saline. Using this regime, CBAF1 mice show greater than 50% of ovulations have occurred by 12 h and the number of ovulations peaks by 12.5 h post-hCG (Figure 2.2). Allowing for a 30 min lag between release from the follicle and appearance in the ampulla of the oviduct, this suggests ovulation was maximal around 12 h. Similarly,

Lisa Akison 2012 71

A NOTE: This figure/table/image has been removed to comply with copyright regulations. It is included in the print copy of the thesis held by the University of Adelaide Library.

Figure 2.1 Creation of the PRlacZ mouse and targeted disruption of the mouse PGR gene. A) Targeting vector for the positive-negative selection and reporter gene. Exon 1 is shown in red and exon 2 as a solid black box. The neomycin-resistant cassette (NEO) was cloned immediately 3’ to the lacZ reporter gene (LAC-Z) which was inserted downstream from the initiating methionine for PGR-B. The lacZ insertion resulted in removal of a 122-aa fragment containing the initiating methionine for PGR-A. HSV-TK = herpes simplex virus-thymidine kinase. The vector sequence is located at the 5’ end of the targeting vector. B) The wild-type, mPGR allele. Exon 1 and 2 as for A) and relevant restriction sites shown. C) Mutated (knock-out) PGR allele after homologous recombination between A) and B) showing insertion of LacZ and NEO into exon 1. Transcription of both PGR isoforms is disrupted and a severely truncated, non- coding PGR message results. Adapted from [Ismail et al., 2002].

Lisa Akison 2012 72

25 b b

20

15 ab ab

10

# COCs per oviduct (Mean ± SE)(Mean per oviduct # COCs 5

a 0 11.0 11.5 12.0 12.5 13.0 Time post-hCG (Hours)

Figure 2.2 Timing of ovulation in eCG + hCG stimulated CBA X C57Bl/6 (F1) female mice. Female mice (21-23 days old; n = 20) were injected i.p. with 5 IU of equine chorionic gonadotrophin (eCG) followed 44 h later with 5 IU human chorionic gonadotrophin (hCG). Ovulated cumulus oocyte complexes (COCs) were isolated from the oviducts at 11 h, 11.5 h, 12 h, 12.5 h or 13 h post-hCG, and counted. Data shows the mean (± SE) number of ovulated COCs per oviduct at each time point (n = 4 mice per time point). Different letters denote significantly different groups at P<0.01 by one-way ANOVA.

Lisa Akison 2012 73 the PRlacZ transgenic strain show the majority of ovulations have occurred at 12 h post-hCG (data not shown).

2.1.3 PRlacZ transgenic mouse genotyping

Mice were genotyped by PCR analysis of tail DNA. Genomic DNA was obtained by digesting tissue in 350 μl NTES Tail Digest Buffer and 4 l of 10 mg/ml Proteinase (Sigma-Aldrich Pty Ltd, Castle Hill, NSW, AU) at 55C for 2 h on a shaking incubator (180 rpm). Proteinase K was denatured by boiling 3

l of tail digest in 87 l Milli-Q H2O for 10 mins at 95C. DNA was amplified using primers specific for the PGR gene and the neomycin insert as shown below:

PGR sense 5’ – TAG ACA GTG TCT TAG ACT CGT TGT TG – 3’ PGR antisense 5’ – GAT GGG CAC ATG GAT GAA ATC – 3’ Neo 5’ – CTT CAC CCA CCG GTA CCT TAC GCT TC – 3’ Genotyping with the above primers was accomplished by a two-way PCR strategy. The Neo primer, within the selectable Neo gene, was used with a primer from the PGR gene to amplify a 110 bp product from the mutant allele (Figure 2.3). A 590 bp WT product was created using the 2 PGR primers (Figure 2.3). The components for the 25 l PCR reaction are shown in Table 2.1. For all genotyping PCR reactions, GoTaq Flexi DNA polymerase and associated buffers were used (Promega Corporation, Annandale, NSW, AU). The thermal profile for this PCR was: Hold at 94C for 3 mins, 35 cycles of 94C for 1 min, 60C for 2 mins and 72C for 3 mins, hold 72C for 10 mins, and hold at 4C. Reactions were amplified using an Applied Biosystems GeneAmp PCR System 9700 Thermal Cycler (Applied Biosystems, Mulgrave, VIC, AU). Amplified products were evaluated by agarose gel electrophoresis (see Section 2.2).

2.1.4 Preliminary verification of the PRKO phenotype

Given that these are the first experiments to be done with this particular colony of PRKO mice, I verified the anovulatory phenotype as reported by Lydon and others. This was done using histology to compare the structure of PRKO and PR+/- ovaries at 24 h post-hCG (i.e. ~12 h after ovulation should have occurred) (Figure 2.4). For details on histological methods, see Section 2.6. Briefly, ovaries were fixed in 4% paraformaldehyde, processed, embedded in paraffin, sectioned and stained with haematoxylin and eosin (H & E). PR+/- ovaries show numerous corpora lutea and no COCs, indicating that ovulation has proceeded normally. PRKO ovaries, however, show entrapped yet expanded COCs

Lisa Akison 2012 74

Genotype

+/+ +/- -/-

Wild-type band 590 bp

Neomycin band 110 bp

Figure 2.3 PCR products for genotyping PGR transgenic mice. +/+ = homozygous wild type; +/- = heterozygous; -/- = homozygous knockout. The heterozygous mouse is a phenocopy of the wild type and lacZ is a reporter of PGR expression (as used by [Ismail et al., 2002]). The homozygous knockout is a phenocopy of the original PRKO mouse described by [Lydon et al., 1995].

Table 2.1 Progesterone receptor transgenic mouse genotyping PCR reaction. Primer sequences are reported in text.

Reagent/Stock Final Volume per 1X (concentration) concentration reaction (μl)

PCR Buffer (5X) 1X 5

MgCl2 (25 mM) 2 mM 2 dNTPs (each 25 mM) 0.25 mM 0.25 PR sense (20 μM) 1.2 μM 1.5 PR antisense (20 μM) 1.2 μM 1.5 Neo (20 μM) 0.6 μM 0.75 GoTaq (5 U/μl) 1 U 0.2

H2O 11.8 Genomic DNA 2 Total 25

Lisa Akison 2012 75

A) PR+/- ovary, 24 h post-hCG B) PRKO ovary, 24 h post-hCG

Figure 2.4 Histology of PRKO and PR+/- mouse ovaries at 24 h post-hCG. One section from one representative ovary from each genotype are shown. A) PR+/- ovary; B) PRKO ovary. This was used to confirm the anovulatory phenotype of the PRKO females.

Lisa Akison 2012 76 in luteinized follicles. This is as described in previous studies using PRKO mice [Lydon et al., 1995; Robker et al., 2000]. Ovulation rates were also compared for PRKO and PR+/- females in hormonally primed, pre-pubertal females (Figure 2.5A) and in naturally mated, older, cycling females paired with stud males (Figure 2.5B). Only two of the PRKO females primed with hormones had only 1 or 2 COCs present in the oviduct (Figure 2.5A). None of the naturally mated, older PRKO females had any ovulated COCs in the oviduct (Figure 2.5B). Thus, the anovulatory phenotype of the PRKO colony was confirmed.

2.1.5 Isolation of COCs, granulosa cells and whole tissue collection

Immature, unexpanded COCs were collected by puncturing antral follicles from ovaries collected at 44- 48 h post-eCG with a 30-gauge needle. Pre-ovulatory COCs were collected from antral follicles in the same manner at 4-12 h post-hCG (see individual chapters for details). Granulosa cells were collected in the same manner and at the same time points as COCs. Mature, ovulated COCs were isolated from the ampulla region of the oviduct by dissection of the oviduct wall at 12 h and 14 h post-hCG. All isolations were conducted in HEPES-buffered α-MEM (GIBCO, Invitrogen Australia Pty. Ltd., Mulgrave, VIC, AU) supplemented with 5% (v/v) fetal calf serum (FCS; JRH Biosciences, Kansas City, MO, USA) at 37ºC unless specified otherwise. Cells and tissues isolated for RNA had no FCS added to the media. Typical COCs from time course collections over the pre- and postovulatory period are shown in Figure 2.6. For most experiments, COCs were pooled from at least 6 animals for each independent experiment. Preovulatory and postovulatory whole ovaries and oviducts were collected via dissection.

2.2 Gel electrophoresis

PCR products were separated by agarose gel electrophoresis. Each gel contained 1.5% (w/v) agarose (Promega Corporation, Annandale, NSW, AU) in 0.5X TBE Buffer and 1 μg/ml ethidium bromide or 1X Gel Red nucleic acid stain (Biotium, Jomar Bioscience, Kensington, SA, AUS). Electrophoresis was performed in 0.5X TBE buffer at 90V. Samples were run alongside a 100 bp DNA ladder (Promega Corporation, Annandale, NSW, AU) to confirm the size of resolved DNA fragments. Gels were visualised and photographed using a UV transilluminator and gel documentation system (Kodak DC120).

Lisa Akison 2012 77

50

40 ** 30

20 # COCs (Mean SE)+ (Mean # COCs 10 ***

0 PR+/- PRKO PR+/- old PRKO old n = 8 n = 11 n = 6 n = 10 (A) Primed females (B) Naturally mated

Figure 2.5 Breeding performance of PRKO and PR+/- mice. A) Pre-pubertal mice were primed with eCG and hCG and COCs were dissected from the oviduct at ~22 h post-hCG and counted. The number of COCs in PR+/- oviducts was significantly greater than in PRKO by Student’s t-test (P = 0.004). B) Naturally mated older mice (~5 months old) were paired with a stud male, checked for a vaginal plug to confirm mating and then the oviduct was checked for ovulated COCs. The number of COCs in PR+/- oviducts was significantly greater than in PRKO by Student’s t-test (P = 0.001).

Lisa Akison 2012 78

Figure 2.6 Morphology of COCs following exposure to hCG in vivo. COCs were punctured from antral follicles at A) 48 h post-eCG, B) eCG + 4 h post-hCG, C) eCG + 8 h post-hCG, D) eCG + 10 h post-hCG and E) eCG + 12 h post-hCG. Ovulated COCs were collected from the ampulla region of the oviduct at F) eCG + 12 h post-hCG and G) eCG + 14 h post-hCG. Note that E) and F) were often collected from the same animal, as eCG + 12 h post-hCG approximately coincides with ovulation in CBA F1 strain mice. A-C were taken at 20X magnification; D-G were taken at 10X magnification.

Lisa Akison 2012 79 2.3 RNA extraction & purification

Tissue samples were added to 500 μl (COCs) or 1 ml (granulosa cells and oviducts) Tri Reagent® (Sigma-Aldrich Pty Ltd, Castle Hill, NSW, AU) and either vortexed (COCs) or homogenised (granulosa cells and oviducts) using a Precellys 24 tissue homogeniser (Sapphire Bioscience, Waterloo, NSW, AU). Total RNA was isolated from tissue samples using a modified Tri Reagent® protocol, which included an overnight precipitation step at -20C and the addition of 1 μl Ambion GlycoBlue™ (15 mg/ml; Applied Biosystems, Mulgrave, VIC, AU) during precipitation to allow for visual detection of the RNA pellet. The final pellet was dissolved in 20 μl (COCs) or 25 μl (granulosa cells and oviducts) of ultrapure water. To eliminate potential contamination by genomic DNA, all samples were DNase- treated using Ambion DNA-free™ (Applied Biosystems, Mulgrave, VIC, AU) according to the manufacturer’s instructions. RNA concentration and purity were quantified using a Nanodrop ND-1000 Spectrophotometer (Biolab Ltd, Clayton Vic, Australia). To ensure that the genotype of all PR+/- and PRKO samples were correct, 300 ng of RNA was reverse-transcribed as described in Section 2.4. The cDNA was genotyped using the PGR Genotyping PCR Protocol (Section 2.1.3) and products visualised using gel electrophoresis (Section 2.2). cDNA was also tested for Rpl19 expression using real-time PCR as detailed in Section 2.4 as a further test of sample homogeneity within treatments.

2.4 Real time RT-PCR

First strand complementary DNA (cDNA) was synthesised from 300-1000 ng of total RNA (see individual chapters for specific amounts) using random hexamer primers (250 ng/μl; Roche Diagnostics Pty Ltd, Castle Hill, NSW, AU) and Superscript III Reverse Transcriptase (GIBCO Invitrogen Australia Pty. Ltd., Mulgrave, VIC, AU) according to the manufacturer’s instructions. The absence of contaminating genomic DNA was confirmed by running a control sample lacking Superscript™ III RT enzyme. Gene primers for real time RT-PCR were Quantitect Primer Assays (Qiagen, Doncaster, VIC, AU) or self-designed primer sets (all primers used in this thesis are summarised in Table 2.2). Complementary DNA templates were subjected to fluorometric semi-quantitative real-time PCR in triplicate using the Rotor-Gene™ 6000 real-time rotary analyser (Qiagen, Doncaster, VIC, AU) with Power SYBR® Green PCR Master Mix (Applied Biosystems, Mulgrave, VIC, AU). Ribosomal protein L19 (Rpl19), which is commonly used as an endogenous control gene for studies on mouse ovaries (e.g. [Salmon et al., 2005; Trombly et al., 2009]), was used as an internal control for every sample. All primers were verified for comparable amplification efficiency against the internal control. Each 20 μl reaction contained cDNA from 10 ng total RNA (at 5 ng/μl), 2.5 μl of Quantitect Primer (or 0.2 μl each of 50 μM sense and antisense self-designed primers), 10 μl of Power SYBRgreen Master Mix and water. Lisa Akison 2012 80

Table 2.2 Primers used throughout thesis for real-time PCR validation of gene expression. Qiagen Quantitect primers were used for most genes. Exceptions were Pgr, which had primers designed in-house to the region deleted in the PRKO mouse (see Figure 2.1); and Ptgs2, which used primers designed in-house for examining expression in the ovary and Quantitect primers for examining expression in the oviduct.

Gene name Gene Qiagen Cat. # or Primer Amplicon Accession symbol Sequence size (bp) Number(s) Ribosomal protein L19 Rpl19 Mm_Rpl19_1_SG 94 NM_009078 Chemokine (C-X-C motif) receptor 4 Cxcr4 Mm_Cxcr4_1_SG 106 NM_009911 Chemokine (C-X-C motif) ligand 12 Cxcl12 Mm_Cxcl12_1_SG 71 NM_021704, NM_013655 Integrin  8 Itga8 Mm_Itga8_1_SG 70 NM_001001309 A disintegrin-like and metallopeptidase with Adamts1 Mm_Adamts1_1_SG 130 NM_009621 thrombospondin type 1 motif, 1 Endothelin 3 Edn3 Mm_Edn3_1_SG 140 NM_007903 Prostaglandin-endoperoxide Ptgs2 Mm_Ptgs2_1_SG 95 NM_011198 synthase 2 Smooth muscle actin γ 2 Actg2 Mm_Actg2_1_SG 109 NM_009610 Oviductal glycoprotein 1 Ovgp1 Mm_Ovgp1_1_SG 104 NM_007696

Prostaglandin-endoperoxide Ptgs2 - F CTGGGCCATGGAGTGGAC 93 NM_011198 synthase 2 Ptgs2 - R CCTCTCCACCAATGACCTG

Progesterone receptor Pgr - F CTTAGACTCGTTGTTGACTCC 134 NM_008829 Pgr - R CTTTGGTAGCAGGGACACT

Lisa Akison 2012 81 PCR thermal conditions were: 50C for 2 mins, 95C for 10 mins, and 40 cycles of 95C for 15 secs followed by 60C for 60 secs. A final melt at 60-95C was performed and dissociation curves analysed to confirm single product amplification. PCR products were also confirmed on a 1.5%/0.5X TBE agarose gel stained with ethidium bromide (see Section 2.2). A No Template Control (NTC) was included for each gene to confirm absence of contamination. Whole ovary (10 h post-hCG) or whole oviduct (10 h post-hCG; Chapter 7 only) was used as the calibrator sample and gene expression was expressed as fold change relative to the calibrator using the CT Method [Livak and Schmittgen, 2001]. Results were normalised to a PR+/- sample which was set to a mean fold change of 1.0 (see individual chapters for details).

2.5 Microarray

Microarray requires that high quality RNA is extracted from the samples of interest, that this RNA is reverse-transcribed and labelled, hybridised to the gene array, the array is stained and scanned, and finally that the resulting gene expression data set is analysed. For a general review of microarray standard operating procedures, refer to Forster et al. [2003]. Details for the RNA extraction protocol are given in Section 2.3.

2.5.1 Microarray sample preparation, hybridisation and scanning

Affymetrix GeneChip® Mouse Gene 1.0 ST Arrays (Affymetrix, Santa Clara, CA, USA) were used to analyse differential gene expression across the genome for PRKO and PR+/- samples. This array contains 28,853 genes with approximately 27 probes distributed evenly across each transcript, allowing unbiased analysis of expression. Gene-level analysis of multiple probes on different exons is summarised into an expression value representing all transcripts from the same gene.

For details of the RNA used for each microarray experiment, refer to the individual chapters and Appendix 2. Final pooled samples were checked for RNA integrity (RIN) by the Adelaide Microarray Centre (AMC) using an Agilent Bioanalyzer (Agilent Technologies, Santa Clara, USA; Appendix 2) and were considered acceptable for microarray analysis at a minimum threshold of 7-7.5 (M. Van der Hoek, AMC, pers. comm.). Sample preparation, array hybridisation and scanning were performed by the AMC using Affymetrix GeneChip® Kits (Affymetrix, Santa Clara, CA, USA) according to the manufacturer’s instructions. Briefly, 100 ng total RNA underwent reverse transcription to synthesise double-stranded cDNA using the GeneChip® Whole-Transcript (WT) cDNA Synthesis and Amplification . This cDNA was amplified using T7 RNA polymerase to produce antisense cRNA, which was Lisa Akison 2012 82 reverse transcribed in a second cycle of cDNA synthesis incorporating dUTP into the cDNA sequence. This random-primed, single-stranded cDNA was then fragmented using uracil DNA glycosylase (UDG) and apurinic/apyrimidinic endonuclease 1 and labelled with biotin-conjugated nucleotides in the final in vitro transcription reaction using the GeneChip® WT Terminal Labeling Kit. Following biotinylation, samples were hybridised overnight to the gene arrays. The arrays were washed, stained using a fluorescently-labelled antibody and scanned using a high resolution scanner (Affymetrix GeneChip Scanner 3000 7G Plus).

2.5.2 Microarray data analysis

Microarray data were analysed by the AMC using Partek® Genomics Suite™ software (Partek Incorporated, St Louis, MI, USA). Background correction was performed by robust multichip averaging followed by probe affinity adjustment for the variable G-C content of probes. Quantile normalisation was performed to remove systematic variations resulting from array preparation or sample hybridization conditions. A mean probe-set summary was obtained by averaging the intensity values for the multiple probes representing an individual gene. Linear modelling statistics using a mixed model Analysis of Variance (ANOVA) was used to compare PRKO to PR+/- samples for every gene, with a False Discovery Rate (FDR) correction made for multiple testing to reduce the chance of Type I errors (i.e. false positives). Gene expression was considered significantly different between genotypes at P<0.05 and is presented as fold change of PRKO samples relative to PR+/- samples. Negative fold change indicates down-regulation; positive fold change indicates up-regulation. Principal Component Analysis (PCA) was used to summarise the gene expression data for each sample array and to examine the variability amongst arrays within genotype for each tissue/cell type (for more information on the use of PCA to analyse microarray datasets see [Raychaudhuri et al., 2000]). Mapping the data to three dimensions in this way allowed a visual comparison of how similar each sample was within and between treatments. Volcano plots were used for each microarray dataset to identify the number of genes with large magnitude fold changes (i.e. high biological significance) and/or high statistical significance [Cui and Churchill, 2003]. These were constructed by plotting the –log10 of the significance values (i.e. step-up P-values) on the Y-axis versus the log2 of the fold change values on the X-axis for each gene. The log of the fold change is used so that up- and down-regulated genes can be identified and are equidistant from the centre of the plot. By plotting the -log10 for the significance values, genes with low P-values (i.e. highly significant) appear towards the top of the plot. For each cell type/tissue, data sets containing genes that were differentially expressed between the two genotypes were imported into the Ingenuity Pathway Analysis software (IPA; Ingenuity Systems, Redwood City, CA, USA) to determine significant associations with biological functions.

Lisa Akison 2012 83

2.6 Histology

2.6.1 Tissue preparation and sectioning

Tissues were collected from mice and placed directly in freshly-made 4% paraformaldehyde in phosphate buffered saline (PBS) and fixed at 4C for 24-48 h. Following fixation, tissues were washed briefly in PBS before transferring to embedding cassettes and storing at 4C in 70% ethanol until processed and embedded. Tissues were processed using the Tissue-Tek VIP5 Jr Vacuum Infiltration Processor (Sakura-Finetek, Japan) by the Histology Service at the Discipline of Anatomy and Pathology, University of Adelaide, using the following dehydration and processing protocol:

1 h 70% EtOH 2 x 1 h 80% EtOH 30 min 95% EtOH (1) 1 h 95% EtOH (2) 2 x 90 min Absolute EtOH 1 x 1 h, 2 x 2 h Histolene 2 x 2 h Paraffin wax under vacuum conditions Tissues were embedded in paraffin wax blocks and cut in 5 μm sections using a Leica Rotary Microtome (Leica Microsystems, North Ryde, NSW, AU). Sections were fixed to Superfrost Plus slides (HD Scientific Supplies Pty Ltd, Wetherill Park, NSW, AU) using a 45C water bath and dehydrated overnight at 37C.

2.6.2 H & E staining and image capture

Slides were de-waxed using xylene (2 x 5 mins), hydrated in decreasing concentrations of ethanol (absolute, 90%, 70%, 50%, milliQ water) and then stained with haematoxylin and eosin (H & E, Sigma- Aldrich Pty Ltd, Castle Hill, NSW, AU). Sections were dehydrated in ethanol, cleared using xylene and then cover-slipped using Pertex mounting medium (HD Scientific Supplies Pty Ltd, Wetherill Park, NSW, AU).

All images were captured at 40X resolution using the NanoZoomer HT Digital Pathology System (Hamamatsu Photonics K.K., Japan). Images were then viewed using NDP View (Digital slide viewer, Hamamatsu Photonics K.K., Japan), bitmap images created at various magnifications and composite images created using Adobe Photoshop 7.0.

Lisa Akison 2012 84

2.7 Immunohistochemistry

Tissues were fixed, processed, embedded in paraffin and sectioned as described in Section 2.6.1. Sections were dewaxed in xylene and rehydrated through graduated dilutions of ethanol with a final wash in PBS. Antigen retrieval was performed by boiling slides in 10 mM citrate buffer antigen retrieval solution for 20 mins at 90ºC. Slides were washed in PBS and then incubated in 3% hydrogen peroxide

(H2O2) for 10 mins at room temperature (RT) to quench endogenous peroxidase activity. Slides were washed with PBS followed by PBST and then sections were blocked with 10% serum (from the host species of the secondary antibody, i.e. goat serum) in PBST for 1 h at RT. Sections were then incubated with primary antibody diluted in 1% serum (from the host species of the secondary antibody) overnight in a humid chamber. Slides were washed well with PBST and then incubated with biotinylated secondary antibody (goat--rabbit IgG; Vector Laboratories, Burlingame, CA, USA) diluted 1:500 in 10% serum (from the host species of the secondary antibody) for 1 h in a humid chamber. Slides were washed well in PBST and PBS and then incubated with Streptavidin-conjugated horseradish peroxidase (HRP) (Vectastain ABC Elite Kit, Vector Laboratories, Burlingame, CA, USA) for 1 h in a humid chamber. Slides were washed well with PBS and then stained using diaminobenzadine (DAB, Vector Laboratories, Burlingame, CA, USA) according to the manufacturer’s instructions. Sections were counterstained with 10% haematoxylin, dehydrated in increasing concentrations of ethanol, air-dried and cover-slipped using Pertex mounting medium (HD Scientific Supplies Pty Ltd, Wetherill Park, NSW, AU). Negative controls had the primary antibody omitted. Slides were digitally captured using the Nanozoomer HT as described in Section 2.6.2.

2.8 Real-time cell adhesion assays

Adhesion of COCs to various extracellular matrices (ECMs) was determined using the xCELLigence Real-Time Cell Analyzer (RTCA) DP instrument (Roche Diagnostics, Indianapolis, IN, USA). The xCELLigence RTCA DP instrument electronic plate (E-plate 16) incorporates micro-electronic sensors into the bottom of each well. The change in electrical impedance measured by electrodes allows dynamic monitoring of cell interaction with the substratum over time [Solly et al., 2004]. Wells were coated with matrices previously identified as components of the ovarian follicle wall; collagens, fibronectin and laminin [Berkholtz et al., 2006a; Berkholtz et al., 2006b; Figueiredo et al., 1995; Frojdman et al., 1998; Lind et al., 2006a; van Wezel et al., 1998; Yamada et al., 1999; Zhao and Luck,

1995]. All ECMs were incubated for a minimum of 4 h at 37°C/5% CO2. Wells were washed with PBS and then pre-incubated with 50 μl/well of serum-free media (SFM, αMEM media supplemented with 250 Lisa Akison 2012 85 μM pyruvate; GIBCO Invitrogen Australia Pty. Ltd., Mulgrave, VIC, AU) for 1 h at 37°C/5% CO2. Ten COCs were added to each well in 50 μl of SFM. The extent of cell adhesion and spreading was measured using the RTCA DP instrument every 3 min for a minimum of 12 h. Adhesion index was calculated from Rn – Rb, where Rn is the cell-electrode impedance of the well when it contains cells and

Rb is the background impedance of the well with media alone.

2.9 Real-time cell migration and invasion assays

Cell invasion and migration assays were performed using the xCELLigence Real-Time Cell Analyzer (RTCA) DP instrument (Roche Diagnostics, Indianapolis, IN, USA). The cellular invasion/migration plate (CIM-plate 16) uses micro-electronic sensors on the underside of an 8 μm microporous polyethylene terephthalate (PET) membrane of a Boyden-like upper chamber. Cells migrating from the upper chamber through the membrane interact and adhere to the electronic sensors, thus causing an increase in electrical impedance [Solly et al., 2004]. Changes in cell impedance over time indicate the change in the number of cells interacting with electrodes, therefore allowing automatic and continuous measurement of migration. For invasion assays, the upper surface of the membrane was pre-coated with 20 μl of rat tail collagen type I at 400 μg/mL (Coll I; BD Biosciences, Bedford, MA, USA), incubated at 37°C/5% CO2 for 4 h, then washed with PBS. For all migration and invasion assays, 160 μl of αMEM media supplemented with 250 μM pyruvate, 3 ng/ml EGF and 5% FCS was added to the lower chamber of each well and 50 μl of SFM (αMEM media supplemented with 250 μM pyruvate) to the upper chamber and the plate pre-incubated for 1 h at 37°C/5% CO2. COCs were collected from at least 10 mice at each time point then pooled and twenty intact COCs were distributed into the upper chambers with an additional 50 μl of SFM. Cumulus cell migration and invasion were monitored using the RTCA DP instrument, taking cell impedance readings every 10 min for a minimum of 14 h.

Migration index in uncoated or through Coll I coated wells (invasion) was calculated from Rn – Rb

(where Rn and Rb are defined above). Invasion index was calculated by dividing the migration index measured in wells coated with Coll I with the migration index measured in wells with no ECM coating at 6 h and multiplying by 100, providing a percentage of migratory cells that were also invasive.

2.10 Statistical analyses

Most experiments were analysed using a one- or two-way analysis of variance (ANOVA) with the Holm- Sidak post-hoc multiple comparison procedure to determine significant differences between groups. Where only two groups were being compared, the Student’s t-test (either paired or unpaired as

Lisa Akison 2012 86 required) was used. Before analysis, all data sets were tested for a normal distribution and homogeneity of variances using the Kolmogorov-Smirnov test. Data were log- or square root- transformed where required to normalise the distribution. All analyses were performed using the Sigmaplot 11.0 graphing and statistical package (Systat Software Inc., Chicago, USA).

2.11 Solutions

All reagents obtained from Sigma-Aldrich Pty Ltd (Castle Hill, NSW, AU) unless specified otherwise.

NTES tail digest buffer (pH 8.0) Reagent/Stock Final Volume per 1X (concentration) concentration solution (mL) Tris pH 8.0 (1 M) 50 mM 5 EDTA pH 8.0 (0.5 M) 50mM 10 NaCl (5 M) 100mM 2 SDS (20%) 1% 5

MilliQ H2O 78 Total 100

TBE buffer (pH 8.0) Final Reagent/Stock concentration Grams/mL per 5X (concentration) in 1X solution stock solution Tris 89 mM 54 g Boric Acid 89 mM 27.5 g EDTA pH 8.0 (0.5 M) 2mM 20 mL

MilliQ H2O To 1 L

Phosphate Buffered Saline (PBS; pH 8.0) Final concentration Grams per 10X Reagent in 1X solution solution

Na2HPO4.2H20 80 mM 142.4 g

NaH2PO4.2H20 20 mM 31.2 g NaCl 100 mM 58.4 g

MilliQ H2O to 1 L

Lisa Akison 2012 87 4% Paraformaldehyde Paraformaldehyde 2 g PBS 50 mls NaOH (10 M) 200 μl Warm (do not boil) to dissolve. Adjust pH to 7.0-7.5 using concentrated HCl. Store at 4C and use within 4 days.

PBST To 1 L of 1X PBS add 250 μl Tween-20 (0.025%)

0.1 M Citric Acid Solution Citric Acid (FW = 192.12 g/L) 1.9212 g of citric acid

100 ml H2O

0.1 M Sodium Citrate Solution Sodium Citrate tribasic dehydrate (FW = 294.1 g/L) 13.2345 g of Sodium Citrate

450 ml H2O

Citrate Buffer Antigen Retrieval Solution (pH 6.0) Reagent/Stock Final Volume per 1X (concentration) concentration solution (mL) Citric acid (0.1 M) 1.8 mM 9 Sodium citrate (0.1 M) 8.2 mM 41

MilliQ H2O 450 Total 500

MEM and MEM HEPES media 1. Dissolve a 1 L sachet of MEM powder (GIBCO Invitrogen Australia Pty. Ltd., Mulgrave, VIC, AU) in 200 mL of MilliQ water. 2. Place 100 mL each into 2 beakers/volumetric flasks and label. Add the following to each: MEM MEM HEPES

NaHCO3 (Bicarb) 1100 mg 252 mg HEPES - 2380 mg Streptomycin Sulphate 25 mg 25 mg Penicillin G (potassium salt) 37.5 mg 37.5 mg 3. pH to 7-7.1. Make up volumes to 500 ml with Milli Q. Filter sterilise and store at 4C for a maximum of 2 weeks. Lisa Akison 2012 88

Chapter 3 – Phenotype of the PRKO ovary at the time of ovulation

3.1 Introduction

PRKO mouse models dramatically demonstrate the critical role of PGR in ovulation. These mice have a profound and complete anovulatory phenotype, even when hyperstimulated with exogenous gonadotrophins, resulting in oocytes entrapped within follicles ([Lydon et al., 1995; Robker et al., 2000] and Figures 1.13 & 2.4). This has been observed at 13, 24 and 48 h post-hCG ([Lydon et al., 1995; Robker and Richards, 2000; Robker et al., 2000] and see also Section 2.1.4), after ovulation has occurred in phenotypically normal PR+/- mice. This is despite apparently normal growth and development of follicles and oocytes up to the antral stage, and a normal response to the LH surge as demonstrated by the presence of cumulus expansion and granulosa cell luteinisation [Lydon et al., 1995; Robker et al., 2000]. Therefore, PGR does not appear to be required for follicle growth and development or granulosa cell differentiation or luteinisation, but is specifically and absolutely required for LH-induced rupture of the preovulatory follicle and ovulation. However, aside from examination of ovarian morphology during what would normally be the postovulatory period, there has been no detailed morphometric analysis of PRKO ovaries during the periovulatory period to attempt to identify specific morphological defects. This might provide a better understanding of the role of PGR in follicle rupture and oocyte release.

Therefore, the primary aim of this chapter was to compare the gross histology of ovaries from PRKO and PR+/- mice at early time points after hCG administration, when the ovary is rapidly changing in the lead up to ovulation. As discussed in detail in Section 1.2.2, the periovulatory ovary has characteristic structural features. In particular, there are large, antral, preovulatory follicles in the cortical region; expansion of cumulus cells in the COC within preovulatory follicles; increased vascularisation in the stroma of the medulla and in the theca layer surrounding preovulatory follicles; thinning of all layers of the apical follicle wall; and structural remodelling of the basal follicle wall. All of these were examined in detail in ovarian sections from multiple animals of both PRKO and PR+/- genotype at 8 h, 10 h and 12 h post-hCG. In addition, the structure of the ovary immediately post-ovulation, at 14 h post-hCG, was examined during the time when corpus luteum formation is occurring in normal mice. The follicles containing mature, entrapped oocytes were examined for any anomalies in the structural characteristics described above. In addition, the location of expanded COCs within these follicles was examined to determine if they were associated with the basal or apical follicle wall or whether they had a more central position. Our working hypothesis of active participation of the COC in facilitating oocyte release Lisa Akison 2012 89

(detailed in Chapter 1) requires the close juxtaposition of the COC with the apical follicle wall to allow adhesion to exposed ECM components and invasion facilitated by proteases present in the cumulus matrix.

By far the highest expression of PGR occurs in female reproductive tissues, specifically the uterus, ovary, oviduct, and mammary gland [Gadkar-Sable et al., 2005; Ismail et al., 2002]. However, it also shows widespread expression in tissues from other systems [Bookout et al., 2006; Uotinen et al., 1999]. This includes high expression in the central nervous system, including the hypothalamic neurons and LH-secreting cells of the pituitary in the brain [Bethea et al., 1996], and moderate expression in metabolic, immune, cardiovascular and adipose tissues. For example, steroid receptors, including PGR, are expressed in adipose tissues (both brown and white) and adiposity is thought to be regulated by their respective steroid ligands [Mayes and Watson, 2004; Rodriguez-Cuenca et al., 2007; Rodriguez-Cuenca et al., 2005]. With respect to immune cells, PGR has been found to be expressed in leukocytes from kidney, liver, spleen and thymus by flow cytometry [Butts et al., 2010]. As mentioned briefly in Chapter 1, and discussed in more detail in the next chapter, an inflammatory reaction in the ovary is typical during ovulation, with infiltration of leukocytes a key feature of the periovulatory period [Brannstrom and Enskog, 2002; Espey, 1980; Richards et al., 2002a]. An intriguing hypothesis put forward by Oakley et al. [2010] is that the source of these leukocytes is possibly the spleen. They found, using flow cytometric analysis of both total number and specific subsets of immune cells in rats, a decrease in leukocyte numbers in the spleen concomitant with the dramatic increase in leukocyte number in the ovary just prior to ovulation. Further, they demonstrated a reduced influx of leukocytes to the ovary in splenectomised rats. Given the pleiotropic functions of P4/PGR in mammalian reproduction, it has been proposed that P4 may also play a role in regulating leukocyte infiltration from the spleen to the ovary [Hedin, 2010]. PGR is also expressed in thymic epithelial cells and is required for thymic involution which occurs during pregnancy, resulting in a general blockade of lymphocyte development [Tibbetts et al., 1999]. This appears to be important for maternal immune regulation and prevention of foetal loss, as PRKO thymus transplants into normal mice followed by embryo transfers resulted in increased resorptions and unimplanted embryos and less viable embryos when compared with wild-type controls [Tibbetts et al., 1999].

Our PRKO mouse model has ablation of PGR protein in all tissues, and therefore the relative contribution of PGR loss in the ovary versus other tissues to the observed anovulatory phenotype is not known. There is a possibility that the knockdown of PGR, particularly in tissues from the immune system or involved in the hypothalamic-pituitary axis that controls gonadotrophin release, may impact on ovarian function. Moreover, the impact of obesity [Gosman et al., 2006; Metwally et al., 2007; Rachon and Teede, 2010; Robker et al., 2011] and diabetes [Livshits and Seidman, 2009; Rachon and

Lisa Akison 2012 90

Teede, 2010] on reproductive health highlights the link between non-reproductive (in this case, metabolic) systems and fertility. Although a PGR conditional excision allele has been generated using loxP sites [Hashimoto-Partyka et al., 2006], which would allow knockdown of PGR in specific cell types, a granulosa cell-specific knockout for PGR, using an Amhr2Cre/+ transgenic mouse for example, has not been created to-date. Thus, in order to determine if the anovulatory phenotype is due to intrinsic defects in the ovary versus extrinsic systemic defects, the second aim of this chapter was to conduct orthotopic transplant experiments in which PRKO ovaries were transplanted into ovariectomised, PRWT mice followed by examination of ovarian function.

The first study to provide a detailed description of orthotopic ovarian transplants in mice was conducted over 50 years ago [Jones and Krohn, 1960], and since then, the technique has been widely adopted to rescue the germ line of mutant or transgenic female mice with low fertility using cryopreserved or fresh ovaries [Brem et al., 1990; Cox et al., 1996; Gunasena et al., 1997; Sztein et al., 1998]. More recently, xenotransplantation of ovaries from one species to another is being considered for conservation of rare and endangered species [Paris et al., 2004] and in humans, transplantation of cryopreserved ovarian tissue, collected prior to chemotherapy treatment, can restore fertility to cancer patients [Donnez et al., 2004; O'Hanlon, 2004]. This technique has also been used in studies of potential regulators of ovarian function. For example, extra-gonadal LHCGR activity was found to be redundant for normal ovarian function by orthotopic replacement of the ovaries in LHCGR-KO mice with normal wild-type ovaries and comparison with similarly transplanted WT mice as controls [Pakarainen et al., 2005]. Similarly, transplants of wild-type ovaries into nuclear receptor interacting protein 1 (NRIP1 or RIP140) null mice, which have an anovulatory phenotype reminiscent of PRKO mice, restored fertility, while transfer of RIP140-null ovaries to wild-type recipients did not [Leonardsson et al., 2002]. This demonstrated that RIP140 expression in the ovary is necessary for ovulation and expression in other tissues is not essential [Leonardsson et al., 2002]. However, there are also examples where transfer of null ovaries to wild-type recipients does restore function. For example, high density lipoprotein-receptor (SCARB1 or SR-BI) knockout mice can successfully ovulate, but the ovulated oocytes are dysfunctional and therefore these mice are infertile [Trigatti et al., 1999]. However, transfer of SR-BI knockout ovaries to SR-BI wild-type mice restored the capacity of the ovary to produce functional oocytes, with 85.7% of these mice becoming pregnant compared to 0% of the sham controls [Miettinen et al., 2001]. Similarly, knockout (AR-/-) females are subfertile, with abnormal or absent estrous cycles and reduced litter sizes [Walters et al., 2009], but ovarian function was restored when AR-/- ovaries were transferred to AR+/+ recipients [Walters et al., 2009].

Therefore, this chapter reports on systematic, morphological examination of histological sections to determine the structural phenotype of the PRKO ovary during the periovulatory period. In addition,

Lisa Akison 2012 91 ovarian transplants of PRKO ovaries into PRWT females were used to determine if function can be restored to PRKO ovaries under the influence of PGR expression in other tissues.

3.2 Materials & Methods

3.2.1 Tissue collection & histology

Whole ovaries alone or ovaries with oviduct and bursa still attached were collected at 44 h eCG + 8 h, 10-10.5 h (referred to hereafter as 10 h in figures and text), 11.5-12 h (referred to hereafter as 12 h in figures and text) and 14 h post hCG. There were 4 animals examined per genotype (PRKO and PR+/-) at each time point. In addition, COCs were obtained by puncturing antral follicles at 44 h eCG + 10 h post-hCG in ovaries from both genotypes to compare cumulus expansion. Tissue collection, processing, embedding, sectioning and staining with haematoxylin and eosin (H & E) were as described in Chapter 2. Images of sections were captured at 40X magnification using the NanoZoomer HT Digital Pathology System (Hamamatsu Photonics K.K., Japan). Images of intact COCs were captured using an Olympus F-View soft image system camera fitted to an inverted Olympus 1X81 microscope (Olympus Australia Pty Ltd, Mt Waverley, VIC, AU) at 4X magnification.

Several sections (8-10) were examined in detail from each ovary, with one representative section included in a comparative figure. The ovaries were examined at three magnifications: 5X to show the whole ovary and the general layout and stages of follicles; 10X to show more detail of the follicles; and 20X to show more detail of the stroma within the medulla region. The genotypes were systematically compared at each time point with particular attention given to a) the size and location of follicles throughout the ovary, b) the degree of thinning of the follicle wall in large antral follicles, c) the degree of cumulus expansion occurring in visible COCs and d) the extent of stromal and thecal vascularisation. At the 12 h time point, coincident with ovulation, the basal wall of preovulatory follicles was examined at higher magnification (20X) to examine basal invagination of the theca layer into the granulosa cell layer. A separate comparative figure to the one described above was compiled to illustrate this basal invagination, with one representative section from 3 animals of each genotype.

3.2.2 Ovarian transplants

Donor ovaries were obtained from female PRlacZ mice (either PRKO or PRWT) 3.5 to 6.5 weeks old. Ovaries were removed from sacrificed donor mice and placed in PBS at room temperature. Recipient mice (PRWT genotype) were larger and older than the donor mice (approximately 11 to 17 weeks old) Lisa Akison 2012 92 to facilitate transplantation of the donor ovary into the bursal cavity. Recipient mice were anaesthetised via inhalation of isoflurane. After the induction of anaesthesia, the dorsal surface of the mouse was shaved and swabbed with 10% povidone-iodine in water (Betadine®). A small mid-dorsal incision was made in the skin just below the last rib. The ovary and associated fat pad were visualised through the body wall, a small incision made in the muscle layers and then scissors used to stretch the incision to gain access to the ovary, oviduct and uterus. A Serrefine clamp was attached to the ovarian fat pad and laid out on a sterile pad to expose the ovary and oviduct and secure it in place (Figure 3.1A). The ovarian transplant surgeries were conducted as described by Nagy et al. (2003) (Figure 3.1A). Briefly, fine spring scissors were used to make a small incision in the bursa (the membrane surrounding the ovary) adjacent to the fat pad and on the opposite side to the oviduct. Fine forceps were used to slip the ovary out of the bursa and the ovary removed by grasping the supporting stalk and pinching off with fine forceps. The donor ovary was then inserted into the recipient’s bursal sac. The Serrefine clamp was removed and the transplanted ovary, oviduct and uterus returned to the body cavity. This procedure was repeated for the opposite side. After the ovarian transplants were completed, the skin incision was swabbed with iodine solution and closed using wound clips. Recipient females were placed on a heating pad to maintain body temperature until they recovered from the anesthesia. Carprofen (Rimadyl®) was administered subcutaneously post-surgery as an analgesic (5 mg/kg).

There were two ovarian transplant experiments (Figure 3.1B). Experiment 1 was a short term experiment to determine the feasibility of the surgical procedure and to examine the structure of the transplanted ovaries and their ability to successfully ovulate following hormonal stimulation of the recipient female. One PRKO and one PRWT ovary from 3.5 week-old donor mice were fixed, processed, sectioned and stained to demonstrate the ‘baseline’ status of these ovaries. All other PRKO and PRWT donor ovaries were placed in contralateral sides of the same PRWT, ovariectomised recipient female (see Figure 3.2B). This was to allow a direct comparison of PRKO and PRWT donor ovary morphology and function after a pre-determined transplant period while removing potential variation introduced by using different recipient females. This was done in 3 PRWT recipient females. At 3-6 weeks post-surgery, the recipients were hormonally stimulated with eCG and hCG and at 23 h post-hCG, the ovaries and associated oviducts were removed for histological examination. The oviducts were also examined for ovulated COCs. Tissues were fixed in 4% paraformaldehyde and processed, embedded and sectioned as per detailed methods in Chapter 2. The entire ovary/oviduct was sectioned and stained with H & E (see Section 2.6.2) to allow quantification of anovulatory follicles and corpora lutea. Anovulatory follicles included unruptured, yet non-luteinised, follicles (UFs) with expanded COCs and luteinised, unruptured follicles (LUFs) with entrapped oocytes (terminology after [Shozu et al., 2005]).

Lisa Akison 2012 93

A)

A NOTE: This figure/table/image has been removed to comply with copyright regulations. It is included in the print copy of the thesis held by the University of Adelaide Library.

B)

Experiment 1 Experiment 2 Figure 3.1 Ovarian transplant surgical protocol and experimental design. A) Ovarian transplant surgical procedure (adapted from [Nagy et al., 2003b]). The recipient female ovary was removed via an incision in the bursa (a-c) and the donor ovary transplanted inside the recipient’s bursal membrane (d-f). B) Recipient mice and donor ovaries used in Experiments 1 & 2. In Experiment 1, a PRWT and a PRKO ovary were transplanted into the same PRWT recipient on contralateral sides. The recipient female was hormonally stimulated after 3-4 weeks with eCG and hCG and the ovaries removed for histological examination at 23 h post-hCG. Oviducts were also checked for ovulated COCs. In Experiment 2, only 1 ovary was transplanted into either the left or right side of an ovariectomised PRWT female. After 2 weeks, the female was mated with a PRWT male. Any pups produced were genotyped to confirm ovarian origin.

Lisa Akison 2012 94

Experiment 2 was a longer-term experiment to allow greater time for the transplanted ovary to become established, ovulate and potentially produce live pups. One ovary (either from a PRWT or PRKO donor) was transplanted into each ovariectomised recipient PRWT female (n = 6; 3 with a PRKO and 3 with a PRWT donor ovary). Due to implantation defects in the PRKO uterus [Lydon et al., 1995], the reverse transplantation experiment could not be performed. Two weeks post-surgery, each recipient female was paired with a PRWT male for 3 months and any resulting pups were genotyped to confirm ovarian origin of the oocyte. At the conclusion of the mating period, all females were sacrificed and uteri were examined for implantation sites or foetuses yet to be born. As pregnancies may be difficult to detect when there are a small number of foetuses and early pup loss can occur in laboratory strains [Perrigo et al., 1993; Weber et al., 2007], checking the uteri for implantation sites was particularly important for females where no pups had been observed during the mating period.

3.3 Results

3.3.1 Ovarian histology

Gross histology at three different magnifications revealed no discernible differences in the structure or vascularisation of the ovary between PRKO and PR+/- mice during the periovulatory period (8 h, 10 h and 12 h post-hCG; Figure 3.2A-C). At 8 h post-hCG, in both PRKO and PR+/- ovaries, large antral follicles were present in similar numbers and in similar locations throughout the ovary (Figure 3.2A). The exception was one of the PRKO mice (#691) which had very few antral follicles suggestive of a poor response to hormonal stimulation. Large blood vessels were observed in the stroma of both PRKO and PR+/- ovaries and vascularisation of the theca layer around large follicles was evident in both genotypes (Figure 3.2A, 20X). Cumulus cells were still tightly associated with the oocyte in both genotypes (as indicated by the arrowheads in the high-power images from Figure 3.2A). By 10 h post- hCG, the cumulus cells were starting to show expansion away from the oocyte, with the degree of expansion observed similar in the PRKO and PR+/- ovary sections (as indicated by the arrowheads in 10X images from Figure 3.2B). Both PRKO and PR+/- ovaries contained large blood vessels in the stroma (as indicated by arrows in the high-power images from Figure 3.2B) and vascularisation of the theca. Thinning of the apical follicle wall was also evident in some large antral follicles from both PRKO and PR+/- ovaries (Figure 3.2B). By 12 h post-hCG, there was expansion of the cumulus cells away from the oocyte in both PRKO and PR+/- COCs (as indicated by the arrowheads in 10X images from Figure 3.2C). Thinning of the apical follicle wall of large preovulatory follicles occurred in both genotypes (Figure 3.2C), and an extensive vascular network with many large vessels was present in the stroma of the medulla in both PRKO and PR+/- sections. The theca layer between adjacent follicles Lisa Akison 2012

Figure 3.2A) PR+/- ovaries 8 h post-hCG PRKO ovaries 8 h post-hCG

Whole Ovary (5X) Follicles (10X) Stroma (20X) Whole Ovary (5X) Follicles (10X) Stroma (20X)

Figure 3.2B) PR+/- ovaries 10 h post-hCG PRKO ovaries 10 h post-hCG

Whole Ovary (5X) Follicles (10X) Stroma (20X) Whole Ovary (5X) Follicles (10X) Stroma (20X)

Figure 3.2C) PR+/- ovaries 12 h post-hCG PRKO ovaries 12 h post-hCG Whole Ovary (5X) Follicles (10X) Stroma (20X) Whole Ovary (5X) Follicles (10X) Stroma (20X)

*

*

Figure 3.2D) PR+/- ovaries 14 h post-hCG PRKO ovaries 14 h post-hCG Whole Ovary (5X) Follicles (10X) Stroma (20X) Whole Ovary (5X) Follicles (10X) Stroma (20X)

CL

CL

CL

* *

99

Figure 3.2 Ovarian histology appears normal in PRKO mice until 12 h post-hCG. Photomicrographs of ovarian sections from PRKO and PR+/- mice stained with haematoxylin and eosin (H & E) are shown at A) 8 h, B) 10 h, C) 12 h and D) 14 h post-hCG. Numbers denote individual animal identification numbers. All PR+/- mouse ovaries are shown in the left-most panels and PRKO ovaries in the right-hand panels for each figure. For each ovary, the first (left- most) section is shown at 5X magnification, the middle section at 10X magnification and the right- most section at 20X magnification. Arrows indicate large blood vessels; arrowheads indicate cumulus oocyte complexes at various stages of expansion as described in the text; and asterisks indicate thinning of the apical wall of the follicle. CL = corpus luteum.

Lisa Akison 2012 100 was also highly vascularised in both genotypes (Figure 3.2C). In addition, examination of the basal follicle wall at 20X magnification revealed normal invagination of the theca layer in PRKO follicles at this time point (Figure 3.3). As expected, the PR+/- sections were drastically altered at 14 h post-hCG compared to the 12 h post-hCG time point due to ovulation of COCs and subsequent formation of corpora lutea (Figure 3.2D). In contrast, at 14 h post-hCG, PRKO ovary sections had similar morphology to that seen at 12 h post-hCG, with fully expanded COCs within large, antral follicles, often with obvious thinning of the apical follicle wall (as indicated by the asterisks in the 10X images from Figure 3.2D). Interestingly, the expanded COCs tended to be closer to the basal side than the apical side of the follicle (10X images in Figure 3.2D).

3.3.2 Cumulus expansion in PRKO COCs

Although cumulus expansion in COCs appeared normal from the morphological analysis described in the previous section (and shown in Figure 3.2), more detailed observations were made at higher magnification in sections from the two genotypes at 10 h post-hCG, as well as in whole COCs punctured from ovaries from another cohort of mice at the same time point (Figure 3.4). Although cumulus expansion scoring using previously described methods for IVM COCs [Dragovic et al., 2005; Vanderhyden et al., 1990] is difficult to apply to in vivo-derived COCs, general comparisons reveal no discernible differences between the genotypes (Figure 3.4A). In follicle sections from both genotypes, the degree of cumulus expansion observed in both the corona radiata (the cumulus cells immediately adjacent to the oocyte) and the outer layer of cumulus cells were similar, with cumulus cells filling the entire antral cavity in some cases (Figure 3.4B). Therefore, I confirm that COCs isolated from PRKO ovaries during the periovulatory period show morphologically normal cumulus expansion when compared with PR+/- littermates.

3.3.3 Ovarian transplants

Transplantation of the donor ovaries was judged successful with the transplanted ovaries remaining in the bursal cavity adjacent to the oviduct in all cases (Figure 3.5). In some cases there was some adhesion to the ovarian fat pad. No infection or necrosis was observed at autopsy or in histological sections in Experiment 1 (Figure 3.5 and 3.6). In one case, the ovary had adhered to the body wall (Figure 3.6). In two cases there appeared to be a small piece of residual ovary from the recipient female still present and adjacent to the donor ovary, with ovulated COCs observed in the oviduct adjacent to one of these ovaries (Figure 3.6). Lisa Akison 2012 101

Figure 3.3 Basal invagination occurs in PRKO follicles at 12 h post-hCG. One representative follicle from 3 animals of each genotype (PRKO, PR+/-) are shown, although a total of 4 were examined. All images are at 20X magnification. Arrowheads indicate regions of invagination of the thecal layer into the granulosa cell layer in the basal region of the follicle.

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A)

B) PR+/- PRKO

Figure 3.4 PRKO and PR+/- COCs show the same degree of expansion at 10 h post- hCG. A) Whole COCs punctured from antral follicles of PRKO and PR+/- mice at 10 h post-hCG. 4X magnification. B) Histology of 10 h post-hCG ovary sections from each genotype. Images show representative sections of a preovulatory follicle from two animals per genotype. 20X magnification.

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oviduct CL ts

uterus

Figure 3.5 Recipient female with transplanted ovary in situ. Photo taken 2 weeks post-surgery of a PRWT ovary transplanted into a PRWT recipient. Mouse was hormonally stimulated with eCG + hCG and dissection performed 23 h post-hCG. A) Note healthy tissue with numerous corpora lutea evident on the ovary and the location of the ovary with respect to the oviduct and uterus. B) Close-up of the section highlighted in A) showing the transplanted ovary with corpora lutea. CL = corpora lutea.

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CL

Pre-transplant

RO CL

Pre-transplant

CL BW

CL

CL

RO

RO

Figure 3.6 PRKO ovaries transplanted into PRWT females remain anovulatory. A PRWT and a PRKO donor ovary were transplanted into contralateral sides of a PRWT recipient mouse. This was repeated in 3 recipient mice with donor ovaries from 3 independent PRWT (PRWT1-3) and 3 independent PRKO (PRKO1-3) mice. For PRKO1 and PRWT1, one ovary from each donor mouse was collected pre-transplant, fixed, sectioned and stained for comparison with the corresponding transplanted ovary. Three or four representative sections are shown for each transplanted ovary. Black arrowheads identify some of the unruptured follicles (UFs) with expanded COCs; white arrowheads indicate luteinised, unruptured follicles (LUFs) with entrapped oocytes; and arrows indicate ovulated COCs in oviducts. RO = residual ovary of the recipient mouse. BW = body wall. CL = corpus luteum. Scale bar = 300 μm.

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Following isolation and fixation of transplanted ovaries, the entire ovary was sectioned and stained with H & E, and between 21-43 sections were closely assessed per ovary. Histological examination showed that all ovaries responded to the hormonal stimulation, as shown by comparison with the ovaries that were fixed prior to transplantation, and the transplanted ovaries grew and supported development of large follicles (Figure 3.6). Ovulated COCs were observed in the bursal cavity and oviduct adjacent to the PRWT ovary in one animal (Figure 3.6), with the bursal cavity visibly fluid-filled at autopsy and the bursal membrane noticeably connecting the ovary and the oviduct. No ovulated COCs were observed in the bursal cavity or the adjacent oviduct of any of the PRKO ovaries. All PRWT donor ovaries contained corpora lutea and very few anovulatory follicles while the PRKO donor ovaries, on the contralateral side of the same animals, contained a significantly higher number of anovulatory follicles and similar numbers of corpora lutea (Figure 3.7).

In Experiment 2, recipient females containing a transplanted ovary from either a PRWT or PRKO donor were paired with proven stud PRWT males to determine if reproductive function could be restored and result in successful production of pups. Vaginal plugs were observed between 1 and 7 days after pairing in all recipient females, including those with PRKO donor ovaries. Two out of the three females with PRWT donor ovaries produced pups (total of 14 pups over 5 litters) and one of these females had a foetus (approximately day e 17-18) in one uterine horn at autopsy. Therefore, a total of 15 offspring (pups/foetuses) were produced by recipient females with PRWT transplant ovaries over the 107 days that the mice were paired (Figure 3.8). The one female with PRWT donor ovaries that did not produce pups had two ovaries transplanted, whereas those that produced pups had only one ovary transplanted. The stud male allocated to this female was replaced with another proven male after 6 weeks to discount possible male infertility issues. However, autopsy revealed that on both sides, the transplanted ovaries were heavily embedded in the ovarian fat pad that lies adjacent to the bursal cavity and on one side the ovary had adhered to the body wall. One of the three females with PRKO donor ovaries produced 2 pups, however when genotyped, these were PRWT and not PR+/-, indicating that the oocytes originated from residual ovary of the recipient PRWT female. The presence of some residual ovary from the recipient mouse was confirmed at autopsy. For the three females that did not produce any pups (two with PRKO donor ovaries and one with a PRWT donor ovary) there were no uterine scars observed at autopsy, confirming that no implantations had occurred. Thus, no pups with PR+/- genotype were produced during the mating period (Figure 3.8), indicating that function was not restored to the PRKO ovaries.

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A) B) 30 12 * ns 25 10

20 8

15 6

10 4

5 2 # Corpora lutea (Mean + SE) lutea (Mean # Corpora

# Anovulatory follicles (Mean + SE) (Mean follicles # Anovulatory 0 0 PRWT PRKO PRWT PRKO Transplanted ovaries Transplanted ovaries Figure 3.7 PRKO transplant ovaries had more anovulatory follicles than PRWT. A) There were a significantly greater number of anovulatory follicles in the PRKO compared with the PRWT transplanted ovaries, indicating that function was not restored in the null ovaries. Anovulatory follicles included unruptured follicles with expanded COCs and luteinised, unruptured follicles with entrapped oocytes. B) The number of corpora lutea was not different between PRWT and PRKO transplanted ovaries. n = 3 donor ovaries per genotype for both A) and B). Statistical significance was determined using a Student’s t-test. * = P<0.05. ns = not significant.

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16 PRWT genotype 14 PR+/- genotype

12

10

8

6 # pups/foetuses 4

2 0 0 20 40 60 80 100 120 Days post-pairing

Figure 3.8 Function was not restored to PRKO ovaries transplanted into PRWT females.

Recipient females were paired with PRWT stud males, thus offspring originating from a PRKO transplanted ovary would be PR+/- genotype and offspring originating from a PRWT transplanted ovary would be PRWT genotype. A total of 15 pups/foetuses from 6 litters were produced from 2 out of 3 mice transplanted with PRWT ovaries. No pups/foetuses of the appropriate genotype were produced from the PRKO transplanted ovaries.

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3.4 Discussion

PGR is known to be essential for ovulation and this is convincingly demonstrated by multiple PRKO transgenic mouse strains. These mice have previously been shown to have a profound anovulatory phenotype due to an inability of the follicles to rupture at ovulation, trapping the oocytes within seemingly normal, antral, preovulatory follicles. In this chapter, I used orthotopic ovarian transplants to determine if the anovulatory phenotype in PRKO ovaries is intrinsic to the ovary or due to additional complications of PGR knockdown in other tissues. There was no evidence that ovarian function could be even partially restored to the PRKO ovary when transplanted into a normal mouse. In Experiment 1, transplanted PRKO ovaries within hormonally-stimulated normal mice showed a significantly higher number of anovulatory follicles than PRWT donor ovaries on the contralateral side of the same animal, and no sign of ovulated COCs in the oviduct or bursa. In Experiment 2, recipient PRWT mice with PRKO donor ovaries did not produce pups derived from the donor ovary during a natural mating experiment over 3 months, despite obvious signs of mating as demonstrated by the appearance of vaginal plugs. This was in contrast to 2 out of 3 PRWT recipient mice with PRWT donor ovaries that produced 15 pups/foetuses from 6 litters. Thus the anovulatory phenotype of the PRKO ovary appears to be due to some defect intrinsic to the ovary and is not the result of PGR ablation at other sites. To further confirm this conclusion, a follow-up experiment reversing the genotypes and examining oocyte release in PRWT and PRKO ovaries transplanted into contralateral sides of an ovariectomised, PRKO female would be informative. If the hypothesis of PGR knockdown in the ovary being solely responsible for the anovulatory phenotype is true, then I would predict that the PRKO donor ovary would have significantly more anovulatory follicles than the PRWT donor ovary as is shown in this chapter. This experiment would only be feasible as a short-term assessment of oocyte release after injection with eCG/hCG, as was conducted in Experiment 1. Use of PRKO females as recipients in a longer term breeding trial, as was conducted in Experiment 2, would not be possible given the known impairment of the lordosis response and uterine implantation defects due to PGR loss in the brain and uterus respectively [Lydon et al., 1995].

Orthotopic ovarian transplants are a commonly used but technically difficult surgical technique, especially for the novice, and thus the number of animals used in these experiments was low relative to other experiments in this thesis. Grafting of ovarian tissue back to the ovarian pedicle allows natural conception to occur, but the surgery is invasive and removal of all of the recipient’s ovarian tissue sometimes difficult. I genotyped all offspring to identify their ovarian origin, but I could not be completely certain that all of the 15 offspring from the recipients with PRWT donor ovaries were from the donor and not from any residual ovary in the recipient. Given that 2 out of 6 transplant sites in Experiment 1 had obvious residual ovary from the recipient in histological sections and 1 out of 3 mice Lisa Akison 2012 109 with PRKO donor ovaries produced WT pups, I can probably assume that 30% of pups from females with PRWT donor ovaries could have arisen from residual ovary left in the recipient at ovariectomy. This is a similar frequency to a previous report (36% [Sztein et al., 1998]). This still means that approximately two-thirds of these pups (~10) were from the transplanted WT ovaries and establishes that pups could be produced after the surgical intervention. Thus, the data shown within this chapter now shows, for the first time, that the ovulatory defect in PRKO mice is intrinsic to the ovary.

Detailed histological comparisons of PRKO and PR+/- ovarian sections at 8 h, 10 h and 12 h post-hCG revealed no detectable differences between the genotypes. The PRKO ovaries showed normal antral follicle formation following administration of eCG and hCG, and these follicles were found in the cortical region of the ovary as per the PR+/- ovaries. Large blood vessels were increasingly evident in the stroma as ovulation approached, and there was noticeable vascularisation in the theca layer surrounding large follicles in ovaries of both genotypes. Follicle wall thinning in the apical region of preovulatory follicles was evident, as was invagination or ‘merging’ of the thecal layer with the granulosa cell layer in the basal region of the follicles. Cumulus expansion of the COCs within PRKO follicles was to the same degree as in PR+/- follicles, with fully expanded COCs extending across the entire antrum in preovulatory follicles by 12 h post-hCG. It was only at 14 h post-hCG that the PRKO ovaries showed different morphology to the PR+/- ovaries, with entrapped COCs evident within luteinising follicles instead of corpora lutea, indicative of successful ovulations. Thus there were no obvious morphological defects in the PRKO follicles or COCs during the period immediately preceding ovulation.

The presence of normal basal invagination in the PRKO ovaries is in contrast to what has been observed in ADAMTS1KO mice. These mice show a lack of thecal/vascular invagination in the basal wall of follicles, with an acellular space demarcating the granulosa and thecal cell layers [Brown et al., 2010a]. ADAMTS1 has previously been reported to be down-regulated in PRKO mice [Robker et al., 2000; Russell et al., 2003b] and so it is somewhat surprising that a similar defect in follicle remodelling was not observed in the PRKO mice. However, only a portion of Adamts1 expression is due to progesterone receptor induction and there is not total knockdown of ADAMTS1 in PRKO mice; approximately 10% remains [Doyle et al., 2004; Russell et al., 2003b]. Further, non-granulosa cell sources of ADAMTS1, such as the theca interna [Boerboom et al., 2003], may provide enough functional ADAMTS1 in this basal region to support normal thecal cell invasion. Additionally, processing of the major substrate of ADAMTS1, versican, is necessary for basal invagination [Brown et al., 2010a], and this is only reduced by 50% in PRKO mice [Russell et al., 2003b]. The presence of the closely related ADAMTS4 may compensate for reduced ADAMTS1 in the PRKO ovary [Russell et al., 2003b].

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From examination of gross histology, there were no obvious differences in vascularisation. However, immunohistochemical staining using a specific endothelial cell marker, such as CD34 or CD31 (also known as PECAM1), would be a beneficial follow-up experiment to quantify this further in PRKO and PR+/- ovaries. P4 is known to regulate endothelial cell proliferation and PGR is expressed on endothelial cells [Vazquez et al., 1999], so presumably, knock-down of PGR may impact angiogenesis in the ovary, albeit in a more subtle way than may be detectable by examination of gross histology. In addition, a lymphangiogenic marker, such as lymphatic vessel endothelial hyaluronan receptor (LYVE1), would also allow any anomalies in the number or extent of lymphatic vessels throughout the ovary to be quantified in PRKO mice. The lymphatic network has been found to be defective in ADAMTS1 KO mouse ovaries, with delayed lymphangiogenesis [Brown et al., 2006] and reduced vessel size and number [Brown et al., 2010b] compared to heterozygous controls. Therefore, given the regulation of ADAMTS1 expression by PGR, lymphangiogenesis could potentially be defective in PRKO ovaries as well. Both the ovarian vascular network and lymphatic network are important for transporting substances critical for ovulation. For example, the heavy chains of II (also known as serum-derived hyaluronan associated proteins or SHAPs) are present in serum and are an important component of the cumulus matrix (see Chapter 1). As vascular permeability increases around the time of ovulation, these serum-derived products are able to reach the follicle. Thus, a further follow-up experiment using immunohistochemical staining for proteins such as SHAP, may provide a method for comparing vascular permeability in PRKO and PR+/- ovaries.

There was no evidence of impaired cumulus expansion in PRKO COCs in side-by-side comparison with PR+/- COCs, from both histological examination of COCs within follicles and whole COCs punctured from preovulatory follicles. This is consistent with previous anecdotal evidence [Lydon et al., 1995; Robker et al., 2000]. Again, this is in contrast to periovulatory COCs from ADAMTS1KO mice, which show cumulus cell aggregates resulting from aberrant matrix formation [Brown et al., 2010a]. This suggests that, at least morphologically, cumulus expansion in PRKO COCs is normal. Interestingly, COCs entrapped in follicles at the 14 h time point in PRKO ovarian sections appeared to be located in the basal region rather than near the apical follicle wall, the site of follicle rupture in wild-type mice. The reason for this is currently unknown, but may suggest reduced proteolytic activity or a decreased propensity to adhere to ECM proteins exposed during follicle wall thinning.

Thus, the morphology of the PRKO ovary appears normal right up until the time of ovulation, and yet has a profound and intrinsic anovulatory defect. In rodent ovaries, PGR is predominantly expressed in the granulosa cells, specifically in preovulatory follicles [Ismail et al., 2002; Park and Mayo, 1991; Robker et al., 2000; Teilmann et al., 2006]. Therefore, the ovarian transplant experiments confirm that functional PGR protein, specifically in the granulosa cells, is absolutely required for follicle rupture and

Lisa Akison 2012 111 oocyte release. As described in detail in Chapter 1, it is the mural granulosa cells that respond to the ovulatory surge of LH, via the LH receptor, transiently modifying their transcriptional activity to initiate expression in a specific cohort of genes with known roles in ovulation [Russell and Robker, 2007]. Importantly, PGR has been shown to be a critical regulator of many of the genes in this ovulatory cascade (see [Robker et al., 2009] and Table 1.2). A prime example is ADAMTS1 protease, which has been localised to the ovulatory stigma [Richards et al., 2005], is down-regulated in PRKO granulosa cells [Robker et al., 2000; Russell et al., 2003b] and when deleted in null mice produces a similar phenotype to the PRKO; although ADAMTS1 null mice are not completely anovulatory [Brown et al., 2010a; Mittaz et al., 2004]. Therefore, ADAMTS1 probably contributes to weakening of the apical follicle wall, although this has not been directly shown, but other proteases or factors must also contribute given that the ADAMTS1KO is subfertile. PGR likely also regulates many genes that are unknown yet involved in the critical proteolytic, biochemical and/or immunological events believed to contribute to successful ovulation. Given the suggestion that the COC may play an active role in mediating its release via adhesion to the follicle wall and invasion and migration out towards the oviduct (see Section 1.2.2.4), it could be molecules involved in these functions that are also absent in the PRKO ovary. Previous work by our lab has suggested that inflammation is altered in the PRKO ovary, and so this is another potential area in which PGR regulation may control follicle rupture and COC release.

In conclusion, given the intrinsic anovulatory phenotype of the PRKO ovary, and the lack of visible structural defects that may prevent follicle rupture, I hypothesise that critical proteolytic, biochemical or immunological events, undetectable visibly, are dysregulated or absent in the PRKO ovary. The next chapter will examine whole ovaries and the potential contribution of inflammatory genes to the anovulatory defect of the PRKO ovary. Subsequent chapters will also identify PGR-regulated genes in specific ovarian cell types and investigate the migratory and invasive properties of cumulus cells.

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Chapter 4 – PGR-regulated immune genes in the ovary

4.1 Introduction

Over 30 years ago Lawrence Espey famously proposed a ‘working model’ of ovulation as an inflammatory reaction [Espey, 1980]. In this review, he highlighted specific similarities between the biochemical events that were known at the time to occur in both inflammation and ovulation. Both of these processes have characteristic physical and chemical changes that are dynamic and often involve simultaneous damage and repair of tissues. There are local modifications to the vasculature which increase blood flow and the permeability of capillaries, resulting in oedematous swelling of the tissue and exudation of serum proteins. Espey hypothesised that chemical mediators of this process would be similar to those seen in the early stages of inflammation in other tissues, namely histamine, bradykinin, serotonin and prostaglandins. He cited early studies which demonstrated that antihistamines or the prostaglandin synthesis inhibitor, indomethacin, could inhibit ovulation either in vivo and/or in vitro in ovary perfusion experiments (see [Espey, 1980] for specific references). Inflamed tissue then produces chemotactic agents that stimulate infiltration of leukocytes, including macrophages and neutrophils, which release a number of chemical mediators and enzymes that amplify the inflammatory reaction, causing further tissue damage. Espey identified prostaglandins and proteolytic enzymes as these putative mediators, which are locally and transiently produced, activating positive feedback loops which facilitate the release of more inflammatory mediators and further infiltration of immune cells. At this time, prostaglandin E and F2 (PGE, PGF2) synthesis had been shown to occur in the ovary in response to gonadotrophins, specifically in granulosa and theca cells of preovulatory follicles [Erickson et al., 1977; LeMaire et al., 1973; Plunkett et al., 1975]. Proteolytic enzymes that had been identified at this time in ovarian follicles included plasminogen activator, which had been shown to be induced by PGE1 and PGE2 [Strickland and Beers, 1976], cathepsin and collagenase [Espey, 1974]. Espey proposed that these and other, as yet unidentified, proteolytic enzymes may aid in the release of specific factors from inflamed tissue, as well as being involved in remodelling of extracellular matrix and proliferation of fibroblasts which are part of the ‘repair phase’ of the inflammatory reaction.

Ensuing research has strongly supported Espey’s hypothesis, with the identification of many of the specific inflammatory mediators and immune cells involved in the process of ovulation (see Figure 4.1 for summary). The temporal pattern of inflammatory and immunological changes which are believed to occur during the periovulatory period in response to the LH surge will be reconstructed in more detail Lisa Akison 2012 113

Figure 4.1 Ovulation is likened to an inflammatory reaction. Due to the many similarities between events occurring in the ovulating follicle and events that are key characteristics of inflammation, ovulation is likened to an inflammatory reaction. In response to LH/hCG, PTGS2 is highly induced in granulosa cells, synthesising prostaglandins which are essential for ovulation. There is increased vascular permeability and dilation of blood vessels, analagous to that which leads to swelling during inflammation, initially in response to histamine released from mast cells. Finally, immune cell numbers increase in the theca and apical wall, and eventually infiltrate into the follicle, responding to increasing levels of inflammatory cytokines/chemokines and producing proteases which contribute to follicle rupture. The role that progesterone receptor (PGR) plays in coordinating these events is largely unknown.

Lisa Akison 2012 114 below. Only the immune-related features of this process will be discussed in detail here; other aspects of the physical changes and proteases involved in ovulation are discussed elsewhere (Section 1.2.2).

Within the first few hours after the LH surge, vascular changes in the capillaries of the theca layer surrounding preovulatory follicles result in hyperaemia or increased blood flow, tissue reddening, fluid accumulation and swelling, and increased vascular permeability [Tanaka et al., 1989]. This is thought to be mediated initially by histamine released primarily from mast cells, but also from basophils and/or , as the LH-induced increase in blood flow is completely blocked by antihistamines in cannulated ovaries [Piacsek et al., 1971]. In isolated ovaries from rat [Schmidt et al., 1986] and rabbit [Kobayashi et al., 1983], histamine alone has been demonstrated to induce ovulation and a further study demonstrated the direct mechanical responses of isolated rat ovarian arteries to histamine and histamine antagonists [Schmidt et al., 1990]. A recent study has confirmed the anti-ovulatory affect of histamine receptor 2 (H2) blockers in vivo in the rabbit [Agrawal and Jose, 2011]. Most of the effects of histamine in the ovary however have been investigated in vitro [Krishna et al., 1989], for instance histamine has a direct stimulatory effect on estradiol production of cultured human granulosa cells [Bodis et al., 1993]. Interestingly, a recent in vitro study, using purified rat peritoneal mast cells, demonstrated that progesterone could inhibit secretion of histamine by these cells [Vasiadi et al., 2006].

This vasodilation and increased vascular permeability that occurs following the LH surge facilitates the infiltration and proliferation of leukocytes in the preovulatory ovary (see [Oakley et al., 2011] for review and Figure 4.1). Since Espey’s review in 1980, the nature of these immune cells, and their roles in ovulation, has become clearer, largely due to several immune cell depletion studies.

Neutrophils are predominant immune cells during the early stage of an immune reaction, as well as during ovulation [Brannstrom and Enskog, 2002]. Invasion of neutrophils into the periovulatory follicle occurs within a few hours of the LH surge as demonstrated in human [Brannstrom et al., 1994b], rat [Brannstrom et al., 1993a], sheep [Cavender and Murdoch, 1988] and pig [Standaert et al., 1991] ovaries. A detailed study in the rat showed an 8-fold increase in the density of neutrophils in the theca of ovulating follicles, with a large number concentrated around the apical region [Brannstrom et al., 1993a]. Our lab has also observed a similar distribution of neutrophils in the preovulatory mouse ovary [Robker et al., 2010]. Neutrophil-depleting antibody treatment has been shown to impair ovulation in rats [Brannstrom et al., 1995], indicating the direct role of neutrophils in oocyte release. Interestingly, our lab has evidence that the number of neutrophils are significantly reduced in periovulatory follicles of PRKO mice relative to heterozygous littermates (see [Robker et al., 2010] and Figure 4.2). Additionally,

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A) B)

A NOTE: This figure/table/image has been removed to comply with copyright regulations. It is included in the print copy of the thesis held by the University of Adelaide Library.

Figure 4.2 Fewer neutrophils are present in PRKO ovaries. A) Immunohistochemical staining of neutrophils in sections of preovulatory follicles from eCG + 16 h post-hCG treated PRKO and PR+/- mice. B) Quantification of neutrophils in PR+/- and PR- /- sections. (Unpublished data presented by Robker et al at the Society for the Study of Reproduction Annual meeting; see [Robker et al., 2010] for abstract).

Lisa Akison 2012 116 eosinophils have also been localised to the theca layer of preovulatory follicles in the pig [Standaert et al., 1991], horse [Kerban et al., 1999], rat [Gaytan et al., 2003b] and cow [Reibiger and Spanel- Borowski, 2000]. Macrophages have been detected in the ovary of many species at various stages of the estrous cycle and have been shown to be involved in many aspects of ovarian function, including follicular growth and atresia, luteal regression and ovulation (see [Wu et al., 2004] for review). In the ovary, they are thought to secrete chemokines (e.g. IL8), cytokines (e.g. IL1, IL6, TNFa, IL10), growth factors (e.g. EGF, TGF), prostaglandins and proteases (e.g. plasminogen activator, stromelysin, gelatinase and collagenase) as they do in other tissues, although proteases and cytokines are the most likely macrophage-derived products to directly facilitate ovulation [Wu et al., 2004]. In particular, macrophages have recently been shown to be major producers of MMP9, the most abundant MMP in the preovulatory ovary in response to the LH surge [Fedorcsak et al., 2010]. Immediately prior to ovulation, there is increased macrophage migration into the thecal layers of preovulatory follicles as shown in the mouse [Van der Hoek et al., 2000], rat [Brannstrom et al., 1993a] and human [Brannstrom et al., 1994b; Takaya et al., 1997]. Activated macrophages (i.e. those that express MHC class II antigens) have also been detected in the theca and granulosa cell layers in the apical region of ovulating follicles [Brannstrom et al., 1993a]. Importantly, their role in ovulation has been demonstrated in the mouse, as depletion of ovarian macrophages by intrabursal injection with clodronate liposomes decreases ovulation rate by ~50% [Van der Hoek et al., 2000].

In addition to neutrophils, eosinophils and macrophages, T-cells have also been found to infiltrate the preovulatory ovary, although to a much lesser degree [Brannstrom et al., 1993a; Suzuki et al., 1998a; Zhuo et al., 2001]. They have been localised to the theca and medulla of preovulatory ovaries. Despite their relatively low numbers, they appear to still be important in ovulation, as a recent study has demonstrated that depletion of a specific CD8+ subset of T-cells in the ovary can block ovulation [Zhou et al., 2009]. This was achieved using an antibody against thymus expressed chemokine (TECK), which is transiently expressed in theca cells of follicles during hCG-induced ovulation [Zhou et al., 2005] and is the chemoattractant for this subset of T-cells [Zhou et al., 2009].

Just prior to ovulation, breakdown of the basement membrane separating the vascularised theca layer from the avascular mural granulosa cell layer occurs, allowing invagination of the theca layer into the preovulatory follicle (see Chapter 1 for more details) and infiltration of immune cells from the blood into the follicular antrum. Thus, leukocytes have been isolated in follicular fluid from women undergoing oocyte pick-up following ovarian hyperstimulation for IVF. In a recent study, in which only patients seeking IVF for male factor infertility were included, leukocytes constituted 22% of the follicular fluid- derived cell population by flow cytometry, with cells expressing macrophage, monocyte and lymphocyte-specific markers [Fedorcsak et al., 2007]. Interestingly, earlier studies have indicated that

Lisa Akison 2012 117 leukocyte subpopulations in the follicular fluid of patients with idiopathic infertility are altered, with either higher levels of T lymphocytes [Lachapelle et al., 1996] or cytotoxic natural killer cells [Lukassen et al., 2003] compared to patients with male factor or .

Recently, an interesting hypothesis has been proposed linking leukocytes originating from the spleen with infiltrating leukocytes in the periovulatory ovary [Oakley et al., 2011]. Flow cytometric analysis of rat ovaries demonstrated that the LH/hCG surge induces a massive influx of leukocytes into the ovary during ovulation, concomitant with the release of millions of leukocytes from the spleen into the blood [Hedin, 2010; Oakley et al., 2010]. In addition, splenectomised rats showed a significant reduction in leukocyte sub-populations in the ovary after hCG injection compared to intact animals [Oakley et al., 2010]. There is also one report of a delay in ovulation in 69% of splenectomised rats, specifically when splenectomy was done on the morning of metestrous [Matsuyama et al., 1987]. Ovulation was delayed by one day when compared against intact animals, but was restored to normal when splenectomised rats were injected with splenocytes from a metestrous or estrous rat, or when injected specifically with macrophages separated from the splenocyte preparation. However, ovulations still occurred in all rats irrespective of treatment.

There are many inflammatory mediators that are induced in the ovarian follicle during the periovulatory period (see [Richards et al., 2008; Wu et al., 2004] and Figure 4.1), with several suggested to play specific roles during ovulation. These include cytokines/chemokines such as IL1, IL6, IL8, TGF/, IFN, GM-CSF and activin which are thought to be secreted by leukocytes infiltrating the ovary [Wu et al., 2004] as well as being specifically expressed in periovulatory COCs and granulosa cells [Hernandez-Gonzalez et al., 2006; Shimada et al., 2006a]. Many of these inflammatory mediators can also regulate the production of proteases. For example, IL1 inhibits the LH-induced activity of plasminogen activator (PA) in vitro [Bonello et al., 1995] and thus may mediate a regulatory loop controlling the extent and distribution of PA activity in preovulatory follicles. In addition, both endothelial and inducible nitric oxide synthases (eNOS/iNOS) are expressed in the theca [Zackrisson et al., 1996], producing nitric oxide (NO), which mediates the actions of IL1 and contributes to vasodilation. Mutant mouse models lacking NOS enzymes (reviewed by [Dixit and Parvizi, 2001]) and pharmacological inhibition of NO production [Bonello et al., 1996] reduce the number of ovarian leukocytes and ovulation rate. Finally, prostaglandins have long been recognised to be important inflammatory mediators in the ovary. In response to the LH surge, the synthesising enzyme, prostaglandin-endoperoxide synthase 2 (PTGS2), is highly induced in granulosa cells as shown in rat [Sirois and Richards, 1992], mouse [Mori et al., 2011], cow [Sirois, 1994] and monkey [Duffy and Stouffer, 2001]. Importantly, this enzyme has been shown to be essential for ovulation, as PTGS2-null mice fail to ovulate [Davis et al., 1999;

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Dinchuk et al., 1995; Lim et al., 1997] and anti-inflammatory PTGS2 inhibitors, such as indomethacin, block ovulation [Tanaka et al., 1991].

In this chapter, I examined whether PGR could be regulating inflammatory mediators in the ovary just prior to ovulation. Given the anovulatory phenotype of the PRKO mice, it is reasonable to hypothesise that inflammatory events are altered in the PRKO ovary during the periovulatory period, thus contributing to the ovulatory defect. There is currently very little known about PGR-regulation of specific immune genes. Only one ovarian cytokine, IL6, has been demonstrated to have reduced LH- induced expression in PRKO granulosa cells [Kim et al., 2008]. Additionally, SNAP25, a component of the SNARE exocytosis complex which is involved in secretion of IL6 and at least 6 other cytokines, has also been demonstrated to have reduced expression in preovulatory PRKO granulosa cells [Shimada et al., 2007]. Thus, the apparent regulation of IL6 by PGR may in fact be a consequence of PGR- regulation of SNAP25.

Aside from IL6/SNAP25, there is some evidence that expression of the prostaglandin synthesis enzyme, PTGS2, may be regulated by PGR. However, reports for this are conflicting (see Section 1.5.5.2 for more detail). In vitro studies using PGR inhibitors show attenuation or inhibition of PTGS2 and/or PGE2 in preovulatory follicles, ovaries or isolated granulosa cells [Bridges et al., 2006; Hedin and Eriksson, 1997; Pall et al., 2000; Tsai et al., 2008], as do mice treated with RU486 or trilostane [Mori et al., 2011]. However, PTGS2 expression does not appear to differ in ovaries of PRKO mice compared to their normal littermates [Kim et al., 2008; Robker et al., 2000].

Therefore, the first aim of this chapter was to use low density arrays to compare the expression of a suite of inflammatory genes in PRKO and PR+/- whole ovaries immediately prior to ovulation. These arrays included PTGS2. The second aim was to fully characterise the mRNA and protein expression of PTGS2 in whole ovaries, granulosa cells and COCs, specifically its induction by LH and regulation by PGR.

4.2 Materials & Methods

4.2.1 Animals, tissue collection and RNA extraction

PRKO and PR+/- mice (n = 8 per genotype) were treated with eCG, followed 44 h later by hCG as described in Section 2.1.2. Whole ovaries were collected at 10 h post-hCG as described in Section 2.1.5, snap-frozen in liquid nitrogen and stored at -80C. Granulosa cells and COCs were also isolated from a different cohort of PRKO and PR+/- mice at 4 h, 8 h or 10 h post hCG. Individual mice

Lisa Akison 2012 119 constituted the biological replicates for each genotype (4 mice per cell type per time point). RNA extractions and DNase treatment were performed as detailed in Section 2.3. RNA concentration and quality was assessed using a Nanodrop ND-1000 Spectrophotometer (Biolab Ltd, Clayton Vic, Australia).

4.2.2 Taqman Low Density Arrays

RNA samples were reverse transcribed to form cDNA using Superscript III polymerase as detailed in Section 2.4. Each 60 μl reaction included 600 ng of DNase-treated RNA and 1 μl (20 U) of reverse transcriptase. Genotypes were verified for all cDNA samples by running a PCR using the PGR genotyping primers listed in Section 2.1.3. Expression of ribosomal protein L19 (Rpl19) was compared across samples to validate sample integrity and quantity of starting material. Real-time PCR was performed for 89 immune-related genes and 7 putative endogenous control genes (96 in total) using the Mouse Immune Taqman Low Density Array V2.0 (catalog 437786; Applied Biosystems, Mulgrave, Vic, AU) following the manufacturer’s instructions. For the full list of genes examined, see Appendix 1. Briefly, 100 ng of RNA equivalent reverse-transcribed cDNA was made up to a volume of 100 μl in Taqman Gene Expression Master Mix (Applied Biosystems, Mulgrave, Vic, AU) and applied to the Taqman Array microfluidic card. Loaded arrays were run on the Applied Biosystems 7900HT Fast Real Time PCR System (Applied Biosystems, Mulgrave, Vic, AU) using the following thermal profile: 50C for 2 mins, 94.5C for 10 mins and 40 cycles of 97.0C for 30 secs and 59.7C for 1 min. The most stably expressed endogenous control was determined from the 7 putative genes provided on the array (18S, Actb, Gapdh, Gusb, Hprt1, Pgk1, and Tfrc) using the geNorm gene expression stability measure, M, calculated using qbasePLUS software (available from www.biogazelle.com; see [Hellemans et al., 2007; Vandesompele et al., 2002] for more information). Briefly, the geNorm algorithm determines the pair-wise variation for each control gene with all other reference genes as the standard deviation of the logarithmically transformed expression ratios. An M value was calculated for each putative endogenous control gene by calculating the average pair-wise variation of a particular gene with all other control genes included in the analysis. Genes with the lowest M value have the most stable expression. Sequential elimination of the least stable gene (highest M value) generates a ranking of genes according to their M values and identification of the most stably expressed endogenous control in the samples under analysis. Expression of each putative control gene was also compared between treatments to discount any genes with evidence of PGR regulation. Once an endogenous control was selected, fold change was calculated using the CT Method [Livak and Schmittgen, 2001]. One of

Lisa Akison 2012 120 the PR+/- samples was randomly assigned as the calibrator sample. Fold change was normalised to the PR+/- mean fold change which was set at 1.0 for each gene.

4.2.3 Real-time PCR

Ptgs2 mRNA expression was quantified in the 10 h post-hCG whole ovary cDNA from Section 4.2.1 to confirm the Low Density Array results using an independent set of primers designed in-house to a different region of the Ptgs2 gene (see Table 2.2 for details). A QuantiTect Primer Assay (Qiagen, Pty. Ltd., Doncaster, Vic, AU) was used for measuring expression of the endogenous control, Rpl19 (Mm_Rpl19_1_SG). Amplification efficiency of the gene of interest was comparable to the internal control. These same primers were then used to examine the expression of Ptgs2 in a time course of granulosa cells and COCs collected from PRKO and PR+/- mice at 44 h eCG + 4 h, 8 h or 10 h post- hCG. All real-time PCR assays were performed as described in Section 2.4. Briefly, each reaction included 10 ng of cDNA (5 ng/μl) and 2.5 μl Quantitect Primer Mix for Rpl19 or 0.2 μl each of sense/antisense primers for Ptgs2 (12.5 μM) in a 20 μl reaction using Power SYBRGreen Master Mix (Applied Biosystems, Mulgrave, Vic, AU). Samples were analysed in triplicate on a Corbett Rotor-Gene 6000 Real-time Rotary Analyzer (Corbett Research Pty Ltd, Sydney, NSW, AU). Time course samples were analysed over 3 runs, with at least one sample for each tissue type and time point included on each run. A 10 h post-hCG whole ovary sample was used as the calibrator sample and was included on all runs. Each gene (including the housekeeper, Rpl19) was run on separate days on the same cDNA. However, Rpl19 was included for the calibrator on every PCR run to check for between-run variation. The same Rotorgene machine was used for all reactions. Gene expression was expressed as fold change relative to the calibrator using the CT Method [Livak and Schmittgen, 2001]. For analysis of expression in PRKO and PR+/- cells, all data was normalised to the 4 h PR+/- COC sample (fold change = 1.0).

4.2.4 Immunohistochemistry

In situ expression of PTGS2 protein was examined in ovarian sections by immunohistochemistry. Ovaries were collected from PR+/- (n = 4) and PRKO (n = 5) mice at 44 h eCG + 10 h post-hCG, with 3-4 sections stained per animal. Detailed methods for tissue processing and sectioning are given elsewhere (Section 2.6.1). General methods for immunohistochemistry are given in Section 2.7. The PTGS2 rabbit polyclonal primary antibody (Cayman Chemical Co., Ann Arbor, MI, USA) was used at 1:100 concentration and the secondary antibody (biotinylated goat--rabbit IgG; Vector Labs, Burlingame, CA, USA) was used at 1:500 concentration. Negative controls had the primary antibody Lisa Akison 2012 121 omitted. Antigen retrieval was done by boiling under pressure in citrate buffer (details Section 2.7). Stained sections were imaged at 40X resolution using the NanoZoomer HT Digital Pathology System (Hamamatsu Photonics K.K., Japan).

4.2.5 Statistical analyses

For the Low Density Arrays, expression in PRKO samples was considered significantly different from PR+/- samples at P<0.05 using individual unpaired Student’s t-tests for each gene. For analysis of other real-time PCR assays, either an unpaired Student’s t-test (whole ovaries from PRKO and PR+/- mice) or two-way ANOVA and Holm-Sidak post-hoc test (granulosa cell/COC time course from PRKO and PR+/- mice) was used to determine statistically significant treatment groups at each time point (P<0.05). Real-time PCR data were analysed after testing for homogeneity of variances and a normal distribution and performing data transformation as required.

4.3 Results

4.3.1 Taqman Low Density Immune Arrays

Low density arrays with an unbiased selection of 89 pre-loaded immune gene primers were used to examine dysregulation in genes associated with a variety of immune processes in PRKO relative to PR+/- ovaries just prior to ovulation (see Appendix 1 for a complete list of genes on the array). These included genes encoding cytokines and cytokine transcription factors; chemokine ligands and receptors; macrophage, T-cell and other immune cell markers; prostaglandin synthesising enzymes; endothelial adhesion receptors/factors and factors involved in vasoconstriction/dilation. Examination of raw CT values for the normal (i.e. PR+/-) ovary samples indicated that almost all the genes of interest were expressed in the ovary at 10 h post-hCG (91%) and only 8 genes were not detectable in any samples (i.e. Cxcl11, Cyp1a2, H2-Ea, Il2, Il3, Il4, Il9, Lta with CT = 40). However, the majority of expressed genes had relatively low expression in normal ovarian tissue, with average CTs of ≥30 (55.5%).

There were 7 putative endogenous control genes included on the array, with all but one of these genes expressed at the same level in PR+/- and PRKO genotypes (Figure 4.3A). The exception was Hprt1 which had a significantly higher mean CT value in the PRKO samples relative to the PR+/- samples (Figure 4.3A). The geNorm analysis ranked the endogenous control genes provided on the array in terms of their expression stability across all the ovarian samples and identified Hprt1 and Actb to be the Lisa Akison 2012 122

A) ns+ 26 ** PR+/- ns PRKO 24 ns+

22

ns 20 ns CT (Mean SE)+ CT (Mean 18

10 ns 8

6 B) Tfrc Gusb 18S Gapdh Pgk1 Hprt1 Actb Putative Endogenous Control Genes 0.210 0.205 B) 0.200 0.195 0.190 0.185 0.180 0.175 0.170 0.165 0.160 0.155 geNorm M 0.150 0.145 0.140 0.135 0.130 0.125 0.120 0.115 Tfrc Gusb 18S Gapdh Pgk1 Hprt1 Actb Endogenous controls

Figure 4.3 Endogenous control gene expression in 10 h post-hCG ovary samples. A) Comparison of expression of putative endogenous control genes between genotypes (n = 8 per genotype). Data shown as mean Cycle Threshold (CT) + SE. Significant differences were determined between genotypes individually for each gene using Student’s t-test or Mann-Whitney Rank Sum Test (where variances were unequal, indicated by +). ** P<0.01. ns = not significant at P<0.05. B) The geNorm stability measure, M, was calculated using qbasePLUS software for 7 putative endogenous control genes in 10 h post-hCG ovary samples used in the Taqman Low Density Immune Array (n = 8 per genotype as for A). Genes with the lowest M values have the most stable expression; therefore Actb was the most stably expressed endogenous control for this experiment.

Lisa Akison 2012 123 most stably expressed (Figure 4.3B). Therefore, geNorm recommended the use of both Hprt1 and Actb as endogenous controls. However, as Hprt1 was found to be differentially expressed between the two genotypes, Actb was selected as the sole endogenous control gene for analysis of fold change. Ovaries of PRKO mice exhibited an altered inflammatory gene expression profile at 10 h post hCG, 2 h prior to ovulation. A total of 17 of the 81 immune-related genes detectable in normal ovaries at this time point were differentially expressed in PRKO ovaries compared to PR+/- ovaries (21% of genes; Figure 4.4). One of the immune genes that was dramatically different was Ptgs2, which was reduced more than 3-fold in PRKO ovaries (Figure 4.4). Expression of both E-selectin (Sele) and CD34, leukocyte adhesion receptors expressed on endothelial cells in response to inflammatory stimuli, were significantly decreased 2-3 fold in PRKO ovaries (Figure 4.4). However, the endothelial adhesion receptor, Vcam1, was not significantly different. Also, P-selectin (Selp), which is primarily expressed on leukocytes, was not different. The vasoconstrictive peptide, endothelin 1 (Edn1), and its synthesising enzyme, endothelin converting enzyme 1 (Ece1) were also reduced in the PRKO ovaries compared to PR+/- ovaries (Figure 4.4). Edn1 was the only endothelin included on the array.

PRKO ovaries also exhibited dysregulated expression of the cytokines Il6, Il18, Tgf1, Il1, and Il10. In particular, Il6 was reduced more than 4-fold in PRKO ovaries at this time while Il18 and Tgf1 were up-regulated almost 1.5-fold in PRKO ovaries (Figure 4.4). However, ten other cytokines detected in PR+/- ovarian tissue were also expressed normally in the PRKO ovaries (Il1, Il5, Il7, Il12/β, Il13, Il15, Il17, Il18 and Tnf). Several transcription factors were included on the array, including Smads (Smad3, Smad7) which are involved in Tgfβ signalling; Nfkbs (Nfkb1 and Nfkb2) which regulate many inflammatory genes; and Stat and Socs genes (Stat1, Stat3, Stat4, Stat6, Socs1, Socs2) which are involved in activation and inhibition of cytokine signalling respectively. Of these, Stat3 was down- regulated while Socs1 and Nfkb2 were up-regulated in PRKO ovaries relative to PR+/- ovaries (Figure 4.4). There were also genes for many immune cell markers on the array (see Appendix 1 for more details) including specific chemokine receptors (and their ligands) and cluster of differentiation (CD) proteins which are found on the surface of T-cells, B-cells, macrophages, neutrophils and natural killer cells. However, only two T-cell receptors were dysregulated in PRKO ovaries, with Ccr4 down- regulated 3-fold and CD28 up-regulated 2-fold in PRKO relative to PR+/- ovaries (Figure 4.4).

Two final genes that were up-regulated in PRKO relative to PR+/- ovaries were the pro-apoptotic Bcl- associated X protein (Bax) and heme oxygenase (decycling) 1 (Hmox1) which is an enzyme involved in heme catabolism (Figure 4.4).

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3.0 Vasoconstrictors Endothelial adhesion receptors/factors Cytokines * 2.5 Transcription factors T-cell receptors Others

2.0 ***

1.5 *** *** *** *** * up-regulated 1.0 ** *** down-regulated

Fold change (Mean SE)+ Fold (Mean change *** * *** 0.5 ** * *** * ***

0.0 Il6 (4.4) Il1b (1.8) Il10 (3.1) Bax (1.3) Bax Il18 (1.4) Sele (2.5) Ccr4 (3.0) Ccr4 Edn1 (1.6) Ece1 (1.3) Stat3 (1.3) Cd28 Cd28 (2.2) Cd34 Cd34 (1.8) Ptgs2 (3.8) Nfkb2 (1.2) Tgfb1 (1.4) Socs1 Socs1 (1.8) Hmox1 (1.2) Hmox1

Figure 4.4 PGR regulates immune genes in the periovulatory ovary. Expression of a panel of 89 immune-related genes was examined in PRKO (n = 8) and PR+/- (n = 8) ovaries collected at 10 h post-hCG using Taqman Mouse Immune Arrays. Of these, 81 genes were expressed in normal ovaries at this time point and 17 genes were differentially expressed in PRKO relative to PR+/- ovaries. All fold change values for PRKO samples were normalised to the mean fold change for PR+/- ovaries which was set at 1. Therefore, genes with a fold change value above the line were up-regulated in PRKO ovaries and genes with a fold change value below the line were down-regulated in PRKO ovaries. The magnitude of the fold change is given in brackets after the symbol for each gene. Significant differences between gene expression in PR+/- and PRKO samples were determined separately for each gene using Student’s t-tests. * P<0.05; ** P<0.01; *** P<0.001.

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As previous reports in the literature of PGR-regulation of Ptgs2 in the ovary are conflicting, the expression of this gene in PRKO and PR+/- whole ovaries and isolated ovarian cells was further characterised during the periovulatory period. First, the Immune Array result was confirmed using an independently designed set of primers to the Ptgs2 gene. These same primers were then used to examine the expression of Ptgs2 in granulosa cells and COCs isolated from PRKO and PR+/- mice at three time points leading up to ovulation. Finally, the expression of PTGS2 protein was compared in PRKO and PR+/- ovarian sections using immunohistochemistry.

4.3.2 Ptgs2 mRNA expression

The reduced expression of Ptgs2 mRNA in the 10 h post-hCG PRKO ovary samples was confirmed with a different set of primers using real-time PCR (Figure 4.5A), with a 5-fold reduction in expression compared to the PR+/- samples. In order to determine if this difference was due specifically to dysregulation in follicular cells, Ptgs2 expression was measured in granulosa cells and COCs isolated from PRKO and PR+/- mice at 4 h, 8 h and 10 h post-hCG. At 4 h post-hCG, Ptgs2 expression was significantly higher in granulosa cells compared to COCs but there was no difference in the expression between genotypes (Figure 4.5B). By 8 h post-hCG, the overall expression of Ptgs2 was much lower but there was no difference between cell type or genotype by two-way ANOVA (Figure 4.5B). Similar low levels of Ptgs2 were measured at 10 h post-hCG, and although there was a trend for lower expression in the PRKO COC samples relative to the PR+/- COC samples, there was no statistically significant difference between genotypes or cell types at this time point using a two-way ANOVA for the analysis (Figure 4.5B). A t-test comparing just the COC samples at this time point did reveal a statistically significant difference in mRNA expression. Therefore, the dramatic reduction in Ptgs2 expression observed for the whole ovary samples at 10 h post-hCG does not appear to be due to differences in expression specifically in granulosa and/or COCs.

4.3.3 PTGS2 immunohistochemistry

PTGS2 protein expression was measured in sections of PRKO and PR+/- ovaries collected at 10 h post-hCG using immunohistochemistry. Strong staining was localised to granulosa cells and COCs of antral follicles, but staining was also found in the stroma (Figure 4.6). There was no apparent difference in the degree of staining between genotypes. Some sections showed strong staining of oocytes in follicles of all stages, but non-specific staining of oocytes is frequently observed with many

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A) ** 1.2

1.0

0.8

0.6

0.4

0.2 Relative fold change (Mean + SE) Relative (Mean fold change 0.0 PR+/- PRKO B) 3.0 *** PR+/- 2.5 PRKO

2.0

1.5 Fold Change 1.0

0.5

0.0 COC GC COC GC COC GC 4h post-hCG 8h post-hCG 10h post-hCG Figure 4.5 Ptgs2 expression in PR+/- and PRKO ovaries, COCs and granulosa cells. A) Ptgs2 expression was measured by RT-PCR in eCG + 10 h post-hCG whole ovaries (n = 8 per genotype), previously used in the Low Density Immune Array. Data is shown as fold change (mean + SE) relative to PR+/- (set at a fold change of 1). ** = significantly different by Student’s t- test (P<0.001). B) Cumulus oocyte complexes (COCs) and granulosa cells (GCs) were isolated from PR+/- and PRKO ovaries at eCG + 4 h, 8 h and 10 h post-hCG (n = 4 samples per tissue and time point). All data was normalised to the 4 h PR+/- COC sample (fold change = 1). Significant differences between cell type and genotype were determined at each time point by two-way ANOVA and Holm-Sidak post-hoc test. The 8 h and 10 h data sets were log-transformed before analysis due to non-normal distribution. *** = P<0.001.

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Figure 4.6 Whole ovary (5X) Follicles (10X) Stroma (20X)

PR+/- #1

PRKO #1

PR+/- #2

PRKO #2

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Figure 4.6 (continued)

Whole ovary (5X) Follicles (10X) Stroma (20X)

PR+/- #3

PRKO #3

PR+/- #4

PRKO #4

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Figure 4.6 PTGS2 protein localisation is similar in PRKO and PR+/- ovaries. PTGS2 protein expression was examined in 10 h post-hCG ovary sections from PR+/- and PRKO mice by immunohistochemistry. Expression was localised to GC and COC from antral follicles and was also found in the ovarian stroma. Staining was comparable between PRKO and PR+/- mice (n = 4 of each). Inset photomicrograph is from sections processed with no primary antibody as a negative control.

Lisa Akison 2012 130 antibodies (e.g. [Kim et al., 2004; Teilmann et al., 2006; Xing et al., 2006]; our own observations) and therefore this is considered artefact.

4.4 Discussion

This chapter clearly demonstrates that specific aspects of the inflammatory profile induced at ovulation are disrupted in PRKO mice (Figure 4.7). Given that PRKO mice are anovulatory, these changes may provide evidence for cellular mechanisms by which immune cells and immuno-modulators contribute to the process of ovulation. These include the production of inflammatory cytokines, endothelial adhesion and subsequent activation of specific immune cells, the synthesis of prostaglandins, vasoconstriction and apoptosis. Of the 17 genes that were found to be dysregulated in the PRKO ovaries, only 5 have been previously shown to play some role in ovulation (Table 4.1). These are the cytokines, Il6 and Il1, the prostaglandin synthesis enzyme, Ptgs2, the pro-apoptotic Bax and the heme gene, Hmox1. Notably absent from the list of dysregulated genes, were macrophage/monocyte markers of which there were 6 genes included on the array (Cd40, Cd68, Cd80, Cd86, Cxcl10, Cxcl11).

Inflammatory cytokines altered in PRKOs

Cytokines are soluble, protein signalling molecules that can have myriad effects on cells particularly those of the immune system. They include interleukins and TGF super-family members [Cannon, 2000] which are produced primarily by leukocytes. For example, IL6 is produced by neutrophils and macrophages in response to injury and is one of the mediators of the ‘acute phase’ response [Akira and Kishimoto, 1992], as are the IL1 proteins, IL1 and IL1 [Dinarello, 1994]. In addition, IL18 has relatively recently been designated as part of the IL1 superfamily [Huising et al., 2004]. Each of these interleukin genes, as well as the anti-inflammatory cytokine, Il10 [Fiorentino et al., 1991a; Fiorentino et al., 1991b], were dysregulated in PRKO ovaries immediately prior to ovulation, Il6 dramatically so. Further, Tgf1, which is also secreted by leukocytes and regulates immune cell differentiation, proliferation and activation [Letterio and Roberts, 1998], was also dysregulated. This suggests that the inflammatory response during the periovulatory period is disrupted in PRKO ovaries. Each of these cytokines has been previously identified in normal, healthy ovaries by RT-PCR [Burke et al., 1996]; however, only Il6 and Il1 appear to be specifically involved in the process of ovulation (Table 4.1).

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Figure 4.7 PGR regulation of immune genes in the periovulatory ovary. Taqman immune arrays revealed that genes involved in vasoconstriction, endothelial adhesion of immune cells, T-cell activation, prostaglandin synthesis and cytokine signalling were dysregulated in PRKO ovaries just prior to ovulation. In addition, the pro-apoptotic Bax gene and heme catalysis gene, Hmox1, were up-regulated in PRKO ovaries. Ptgs2 was decreased in PRKO whole ovaries but not in isolated granulosa cells or COCs.

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Table 4.1 Differentially expressed immune genes in whole ovaries at 10 h post-hCG.  indicates up-regulated and  indicates down-regulated in PRKO relative to PR+/- ovaries. Fold change and significance values given in Figure 4.3.  Demonstrated role in ovulation. Gene Symbol Gene Name Specific Function Role in ovulation? Vasoconstriction Edn1  endothelin 1 Vasoconstriction Not demonstrated; Edn2 yes Ece1  endothelin converting Processing of endothelins Indirectly; processes all endothelins enzyme 1 Endothelial adhesion receptors/factors Cd34  CD34 antigen Angiogenesis marker Unknown, but induced by LH/hCG in COCs and granulosa cells [Hernandez- Gonzalez et al., 2006] Sele  selectin, endothelial cell Endothelial adhesion Unknown receptor Cytokines Il6  interleukin 6 Inflammatory cytokine IL6R KO has reduced ovulation [Molyneaux, Schaible et al. 2003] 

Il18  interleukin 18 Inflammatory cytokine No – IL18 KO have normal fertility [Takeda et al., 1998] Il1  interleukin 1 beta Inflammatory cytokine Il1b induces ovulation in rat [Brannstrom et al., 1993b; Van der Hoek et al., 1998] and restores ovulation in Ptgs2KO mice [Davis et al., 1999] but Il1R KO is fertile [Labow et al., 1997].  Il10  interleukin 10 Anti-inflammatory cytokine No – Il10 KO females used to generate experimental mice [Roberts et al., 2003] Tgf1  transforming growth ECM remodelling; T-cell/B- No – Tgf1 KO ovulates normally in factor, beta 1 cell activity; cell growth, response to exogenous gonadotrophins proliferation, differentiation [Ingman et al., 2006] and apoptosis Transcription factors Stat3  signal transducer and Cytokine transcription Unknown activator of transcription 3 factor Socs1  suppressor of cytokine Suppresses cytokine Unknown signaling 1 transcription Nfkb2  nuclear factor of kappa Pleiotrophic transcription Unknown light polypeptide gene factor; regulates many enhancer in B-cells 2 inflammatory genes Immune cell markers Ccr4  chemokine (C-C motif) T-cell receptor Unknown receptor 4 Cd28  CD28 antigen Co-stimulator of T-cell Unknown activation Other Ptgs2  Prostaglandin synthase 2 Production of Ptgs2 KO has reduced ovulation [Davis et prostaglandins al., 1999; Lim et al., 1997]  Bax  Bcl2-associated X protein Promotes apoptosis Bax KO has reduced ovulation [Greenfeld et al., 2007]  Hmox1 heme oxygenase catalyses breakdown of Hmox1 KO has reduced ovulation  (decycling) 1 heme [Zenclussen et al., 2012] 

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IL6 has previously been shown to be down-regulated in PRKO granulosa cells and may also be a downstream target of the PGR-regulated transcription factor, PPARγ [Kim et al., 2008], although a more recent study found an inverse relationship between IL6 and PPARγ expression in the COC [Liu et al., 2009b]. IL6 was shown to promote cumulus expansion independently of EGF-like factors via induction of cumulus matrix genes including Has2, Tnfaip6/Tsg6, Ptx3 and Ptgs2 [Liu et al., 2009b] and also induces other immune-related genes such as Runx1 and Runx2 [Liu et al., 2009b]. IL6 is dramatically up-regulated in COCs and granulosa cells in vivo in response to hCG, peaking at ovulation [Hernandez-

Gonzalez et al., 2006; Liu et al., 2009b] and is also induced by AREG, FSH and PGE2 in cultured COCs [Liu et al., 2009b]. Selective inactivation of the IL6 receptor component GP130 specifically in germ cells resulted in a ~60% reduction in ovulation rate [Molyneaux et al., 2003a], suggesting a direct role for this cytokine in ovulation. However, IL6 null mice appear to be fertile [Kopf et al., 1994; Poli et al., 1994] suggestive of functional redundancy of this cytokine. Interestingly, IL6 up-regulation in response to hCG has previously been shown to be associated with a concomitant up-regulation in Stat3 and down-regulation in Socs1 mRNA expression in COCs [Liu et al., 2009b]. The results in this chapter show the opposite relationship in PRKO ovaries, with down-regulation of IL6 and Stat3 and up- regulation of Socs1 in response to hCG and thus confirms that IL6 regulates the JAK/STAT pathway of cytokine-induced transcription in the ovary. Importantly, COCs matured in vitro in the presence of IL6 showed improved embryo transfer rates compared to controls, to a level comparable to in vivo-matured oocytes [Liu et al., 2009b]. Therefore, I confirmed PGR regulation of IL6 in the ovary, a cytokine potentially critical for appropriate cumulus expansion, initiation of down-stream signalling pathways and ovulation, as well as oocyte competence.

IL1 increases in the ovary in the lead up to ovulation [Brannstrom et al., 1994a], with mRNA induced in theca, granulosa and cumulus cells of preovulatory follicles in response to LH/hCG (see [Gerard et al., 2004] for review). It has been demonstrated to stimulate ovulation in perfused ovaries of rat [Brannstrom et al., 1993b; Van der Hoek et al., 1998] and rabbit [Takehara et al., 1994], and injection of the IL1 receptor antagonist (IL1RA) inhibits ovulation in vivo [Martoriati et al., 2003; Simon et al., 1994]. Interestingly, IL1 upregulates Ptgs2 expression in mouse, rat and human granulosa-luteal cells in vitro [Ando et al., 1999; Davis et al., 1999; Narko et al., 2001] and injection of this cytokine into anovulatory PTGS2-null mice restores ovulation [Davis et al., 1999]. IL1 has also been shown to regulate VEGF secretion during the periovulatory period in the rat [Levitas et al., 2000], as well as induce NO production [Ahsan et al., 1997]. Finally, IL1 also appears to induce in ovarian cells, at least in vitro, the production and activation of MMP9 [Hurwitz et al., 1993], a proteolytic enzyme which has been shown to be induced during the ovulatory period in the ovary [Robker et al., 2000]. Thus, IL1 appears

Lisa Akison 2012 134 to regulate multiple processes during the periovulatory period; yet, IL1R KO females are fertile [Labow et al., 1997], suggesting some redundancy for IL1.

The transcription factors Stat3, Socs1 and Nfkb2 have no known direct roles in ovulation, but have all been reported as being expressed in ovarian cells. Socs expression has been examined in the rat ovary but only during pregnancy [Anderson et al., 2009] or lactation [Tam et al., 2001]. Stat3 has been identified in oocytes, granulosa, cumulus and theca cells in the pig and phosphorylated Stat3 is upregulated in cultured granulosa cells in response to EGF [Wen et al., 2006]. Similarly, phosphorylated STAT3 has been identified by Western blot in granulosa cells from hCG-treated hypophysectomised rats [Russell and Richards, 1999]. It has also been identified by immunohistochemical staining in granulosa cells of primordial, activating and early secondary follicles of mouse neonatal ovaries where it has recently been shown to play a role in primordial follicle activation [Sutherland et al., 2012]. Nfkb2 has been identified in the rat corpus luteum where it regulates prostaglandin synthesis [Taniguchi et al., 2010] and has also been found to regulate CXCR4/CXCL12 and VEGF signalling in ovarian cancer cell invasion in vitro [Huang et al., 2000; Miyanishi et al., 2010]. As mentioned above, Stat3 and Socs1 appear to be regulated by IL6, but no such relationship has been found with Nfkb2 [Liu et al., 2009b]. Tissue-specific Stat3 deficient mice indicate that this transcription factor plays a role in diverse biological functions including cell growth, suppression of apoptosis and cell motility (see [Akira, 1999] for review), but to-date, knock-down of Stat3 in the ovary has not been done. Further, the Stat3 global knockout is embryonic lethal [Takeda et al., 1997]. Similarly, Socs1 null mice die at 3 weeks of age and display aberrant activation of T-cells [Marine et al., 1999]. Thus, the role of these transcription factors in regulating genes and/or cytokines involved in ovulation remains to be determined. Interestingly, a recent study has identified a synthetic inhibitor of Stat3 as a potential targeted therapeutic for cancer treatment [Madoux et al., 2011]. This inhibitor may prove useful for targeted knockdown of Stat3 in the ovary to determine its role in ovulation.

Adhesion and activation of immune cells in PRKO ovaries

Emigration of leukocytes into tissues during inflammation requires a specific sequence of immune cell capture, rolling, arrest and eventual transmigration through endothelial cells (see [Ley et al., 2007] for review). These precise cellular processes are tightly regulated by the adhesion receptors that are present on leukocytes and their counter-receptors on endothelial cells which are upregulated by cytokines during inflammation. Two endothelial adhesion receptors, endothelial cell selectin (Sele) and Cd34, were found to be down-regulated in PRKO ovaries immediately prior to ovulation. Cd34 is a cell- surface glycoprotein which is commonly used as a marker for angiogenesis as it is specifically localised to endothelial cells. Interestingly, it has also been found to be dramatically up-regulated in the COC, and less so in granulosa cells, in response to hCG injection in the mouse, peaking in the COC at 12 h Lisa Akison 2012 135 post-hCG when ovulation occurs [Hernandez-Gonzalez et al., 2006]. Immunohistochemistry revealed that this protein was localised to the membrane of cumulus cells at 8 h post-hCG [Hernandez-Gonzalez et al., 2006]. Sele has previously been identified in the microvasculature of human ovarian follicles using in vitro culture of follicle endothelial cells [Ratcliffe et al., 1999] and soluble E-selectin is elevated in sera from women with PCOS [Foltyn et al., 2011] or severe ovarian hyperstimulation syndrome following ovulation induction for IVF [Abramov et al., 2001]. Pecam1 and Icam1 are also important adhesion factors on endothelial cells involved in leukocyte capture and transmigration [Ley et al., 2007] but were not included on the array. It would be interesting to examine their expression in PRKO ovaries. However, another endothelial adhesion factor that was included on the array, Vcam1, was not significantly different in PRKO ovaries at this time point.

As a consequence of disruption of these endothelial adhesion factors, immune cell infiltration may be perturbed in the PRKO ovary, possibly contributing to the anovulatory phenotype observed in these mice. A detailed analysis of immune cell populations in PRKO compared with PR+/- ovaries during the periovulatory period using flow cytometry would be informative to determine the precise nature of immune cell infiltration in this null model. Given the recent hypothesis of the potential involvement of the spleen as the source of infiltrating leukocytes [Oakley et al., 2011], and that PGR is also expressed in leukocytes in the spleen [Butts et al., 2010], a comparative analysis of immune cell populations in PRKO and PR+/- ovaries and spleen before and after administration of eCG/hCG would be an interesting study. However, our laboratory has immunohistochemical evidence that neutrophil numbers, but not macrophages, are reduced in PRKO preovulatory follicles. Additionally, the ovarian transplant experiments suggest that it is not the supply of immune cells from outside the ovary that is critical, but rather the ovary’s ability to ‘attract’ and ‘capture’ these immune cells that is the key to successful ovulation.

Genes encoding immune cell markers for all leukocyte cell types were present on the immune array. T- cell markers Cd4 and Cd8 were expressed normally while the T-cell receptor Ccr4 and a co-stimulator of T-cell activation, Cd28, were dysregulated in PRKO ovaries. Cd28 interacts with the ligands Cd80 and Cd86 on antigen presenting cells [Lenschow et al., 1996] and Ccr4 binds to several CC chemokines including CCl2/MCP1, CCL5/RANTES and CCL4/MIP1 which have all been identified in the ovary [Burke et al., 1996; Wu et al., 2004]. Cd80 and Cd86 expression was normal. Thus, the exact nature of PGR regulation of T-cell activation requires further clarification. Expression of Ccr4 and Cd28 has only been examined in the ovary with respect to T-cell activation associated with ovarian cancer (e.g. [Fialova et al., 2012; Melichar et al., 2000]) and their roles in ovulation are currently unknown.

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Regulation of Ptgs2 in the ovary

Prostaglandins are important signalling molecules involved in the immune response and are required for stabilisation of the cumulus matrix and ovulation. The major prostaglandin in the ovary, PGE2, is synthesised by the enzyme PTGS2 (COX2), which is undetectable normally in tissues but is induced during inflammation. Ptgs2 mRNA was significantly down-regulated in PRKO ovaries relative to PR+/- ovaries from the immune array, a result confirmed using a different primer set. This suggests that prostaglandin synthesis may be perturbed in the PRKO ovary during the periovulatory period. However, analysis of Ptgs2 mRNA expression specifically in granulosa cells and COCs, did not reveal any differences in expression between PRKO and PR+/- samples at several time points leading up to ovulation, although there was a trend for reduced expression in PRKO COCs at 10 h post-hCG. Similarly, an analysis of protein expression in PRKO and PR+/- ovary sections at 10 h post-hCG by immunohistochemistry did not show any observable differences in expression between these genotypes. These conflicting results reflect similar discrepancies with respect to PGR-regulation of Ptgs2 in previous studies. PGR inhibitor studies indicate attenuation of PTGS2, both in vitro and in vivo [Bridges et al., 2006; Hedin and Eriksson, 1997; Mori et al., 2011; Pall et al., 2000; Tsai et al., 2008], while PRKO ovaries show PTGS2 expression comparable to normal littermates [Kim et al., 2008; Robker et al., 2000]. Immunohistochemistry is not considered a quantitative measure of protein in tissue, being utilised more for localisation of expression, and so a Western blot comparison of PTGS2 protein in PRKO and PR+/- ovaries is required to clarify whether there is PGR-regulation of PTGS2 protein during the periovulatory period, similar to the mRNA.

Ptgs2 knockout (Ptgs2-/-) mice show defects in ovulation [Davis et al., 1999; Dinchuk et al., 1995; Lim et al., 1997], both with and without administration of exogenous gonadotrophins. Follicular development appears normal and ovulation is reduced but is not totally blocked, with the extent of the reduction in the number of oocytes ovulated per female varying from ~90% reduction [Davis et al., 1999] to ~40% reduction [Lim et al., 1997]. Further, any oocytes that are ovulated from Ptgs2-/- mice are devoid of cumulus cells and fail to fertilise [Lim et al., 1997]. Like PRKO mice, anovulatory follicles contain entrapped oocytes and by 36 h post-hCG, luteinisation and corpus luteum formation has occurred around the oocyte. However, unlike PRKO mice, cumulus expansion appears to be attenuated in Ptgs2 knockout mice and there is a lack of organised cumulus cell polarisation around the oocyte in the corona radiata [Davis et al., 1999]. Thus, although both PRKO and Ptgs2-/- mice have ovulation defects, the underlying mechanisms appear to vary between models.

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Potential PGR-regulated vasoconstriction and neovascularisation

The genes encoding the vasoconstrictive factor endothelin 1 (Edn1) and the converting enzyme responsible for processing all endothelins, Ece1, were both down-regulated in PRKO ovaries during the periovulatory period. Edn1 has previously been shown to be reduced in PRKO ovaries [Sriraman et al., 2010] and specifically induced by PGR-A in cultured granulosa cells [Sriraman et al., 2010]. However, it has not been shown to play a role in ovulation, but rather appears to be involved in folliculogenesis, steroidogenesis and luteolysis (see [Bridges et al., 2011] for review). Interestingly, Vegfa and Agtr2, which like Edn1 are involved in regulating vascular function and angiogenesis, were not dysregulated in the PRKO ovaries. In contrast, the decreased expression of the endothelial marker, Cd34, in PRKO ovaries suggests that angiogenesis/vascularisation may be impaired in these ovaries. Histological examination of PRKO ovaries (see Chapter 3) did not suggest any differences in vascularisation compared to PR+/- ovaries during the periovulatory period. However, immunohistochemical staining with CD34, as has been used previously to study cyclic changes of vasculature in normal ovaries [Suzuki et al., 1998b], would be informative for a more quantitative assessment of neovascularisation in PRKO ovaries during the lead up to ovulation.

Apoptotic Bax and Hmox in PRKO ovaries

The pro-apoptotic Bax gene and heme oxygenase (decycling) 1 (Hmox1) were both up-regulated in PRKO ovaries during the periovulatory period, although fold-change differences were relatively minor. To date, this is the first report of PGR regulation of these genes in the ovary. Interestingly, null mouse models for both of these genes show reduced ovulation rates. Hmox1-/- mice ovulated significantly less oocytes after hormonal stimulation (137 from 8 mice) compared to age-matched wild-type controls (208 oocytes from 8 mice), despite normal growth and development of follicles [Zenclussen et al., 2012]. Cumulus expansion was not assessed in this knockout mouse model. These mice have also been shown to have reduced fertilisation rates in vitro [Zenclussen et al., 2012], delayed blastocyst attachment and defective placentation resulting in intrauterine growth restriction and fetal death [Zenclussen et al., 2011]. Heme oxygenases catalyse the first and rate-limiting step in heme catabolism to form biliverdin (eventually converted to bilirubin in the liver), carbon monoxide and free iron [Tenhunen et al., 1968]. HMOX1 has been localised by immunohistochemistry to granulosa and theca cell layers of follicles in mature rats and appears to play a role in steroidogenesis [Alexandreanu and Lawson, 2003]. In other tissues, it has been found to modulate inflammation and is cytoprotective [Otterbein et al., 2000; Otterbein et al., 2003; Petrache et al., 2000]. It has been proposed that HMOX1 may also play this role in the ovary, conferring cytoprotection for the oocyte during the inflammatory process of follicle rupture [Zenclussen et al., 2012].

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Bax-/- mice also show reduced ovulation rate (~40%) compared to wild-type mice following super- ovulation, despite similar numbers of antral follicles in both genotypes [Greenfeld et al., 2007]. Bax-/- mice had greater numbers of primordial follicles at 3 months of age and more primordial, primary and preantral follicles at 13 months of age. Bax is a pro-apoptotic member of the BCL-2 , important regulators of apoptosis in many cell types which are also expressed in growing follicles (see [Hussein, 2005] for review). Thus ablation of Bax prevented follicle loss due to apoptosis during follicle growth and development. That ovulation rate was reduced in these mice seems counter-intuitive, given the increased number of follicles in these mice, a discrepancy which has yet to be adequately explained. Our results suggest that Bax is upregulated in PRKO ovaries during the periovulatory period, which would result in an increase in apoptosis. Bax is also linked to luteogenesis in the ovary [Hussein, 2005] and thus its elevated expression in PRKO ovaries may simply reflect terminal differentiation and luteinisation of granulosa cells as ovulation approaches.

This chapter revealed PGR-regulation of immune-related genes, some novel, immediately prior to ovulation, in whole mouse ovaries. These changes may provide evidence for cellular mechanisms by which immune cells and immuno-modulators contribute to the process of ovulation. Given that PGR is specifically induced in granulosa cells in response to LH/hCG, the next chapter will examine the effect of PGR ablation on gene expression in granulosa cells isolated from ovaries at the time of peak PGR expression in normal tissues at 8 h post-hCG.

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Chapter 5 – PGR-regulated genes in granulosa cells of periovulatory follicles

5.1 Introduction

The profound anovulatory phenotype of female PRKO mice is characterised by a specific defect preventing follicle wall breakdown and release of the oocyte at ovulation. Thus, this transgenic model presents a unique opportunity to investigate molecular pathways specifically underlying this process. PGR is known to regulate gene transcription in other reproductive tissues such as the uterus [Cheon et al., 2002; Jeong et al., 2005] and mammary gland [Santos et al., 2009] and has also been identified as an important regulator of downstream target genes in the ovary [Kim et al., 2009a; Robker et al., 2009]. To fully understand the nature of P4 action during ovulation, it is critical to identify the PGR-regulated genes and pathways and how the various molecules interact in order to produce the biological events required for follicle wall degradation and COC release. Genome wide approaches, such as DNA microarray analysis, provide an invaluable unbiased survey of global gene expression in a single assay. These expression profiles can then be compared between treatments, or in our case genotypes, to identify differentially expressed genes. Thus, microarray analysis can be used to not only test hypotheses, but also generate new hypotheses about biological processes or functions that may be important to the area of interest [Gibson, 2003].

A summary of the genes currently identified to be PGR-regulated in the ovary was presented in Section 1.5.5. However, very few of these have been demonstrated to play a direct role in ovulation, and knockout or inhibition of these gene products individually only results in a reduction in ovulation rate and not total anovulation. No doubt, a combination of these factors is required. Despite these discoveries, the exact nature of pathways downstream of PGR during the ovulatory process is largely unknown.

There have been several studies, each describing specific PGR-regulated genes in the ovary, in which the authors disclose that the discovery of these genes was from unpublished gene expression profiling/microarray studies carried out by their own laboratories [Kim et al., 2009a, b; Kim et al., 2008; Palanisamy et al., 2006; Robker et al., 2000; Sriraman et al., 2008; Sriraman et al., 2006]. However, one lab did not disclose the time post-hCG that samples were collected for analysis [Sriraman et al., 2008; Sriraman et al., 2006], and in all cases, the array studies were conducted on whole ovaries. One microarray study by Kim and co-workers, from which specific genes were reported in 3 publications [Kim et al., 2009a, b; Kim et al., 2008], revealed that 310 genes were down-regulated >1.5 fold and 114

Lisa Akison 2012 140 genes were up-regulated >1.5-fold in PRKO versus PRWT ovaries. To-date, there have been only two studies to publish at least portions of their microarray data on PGR-regulated genes in the ovary [Friberg et al., 2010; Sriraman et al., 2010], with both studies conducted on granulosa cells treated in vitro with PGR antagonists. However, even one of these studies [Friberg et al., 2010] recognised the limitations of such an approach by acknowledging that the use of a PGR antagonist to study transcriptional regulation by P4 could include genes that are not actually regulated by P4 in vivo. This is due to the inherent properties of antagonists, such as partial agonism [Tung et al., 1993].

In response to the LH surge, PGR expression is transiently induced, specifically in the mural granulosa cells of preovulatory follicles that are destined to ovulate. Presumably then, its transcriptional regulation of target genes would also occur in these cells, with maximal impact coincident with peak protein abundance. Therefore, the primary aim of this chapter was to use a genome-wide, microarray approach to detect differentially expressed genes in periovulatory granulosa cells isolated from PRKO and PR+/- mice at 8 h post-hCG. This is when PGR expression is maximal in the ovary [Ismail et al., 2002; Robker et al., 2000; Teilmann et al., 2006]. Specifically, genes associated with processes that may be involved in ovulation were identified. In addition, one novel gene identified was validated using RT-PCR and expression examined in a time course of tissues/cells collected after administration of hCG. The gene chosen was one that has not previously been described in detail in the ovary, or identified as being involved in ovulation – the chemokine receptor CXCR4. However, this gene is known to be expressed in the ovary and, with its chemokine ligand CXCL12 (previously known as stromal cell-derived factor 1 or SDF1), has known functions in cell adhesion, chemotaxis, migration and invasion in other cells and systems, particularly immune cells and cancer cells. These are all processes hypothesised to be involved in the release of the oocyte at ovulation. Information on this signalling axis is given below.

5.1.1 The CXCL12/CXCR4 chemotactic signalling axis

Chemokines are chemotactic proteins that interact with G-protein coupled, 7-transmembrane receptors, to facilitate migration and invasion by cells in many different systems [Taub and Oppenheim, 1994]. Receptor activation induces a cascade of intracellular signalling pathways that ultimately regulates the trafficking of cells. One such chemokine axis is the CXCL12/CXCR4 axis. CXCL12 is the sole ligand for the receptor, CXCR4, which is also a co-receptor for the X4 strains of human immunodeficiency virus or HIV [Feng et al., 1996]. Thus, there is much interest in this receptor as a potential therapeutic for HIV infection. It was originally thought that CXCR4 was the only receptor for CXCL12, but more recently this chemokine has been found to bind to other receptors including orphan receptor RDC1

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(now known as CXCR7 [Balabanian et al., 2005]), and syndecan-4 [Charnaux et al., 2005]. As per other chemokines, CXCR4 is a G-protein coupled receptor and ligand binding frees Gβ & Gγ protein subunits, triggering specific downstream target molecules and intracellular pathways [Maghazachi, 1999]. These pathways regulate cell motility, chemotaxis, proliferation and survival and vary with cell type [Kucia et al., 2004; Murdoch, 2000; Scotton et al., 2002]. With respect to cell motility, the main pathways involved are phospholipase C (PLC)/protein kinase C (PKC), phosphatidylinositol-3-kinase (PI3K) and MAP-kinase via ERK1/ERK2 [Ganju et al., 1998]. More recently, noncanonical WNT signalling via PKC has also been implicated in cell migration via the CXCR4/CXCL12 axis [Ghosh et al., 2009].

Six splice variants of CXCL12 have been identified (CXCL12, CXCL12β, CXCL12γ, CXCL12ε, CXCL12δ, CXCL12θ) arising from alternate splicing of a single gene [Altenburg et al., 2007]. CXCL12 and CXCL12β are the most similar, with CXCL12β only having an extra 4 amino acids at the carboxy terminus. Mouse CXCL12 and CXCL12β are >92% homologous to human CXCL12 and CXCL12β [Shirozu et al., 1995]. Only CXCL12 and CXCL12β have been identified in neonatal and adult mouse ovaries [Holt et al., 2006] and CXCL12 is the most widely described and best characterised in the literature.

In the ovary, CXCR4 expression is up-regulated 8-12 h post-hCG [Hernandez-Gonzalez et al., 2006; Kim et al., 2009b]. There is also a dramatic (82-fold) up-regulation of CXCR4 expression in the COC 8 h post-hCG in the mouse [Hernandez-Gonzalez et al., 2006]. The timing of this up-regulation suggests that this receptor may be important during the pre-ovulatory period. CXCR4 may also be a potential indicator of human embryo viability, as its expression was down-regulated in cumulus cells from COCs that resulted in an early-cleavage embryo [van Montfoort et al., 2008].

However, the mechanism of regulation and functional role of the CXCL12/CXCR4 axis in the ovary is unclear. It may be involved in migration and/or recruitment of immune cells or it may activate other downstream genes (e.g. ERK-1/2, MMPs) which are known to be important for ovulation. It may also play a pro-angiogenic role. Later in this chapter, the expression of CXCR4 in ovarian cells is characterised across the periovulatory period, both mRNA and protein. Also, its potential role in ovulation is examined by injecting mice with the specific CXCR4 antagonist, AMD3100.

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5.2 Materials & Methods

5.2.1 Tissue collection, RNA extraction and quality control

For the microarray study, granulosa cells were collected from PRKO and PR+/- mice as per Section 2.1.5. Briefly, cells were collected at 8 h post-hCG in HEPES-buffered αMEM with no serum added, snap-frozen in liquid nitrogen and stored at -80ºC. RNA was extracted in Tri Reagent and DNase- treated before use (see Section 2.3 for more details). Sample genotypes were verified as per Section 2.3, before pooling for microarray assays.

For real-time PCR studies analysing normal gene expression, granulosa cells, COCs and whole oviducts were collected over a time course following hCG administration in C57Bl/6 mice. The C57Bl/6 strain was chosen as this is the background strain for PRlacZ transgenic mice. Cells & tissues were collected as described in Section 2.1.5 at 48 h post-eCG and eCG + 4 h, 6 h, 8 h, 10 h, or 12 h post- hCG. There were 3 to 4 samples per time point made up of cells/tissues pooled from 6 mice. A smaller time course was collected from PRKO and PR+/- transgenic mice to validate the microarray results and further examine the extent of PGR regulation during the periovulatory period. Granulosa cells and COCs were collected at 44h eCG + 4 h, 8 h or 10 h post-hCG. Individual mice constituted the biological replicates for each genotype (4 to 5 mice per time point). RNA was extracted in Tri Reagent and DNase-treated before use (see Section 2.3 for more details).

RNA concentration and quality was assessed using a Nanodrop ND-1000 Spectrophotometer (Biolab Ltd, Clayton Vic, Australia) and preliminary RT-PCR analysis of Rpl19 expression as described in Section 2.3.

5.2.2 Microarray sample preparation, array hybridisation, scanning and analysis

Once sample quality and genotype were confirmed, 5 pools of RNA (3 animals/pool) were created for each genotype (see Appendix 2 for details of microarray pooled samples). Approximately 100 ng total RNA from each sample was sent to the Adelaide Microarray Centre (AMC, Adelaide, SA, Australia) for analysis. Final pooled samples were checked for RNA integrity by the AMC using an Agilent Bioanalyzer (Agilent Technologies, Santa Clara, USA; Appendix 2) before use. Sample preparation was performed by AMC using Affymetrix GeneChip® Kits (Affymetrix, Santa Clara, USA) according to the manufacturer’s instructions. A brief description of the protocol is given in Section 2.5. Following biotinylation, samples were hybridised overnight to Affymetrix GeneChip® Mouse Gene 1.0 ST Arrays

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(Affymetrix, Santa Clara, USA). The arrays were washed, stained using a fluorescently-labelled antibody and scanned using a high resolution scanner (Affymetrix GeneChip Scanner 3000 7G Plus).

Microarray data were analysed by the AMC using Partek® Genomics Suite™ software (Partek Incorporated, St Louis, MO, USA). See Section 2.5.2 for more details. A Principal Components Analysis (PCA) plot was used to examine the relationship of individual samples within genotype (see Section 2.5.2 for more details). A volcano plot was also created using all genes found on the array to summarise the data set and highlight genes of interest with large magnitude fold changes and high statistical significance ( see [Cui and Churchill, 2003] and Section 2.5.2 for more details). Data sets containing genes that were differentially expressed between the two genotypes were imported into the Ingenuity Pathway Analysis software (IPA; Ingenuity Systems, Redwood City, CA, USA) to identify genes associated with statistically relevant biological functions (i.e. P<0.05). Specific keywords in the ‘Category’, ‘Function’ or ‘Function Annotation’ terms for these groups were used to form composite gene lists.

5.2.3 Real-time PCR

RNA was reverse-transcribed to synthesise cDNA (as per Section 2.4) on 300 ng RNA in a 20 μl reaction. QuantiTect Primer Assays (Qiagen, Pty. Ltd., Doncaster, Vic, AU) were used for analysis of expression of CXCR4 and for the housekeeping gene, Rpl19 (See Table 2.2). Real-time PCR was performed for each sample as described in Section 2.4. Briefly, each reaction included 10 ng of cDNA (5 ng/μl) and 2.5 μl Quantitect Primer Mix in a 20 μl reaction using Power SYBRGreen Master Mix (Applied Biosystems, Mulgrave, Vic, AU). Samples were analysed in triplicate on a Corbett Rotor-Gene 6000 Real-time Rotary Analyzer (Corbett Research Pty Ltd, Sydney, NSW, AU). Samples were analysed over 3 runs, with at least one sample for each tissue type and time point included on each run. A 10 h post-hCG whole ovary sample was used as the calibrator sample and was included on all runs. Each gene (including the housekeeper, Rpl19) was run on separate days on the same cDNA. However, Rpl19 was included for the calibrator on every PCR run to check for between-run variation. The same Rotorgene machine was used for all reactions. Gene expression was expressed as fold change relative to the calibrator using the CT Method [Livak and Schmittgen, 2001]. For analysis of expression in normal tissues, results were normalised to each tissue’s respective 48 h post-eCG sample which was set to a fold change of 1.0. For analysis of expression in PRKO and PR+/- cells, all data was normalised to the 4 h PR+/- COC sample (fold change = 1.0). See Appendix 4 for information on the stability of housekeeper gene expression across samples.

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5.2.4 Immunohistochemistry

In situ expression of CXCR4 protein was examined in ovary and oviduct sections by immunohistochemistry. Ovaries were collected from PR+/- and PRKO mice (n = 4 per time point per genotype) at 44 h eCG + 8 h, 10 h and 12 h post-hCG, with 6-8 sections stained per animal. Detailed methods for tissue processing and sectioning are given elsewhere (Section 2.6.1). General methods for immunohistochemistry are given in Section 2.7. The CXCR4 rabbit monoclonal primary antibody (Epitomics, Burlingame, CA, USA) was used at 1:100 concentration and the secondary antibody (biotinylated goat--rabbit IgG; Vector Labs, Burlingame, CA, USA) was used at 1:500 concentration. Antigen retrieval was done by boiling under pressure in citrate buffer (details Section 2.7). Stained sections were imaged at 40X resolution using the NanoZoomer HT Digital Pathology System (Hamamatsu Photonics K.K., Japan).

5.2.5 In vivo inhibition of CXCR4 by AMD3100

The synthetic bicyclam, AMD3100 (also known as plerixafor hydrochloride), is widely regarded as a specific antagonist for CXCR4 (see [Liang, 2008] for review). CBAF1 females (21 day-old) were injected with eCG and hCG to initiate follicle growth and induce ovulation as per Section 2.1.2. The pharmacokinetics of AMD3100 indicate that its half-life in sera from a subcutaneous injection is approximately 1 h in dogs [Burroughs et al., 2005] and 30 mins in humans [Hendrix et al., 2004] from concentrations measured in sera. Peak concentrations were reached in humans at 15 mins post- treatment with a steady decline to low levels by 12 h and total clearance of the inhibitor by 24 h post- treatment [Hendrix et al., 2004]. Therefore, mice were given multiple injections i.p. with either 1.5 mg/kg (n = 10), 5 mg/kg (n = 25), 10 mg/kg (n = 4) or 20 mg/kg (n = 5) of AMD3100 (Sigma-Aldrich Pty Ltd, Castle Hill, NSW, AU) in 0.8% saline, or with saline alone (control; n = 25) at 4 h, 6 h, 8 h and 10 h post-hCG. Dose rates were based on typical daily doses reported in the literature for mice (e.g. [Broxmeyer et al., 2005; Kajiyama et al., 2008; Matthys et al., 2001]). Mice were killed at 16 or 24 h post-hCG (4-12 h after ovulation) and ovulated COCs in the oviduct counted.

5.2.6 Statistical analyses

The microarray experiment was analysed after quantile normalisation using a mixed model Analysis of Variance (ANOVA) with a False Discovery Rate (FDR) correction (see Section 2.5.2 for more details). Real-time PCR data were analysed after testing for homogeneity of variances and a normal distribution

Lisa Akison 2012 145 and performing data transformation as required. For analysis of expression in normal tissues, time post-hCG and tissue type were compared using a two-way ANOVA and post-hoc Holm-Sidak pair-wise comparison procedure. Two-way ANOVAs and Holm-Sidak post-hoc tests were also used for analysis of expression in PRKO and PR+/- granulosa cells and COCs at each time point post-hCG. For the AMD3100 study, data were expressed as the number of ovulated COCs per mouse (mean + SE) for each treatment. A one-way ANOVA was used to examine for significant differences between groups.

5.3 Results

5.3.1 Granulosa Cell Microarray

Ten Affymetrix Mouse Gene 1.0 ST Arrays were used to investigate transcriptional changes in granulosa cells isolated from PRKO and PR+/- mice at 8 h post-hCG. A PCA plot revealed that the samples were clustered into two distinct groups corresponding to genotype based on their gene expression profiles (Figure 5.1). Within genotype, the PRKO samples were more heterogeneous than the PR+/- samples, with samples divided into two clusters. There were 296 genes differentially expressed between PRKO and PR+/- samples (P<0.05), with 78% down-regulated in the PRKO mice relative to PR+/- (Figure 5.2; see Appendix 3 for entire list of genes). The majority of differentially expressed genes had fold differences of 1.5 (60%) and 27% showed large magnitude fold differences (>2.0) (Figure 5.2). Large fold changes are typically indicative of gene expression changes of a high biological significance [Cui and Churchill, 2003] and these are highlighted in the volcano plot depicted in Figure 5.2.

Gene ontology analysis identified genes associated with the statistically relevant functions of ‘migration’, ‘movement’, ‘chemotaxis’ or ‘invasion’ (Table 5.1). All of these keywords were also associated with ‘cancer’ or various immune cell descriptors (e.g. ‘lymphocytes’, ‘monocytes’), indicative of the types of cells that exhibit these processes. Genes with high statistical significance and/or fold change in this list included the endothelial adhesion receptor Cd34, related RAS viral (r-ras) oncogene homolog 2 (Rras2), the zinc finger protein Zbtb16, the chemokine receptor CXCR4, and sphingosine kinase 1 (Sphk1) which were all down-regulated in the PRKO samples. Also included in this group

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Figure 5.1 Principle Component Analysis plots for granulosa cell microarray samples. Red spheres are PR+/- samples and blue spheres are PRKO samples. Top view

has principal components 1 and 2 shown for the X and Y axes respectively. Bottom view shows the chart rotated clockwise to show the clustering of samples for each genotype.

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5

Snap25 Entpd1 Adam8 4 Rras2 Cd34 Sphk1 Cxcr4 Zbtb16 Efnb2

3 Cgn

Rgmb

p-value Adamts1 10 2 Epas1 -log Apoa1 Mmp19

1

0 -4 -3 -2 -1 0 1 2 3 4

log2 Fold Change

Figure 5.2 Volcano plot of granulosa cell microarray data. Samples collected at 8 h post-hCG. All 28,853 genes from the Affymetrix GeneChip® Mouse

Gene 1.0 ST Array are plotted. The red dashed line represents P = 0.05 with points above the line significantly dysregulated in PRKO relative to PR+/- samples (n = 296) and points below the line not significant. The plot is centred around genes with a fold change of 1 (log2 1 = 0), with genes to the right of the vertical black line up-regulated in PRKO and genes to the left of the vertical black line down-regulated in PRKO compared with PR+/-. Genes with a fold change <2 are shown in grey. Some of the genes discussed further in the text are shown in green.

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Table 5.1 Differentially expressed genes in PRKO granulosa cells associated with cell migration/movement, chemotaxis or cell invasion. Fold change is PRKO relative to PR+/- granulosa cells; negative fold change indicates down-regulation and positive fold change indicates up-regulation. * P<0.05; ** P<0.01; *** P<=0.001; **** P<=0.0001. Genes ordered by statistical significance then by fold-change.

Cell Migration/Cell Movement/Chemotaxis/Cell Invasion Gene Fold P- Gene Fold P- Symbol Gene Name change value Symbol Gene Name change value

Cd34 CD34 antigen -2.68 **** Lpar1 lysophosphatidic acid receptor 1 -1.89 * Rras2 related RAS viral (r-ras) oncogene homolog 2 -2.33 **** Pcdh10 protocadherin 10 -1.80 * Zbtb16 zinc finger and BTB domain containing 16 -13.73 *** Prkcb protein kinase C, beta 1.77 * Efnb2 ephrin B2 -3.72 *** Runx2 runt related transcription factor 2 -1.74 * Cxcr4 chemokine (C-X-C motif) receptor 4 -3.48 *** Stard13 StAR-related lipid transfer (START) domain -1.68 * containing 13 Sphk1 sphingosine kinase 1 -2.80 *** Tns1 tensin 1 -1.62 * Abhd2 abhydrolase domain containing 2 -2.72 *** Cd47 CD47 molecule -1.50 * Gna01 guanine nucleotide binding protein, alpha O -3.61 ** Palld palladin, cytoskeletal associated protein 1.50 * Adamts1 ADAM metallopeptidase with thrombospondin type -2.58 ** Prkca protein kinase C, alpha 1.46 * 1 motif, 1 Lrp8 low density lipoprotein receptor-related protein 8, -2.26 ** Ctsl cathepsin L -1.45 * apolipoprotein e receptor Rgmb RGM domain family, member B 2.16 ** Cxcl12 chemokine (C-X-C motif) ligand 12 1.44 * Egfr epidermal growth factor receptor -2.02 ** Zyx zyxin -1.42 * Pappa pregnancy-associated plasma protein A 1.87 ** Cnr1 cannabinoid receptor 1 (brain) 1.41 * Amd1 S-adenosylmethionine decarboxylase 1 -1.58 ** Tnfrsf21 tumor necrosis factor receptor superfamily, -1.40 * member 21 / Lif leukemia inhibitory factor -1.57 ** Vcl vinculin -1.33 * Nme2 non-metastatic cells 2, protein (NM23B) expressed 1.31 ** Dkk3 dickkopf homolog 3 (Xenopus laevis) 1.33 * in Sfrp2 secreted frizzled-related protein 2 2.84 * Il18 interleukin 18 1.33 * Mmp19 matrix metallopeptidase 19 -2.45 * Vcan versican -1.32 * Apoa1 apolipoprotein A-I -2.20 * Igf2r insulin-like growth factor 2 receptor 1.30 * Pla2r1 phospholipase A2 receptor 1 -2.14 * Plekhg5 pleckstrin homology domain containing, family G 1.24 * (with RhoGef domain) member 5 Rnd3 Rho family GTPase 3 -1.90 * Actn4 actinin alpha 4 -1.23 *

149 were genes previously identified as PGR-regulated genes in the ovary by other studies [Kim et al., 2009b; Robker et al., 2000] or our own immune array conducted in Chapter 4 (i.e. Adamts1, Ctsl, Cd34, Il18, Cxcr4), thus strengthening the validity of our microarray results. The most highly up-regulated gene in this group, considering both statistical significance and fold change relative to PR+/- samples, was RGM domain family, member B (Rgmb) (Figure 5.2 and Table 5.1). This gene is part of the repulsive guidance molecule family and is a BMP co-receptor that is expressed in the ovary, uterus and pituitary of female mice and in the testis in males [Xia et al., 2005].

Another group of genes identified from the array data were those associated with significant functional groups containing the keywords ‘adhesion’, ‘cell-cell contact’ or ‘binding’ (Table 5.2). The majority of these genes (53%) were also represented under the cell migration ontology (Table 5.1), indicative of the functional overlap between these two mechanisms. However, several genes were unique to this group. For example, Adam8, previously identified as PGR-regulated in the ovary [Sriraman et al., 2008], was highly down-regulated in PRKO granulosa cells, as well as the , Entpd1, and the tight-junction protein cingulin (Cgn). Also identified was endothelial PAS domain protein 1 (Epas1, also known as Hif2) which has previously been identified as a PGR-regulated gene in the ovary [Kim et al., 2009b].

Given the results in Chapter 4, where a suite of immune-related genes were found to be dysregulated in the whole ovary, data from this genome-wide assessment of PGR-regulated transcripts were interrogated for genes involved in immune responses at the granulosa cell level. Genes associated with significant functional groups with the keywords ‘immune response’ (either cell-mediated or humoral), ‘immune cell trafficking’, ‘inflammatory response’ or ‘leukocytosis’ were compiled (Table 5.3). Relatively few genes identified by targeted analysis of immune genes in whole ovary (Chapter 4) were present amongst genes differentially expressed in PRKO granulosa cells. These included only Cd34 and Il18, with -2.68 down- or 1.33 up-regulated expression respectively in the PRKO samples (see Chapter 4 for further discussion of these two genes). Genes associated with vascular changes were also identified as a significantly affected pathway in PRKO ovaries using IPA (Table 5.4). This list included CXCR4/CXCL12, Adamts1, Hif2 and ephrin B2 (Efnb2).

There were 11 proteases dysregulated in the PRKO granulosa cell samples; most down-regulated but 3 genes (Pappa, Hm13 and Adamts7) were up-regulated (Table 5.5). Several of these genes have been previously identified as PGR-regulated in the ovary (i.e. Adamts1, Adam8, and Ctsl) as mentioned above. Matrix metalloproteinase 19 (Mmp19) has recently been shown to be up-regulated following hCG in preovulatory follicles of rhesus macaques and implicated in successful follicle rupture at ovulation [Peluffo et al., 2011].

Lisa Akison 2012

Table 5.2 Differentially expressed genes in PRKO granulosa cells associated with adhesion, cell-to-cell contact and cell binding. Fold change is PRKO relative to PR+/- granulosa cells; negative fold-change indicates down-regulation and positive fold-change indicates up-regulation. * P<0.05; ** P<0.01; *** P<=0.001; **** P<=0.0001. Genes ordered by statistical significance then by fold-change.

Adhesion/cell-to-cell contact/ cell binding Gene Fold P- Gene Fold P- Symbol Gene Name change value symbol Gene Name change value

Adam8 a disintegrin and metallopeptidase domain 8 -3.48 **** Adam2 a disintegrin and metallopeptidase domain 2 -2.10 * Entpd1 ectonucleoside triphosphate diphosphohydrolase 1 -3.17 **** Rnd3 Rho family GTPase 3 -1.90 * Cd34 CD34 antigen -2.68 **** Pcdh10 protocadherin 10 -1.80 * Efnb2 Ephrin B2 -3.72 *** Rasgrf2 RAS protein-specific guanine nucleotide-releasing 1.79 * factor Cgn cingulin -3.53 *** Lama4 laminin, alpha 4 1.68 * Cxcr4 chemokine (C-X-C motif) receptor 4 -3.48 *** Astn1 astrotactin 1 1.58 * Foxp1 forkhead box P1 -1.79 *** Cd47 CD47 molecule -1.50 * Cblb Casitas B-lineage lymphoma b -1.74 *** Palld palladin, cytoskeletal associated protein 1.50 * Gna01 guanine nucleotide binding protein, alpha O -3.61 ** Prkca protein kinase C, alpha 1.46 * Lepr -3.06 ** Cxcl12 chemokine (C-X-C motif) ligand 12 1.44 * Cldn1 claudin 1 -3.02 ** Zyx zyxin -1.42 * Rgmb RGM domain family, member B 2.16 ** Vcl vinculin -1.33 * Egfr epidermal growth factor receptor -2.02 ** Dkk3 dickkopf homolog 3 (Xenopus laevis) 1.33 * Lif leukemia inhibitory factor -1.57 ** Il18 interleukin 18 1.33 * Adipor2 adiponectin receptor 2 -1.48 ** Vcan versican -1.32 * Snx1 sorting nexin 1 -1.45 ** Igf2r insulin-like growth factor 2 receptor 1.30 * Nme2 non-metastatic cells 2, protein (NM23B) expressed 1.31 ** Inppl1 inositol polyphosphate phosphatase-like 1 1.29 * in Epas1 endothelial PAS domain protein 1 (Hif2a) -3.39 * Actn4 actinin alpha 4 -1.23 * Aldob aldolase B, fructose-bisphosphate -2.71 * Maea macrophage erythroblast attacher -1.21 * Mmp19 matrix metallopeptidase 19 -2.45 *

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Table 5.3 Differentially expressed genes in PRKO granulosa cells associated with immune responses and immune cell trafficking. Genes highlighted in bold (Cd34 and Il18) were also identified as PGR-regulated from the Immune Array analysis of whole ovaries at 10 h post-hCG (see Chapter 4). Fold change is PRKO relative to PR+/- granulosa cells; negative fold-change indicates down-regulation and positive fold-change indicates up-regulation. * P<0.05; ** P<0.01; *** P<=0.001; **** P<=0.0001. Genes ordered by statistical significance then by fold-change.

Immune Response/Immune Cell Trafficking Gene Fold P- Symbol Gene Name change value Cd34 CD34 antigen -2.68 ****

Snap25 synaptosomal-associated protein 25 -3.21 **** Zbtb16 zinc finger and BTB domain containing 16 -13.73 *** Efnb2 ephrin B2 -3.72 *** Cxcr4 chemokine (C-X-C motif) receptor 4 -3.48 *** Kl klotho -2.88 *** Sphk1 Sphingosine kinase 1 -2.80 *** Tsc22d3 TSC22 domain family, member 3 -2.69 *** Gna01 guanine nucleotide binding protein, alpha O -3.61 ** Lepr leptin receptor -3.06 ** Klf9 Kruppel-like factor 9 -2.06 ** Prkcb protein kinase C, beta 1.77 ** Cblb Casitas B-lineage lymphoma b -1.74 ** Rorc RAR-related orphan receptor gamma -1.65 ** Pawr PRKC, apoptosis, WT1, regulator -1.57 ** Lif leukemia inhibitory factor -1.57 ** Ppm1d protein phosphatase 1D magnesium-dependent, delta isoform -1.38 ** Rasgrf2 RAS protein-specific guanine nucleotide-releasing factor 1.79 * Runx2 runt related transcription factor 2 -1.74 * Notch1 Notch gene homolog 1 (Drosophila) 1.52 * Cd47 CD47 molecule -1.50 * Aff1 AF4/FMR2 family, member 1 -1.47 * Prkca protein kinase C, alpha 1.46 * Cxcl12 chemokine (C-X-C motif) ligand 12 1.44 * Ctsl cathepsin L -1.45 * Brca1 breast cancer 1 -1.42 * Tnfrsf21 tumor necrosis factor receptor superfamily, member 21 / -1.40 * Il18 interleukin 18 1.33 *

Igf2r insulin-like growth factor 2 receptor 1.30 * Actn4 actinin alpha 4 -1.23 * Tcf4 transcription factor 4 -1.22 * Ep300 E1A binding protein p300 -1.22 * Lisa Akison 2012 152

Table 5.4 Differentially expressed genes in PRKO granulosa cells associated with vascular remodelling, angiogenesis or formation of blood vessels. Fold change is PRKO relative to PR+/- granulosa cells; negative fold-change indicates down- regulation and positive fold-change indicates up-regulation. * P<0.05; ** P<0.01; *** P≤0.001. Genes ordered by statistical significance then by fold-change.

Remodelling of vasculature, angiogenesis, blood vessel formation Gene Fold P- Symbol Gene Name change value

Efnb2 ephrin B2 -3.72 ***

Cxcr4 chemokine (C-X-C motif) receptor 4 -3.48 ***

Sphk1 sphingosine kinase 1 -2.8 ***

Adamts1 ADAM metallopeptidase with thrombospondin type 1 motif, 1 -2.58 ** Epas1 (Hif2a) endothelial PAS domain protein 1 -3.39 *

Cxcl12 chemokine (C-X-C motif) ligand 12 1.44 *

Il18 interleukin 18 1.33 *

Igf2r insulin-like growth factor 2 receptor 1.30 *

Lisa Akison 2012 153

Table 5.5 Differentially expressed proteases in PRKO granulosa cells. Fold change is PRKO relative to PR+/- granulosa cells; negative fold-change indicates down-regulation and positive fold-change indicates up-regulation. * P<0.05; ** P<0.01; **** P≤0.0001. Genes ordered by statistical significance then by fold-change.

Proteases Gene Fold P- Symbol Gene Name change value

Adam8 a disintegrin and metallopeptidase domain 8 -3.48 ****

Adamts1 ADAM metallopeptidase with thrombospondin type 1 motif, 1 -2.58 **

Pappa pregnancy-associated plasma protein A 1.87 **

Hm13 histocompatibility 13 1.37 **

Mmp19 matrix metallopeptidase 19 -2.45 *

Adam2 a disintegrin and metallopeptidase domain 2 -2.1 *

Tll1 tolloid-like 1 -1.91 *

Xpnpep1 X-prolyl aminopeptidase (aminopeptidase P) 1, soluble -1.64 *

Ctsl cathepsin L -1.45 *

Hgfac hepatocyte growth factor activator -1.4 *

Adamts7 ADAM metallopeptidase with thrombospondin type 1 motif, 7 1.4 *

Lisa Akison 2012 154

5.3.2 Cxcr4 mRNA expression

There was compelling evidence for PGR-regulation of CXCR4 from the microarray data. In the PRKO granulosa cell samples, CXCR4 was down-regulated 3.5-fold compared to the PR+/- samples. Thus, CXCR4 mRNA expression was validated in a time course across the periovulatory period in wild-type C57Bl/6 as well as PRKO/PR+/- mice.

CXCR4 mRNA was dramatically induced by LH in both COCs and granulosa cells in the ovary (Figure 5.3), with a peak in expression at 8 h post-hCG. In COCs, expression appeared to be transient, with a significantly lower level of expression by 12 h post-hCG. In contrast, the oviduct showed very low levels of CXCR4 expression and no induction by LH.

Real-time PCR was also used to validate that CXCR4 is regulated by PGR in the ovary. The microarray result (Section 5.3.1) was confirmed (Figure 5.4), with CXCR4 expression down-regulated in granulosa cells from PRKO mice relative to PR+/- mice at 8 h post-hCG, the same time point used for the microarray experiment. In addition, expression was significantly reduced at 10 h post-hCG and there was a trend for reduced expression at 4 h post-hCG. Interestingly, although PGR is not expressed at detectable levels in the COC [Ismail et al., 2002; Robker et al., 2000; Teilmann et al., 2006], expression of CXCR4 in COCs from PRKO mice was significantly down-regulated at 8 h and 10 h post-hCG (Figure 5.4), indicating a down-stream effect of PGR-knockdown in the granulosa cells on COC gene transcription. Further, the ligand for CXCR4, CXCL12, was confirmed to be significantly up- regulated 1.7-fold in PRKO granulosa cells collected at 8 h post-hCG (Student’s t-test, P<0.05, data not shown), validating the microarray result reported in Tables 5.1-5.4.

5.3.3 CXCR4 immunohistochemistry

The expression and localisation of CXCR4 protein in the ovary and oviduct showed a similar pattern to that shown for mRNA expression (Figure 5.5). CXCR4 expression was strongest at 8 h post-hCG, although CXCR4 was detectable at all time points examined, with staining predominantly localised to granulosa and cumulus cells of antral follicles (Figure 5.5A). There was also some staining of the luminal epithelium of the oviduct (Figure 5.5A, right panel). There was no staining of CXCR4 protein visible in the PRKO ovary or oviduct sections (Figure 5.5) suggesting that detectable levels of expression depend on the presence of PGR.

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350 cumulus oocyte complex granulosa cells a oviducts

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250 ac

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bc Relative Fold Change (Mean SE)+ Fold (Mean Change Relative b bd bc 100 bd d

bd d 50

e e e e e e e 0 48h 4h 6h 8h 10h 12h post-eCG post-hCG Figure 5.3 Cxcr4 mRNA is induced by hCG in COCs and granulosa cells. CXCR4 mRNA expression was measured in COCs, granulosa cells and whole oviducts from C57Bl/6 mice. Each tissue was normalised to its respective 48 h post-eCG sample. Data was analysed using a two-way ANOVA on log-transformed data and Student Neuman Kuel’s pair-wise comparison procedure. n = 3 - 4 for each tissue type at each time point. Different letters denote significant differences at P<0.05.

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8 *** PR+/- PRKO 7 *** ***

6

5 ** 4 **

3

2 Relative Fold Change (Mean SE)+ Fold (Mean Change Relative

1

0 COC GC COC GC COC GC 4h post-hCG 8h post-hCG 10h post-hCG Figure 5.4 Cxcr4 is down-regulated in PRKO GCs and COCs during the periovulatory period. All data were normalised to the 4 h PR+/- COC sample. n = 4 samples per tissue per time point. Data were analysed using a two-way ANOVA with Holm-Sidak pair-wise comparison procedure. Data at the 4 h time point were log-transformed before analysis. There was a significant effect of genotype at 8 h and 10 h post-hCG. *** = P<0.001; ** = P<0.01.

Lisa Akison 2012

Figure 5.5 A) 8 h post-hCG

Whole ovary (5X) Follicles (10X) Stroma (20X) Oviduct (20X)

PR+/-

PRKO

Figure 5.5 B) 10 h post-hCG

Whole ovary (5X) Follicles (10X) Stroma (20X) Oviduct (20X)

PR+/-

PRKO

Figure 5.5 C) 12 h post-hCG

Whole ovary (5X) Follicles (10X) Stroma (20X) Oviduct (20X)

PR+/-

PRKO

160

Figure 5.5 CXCR4 protein is detected in ovaries and oviducts from PR+/- mice. A) Strongest staining is seen in antral follicles of 8 h post-hCG PR+/- ovaries. Staining is also visible in cells from the luminal epithelium of the oviduct. No staining is visible in PRKO ovaries or oviduct. Some protein is also seen at 10 h (B) and 12 h (C) post-hCG in PR+/- ovaries but not in PRKO ovaries. Numbers indicate individual animals: one representative animal shown from four animals examined for each genotype at each time point. One representative section is shown for each animal at 5X (whole ovary), 10X (follicles), 20X (stroma) and 20X (oviduct).

Lisa Akison 2012 161 To determine whether CXCR4 could play a role in ovulation, I designed an in vivo experiment in which gonadotrophin-stimulated normal mice were treated with the CXCR4 inhibitor, AMD3100, to test whether this could block or reduce ovulation.

5.3.4 CXCR4 inhibitor, AMD3100, does not block ovulation in vivo

Doses of AMD3100 from 1.5 to 20 mg/kg were administered to female mice (CBAF1 strain) at two- hourly intervals from 4 h to 10 h post-hCG in the lead up to ovulation. There was no significant difference in the numbers of ovulated COCs present in the oviducts at 16 or 24 h post-hCG when compared across treatments or against saline treated controls (Figure 5.6). Note ovulation in this strain occurs typically at 12 h post-hCG (Figure 2.2).

5.4 Discussion

PGR is critical for follicle rupture and oocyte release at ovulation, as is clearly shown by the lack of these processes in PRKO mice. Given that PGR is a transcription factor, the search for its downstream targets in the ovary has led to the discovery of several genes which have since been found to play a role in ovulation (see Section 1.5.5). However, no known PGR target gene has been shown to mediate PGR’s effect on ovulation leaving open the possibility that an as yet unidentified PGR target gene is the critical ovulatory mediator. There have been few reported genome-wide surveys for PGR-regulated genes, and none specifically on granulosa cells collected from in vivo-stimulated animals when peak PGR expression will have its maximal effect on target gene expression. I performed such an experiment and present in this chapter a comprehensive list of genes influenced by PGR in granulosa cells in vivo with potential roles in the molecular processes contributing to ovulation. Several pathways dependent on PGR were those involved in migration, invasion, chemotaxis and adhesion which may contribute to ‘activation’ of the periovulatory COC, thus facilitating the eventual release of the COC from the follicle at ovulation. It also includes pathways involved in inflammatory and non-specific innate immune responses that have been previously associated with ovulation [Brannstrom and Enskog, 2002; Richards et al., 2008; Richards et al., 2002a], as well as genes associated with angiogenesis and vascular remodelling, also hallmarks of the periovulatory process [Reynolds et al., 1992]. As confirmation of the validity of our microarray data, several of the genes have been previously reported as PGR-regulated in pre-ovulatory granulosa cells or whole ovaries (e.g. Adamts1, Ctsl, Snap25, Epas1/Hif2, Adam8, Apoa1) [Kim et al., 2009a; Robker et al., 2000; Shimada et al., 2007; Sriraman et al., 2008; Sriraman et al., 2010]. However, the vast majority of genes are, to the best of our knowledge,

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# COCs/mouse (Mean + SE) + (Mean COCs/mouse # 10

0 Saline 1.5 5 10 20 (n = 25) (n = 10) (n = 25) (n = 4) (n = 5)

AMD3100 (mg/kg) Figure 5.6 The CXCR4 inhibitor, AMD3100, does not reduce ovulation rate in vivo. CBAF1 mice were injected with AMD3100 in saline (dose rates shown) or saline alone at eCG + 4 h, 6 h, 8 h and 10 h post-hCG. Ovulated COCs were counted from the oviducts at 16 or 24 h post-hCG. n = 4-25 mice per treatment as indicated. No significant differences between treatments by one-way ANOVA (P = 0.615).

Lisa Akison 2012 163 novel down-stream targets of PGR regulation in periovulatory ovarian granulosa cells, including CXCR4 which I further validated and characterised.

The complete list of differentially expressed genes in PRKO relative to PR+/- granulosa cells is available in Appendix 3 and specific genes associated with molecular processes purported to be critical for ovulation are given in Tables 5.1 – 5.5. These provide an important resource for the generation of new hypotheses with respect to potential molecular pathways underlying ovulation. It is imperative that genes of interest are validated using other more highly quantitative assays such as real-time PCR, as microarray assays and the associated statistics required for identifying significantly dysregulated genes unavoidably generate false positives; despite the use of False Discovery Rate (FDR) normalisations for adjusting P-values (for further discussion on this see [Pawitan et al., 2005]). However, several genes with convincing differences in PRKO may be expected to contribute to the ovulatory process based on prior knowledge of their functions.

Zinc finger and BTB domain containing 16 (Zbtb16)

Zbtb16, also known as promyelocytic leukemia zinc finger (Plzf), was the most significantly dysregulated gene in PRKO granulosa cells, with a 13.7 fold reduction in expression compared with PR+/- samples. It has recently been identified to be PGR-regulated in rat granulosa cells treated in vitro with the PGR inhibitor, Org-31710, by microarray analysis and qPCR [Friberg et al., 2010]. However, in vitro studies in human myometrial smooth muscle cells suggest that activated PGR does not affect Zbtb16 transcription via its promoter, and P4 only modestly induced Zbtb16 mRNA [Fahnenstich et al., 2003]. This gene encodes a sequence-specific transcriptional repressor [Kumar et al., 2005; Li et al., 1997a]. Interestingly, it has been found in one study to reduce migration and invasion in cancer cell lines in vitro [Felicetti et al., 2004], thus its reduction in PRKO granulosa cells may potentially improve the migratory or invasive potential of cells. This is counter to the increased migration/invasion by the periovulatory COC. Alternatively, this gene may regulate processes such as proliferation, differentiation and apoptosis in granulosa cells, as has been reported in the endometrium, where it has an anti-proliferative effect and confers resistance to apoptosis [Brosens and Gellersen, 2006]. Zbtb16 mRNA has been shown to be up-regulated 16.2-fold in COCs collected at 8 h post-hCG by microarray [Hernandez-Gonzalez et al., 2006]. However, although Plzf-null mice demonstrate a critical role for this gene in spermatogenesis and male fertility [Costoya et al., 2004], defects in female fertility have not been reported. However, its role in the ovary remains unknown. Identification of direct targets in the ovary at ovulation in the future will help to elucidate its role in the overall process.

Ephrin B2 (Efnb2)

Efnb2, which is one of the eph family receptor interacting proteins (ephrins), was highly down-regulated in the PRKO granulosa cell sample. Ephrins are ligands for eph receptors (Ephs), high affinity cell Lisa Akison 2012 164 surface receptors [Arvanitis and Davy, 2008]. As both Ephs and ephrins are membrane-bound proteins, binding and activation of intracellular signalling pathways occurs by direct cell-to-cell interaction [Dravis, 2010]. Eph/ephrin interaction induces either repulsion or adhesion between cells depending on the context [Dravis, 2010] such as during axon guidance [Palmer and Klein, 2003], angiogenesis and lymphangiogenesis [Wang et al., 2010]. This interaction is also important in regulating migration, adhesion and angiogenesis in adult tissues [Himanen et al., 2007; Kuijper et al., 2007] and in cancer [Genander and Frisen; Pasquale, 2010]. Interestingly, Eph/ephrin has been found to cross-regulate the CXCR4/CXCL12 signalling axis, where down-stream effectors from both pathways have been found to be either agonistic [Salvucci et al., 2006] or antagonistic [Lu et al., 2001] to cell migration and adhesion by endothelial cells and cerebellar cells respectively. Efnb2 in particular has been shown to be a key regulator of Vegf signalling, thereby controlling angiogenesis and lymphangiogenesis in both development and tumour formation [Sawamiphak et al., 2010; Wang et al., 2010]. The importance of VEGF signalling to the neovascularisation that occurs in the ovary during ovulation was discussed in Chapter 1.

In the ovary, mRNA expression of several Ephs and ephrins (including Efnb2) have been detected in human granulosa cells, but expression did not change in response to hCG treatment in vitro [Xu et al., 2006a]. However, in another study, Efnb1 expression was found to rapidly increase in luteinising granulosa cells after ovulation using immunohistochemistry, suggesting a role for the Eph/ephrin axis in CL formation [Egawa et al., 2003].

Sphingosine kinase 1 (Sphk1), epidermal growth factor receptor (Egfr) and endothelial PAS domain protein 1 (Epas1/Hif2)

Sphk1 is one of two lipid kinases (with Sphk2) that catalyses the phosphorylation of sphingosine to sphingosine 1-phosphate (S1P), a lipid messenger with diverse extracellular roles in tumour progression, immune cell infiltration and development of the vascular and nervous system [Mizugishi et al., 2005; Spiegel and Milstien, 2007]. Sphk1 was down-regulated 2.8-fold in the PRKO granulosa samples. This gene has previously been identified to be induced over 35-fold in the COC 8 h post-hCG [Hernandez-Gonzalez et al., 2006] but its role in the ovary is unknown. In the rat, Sphk1 mRNA is up- regulated in the uterus during pregnancy, and in vivo administration of P4 or the PGR antagonist, ornapristone, resulted in up- or down-regulation respectively [Jeng et al., 2007]. Sphk1-/- and Sphk2-/- mice have normal fertility [Allende et al., 2004; Mizugishi et al., 2005], and the double knockout, Sphk1- /-Sphk2-/-, is embryonic lethal [Mizugishi et al., 2005]. However, Sphk1-/-Sphk2+/- mutant mice are infertile, although this is due to a defect in uterine decidualisation rather than an ovulation defect [Mizugishi et al., 2007].

Lisa Akison 2012 165 Sphk1 has been implicated in signalling linked to epidermal growth factor (EGF) up-regulation of plasminogen activator inhibitor 1 (PAI1), a pathway functionally involved in the regulation of migration and invasion in glioma cells [Paugh et al., 2008]. Egfr was down-regulated 2-fold in our PRKO microarray samples, which is the first time that this gene has been shown to be regulated in vivo by PGR. The only other evidence of PGR regulation is from a recent microarray assay on granulosa cells treated in vitro with a PGR antagonist [Friberg et al., 2010]. Egfr was also found to be induced in primary granulosa cells in vitro 16 h after transfection with a PGR-A adenoviral vector [Sriraman et al., 2010].

Sphk1 has also been found to modulate the transcription factor, Epas1 (Hif2), in glioma cells [Ader et al., 2009; Anelli et al., 2008]. Hypoxia inducible factors (Hifs) have previously been shown to be PGR- regulated genes that are induced during the periovulatory period [Kim et al., 2009b]. Epas1/Hif2 was down-regulated 3.4-fold in the PRKO microarray samples and was associated with the functions of adhesion/cell to cell contact and vascular remodelling/angiogenesis.

Thus, Sphk1 expression appears to be linked to the expression of several known ovulatory genes and thus may play some role during ovulation. Validation of Sphk1 expression in the ovary, and potential regulation by PGR, is required. However, the lack of an ovulatory defect in Sphk1 knockout mice suggests a potentially redundant contribution of Sphk1 to ovulation in the presence of functional Sphk2.

Runt related transcription factor 2 (Runx2)

As mentioned in Chapter 1, Runx1 has been shown to be down-regulated by PGR in vitro in granulosa cells treated with a PGR antagonist [Jo and Curry, 2006]. Our microarray dataset from granulosa cells isolated from PRKO and PR+/- mice did not find this, but instead revealed that another member of the runt related transcription factor family, Runx2, was down-regulated 1.7-fold in the PRKO samples. Statistical analysis revealed that this was significant, but given the moderate fold-change, validation of this result by RT-PCR is required. Like Runx1, Runx2 has been previously identified to be induced by hCG in periovulatory follicles of mouse, rat and human ovaries [Hernandez-Gonzalez et al., 2006; Park et al., 2010] and this induction was reduced in rat granulosa cells treated in vitro with RU486 [Park et al., 2010]. Thus, although this gene has been shown to be PGR-regulated in vitro, this is the first demonstration of PGR-regulation in cells isolated from PRKO mice. However, unlike Runx1, expression of Runx2 remains elevated until at least 16 h post-hCG, approximately 4 h after ovulation in the mouse [Hernandez-Gonzalez et al., 2006]. A recent study has demonstrated that Runx2 is a transcriptional repressor in luteinising granulosa cells in vitro [Park et al., 2012], specifically of Runx1, Ptgs2 and Tnfaip6 which are all induced by LH/hCG during the periovulatory period and are critical for ovulation and/or COC expansion (see Chapter 1). Down-regulation of Ptgs2 and Tnfaip6 may be direct and/or indirect via down-regulation of Runx1 [Park et al., 2012]. Thus, Runx2 may be more important

Lisa Akison 2012 166 for luteal development than for ovulation as it contributes to rapid down-regulation of a distinctive set of transiently induced preovulatory genes and up-regulation of specific luteal genes (e.g. Rgc32, Mmp13, Ptgds) in luteinized granulosa cells [Park et al., 2010]. These opposing actions are typical of RUNX proteins which are often described as context-specific transcription factors (see [Cameron and Neil, 2004] for review). This demonstrates that PGR not only induces the expression of preovulatory genes but is also involved in the down-regulation of genes via transcription factors such as Runx2.

Repulsive guidance molecule b (Rgmb)

The majority of genes dysregulated in the PRKO granulosa cells showed down-regulated expression, but one notable exception was Rgmb, also known as Dragon. This gene showed 2.16-fold up- regulation in PRKO relative to PR+/- granulosa cells, and was associated with the functions of migration/invasion and adhesion/cell binding. Repulsive guidance molecules (RGMs) are expressed in many tissues, including both embryonic and adult neural tissues where they regulate axon guidance (see [Mueller et al., 2006] for review). In cancer, RGMs play inhibitory roles by suppressing cell growth, adhesion, migration and invasion, as shown in prostate cancer [Li et al., 2012a] and breast cancer [Li et al., 2012b] cell lines and aberrant expression of RGMs is a prognostic indicator of cancer progression [Li et al., 2011]. The demonstrated role in reducing adhesion, migration and invasion in cancer cells may contribute to the anovulatory defect seen in the PRKO ovary, as Rgmb up-regulation may mediate reduced ability for the COC to adhere to the follicle wall and adopt its migratory/invasive phenotype (this hypothesis is examined in Chapter 6). Rgmb knockout mice show up-regulated IL6 in macrophages and dendritic cells isolated from the lung, as well as in whole lung and liver, compared with similar cells/tissues isolated from wild-type littermates [Xia et al., 2011]. These Dragon knockout mice die 2-3 weeks after birth [Xia et al., 2011]. Interestingly, I found a decrease in Il6 in the PRKO ovary (see Chapter 4), concomitant with the up-regulation of Rgmb in the granulosa cells shown in this chapter, and there is evidence that IL6 plays a role in ovulation [Molyneaux et al., 2003a].

Rgmb/Dragon has been localised to reproductive tissues in both the male and female, including the testis, epididymis, ovary, uterus and pituitary [Xia et al., 2005]. In adult (day 60) and immature (day 9) mouse ovaries, RGMB was localised by immunohistochemistry and in situ hybridisation, specifically to oocytes. Stronger staining was detected in oocytes from secondary follicles compared to antral follicles (all COCs were unexpanded), and there was no staining detected in oocytes from primordial or primary follicles or in somatic cells. Therefore, it is unknown whether LH/hCG upregulates Rgmb in the ovary. It is curious that such a strong regulation of Rgmb mRNA by PGR was detected in granulosa cells in this chapter, given the apparent lack of Rgmb expression in somatic cells in the Xia et al study.

Lisa Akison 2012 167 Further examination of PGR-regulation of RGMB in the ovary, and its relationship to IL6 expression, may be important for determining the role of PGR in regulating aspects of the immune response during the periovulatory period.

Proteases

There were 11 proteases found to be dysregulated in the PRKO granulosa cells, with several of these previously identified to be either directly or indirectly regulated by PGR in the ovary. These include Adamts1 [Robker et al., 2000; Russell et al., 2003b], cathepsin L [Robker et al., 2000] and Adam8 [Sriraman et al., 2008]. Interestingly, the main substrate for Adamts1, versican (Vcan), was also found to be moderately but significantly down-regulated (1.3-fold) which has not been previously reported. In a previous study, levels of both Vcan protein and mRNA were not found to be significantly different in PR+/- and PRKO mice during the periovulatory period, although there was a trend for reduced expression of mRNA at 8 h post-hCG [Russell et al., 2003c]. Adam2 is well known for its role in male fertility and sperm-egg binding [Cho et al., 1998; Nishimura et al., 2007] and is one of the best characterised Adams in terms of its binding to integrins on the oocyte surface (see [Evans, 2001] for review). However, to-date, it has not been reported in the ovary and Adam2-null females apparently show normal fertility [Cho et al., 1998]. Nonetheless, given its 2-fold down-regulation in PRKO granulosa cells, this may indicate a previously unreported role of this protease in ovulation. Similarly, the role of Adamts7 in the ovary is unknown. There is only one report of this protease in periovulatory follicles of the cow [Madan et al., 2003], which suggested, at least in this species, that Adamts7 mRNA expression is down-regulated after the LH surge in both granulosa and theca cells. Interestingly, Adamts7 expression was up-regulated in the PRKO granulosa cell samples.

Previous investigation of the mRNA expression of 11 MMPs in the mouse ovary during the periovulatory period revealed that only MMP19 was up-regulated in response to an ovulatory dose of hCG [Hagglund et al., 1999]. Interestingly, MMP19 was also the only matrix metalloproteinase, to be down-regulated in the PRKO granulosa cell samples (2.45-fold). This is the first time that PGR- regulation of MMP19 has been reported in the ovary. This MMP has been found to be localised to theca and granulosa cells in rat ovary during the periovulatory period and was transiently up-regulated following hCG administration [Jo and Curry, 2004]. However, this study found no evidence for PGR- regulation of MMP19 expression in whole ovaries by 6 h and 12 h post-CG after injection with PGR antagonists (RU486 and ZK98299) 1 h prior to hCG injection. Therefore, validation of our microarray result is required to clarify potential regulation of MMP19 by PGR, specifically in granulosa cells at the peak time of PGR expression.

Pregnancy-associated plasma protein-A (Pappa) was up-regulated 1.87-fold in the PRKO samples relative to PR+/-. This is the first demonstration of PGR-regulation of Pappa in the ovary, although it

Lisa Akison 2012 168 has previously been shown to be down-regulated by RU486 treatment in the placenta of pregnant cynomolgus monkeys [Sinosich et al., 1989]. This protease has previously been recognised as an important protease in ovulation as Pappa knockouts have reduced ovulation rate, despite normal growth and development of antral follicles and normal cumulus expansion [Nyegaard et al., 2010]. Pappa cleaves insulin-like growth factor binding protein 4 (IGFBP4), which binds to and inhibits IGF action, and thus increased Pappa results in decreased IGFBP binding to IGFs and increased IGF bioavailability [Boldt and Conover, 2007], allowing IGFs to bind to IGF receptors and exert their effects. In the ovary, IGFs modulate follicle growth, selection, atresia, differentiation, steroidogenesis, oocyte maturation and cumulus expansion [Kwintkiewicz and Giudice, 2009] and their impairment can lead to compromised steroidogenesis and ovulatory potential. Atretic follicles typically show high levels of IGFBPs, low IGF levels and low IGFBP protease/Pappa expression [Giudice, 1999; Hourvitz et al., 2000], while in dominant or preovulatory follicles, IGF levels are high, Pappa expression is high and intact IGFBPs are almost undetectable [Cataldo and Giudice, 1992; Hourvitz et al., 2000]. Thus, the up-regulation of Pappa in granulosa cells in the absence of PGR is intriguing and seems counter- intuitive to its demonstrated role in ovulation. It may relate to the concomitant down-regulation of cathepsin L in PRKO granulosa cells. Cathepsin L has been shown to clear IGFBP3 in fibroblasts [Zwad et al., 2002] and could potentially be involved in clearance of other IGFBPs. Hence, the accumulation of IGFBPs due to down-regulation of cathepsin L in the PRKO may result in a compensatory increase in Pappa to clear these binding proteins, thus increasing the bioavailability of IGFs. Validation of these microarray results is required using RT-PCR before further investigation of the relationship between PGR, Pappa, cathepsin L and IGF components.

Chemokine (C-X-C motif) receptor 4 (Cxcr4)

The chemokine receptor, CXCR4, was significantly down-regulated more than 3-fold in PRKO relative to PR+/- granulosa cells from the microarray assay, and this result was confirmed using real-time PCR and immunohistochemistry. CXCR4 has been shown to be regulated by PGR in tumour cells [Staller et al., 2003] and in the endometrium [Cloke et al., 2008]. There is also some previous evidence that PGR regulates CXCR4 expression in the ovary. A microarray study comparing PRKO and PR+/- whole ovaries collected at 11 h post-hCG reported reduced expression of CXCR4 in PRKO ovaries compared with PR+/- ovaries [Kim et al., 2009b]. Also, a more recent study using rat granulosa cells found that CXCR4 was down-regulated 8-fold after 5 h of culture with the PGR antagonist, Org 31710 [Friberg et al., 2010].

Real-time PCR showed that CXCR4 expression was up-regulated in granulosa cells in response to hCG, with a peak in expression at 8 h post-hCG. This corresponds with the peak in PGR expression in granulosa cells reported in rodents [Ismail et al., 2002; Park and Mayo, 1991; Robker et al., 2000;

Lisa Akison 2012 169 Teilmann et al., 2006]. A similar, transient expression of CXCR4 in granulosa cells has previously been shown [Kim et al., 2009b].

Importantly this chapter also shows, by real-time PCR, that COCs have a dramatic yet transient induction of CXCR4 expression in response to hCG, and that this induction is completely abolished in the PRKO mice. Up-regulation of CXCR4 has previously been shown in the COC [Hernandez- Gonzalez et al., 2006; Kim et al., 2009b], but this is the first time that this expression has been shown to be regulated by PGR. This was an interesting finding, given that PGR expression is restricted to granulosa cells and is absent from the cumulus cells or oocyte [Ismail et al., 2002; Robker et al., 2000; Teilmann et al., 2006]. This suggests that there is down-stream signalling from PGR in the granulosa cells that impacts on gene transcription in the COC.

CXCL12/CXCR4 is constitutively expressed in a wide variety of tissues and knockout models have demonstrated its importance in the development of B-lymphocytes, heart septum formation and cerebellar neuron migration [Ma et al., 1998], as well as gastrointestinal tract blood vessel development [Tachibana et al., 1998]. Deletion of either CXCR4 [Zou et al., 1998] or CXCL12 [Nagasawa et al., 1996] genes results in embryonic lethality. CXCL12/CXCR4 has also been found to be involved in retaining primordial follicles in an inactivated state in neonatal mouse ovaries, thus playing a role in maintaining the size and longevity of the primordial follicle pool [Holt et al., 2006].

Both in vitro and in vivo studies have demonstrated roles for CXCL12/CXCR4 in cell migration, chemotaxis and cell invasion through extracellular matrix. This includes immune cell chemotaxis and migration [Bleul et al., 1996; Ghosh et al., 2009], metastasis of tumour cells [Gelmini et al., 2008; Kucia et al., 2004; Sun et al., 2010; Teicher and Fricker, 2010], cancer cell migration and invasion through extracellular matrix [Scotton et al., 2001; Scotton et al., 2002; Teicher and Fricker, 2010], migration of neurons during CNS development [Belmadani et al., 2005], cellular trafficking of endothelial progenitor cells [Salvatore et al., 2010] and migration of primordial germ cells to the gonadal ridge during fetal development [Ara et al., 2003; Molyneaux et al., 2003b; Stebler et al., 2004].

The synthetic bicyclam, AMD3100 (also known as plerixafor hydrochloride), is widely regarded as a specific antagonist for CXCR4 (see [Liang, 2008] for review). AMD3100 was originally considered as a potential therapeutic for treating HIV infection, as CXCR4 is a co-receptor for the X4 HIV virus [Schols et al., 1997]. However, it has more recently been considered for treatment of metastatic . In vitro studies demonstrate that both proliferation and invasion by ovarian cancer cell lines (e.g. IGROV cells) were inhibited when cells were treated with AMD3100 [Scotton et al., 2002]. A recent study using bioluminescence resonance energy transfer (BRET) suggests that AMD3100 also binds to CXCR7, the alternative receptor for CXCL12, and is an agonist for this receptor [Kalatskaya et al., 2009]. Although the authors recommend caution in the use of this compound as a tool to dissect the effects of CXCL12 Lisa Akison 2012 170 on the respective receptors in vitro and in vivo, this is the only study in which this dual action has been reported. CXCR7 has been found to be expressed in ovarian cancer cells [Sun et al., 2010; Zabel et al., 2011] but to date has not been identified in normal ovarian granulosa or cumulus cells.

However, an attempt to inhibit binding of the chemokine ligand, CXCL12, to CXCR4 in vivo using AMD3100, did not reduce ovulation rate. This suggests that CXCR4 is not the key ovulatory mediator, or that it has functional redundancy. However, there is the possibility that the inhibitor was not reaching the follicles at a sufficient dose to have an effect. Previous studies which have used this inhibitor in vivo have shown that AMD3100 has a relatively short half life (30-60 mins) [Burroughs et al., 2005; Hendrix et al., 2004] and that it is undetectable in sera by 24 h, at least in humans [Hendrix et al., 2004]. To accommodate this, multiple doses were given over a relatively short period throughout the periovulatory window using dose rates previously reported in the literature for mice (e.g. [Broxmeyer et al., 2005; Kajiyama et al., 2008; Matthys et al., 2001]). Injections were given intraperitoneally, but the levels of AMD3100 in the sera were not measured to confirm that the inhibitor was in circulation and thus reaching the ovary. Intrabursal injections have been used previously to directly target specific inhibitors to preovulatory follicles (e.g. [Abramovich et al., 2009; Cheng et al., 2012; Martin and Talbot, 1981a; Martin et al., 1981; Van der Hoek et al., 2000]) and this may be a more appropriate method of delivery in future experiments.

This chapter identified a large number of dysregulated genes in PRKO granulosa cells that were associated with the functions of adhesion, migration and invasion and also provided evidence that PGR could indirectly affect the transcription of a gene, CXCR4, in the COC. Preliminary data from our laboratory suggests that the COC adopts an adhesive, migratory and invasive phenotype in response to hCG and so I hypothesise that this ‘activation’ of the COC contributes to facilitate its own release from the follicle. Perhaps this phenotype is defective in PRKO COCs, accounting for the observed anovulatory phenotype. Therefore, I proceeded next to focus on the COC. I characterised a novel adhesive, migratory and invasive phenotype of the periovulatory COC and then, using optimal conditions based on these experiments, compared PRKO and PR+/- COCs to determine if the PRKO COCs are defective. Additionally, other aspects of COC integrity and functioning were examined and compared between the PRKO and PR+/- COCs, including an analysis of genes regulated by PGR in the COC using microarray.

Lisa Akison 2012 171 Chapter 6 – Characterisation of the periovulatory cumulus oocyte complex and impact of PGR on structure and function

6.1 Introduction

It is clear that much of the ovulatory signalling cascade converges on the cumulus complex, coordinating oocyte maturation and COC matrix expansion [Russell and Robker, 2007]. Despite cumulus expansion being identified as critical to ovulatory success, the mechanism by which the cumulus oocyte complex mediates ovulation is unknown. Our laboratory has observed that the COC adopts an adhesive, migratory, and invasive phenotype in response to LH-induced expansion [Akison et al., 2012; Alvino, 2010]. Thus, our working model proposes that the COC plays an active role in facilitating its own release from the follicle via the processes of matrix production leading to cumulus expansion, adhesion to ECM components of the follicle wall and invasive migration.

The evidence-to-date supporting this proposal is compelling. Many of the extracellular matrix (ECM) components in the expanded cumulus complex are also known mediators of cellular motility and invasive capacity in other physiological systems. For example, hyaluronan is consistently associated with both pathological and physiological mechanisms of cell migration and invasion [Evanko et al., 2007; Toole, 2004; Turley, 1992]. Assembly of hyaluronan into a pericellular ‘sheath’ matrix is a key mechanistic step in the progression of epithelial to mesenchymal transition (EMT), activating migration of epithelial cells in scenarios such as wound healing [Ricciardelli et al., 2007; Toole et al., 2005]. The COC matrix is strikingly similar in composition to pericellular sheaths of motile cells comprising HA as well as versican and CD44. The interaction of hyaluronan with cells via CD44, both strongly induced after the LH surge in COCs [Kimura et al., 2002; Ohta et al., 1999; Schoenfelder and Einspanier, 2003; Yokoo et al., 2002], has been widely demonstrated to activate cell motility mechanisms in many systems [Bourguignon et al., 2006; Bourguignon et al., 2007; Bourguignon et al., 2010]. Another abundant cumulus matrix protein, versican, is a widely known promoter of EMT [Kern et al., 2006]. In cancer, versican is a well characterised anti-adhesive proteoglycan that cross-links hyaluronan in pericellular matrix [Evanko et al., 2007] and facilitates cell motility and metastasis [Ricciardelli et al., 2007; Wasa et al., 2011; Ween et al., 2010]. Furthermore, the ECM protease ADAMTS1 cleaves versican [Russell 2003] and is important for ovulation [Brown et al., 2010a; Mittaz et al., 2004] and is predominantly sequestered in its active form in the COC matrix near the time of ovulation [Russell et al.,

Lisa Akison 2012 172 2003b]. Active ADAMTS1 has been established to play a role during invasive cancer metastasis in other tissues [Keightley et al., 2010; Liu et al., 2006b; Lu et al., 2009; Ricciardelli et al., 2011]. Thus, the expanded COC matrix may be conducive to invasive migration of cumulus cells.

Our laboratory has identified that the COC does indeed develop a migratory, adhesive and matrix invading phenotype that is induced following the ovulatory LH surge [Akison et al., 2012; Alvino, 2010]. As previously described in Chapter 1, this phenotype was initially observed using in vitro Boyden chamber-style assays. Cumulus cells from expanded, preovulatory COCs displayed a greater affinity to adhere to ECM proteins present in the follicle wall than cumulus cells from immature, unexpanded COCs. Cumulus cells from expanded COCs also showed a propensity to migrate that was not observed in granulosa cells or cumulus cells from unexpanded COCs. They were also able to invade through an ECM as readily as a known invasive cancer cell line. However, it is not known precisely when this phenotype develops after the ovulatory stimulus or whether it is maintained after ovulation of the COC from the follicle. Therefore, the first aim of this chapter was to fully characterise the dynamically changing adhesive, migratory and invasive capacities of normal (wild-type) COCs throughout the periovulatory period.

Chapter 5 clearly demonstrated that many genes associated with migration, adhesion and invasion of cells were dysregulated in PRKO granulosa cells. One of the genes with the highest differential expression between PR+/- and PRKO samples was the chemokine receptor, CXCR4. Interestingly, although PGR is absent in cumulus cells, CXCR4 was found to be highly regulated by PGR in COCs using real-time PCR. Thus, PGR appears to have indirect, down-stream transcriptional targets in the COC. This is the first time that this has been reported. Therefore, the second aim of this chapter was to use microarray assays to uncover novel, dysregulated genes in PRKO COCs compared to PR+/- COCs during the periovulatory period. In addition, genes associated with the functions of migration/invasion and/or adhesion were identified.

Given that so many genes associated with adhesion, migration and invasion have been found to be dysregulated in periovulatory granulosa cells and COCs from PRKO follicles, I hypothesised that these processes may be defective in the periovulatory COCs from these mice, perhaps contributing to the observed anovulatory phenotype. Therefore, the third aim was to use optimal conditions for adhesion, migration and invasion of periovulatory COCs, as determined by the experiments characterising the COC’s phenotype in Aim 1, to test whether periovulatory COCs from PRKO mice are defective in these processes.

Although periovulatory COCs from PRKO mice appear to have normal morphology and cumulus expansion (see Chapter 3), other sub-cellular defects in PRKO COCs, which are undetectable in H & E stained sections, may be contributing to their anovulation. For example, PGR is known to regulate Lisa Akison 2012 173 ADAMTS1 expression, with PRKO mice showing reduced ADAMTS1 expression and reduced cleavage of its main substrate, versican, in the COC immediately prior to ovulation [Russell et al., 2003b]. As mentioned earlier in this thesis, ADAMTS1 is produced in the granulosa cells of preovulatory follicles and becomes associated with the ECM of the COC during cumulus expansion [Brown et al., 2010a; Russell et al., 2003b]. ADAMTS1 null mice show abnormal matrix formation and cumulus cell aggregation [Brown et al., 2010a], supporting its role in the formation of a correctly assembled cumulus matrix during the process of expansion. Thus, the composition of the matrix may be defective in some way due to the reduced expression and activity of ADAMTS1 in these mice. In addition, the results of the Immune Array from Chapter 4 suggest that prostaglandin synthesis may also be perturbed, given the reduced expression of Ptgs2 in the PRKO ovary at 10 h post-hCG. Ptgs2 is the synthesising enzyme for the prostaglandin, PGE2, which is critical for the regulation of EGF-like ligands that stimulate the production of essential cumulus matrix components [Hizaki et al., 1999; Segi et al., 2003; Shimada et al., 2006b; Takahashi et al., 2006]. Taken together, dysregulation of ADAMTS1 and prostaglandin production in PRKO COCs may result in compromised cumulus matrix. Therefore, the fourth aim was to examine matrix integrity in PRKO COCs compared to PR+/- COCs using a bio-assay which measures the retention of secreted PGE2.

Finally, the oocytes of periovulatory PRKO COCs were also examined for sub-cellular defects. Specifically, inner mitochondrial membrane potential (m) was measured, as mitochondrial bioenergetic activities in the oocyte are sensitive to external signals and have also been linked to oocyte developmental competence in the human (see [Van Blerkom, 2011] for review) and the mouse [Fernandes et al., 2012]. Mitochondria are specialised organelles that catalyse the formation of ATP through the metabolism of carbohydrates and fats contained within the cell cytoplasm. m is the proton gradient, created by the electron transport chain, between the inner and outer membrane of the mitochondria that drives ATP production required for cellular functions [Chen, 1988]. Using the frequently utilised JC-1 cationic dye, sub-cellular localisation of high and low membrane potential mitochondria was examined. Typically, dye aggregates which fluoresce red are indicative of high m and are localised to the pericortical region of periovulatory oocytes, while dye monomers which fluoresce green are indicative of low m and are localised to the inner cytoplasm [Van Blerkom et al., 2002]. This cytoplasmic zonation of high and low potential mitochondria in the oocyte is believed to be due to elevated requirements for ATP associated with the molecular and structural remodelling of the oolemma and pericortical cytoplasm in readiness for fertilisation [Van Blerkom, 2011]. Perturbations in mitochondrial membrane potential in the oocyte have been recently reported in mice in response to metabolic insult (e.g. high fat diet/fatty acid treatment [Wu et al., 2010; Wu et al., 2012]), insulin resistance [Ou et al., 2012], disruption/knockout of specific genes (e.g. Nlrp5 [Fernandes et al., 2012]) and vitrification [Demant et al., 2012; Zhao et al., 2011]. Thus, the final aim was to compare JC-1

Lisa Akison 2012 174 staining of m in PRKO with PR+/- periovulatory COCs to determine if mitochondrial function was perturbed.

6.2 Materials & Methods

6.2.1 Animals, hormonal stimulation and tissue collection

For the migration/adhesion/invasion experiments, female CBAF1 or PRKO/PR+/- mice were injected i.p. with 5 IU of eCG and 5 IU hCG to initiate follicle growth and induce ovulation, as detailed in Section 2.1.4. For the CBAF1 mice, COCs were collected as described in Section 2.1.5 at 48 h post-eCG and 4 h, 8 h, 10 h, 12 h and 14 h post-hCG, where ovulation occurred at around 12 h post-hCG. COCs were pooled from at least 6-10 animals for each independent experiment. For experiments using PRKO and PR+/- mice, COCs were isolated at 44 h eCG + 10 h post-hCG only and individual mice were used as the biological replicates.

For the microarray experiment, COCs were collected from PRKO and PR+/- mice as per Section 2.1.5. Briefly, cells were collected at 44 h eCG + 8 h post-hCG in HEPES-buffered αMEM with no serum added, snap-frozen in liquid nitrogen and stored at -80ºC.

For analysis of PGE2 production and JC-1 staining of oocyte mitochondrial membrane potential, COCs were collected from PRKO and PR+/- mice at 44 h eCG + 10 h post hCG as per Section 2.1.5. For the

PGE2 assay, COCs pooled from individual mice constituted the biological replicates. For JC-1 staining, COCs were collected from 4 animals of each genotype.

6.2.2 Breast cancer cell lines

Two highly invasive, metastatic human breast cancer cell lines, MDA-MB-231 (hereafter referred to as MB-231) and Hs578t (American Type Culture Collection, Manassas, VA, USA), were used as positive controls for the invasion assays. The invasive capacity of these cell lines has been described previously [Blick et al., 2008]. Cells were maintained in RPMI media (Sigma-Aldrich Pty Ltd, Castle Hill, NSW, AU) supplemented with 5% FCS and 1% penicillin-streptomycin solution (GIBCO, Invitrogen

Australia Pty. Ltd., Mulgrave, VIC, AU) at 37°C/5% CO2 until 80% confluent. Cells were trypsinized using 0.25% Trypsin in EDTA (GIBCO, Invitrogen Australia Pty. Ltd., Mulgrave, VIC, AU) for 2 min at room temperature, washed with serum-free media (SFM; RPMI), centrifuged at 450  g for 5 min and re-suspended in SFM. Cells were counted using a haemocytometer and 4 x 104 cells were loaded in 100 μl of SFM to the top chamber of the assay instrument (Section 6.2.4). This is approximately Lisa Akison 2012 175 equivalent to the number of cells in 20 COCs, with COCs estimated at 2000 cells/COC [Amiel et al., 1993].

6.2.3 RNA extraction and microarray analysis

RNA was extracted in Tri Reagent and DNase-treated before use (see Section 2.3 for more details). RNA concentration and quality was assessed using a Nanodrop ND-1000 Spectrophotometer (Biolab Ltd, Clayton Vic, Australia) and preliminary RT-PCR analysis of Rpl19 expression as described in Section 2.3. Sample genotypes were verified before pooling for microarray assays as per Section 2.3.

Once quality and genotype were confirmed, RNA from 3 animals was pooled for each sample, with 4 replicates for each genotype (see Appendix 2 for details of microarray pooled samples). Approximately 100 ng total RNA from each sample was sent to the Adelaide Microarray Centre (AMC) for analysis. Final pooled samples were checked for RNA integrity (RIN) by the AMC using an Agilent Bioanalyzer (Agilent Technologies, Santa Clara, USA; Appendix 2) and were considered acceptable for microarray analysis at a minimum threshold of 7-7.5 (M. Van der Hoek, AMC, pers. comm.). Sample preparation was performed by AMC using Affymetrix GeneChip® Kits (Affymetrix, Santa Clara, USA) according to the manufacturer’s instructions. A brief description of the protocol is given in Section 2.5. Following biotinylation, samples were hybridised overnight to Affymetrix GeneChip® Mouse Gene 1.0 ST Arrays (Affymetrix, Santa Clara, USA). The arrays were washed, stained using a fluorescently-labelled antibody and scanned using a high resolution scanner (Affymetrix GeneChip Scanner 3000 7G Plus).

Microarray data were analysed by the AMC using Partek® Genomics Suite™ software (Partek Incorporated, St Louis, MO, USA). See Section 2.5.2 for more details. A Principal Components Analysis (PCA) plot was used to examine the relationship of individual samples within genotype (see Section 2.5.2 for more details). A volcano plot was also created using all genes found on the array to summarise the data set (see Section 2.5.2 for more details). A data set containing genes that were differentially expressed between the two genotypes was imported into the Ingenuity Pathway Analysis software (IPA; Ingenuity Systems, Redwood City, CA, USA) to identify significant associations with biological functions.

6.2.4 In vitro real-time cell adhesion, migration and invasion assays

Cell adhesion, migration and invasion assays were performed using the xCELLigence Real-Time Cell Analyzer (RTCA) DP instrument (Roche Diagnostics, Indianapolis, IN, USA) as described in detail in Sections 2.8 and 2.9. The RTCA system requires no fixed end-point or manual staining and counting of Lisa Akison 2012 176 cells, therefore increasing reproducibility and precision. It is also much less labour-intensive, thus a study including multiple time points is feasible. For adhesion assays, 10 COCs collected at 10 h, 12 h or 14 h post-hCG were added to E-plate 16 wells coated with mouse collagen type IV (Coll IV), rat tail collagen type I (Coll I), purified human fibronectin (FN) (all from BD Biosciences, Bedford, MA, USA) or laminin (Geltrex reduced growth factor basement membrane matrix; GIBCO, Invitrogen Australia Pty. Ltd., Mulgrave, VIC, AU), as well as BSA (Sigma-Aldrich Pty Ltd, Castle Hill, NSW, AU) as a negative control. All ECMS were coated in quadruplicate wells at a concentration of 50 μg/ml (20 μl/well). For migration assays, 20 whole COCs collected at 48 h post-eCG, or 4 h, 8 h, 10 h, 12 h or 14 h post-hCG were added in media to each upper chamber of an xCELLigence CIM-plate and incubated with media in the lower chamber containing EGF (3 ng/ml) and 5% FCS. Cell Index was measured for at least 14 h (see Section 2.11). Data was from 3-5 independent experiments. For invasion assays, 20 whole COCs collected at 10 h post-hCG were added in media to each upper chamber of an xCELLigence CIM-plate pre-coated with 400 g/ml collagen I. Media in the lower chamber was as for migration assays. Cell Index was measured for at least 6 h (see Section 2.11). Invasion index was calculated by dividing the migration index measured in wells coated with Coll I with the migration index measured in wells with no ECM coating at 6 h, and multiplying by 100 to provide the percentage of migratory cells that were also invasive. Data was from 3-5 independent experiments. For comparison of PRKO and PR+/- COC adhesion, migration, and adhesion, the appropriate number of COCs was added to each well (as per experiments with COCs from CBAF1 mice, see above) from individual mice to delineate between different genotypes. Therefore, individual mice formed the biological replicates for these experiments and were usually run in duplicate wells.

6.2.5 Prostaglandin E2 assay as a measure of cumulus matrix integrity

Levels of PGE2 retained in the extracellular matrix of the cumulus complex and secreted into the surrounding media were measured. Thus, this assay functions as a bioassay of matrix integrity, and has been used previously by our laboratory to compare in vivo and in vitro matured COCs [Dunning et al., 2012]. COCs (n = 20 collected from individual mice) were cultured in 100 μl of complete MEM (MEM supplemented with 5% FCS and 250 μM pyruvate) containing 50 mIU/ml FSH and 3 ng/ml EGF in an Eppendorf tube for 1 h at 37C/6% CO2 (20 COCs per 100 μl). COCs were lightly pelleted by centrifugation at 5,000 X g for 2 min and the resultant supernatant (the media fraction) was collected for the PGE2 assay. Pelleted COCs were then resuspended in 50 μl hyaluronidase (100 U/ml), vortexed briefly, followed by centrifugation at 5,000 X g for 2 min to pellet cumulus cells. The resultant supernatant (the extracellular matrix fraction) was also collected for the PGE2 assay. Separate media and extracellular matrix fractions were snap-frozen in liquid nitrogen and stored at -80oC until analysis. Lisa Akison 2012 177 Levels of PGE2 were measured by commercially available competitive ELISA (Thermo Scientific,

Rockford, IL; sensitivity 15.9 pg/ml; range 39-5000 pg/ml) as per the manufacturer’s instructions. PGE2 measurements were made in duplicate on 1-2 samples from each individual mouse, with 7 PRKO and 6

PR+/- mice used to compare PGE2 concentrations for media and matrix fractions between the genotypes. The ratio of PGE2 in media to matrix was calculated by dividing the amount of PGE2 measured in the matrix by the amount measured in the media. Culture media and hyaluronidase alone contained negligible levels of PGE2 (data not shown).

6.2.6 JC-1 staining of oocytes as a measure of mitochondrial membrane potential

Oocytes were denuded by adding 50 μl of pre-warmed hyaluronidase (1000 IU/ml; GIBCO, Invitrogen Australia Pty. Ltd., Mulgrave, VIC, AU) to the COCs in the collection media (MEM-HEPES + 5% FCS) for 1 min, followed by gentle repeated pipetting with a fine, glass pipette to remove remaining cumulus cells. Denuded oocytes were washed in fresh collection media and then incubated in collection media containing the cationic dye, JC-1 (5, 5’, 6, 6’-tetrachoro-1, 1’, 3, 3’-tetraethylbenzimidazolyl carbocyanine iodide; GIBCO, Invitrogen Australia Pty. Ltd., Mulgrave, VIC, AU) at 6 μM for 15 mins at 37C in the dark. JC-1 exhibits potential-dependent accumulation in mitochondria, indicated by a change in fluorescence emission from green (~525 nm) to red (~590 nm). High membrane potential promotes formation of J-aggregates which fluoresce red, while low membrane potential results in monomeric dye particles which fluoresce green. The ratio of red to green fluorescence is dependent only on the membrane potential and not on other factors such as mitochondrial size, shape or density [Smiley et al., 1991]. Oocytes were then immediately imaged using a Fluoview FV10i Olympus confocal microscope using both red and green fluorescence channels at identical magnification (60X) and gain settings throughout experiments. One image from each oocyte was taken in an optical cross- section through the centre of the oocyte at its largest diameter. A total of 61 oocytes from 4 PR+/- mice and 58 oocytes from 4 PRKO mice were imaged on two separate occasions. AnalySIS LS Professional software (Olympus Australia, Mt Waverly, VIc, AU) was used to measure red or green fluorescence intensity in a ~10 μm wide box placed across the entire oocyte. Total red or green fluorescence intensity was determined at 0.3 μm intervals across this box for each oocyte. Mean and SE red or green fluorescence intensity was calculated across all PRKO or PR+/- oocytes.

Lisa Akison 2012 178 6.2.7 Statistical analyses

For xCELLigence real-time adhesion, migration and invasion assays, delta Cell Index values were calculated at 12 h for adhesion assays and 14 h for migration assays/invasion assays to compare treatment groups. To analyse xCELLigence experiments and the PGE2 assay, a one- or two-way analysis of variance (ANOVA) was used, with the Holm-Sidak post-hoc multiple comparison procedure to determine significant differences between groups. Where samples were collected from the same animals (i.e. some adhesion assays), a repeated-measures two-way ANOVA was used. Where only two groups were being compared, the Student’s t-test (either paired or unpaired as required) was used. Data were log- or square root-transformed where required to normalise the distribution. All analyses were performed using the Sigmaplot 11.0 graphing and statistical package (Systat Software Inc.). For comparison of red or green channels between genotypes for the JC-1 staining across the COC, a mixed model 2-way ANOVA was used. This analysis was performed using GraphPad Prism software (GraphPad Software Inc., La Jolla, CA, USA).

6.3 Results

6.3.1 COC Adhesion to ECM proteins

The binding affinity of intact, preovulatory COCs to various extracellular matrix proteins was examined (Figure 6.1). The adhesion index to negative control BSA-coated wells remained around 0.1 throughout the analysis and was used to visualise the baseline adhesion level (Figure 6.1A). Over 12 h in real-time cell analysis, the COC cell index rose sharply against all extracellular matrix proteins, indicative of a specific interaction between the COCs and ECM coating (Figure 6.1A). COC adhesion to collagen type I was significantly higher than to fibronectin and adhesion to each of the ECMs was significantly greater than the BSA negative control, with the exception of fibronectin (Fig 6.1B).

Our lab has previously shown that adhesion to ECM proteins was induced in cumulus cells shortly after hCG stimulation (Chapter 1, Fig 1.6). Interestingly, the adhesive capacity of expanded COCs to various extracellular substrates was also dependent on the stage in the ovulatory process. Preovulatory COCs at both 10 h and 12 h post-hCG showed high adhesive affinity to Geltrex (main component laminin), and collagen types I and IV (Figure 6.1C). However, ovulated COCs isolated from the oviduct 14 h post-hCG showed a significantly reduced capacity to adhere to these proteins (Figure 6.1C). This marked change in binding capacity suggested that adhesion was rapidly reduced upon release of COCs into the oviduct. To confirm that this loss of adhesive capacity was a result of the

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A 0.7 C 0.6 Coll I 10 h post-hCG COCs 0.6 Coll IV 12 h post-hCG COCs 0.5 a Geltrex a a 14 h post-hCG COCs 0.5 FN 0.4 ad 0.4 BSA ad d 0.3 0.3 c 0.2 0.2 bc

Adhesion Index Adhesion b b 0.1 0.1 b b 0.0 0.0

0 1 2 3 4 5 6 7 8 9 10 11 12 13 + SE) at 12 h (Mean Index Adhesion Geltrex Coll I Coll IV BSA Time (Hour) B D 0.7 0.35 12 h post-hCG COCs a a a Preovulatory COCs 0.6 0.30 Ovulated COCs 0.5 ab 0.25 a ab bc 0.4 0.20 c bc 0.3 0.15 bc 0.2 c 0.10 b b 0.1 0.05

0.0 0.00 Adhesion Index at 12 h (Mean + SE) at 12 h (Mean Index Adhesion Adhesion Index at 12 h (Mean + SE) at 12 h (Mean Index Adhesion Coll I Coll IV Geltrex FN BSA Geltrex Coll I Coll IV BSA

Figure 6.1 Adhesion of COCs to ECM substrates is dynamic across the periovulatory window. Cellular adhesion to extracellular matrix (ECM) proteins was assessed in real-time using intact COCs. A) Preovulatory COCs (10 h post-hCG) were examined for adhesive potential to 4 ECM proteins. Adhesion index (mean ± SE) was plotted at 24 min intervals for each ECM. B) Adhesion index after 12 h real-time cell analysis (mean + SE). Different letters denote significantly different groups at P<0.01. C) Comparative adhesive capacity of preovulatory COCs (10 h and 12 h post-hCG) and ovulated COCs (14 h post-hCG) after 12 h real-time cell analysis. Different letters denote significantly different groups at P<0.001. D) Adhesive capacity after 12 h real-time cell analysis of preovulatory and postovulatory COCs collected at 12 h post-hCG from the same animals. Different letters denote significantly different groups at P<0.05. For A) to D), data is from 3-4 independent xCELLigence experiments for each ECM and/or time point. Coll = collagen; FN = fibronectin; BSA= bovine serum albumin.

Lisa Akison 2012 180 release of COCs into oviducts rather than the time elapsed, COCs were collected from oviducts or by follicle puncture from the same mice at 12 h post-hCG, the time when 50% of follicles have ovulated in this mouse model (see Chapter 2, Figure 2.2). COCs collected from within follicles compared to those collected from oviducts, showed a significantly greater adhesion to the ECM proteins (Figure 6.1D). This difference in binding affinity of pre- and postovulatory COCs was not observed for the BSA negative control (Figure 6.1C and D).

6.3.2 Migratory phenotype of COCs

Previous observations of increased cumulus cell migration in 10 h post-hCG treated COCs suggested that cell migration was induced with COC expansion [Akison et al., 2012; Alvino, 2010]. The pattern of regulation of cell migration was further examined by assessing the migratory capacity of COCs over a time course after hCG (Figure 6.2). Cell migration index of unexpanded COCs (0 h post-hCG) showed little change over time in Cell Invasion Migration (CIM) chambers (Figure 6.2A). With increasing time post-hCG, the capacity of cumulus cells in COCs to migrate increased sequentially and was significantly greater than basal levels by 10 h and maximal at 12 h post-hCG (Figure 6.2A and B), when ovulation occurs. Ovulated COCs collected from the oviduct had a reduced capacity to migrate immediately post-ovulation at 12 h post-hCG and was significantly lower at 14 h post-hCG (P<0.05); at which time migration rates were not significantly different from the basal rate in unexpanded COCs (Figure 6.2A and B). Thus, COCs display a transient migratory phenotype that is hormonally induced, peaking at the time of ovulation and declining dramatically after COCs are released into the oviduct.

6.3.3 Invasion of preovulatory COCs through an ECM protein

Collagen type I is abundant in the ovarian wall and our adhesion assays showed that preovulatory COCs had a high affinity to bind to collagen type I (Figure 6.1). I therefore assessed the capacity of COCs to invade through collagen type I using the xCELLigence RTCA system (Figure 6.3). Two positive control invasive breast cancer cell lines, MB-231 and Hs578t, were able to penetrate a layer of collagen type I, albeit more slowly relative to uncoated (No ECM) membranes (Figure 6.3A and B), as expected based on extensive characterisation of invasion in these cells [Sakai et al., 2011]. The delay in cell migration through collagen-coated membranes demonstrates that the ECM coating presents an effective barrier, but not a total block, to the movement of invasive cancer cell lines (Figure 6.3A and B).

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A

0.25 0 h post-hCG (unexpanded) 4 h post-hCG 8 h post-hCG 0.20 10 h post-hCG 12 h post-hCG 12 h post-hCG (ovulated) 0.15 14 h post-hCG (ovulated)

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0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 B Time (Hour) 0.25 b

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a 0.05

Migration Index at 14 h (Mean + SE) at 14 h (Mean Index Migration 0.00 0 h 4 h 8 h 10 h 12 h 14 h Preovulatory Ovulated Time post-hCG

Figure 6.2 The migratory phenotype of COCs is temporally regulated. Cellular migration was assessed in real-time using intact COCs isolated from preovulatory follicles or from the the oviduct (ovulated). A) Migration Index (mean ± SE) at 30 min intervals for preovulatory COCs at 0 h, 4 h, 8 h, 10 h and 12 h post-hCG, and ovulated COCs at 12 h and 14 h post-hCG. B) Migration Index after 14 h real-time cell analysis (mean + SE). Data is from 3-5 independent experiments for each time point and different letters indicate significant differences (P<0.05).

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A B C 1.0 MB-231 2.5 Hs578t 0.30 No ECM No ECM COCs 0.8 Coll I 2.0 0.25 Coll I No ECM Coll I 0.20 0.6 1.5 0.15 0.4 1.0 0.10 Migration Index Migration 0.2 Index Migration 0.5 Index Migration 0.05

0.0 0.0 0.00 0 2 4 6 8 10 12 14 0 2 4 6 8 10 12 14 0 2 4 6 8 10 12 14 Time (Hour) Time (Hour) Time (Hour)

D 120 * E 120 ns 100 100 80 80 60 60 40 40 20 20 Invasion Index (%) Invasion Index Invasion Index (%) Invasion Index 0 0 COCs MB-231 COCs Hs578t

183

Figure 6.3 Preovulatory expanded COCs are as invasive as two known invasive cell lines. Expanded COCs (10 h post-hCG) were analysed for their ability to invade an extracellular matrix (collagen I) and were compared to two known invasive breast cancer cell lines (MB-231 and Hs578t). Migration index (mean ± SE) plotted at 30 min intervals for wells with No ECM and wells coated with collagen I (Coll I) for (A) MB-231 cells, (B) Hs578t cells and (C) COCs. Data after 6 h of real-time cell analysis was used to calculate the invasion indices (mean ± SE) for COCs, MB-231 cells and Hs578t cells (D, E). Invasion index was calculated for each cell type by dividing the migration index measured in Coll I coated wells by the migration index measured in wells without ECM and multiplying by 100, providing a percentage of the total migratory cells able to invade the ECM barrier. Data is from 3-5 independent experiments. * P<0.05 by unpaired Student’s t-test; ns = not significant.

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Preovulatory COCs (10 h post-hCG) invaded through the collagen-coated membranes with similar efficiency as the migration of COCs through uncoated membranes, demonstrating that the cumulus cells from these COCs are highly invasive and not impeded by the collagen I barrier (Figure 6.3C). As a result, COCs showed close to 100% invasive index through collagen I, which was significantly greater than the invasion index of the MB-231 cells (P<0.05; Figure 6.3D) and indistinguishable from the invasion index of the Hs578t cells (P=0.46; Figure 6.3E). Thus, preovulatory COCs showed invasive capacity through collagen type I that was equivalent to or greater than two of the most highly invasive cancer cell lines.

6.3.4 Cumulus Cell Microarray

Affymetrix Mouse Gene 1.0 ST Arrays were used to examine potential down-stream regulation by PGR in COCs. Principal components analysis revealed that the 8 samples could be clustered into two distinct groups based on their gene expression profiles that corresponded to each genotype (Figure 6.4). There were 44 genes differentially expressed in the cumulus cell microarray experiment (P<0.05), with 52% down-regulated in the PRKOs (Fig. 6.5, Table 6.1). The majority of these genes (n = 28, 64%) were specific to the COC microarray while the remaining 16 genes were also identified to be differentially expressed in the granulosa cell microarray. This may reflect granulosa cell contamination during COC isolation. The volcano plot for the COC microarray analysis (Figure 6.5) highlights the relatively fewer, statistically significant genes compared to the granulosa cell microarray analysis (Figure 5.2). This is not surprising given that PGR is not expressed in the COC, and thus any transcriptional changes are down-stream of the regulatory effects of PGR in the granulosa cells. However, there were comparatively more genes with large magnitude fold changes in the COC (i.e. 15/44 significant genes versus 7/296 genes in granulosa cells with fold change >4), which is typically a measure of high biological significance [Cui and Churchill, 2003].

The most highly down-regulated gene was the zinc-finger protein, Zbtb16, which was also the most highly down-regulated gene in PRKO granulosa cells. It was one of 11 genes identified by IPA as being involved in invasion/migration or adhesion, 25% of the total significant genes in Table 6.1. Also included amongst these were Epas1/Hif2 and Rgmb which were also different in the granulosa cell microarray and were discussed in detail in Chapter 5. Given our hypothesis of an ‘activated’ COC facilitating its own release from the ovary at ovulation, these genes may be involved in regulating the adhesion of the COC to ECM components in the follicle wall, as well as invasion and migration out of the follicle at ovulation. There were also several other interesting genes in PRKO COCs that were close to being statistically significant and had high fold change differences relative to PR+/- COCs.

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Figure 6.4 Principle Component Analysis plots for COC microarray samples. Red spheres are PR+/- samples and blue spheres are PRKO samples. Top view has principal components 1 and 2 shown for the X and Y axes respectively. Bottom view shows the chart rotated clockwise to show the clustering of samples for each genotype.

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1.8

Zbtb16 1.6 Epas1 Rgmb Pparg Cxcr4 1.4 Stxbp6 Efnb2 Adam8 1.2

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-4 -3 -2 -1 0 1 2 3 4

log2 Fold Change Figure 6.5 Volcano plot of COC microarray data. Samples collected at 8 h post-hCG. All 28,853 genes from the Affymetrix GeneChip® Mouse Gene 1.0 ST Array are plotted. The red dashed line represents P = 0.05 with points above the line having significantly dysregulated in PRKO relative to PR+/- samples (n = 44) and points below the line not significant. The plot is centred around genes with a fold change of 1 (log2 1 = 0), with genes to the right of the vertical black line up-regulated in PRKO and genes to the left of the vertical black line down-regulated in PRKO compared with PR+/-. Genes with a fold change <2 are shown in grey. Some of the genes discussed further in the text are shown in green.

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Table 6.1 Genes differentially expressed in PRKO and PR+/- COCs from microarray analysis. Fold change is PRKO relative to PR+/- COCs. P<0.05 for all genes listed. Genes in bold were also identified as differentially expressed in the granulosa cell microarray. M/I = genes associated with cell migration/invasion; A = genes associated with cell adhesion/cell binding. Associations with functions were determined using Ingenuity Pathway Analysis. Migration/ Gene Fold Invasion/ Symbol Gene Name change Adhesion Zbtb16 zinc finger and BTB domain containing 16 -14.15 M/I Hsd17b11 hydroxysteroid (17-beta) dehydrogenase 11 -8.81 Epas1 endothelial PAS domain protein 1 (Hif2a) -7.18 A Arl4d ADP-ribosylation factor-like 4D -6.00 Gpt2 glutamic pyruvate transaminase (alanine aminotransferase) 2 -4.51 Stxbp6 syntaxin binding protein 6 (amisyn) -3.21 Lepr leptin receptor -2.71 A Lipg lipase, endothelial 2.55 A Rasal1 RAS protein activator like 1 (GAP1 like) 2.54 Mapre2 microtubule-associated protein, RP -2.54 Kcng3 potassium voltage-gated channel, subfamily G, member 3 -2.38 Rasl10a RAS-like, family 10, member A -2.32 Rgmb RGM domain family, member B 2.24 M/I A Gm2a GM2 ganglioside activator protein 2.23 Rab11fip1 RAB11 family interacting protein 1 (class I) -2.13 Amigo2 adhesion molecule with Ig like domain 2 -1.95 A Adipor2 adiponectin receptor 2 -1.71 A Lgmn legumain 1.70 Slc1a4 solute carrier family 1 (glutamate 1.66 Dpy19l1 dpy-19-like 1 (C. elegans) 1.62 Rasgrf2 RAS protein-specific guanine nucleotide-releasing factor 1.61 A Icosl icos ligand -1.61 A Gzf1 GDNF-inducible zinc finger protein 1 -1.60 Pogk pogo transposable element with KRAB domain 1.58 Paqr8 progestin and adipoQ receptor family member VIII -1.56 Ddah2 dimethylarginine dimethylaminohydrolase 2 1.54 Gab2 growth factor receptor bound protein 2-associated protein 2 -1.53 A Oplah 5-oxoprolinase (ATP-hydrolysing) 1.50 Endod1 endonuclease domain containing 1 1.48 Zc4h2 zinc finger, C4H2 domain containing 1.42 Mbnl3 muscleblind-like 3 (Drosophila) -1.41 Ptp4a2 protein tyrosine phosphatase 4a2 1.39 Arhgef10 Rho guanine nucleotide exchange factor (GEF) 10 -1.38 Sh3glb2 SH3-domain GRB2-like endophilin B2 1.33 Cbx4 chromobox homolog 4 (Drosophila Pc class) 1.31 Ddx10 DEAD (Asp-Glu-Ala-Asp) box polypeptide 10 1.30 Inppl1 inositol polyphosphate phosphatase-like 1 1.29 A Gse1 genetic suppressor element 1 -1.29 Tmco3 transmembrane and coiled-coil domains 3 1.26 Hdac10 histone deacetylase 10 1.20 Slc30a9 solute carrier family 30 (zinc transporter), member 9 -1.19 Spats1 spermatogenesis associated, serine-rich 1 -1.19 Sart1 squamous cell carcinoma antigen recognized by T-cells 1 1.16 Stap1 signal transducing adaptor family member 1 -1.14 Lisa Akison 2012 188

These were CXCR4 (P = 0.0507; fold change = -2.92), Efnb2 (P = 0.0517; fold change = -4.16) and Adam8 (P = 0.0553; fold change = -4.31), which were all previously identified as PGR-regulated in granulosa cells in Chapter 5. Pparg (P = 0.0507; fold change = -2.42) and Plat (P = 0.0507; fold change = 1.93) are also worth mentioning here as they were almost significantly different in COCs but not in granulosa cells.

6.3.5 Is adhesion, migration, and invasion by PRKO pre-ovulatory COCs defective?

Given that PRKO granulosa cells and COCs have many genes dysregulated that are associated with the processes of adhesion, migration and invasion of cells, I next wanted to determine whether the COCs of anovulatory PRKO mice were deficient in these properties. Therefore, the migratory capability and adhesive and invasive properties in the presence of collagen I were compared for 10 h post-hCG COCs collected from PRKO and PR+/- mice. Collagen I was chosen as adhesion assays had shown that preovulatory COCs had an affinity to bind to this ECM (Figure 6.1) and 10 h post-hCG COCs were used for this genotypic comparison as this was when migration rates were maximal without ovulations occurring (Figure 6.2). Typically, serum (FCS) is added to the handling media during the collection of COCs for in vitro adhesion, migration and adhesion assays and then COCs are transferred to serum- free media for loading into the plate chambers for each assay. However, as mentioned in Chapter 1, there are factors present in serum that are known to be important for the correct assembly of the cumulus matrix during expansion (e.g. II, [Chen et al., 1992; Salustri et al., 1989]). Although the vasculature of PRKO ovaries appeared normal during the periovulatory period, I did not directly compare the ability of serum factors, such as II, to enter the follicle and therefore there may in fact be differences in exposure of PRKO COCs to serum factors in vivo. If this were the case, including serum in the media during isolation of COCs from the ovary, would expose PRKO COCs to serum factors that they may not be exposed to in vivo and potentially ‘mask’ a defective phenotype. Therefore, separate experiments compared COCs that were collected in the presence or absence of serum in the media.

The adhesive, migratory and invasive phenotypes of COCs from both genotypes were very similar. There was no significant difference in the migratory capacity of PRKO COCs compared with PR+/- COCs (Figure 6.6), irrespective of whether there was serum added to the handling medium during the isolation of the COCs from the ovary (Figure 6.6A) or omitted from the isolation procedure (Figure 6.6B). Therefore, in all subsequent experiments, the practise of adding serum to the handling medium was retained. There was also no significant difference in the adhesive capacity of PRKO and PR+/-

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A) A 0.6 0.6 PR+/- (n = 8 animals) Serum 0.5 PRKO (n = 5 animals) 0.5 0.4 0.4 0.3 0.3

0.2 0.2

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Migration Index (Mean +/- SE) +/- (Mean Index Migration 0.0 0.0 0 2 4 6 8 10 12 14 PR+/- PRKO Migration Index at 14h (Mean + SE) (Mean at 14h Index Migration Time (Hour) B) B 0.6 No Serum PR+/- (n = 7 animals) 0.6 0.5 PRKO (n = 6 animals) 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1

Migration Index (Mean +/- SE) +/- (Mean Index Migration 0.0 0.0 0 2 4 6 8 10 12 14 PR+/- PRKO Migration Index at 14h (Mean + SE) (Mean at 14h Index Migration Time (Hour)

Figure 6.6 PRKO COCs show migratory capacity comparable to PR+/- COCs. COCs were isolated at 10 h post-hCG either A) in the presence of 5% serum (FCS) in the handling media during collection or B) in the absence of serum in the handling media. There was no significant difference in the migration rate of COCs between the two genotypes, irrespective of whether serum was included, after 14 h of Real Time Cell Analysis by unpaired Student’s t-test (serum P = 0.331; no serum P = 0.243).

Lisa Akison 2012 190 preovulatory COCs to collagen I (Figure 6.7). Similarly, the invasive capacity of PRKO versus PR+/- COCs through collagen I was virtually identical (Figure 6.8). Therefore, from these in vitro assays, it appears that the migratory, adhesive and invasive capacity of PRKO COCs is normal.

6.3.6 Integrity of the matrix in PRKO COCs may be perturbed: a bioassay using

PGE2 production

Another functional property of the expanded COC matrix that forms in the periovulatory period is the ability to act as a molecular filter, which excludes small molecules such as glucose and cholesterol diffusing towards the oocyte but also retains products such as PGE2 made by the cumulus cells within the complex [Dunning et al., 2012]. Our lab has recently discovered this property and developed it as a sensitive test of COC matrix function. The secretion of PGE2 from the COCs into surrounding culture media over 1 h is a highly quantitative indicator of ECM integrity (considered to be dependent on composition and structure). I investigated the secretion of PGE2 from intact COCs of both PRKO and PR+/- genotypes.

The gene for the rate-limiting enzyme in PGE2 production, PTGS2, was shown to be down-regulated in PRKO COCs compared to PR+/- at 10 h post-hCG (Figure 6.9A; data is from complete time-course shown in Figure 4.6). The concentration of PGE2 was measured in the extracted matrix as well as in the media in which the COCs were incubated. Total concentrations of PGE2 (matrix-bound plus secreted) for COCs of each genotype showed no statistically significant difference (Figure 6.9B), although there was a trend for higher overall production in the PRKO COCs. When analysed as the specific medium and matrix fractions, the concentration of PGE2 in the matrix fraction collected from the PRKO COCs was equivalent to that collected from the PR+/- COCs (Figure 6.9C). However, the concentration of PGE2 in the media surrounding the PRKO COCs was significantly higher than that of the media surrounding the PR+/- COCs (Figure 6.9C). Thus, the medium:matrix ratio of PGE2 was significantly higher in PRKO compared with PR+/- COCs (Figure 6.9D). These results are suggestive of altered capacity of the COC matrix to restrain the diffusion of small molecules and hence may indicate a possible deficiency at the molecular level.

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0.6 0.6 PR+/- (n = 7 animals) 0.5 PRKO (n = 5 animals) 0.5 0.4 0.4

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Adhesion Index (Mean +/- SE) (Mean Index Adhesion 0.0 0.0 0 2 4 6 8 10 12 14 PR+/- PRKO Adhesion Index at 12 h (Mean + SE) h (Mean at 12 Index Adhesion Time (Hour)

Figure 6.7 PRKO COCs are as adhesive to collagen I as PR+/- COCs. COCs were isolated at 10 h post-hCG and assayed for their adhesion to collagen I (50 g/ml). There was no significant difference in the adhesive ability of COCs between the two genotypes after 12 h of Real Time Cell Analysis by unpaired Student’s t-test (P = 0.278). Data was log- transformed before analysis to normalise the distribution.

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0.4 PR+/- (n = 4 animals) 0.4 PRKO (n = 5 animals) 0.3 0.3

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Migration Index (Mean +/- SE) +/- (Mean Index Migration 0.0 0.0 0 2 4 6 8 10 12 14 PR+/- PRKO Migration Index at 14h (Mean + SE) at 14h (Mean Index Migration Time (Hour)

Figure 6.8 PRKO COCs are as invasive through collagen I as PR+/- COCs. COCs were isolated at 10 h post-hCG. Cell migration was measured in wells coated with collagen I (400 g/ml). There was no significant difference in the invasive capacity of COCs between the two genotypes after 12 h of Real Time Cell Analysis by unpaired Student’s t-test (P = 0.744).

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A) 16 14 a

12 10 8

Change Fold 6 b 4 Ptgs2 2 0 PR+/- PRKO B) 8000 ns 6000

4000 /COC (pg/ml) /COC 2 2000 PGE

0 PR+/- PRKO C) 4000 b b b medium 3000 matrix

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0 PR+/- PRKO D) 1.0 b

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Ratio of PGE 0.0 PR+/- PRKO

Figure 6.9 PRKO COCs lose more PGE2 to the media than PR+/- COCs. A) Ptgs2 expression in COCs collected at 10 h post-hCG relative to Rpl19 expression (data taken

from Figure 4.6; n = 4 per genotype). B) Total concentration of PGE2/COC produced from 1 h incubation of 10 h post-hCG COCs collected from PR+/- (n = 6) and PRKO (n = 7) mice. C) PGE2 detected in the media and matrix fractions from samples in B). D) Ratio of PGE2 in medium:matrix from PR+/- and PRKO COCs. All bars are mean + SE. Different letters denote significant difference (P<0.05) by: Student’s t-test on log-transformed data (A,B); two-way repeated measures ANOVA on log-transformed data (C); Student’s t-test on square-root transformed data (D). ns = not significant. Lisa Akison 2012 194

6.3.7 Mitochondrial membrane potential is altered in PRKO oocytes

Mitochondrial bioenergetic activities in the oocyte have been linked to oocyte viability and developmental competence (see [Van Blerkom, 2011] for review). To determine whether mitochondrial function in PRKO oocytes is altered, mitochondrial membrane potential (m) was compared in PRKO and PR+/- denuded oocytes, as assessed by JC-1 staining; where red staining is indicative of high m and green staining of low m. The PR+/- oocytes showed red fluorescent staining mainly concentrated in the pericortical region, while green fluorescent staining predominated in the deeper cytoplasm (Figure 6.10). This is consistent with previous reports of zonation of high and low potential mitochondria in the oocyte [Van Blerkom et al., 2002]. However, in PRKO oocytes, there was a statistically significant increase in red staining in the centre of the oocytes compared to PR+/- oocytes, which indicates a higher m in these mitochondria (Figure 6.10). The distribution of green fluorescent staining across the PRKO oocyte was consistent with that seen in PR+/- oocytes (Figure 6.10). Therefore, the distribution of mitochondria with high m was altered in the PRKO oocytes.

6.4 Discussion

Ovulation depends on breaching the follicle and ovarian wall to release the oocyte, yet despite considerable investigation, no specific mechanism for degrading the ovarian wall structure has been identified. Our working model is that oocyte release is actively mediated by the expanded COC [Russell and Robker, 2007]. In this chapter, I clearly demonstrate that the COC transitions to an adhesive, migratory and invasive cell phenotype in response to an ovulatory dose of hCG, and thus may contribute to the process of release of the COC from the follicle.

The adhesive, migratory and invasive phenotype of the periovulatory COC

In response to the LH surge, expanding COCs rapidly increased adhesive capacity to extracellular matrix proteins abundant in the ovarian follicle wall. The results demonstrate a propensity for preovulatory COCs to adhere to collagens, fibronectin and the laminin-rich basement membrane analogue Geltrex. This increase in adhesive ability coincides temporally with the thinning of the follicular apex which is well described [Espey, 1999] and proposed to involve smooth muscle contraction induced by endothelins [Bridges et al., 2010] and increased vascular permeability causing an influx of serum and increased intrafollicular pressure [Matousek et al., 2001]. Collagens, fibronectin and laminin are abundant in the antral follicle wall of mouse ovaries [Berkholtz et al., 2006a]. Thinning of the apical granulosa layers may expose the underlying ECM and simultaneous increased adhesive

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0 0 0 10 20 30 40 50 60 70 0 10 20 30 40 50 60 70 Distance (um) Distance (um)

Figure 6.10 Oocyte mitochondrial membrane potential is altered in PRKO COCs. Mitochondrial membrane potential (m) was measured using JC-1 staining. COCs were isolated from PRKO and PR+/- ovaries at 10 h post hCG and denuded before incubating in 6 μM JC-1 for 15 mins. A) Representative images of PRKO and PR+/- denuded oocytes stained with JC-1 and imaged using the green and/or red fluorescence channels. PRKO oocytes appear to have more red staining in the centre of the oocyte than PR+/- oocytes. B) Analysis of fluorescence intensity across the oocyte using AnalySIS LS Professional software. Top panels show mean ± SE intensity for red and green channels separately for PR+/- and PRKO oocytes. Bottom panels compare red and green channels across genotypes. Red channels were significantly different across genotype by mixed model two-way ANOVA (P<0.0001).

Lisa Akison 2012 196 capacity of the COC would result in re-localisation of the COC to the apical region. Immediately post- ovulation, COCs showed significantly reduced adhesion to ECM, suggesting that cell modifications during rupture or exposure to the oviduct environment rapidly down regulates COC adhesion as a rapid response to release from the follicle. The mechanism driving this transient adhesive ability of the periovulatory COC is unknown, but presumably involves the action of adhesion molecules such as integrins. Integrins are obligate heterodimers composed of  and β subunits that regulate cell-cell, cell- matrix and cell-pathogen interactions by binding to distinct but often overlapping combinations of ligands (see [Springer and Wang, 2004] for review). Integrin ligands include collagen, laminin, fibronectin, fibrinogen, vitronectin, thrombospondin and osteopontin, many of which are present in the follicle wall during the periovulatory period (see Chapter 1). In vertebrates, there are 19  subunits and 8 β subunits that form at least 25 β heterodimers; thus integrins are arguably the most functionally and structurally diverse family of cell adhesion molecules. They play pivotal roles in a broad range of biological processes such as inflammation, tissue morphogenesis, cell motility, wound healing and cell growth and differentiation [Curley et al., 1999; Hynes, 1992] and their dysregulation is associated with pathologies such as autoimmunity, vascular disease, tumour growth and cancer metastasis [Stupack, 2007]. Shifts in the expression profile of integrin heterodimers, commonly known as the ‘integrin switch’, are a typical feature of adhesion dynamics and cell motility during these conditions of increased cell migration [Truong and Danen, 2009]. For example, fibronectin (FN) can be recognised by 9 different integrin heterodimers and shifts in cell-matrix adhesions to this ECM occur via changes in the expression of FN-binding integrins, providing a shift from a stationary to a motile state in the cell [Truong and Danen, 2009]. Therefore, investigation of the expression of various integrins in the COC throughout the periovulatory window is the next logical step in characterising the observed adhesive phenotype. Studies to date have focussed on integrin expression in granulosa and theca cells during follicle growth and corpus luteum formation [Burns et al., 2002; Fujiwara et al., 1998; Fujiwara et al., 1996; Honda et al., 1995; Honda et al., 1997; Yamada et al., 1999] or in cumulus cells around the time of fertilisation [Tamba et al., 2008]. However, very little is known about integrin expression in the preovulatory COC. Only one study has shown that LH-induced cumulus expansion of bovine COCs in vitro was concomitant with increased expression of integrins 6 and β1 [Sutovsky et al., 1995]. Interestingly, I did not find any evidence that the expression of integrins is regulated by PGR in granulosa cells or COCs. However, several other genes involved in integrin-mediated cell adhesion and migration were found to be dysregulated in PRKO mice and will be discussed below.

Ovulatory hCG also induced transient migratory and invasive capacity specifically in COCs that peaks in COCs within follicles at 12 h post-hCG, the time when ovulation also peaks (see Chapter 2, Figure 2.2). This transition in cumulus cells from a stratified epithelium to mesenchymal-like phenotype is

Lisa Akison 2012 197 consistent with the known effects on cell behaviour of hyaluronan and versican-rich extracellular matrix environments [Evanko et al., 1999; Kern et al., 2006; Shukla et al., 2010]. The resulting capacity to invade through an ECM barrier and migrate may facilitate breaching of the follicle apex thus the COC may orchestrate its own release from the follicle.

Again, the mechanism underlying the invasive and migratory phenotype of the periovulatory COC is currently unknown. However, adhesion via integrins plays a pivotal role in cell migratory mechanisms. While there was no evidence of PGR-regulation of integrins in ovarian cells from the microarray assays several genes involved in integrin-mediated processes were dysregulated in PRKO cells. These included 9 genes from the Ras GTPase superfamily that control integrin function (i.e. RAB11 family interacting protein 1 (class I) (Rab11fip1); related RAS viral (r-ras) oncogene homolog 2 (Rras2); RAS- like, family 11, member B (Rasl11b); RAS protein-specific guanine nucleotide-releasing factor 2 (Rasgrf2); RAS and EF hand domain containing (Rasef); RAS protein activator like 1 (GAP1 like) (Rasal1); Rho guanine nucleotide exchange factor (GEF) 17 (Arhgef17); Rho GTPase activating protein 6 (Arhgap6); Rho family GTPase 3 (Rnd3)). In particular, Rab11fip1 was significantly down-regulated with a high magnitude fold-change in both PRKO COC and granulosa cells. Rab GTPases, including Rab11fip1, are involved in cell surface receptor trafficking and recycling from inside the cell to the plasma membrane [Hales et al., 2001; Hales et al., 2002]. This includes the recycling of integrins to promote cell invasive migration [Jones et al., 2006a; Rainero et al., 2012; Subramani and Alahari, 2010]. Rho- and Rac-GTPases also interact with the hyaluronan receptor, CD44, which is expressed in cumulus cells in response to the LH surge [Alvino, 2010; Okada et al., 2003; Rodriguez Hurtado et al., 2011; Schoenfelder and Einspanier, 2003; Yokoo et al., 2002]. Rho/Rac GTPases are involved in the cytoskeletal remodelling required for activating cellular movement and invasion, as has been extensively described in tumour metastasis and progression (see [Bourguignon, 2008] for review). However, expression of many of the Ras GTPase superfamily molecules has not been examined in detail in the mammalian ovary and their roles are still being elucidated. Only relatively recently, RAS (KRAS) has been identified in mouse granulosa cells and corpora lutea and mutant mouse models implicate KRAS in follicle growth, granulosa cell proliferation and differentiation, and ovarian cancers (see [Fan and Richards, 2010] for review). Preliminary data from our laboratory indicates that RhoA mRNA is upregulated in both granulosa cells and COCs from mice treated with hCG during the periovulatory period [Alvino, 2010]. However, another study indicates that Rho/ROCK signalling needs to be down-regulated in the postovulatory COC to allow successful fertilisation [Yodoi et al., 2009].

Also down-regulated in the PRKO granulosa cells were the cytoskeletal genes alpha actinin 4 (Actn4), vinculin (Vcl) and zyxin (Zyx) (see Chapter 5) which may also have down-stream affects on integrin- mediated COC adhesion and migration. ECM, integrins and the cell cytoskeleton interact at focal

Lisa Akison 2012 198 adhesion sites and these proteins are recruited to these sites. Interestingly, Zyx has recently been shown to be regulated by TGFβ1 in lung cancer cells and is involved in cell motility via its interaction with integrin 5β1 [Mise et al., 2012]. Tgfβ1 was also found to be dysregulated in the PRKO ovary from the Taqman Immune Array in Chapter 4. Further, the SNARE complex, of which the PGR- regulated gene SNAP25 is a component, has also been connected to RhoA-regulated focal adhesion formation and trafficking of integrin 5β1 in CHO cells [Gonon et al., 2005; Skalski and Coppolino, 2005].

A recent study also implicates calpain proteases in mediating cumulus cell movement during expansion of the COC [Kawashima et al., 2012]. In particular, calpain 2 was found to be expressed in cumulus cells and its activity was rapidly induced in response to hCG via EGF-like factors in mice. Inhibition of calpain activity in vitro blocked the detachment and movement of cumulus cells and impaired COC expansion. Calpain activity was associated with proteolytic degradation of paxillin and talin, two other proteins associated with the focal adhesion complexes mentioned above.

Therefore, there is compelling evidence to suggest that integrin signalling may be an important molecular driver of the observed adhesive, migratory and invasive phenotype of periovulatory COCs. However, further work is required to identify the specific integrin dimers and their ECM binding partners involved.

The large number of genes dysregulated in PRKO granulosa cells and COCs that are associated with the processes of cell adhesion, migration and invasion in other systems suggests that these processes may be defective in the PRKO ovulatory COC. One of these genes, the protease ADAMTS1, has previously been shown to be a PGR-regulated gene in the ovary [Robker et al., 2000] as well as specifically in COCs [Russell et al., 2003b]. ADAMTS1 is a key mediator of ovulation [Brown et al., 2010a; Brown et al., 2006; Mittaz et al., 2004; Robker et al., 2000] and active ADAMTS1 is localised mainly in the COC matrix of ovulating follicles where it cleaves versican [Russell et al., 2003b]. Collagens found in the ovarian wall are substrates for ADAMTS1 [Rehn et al., 2007; Shindo et al., 2000] raising the possibility that this protease in the COC contributes to degradation of the tensile strength of the ovarian wall to facilitate COC release. Since ADAMTS1 is known to promote invasion of cancer cells [Ricciardelli et al., 2011], it could play a similar role in the invasive migration of cumulus cells. Further, other genes such as Cxcr4, Sphk1, Zbtb16/Plzf, Cd34, Rgmb, Adam8, Epas1/Hif2, Egfr, Efnb2, Runx2 and the genes associated with integrin-mediated signaling mentioned above, have all been associated with cell adhesion, migration and invasion and were all dysregulated in PRKO cells. Interestingly, Efnb2 and Runx2 have previously been found to be upregulated in the highly invasive breast cancer cell line, MDA-MB-231, relative to the non-invasive breast cancer cell line, MCF7

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[Nagaraja et al., 2005], cell lines that I have also used to compare against the invasive capabilities of preovulatory COCs.

However, despite evidence for dysregulation of adhesion and migration related genes, COCs from PRKOs displayed the same migratory and invasive capabilities as PR+/- COCs. In addition, the adhesive capacity of PRKO COCs to collagen I was not significantly different to that recorded for PR+/- COCs. It may be that the in vitro method for assessment of these properties was not sensitive enough or failed to recapitulate relevant in vivo conditions needed for differences that may occur in COC migration/invasion to be detected. Growth factors provided by the serum, which was used as the chemoattractant in the lower chamber, may have overridden any deficiencies present in PRKO COCs in vivo. Although an experiment was done to compare the presence or absence of serum in the collection media and its potential effects on migration, serum was eventually present in both of these experiments in the lower chamber. Interestingly, the magnitude of the migratory capacity of the COCs collected in the absence of serum was greater than that for COCs collected with serum in the collection media (Figure 6.6). An alternative approach may be to compare cumulus cell migration from PRKO and PR+/- COCs using a 3-dimensional hydrogel system of varying stiffness and susceptibilities to MMP degradation [Ehrbar et al., 2011]. In our xCELLigence real-time migration system, although no statistically significant differences were found, there was a trend for increased adhesion in the PRKO COCs (Figure 6.7). However, there was large variability between mice for this genotype and therefore the t-test was under-powered, as were the t-tests for comparison of migration and invasion between genotypes. Intriguingly, histological sections of entrapped COCs in PRKO follicles at 14 h post-hCG (Chapter 3) suggested that COCs occupied a more basal position in the follicle, rather than near the apical region which is the site of follicle rupture in normal mice. It was suggested in Chapter 3 that this may be due to a decreased propensity of PRKO COCs to adhere to ECM proteins exposed during follicle wall thinning. However, increased propensity to remain adherent to the basal granulosa cell layers is equally able to explain this observation. The use of other chemoattractants, more relevant to those potentially present in vivo, remain to be explored. Due to its intimate association with the ovary, particularly the fimbriated infundibulum around the time of ovulation [Piňon, 2002], it is possible that the oviduct provides a source of chemical signals to the COC to influence its directed passage through the apical region of the follicle. However, preliminary tests using oviduct conditioned media and the ligand for CXCR4, CXCL12, which was found to be present in the oviduct at the same time that the receptor is up-regulated in the COC, did not substantiate this (see Appendix 5).

A dramatic decline in both adhesion and migratory ability of COCs occurred immediately post-ovulation, despite no apparent change in the morphology of COCs isolated from either follicles or the oviduct 12 h post-hCG (see Chapter 2). The mechanism for such a rapid loss of adhesive and migratory capacity is

Lisa Akison 2012 200 currently unknown. However, it would suggest that adhesion and invasive migration through collagen I are important in the preovulatory phase but potentially detrimental to oocyte transfer through the oviduct. This is consistent with the fact that ciliated oviductal cells are known to actively mediate transport of COCs and sperm and regulate their interaction (see Chapter 1 and [Pulkkinen, 1995]). Importantly, COCs harvested from preovulatory follicles did not lose migratory ability under in vitro assay conditions even after 24 or more hours of culture (data not shown), suggesting that exposure to the oviduct after ovulation may be required for the rapid down regulation of COC migration.

Reduced matrix integrity of the PRKO COC?

Prostaglandin E2 (PGE2) is critical in normal ovarian physiology, with essential roles in oocyte maturation, cumulus expansion and ovulation [Davis et al., 1999; Hizaki et al., 1999; Lim et al., 1997;

Shimada et al., 2006b; Takahashi et al., 2006]. In Chapter 4, the gene responsible for PGE2 synthesis, Ptgs2, was found to be reduced as much as 5-fold in PRKO ovaries compared to PR+/- ovaries at 10 h post-hCG (Figures 4.3 and 4.4). However, regulation of PTGS2 by PGR is hotly debated in the literature (see Section 1.5.5.2 and Chapter 4), with discrepancies between in vitro and in vivo studies, but may occur indirectly via PPARγ [Kim et al., 2008] and/or RUNX1 [Liu et al., 2009a]. Further exploration of PTGS2 in granulosa cells and COCs isolated from PRKO and PR+/- mice revealed some evidence that Ptgs2 mRNA was reduced in PRKO COCs at 10 h post-hCG but not at 4 h or 8 h post- hCG (Figure 4.5 and Figure 6.9A). However, immunohistochemical staining of PTGS2 protein in ovarian sections from ovaries collected at 10 h post-hCG was comparable between PRKO and PR+/- mice (Figure 4.6). Although these results are somewhat conflicting, it suggests that Ptgs2 expression is perturbed in PRKO ovaries, indicating that PGE2 production may also be affected. Given the importance of PGE2 for a correctly assembled cumulus matrix in the COC, PGE2 production was measured in PRKO and PR+/- COCs collected 2 h prior to ovulation and cultured for 1 h. Intriguingly, despite the results in Chapter 4 and elsewhere suggesting that PTGS2 expression is reduced in PRKO ovaries, the overall production of PGE2 in PRKO COCs in vitro was not statistically different to that of PR+/- COCs, and if anything, tended to be higher in PRKO COCs. However, a greater proportion of

PGE2 produced in the PRKO COC was lost to the surrounding media compared to the PR+/- COCs. The functional significance of this to the maintenance of normal matrix structure may be negligible, however, given that the amount of PGE2 still remaining in the matrix of PRKO COCs was similar to that in PR+/- COCs. This may suggest some deficiency in the PRKO COC matrix to restrain the movement of PGE2 out of the complex and into the surrounding media.

Measurement of PGE2 production and retention in the COC, as a bioassay of matrix integrity, was recently reported in a comparison of in vivo and in vitro matured (IVM) COCs [Dunning et al., 2012]. In this study, IVM COCs had lower expression of Ptgs2, lower overall production of PGE2, and greater Lisa Akison 2012 201 loss of PGE2 to the surrounding media, proportional to the total amount produced. This was in addition to other perturbations in the filtration properties of IVM COCs, namely diffusion of exogenously supplied, fluorescently labelled, dextrans and hydrophilic (glucose) and hydrophobic (cholesterol) metabolites. As per IVM COCs, our results also showed relatively higher amounts of endogenously produced PGE2 in the surrounding media of PRKO COCs. Measurement of the diffusion of exogenous metabolites in PRKO relative to PR+/- COCs, as was performed in this study comparing in vivo and IVM COCs, would be informative to further clarify the matrix integrity and diffusion properties of PRKO COCs.

Other indicators of potentially defective matrix integrity in PRKO COCs are the reduced expression of genes associated with cumulus matrix formation in these mice. ADAMTS1 is an obvious example due to its role in cleaving versican, the hyaluronan-binding proteoglycan found in COC matrix [Russell et al., 2003b]. Indeed, versican itself was found to be down-regulated in granulosa cells of PRKO mice in Chapter 5 and its cleavage has previously been found to be reduced in PRKO COCs [Russell et al., 2003b]. Results in Chapters 4 and 5 also revealed that Il6 is down-regulated in PRKO ovaries and granulosa cells respectively, with this cytokine previously identified as playing a role in inducing COC expansion [Liu et al., 2009b] and previously identified as a PGR-regulated gene in granulosa cells via PPARγ [Kim et al., 2008]. Also, the EGF-like factors Areg and Ereg, which are critical for COC expansion, have previously been shown to be PGR-regulated in the COC [Shimada et al., 2006b]. In addition, others have indicated that the matrix genes Tnfaip6/Tsg6, Ptx3 and Has2 are down-regulated in ovaries from PRKO mice compared to PRWT mice [Kim et al., 2009a], although no data was shown. Therefore, quantification of both mRNA expression of matrix-forming genes and specific matrix proteins in PRKO COCs is required to further clarify the molecular integrity of PRKO cumulus matrix.

Increased mitochondrial membrane potential in the PRKO COC

The influence of P4/PGR on oocyte developmental competence is an issue of contention in the literature (see Section 1.5.4.2 for more details). Although there are no doubt species differences due to differing expression patterns of PGR in cumulus cells, within rodents alone, there is conflicting evidence of a role for PGR. However, only one study has reported that oocytes from PRKO mice can be successfully matured and fertilised in vitro, resulting in normal blastocyst development [Robker and Richards, 2000]. Uterine transfer of these embryos into wild-type mice also resulted in live pups. However, the issue of whether maturation of oocytes in PRKO mice results in oocytes with reduced developmental competence and, consequently, reduced blastocyst formation, has not been addressed. While experiments comparing in vitro fertilisation of oocytes matured in PRKO mice with those matured in PRWT or PR+/- mice are still required, I used a different approach for examining this issue in this chapter. Mitochondrial membrane potential (m) was measured in oocytes from PRKO and PR+/- Lisa Akison 2012 202 mice after in vivo maturation in response to hCG. This was done because perturbations in mitochondrial bioenergetic activities in the oocyte have recently been linked to changes in oocyte developmental competence [Fernandes et al., 2012; Van Blerkom, 2011]. A reduction in m, particularly in the pericortical region, is typical in other studies examining perturbations in mitochondrial function in the oocyte [Demant et al., 2012; Fernandes et al., 2012; Ou et al., 2012; Wu et al., 2010; Wu et al., 2012; Zhao et al., 2011]. Interestingly, I found the converse to be true in PRKO oocytes, with increased m, particularly in the centre of the oocyte, compared to PR+/- oocytes. The implications for this increase on oocyte developmental competence in PRKO oocytes remains to be tested.

As discussed in Chapter 1, the oviduct is inextricably linked to the ovary during the periovulatory period, both physically and functionally. It plays a well-documented role in facilitating oocyte pick-up at ovulation and is critical for the next phase of oocyte transport to the site of fertilisation and early embryo transport to the uterus. It may also produce critical biochemical stimuli to provide directionality to the ovulating COC and/or induce the adhesive, migratory and invasive phenotype observed in the periovulatory COC. The role of ovarian hormones, including progesterone, in regulating oviductal function has been discussed in Chapter 1 but the direct role of PGR has not been adequately addressed. Therefore, the next chapter will examine the role of PGR in regulating oviductal structure and function during the periovulatory period.

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Chapter 7 – PGR regulation of oviduct structure and function

7.1 Introduction

The oviducts are active and highly specialised organs that are critical in bi-directional transport of gametes, as well as nourishment and precisely timed movement of the developing embryo to the uterus (see Section 1.3 for more detail). They are the first point of contact for the newly ovulated COC, with ciliated cells assisting in the pick-up and transport of the expanded COC to the site of fertilisation [Talbot et al., 1999]. Secretory cells contribute a multitude of products to oviductal fluid which facilitates transport, fertilisation and early embryo development (see Table 1.1). Contraction by smooth muscle cells in the oviductal wall also regulate transport of the embryo [Croxatto, 2002; Hunter, 2011]. All of these processes are regulated by ovarian hormones, and thus the oviducts and ovaries are inextricably linked, both structurally and functionally.

The overall aim of the studies described in this chapter was to examine the role that PGR may play in regulating oviductal structure and function. Ovarian steroid hormones, including progesterone, impact oviduct ciliary function, regulate muscular and nerve function, and control the volume and composition of fluids in the lumen (see [Hunter, 2011] for review and Chapter 1). Presumably, PGR is important in the oviduct at this time, as both mRNA and protein are highly expressed (as shown in Figures 1.12 and 1.15) and progesterone production by the ovary increases dramatically in the hours leading up to ovulation, surpassing the levels of oestradiol (see [Szoltys et al., 1994] for quantification of hormone levels in naturally cycling and super-ovulated rats). However, whether PGR isoforms are induced by the LH surge in the oviduct remains to be clarified, as there are conflicting reports in the literature, both within and between species (see also Section 1.6.1 for more details). Constitutive expression of PGR in the oviduct across the oestrous cycle has been suggested by a lacZ reporter study in mice ([Ismail et al., 2002] and see also Figure 1.12) and has also been reported in human Fallopian tubes [Amso et al., 1994] and in the bovine oviduct [Saruhan et al., 2011]. However, other studies in the mouse [Shao et al., 2006; Teilmann et al., 2006], human [Pollow et al., 1981] and bovine [Kenngott et al., 2011; Ulbrich et al., 2003; Valle et al., 2007] found variable expression in response to hCG or different stages of the cycle. Therefore, the first aim was to determine the expression profile of PGR mRNA in mouse oviducts in response to the LH surge using real-time PCR.

Much is known about PGR regulation of mammary gland and uterine structure, function and gene expression from previous studies in PRKO mice [Cheon et al., 2002; Cloke et al., 2008; Conneely et al.,

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2003; Fernandez-Valdivia et al., 2005; Ismail et al., 2002; Jeong et al., 2005; Lydon et al., 1995]. In addition, the role of PGR in regulation of ovarian structure, function and gene expression has been examined in the preceding chapters of this thesis, as well as by others [Lydon et al., 1995; Robker et al., 2000]. However, investigation of the oviducts from PRKO mice has been relatively overlooked. Therefore, the second aim was to compare the histology of PR+/- and PRKO oviducts during the periovulatory period, to determine if there were any obvious structural defects in the PRKO oviducts.

As PGR is a nuclear transcription factor involved in gene regulation, the third aim was to identify PGR- regulated genes in the oviduct using a microarray study and to thus determine potential regulation of oviductal function. To date, no studies have examined gene expression in the oviduct during the periovulatory period, a time when the oviduct is preparing to receive the newly-ovulated COC. Previous microarray studies of oviduct have examined endothelin-regulated signalling cascades in mouse oviduct following endothelin inhibition [Jeoung et al., 2010]; sperm-induced modification of mouse oviduct genes 6 h post-mating [Fazeli et al., 2004]; sperm- and oocyte-induced modification of pig oviduct genes 24 h after ovulation and artificial insemination [Georgiou et al., 2007]; and effect of mating on E2-induced gene expression profiles in the rat oviduct [Parada-Bustamante et al., 2009]. Several target genes identified from the current microarray study were validated and examined for induction by LH using quantitative real-time PCR. Note that a rigorous comparison of gene expression between PRKO and heterozygous oviducts cannot be made during the normal postovulatory period due to the absence of ovulated COCs in PRKO oviducts versus the presence of ovulated COCs in heterozygous oviducts.

7.2 Materials & Methods

7.2.1 Animals and tissue collection

PRKO and PR+/- mice were treated with eCG and hCG to stimulate follicle growth and ovulation as described in Section 2.1.2. For experiments examining gene expression, whole oviducts were collected from 5 mice of each genotype at 48 h eCG and eCG + 4 h, 8 h and 10 h post-hCG. Tissues were snap- frozen in liquid nitrogen then stored at -80ºC. Whole ovaries with bursa and oviducts attached or oviducts alone were also collected from PRKO and PR+/- mice at 44 h eCG + 8 h, 10 h, 12 h, or 14 h post-hCG for histology.

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7.2.2 Histology

Oviducts from 4 animals per genotype were examined. All tissues were fixed in 4% paraformaldehyde for 24-48 h at 4C and then stored in 70% EtOH at 4C. Oviduct tissue was processed, sectioned and 8-10 sections per animal were stained with H & E as detailed in Chapter 2. Images of sections were captured at 40X magnification using the NanoZoomer HT Digital Pathology System (Hamamatsu Photonics K.K., Japan) and one representative image from each animal was compiled for comparison of gross histology. Sections were also examined at 60X using an Olympus BX51 microscope and one representative image at each time point for each genotype was captured using a SPOT RT-SE digital camera (Scitech Pty. Ltd., Melbourne, Vic, Australia) to show greater detail of the cells in the luminal epithelium. Where possible, images were taken from the distal oviduct (infundibulum and ampulla) which has a highly folded mucosal layer and is adjacent to the ovary, rather than from the caudal section (isthmus) which has a much narrower lumen and less plicate mucosal layer (see Chapter 1).

7.2.3 RNA extraction and quality control

RNA was extracted in Tri Reagent and DNase-treated before use (see Section 2.3 for more details). RNA concentration and quality was assessed using a Nanodrop ND-1000 Spectrophotometer (Biolab Ltd, Clayton Vic, Australia) and preliminary RT-PCR analysis of Rpl19 expression as described in Section 2.3. Sample genotypes were verified as per Section 2.3, before pooling for the microarray assay.

7.2.4 Microarray sample preparation, array hybridisation, scanning and analysis

Once quality and genotype were confirmed, RNA from 3 animals collected at 44 h eCG + 8 h post-hCG was pooled for each sample, with 5 replicates for each genotype (see Appendix 2 for details of microarray pooled samples). Approximately 100 ng total RNA from each sample was sent to the Adelaide Microarray Centre (AMC) for analysis. RNA integrity (RIN) was quantified for each sample using an Agilent Bioanalyzer (Agilent Technologies, Santa Clara, USA; Appendix 2) and was considered acceptable for microarray analysis at a minimum threshold of 7-7.5 (M. Van der Hoek, AMC, pers. comm.).

Sample preparation was performed by AMC using Affymetrix GeneChip® Kits (Affymetrix, Santa Clara, USA) according to the manufacturer’s instructions. A brief description of the protocol is given in Section 2.5. Following biotinylation, samples were hybridised overnight to Affymetrix GeneChip® Mouse Gene Lisa Akison 2012 206

1.0 ST Arrays (Affymetrix, Santa Clara, USA). The arrays were washed, stained using a fluorescently- labelled antibody and scanned using a high resolution scanner (Affymetrix GeneChip Scanner 3000 7G Plus).

Microarray data were analysed by the AMC using Partek® Genomics Suite™ software (Partek Incorporated, St Louis, MO, USA). See Section 2.5.2 for more details. Volcano Plots were also created using all genes found on the array to highlight genes of interest with large magnitude fold changes and high statistical significance ( see [Cui and Churchill, 2003] and Section 2.5.2 for more details). Data sets containing genes that were differentially expressed between the two genotypes were imported into the Ingenuity Pathway Analysis software (IPA; Ingenuity Systems, Redwood City, CA, USA) to identify significant gene associations with biological functions.

7.2.5 Real-time PCR

RNA isolated from oviducts collected from for the time course, as well as a sub-sample of pooled RNA used in the microarray study, was reverse-transcribed to synthesise cDNA as per Section 2.4. Briefly, 300 ng RNA was included per 20 μl reaction. QuantiTect Primer Assays (Qiagen, Pty. Ltd., Doncaster, Vic, AU) were used for validation of specific target genes and for the housekeeping gene, Rpl19 (see Table 2.2 for details). Primers for Pgr were designed in-house to specifically target the region deleted in the PRKO mice (see Figure 2.1) and confirmed ablation of the gene in samples of this genotype (primer sequences given in Table 2.2). Thus, only expression in PR+/- samples is shown. Real-time PCR was performed for each sample as described in Section 2.4. Briefly, each reaction included 10 ng of cDNA in a 20 μl reaction using Power SYBRGreen Master Mix (Applied Biosystems, Mulgrave, Vic, AU) on a Corbett Rotor-Gene 6000 Real-time Rotary Analyser (Corbett Research Pty Ltd, Sydney, NSW, AU). Samples were analysed over 3 runs, with samples from each time point included on each run. A sample of RNA from 6 pooled C57Bl/6 oviducts collected at 10 h post-hCG was used as the calibrator and was included on all runs. Each gene (including the housekeeper, Rpl19) was run on separate days on the same cDNA. However, Rpl19 was included for the calibrator on every PCR run to check for between-run variation. The same Rotorgene machine was used for all reactions.

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7.3 Results

7.3.1 PGR mRNA expression in the oviduct during the periovulatory period

There are conflicting reports of PGR mRNA expression in the oviduct during the periovulatory period. Therefore, I quantified PGR mRNA expression in PR+/- oviducts collected at 48 h post eCG and 44 h eCG + 4 h, 8 h and 10 h post hCG using real-time PCR. There was no statistically significant difference in the expression of PGR mRNA across this time course, although there was a trend for decreased expression by 10 h post-hCG (Figure 7.1). I also confirmed a lack of PGR mRNA expression in the PRKO oviducts (data not shown).

7.3.2 Oviductal histology

Gross histology revealed no discernible differences between the knockout and heterozygous oviducts in terms of the degree of epithelial layer folding or thickness of the underlying muscle wall layers at any of the time points preceding ovulation (Figure 7.2). Ovulated COCs were only observed in the lumen of PR+/- oviducts at 14 h post-hCG (Figure 7.2D). At higher magnification, the luminal epithelial cells of the PRKO oviducts looked normal, with ciliated cells and secretory ‘peg’ cells visible at each time point (Figure 7.3). Therefore, there were no obvious structural abnormalities in the PRKO oviducts. The next section examines potential gene networks disrupted in the PRKO oviducts using microarray.

7.3.3 Oviduct microarray

Ten Affymetrix Mouse Gene 1.0 ST Arrays were used to investigate transcriptional changes in whole oviducts isolated from PRKO and PR+/- mice at 8 h post-hCG. A PCA plot revealed that the PRKO samples were tightly clustered based on their gene expression profiles and were in fact more homogenous within this genotype group than for any other tissue/cell type examined in this thesis (Figure 7.4; refer to Figures 5.1 and 6.4 for comparison). However, the PR+/- samples were the most variable compared to other groups (Figure 7.4 and see Figures 5.1 and 6.4 for comparison). There was a profound effect of the PGR null genotype in the oviduct, with 1003 genes differentially expressed in the PRKO compared to PR+/- (P<0.05; Figure 7.5) and 265 genes at the P<0.01 level of significance (see Appendix 6 for the entire list of differentially expressed genes at this significance level). The vast majority of these genes were down-regulated in PRKO mice (83% at P<0.05 and 93% at P<0.01).

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Relative Fold Change (Mean + SE) (Mean Change Relative Fold 0.0 48h eCG 4h 8h 10h post-hCG Figure 7.1 Pgr mRNA is stably expressed in the oviduct during the periovulatory period. Oviductal tissues were collected over a periovulatory time course from mice injected with eCG and hCG. n = 5 animals for each time point. Only results from PR+/- mice are shown. All PRKO samples tested showed no expression of PGR (n = 5 animals). One- way ANOVA did not detect any statistically different time points, although there is a trend (P = 0.090) for decreased expression at 10 h post-hCG.

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Figure 7.2 A)

PR+/- 8 h post-hCG oviducts PRKO 8 h post-hCG oviducts

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Figure 7.2 B)

PR+/- 10 h post-hCG oviducts PRKO 10 h post-hCG oviducts

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Figure 7.2 C)

PR+/- 12 h post-hCG oviducts PRKO 12 h post-hCG oviducts

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Figure 7.2 D)

PR+/- 14 h post-hCG oviducts PRKO 14 h post-hCG oviducts

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Figure 7.2 Oviductal histology appears normal in PRKO mice. Photomicrographs of oviduct sections stained with haematoxylin and eosin (H & E) are shown at A) 8 h, B) 10 h, C) 12 h and D) 14 h post-hCG. Numbers denote individual animal identification numbers. One representative section is shown per animal. All sections are shown at 20X magnification unless specified otherwise. All PR+/- mice are shown on the left and PRKO mice on the right for each figure. Arrows indicate ovulated COCs.

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PR+/- oviducts PRKO oviducts Figure 7.3 A)

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Figure 7.3 Cells of the luminal epithelium appear normal in PRKO oviducts. Higher power (60X) photomicrographs of oviduct sections stained with haematoxylin and eosin (H & E) are shown at A) 8 h or 10 h post-hCG; B) 12 h or 14 h post-hCG. Numbers denote individual animal identification numbers. One representative section is shown per time point for each genotype. All PR+/- mice are shown on the left and PRKO mice on the right for each figure. Arrows indicate ciliated cells and arrow heads indicate secretory ‘peg’ cells.

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Figure 7.4 Principle Components Analysis plots for oviduct microarray samples. Red spheres are PR+/- samples and blue spheres are PRKO samples. Top view has principal components 1 and 2 shown for the X and Y axes respectively. Bottom view shows the chart rotated anti-clockwise to show the clustering of samples for each treatment.

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Figure 7.5 Volcano plot of oviduct microarray data. Samples collected at 8 h post-hCG. All 28,853 genes from the Affymetrix GeneChip® Mouse Gene 1.0 ST Array are plotted. The red dashed line represents P = 0.05 with points above the line having P<0.05 (i.e. significantly dysregulated in PRKO relative to PR+/- samples; n = 1003) and points below the line with P>0.05 (i.e. not significant). The green dashed line represents P = 0.01. The plot is centred around genes with a fold change of 1 (log2 1 = 0), with genes to the right of the vertical black line up-regulated in PRKO and genes to the left of the vertical black line down-regulated in PRKO compared with PR+/-. Genes with a fold change <2 are shown in grey. Some of the genes mentioned in the text are shown in green.

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The 50 most differentially expressed genes based on fold-change are shown in Table 7.1. Integrin alpha 8 (Itga8) was the most down-regulated gene in the PRKO oviducts at this time point (almost 10- fold difference to PR+/-, see also Figure 7.4). As per the granulosa cell and COC microarray (Chapter 5), the zinc finger protein, Zbtb16, was down-regulated in the absence of PGR (more than 4-fold difference), as were other genes previously identified to be regulated by PGR in the ovary (e.g. Adamts1, Hif3). Genes encoding collagens were highly down-regulated in PRKO oviducts (Col11a1, Col12a1), as well as the vasoactive peptide, endothelin 3 (Edn3) and the contractile protein, actin, gamma 2, smooth muscle, enteric (Actg2). Also the prostaglandin F receptor (Ptgfr) was down- regulated more than 2-fold. Only one gene was identified to be up-regulated in this group of highly dysregulated genes, an ion transporter from the solute carrier family, Slc26a4, also known as pendrin (2.69 fold change).

Ingenuity Pathway Analysis (IPA) was used to identify significant biological functions represented by the dysregulated genes in the PRKO oviducts which may be associated with oocyte/embryo transport. One group of differentially expressed genes was associated with the functions of ‘adhesion’, ‘attachment of cells’ or ‘binding of cells’ (n = 107; Table 7.2). Many of these genes were integrins (11 genes, highlighted in bold in Table 7.2).

IPA also identified 167 genes associated with the functions of ‘cell movement’, ‘chemotaxis’, ‘migration’ and/or ‘invasion’ (Table 7.3), as well as 39 genes associated with vasoconstriction and/or muscle contraction (Table 7.4).

Several genes that were highly down-regulated in PRKO oviducts from this microarray analysis were validated using quantitative real-time PCR. This was done using a time-course of oviductal tissues collected from both PR+/- and PRKO mice over the periovulatory period, as well as on a subset of the original RNA samples used in the microarray. These genes were selected as they represent several key processes/functions that may contribute to appropriate oocyte and/or embryo transport through the oviduct or facilitate fertilisation.

7.3.4 Validation of PGR target genes in the oviduct

Several genes dysregulated in the PRKO oviducts relative to the PR+/- oviducts, as identified from the microarray experiment, were validated for their regulation by PGR using real-time PCR. These genes were also examined across a periovulatory time course to determine if expression was up-regulated by LH in the normal, PR+/- oviducts.

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Table 7.1 50 most differentially expressed genes in PRKO versus PR+/- oviducts. List created from genes with highest fold-change values, which reflects genes of high biological significance. ** P<0.01; *** P≤0.001; **** P≤0.0001. Those in bold are discussed in the text. Gene Fold Symbol Gene Name Change P-value Itga8 integrin alpha 8 -9.87 **** Hmgcs2 3-hydroxy-3-methylglutaryl-Coenzyme A synthase 2 -5.81 *** Maob monoamine oxidase B -5.48 *** Gm106 gene model 106, (NCBI) -4.51 ** Zbtb16 zinc finger and BTB domain containing 16 -4.33 *** Dpep1 dipeptidase 1 (renal) -4.02 ** Cyp1b1 cytochrome P450, family 1, subfamily b, polypeptide 1 -3.88 ** Slc7a8 solute carrier family 7, member 8 -3.76 ** Rgs2 regulator of G-protein signaling 2 -3.64 *** Tcf23 transcription factor 23 -3.56 *** Des desmin -3.55 *** Arl4d ADP-ribosylation factor-like 4D -3.52 ** Edn3 endothelin 3 -3.43 ** Prlr prolactin receptor -3.39 ** Lrp2 low density lipoprotein receptor-related protein 2 -3.32 *** Adamts1 ADAM metallopeptidase with thrombospondin type 1 motif, 1 -3.18 *** Kcnj8 potassium inwardly-rectifying channel, subfamily J, member -3.15 *** Gria3 glutamate receptor, ionotropic, AMPA3 (alpha 3) -3.14 ** Cpxm2 carboxypeptidase X 2 (M14 family) -3.12 *** Ppap2b phosphatidic acid phosphatase type 2B -2.89 *** Postn periostin, osteoblast specific factor -2.86 ** Fxyd4 FXYD domain-containing ion transport regulator 4 -2.85 *** Errfi1 ERBB receptor feedback inhibitor 1 -2.78 *** Sult1a1 sulfotransferase family 1A, phenol-preferring, member 1 -2.71 *** Tmem204 transmembrane protein 204 -2.71 ** Slc26a4 solute carrier family 26, member 4 2.69 *** Fkbp5 FK506 binding protein 5 -2.68 ** Col12a1 collagen, type XII, alpha 1 -2.67 *** Abca8a ATP-binding cassette, sub-family A (ABC1), member 8a -2.66 ** Col11a1 collagen, type XI, alpha 1 -2.64 **** Penk1 preproenkephalin 1 -2.64 *** Figf c-fos induced growth factor -2.63 ** Rasd2 RASD family, member 2 -2.53 ** Actg2 actin, gamma 2, smooth muscle, enteric -2.52 **** Klf15 Kruppel-like factor 15 -2.51 *** Hif3a hypoxia inducible factor 3, alpha subunit -2.50 *** Mamdc2 MAM domain containing 2 -2.49 *** Mapk11 mitogen-activated protein kinase 11 -2.47 *** Sectm1a secreted and transmembrane 1A -2.46 ** Pdlim3 PDZ and LIM domain 3 -2.43 ** Kcnip2 Kv channel-interacting protein 2 -2.42 ** Wfdc15b WAP four-disulfide core domain 15B -2.40 ** Osr2 odd-skipped related 2 (Drosophila) -2.38 ** Pgr progesterone receptor -2.37 *** Galntl2 UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylg -2.36 *** Pde5a phosphodiesterase 5A, cGMP-specific -2.35 *** Rasl11b RAS-like, family 11, member B -2.34 ** Wfdc1 WAP four-disulfide core domain 1 -2.32 ** Slc41a3 solute carrier family 41, member 3 -2.31 *** Ptgfr prostaglandin F receptor -2.28 ** Lisa Akison 2012 221

Table 7.2 Differentially expressed genes in PRKO oviducts associated with the functions of adhesion, attachment or binding of cells. Fold change is PRKO relative to PR+/- oviducts; negative fold-change indicates down-regulation and positive fold-change indicates up-regulation. Integrins are highlighted in bold. * P<0.05; ** P<0.01; *** P≤0.001; **** P≤0.0001. See Appendix 4 for full gene names. Genes ordered by statistical significance then by fold-change.

Adhesion/attachment/binding of cells Fold P- Fold P- Fold P- Gene change value Gene change value Gene change value Itga8 -9.87 **** Pecam1 -1.36 ** Entpd1 -1.41 * Edn3 -3.43 *** Mfge8 -1.27 ** Snx1 -1.41 * Postn -2.86 *** C3 1.32 ** Cxcl16 1.41 * Penk -2.64 *** Cdh16 1.76 ** Dab2 -1.39 * Pgr -2.37 *** Oxtr 1.90 ** Nrp1 -1.39 * Itgbl1 -2.20 *** Itga1 -1.95 * Nppc 1.39 * Tgfb1 -2.13 *** Itgb3 -1.88 * Vcam1 1.39 * Boc -1.93 *** Cldn1 -1.72 * Lamc1 -1.38 * Mcam -1.90 *** Itga9 -1.64 * Ptp4a3 -1.38 * Igfbp7 -1.89 *** Cercam -1.48 * Prkca -1.36 * Nid1 -1.85 *** Calcrl -1.48 * Tspan5 -1.35 * Mras -1.56 *** Itga5 -1.44 * Fermt2 -1.34 * Prlr -3.39 ** Chst10 -1.44 * Pgf -1.33 * Figf -2.63 ** Axl -1.30 * Sparc -1.32 * Ctgf -2.18 ** Abl1 -1.27 * Vcl -1.31 * Cldn3 -2.13 ** Itgb1 -1.27 * Zyx -1.30 * Timp3 -2.03 ** Bcl2 -1.26 * Lyn -1.29 * Bgn -2.00 ** Actn4 -1.21 * Parva -1.29 * Lama4 -1.97 ** Cntn6 1.20 * Msn -1.28 * Ramp1 -1.97 ** Cntn3 1.32 * Emilin1 -1.27 * Rhob -1.85 ** Itgad 1.39 * Gcnt1 -1.25 * Itgb5 -1.81 ** Rras -1.62 * Zeb1 -1.25 * Gab2 -1.79 ** Lama2 -1.62 * Lrpap1 -1.25 * Plcb1 -1.77 ** Gpc3 -1.61 * Prtn3 1.25 * Pkd1 -1.66 ** Timp2 -1.58 * Dcc 1.25 * Cd34 -1.64 ** F2r -1.52 * Lims1 -1.20 * Hspg2 -1.62 ** Hs3st1 -1.51 * Prnp -1.19 * Ilk -1.62 ** Lox -1.50 * Faslg 1.18 * Tgfb1I1 -1.59 ** Mertk -1.48 * Ctnnd1 1.17 * S100a10 -1.58 ** Gas6 -1.47 * Dlg1 1.14 * Sema5a -1.54 ** Gsn -1.47 * Rab21 -1.12 * Cav1 -1.52 ** Serping1 -1.46 * Ush2a 1.12 * Itga7 -1.46 ** Tgm2 -1.44 * Ptprk 1.11 * Tfp1 -1.43 ** Ppap2a -1.43 * Il11 1.10 * Rasgrp2 -1.40 ** Scarf2 -1.43 *

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Table 7.3 Differentially expressed genes in PRKO oviducts associated with the functions of cell movement, migration, chemotaxis or invasion. Fold change is PRKO relative to PR+/- oviducts. * P<0.05; ** P<0.01; *** P≤0.001. See Appendix 4 for full gene names. Genes ordered by statistical significance then by fold-change.

Cell Movement/Migration/Chemotaxis/Invasion Fold P- Fold P- Fold P- Fold P- Gene change value Gene change value Gene change value Gene change value Zbtb16 -4.33 *** Col4a1 -1.43 ** Flna -1.47 * Vcl -1.31 * Ppap2b -2.89 *** Trib1 -1.43 ** Gas6 -1.47 * Wasf1 1.31 * Postn -2.86 *** Tfpi -1.43 ** Gsn -1.47 * Axl -1.3 * Errfi1 -2.78 *** Rasgrp2 -1.4 ** Ptger1 -1.46 * Zyx -1.3 * Penk -2.64 *** Pecam1 -1.36 ** Serping1 -1.46 * Gnb2 -1.29 * Mapk11 -2.47 *** Foxo3 -1.35 ** Ang -1.45 * Lyn -1.29 * Tgfbi -2.13 *** Nr2f2 -1.34 ** Elmo1 -1.45 * Palm -1.29 * Tgfbr3 -2.04 *** C3 1.32 ** Mapk3 -1.45 * S100a6 -1.29 * Cnn1 -1.92 *** Wwtr1 -1.29 ** Gpr44 1.45 * Il17ra 1.29 * Mcam -1.9 *** Sphk1 1.29 ** Itga5 -1.44 * Hoxa9 -1.28 * Fhl1 -1.89 *** Cfl1 -1.26 ** Tgm2 -1.44 * Msn -1.28 * Clic4 -1.8 *** Gna13 -1.22 ** Ppap2a -1.43 * Mst1r -1.28 * Mras -1.56 *** Mapk12 -1.21 ** Pdgfrb -1.41 * Abl1 -1.27 * Edn3 -3.43 ** Cited2 -2.26 * Cxcl16 1.41 * Itgb1 -1.27 * Figf -2.63 ** Lama1 -2.17 * Apbb2 -1.4 * Lpar3 -1.27 * Ctgf -2.18 ** Chi3l1 1.99 * Slc2a1 -1.4 * Scgb3a1 1.27 * Agtr2 2.18 ** Cnn2 -1.96 * Col4a2 -1.39 * Bcl2 -1.26 * Fgf7 -2.15 ** Itga1 -1.95 * Dab2 -1.39 * Gcnt1 -1.25 * Cldn3 -2.13 ** Itgb3 -1.88 * Dstn -1.39 * Lrpap1 -1.25 * Timp3 -2.03 ** Lgi1 -1.84 * Nrp1 -1.39 * Dcc 1.25 * Bgn -2 ** Ptgs2 -1.83 * Prune -1.39 * Prtn3 1.25 * Gem -1.88 ** Adm -1.73 * Tnfrsf1a -1.39 * Adrbk1 -1.24 * Rhob -1.85 ** Nbl1 -1.69 * Itgad 1.39 * Actn4 -1.21 * Itgb5 -1.81 ** Pmp22 -1.67 * Mycn 1.39 * Dnajb4 -1.21 * Gab2 -1.79 ** Itga9 -1.64 * Nppc 1.39 * Nfix -1.21 * Reck -1.72 ** Lama2 -1.62 * Vcam1 1.39 * Cdk5r2 1.21 * Stard13 -1.7 ** Rras -1.62 * Igfbp6 -1.38 * Lims1 -1.2 * Lims2 -1.69 ** Slit3 -1.62 * Lamc1 -1.38 * Prnp -1.19 * Hdc -1.66 ** Myh11 -1.6 * Ptp4a3 -1.38 * Foxc1 1.19 * Pkd1 -1.66 ** Tns1 -1.59 * Fadd -1.37 * Kif1c -1.18 * Fstl1 -1.65 ** Timp2 -1.58 * Eln -1.36 * Faslg 1.18 * Cd34 -1.64 ** Atp2b4 -1.57 * Prkca -1.36 * Macf1 -1.17 * Ilk -1.62 ** Mgll -1.57 * Prkaca -1.35 * Ctnnd1 1.17 * S100a10 -1.58 ** Rps6ka5 -1.54 * Ehd1 -1.34 * Cyct 1.17 * Mylk -1.55 ** Tagln -1.54 * Fermt2 -1.34 * Gap43 1.17 * Adam19 -1.55 ** Tnfrsf21 -1.53 * Rhog -1.34 * Gnai2 -1.13 * Nrp2 -1.54 ** F2r -1.52 * Wasf2 -1.34 * Ucp2 -1.13 * Sema5a -1.54 ** Lamb3 1.52 * Pgf -1.33 * Capn2 -1.12 * Id3 -1.54 ** Lox -1.5 * Ccl6 -1.32 * Rab21 -1.12 * Hoxa7 -1.54 ** Calcrl -1.48 * Cdkn1b -1.32 * Ptprk 1.11 * Cav1 -1.52 ** Cercam -1.48 * Sparc -1.32 * Il11 1.1 * Ndrg1 -1.44 ** Dapk3 -1.47 * Tpm1 -1.31 *

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Table 7.4 Differentially expressed genes in PRKO oviducts associated with the functions of vasoconstriction and/or muscle contraction. Fold change is PRKO relative to PR+/- oviducts; negative fold-change indicates down-regulation and positive fold-change indicates up-regulation. * P<0.05; ** P<0.01; *** P≤0.001; **** P<0.0001. Vasoconstriction/muscle contraction Gene Fold P- Gene Fold P- Symbol Gene Name change value Symbol Gene Name change value Actg2 actin, gamma 2, smooth muscle, enteric -2.52 **** Hspb6 heat shock protein, alpha-crystallin-related, B6 -1.55 * Des desmin -3.55 *** F2r coagulation factor II (thrombin) receptor -1.52 * Edn3 endothelin 3 -3.43 *** Npy1r neuropeptide Y receptor Y1 -1.49 * Cnn1 calponin 1 -1.92 *** Calcrl calcitonin receptor-like -1.48 * Mylk myosin, light polypeptide kinase -1.55 *** Fxyd1 FXYD domain-containing ion transport regulator 1 -1.47 * calcium channel, voltage-dependent, L type, alpha 1C Myocd myocardin -2.27 ** Cacna1c subunit -1.44 * potassium large conductance calcium-activated channel, Agtr2 angiotensin II receptor, type 2 2.18 ** Kcnma1 subfamily M, alpha member 1 -1.37 * Pln phospholamban 2.03 ** Prkca protein kinase C, alpha -1.36 * Oxtr oxytocin receptor 1.90 ** Lmod1 leiomodin 1 (smooth muscle) -1.36 * Arg2 arginase type II -1.74 ** Adra1a adrenergic receptor, alpha 1a 1.36 * Slc8a1 solute carrier family 8 (sodium -1.67 ** Tpm1 tropomyosin 1, alpha -1.31 * Cav1 caveolin 1, caveolae protein -1.52 ** Ptgs1 prostaglandin-endoperoxide synthase 1 -1.31 * Tpm2 tropomyosin 2, beta -1.51 ** Snta1 syntrophin, acidic 1 -1.29 * Acta2 actin, alpha 2, smooth muscle, aorta -1.49 ** Agtr1b angiotensin II receptor, type 1b 1.28 * Smtn smoothelin -1.45 ** Adrbk1 adrenergic receptor kinase, beta 1 -1.24 * calcium channel, voltage-dependent, T type, alpha 1H Atp1a2 ATPase, Na+/K+ transporting, alpha 2 polypeptide -1.43 ** Cacna1H subunit -1.23 * Sphk1 sphingosine kinase 1 1.29 ** Cryab crystallin, alpha B -1.21 * Ptgs2 prostaglandin-endoperoxide synthase 2 -1.83 * Lims1 LIM and senescent cell antigen-like domains 1 -1.20 * Adm adrenomedullin -1.73 * Myh6 myosin, heavy polypeptide 6, cardiac muscle, alpha 1.14 * Myh11 myosin, heavy polypeptide 11, smooth muscle -1.60 * Chrnd cholinergic receptor, nicotinic, delta polypeptide 1.14 * Camk2d calcium/calmodulin-dependent protein kinase II delta -1.59 * Gnai2 guanine nucleotide binding protein (G protein), alpha inhi -1.13 *

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Prostaglandins have been implicated in regulating cilia beat frequency (CBF) in oviduct epithelial cells [Hermoso et al., 2001], as well as potentially inducing muscular contractions in the ampulla-isthmic junction [Wanggren et al., 2008], at least from in vitro studies (see also Section 1.3.2 for more detail). Thus, expression of synthesising enzymes or prostaglandin receptors may be important for regulating oocyte and embryo transport in the oviduct. The microarray study found that both prostaglandin synthase 1 (Ptgs1; fold-change 1.31; P = 0.048) and prostaglandin synthase 2 (Ptgs2; fold-change 1.83; P = 0.014) were significantly down-regulated in PRKO relative to PR+/- oviducts, as well as the prostaglandin F receptor (Ptgfr; fold-change 2.28; P = 0.0143) and prostaglandin E receptor 1 (Ptger1; fold change 1.46; P = 0.046). Of these, Ptgs2 expression was validated by real-time PCR and was confirmed to be highly down-regulated in the 8 h post-hCG RNA samples used for the microarray (Figure 7.6A). However, although there was a trend for reduced expression in the hCG-treated PRKO oviducts relative to the PR+/- oviducts, this was not statistically significant (Figure 7.6A).

Included in the list of the 50 most-dysregulated genes in the PRKO oviducts was actin, gamma 2, smooth muscle, enteric (Actg2), which has been shown to be preferentially expressed, along with other contractile proteins, in contractile vascular smooth muscle cells derived from the rat [McBride et al., 2004] and also participates in cell motility. Down-regulated expression of this gene in the PRKO oviducts was confirmed for the RNA used in the microarray (Figure 7.6B), and there was a trend for down-regulated expression in the PRKO oviduct samples across the periovulatory time course, although this was not statistically significant. This gene was also not induced by LH (Figure 7.6B).

The oviductal glycoprotein, Ovgp1, encodes a mucoid protein exclusively produced by oviductal secretory cells that has been described in a number of species (see Section 1.3.2.3 for more details), is present in the oviduct around the time of ovulation and is believed to be important for regulating sperm binding, reducing polyspermy and increasing fertilisation rate, at least from in vitro evidence [Buhi, 2002; McCauley et al., 2003]. Although it has been reported to be primarily induced by E2 [Buhi, 2002], expression of Ovgp1 was moderately but significantly down-regulated in the PRKO oviducts from microarray (1.09 fold-change; P = 0.043) and therefore was potentially regulated by PGR. However, real-time PCR validation indicated that this gene was not significantly regulated by PGR, nor was it induced by LH (Figure 7.6C).

A further three genes were validated and were all found to be highly down-regulated in the PRKO oviducts relative to the PR+/- oviducts over the periovulatory period (Figure 7.7). They were the protease Adamts1, endothelin 3 (Edn3) and integrin alpha 8 (Itga8). All three genes were among the 50 most highly dysregulated genes in the PRKO oviducts.

Lisa Akison 2012 225 A) 2.0 PTGS2

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Relative Fold Change (Mean + SE) + (Mean Change Fold Relative 0.0 0.0 48h 4h 8h 10h PR+/- PRKO post-eCG post-hCG Figure 7.6 RT-PCR validation of putative PGR-regulated genes in the oviduct. Real-time PCR validation of several genes identified by microarray as down-regulated in PRKO oviducts at 8 h post-hCG. These genes were examined in oviductal tissues collected over a periovulatory time course from mice injected with eCG and hCG. n = 5 animals from each time point/genotype. Different letters denote significant differences from a two-way analysis of variance and an ad-hoc Holm-Sidak multiple comparison procedure (P<0.05). Data was log-transformed where required to normalise the distribution. Right panels for each gene show real-time PCR validation of the pooled oviduct samples used in the original microarray experiment. For each genotype, there were 5 samples with 3 animals pooled per sample (see Appendix 2 for details of pooled samples). Significant differences were determined using a Student’s t-test. ** = P<0.01; *** = P<0.001. Lisa Akison 2012 226

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Relative Fold Change (Mean + SE) + (Mean Change Fold Relative 0 0.0 48h 4h 8h 10h PR+/- PRKO post-eCG post-hCG Figure 7.7 A subset of PGR-regulated genes in the oviduct are also induced by hCG. Real-time PCR validation of several genes that were identified by microarray to be highly down- regulated in PRKO oviducts at 8 h post-hCG. These genes were examined in oviductal tissues collected over a periovulatory time course from mice injected with eCG and hCG. n = 5 animals from each time point/genotype. Different letters denote significant differences from a two-way analysis of variance and an ad-hoc Holm-Sidak multiple comparison procedure (P<0.05). Data was log-transformed where required to normalise the distribution. Right panels for each gene show real-time PCR validation of the pooled oviduct samples used in the original microarray experiment. For each genotype, there were 5 samples with 3 animals pooled per sample (see Appendix 2 for details of pooled samples). Significant differences were determined using a Student’s t-test. ** = P<0.01; *** = P<0.001.

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7.4 Discussion

PGR mRNA expression was quantified in normal oviducts across the periovulatory window and was found to be relatively constant, although there was a suggestion of a decline in expression just prior to ovulation at 10 h post-hCG. However, expression was not examined prior to injection with eCG and so the comparative expression of PGR mRNA in the absence of gonadotrophin stimulation is not known. This was also the case in the only other study of PGR mRNA in the mouse, which used X-gal staining of tissues from a PRlacZ reporter mouse, and indicated constitutive expression of PGR in the oviduct from 48 h post eCG until 24 h post-hCG [Ismail et al., 2002], although the level of staining was not quantified. Interestingly, one study has reported a similar pattern of expression for PGR protein to that reported here for mRNA expression, with maximal protein detected at 48 h post-eCG and a decrease in both isoforms of PGR after hCG injection in the mouse [Shao et al., 2006]. This decrease in expression was concomitant with an increase in serum P4. However, another study showed an increase in PGR protein in response to hCG, particularly in ciliated cells [Teilmann et al., 2006]. The results in this chapter report the first quantification of PGR mRNA in mouse oviducts during the periovulatory period. Quantification of expression at a time point prior to injection with gonadotrophins would be informative to verify that PGR mRNA is induced by eCG. Also, quantitative immuno-staining or Western Blot quantitation of PGR protein in the oviduct over the pre- and periovulatory period is required to resolve the conflicting reports of PGR expression over this period.

Evidence for PGR regulation of oviductal function in vivo

Progesterone is known to affect oviductal cells, at least in vitro, and therefore one can assume that PGR must somehow be playing a role in regulating oviductal function (see Figure 7.8). Two in vivo antagonist studies have shown evidence that PGR directly affects oviductal function in vivo [Fuentealba et al., 1987; Vinijsanun and Martin, 1990]. In one study, rats were treated continuously with RU486 using osmotic pumps from day 1 of pregnancy and were sacrificed at various times during early pregnancy, followed by flushing of both the oviduct and the uterus [Fuentealba et al., 1987]. In the rats treated with RU486, embryos arrived prematurely to the uterus, approximately 11 h earlier than in control rats. Similarly, in a later study, mice were injected subcutaneously with either RU486, ZK98734 or vehicle daily for the first 3 days of pregnancy and the uteri flushed on the afternoon of day 3 [Vinijsanun and Martin, 1990]. Of the vehicle-treated mice, only 1 out of 10 had 1 embryo in the uterus while 52% of mice in both PGR antagonist groups had large numbers of embryos in the uterus. This suggests that there was a defect in oviductal transport in the animals treated with the PGR antagonists, however the mechanism for this defect was not determined.

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Although multiple reproductive defects have been reported for PRKO female mice, including uterine implantation failure, impaired mammary gland morphogenesis/differentiation, lack of sexual receptiveness and anovulation [Lydon et al., 1995], this is the first time that morphological and functional consequences of PGR ablation have been examined in the oviducts. Detailed histological examination at various time points leading up to ovulation, as well as immediately post-ovulation, revealed no obvious structural defects in whole oviducts or in the cells of the luminal epithelium. Ciliated cells and secretory cells were evident and their distribution and abundance did not suggest any marked differences between the genotypes using H & E stained sections. However, quantification of the number of secretory cells by staining for specific markers of these cells was not performed. OVGP1 [Rodriguez-Manzaneque et al., 2002; Verhage et al., 1997] and PAX8 [Bowen et al., 2007] are both proteins reported to be specific to these secretory peg cells, and not found in the ciliated cells of the oviduct. However, Pax8 mRNA was not found to be significantly different between genotypes by microarray. Further, although Ovgp1 mRNA was significantly but modestly down-regulated in PRKO oviducts by microarray analysis, this was not supported by quantitative real-time PCR. Therefore, there is no evidence for morphological anomalies in the oviducts from PRKO mice.

Although the morphology of oviducts from PRKO mice was normal, there was a profound effect of PGR ablation on gene expression in the oviduct. In this Chapter and in Appendix 6, I present a comprehensive list of putative PGR-regulated genes in the oviduct during the periovulatory period, with potential roles in oocyte pick-up and early embryo transport. Given the well documented role of P4 in eliciting changes in the oviduct luminal epithelium, muscular and nerve function and oviductal fluid (see Chapter 1 for review), it is perhaps surprising that to-date, this is the first genome-wide survey of PGR- regulated genes in the oviduct. Predominant biological functions associated with PGR-regulated genes in the oviduct were adhesion, attachment and binding of cells, perhaps involved in the initial capture or movement of the newly ovulated COC; cell migration, chemotaxis and invasion, which may play a role in the transport of the oocyte/embryo along the oviductal lumen; and vasoconstriction and muscle contraction, which may also contribute to embryo transport as well as the movement of transudates from oviductal vessels into the luminal fluid. The results of this microarray experiment provide an invaluable resource for the generation of new hypotheses related to the molecular mechanisms underlying progesterone regulation of oviductal function.

As with any investigation of genes of interest generated from a microarray experiment, expression needs to be validated using quantitative assays such as real-time PCR, as discussed previously in Chapter 5. As a preliminary examination, six genes were chosen based on their previously described functions in the oviduct or in other systems. Three of these genes, Ovgp1, Ptgs2 and Actg2, did not show reliable evidence of PGR-regulation, nor were they induced by LH during the periovulatory period.

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However, three genes, Adamts1, Edn3 and Itga8, did show significant regulation by PGR and an interesting induction in expression in response to LH; and are discussed in more detail below.

A disintegrin and metalloproteinase with thrombospondin motifs 1 (Adamts1)

Expression of the protease, Adamts1, was highly down-regulated (more than 3-fold) in the PRKO oviducts from the microarray, and this down-regulation was confirmed by real-time PCR in a separate periovulatory time-course with approximately the same magnitude fold-change. Adamts1 is a well- known PGR-regulated gene in the ovary [Robker et al., 2000; Russell et al., 2003b] but this is the first report of PGR-regulation of this gene in the oviduct. Interestingly, several other Adamts genes were also down-regulated in the PRKO oviducts (Adamts6, 10, 3, 9, 5, 12; see Appendix 6 for details). There is only one recent report of Adamts gene expression in the oviduct, with expression detected in the ampulla region of human fallopian tubes measured across the menstrual cycle as part of a PCR array [Diaz et al., 2012]. Adamts1, 8 and 13 were examined, with Adamts8 constitutively expressed across the cycle and Adamts1 and 13 significantly up-regulated more than 2-fold in the periovulatory compared to the follicular phase. Similarly, my real-time data across the periovulatory period in mouse oviducts also showed an induction in Adamts1 mRNA in response to LH/hCG. The role that Adamts protein, and Adamts1 specifically, may be playing in the oviduct is not known. The ADAMTS family are members of the metzincin protease family with several protein domains involved in ECM binding [Porter et al., 2005]. In the ovary, it has been shown to be important for processing of the proteoglycan versican, a key component of the extracellular matrix in the expanded COC and the follicle wall [Brown et al., 2010a; Russell et al., 2003b], and also a major substrate for Adamts1 in other tissues [Jonsson- Rylander et al., 2005; Ricciardelli et al., 2011; Verhage et al., 1997]. However, Adamts1 also cleaves collagen type I [Guo et al., 2010; Lind et al., 2006b] which has been reported to be present in the oviduct [Lantz et al., 1998; Schultka et al., 1989]. Active ADAMTS1 has been established to play a role during invasive cancer metastasis [Keightley et al., 2010; Liu et al., 2006b; Lu et al., 2009; Ricciardelli et al., 2011] and it has also been shown to be antiangiogenic [Carpizo and Iruela-Arispe, 2000; Xu et al., 2006b] and pro-inflammatory [Kuno et al., 1997] in other tissues.

Endothelin 3 (Edn3)

Edn3 was strongly down-regulated in the PRKO oviduct, as shown by microarray and then validation using real-time PCR. Interestingly, Edn1 and Edn2 were not regulated by PGR in the oviduct as they are in the ovary [Palanisamy et al., 2006; Sriraman et al., 2010]. Edn1 and Edn2 have been previously examined in the oviduct and their ability to affect smooth muscle tone, thus modulating oviductal contractility and ultimately regulating oocyte/embryo transport, has been demonstrated in animal models (see [Bridges et al., 2011] for review). However, Edn3 has only recently been identified in the oviduct in mice [Jeoung et al., 2010], showing a gondadotrophin-induced increase in mRNA expression Lisa Akison 2012 230 in luminal epithelial cells of the isthmus region. The receptor for Edn3, Ednrb, was also localised to the luminal epithelial cells of the oviduct, with its expression induced by hCG, peaking around the time of ovulation. EDNRB protein was predominantly localised to epithelial secretory cells using immunohistochemistry [Jeoung et al., 2010]. Treatment with a dual endothelin receptor antagonist (tezosentan) resulted in significantly fewer 2-cell embryos flushed from the oviducts, prompting the authors to hypothesise that, unlike the other endothelins, Edn3 may play a specific role in regulating oviductal epithelial cell secretions, which have been shown, at least in vitro, to affect fertilisation and early embryonic development [Kito et al., 2004; Munuce et al., 2009]. I also found an induction of Edn3 mRNA expression in response to hCG in whole oviducts, but this is the first report of PGR regulation of Edn3 in the oviduct. Further experiments to clarify its precise role in the oviduct are required.

Integrin alpha 8 (Itga8)

Itga8 was the most profoundly dysregulated gene in the PRKO oviducts by microarray, showing an almost 10-fold decrease in expression relative to normal, PR+/- oviducts. This result was confirmed across the periovulatory window by real-time PCR. Interestingly, I also found an almost 4-fold induction in Itga8 expression in response to hCG in the normal, PR+/-, oviducts. A recent study has identified Itga8 expression in human fallopian tubes and potentially similar steroidal regulation of this gene, as expression decreased more than 2-fold in the luteal phase compared to the periovulatory phase of the menstrual cycle [Diaz et al., 2012]. Although Itga8 mRNA is regulated by PGR and induced by LH in the oviduct, the role for Itga8 in the oviduct is not known. Itga8 forms heterodimers with the 1 sub-unit and is predominantly localised to smooth muscle cells in other tissues [Schnapp et al., 1995a]. It is involved in the adhesion of cells to extracellular matrix, particularly tenascin, fibronectin and vitronectin [Schnapp et al., 1995b]. Itga8 integrin has been shown to be important for maintaining the contractile smooth muscle phenotype in vascular smooth muscle cells (VSMCs) in vitro by siRNA targeting, with silencing of Itga8 resulting in disassembly of actin stress fibres and focal adhesion components [Zargham and Thibault, 2006]. Thus, its expression in VSMCs and attachment to matrix components maintains the smooth muscle cell differentiated phenotype, while its loss heightens VSMC migration [Zargham and Thibault, 2005]. Therefore, it may play a role in regulating muscular contractility in smooth muscle cells of the oviductal wall. As mentioned in Chapter 1, changes in muscle tone are coordinated by ovarian steroids. Thus, Itga8 may be one of the molecular mechanisms by which E2 and P4, via their respective receptors, controls this contractile phenotype. Alternatively, it may be involved in the initial pick-up of the COC at ovulation or movement of the COC into the ampulla. Fibronectin and tenascin are produced by cumulus cells in the mature COC and show a heterogeneous distribution, suggestive of specific roles in promoting adhesion [Familiari et al., 1996]. Therefore, an

Lisa Akison 2012 231 investigation of the specific cell types expressing Itga8, smooth muscle cells and/or luminal epithelial cells, is required to determine its potential role in oviductal function.

Other genes of interest

Aside from the validated genes mentioned above, several other genes identified from this array are worthy of immediate attention and validation. The gene encoding the prolactin receptor (Prlr) was down-regulated more than 3-fold in the PRKO oviducts. Prolactin is an important reproductive hormone which aside from stimulating mammary gland development and lactation, is also essential for corpus luteum function and progesterone synthesis (see [Binart et al., 2010] for review). Prolactin receptor null mice (Prlr-/-) are completely infertile, despite normal follicle growth, ovulation, and fertilisation [Grosdemouge et al., 2003; Ormandy et al., 1997]. Although this is primarily due to a defect in embryo implantation, pre-implantation embryo development is also affected [Binart et al., 2000]. Interestingly, in these studies, the potential role of Prlr in the oviduct was not examined. A more recent study however has identified several isoforms of the Prlr in both human fallopian tubes and mouse oviducts, with expression restricted to epithelial cells in the mouse, while in the human oviduct, PRLR was detected in epithelial, stromal and muscle cells [Shao et al., 2008]. Further, this study found that administration of P4 to prepubertal mice decreased the expression of Prlr in the oviduct.

Two genes involved in smooth muscle contraction that were highly dysregulated in the PRKO oviducts were myocardin (Myocd, >2-fold reduced) and desmin (Des, 3.5-fold reduced). Myocd is a transcriptional co-activator of and has been identified as a master regulator of gene expression in smooth muscle cells [Li et al., 2003; Wang et al., 2003]. Des is found in smooth muscle cells [Li et al., 1997b], as well as interstitial Cajal-like cells (ICLC) in the oviduct [Popescu et al., 2005] which also express PGR. ICLC are thought to contribute to the contractility of the oviduct via their connections to smooth muscle cells (see Section 1.3.1 for more details). In addition, angiotensin II has been shown to regulate bovine oviductal contractions, at least in vitro [Wijayagunawardane et al., 2001a], and both angiotensin II receptor, type 1b and 2 (Agtr1b, Agtr2) were dysregulated in the PRKO oviduct (1.28-fold and 2.18-fold increase respectively).

In terms of cilia activity in the oviduct, PGR appears important in regulating cilia beat frequency (CBF) from in vitro antagonist studies [Mahmood et al., 1998], although the mechanism of this regulation is not known (see also Section 1.6.2). However, prostaglandins [Hermoso et al., 2001; Verdugo et al., 1980] or angiotensin II [Saridogan et al., 1996] may be involved as they are produced by the oviduct and regulate CBF in vitro. As mentioned above, two angiotensin II receptors were dysregulated in the PRKO oviducts and therefore, there may be multiple roles for angiotensin II in regulating oviductal function. I also found several genes involved in prostaglandin synthesis and activity were dysregulated

Lisa Akison 2012 232 in the PRKO oviducts (Ptgs2, Ptgs1, Ptger1 and Ptgfr), but the prostaglandin F receptor (Ptgfr) showed the most compelling down-regulation (>2-fold reduced). Both Ptgfr and Ptger1 have previously been shown to be down-regulated in human fallopian tubes after treatment with the PGR antagonist, RU486 [Wanggren et al., 2006].

Finally, a previous study has shown that exogenous P4 regulated complement component 3 (C3) mRNA and protein expression in oviducts of ovariectomised mice [Lee et al., 2009]. I also confirmed that C3 mRNA was significantly but moderately (1.3-fold) up-regulated in the PRKO oviducts by microarray. C3 is converted into the embryotrophic derivatives iC3b and C3b in the presence of embryos and oviductal cells [Tse et al., 2008], and therefore it could play a role in supporting early embryo development in the oviduct.

The microarray experiment conducted in this chapter revealed many genes dysregulated in the PRKO oviducts that could be involved in oocyte and early embryo transport (Figure 7.8). Only a few of these have been validated by quantitative real-time PCR, and so further validation of many of these gene targets is required. To determine the functional significance of dysregulation of these gene pathways, in vitro oviductal explant experiments comparing muscular contractility and cilia beat frequency in oviductal tissue collected from PRKO and PR+/- mice immediately prior to ovulation would be informative. These experiments have been previously described for bovine oviducts [Wijayagunawardane et al., 2001b] and hamster oviducts [Riveles et al., 2003] respectively. Thus, the functional consequences of the gene expression changes in the absence of PGR could be measured and quantified directly in the oviduct. However, it is clear from the sheer number of genes that were dysregulated in PRKO oviducts, that PGR must play a key role in regulating oviductal function.

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Figure 7.8 PGR regulation of gene pathways potentially involved in oviductal transport. Previous in vitro studies have demonstrated that progesterone (P4) and estradiol (E2) can affect oviductal cell function, including regulation of cilia beat frequency, muscle contractility and oviductal secretions (e.g. prostaglandins). Each of these may impact on transport of the newly ovulated oocyte and the early embryo. However, the mechanisms underlying these effects are not clear. The results presented in this chapter are the first demonstration that progesterone receptor (PGR) regulates multiple gene pathways that are known to be involved in these functions in similar cells found in other tissues, as well as directly in the oviduct. Functional studies, such as in vitro measurement of cilia beat frequency and muscle cell contractions, are required to definitively demonstrate the impact of PGR ablation on oviductal function.

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Chapter 8 – Conclusions & future research directions

8.1 Introduction

Ovarian progesterone is undeniably the ‘master controller’ of female, mammalian reproduction and progesterone receptor (PGR) plays a critical, pleiotrophic role. This receptor is involved in regulating the gonadotrophin surge that is required to induce ovulation [Chappell et al., 1997; Chappell et al., 1999]; initiates the lordosis response or sexual receptiveness in females [Lydon et al., 1995; Mani et al., 1996]; directly controls ovulation, specifically follicle rupture and oocyte release [Lydon et al., 1995; Robker et al., 2000]; is required for uterine decidualisation and implantation [Franco et al., 2008; Lydon et al., 1995]; and controls mammary gland ductal morphogenesis and lobuloalveolar differentiation [Ismail et al., 2003; Lydon et al., 1995; Mulac-Jericevic et al., 2003]. Therefore, it is involved in a spectrum of processes required for reproductive success. Direct evidence for the critical role of PGR in reproductive function comes from the various knockout mouse models with targeted deletion of the PGR gene. These mice display a range of phenotypes that reiterates the functional versatility of this transcription factor. Experiments reported in this thesis utilise the PGR null (PRKO) mouse model as a tool to investigate the molecular mechanisms underlying ovulation and oviductal transport. Therefore, the results in this thesis build on earlier studies as well as adding entirely new information on the role of PGR in the oviduct.

In Chapter 1, several knowledge gaps were identified that have been addressed in this thesis. These included:

 Whether the anovulatory phenotype of the PRKO mouse is intrinsic to the PRKO ovary. Can function be restored to the PRKO ovary if transferred into a normal mouse, as has been shown in other infertility models? This was addressed in Chapter 3.  A systematic evaluation of ovarian/follicular and oviductal structure in PRKO mice during the periovulatory period and immediately post-ovulation. This was presented in Chapters 3 and 7.  The role that PGR plays in regulating inflammatory pathways and mediators in periovulatory ovaries. This was addressed in Chapter 4.  Gene networks specifically dysregulated in PRKO granulosa cells, where PGR is exclusively expressed in preovulatory follicles. This was addressed in Chapter 5.  Characterisation of the adhesive, migratory and matrix-invading capacity of preovulatory COCs. Specifically, the temporal kinetics of induction of this phenotype in the ovulatory process. What

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happens immediately post-ovulation? Are these processes disrupted in PRKO COCs? This was examined in Chapter 6.  The influence of granulosa-cell PGR on cumulus oocyte complex structure and function. This was addressed in Chapter 6.  Identification of PGR-regulated gene networks in the oviduct. Previous studies have shown that P4 in vitro can impact on oviductal cells, but the role that PGR plays in the oviduct in vivo has not been examined. This was addressed in Chapter 7.

8.2 Thesis conclusions

The conclusions from the experiments reported in this thesis are summarised in Figure 8.1. Given the extensive discussion of results and conclusions in the relevant experimental chapters, a relatively brief summary of the conclusions for PGR regulation of ovarian and oviductal structure and function is presented below.

8.2.1 PGR regulation of ovarian structure and function

Ovarian transplant experiments reported in Chapter 3 confirmed that despite PGR expression in other tissues, it is specifically ovarian PGR that is required for successful ovulation. This was an important discovery, as PGR is expressed in a range of extraovarian tissues and the relative contribution of PGR loss in the ovary versus other tissues to the observed anovulatory phenotype was not known. Given the inflammatory characteristics of ovulation, PGR expression in tissues and cells from the immune system may have been important extra-ovarian influences on ovulatory success. My demonstration of the inability to restore function to the PRKO ovary in an environment with normal expression of PGR confirmed for the first time that external factors could not override the intrinsic ovarian loss of PGR.

Detailed morphometric analysis of PRKO ovaries during the periovulatory period expanded upon previous reports of normal growth and development of large, preovulatory follicles, that display all the characteristic structural features which appear in the lead up to ovulation. This included expansion of cumulus matrix in the COCs of these follicles, thinning of the apical follicle wall, increased vascularisation and invagination of the basal follicle wall. The only morphological defect was reported at 14 h post-hCG, when COCs became entrapped within luteinising follicles in PRKO ovaries while COC release occurred normally in ovaries from heterozygous littermates, resulting in abundant corpora lutea. Therefore, given the intrinsic anovulatory phenotype of the PRKO ovary, and the lack of visible

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Figure 8.1 PGR regulates multiple processes in periovulatory ovaries and oviducts. Ovarian transplant experiments confirmed that ovarian PGR, expressed specifically in granulosa cells of large, preovulatory follicles, is required for successful ovulation (Chapter 3). Analysis of gene expression in whole ovaries using a Taqman Mouse Immune Array identified a number of PGR-regulated immuno-modulatory genes including cytokines, genes involved in prostaglandin synthesis, vasoconstrictors and specific immune cell receptors (Chapter 4). PGR-regulated genes were also identified by microarray in both the granulosa cell and cumulus oocyte complex (COC) compartments of preovulatory follicles, including specific proteases, genes involved in vascular remodelling and angiogenesis, and genes involved in cell adhesion, migration and invasion (Chapters 5 and 6). PGR expression in granulosa cells appears to impact on other aspects of the COC, including the integrity of the cumulus matrix, specifically its ability to sequester cumulus cell- produced growth factors within the complex, as well as mitochondrial distribution and/or activity in the oocyte (Chapter 6). Finally, novel PGR-regulated genes were identified in the oviduct and associated with various processes which may impact on oviductal transport of oocytes and embryos (Chapter 7).

Lisa Akison 2012 237 structural defects that may prevent follicle rupture, critical proteolytic, biochemical or transcriptional events, undetectable at the level of visual histology, must be dysregulated or absent in the PRKO ovary.

Given that PGR is a transcription factor, its regulation of molecular pathways potentially involved in follicle rupture and oocyte release were investigated in Chapters 4-6. Ovulation shares many of the hallmarks of an inflammatory reaction, and so PGR-regulation of inflammatory pathways and mediators was examined in Chapter 4. This had not been examined previously in any systematic way, even though IL6, Snap25 and Ptgs2 previously showed some evidence of PGR regulation in the ovary in vivo [Kim et al., 2008; Mori et al., 2011; Shimada et al., 2007]. Our lab also has evidence that neutrophil numbers are reduced in PRKO preovulatory follicles relative to PRWT littermates. In PRKO whole ovaries examined 2 h prior to ovulation, I found 17 inflammatory genes dysregulated from 89 examined using a low density array. These included vasoconstrictors, endothelial adhesion receptors, inflammatory cytokines and cytokine transcription factors, T-cell markers, a pro-apoptotic factor and the prostaglandin synthesising enzyme, Ptgs2. The majority of genes identified have not been previously demonstrated to play a role in ovulation. Notably normal in their expression in PRKO ovaries were neutrophil and macrophage markers. The expression of Ptgs2 was further investigated but, although there was evidence for significant down-regulation of mRNA in PRKO ovaries, isolated granulosa cells and COCs showed levels of expression similar to heterozygous littermates. Intriguingly, protein levels appeared normal by immunohistochemistry suggesting that any action of PGR on mRNA steady state levels may not dramatically alter protein levels. The data suggest that reduced Ptgs2 mRNA in PRKO ovaries is attributable to cells other than granulosa and cumulus cells, most likely inflammatory cells. This and other, specific aspects of the inflammatory profile induced at ovulation are clearly disrupted in PRKO ovaries.

To-date, no single PGR-regulated gene has been shown to mediate PGR’s effect on ovulation leaving open the possibility that an as yet unidentified PGR target gene (or pathway) is the critical ovulatory mediator. Therefore, a genome-wide, microarray approach was used to identify PGR-regulated genes, specifically in granulosa cells collected from PRKO and PR+/- mice at a time point coincident with peak PGR expression (8 h post-hCG). Almost 300 genes were found to be dysregulated in PRKO relative to PR+/- granulosa cells, many of which were novel PGR-regulated genes in the ovary. Gene ontology analysis revealed significant associations of these genes with the functions of cell migration, movement, chemotaxis and invasion. There were also genes significantly associated with cell adhesion and binding, immune cell trafficking and immune response, vascular remodelling and angiogenesis, and proteolytic activity. Therefore, this experiment produced a comprehensive list of genes influenced by PGR in granulosa cells in vivo with potential roles in the molecular processes

Lisa Akison 2012 238 contributing to ovulation. Several genes were identified for further validation (see Section 8.4), with the chemokine receptor, CXCR4, given top priority for this thesis. This receptor was found to be dramatically induced by LH in both granulosa cells and COCs and was confirmed to be regulated by PGR using real-time PCR analysis. However, an attempt to inhibit this receptor’s function in vivo failed to have an effect on ovulation rate. Despite a range of mitigating possibilities for this observation explained in Chapter 5, a role for CXCR4 in the ovary remains to be determined.

Finally, the results of Chapter 6 provide the first evidence that PGR expression in ovarian granulosa cells can impact on aspects of the COC. My results found that periovulatory COCs readily adhere to ECM proteins found in the follicle wall, such as collagens, laminin and fibronectin, and that this adhesive capacity peaked at the time of ovulation and was reduced in postovulatory COCs. Similarly, the migratory capacity of COCs peaked at ovulation and declined following ovulation. Thus, exposure to the oviductal environment has a dramatic impact on the adhesive and migratory capacity of the COC. Periovulatory COCs also demonstrated a propensity to invade collagen I that was greater than a known invasive cell line. However, experiments conducted using optimal conditions for adhesion, migration and invasion comparing COCs from PRKO and PR+/- mice failed to detect any differences in these properties between genotypes. However, 44 genes were differentially expressed in PRKO relative to PR+/- COCs by microarray analysis, and many of these genes were associated with the functions of cell adhesion, migration and invasion. Thus, the in vitro assays may not have been sensitive enough or may not have targeted the appropriate adhesive or invasive environments to achieve detection of subtle differences in these properties between the genotypes. Conversely, a ‘bioassay’ of matrix integrity provided some evidence that matrix structure in PRKO COCs may be perturbed. Further, staining of mitochondrial membrane potential or activity in the oocyte suggested a disruption in the distribution of active mitochondria in PRKO relative to PR+/- COCs. Thus, PGR appears to have indirect effects on down-stream transcriptional targets in the COC and this is the first time that this has been reported. There is also evidence that this may have functional and sub-cellular consequences for the COC.

8.2.2 PGR regulation of oviductal structure and function

Despite PGR being highly expressed in the oviduct, and in vitro studies demonstrating that P4 impacts on oviductal cell function and secretions, the role that PGR plays in regulating oviductal structure and function has been overlooked. Ablation of PGR in the oviduct did not appear to impact on the structure of the oviduct or the appearance of ciliated or secretory cells in the luminal epithelium. However, results from Chapter 7 are the first comprehensive evidence of PGR regulation of molecular pathways underlying oviductal transport. Over 1000 genes were dysregulated in oviducts from PRKO mice

Lisa Akison 2012 239 relative to PR+/- mice during the periovulatory period. A significant number of these genes were associated with the functions of cell adhesion and cell binding; cell migration, chemotaxis and invasion; and vasoconstriction and/or muscular contractions. A small subset of genes were validated using quantitative real-time PCR, with some failing to display PGR-regulation across a periovulatory time course (Ptgs2, Actg2, Ovgp1), while others not only confirmed PGR-regulation but were also found to be induced after hCG treatment, during the periovulatory period when P4 levels surge (Adamts1, Edn3, Itga8). Therefore, the results of this microarray experiment provide an important resource for the generation of new hypotheses related to the molecular mechanisms underlying progesterone regulation of oviductal function.

Overall, this thesis has shown that progesterone receptor is truly a ‘master regulator’ in the periovulatory ovary and oviduct, controlling multiple peri-conception events.

8.3 Future research directions

The microarray studies reported in this thesis generated an overwhelming list of putative PGR- regulated genes in granulosa cells and the oviduct. Interrogation of this list is ongoing, but several genes have been identified in the course of this thesis as worthy of immediate validation and investigation. In the ovary, these include Zbtb16, Ephs/ephrins (specifically Efnb2), Sphk1, Runx2, Adam2, Rgmb, Mmp19 and Pappa (see Chapters 5 and 6 for further discussion of these genes). Also genes from the Ras GTPase superfamily that control integrin function (Rab11fip1, Rras2, Rasl11b, Rasgrf2, Rasef, Rasal1, Arhgef17, Arhgap6, Rnd3) and cytoskeletal genes (Actn4, Vcl, Zyx) which may also have down-stream effects on integrin-mediated COC adhesion and migration.

In the oviduct, gene targets of interest include Prlr, Des, Myocd, angiotensin II receptors (Agtr1b, Agtr2), Ptgs1, Ptger1, Ptgfr and C3 (see Chapter 7 for further discussion of these genes). In addition, clarification of PGR expression in the oviduct, both mRNA and protein, is required in the period immediately prior to the administration of gonadotrophins as well as immediately after ovulation. Adamts1, Edn3 and Itga8 mRNA expression was validated by RT-PCR in Chapter 7. As these genes showed interesting induction by hCG during the periovulatory period and dramatic regulation by PGR, analysis of protein expression and functional analysis to determine their role in the oviduct is justified.

Innovative genetic techniques would further clarify the role that these genes down-stream of PGR have on ovarian and oviductal function. One approach is the ‘transgenic rescue’ of genes with reduced expression in PRKO mice to attempt to restore ovulation. However, another strategy would be lentiviral-mediated delivery of specific gene products (see [Park, 2007] for review), perhaps directly into Lisa Akison 2012 240 the bursal cavity to ensure targeted delivery to the ovary. One example illustrating the use of this technique, is the injection of recombinant virus directing over-expression of insulin-like growth factor I (IGF-I) to skeletal muscle fibres, which was used to demonstrate its effect on blocking age-related loss of muscle function in mice [Barton-Davis et al., 1998; Barton, 2006]. Alternatively, in vivo siRNA knockdown or over-expression of specific gene targets in the ovary would allow their roles in ovulation to be determined potentially more efficiently than the creation of individual transgenic null models. For instance, Invivofectamine 2.0 has been used for in vivo transfection of melanomas with IGFBP7 in mice [Chen et al., 2010]. Perhaps use of this technique to either knock-down Cxcr4 expression in the ovaries of normal mice or transfect the ovaries of PRKO mice would be more informative in determining its role in ovulation than blocking its action with an inhibitor, as was attempted in Chapter 5.

The cytokine transcription factors, Stat3 and Socs1, were both dysregulated in PRKO ovaries (see Chapter 4). Tissue-specific Stat3 deficient mice indicate that this transcription factor plays a role in diverse biological functions including cell growth, suppression of apoptosis and cell motility (see [Akira, 1999] for review), but to-date, knock-down of Stat3 in the ovary has not been done. Further, the Stat3 global knockout is embryonic lethal [Takeda et al., 1997]. Similarly, Socs1 null mice die at 3 weeks of age and display aberrant activation of T-cells [Marine et al., 1999]. Thus, the role of these transcription factors in regulating genes and/or cytokines involved in ovulation remains to be determined. A recent study has identified a synthetic inhibitor of Stat3 as a potential targeted therapeutic for cancer treatment [Madoux et al., 2011] and may prove useful for targeted inhibition of Stat3 in the ovary to determine its role in ovulation. However, gene knockdown using lentiviral vectors or in vivo transfection with siRNA, as described previously, could also be used.

Although vascularisation in PRKO periovulatory ovaries appeared normal in H & E stained sections, dysregulation of the endothelial cell marker, Cd34, detected using the low density immune array, suggests that a more quantitative assessment of neovascularisation in PRKO ovaries during the lead up to ovulation is justified. In addition, PGR is expressed on endothelial cells and P4 is known to regulate endothelial cell proliferation [Vazquez et al., 1999]. Immunohistochemical staining with CD34 has been used previously to study cyclic changes of vasculature in normal ovaries [Suzuki et al., 1998b], and PECAM1/CD31 is commonly used as an endothelial marker to quantify vascular changes in the ovary (e.g. [Turner et al., 2011; Van Eyck et al., 2010]). In addition, staining for blood products such as II in PRKO and PR+/- periovulatory ovaries would allow the degree of vascular permeability to be evaluated.

The dysregulation of inflammatory pathways and genes reported in PRKO ovaries and granulosa cells in Chapters 4 and 5 respectively is the first evidence for PGR-regulation of the periovulatory immune response. From the immune array analysis of whole ovaries, several endothelial adhesion factors Lisa Akison 2012 241 known to be involved in facilitating immune cell infiltration were dysregulated (Cd34 and Sele). However the endothelial cell adhesion molecules, Pecam1/Cd31 and Icam1/CD54, were not included on the array and these are also involved in leukocyte capture and transmigration in other tissues [Ley et al., 2007]. Therefore, it would be interesting to examine their expression in PRKO ovaries. A detailed analysis of immune cell populations in PRKO compared with PR+/- ovaries during the periovulatory period using flow cytometry would also be informative to determine the precise nature of immune cell infiltration in this null model. In addition, the exact nature of PGR regulation of T-cell activation, reported in Chapter 4, requires further clarification. T-cells are involved in the adaptive immune response but the majority of studies relating to ovulation focus on innate or cell-mediated immunity (i.e. neutrophils and macrophages).

The mechanism for the transient adhesive and migratory/invasive phenotype of the periovulatory COC is currently unknown. Presumably, integrins and associated factors play a role, as demonstrated in the adhesion and migration of other cell types and the dysregulation of genes involved in integrin-mediated adhesion and migration in PRKO granulosa cells and COCs. The specific integrin heterodimers and their ECM binding partners need to be identified in periovulatory follicular cells. In particular, whether there is a shift in the expression profile of specific integrins, commonly known as the ‘integrin switch’. This is a characteristic feature of adhesion dynamics and cell motility during conditions of increased cell migration in other cell types [Truong and Danen, 2009]. Once putative integrins involved in cumulus cell adhesion and migration have been identified, functional assays using the in vitro real-time cell analysis system described in Chapter 6 should be conducted to attempt to inhibit particular migratory and adhesive mediators. In addition, in vivo knockdown in normal mice or over-expression in PRKO mice could be used to examine their direct impact on ovulation.

The impact of PGR on COC function and oocyte developmental competence remains unresolved. Results presented in Chapter 6 suggest that matrix integrity and oocyte viability may be perturbed. Further measurement of the filtration properties of cumulus matrix in expanded, periovulatory COCs is required, such as the rate of diffusion of exogenous metabolites such as glucose and cholesterol as has been tested previously and found to be increased in COCs matured in vitro relative to in vivo matured COCs [Dunning et al., 2012]. In addition, comparison of cumulus matrix proteins such as TNFAIP6/TSG6, versican and II in PRKO and PR+/- COCs by Western blot would indicate if structural components of the matrix are deficient in PRKO COCs. As mitochondrial bioenergetic activities in the oocyte are sensitive to external signals and have been linked to oocyte developmental competence in the human (see [Van Blerkom, 2011] for review) and the mouse [Fernandes et al., 2012], IVF experiments on PRKO oocytes matured in vivo would resolve the functional consequences of the observed mitochondrial anomaly reported for PRKO oocytes in Chapter 6.

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Finally, results reported in Chapter 7 provide potential biochemical and molecular mechanisms for PGR regulation of oviductal function. As the oviduct microarray was done on whole oviducts, it would be interesting to look at gene expression in specific regions or cell types in the oviduct. This could be accomplished by laser micro-dissection of luminal epithelium in oviduct sections or separation of collected oviducts into infundibula, ampulla and isthmic regions before RNA extraction and gene expression analysis. Most importantly, however, assays to examine the functional consequences of the gene expression changes in the absence of PGR are required. Therefore, in vitro oviductal explant experiments comparing muscular contractility and cilia beat frequency in oviductal tissue collected from PRKO and PR+/- mice immediately prior to ovulation would be informative. Also, knockdown of specific target genes using gene silencing techniques as described above would provide definitive evidence of specific down-stream targets of PGR that are involved in these processes.

8.4 Significance of results

In addition to the contribution of these results to a greater understanding of the fundamental biology underlying ovulation and oviductal transport, there are also, ultimately, several clinical applications of this work. Information on the specific components required for oocyte release has the potential for development as novel, non-invasive therapies for anovulation, a significant cause of infertility for Australian women [Marino et al., 2011]. These components could also be novel targets for contraception, through preventing ovulation. More than 100 million women rely on hormonal contraceptives to control or prevent ovulation [Trussell, 2007] but there is also an urgent need for safe, effective, non-hormonal forms of contraception [Sitruk-Ware et al., 2012]. The identification of appropriate controllers of oocyte release down-stream of P4/PGR, the current focus of conventional oral contraceptives, could provide appropriate targets with similar results. In addition, an understanding of the mechanisms underlying appropriately-timed oviductal transport of the early embryo to the uterus could expand our understanding of the causes of oviductal ectopic pregnancy, as well as pre- implantation pregnancy failure.

At the beginning of this thesis, it was stated that “the over-arching goal was to develop a greater understanding of the molecular processes regulating successful mammalian ovulation and subsequent transport of the oocyte and early embryo”. Although this thesis does not elucidate one individual and definitive ‘ovulatory gene’; it has generated an overwhelming number of potentially important genes for both follicle rupture and oviductal motility, which I hope will provide an important resource for shaping future hypotheses and experimental tests to determine the specific biochemical and molecular

Lisa Akison 2012 243 pathways required for these important reproductive processes. Perhaps this elusive ‘ovulatory gene’ is indeed progesterone receptor itself, given its profound requirement for successful ovulation.

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Appendices

Appendix 1 Complete gene information for the Taqman Low Density Immune Array (Mouse). Highlighted genes are those that were differentially expressed between PRKO and PR+/- ovaries at 10 h post-hCG (P<0.05). Chr = chromosome.

Gene Target NCBI Gene Assay ID Well Context Sequence Symbol Gene Name Chr Exons Reference Mm00607939_s1 A1 TACTGAGCTGCGTTTTACACCCTTT Actb actin, beta, cytoplasmic 5 13 NM_007393 Mm00431727_g1 A2 CTGCATTTTAAGGAGTGCATGCGGG Agtr2 angiotensin II receptor, type 2 X 1 NM_007429 Mm00437762_m1 A3 GTATGCTATCCAGAAAACCCCTCAA B2m beta-2 microglobulin 2 1 NM_009735 Mm00432050_m1 A4 GCAAACTGGTGCTCAAGGCCCTGTG Bax Bcl2-associated X protein 7 4 NM_007527 Mm00477631_m1 A5 ACGGAGGCTGGGATGCCTTTGTGGA Bcl2 B-cell leukemia/lymphoma 2 1 1 NM_009741 Mm00437783_m1 A6 GAACGGCGGCTGGGACACTTTTGTG Bcl2l1 Bcl2-like 1 2 2 NM_009743 Mm00437858_m1 A7 GACACTGAAGGTCGTGCCAGAAGGA C3 complement component 3 17 21 NM_009778 Mm00839967_g1 A8 CAGGGTGCCTGCTGTTGTGTTCACC Ccl19 chemokine (C-C motif) ligand 19 4 2 NM_011888 Mm00441242_m1 A9 TTGGCTCAGCCAGATGCAGTTAACG Ccl2 chemokine (C-C motif) ligand 2 11 1 NM_011333 Mm00441258_m1 A10 TCTTCTCAGCGCCATATGGAGCTGA Ccl3 chemokine (C-C motif) ligand 3 11 1 NM_011337 Hs99999901_s1 A11 GGAGGGCAAGTCTGGTGCCAGCAGC 18S Eukaryotic 18S rRNA N/A 1 N/A Mm01302428_m1 A12 TCTTGCAGTCGTGTTTGTCACTCGA Ccl5 chemokine (C-C motif) ligand 5 11 2 NM_013653 Mm99999051_gH A13 GACCTGCTCTTCCTGCTCACATTAC Ccr2 chemokine (C-C motif) receptor 2 9 N/A NM_009915 Mm00438271_m1 A14 AAGAGCAAGGCAGCTCAACTGTTCT Ccr4 chemokine (C-C motif) receptor 4 9 2 NM_009916 Mm00432608_m1 A15 GGACCCAGGGAAACCCAGGAAAAAC Ccr7 chemokine (C-C motif) receptor 7 11 1 NM_007719 Mm00515420_m1 A16 ATTGCAAGGTCAGCAGTGTGGCTCT Cd19 CD19 antigen 7 4 NM_009844 Mm00483137_m1 A17 TCTTCTCAGTTCAAGTAACAGAAAA Cd28 CD28 antigen 1 1 NM_007642 Mm00519283_m1 A18 TGAGTCTGCTGCATCTAAATAACTT Cd34 CD34 antigen 1 1 NM_133654 Mm00483146_m1 A19 GATAACTACAGGCCTGCCAGGTTTC Cd38 CD38 antigen 5 7 NM_007646 Mm00599683_m1 A20 CAGCCTCCTAGCTGTTGGCACTTGC Cd3e CD3 antigen, epsilon polypeptide 9 2 NM_007648 Mm00442754_m1 A21 ACACTCTCAGTGCTGGGTTTTCAGA Cd4 CD4 antigen 6 5 NM_013488 Mm00839636_g1 A22 ACACTTCGGGCCATGTTTCTCTTGC Cd68 CD68 antigen 11 5 NM_009853 Mm00711660_m1 A23 TCCATCAAAGCTGACTTCTCTACCC Cd80 CD80 antigen 16 2 NM_009855 Mm00444543_m1 A24 AATCAGCCTAGCAGGCCCAGCAACA Cd86 CD86 antigen 16 5 NM_019388 Mm01182107_g1 B1 CCGTGGCTCAGTGAAGGGGACCGGA Cd8a CD8 antigen, alpha chain N/A 2 N/A Mm00801606_m1 B2 CCTGGCCCAAAGGGTGAACCTGGTC Col4a5 procollagen, type IV, alpha 5 X 35 NM_007736 Mm00432688_m1 B3 AAGGATTCTATGCTGGGCACACAGG Csf1 colony stimulating factor 1 (macrophage) 3 9 NM_007778

Mm00438328_m1 B4 ACTGCCCCCCAACTCCGGAAACGGA Csf2 colony stimulating factor 2 (granulocyte-macrophage) 11 3 NM_009969 Mm00438334_m1 B5 TGGAGCAGTTGTGTGCCACCTACAA Csf3 colony stimulating factor 3 (granulocyte) 11 2 NM_009971 Mm00486849_m1 B6 TCTTCTCTGAAGCCATACAGGTGAC Ctla4 cytotoxic T-lymphocyte-associated protein 4 1 1 NM_009843 Mm00445235_m1 B7 GTGGGACTCAAGGGATCCCTCTCGC Cxcl10 chemokine (C-X-C motif) ligand 10 5 1 NM_021274 Mm00444662_m1 B8 CACAGCTGCTCAAGGCTTCCTTATG Cxcl11 chemokine (C-X-C motif) ligand 11 5 1 NM_019494 Mm00438259_m1 B9 CATGTACCTTGAGGTTAGTGAACGT Cxcr3 chemokine (C-X-C motif) receptor 3 X 1 NM_009910 Mm00487224_m1 B10 ATCTTTGGAGCTGGCTTTGACACAG Cyp1a2 cytochrome P450, family 1, subfamily a, polypeptide 2 9 2 NM_009993 Mm00484152_m1 B11 ACCTGCCAGTACTAGATAGCATCAT Cyp7a1 cytochrome P450, family 7, subfamily a, polypeptide 1 4 4 NM_007824 Mm01187091_m1 B12 CGAAGAAGACCTGTATTCCCCGCTG Ece1 endothelin converting enzyme 1 4 10 NM_199307 Mm00438656_m1 B13 TCCAGAAACAGCTGTCTTGGGAGCC Edn1 endothelin 1 13 1 NM_010104 Mm00433237_m1 B14 GGCTGTCCTGCCTCTGGTGCTTGCT Fas Fas (TNF receptor superfamily member) 19 1 NM_007987 Mm01256734_m1 B15 TCAGGACTCATGGTGGCCACTAAAT Fn1 fibronectin 1 1 34 NM_010233 Mm00446953_m1 B16 CCGCTACGGGAGTCGGGCCCAGTCT Gusb glucuronidase, beta 5 1 NM_010368 Mm00442834_m1 B17 CCTCCAGGACAAAGGCAGGGGAGAT Gzmb granzyme B 14 1 NM_013542 Mm00772352_m1 B18 GAGATACCTGGAGGCAATGCCTTCA H2-Ea histocompatibility 2, class II antigen E alpha 17 4 NM_010381 Mm00439221_m1 B19 CAGAGACTCCAGACCATGGTTTTTG H2-Eb1 histocompatibility 2, class II antigen E beta 17 1 NM_010382 Mm00516004_m1 B20 CACAGCCCGACAGCATGCCCCAGGA Hmox1 heme oxygenase (decycling) 1 8 1 NM_010442 Mm00446968_m1 B21 GGTTAAGGTTGCAAGCTTGCTGGTG Hprt1 hypoxanthine guanine phosphoribosyl 1 X 6 NM_013556 Mm00497600_m1 B22 AAAGTCTAGACTTGCAGGTGTGACC Icos inducible T-cell co-stimulator 1 4 NM_017480 Mm00801778_m1 B23 ACTATTTTAACTCAAGTGGCATAGA Ifng interferon gamma 10 1 NM_008337 Mm00833995_m1 B24 AGAAAAGTGAAGAACTGGTGGCCGA Ikbkb inhibitor of kappaB kinase beta 8 20 NM_010546 Mm00439616_m1 C1 ATGCGGCTGAGGCGCTGTCATCGAT Il10 interleukin 10 1 3 NM_010548 Mm00434165_m1 C2 GACATGGTGAAGACGGCCAGAGAAA Il12a interleukin 12a 3 3 NM_008351 Mm01288992_m1 C3 GAGTGGGATGTGTCCTCAGAAGCTA Il12b interleukin 12b 11 1 NM_008352 Mm00434204_m1 C4 CACAAGACCAGACTCCCCTGTGCAA Il13 interleukin 13 11 1 NM_008355 Mm00434210_m1 C5 TTCATTTTGGGCTGTGTCAGTGTAG Il15 interleukin 15 8 4 NM_008357 Mm00439619_m1 C6 TGGACTCTCCACCGCAATGAAGACC Il17 interleukin 17 1 2 NM_010552 Mm00434225_m1 C7 ATCAAAGTGCCAGTGAACCCCAGAC Il18 interleukin 18 9 4 NM_008360 Mm00439620_m1 C8 ACCTGCAACAGGAAGTAAAATTTGA Il1a interleukin 1 alpha 2 1 NM_010554 Mm00434228_m1 C9 CCAAAAGATGAAGGGCTGCTTCCAA Il1b interleukin 1 beta 2 3 NM_008361 Mm00434256_m1 C10 CTTGCCCAAGCAGGCCACAGAATTG Il2 interleukin 2 3 2 NM_008366 Mm00434261_m1 C11 CACCACCGATTTCTGGCTAGTGAGG Il2ra interleukin 2 receptor, alpha chain 2 4 NM_008367 Mm00439631_m1 C12 GACCCTCTCTGAGGAATAAGAGCTT Il3 interleukin 3 11 2 NM_010556 Mm00445259_m1 C13 GCAACGAAGAACACCACAGAGAGTG Il4 interleukin 4 11 2 NM_021283 Mm00439646_m1 C14 CATAAAAATCACCAGCTATGCATTG Il5 interleukin 5 11 2 NM_010558 Mm00446190_m1 C15 AGAAAAGAGTTGTGCAATGGCAATT Il6 interleukin 6 5 2 NM_031168

Mm00434291_m1 C16 GACCATGTTCCATGTTTCTTTTAGA Il7 interleukin 7 3 1 NM_008371 Mm00434305_m1 C17 GAACATCACGTGTCCGTCCTTTTCC Il9 interleukin 9 13 4 NM_008373 Mm99999915_g1 C18 GGTGTGAACGGATTTGGCCGTATTG Gapdh glyceraldehyde-3-phosphate dehydrogenase 6 2 NM_001001303 Mm01328172_g1 C19 CTATGCAGAGATGGACACTGAGCAA Lrp2 low density lipoprotein receptor-related protein 2 N/A 11 N/A Mm00440227_m1 C20 TGGGTCTGGTTCTCCACATGACACT Lta lymphotoxin A 17 1 NM_010735 Mm00476361_m1 C21 CTACCCACAGGTCAAAATTTGCAAC Nfkb1 nuclear factor of kappa light chain gene enhancer in B-cells 1 3 5 NM_008689 nuclear factor of kappa light polypeptide gene enhancer in Mm00479807_m1 C22 CGGAGACACGCCACTGCACCTGGCC Nfkb2 B-cells 2 19 14 NM_019408 Mm00440485_m1 C23 CACAAGGCCACATCGGATTTCACTT Nos2 nitric oxide synthase 2, inducible, macrophage 11 4 NM_010927 Mm00435617_m1 C24 GCCCATAGCTCCATGGTGGGTGTGA Pgk1 phosphoglycerate kinase 1 X 5 NM_008828 Mm00812512_m1 D1 GTCGCATGTACAGTTTTCGCCTGGT Prf1 perforin 1 (pore forming protein) 10 1 NM_011073 Mm00478374_m1 D2 GGGCCATGGAGTGGACTTAAATCAC Ptgs2 prostaglandin-endoperoxide synthase 2 1 5 NM_011198 Mm00448463_m1 D3 TGTCACAGGGCAAACACCTACACCC Ptprc protein tyrosine phosphatase, receptor type, C 1 3 NM_011210 Mm00441278_m1 D4 CCAGTCTGCAAAGCTGTCCAGTGTG Sele selectin, endothelial cell 1 7 NM_011345 Mm00441295_m1 D5 CCTCCCGAATGTCAAGCTGTGTCCT Selp selectin, platelet 1 3 NM_011347 Mm00448744_m1 D6 GCCCCGGGTCTCAGAGCCCCCAGCT Ski Sloan-Kettering viral oncogene homolog 4 1 NM_011385 Mm00489637_m1 D7 ACCACAGCATGGACGCAGGTTCTCC Smad3 MAD homolog 3 (Drosophila) 9 4 NM_016769 Mm00484741_m1 D8 TCAAACCAACTGCAGGCTGTCCAGA Smad7 MAD homolog 7 (Drosophila) 18 3 NM_008543 Mm00782550_s1 D9 CCCTTCCAGATCTGACCGGCTGCCG Socs1 suppressor of cytokine signaling 1 16 8 NM_009896 Mm00850544_g1 D10 ACTGCGCAGAATTCTCTCTTAAGGA Socs2 suppressor of cytokine signaling 2 10 10 NM_007706 Mm00439518_m1 D11 AAAGATTTAATCAGGCCCAGGAGGG Stat1 signal transducer and activator of transcription 1 1 5 NM_009283 Mm00456961_m1 D12 CACGGCAGCCCAGCAAGGGGGCCAG Stat3 signal transducer and activator of transcription 3 11 2 NM_213659 Mm00448890_m1 D13 GGAGTAAAGGAAACGAGGGCTGCCA Stat4 signal transducer and activator of transcription 4 1 13 NM_011487 Mm00447411_m1 D14 GCTGCCGAGGCACCCTGTATATCCC Stat6 signal transducer and activator of transcription 6 10 1 NM_009284 Mm00450960_m1 D15 AAGCAAGGACGGCGAATGTTCCCAT Tbx21 T-box 21 11 1 NM_019507 Mm00441941_m1 D16 ATTCTCTAACTTGTTTGGTGGGGAA Tfrc receptor 16 1 NM_011638 Mm00441724_m1 D17 TGGACCGCAACAACGCCATCTATGA Tgfb1 transforming growth factor, beta 1 7 1 NM_011577 Mm00443258_m1 D18 AAAGGGATGAGAAGTTCCCAAATGG Tnf tumor necrosis factor 17 1 NM_013693 Mm00437136_m1 D19 CAGCCTGTATGCTCCAGGCAAGGAG Tnfrsf18 tumor necrosis factor receptor superfamily, member 18 4 1 NM_009400 Mm00441895_m1 D20 GACAAGCTGTGAGGATAAGAACTTG Cd40 CD40 antigen 2 5 NM_170701 Mm00441911_m1 D21 TTGAAATGCAAAGAGGTGATGAGGA Cd40lg CD40 ligand X 3 NM_011616 Mm00438864_m1 D22 CCATTTAACAGGGAACCCCCACTCA Fasl (TNF superfamily, member 6) 1 3 NM_010177 Mm00449197_m1 D23 GGTGGAGGTCTACTCATTCCCTGAA Vcam1 vascular cell adhesion molecule 1 3 5 NM_011693 Mm00437304_m1 D24 ACCATGCCAAGTGGTCCCAGGCTGC Vegfa vascular endothelial growth factor A 17 1 NM_009505

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Appendix 2 Samples used for the microarray analyses. Individual RNA samples from each PR+/- or PRKO mouse used for pooled samples are shown. GC = granulosa cells; ovid = oviduct; COC = cumulus oocyte complex; RIN = RNA Integrity Number. # μl used Sample Tissue Geno Animal Sample in Total Microarray ID / cells -type # ng/μl microarray ng RNA ng/ul sample RIN 239 GC +/- 486 164.13 4.3 700 300 GC +/- 574 163.52 4.3 700 120 GC +/- 365 167.19 4.2 700 12.7 2100 164.93 GC1 8.7 242 GC +/- 493 164.98 4.2 700 272 GC +/- 523 175.8 4.0 700 199 GC +/- 381 152.04 4.6 700 12.8 2100 163.69 GC2 8.8 245 GC +/- 495 160.61 4.4 700 301 GC +/- 567 133.46 5.2 700 213 GC +/- 362 158.56 4.4 700 14.0 2100 149.81 GC3 9.0 248 GC +/- 496 104.9 6.7 700 306 GC +/- 568 113.75 6.2 700 278 GC +/- 525 166.46 4.2 700 17.0 2100 123.30 GC4 9.0 275 GC +/- 524 185.17 3.8 700 195 GC +/- 375 121.5 5.8 700 291 GC +/- 533 167.37 4.2 700 13.7 2100 153.02 GC5 9.1 117 GC KO 366 159.39 4.4 700 192 GC KO 405 168.18 4.2 700 220 GC KO 440 183.16 3.8 700 12.4 2100 169.69 GC6 8.7 118 GC KO 368 107.86 6.5 700 193 GC KO 370 154.46 4.5 700 269 GC KO 522 128.78 5.4 700 16.5 2100 127.60 GC7 9.2 121 GC KO 396 103.25 6.8 700 194 GC KO 409 121.81 5.7 700 110 GC KO 382 177.08 4.0 700 16.5 2100 127.43 GC8 8.9 122 GC KO 354 168.01 4.2 700 202 GC KO 407 173.51 4.0 700 124 GC KO 353 185.3 3.8 700 12.0 2100 175.32 GC9 8.8 123 GC KO 398 175.34 4.0 700 219 GC KO 434 175.47 4.0 700 299 GC KO 573 154.91 4.5 700 12.5 2100 168.00 GC10 8.6

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Appendix 2 – Continued # μl used Sample Tissue/ Geno Animal Sample in Total Microarray ID cells -type # ng/μl microarray ng RNA ng/ul sample RIN 143 Oviduct +/- 362 187.08 3.7 700 289 Oviduct +/- 533 156.08 4.5 700 311 Oviduct +/- 581 164.49 4.3 700 12.5 2100 168.24 Ovid1 9.1 274 Oviduct +/- 523 217.97 3.2 700 241 Oviduct +/- 486 179.74 3.9 700 313 Oviduct +/- 584 146.41 4.8 700 11.9 2100 176.66 Ovid2 9.1 277 Oviduct +/- 524 227.88 3.1 700 244 Oviduct +/- 493 137.39 5.1 700 304 Oviduct +/- 567 178.79 3.9 700 12.1 2100 173.81 Ovid3 9.4 280 Oviduct +/- 525 164.14 4.3 700 247 Oviduct +/- 495 115.09 6.5 700 149 Oviduct +/- 376 195.57 3.6 700 14.3 2100 146.87 Ovid4 9.1 250 Oviduct +/- 496 207.57 3.4 700 139 Oviduct +/- 365 194.57 3.6 700 305 Oviduct +/- 574 108.45 6.1 700 13.1 2100 160.89 Ovid5 9.6 85 Oviduct KO 353 204.4 3.4 700 157 Oviduct KO 382 201.33 3.5 700 230 Oviduct KO 405 174.21 4.0 700 10.9 2100.0 +2μl H2O 12.9 2100 162.5 Ovid6 8.1 77 Oviduct KO 409 205.4 3.4 700 163 Oviduct KO 398 176.98 4.0 700 233 Oviduct KO 407 185.49 3.8 700 11.1 2100 +2μl H2O 13.1 2100 159.9 Ovid7 8.2 82 Oviduct KO 440 204.92 3.4 700 147 Oviduct KO 366 193.15 3.6 700 290 Oviduct KO 532 177.59 3.9 700 11.0 2100 +2μl H2O 13.0 2100 161.8 Ovid8 8.4 84 Oviduct KO 434 164.62 4.3 700 145 Oviduct KO 368 167.13 4.2 700 226 Oviduct KO 370 195.52 3.6 700 12.0 2100 +1μl H2O 13.0 2100 161.3 Ovid9 8.7 92 Oviduct KO 354 180.11 3.9 700 8 Oviduct KO 433 207.49 3.4 700 164 Oviduct KO 396 180.76 3.9 700 11.1 2100 +2μl H2O 13.1 2100 159.9 Ovid10 8.1

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Appendix 2 – Continued # μl used Sample Tissue Geno Animal Sample in Total Microarray ID / cells -type # ng/μl microarray ng RNA ng/ul sample RIN 246 COC +/- 495 123.2 4.9 600 243 COC +/- 493 94.64 6.3 600 249 COC +/- 496 96.66 6.2 600 17.4 1800 103.35 COC1 8.5 292 COC +/- 533 176.07 3.4 600 63 COC +/- 465 86.23 7.0 600 273 COC +/- 523 85.82 7.0 600 17.4 1800 103.70 COC2 8.4 240 COC +/- 486 159.65 3.8 600 276 COC +/- 524 64.23 9.3 600 66 COC +/- 376 44.60 13.5 600 26.6 1800 67.79 COC3 8.9 135 COC +/- 466 158.45 3.8 600 62 COC +/- 365 57.36 10.5 600 279 COC +/- 525 48.55 12.4 600 26.6 1800 67.66 COC4 8.4 71 COC KO 353 185.59 3.2 600 181 COC KO 368 132.18 4.5 600 293 COC KO 532 71.63 8.4 600 16.1 1800 111.46 COC5 8.3 185 COC KO 407 171.63 3.5 600 126 COC KO 366 150.94 4.0 600 49 COC KO 440 95.42 6.3 600 13.8 1800 130.82 COC6 8.7 216 COC KO 398 168.78 3.6 600 57 COC KO 434 122.08 4.9 600 132 COC KO 354 73.89 8.1 600 16.6 1800 108.50 COC7 9.0 190 COC KO 409 165.72 3.6 600 127 COC KO 405 156.79 3.8 600 129 COC KO 382 114.16 5.3 600 12.7 1800 141.70 COC8 9.2

Lisa Akison 2012

Appendix 3 List of differentially expressed genes (P<0.05) from the granulosa cell microarray. Adjusted (‘Stepup’) P-value given from False Discovery Rate Correction. Negative fold change indicates PRKO down-regulated relative to PR+/-; positive fold change indicates PRKO up-regulated relative to PR+/-. RefSeq = Reference Sequence. Gene symbols are as reported for the Affymetrix GeneChip® Mouse Gene 1.0 ST Arrays (Affymetrix, Santa Clara, USA; 2009). Genes are sorted from lowest to highest P-value (i.e. most significant to least significant). Probeset Gene Stepup (P-value Fold-Change ID Gene Name Symbol RefSeq (KO vs. +/-)) (KO vs. +/-)

1 10463070 ectonucleoside triphosphate diphosphohydrolase 1 Entpd1 NM_009848 7.77E-05 -3.1707 2 10498024 solute carrier family 7 (cationic amino acid transporter, y+ system) member 11 Slc7a11 NM_011990 9.47E-05 -7.5591 3 10531919 hydroxysteroid (17-beta) dehydrogenase 11 Hsd17b11 NM_053262 9.47E-05 -6.5212 4 10476512 synaptosomal-associated protein 25 Snap25 NM_011428 9.47E-05 -3.2078 5 10573626 glutamic pyruvate transaminase (alanine aminotransferase) 2 Gpt2 NM_173866 0.00010 -4.7675 6 10568873 a disintegrin and metallopeptidase domain 8 Adam8 NM_007403 0.00010 -3.4781 7 10567043 related RAS viral (r-ras) oncogene homolog 2 Rras2 NM_025846 0.00010 -2.3339 8 10352905 CD34 antigen Cd34 NM_001111059 0.00014 -2.6770 9 10382802 sphingosine kinase 1 Sphk1 NM_011451 0.00019 -2.7980 10 10350753 glutamate-ammonia (glutamine synthetase) Glul NM_008131 0.00025 -2.8799 11 10405822 cell cycle related kinase Ccrk NM_053180 0.00026 -2.0308 12 10354207 cellular repressor of E1A-stimulated genes 2 Creg2 NM_170597 0.00030 -1.7093 13 10593225 zinc finger and BTB domain containing 16 Zbtb16 NM_001033324 0.00032 -13.7345 14 10357472 chemokine (C-X-C motif) receptor 4 Cxcr4 NM_009911 0.00032 -3.4756 15 10354168 TBC1 domain family, member 8 Tbc1d8 NM_018775 0.00035 -3.5541 16 10576911 ephrin B2 Efnb2 NM_010111 0.00049 -3.7175 17 10494043 tudor and KH domain containing protein Tdrkh NM_028307 0.00049 -3.4170 18 10554269 abhydrolase domain containing 2 Abhd2 NM_018811 0.00049 -2.7182 19 10527936 frizzled homolog 1 (Drosophila) Fzd1 NM_021457 0.00056 -2.0453 20 10493873 small proline-rich protein 2G Sprr2g NR_003548 0.00059 -4.0126 21 10606989 TSC22 domain family, member 3 Tsc22d3 NM_001077364 0.00064 -2.6920 22 10369604 vacuolar protein sorting 26 homolog A (yeast) Vps26a NM_133672 0.00075 -2.1556 23 10377215 growth arrest specific 7 Gas7 NM_008088 0.00083 -3.5699 24 10527870 klotho Kl NM_013823 0.00097 -2.8830 25 10575976 cysteine-rich secretory protein LCCL domain containing Crispld2 NM_030209 0.00098 -2.2351 26 10484283 phosphodiesterase 1A, calmodulin-dependent Pde1a NM_016744 0.00112 -1.9027 27 10448269 zinc finger protein 13 Zfp13 NM_011747 0.00112 -1.6856 28 10400143 syntaxin binding protein 6 (amisyn) Stxbp6 NM_144552 0.00113 -2.4634

29 10464836 actinin alpha 3 Actn3 NM_013456 0.00115 -2.1455 30 10554693 StAR-related lipid transfer (START) domain containing 5 Stard5 NM_023377 0.00126 -2.4531 31 10405163 spindlin 1 Spin1 NM_146043 0.00133 -1.2746 32 10466075 transmembrane protein 132A Tmem132a NM_133804 0.00136 1.4209 33 10500021 cingulin Cgn NM_001037711 0.00136 -3.5274 34 10546661 forkhead box P1 Foxp1 NM_053202 0.00137 -1.7882 35 10492310 muscleblind-like 1 (Drosophila) Mbnl1 NM_020007 0.00142 -1.4080 36 10463911 adducin 3 (gamma) Add3 NM_013758 0.00153 -1.9701 37 10430179 apolipoprotein L 7b Apol7b NM_001024848 0.00161 -2.0430 38 10577808 transforming, acidic coiled-coil containing protein 1 Tacc1 NM_177089 0.00161 -1.9800 39 10443449 potassium channel tetramerisation domain containing 20 Kctd20 NM_025888 0.00161 -1.3283 40 10409162 sushi domain containing 3 Susd3 NM_025491 0.00170 -2.3737 41 10454198 ring finger protein 125 Rnf125 NM_026301 0.00173 -3.7550 42 10438769 claudin 1 Cldn1 NM_016674 0.00173 -3.0150 43 10457323 mohawk Mkx NM_177595 0.00173 -2.8130 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, 44 10462237 subfamily a, member 2 Smarca2 NM_011416 0.00173 -1.6713 45 10520782 zinc finger protein 512 Zfp512 NM_172993 0.00173 -1.5716 46 10392440 solute carrier family 16, member 6 (monocarboxylic acid transporter 7) Slc16a6 NM_001029842 0.00186 -2.0131 47 10440522 ADAM metallopeptidase with thrombospondin type 1 motif, 1 Adamts1 NM_009621 0.00193 -2.5762 48 10603492 porcupine homolog (Drosophila) Porcn NM_016913 0.00193 -2.2888 49 10374366 epidermal growth factor receptor Egfr NM_207655 0.00203 -2.0191 50 10501229 glutathione S-transferase, mu 1 Gstm1 NM_010358 0.00205 -2.3326 51 10530503 cyclic nucleotide gated channel alpha 1 Cnga1 NM_007723 0.00241 -1.4029 52 10381474 ADP-ribosylation factor-like 4D Arl4d NM_025404 0.00254 -4.3798 53 10529801 F-box and leucine-rich repeat protein 5 Fbxl5 NM_178729 0.00258 -1.5127 54 10500837 DNA cross-link repair 1B (PSO2 homolog, S. cerevisiae) Dclre1b NM_133865 0.00272 -2.0147 55 10414374 kinectin 1 Ktn1 NM_008477 0.00272 -1.9746 56 10448081 RGM domain family, member B Rgmb NM_178615 0.00272 2.1630 57 10380285 transmembrane protein 100 Tmem100 NM_026433 0.00277 -5.3345 58 10504017 nuclear transcription factor, X-box binding 1 Nfx1 NM_023739 0.00277 -1.8221 59 10477147 histocompatibility 13 H13 NM_010376 0.00277 1.3690 60 10573979 guanine nucleotide binding protein, alpha O Gnao1 NM_010308 0.00282 -3.6084 61 10498076 mastermind like 3 (Drosophila) Maml3 NM_001004176 0.00282 -3.0398 62 10460263 aspartoacylase (aminoacylase) 3 Acy3 NM_027857 0.00305 -1.4175

63 10397054 WD repeat domain 21 Wdr21 NM_030246 0.00338 -1.6511 64 10438189 solute carrier family 7 (cationic amino acid transporter, y+ system), member 4 Slc7a4 NM_144852 0.00346 -1.4358 65 10581865 lactate dehydrogenase D Ldhd NM_027570 0.00346 -2.6442 66 10430945 polymerase (DNA-directed), delta interacting protein 3 Poldip3 NM_178627 0.00346 -1.4874 67 10411958 ring finger protein 180 Rnf180 NM_027934 0.00361 -2.1572 68 10352777 solute carrier family 30 (zinc transporter), member 1 Slc30a1 NM_009579 0.00386 1.4068 69 10366266 PRKC, apoptosis, WT1, regulator Pawr NM_054056 0.00390 -1.5719 70 10491038 transducin (beta)-like 1X-linked receptor 1 Tbl1xr1 NM_030732 0.00390 -1.5553 71 10392347 phosphatidylinositol transfer protein, cytoplasmic 1 Pitpnc1 NM_145823 0.00409 -2.1853 72 10534889 HIV-1 Rev binding protein-like Hrbl NM_178162 0.00409 -2.1182 73 10494957 adaptor-related protein complex AP-4, beta 1 Ap4b1 NM_026193 0.00409 -1.8073 74 10587266 glutamate-cysteine ligase, catalytic subunit Gclc NM_010295 0.00409 -1.7536 75 10436209 Casitas B-lineage lymphoma b Cblb NM_001033238 0.00409 -1.7408 76 10565935 Rho guanine nucleotide exchange factor (GEF) 17 Arhgef17 NM_001081116 0.00409 1.3770 77 10607169 transient receptor potential cation channel, subfamily C, member 5 Trpc5 NM_009428 0.00448 -1.9238 78 10466712 MAM domain containing 2 Mamdc2 NM_174857 0.00468 -1.8459 79 10505073 zinc finger protein 462 Zfp462 NM_172867 0.00468 -1.7277 80 10574976 lysophospholipase 3 Lypla3 NM_133792 0.00510 -1.7724 81 10539517 dysferlin Dysf NM_021469 0.00512 -2.0700 82 10361381 synaptic nuclear envelope 1 Syne1 NM_001079686 0.00552 -2.1899 83 10489357 junctophilin 2 Jph2 NM_021566 0.00561 -1.5241 84 10472097 formin-like 2 Fmnl2 NM_172409 0.00561 -1.4802 85 10585778 semaphorin 7A, GPI membrane anchor (John Milton Hagen blood group) Sema7a NM_011352 0.00561 1.7506 86 10520950 PDZ and LIM domain 1 (elfin) Pdlim1 NM_016861 0.00574 -2.1859 87 10494023 RAR-related orphan receptor gamma Rorc NM_011281 0.00574 -1.6544 88 10426479 anoctamin 6 Ano6 NM_175344 0.00574 -1.4170 89 10574023 metallothionein 2 Mt2 NM_008630 0.00604 -2.8766 90 10523674 nudix (nucleoside diphosphate linked moiety X)-type motif Nudt9 NM_028794 0.00616 -2.8589 91 10589329 6-phosphofructo-2-kinase/fructose-2~6-biphosphatase 4 Pfkfb4 NM_173019 0.00616 -1.8470 92 10476893 GDNF-inducible zinc finger protein 1 Gzf1 NM_028986 0.00616 -1.7059 93 10547386 adiponectin receptor 2 Adipor2 NM_197985 0.00636 -1.4826 94 10389526 clathrin, heavy polypeptide (Hc) Cltc NM_001003908 0.00646 -1.3392 95 10500813 homeodomain interacting protein kinase 1 Hipk1 NM_010432 0.00680 -1.5494 96 10543369 Ca2+-dependent activator protein for secretion 2 Cadps2 NM_153163 0.00683 -1.9544

97 10544114 homeodomain interacting protein kinase 2 Hipk2 NM_010433 0.00690 -1.7677 98 10362633 REV3-like, catalytic subunit of DNA polymerase zeta RAD54 Rev3l NM_011264 0.00690 -1.4368 99 10359816 pogo transposable element with KRAB domain Pogk NM_175170 0.00741 1.4826 100 10594590 sorting nexin 1 Snx1 NM_019727 0.00758 -1.4529 101 10522467 RAS-like, family 11, member B Rasl11b NM_026878 0.00765 1.6113 102 10429391 solute carrier family 45, member 4 Slc45a4 NM_001033219 0.00777 -1.8860 103 10581455 RNA binding motif protein 35b Rbm35b NM_176838 0.00805 -2.5681 104 10373918 leukemia inhibitory factor Lif NM_008501 0.00805 -1.5717 105 10366004 ATPase, Ca++ transporting, plasma membrane 1 Atp2b1 NM_026482 0.00805 -1.4681 106 10402136 G protein-coupled receptor 68 Gpr68 NM_175493 0.00826 -1.6989 107 10506714 low density lipoprotein receptor-related protein 8, apolipoprotein e receptor Lrp8 NM_053073 0.00877 -2.2629 108 10469581 enhancer trap 4 Etl4 NM_001081006 0.00891 -2.0301 109 10459389 S-adenosylmethionine decarboxylase 1 Amd1 CT010192 0.00900 -1.5805 110 10512895 bile acid-Coenzyme A: amino acid N- Baat NM_007519 0.00900 -1.4489 111 10400718 Son of sevenless homolog 2 (Drosophila) Sos2 ENSMUST00000035773 0.00900 -1.4437 112 10458355 amyloid beta (A4) precursor protein-binding, family B, member 3 Apbb3 NM_146085 0.00900 -1.4293 113 10506301 leptin receptor Lepr NM_001122899 0.00915 -3.0562 114 10389858 non-metastatic cells 2, protein (NM23B) expressed in Nme2 NM_008705 0.00953 1.3144 115 10445826 molybdenum synthesis 1 Mocs1 NM_020042 0.00975 -1.8532 116 10505489 pregnancy-associated plasma protein A Pappa NM_021362 0.00975 1.8704 117 10588263 solute carrier organic anion transporter family, member Slco2a1 NM_033314 0.00991 -3.6604 118 10589773 lupus brain antigen 1 Lba1 BC086653 0.00997 -2.3663 119 10445268 G protein-coupled receptor 116 Gpr116 NM_001081178 0.01028 -1.9480 120 10500011 tuftelin 1 Tuft1 NM_011656 0.01045 -1.6408 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, 121 10604347 subfamily a, member 1 Smarca1 NM_053123 0.01124 -2.0042 122 10374478 SERTA domain containing 2 Sertad2 NM_021372 0.01124 1.2692 123 10528794 spermatogenesis associated glutamate (E)-rich protein 4a Speer4a NM_029376 0.01124 1.7365 124 10462091 Kruppel-like factor 9 Klf9 NM_010638 0.01131 -2.0579 125 10540028 Kruppel-like factor 15 Klf15 NM_023184 0.01191 -1.5603 126 10606941 ripply1 homolog (zebrafish) Ripply1 NM_001037915 0.01203 -1.6044 127 10443764 solute carrier family 37 (glycerol-3-phosphate transporter), member 1 Slc37a1 NM_153062 0.01214 1.1628 128 10577954 RAB11 family interacting protein 1 (class I) Rab11fip1 NM_001080813 0.01214 -2.0100 129 10345777 interleukin 1 receptor-like 2 Il1rl2 NM_133193 0.01264 -2.7330 130 10371356 adaptor protein, phosphotyrosine interaction, PH domain and Appl2 NM_145220 0.01264 -1.5649

containing 2 131 10446537 l(3)mbt-like 4 (Drosophila) L3mbtl4 BC147119 0.01264 -1.5236 132 10377181 myosin, heavy polypeptide 13, skeletal muscle Myh13 NM_001081250 0.01264 -1.2873 133 10505092 RAD23b homolog (S. cerevisiae) Rad23b NM_009011 0.01264 -1.2804 134 10453272 zinc finger protein 36, C3H type-like 2 Zfp36l2 NM_001001806 0.01264 1.2430 135 10412882 beta Thrb NM_009380 0.01264 1.4224 136 10604451 ecto-NOX disulfide-thiol exchanger 2 Enox2 NM_145951 0.01276 -1.1499 137 10447317 endothelial PAS domain protein 1 (Hif2a) Epas1 NM_010137 0.01317 -3.3908 138 10557177 protein kinase C, beta Prkcb NM_008855 0.01318 1.7688 139 10538373 proline rich 15 Prr15 NM_030024 0.01325 -1.4244 140 10498018 protocadherin 18 Pcdh18 NM_130448 0.01336 -1.8620 141 10603208 midline 1 Mid1 NM_010797 0.01336 -1.3529 142 10494092 pogo transposable element with ZNF domain Pogz NM_172683 0.01374 -1.5677 143 10383932 growth arrest-specific 2 like 1 Gas2l1 NM_030228 0.01393 -2.1366 144 10379891 protein phosphatase 1D magnesium-dependent, delta isoform Ppm1d NM_016910 0.01416 -1.3811 145 10535956 StAR-related lipid transfer (START) domain containing 13 Stard13 NM_146258 0.01438 -1.6775 146 10487453 nephronophthisis 1 (juvenile) homolog (human) Nphp1 NM_016902 0.01441 -1.3576 147 10399337 kelch-like 29 (Drosophila) Klhl29 BC145748 0.01471 -1.3490 148 10457733 UDP-Gal:betaGlcNAc beta 1,4-galactosyltransferase, polypeptide 6 B4galt6 NM_019737 0.01475 -2.4530 149 10578922 kelch-like 2, Mayven (Drosophila) Klhl2 NM_178633 0.01500 -1.5099 150 10492798 secreted frizzled-related protein 2 Sfrp2 NM_009144 0.01512 2.8393 151 10578287 CCR4-NOT transcription complex, subunit 7 Cnot7 NM_011135 0.01513 -1.3621 152 10468489 X-prolyl aminopeptidase (aminopeptidase P) 1, soluble Xpnpep1 NM_133216 0.01551 -1.6394 153 10565996 inositol polyphosphate phosphatase-like 1 Inppl1 NM_010567 0.01554 1.2857 154 10352756 lysophosphatidylglycerol acyltransferase 1 Lpgat1 NM_172266 0.01565 -1.7384 155 10410995 RAS protein-specific guanine nucleotide-releasing factor Rasgrf2 NM_009027 0.01589 1.7884 156 10528834 spermatogenesis associated glutamate (E)-rich protein 4b Speer4b NM_028561 0.01628 1.3948 157 10416023 scavenger receptor class A, member 5 (putative) Scara5 NM_028903 0.01649 -3.4423 158 10458589 PRELI domain containing 2 Prelid2 NM_029942 0.01649 1.4055 159 10571567 sorbin and SH3 domain containing 2 Sorbs2 NM_172752 0.01659 -2.9565 160 10466573 osteoclast stimulating factor 1 Ostf1 NM_017375 0.01659 -1.9214 161 10531899 kelch-like 8 (Drosophila) Klhl8 NM_178741 0.01713 -1.3977 162 10477140 rad and gem related GTP binding protein 1 Rem1 NM_009047 0.01733 1.5244 163 10362615 Traf3 interacting protein 2 Traf3ip2 NM_134000 0.01760 -1.6595

164 10509463 eukaryotic translation initiation factor 4 gamma, 3 Eif4g3 NM_172703 0.01760 -1.5017 165 10521356 hepatocyte growth factor activator Hgfac NM_019447 0.01797 -1.4010 166 10495111 WD repeat domain 77 Wdr77 NM_027432 0.01867 1.1704 167 10603182 Rho GTPase activating protein 6 Arhgap6 NM_009707 0.01869 1.5949 168 10410931 versican Vcan NM_001081249 0.01877 -1.3157 169 10584541 zinc finger protein 202 Zfp202 NM_030713 0.01877 1.4551 170 10453604 BMP and activin membrane-bound inhibitor, homolog (Xenopus laevis) Bambi NM_026505 0.01905 1.4291 171 10513256 lysophosphatidic acid receptor 1 Lpar1 NM_010336 0.01913 -1.8863 172 10521057 macrophage erythroblast attacher Maea NM_021500 0.01948 -1.2087 173 10578880 tolloid-like Tll1 NM_009390 0.01976 -1.9093 174 10462281 very low density lipoprotein receptor Vldlr NM_013703 0.01976 -1.6276 175 10394186 dystrobrevin, beta Dtnb NM_007886 0.01976 -1.5785 176 10530029 leucine-rich repeat LGI family, member 2 Lgi2 NM_144945 0.01976 1.7198 177 10543145 thrombospondin, type I, domain containing 7A Thsd7a AK173072 0.02075 -1.8441 178 10513922 RAS and EF hand domain containing Rasef NM_001017427 0.02085 -1.3602 179 10590918 angiomotin-like 1 Amotl1 NM_001081395 0.02152 -1.7217 180 10579894 Hedgehog-interacting protein Hhip NM_020259 0.02152 -1.6613 181 10567010 dickkopf homolog 3 (Xenopus laevis) Dkk3 NM_015814 0.02192 1.3339 182 10435693 cytochrome c oxidase, assembly homolog (S. cerevisiae) Cox17 NM_001017429 0.02209 1.3055 183 10587748 ADAM metallopeptidase with thrombospondin type 1 motif, 7 Adamts7 NM_001003911 0.02213 1.4003 184 10473491 olfactory receptor 1033 Olfr1033 NM_146578 0.02221 -1.5935 185 10346607 frizzled homolog 7 (Drosophila) Fzd7 NM_008057 0.02267 1.5573 186 10570432 ribosomal protein L27a Rpl27a AF357390 0.02283 1.2853 187 10370303 adenosine deaminase, RNA-specific, B1 Adarb1 NR_004429 0.02283 -1.3822 188 10522368 NIPA-like domain containing 1 Npal1 NM_001081205 0.02288 -1.7558 189 10368886 forkhead box O3a Foxo3a ENSMUST00000105502 0.02288 -1.6171 190 10439483 CDC42 GTPase-activating protein Cdgap NM_020260 0.02301 -1.8504 191 10525134 RAS protein activator like 1 (GAP1 like) Rasal1 NM_013832 0.02301 2.0062 192 10523647 AF4/FMR2 family, member 1 Aff1 NM_001080798 0.02338 -1.4671 193 10585194 interleukin 18 Il18 NM_008360 0.02338 1.3299 194 10377439 period homolog 1 (Drosophila) Per1 NM_011065 0.02358 -1.6224 195 10408280 leucine rich repeat containing 16A Lrrc16a NM_026825 0.02358 -1.2263 196 10355514 tensin 1 Tns1 BC055076 0.02392 -1.6215 197 10393395 splicing factor, arginine/serine-rich 2 (SC-35) Sfrs2 NM_011358 0.02513 1.1860

198 10362538 laminin, alpha 4 Lama4 NM_010681 0.02520 1.6832 199 10427796 natriuretic peptide receptor 3 Npr3 NM_008728 0.02520 3.3490 200 10598743 nyctalopin Nyx NM_173415 0.02588 -1.9768 Alport syndrome, mental retardation, midface hypoplasia and elliptocytosis 201 10607116 chromosomal region gene 1 Ammecr1 NM_019496 0.02606 -1.6890 202 10405174 nucleoredoxin-like 2 Nxnl2 NM_029173 0.02606 -1.3692 203 10447799 insulin-like growth factor 2 receptor Igf2r NM_010515 0.02606 1.3018 204 10356020 dedicator of cytokinesis 10 Dock10 NM_175291 0.02621 -1.4707 205 10374356 V-set and transmembrane domain containing 2A Vstm2a NM_145967 0.02637 -1.2518 206 10541075 chemokine (C-X-C motif) ligand 12 Cxcl12 NM_001012477 0.02637 1.4411 207 10578572 storkhead box 2 Stox2 NM_001114311 0.02697 -1.6538 208 10539017 receptor accessory protein 1 Reep1 NM_178608 0.02697 -1.4459 209 10487937 prokineticin receptor 2 Prokr2 NM_144944 0.02697 1.3420 210 10491885 protocadherin 10 Pcdh10 NM_001098171 0.02772 -1.7974 tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, 211 10494662 eta polypeptide Ywhah ENSMUST00000019109 0.02772 -1.3704 212 10425527 E1A binding protein p300 Ep300 NM_177821 0.02772 -1.2163 213 10604165 reproductive homeobox 11 Rhox11 NM_198598 0.02772 -1.2155 214 10561831 zinc finger protein 566 Zfp566 NM_152814 0.02772 1.3654 215 10351491 olfactomedin-like 2B Olfml2b NM_177068 0.02772 2.8525 216 10585005 apolipoprotein A-I Apoa1 NM_009692 0.02786 -2.2031 217 10410124 cathepsin L Ctsl NM_009984 0.02806 -1.4491 218 10462303 potassium channel, subfamily V, member 2 Kcnv2 NM_183179 0.02857 -1.3520 219 10570614 defensin beta 6 Defb6 NM_054074 0.02857 -1.2327 220 10530870 Eph receptor A5 Epha5 NM_007937 0.02857 2.0419 pleckstrin homology domain containing, family G (with RhoGef domain) 221 10510643 member 5 Plekhg5 NM_001004156 0.02894 1.2355 222 10580274 ribonuclease H2, large subunit Rnaseh2a NM_027187 0.02894 -1.5759 223 10365428 BTB (POZ) domain containing 11 Btbd11 NM_028709 0.02894 -1.4046 224 10603011 retinoblastoma binding protein 7 Rbbp7 NM_009031 0.02894 -1.2951 225 10445422 solute carrier family 35, member B2 Slc35b2 NM_028662 0.02894 1.2084 226 10555438 FCH and double SH3 domains 2 Fchsd2 NM_199012 0.02894 1.2529 227 10548899 RAS-like, estrogen-regulated, growth-inhibitor Rerg NM_181988 0.02894 1.4180 228 10539592 SET and MYND domain containing 5 Smyd5 NM_144918 0.02906 1.2117 229 10398211 hedgehog interacting protein-like 1 Hhipl1 NM_001044380 0.02956 -1.3880 230 10456522 transcription factor 4 Tcf4 NM_013685 0.02956 -1.2190

231 10503902 cannabinoid receptor 1 (brain) Cnr1 NM_007726 0.02956 1.4082 232 10595327 pleckstrin homology domain interacting protein Phip NM_001081216 0.02969 -1.3087 233 10438585 transmembrane protein 41a Tmem41a NM_025693 0.03033 1.2104 234 10481056 Notch gene homolog 1 (Drosophila) Notch1 NM_008714 0.03072 1.5176 235 10412038 zinc finger, SWIM domain containing 6 Zswim6 BC021311 0.03145 1.1565 236 10530627 leucine rich repeat containing 66 Lrrc66 BC031901 0.03176 -1.2213 237 10425031 apolipoprotein L 6 Apol6 ENSMUST00000048285 0.03186 -2.4710 238 10535938 NEDD4 binding protein 2-like 1 N4bp2l1 NM_133898 0.03186 -1.4848 239 10561527 actinin alpha 4 Actn4 NM_021895 0.03186 -1.2339 240 10449631 BTB (POZ) domain containing 9 Btbd9 NM_027060 0.03186 1.1320 241 10498386 immunoglobulin superfamily, member 10 Igsf10 ENSMUST00000097075 0.03186 1.7574 242 10501222 glutathione S-transferase, mu 2 Gstm2 NM_008183 0.03236 -1.6540 243 10389373 amyloid beta precursor protein (cytoplasmic tail) binding protein 2 Appbp2 NM_025825 0.03243 -1.3100 244 10512904 aldolase B, fructose-bisphosphate Aldob NM_144903 0.03255 -2.7062 245 10495083 potassium voltage-gated channel, Shal-related subfamily, member 3 Kcnd3 NM_001039347 0.03294 1.4878 246 10387100 gene model 879, (NCBI) Gm879 NM_001034874 0.03307 1.9042 247 10516325 ADP-ribosylhydrolase like 2 Adprhl2 NM_133883 0.03311 1.2107 248 10482766 reprimo, TP53 dependent G2 arrest mediator candidate Rprm NM_023396 0.03311 1.6573 249 10413059 vinculin Vcl NM_009502 0.03322 -1.3278 250 10531588 protein kinase, cGMP-dependent, type II (cGKII) Prkg2 NM_008926 0.03468 -1.9580 251 10568464 arginyltransferase 1 Ate1 NM_013799 0.03468 -1.7363 252 10412624 PX domain containing serine/threonine kinase Pxk NM_178279 0.03490 -1.3679 253 10520043 lipoma HMGIC fusion partner-like 3 Lhfpl3 NM_001081231 0.03517 -1.5728 254 10570472 ceroid-lipofuscinosis, neuronal 8 Cln8 NM_012000 0.03517 -1.3077 255 10445241 tumor necrosis factor receptor superfamily, member 21 / Tnfrsf21 NM_178589 0.03527 -1.4027 256 10586039 transducin-like enhancer of split 3 (E(sp1) homolog, Drosophila) Tle3 NM_001083927 0.03531 -1.4518 257 10366409 coiled-coil domain containing 131 Ccdc131 NM_001033261 0.03531 -1.3963 258 10467420 PDZ and LIM domain 1 (elfin) Pdlim1 NM_016861 0.03563 -1.9924 259 10406551 single-stranded DNA binding protein 2 Ssbp2 NM_024272 0.03563 -1.6753 260 10355536 tensin 1 Tns1 ENSMUST00000050681 0.03563 -1.5072 261 10367413 DnaJ (Hsp40) homolog, subfamily C, member 14 Dnajc14 NM_028873 0.03563 -1.1413 262 10574246 G protein-coupled receptor 114 Gpr114 NM_001033468 0.03614 -1.1426 263 10420913 a disintegrin and metallopeptidase domain 2 Adam2 NM_009618 0.03656 -2.0980 264 10394892 cleavage and polyadenylation specificity factor 3 Cpsf3 NM_018813 0.03690 -1.1207

265 10453256 potassium voltage-gated channel, subfamily G, member 3 Kcng3 NM_153512 0.03740 -1.8494 266 10537770 zyxin Zyx NM_011777 0.03864 -1.4228 267 10391461 breast cancer 1 Brca1 NM_009764 0.03877 -1.4237 268 10451061 runt related transcription factor 2 Runx2 NM_009820 0.03888 -1.7409 269 10535021 glypican 2 (cerebroglycan) Gpc2 NM_172412 0.03999 1.3654 270 10494565 flavin containing monooxygenase 5 Fmo5 NM_010232 0.04030 -1.1914 271 10350896 astrotactin 1 Astn1 NM_007495 0.04108 1.5800 272 10482968 phospholipase A2 receptor 1 Pla2r1 NM_008867 0.04114 -2.1387 273 10567645 glutamyl-tRNA synthetase 2 (mitochondrial)(putative) Ears2 NM_026140 0.04114 1.3064 274 10367400 matrix metallopeptidase 19 Mmp19 NM_021412 0.04135 -2.4518 275 10492689 platelet-derived growth factor, C polypeptide Pdgfc NM_019971 0.04137 -1.3497 276 10578829 palladin, cytoskeletal associated protein Palld NM_001081390 0.04209 1.4969 277 10482500 Rho family GTPase 3 Rnd3 NM_028810 0.04254 -1.8997 278 10436182 CD47 molecule Cd47 NM_010581 0.04254 -1.4978 279 10604564 glypican 4 Gpc4 NM_008150 0.04311 -1.3699 280 10467425 sorbin and SH3 domain containing 1 Sorbs1 NM_178362 0.04338 -1.6644 281 10578771 UDP-N-acetyl-alpha-D-galactosamine: polypeptide N-acetylg Galnt7 NM_144731 0.04338 -1.3402 282 10392388 protein kinase C, alpha Prkca NM_011101 0.04344 1.4577 283 10562349 programmed cell death 2-like Pdcd2l NM_026549 0.04354 1.1523 284 10521337 regulator of G-protein signaling 12 Rgs12 NM_173402 0.04383 -1.7773 285 10549633 CDC42 effector protein (Rho GTPase binding) 5 Cdc42ep5 AK006430 0.04383 -1.4839 286 10544875 secernin 1 Scrn1 NM_027268 0.04410 -1.5603 287 10478401 tocopherol (alpha) transfer protein-like Ttpal NM_029512 0.04424 -1.8724 288 10363430 prosaposin Psap NM_011179 0.04424 -1.4252 289 10554574 transmembrane 6 superfamily member 1 Tm6sf1 NM_145375 0.04552 -1.4245 290 10421932 protocadherin 9 Pcdh9 NM_001081377 0.04553 1.8558 291 10574027 metallothionein 1 Mt1 NM_013602 0.04601 -1.7152 292 10598240 shroom family member 4 Shroom4 NM_001040459 0.04686 1.3649 293 10567355 G protein-coupled receptor, family C, group 5, member B Gprc5b NM_022420 0.04744 -1.4499 294 10381849 EF-hand calcium binding domain 3 Efcab3 ENSMUST00000021029 0.04840 -1.4470 295 10513061 catenin (cadherin associated protein), alpha-like 1 Ctnnal1 NM_018761 0.04840 -1.2647 296 10436804 melanocortin 2 receptor accessory protein Mrap NM_029844 0.04913 -1.4174

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Appendix 4 Housekeeper gene expression across samples used in RT-PCR time series. A 25 Rpl19 – C57Bl/6 time series

COCs Granulosa cells Whole ovary 20 Oviduct

15

10 CT (Mean SD) + CT (Mean

5

0 eCG 4h hCG 6h hCG 8h hCG 10h hCG 12h hCG eCG 4h hCG 6h hCG 8h hCG 10h hCG 12h hCG eCG 4h hCG 6h hCG 8h hCG 10h hCG 12h hCG B 35 Rpl19 – PRlacZ time series COC PR+/- COC PRKO 30 GC PR+/- GC PRKO Ovary (Calibrator) 25

20

15 CT (Mean SD) + CT (Mean 10 5

0 4h post-hCG 8h post-hCG 10h post-hCG 4h post-hCG 8h post-hCG 10h post-hCG

C 30 30

28 28

26 26 24 24 22 L19 Mean Ct Mean L19 CT 22 20

20 18 20 40 60 80 100 120 140 160 180 200 1.6 1.7 1.8 1.9 2.0 RNA (ng/ul after DNase treatment) 260/280 Score D 22 COC PR+/- COC PRKO 20 18S – PRlacZ time series GC PR+/- GC PRKO 18 Ovary (Calibrator) 16 14 12

10

8 CT (Mean + SD) (Mean CT 6

4

2

0 10h post-hCG 4h post-hCG 8h post-hCG 10h post-hCG 4h post-hCG 8h post-hCG Figure A4-1 Housekeeper gene expression for real-time PCR samples. A) Rpl19 CT values in tissues collected from C57Bl/6 mice at 48 h post-eCG and eCG + 4 h, 6 h, 8 h, 10 h, 12 h post-hCG. Whole ovary samples were collected at 10 h post-hCG and were used as the calibrator (same sample used in each of 3 runs). Each sample was run in triplicate and shown as mean + SD. B) Rpl19 CT values in tissues collected from PR+/- and PRKO mice at eCG + 4 h, 8 h and 10 h post-hCG. Whole ovary samples as per panel A. Each sample was run in triplicate and shown as mean + SD. C) Scatter plots show that for PR+/- and PRKO COC samples (shown in panel B), there was no correlation between the Rpl19 CT value after 40 PCR cycles and the initial yield of RNA (left panel) but that there was a correlation between Rpl19 CT value and the 260/280 ratio (right panel). Regression line shows significant correlation, P<0.0001. D) 18S CT values in tissues collected from PR+/- and PRKO mice and shown in panel B. Each sample was run in triplicate and shown as mean + SD. For panels A, B and D, the dotted line indicates the mean CT value across all samples. Lisa Akison 2012 260

Comment:

CT values for the housekeeping gene, ribosomal protein L19 (Rpl19), were generally consistent across tissue type, time point and PCR run for the C57Bl/6 time series and the PRlacZ time series. However, there was some variability in the CT values for the COC samples, particularly at the 4 h time point, and these tended to be higher overall than those for the granulosa cell and oviduct samples indicating a lower expression of mRNA (Panels A & B). This was despite standardising the concentration of RNA converted to cDNA across all samples and standardising the equivalent amount of cDNA used across all reactions. The RNA yield in these samples (total ng/μl after DNase treatment) tended to be much lower as well, but there was no correlation between RNA yield and CT after 40 cycles of real-time PCR (Panel C, left graph). However, there was an inverse correlation between the quality of the RNA, as indicated by the 260/280 ratio and CT score (Panel C, right graph), suggesting that some COC RNA samples had contamination or degradation following RNA extraction and reverse transcription. This variability was also not specific to Rpl19, with CT values for 18S ribosomal RNA showing even more variability across the COC samples (Panel D). This quality control assessment indicates that some caution may be required for the COC results given the potential degradation or contamination of these samples. However, given that final expression data is relative fold change as calculated using the Delta Delta CT method, the housekeeper gene will assist in normalising the variability in inherent expression.

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Appendix 5 Experiments testing the potential role of the oviduct in stimulating COC migration. Experiments in Chapter 6 demonstrated that the cumulus oocyte complex (COC) transitions to an adhesive, migratory and invasive phenotype during the periovulatory period in response to luteinising hormone (LH), peaking at ovulation. Thus, it appears that the COC may play an active role in facilitating its own release from the ovary. However, the mechanism facilitating or controlling this behaviour is currently unknown. Given the physical proximity of the oviducts to preovulatory follicles, perhaps they are somehow involved in driving the migratory and invasive phenotype of the COC that was observed in Chapter 6. Therefore, I hypothesised that chemotactic factors from the oviduct stimulate the directed migration of the COC at ovulation. In vitro experiments using the Real Time Cell Analysis (RTCA) system were conducted to test this hypothesis. These experiments included an ECM coating (collagen I, 20 ug/ml) on the upper and lower surfaces of the membrane as described in the manufacturer’s ‘Growth Factor-Mediated Cell Migration’ protocol. This is recommended by Roche when fetal calf serum (FCS) is not being used as the chemoattractant to induce cell migration and is intended to improve the signal by supporting cell attachment to the electrode. This step is not required when using serum in the lower chamber, as this naturally contains ECMs and growth factors which coat the electrode and make it suitable for cell attachment. Both surfaces of the membrane are coated to prevent haptotactic cell migration; this is chemotaxis in response to the ECM, rather than in response to the soluble chemotactic growth factor in the lower chamber. Briefly, 30 μl of 20 μg/ml ECM in SFM was added to the sensor-side (lower side) of each well of the upper chamber from the CIM-Plate 16 and incubated for 30 mins at RT. The ECM solution was then aspirated using a pipette and another 30 μl drop added to the upper side on the membrane surface inside of the wells of the upper chamber. The ECM was incubated for 30 mins at RT and then aspirated. The plate was then used in a standard xCELLigence migration assay, as detailed in Section 2.9. Collagen I was used as the ECM as COCs readily adhered to this substrate in the adhesion assays described in Chapter 6. Experiments with oviduct conditioned media: Oviduct conditioned media was used as a chemoattractant in RTCA experiments in place of FCS to examine if unknown factors from the oviduct could induce migration in preovulatory COCs. Oviducts were collected from 5 mice at 44h eCG + 10 h post-hCG and placed in 3 ml serum-free media (SFM; αMEM media supplemented with 250 μM pyruvate) in a petri dish pre-incubated at 37°C/5% CO2. Oviducts were then placed into 800 μl pre-incubated SFM in a 12-well plate and were incubated for 30 mins at 37°C/5% CO2. The same volumes of complete media (positive control; SFM + 5% FCS) and SFM (negative control) were also incubated in separate wells of the same plate. The oviduct conditioned media contained 10 oviducts in 800 μl of media which equates to 2 oviducts per 160 μl, which was the volume added to the lower chamber of the CIM-16 plates for migration assays (as per Chapter 6). Migration assays was then conducted as described in Section 2.9 and Chapter 6 with 44 h eCG + 10 h post-hCG COCs pooled from 8-10 mice and quadruplicate wells per treatment (Experiment 1). The experiment was repeated with triplicate wells per treatment (Experiment 2). Conditioned media from incubated preovulatory oviducts was unable to stimulate migration of COCs above basal levels in two separate experiments (Figure A5-1). In fact, in one of the experiments, migration rates in the presence of the oviduct conditioned media was less than that for serum-free media (Figure A5-1B). Thus, this relatively crude preparation of oviductal factors did not stimulate migration in preovulatory COCs. It is possible that the oviductal tissue was producing factors detrimental to COC health due to degradation of the tissue during the incubation period. Therefore, the next section describes experiments using a specific chemokine, CXCL12, which is produced by the oviduct.

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0.25 A) Experiment 1

Complete media Oviduct conditioned media 0.20 SFM

0.15

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0.05 Migration Index (Mean +/- SE) (Mean Index Migration

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0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Time (Hour)

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0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Time (Hour)

Figure A5-1 Conditioned media from preovulatory oviducts did not induce migration of COCs. Two experiments were completed with cell migration assessed in 10 h post-hCG COCs. A) Experiment 1 compared cell migration induced by complete media (includes FCS), oviduct conditioned media (no FCS) and serum free media (SFM). n = 3 wells per treatment. B) Experiment 2 similar to experiment 1; n = 4 wells per treatment.

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CXCL12 as a potential chemoattractant for COC migration: CXCL12 is the ligand for the chemokine receptor, CXCR4, which is induced in granulosa cells and COCs by LH during the preovulatory period (see Chapter 5). Real-time PCR indicated that CXCL12 mRNA was expressed at high levels in oviducts relative to ovarian cells across a preovulatory time- course collected from C57Bl/6 mice (see Chapter 5 for details), as shown in Figure A5-2A. Immunohistochemistry also showed that CXCL12 protein was predominantly localised to the luminal epithelium of the oviduct (Figure A5-2B). Thus, the pattern of regulated expression of the receptor in COCs and high expression of the ligand in the oviduct suggested a potential signalling axis which may induce migration of the COC at ovulation. Therefore, RTCA migration experiments using CXCL12 as the chemoattractant were performed.

A dose response using recombinant mouse CXCL12/SDF1 (R & D Systems Inc, Minneapolis, MN, USA) at 12.5, 25, 50, 100 and 400 ng/ml was used to examine this chemokine’s ability to induce migration of cumulus cells in 10 h post-hCG COCs. Dilutions were made in SFM. SFM and complete media (containing 5% FCS) were used as negative and positive controls respectively. Migration assays were conducted as described in Section 2.9. Each treatment was run in quadruplicate wells in 2-5 independent experiments. There was no trend between dose and cell migration, or evidence for induction of migration (Figure A5-3). However, the highest dose (400 ng/ml) did cause consistent inhibition of migration, although statistical significance could not be determined due to low sample sizes in some groups. There was also high variability in the response to complete media, as shown by the large standard deviation for this treatment (Figure A5-3). Is this inhibition more obvious in the presence of FCS, which normally alone induces migration in COCs? Therefore, the next experiment examined the ability of a high dose (400 ng/ml) of CXCL12 to inhibit induced migration in the presence of FCS, rather than just inhibiting basal rates of migration when serum is absent. Each treatment was done in quadruplicate wells and was repeated in 3 independent experiments. An initial spike in cell index values for CXCL12 treatments (particularly when diluted in complete media) suggested that there was some initial effect of high CXCL12 in this system (Figure A5- 4). Following this initial spike, migration rates appeared to stabilise by 3 h. Therefore, the slope of the cell index migration line from 3-14 h post-start time was calculated, rather than Delta migration rates from 0-14 h, as was used in Chapter 6. This gives a measure of migration rate which can then be compared across treatments. There was no significant effect of CXCL12 on basal migration of COCs but there was a significant reduction in the degree of induced migration in the presence of serum (Figure A5-4). Therefore, CXCL12 does appear to regulate COC migration, albeit in a way contrary to what was predicted.

Conclusion: There was no evidence that factors from the oviduct could induce migration. However, it did appear that a high dose of the chemokine CXCL12, which was found to be abundantly expressed in the oviduct, may inhibit induced migration in the presence of serum. CXCL12 has been shown to induce chemotaxis in a biphasic manner, causing inhibition of migration at high doses. For example, doses of 70nM and above up to 1000nM inhibited chemotaxis in THP-1 cells (human leukaemia cell line) [Veldkamp et al., 2008]. This biphasic response is typical of chemokines in general.

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30 A) cumulus oocyte complex B) granulosa cells b oviducts

25 b

b 20 b b

b 15

Fold ChangeRelative (mean + SE) 10

d 5 d c d d d d a ca ca a a

0 48h 4h 6h 8h 10h 12h post-eCG post-hCG Figure A5-2 CXCL12 mRNA and protein are expressed in the oviduct. A) CXCL12 mRNA expression in C57Bl/6 mouse oviducts, granulosa cells and COCs. Each tissue was normalised to 48 h post-eCG COC. Data was analysed using a two-way ANOVA on log-transformed data & Student Neuman Kuel’s pair-wise comparison procedure. Different letters denote significant differences at P<0.05. n = 3 - 4 samples for each tissue type at each time point, with each sample pooled from 6 mice. B) CXCL12 protein detected in 8 h post-hCG oviducts of C57Bl/6 mice. Two animals are shown to illustrate the range of staining observed in 4 animals. Animal 1 shows strong staining, predominantly in the luminal epithelium of the oviduct, but also some staining is evident in ovarian follicles (arrowheads). Animal 2 shows punctate staining in the luminal epithelium and no staining in the ovary (arrowheads). CXCL12 -Subunit Rabbit Polyclonal primary antibody (eBioscience, San Diego, CA, USA) 1:1000 concentration; secondary antibody (biotinylated goat--rabbit IgG; Vector Labs, Burlingame, CA, USA) 1:500 concentration.

265

A)

0.8 12.5 ng/ml CXCL12 (n=2) 0.7 25 ng/ml CXCL12 (n=2) 50 ng/ml CXCL12 (n=3) 0.6 100 ng/ml CXCL12 (n=3) 400 ng/ml CXCL12 (n=5) 0.5 SFM (n=5) Complete media (n=4) 0.4

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Delta Cell Index @ 14h (Mean + SD) (Mean @ 14h CellDelta Index 0.0 12.5 25 50 100 400 SFM Complete 5% FCS CXCL12 (ng/ml)

Figure A5-3 COC migration in response to CXCL12. A) xCELLigence data plotted for each treatment. Data was collected at 10 min intervals but is plotted here at 30 min intervals for clarity. Each treatment was run in quadruplicate wells and the means (+/- SE) for 2-5 independent experiments are shown. B) Delta cell index from the data shown in A) plotted per treatment after 14 h of Real-time Cell Analysis.

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A) 0.8 SFM + SDF1 (400ng/ml) Complete media + SDF1 (400ng/ml) 0.7 SFM Complete media 0.6

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0.00 SDF1 + SDF1 + SFM Complete SFM Complete Basal Migration Induced Migration

Figure A5-4 A high dose of CXCL12/SDF1 reduces induced migration of preovulatory COCs. Data is from 3 independent experiments with each treatment run in quadruplicate wells. (A) An initial spike in the cell index was observed for the CXCL12/SDF1 treatment wells. Data is from one experiment and is indicative of all experiments. Data was recorded every 10 mins but is shown here at 30 min intervals for clarity. B) The slope of the cell index line was calculated from 3-14 h as a measure of migration rate for each treatment. A Student’s t-test was used to compare the slopes within migration type. There was no significant effect of CXCL12/SDF1 on basal migration of COCs (P = 0.173) but there was a significant reduction in the degree of induced migration in the presence of serum (P = 0.003).

Lisa Akison 2012

Appendix 6 List of differentially expressed genes (P<0.01 only) from the oviduct microarray. Adjusted (‘Stepup’) P-value given from False Discovery Rate Correction. Negative fold change indicates PRKO down-regulated relative to PR+/-; positive fold change indicates PRKO up-regulated relative to PR+/-. RefSeq = Reference Sequence. Gene symbols are as reported for the Affymetrix GeneChip® Mouse Gene 1.0 ST Arrays (Affymetrix, Santa Clara, USA; 2009). Genes are sorted from lowest to highest P-value (i.e. most significant to least significant). Probeset Gene Stepup (P-value Fold-Change ID Gene Name Symbol RefSeq (KO vs. +/-)) (KO vs. +/-) 1 10480090 integrin alpha 8 Itga8 NM_001001309 1.52E-06 -9.8656 2 10495449 collagen, type XI, alpha 1 Col11a1 NM_007729 6.27E-05 -2.6419 3 10545707 actin, gamma 2, smooth muscle, enteric Actg2 NM_009610 6.27E-05 -2.5216 4 10540523 LIM and cysteine-rich domains 1 Lmcd1 NM_144799 6.27E-05 -1.8842 5 10532753 coronin, actin binding protein 1C Coro1c NM_011779 0.00031 -1.9261 6 10494643 3-hydroxy-3-methylglutaryl-Coenzyme A synthase 2 Hmgcs2 NM_008256 0.00031 -5.8122 7 10566543 dachsous 1 (Drosophila) Dchs1 ENSMUST00000078482 0.00031 -1.6886 8 10603746 monoamine oxidase B Maob NM_172778 0.00034 -5.4814 9 10347583 desmin Des NM_010043 0.00034 -3.5479 10 10435388 adenylate cyclase 5 Adcy5 NM_001012765 0.00034 -2.2718 11 10417212 integrin, beta-like 1 Itgbl1 NM_145467 0.00034 -2.2043 12 10505064 transmembrane protein 38B Tmem38b NM_028053 0.00036 -1.7176 13 10583809 calponin 1 Cnn1 NM_009922 0.00037 -1.9246 14 10506488 phosphatidic acid phosphatase type 2B Ppap2b NM_080555 0.00045 -2.8946 15 10510574 ERBB receptor feedback inhibitor 1 Errfi1 NM_133753 0.00045 -2.7791 16 10568001 sulfotransferase family 1A, phenol-preferring, member 1 Sult1a1 NM_133670 0.00045 -2.7081 17 10363415 sparc Spock2 NM_052994 0.00045 -2.1904 18 10577808 transforming, acidic coiled-coil containing protein 1 Tacc1 NM_177089 0.00045 -1.7050 19 10405587 transforming growth factor, beta induced Tgfbi NM_009369 0.00047 -2.1326 20 10532085 transforming growth factor, beta receptor III Tgfbr3 NM_011578 0.00047 -2.0355 21 10568536 carboxypeptidase X 2 (M14 family) Cpxm2 NM_018867 0.00049 -3.1167 22 10606989 TSC22 domain family, member 3 Tsc22d3 NM_001077364 0.00049 -1.7377 23 10547206 FXYD domain-containing ion transport regulator 4 Fxyd4 NM_033648 0.00055 -2.8500 24 10595981 muscle and microspikes RAS Mras NM_008624 0.00055 -1.5602 25 10399854 solute carrier family 26, member 4 Slc26a4 NM_011867 0.00055 2.6851 26 10593225 zinc finger and BTB domain containing 16 Zbtb16 NM_001033324 0.00057 -4.3257 27 10495794 phosphodiesterase 5A, cGMP-specific Pde5a NM_153422 0.00057 -2.3477 28 10549102 potassium inwardly-rectifying channel, subfamily J, member Kcnj8 NM_008428 0.00057 -3.1487

29 10511363 preproenkephalin 1 Penk1 NM_001002927 0.00057 -2.6400 30 10599736 four and a half LIM domains 1 Fhl1 NM_001077361 0.00057 -1.8889 31 10358389 regulator of G-protein signaling 2 Rgs2 NM_009061 0.00058 -3.6444 32 10483439 low density lipoprotein receptor-related protein 2 Lrp2 NM_001081088 0.00060 -3.3155 33 10530841 insulin-like growth factor binding protein 7 Igfbp7 NM_008048 0.00065 -1.8947 34 10417787 guanine nucleotide binding protein (G protein), gamma 2 Gng2 NM_010315 0.00067 -1.8562 35 10551852 CAP-GLY domain containing linker protein 3 Clip3 NM_001081114 0.00076 -1.6241 36 10440522 a disintegrin-like and metallopeptidase (reprolysin type Adamts1 NM_009621 0.00076 -3.1797 37 10560329 hypoxia inducible factor 3, alpha subunit Hif3a NM_016868 0.00076 -2.5048 38 10431410 mitogen-activated protein kinase 11 Mapk11 NM_011161 0.00076 -2.4701 39 10540059 solute carrier family 41, member 3 Slc41a3 NM_027868 0.00076 -2.3101 40 10344990 cysteine-rich secretory protein LCCL domain containing Crispld1 NM_031402 0.00076 -2.1770 41 10485597 DEP domain containing 7 Depdc7 NM_144804 0.00077 -1.3421 42 10466800 phosphoglucomutase 5 Pgm5 NM_175013 0.00085 -2.0499 43 10467319 retinol binding protein 4, plasma Rbp4 NM_011255 0.00086 -1.9295 44 10466712 MAM domain containing 2 Mamdc2 NM_174857 0.00091 -2.4875 45 10344981 peptidase inhibitor 15 Pi15 NM_053191 0.00094 -2.0142 46 10495243 glutathione S-transferase, mu 5 Gstm5 NM_010360 0.00094 -1.4691 47 10520633 transcription factor 23 Tcf23 NM_053085 0.00094 -3.5643 48 10413813 UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylg Galntl2 NM_030166 0.00094 -2.3618 49 10439612 biregional cell adhesion molecule-related Boc NM_172506 0.00094 -1.9310 50 10446763 limb-bud and heart Lbh NM_029999 0.00094 -1.8630 51 10569429 cyclin-dependent kinase inhibitor 1C (P57) Cdkn1c NM_009876 0.00095 -2.0257 52 10540028 Kruppel-like factor 15 Klf15 NM_023184 0.00096 -2.5078 53 10506298 leptin receptor overlapping transcript Leprot NM_175036 0.00096 -1.5474 54 10584674 melanoma cell adhesion molecule Mcam NM_023061 0.00096 -1.9005 55 10595211 collagen, type XII, alpha 1 Col12a1 NM_007730 0.00099 -2.6667 56 10494821 tetraspanin 2 Tspan2 NM_027533 0.00099 -1.7189 57 10458960 aldehyde dehydrogenase family 7, member A1 Aldh7a1 NM_001127338 0.00099 -1.4259 58 10583179 progesterone receptor Pgr NM_008829 0.00099 -2.3740 59 10403584 nidogen 1 Nid1 NM_010917 0.00099 -1.8490 60 10492021 periostin, osteoblast specific factor Postn NM_015784 0.00104 -2.8645 61 10517336 chloride intracellular channel 4 (mitochondrial) Clic4 NM_013885 0.00104 -1.8012 62 10487392 Kv channel interacting protein 3, calsenilin Kcnip3 NM_019789 0.00108 -1.5563 63 10479165 endothelin 3 Edn3 NM_007903 0.00115 -3.4308

64 10527538 RAS-like, family 11, member A Rasl11a NM_026864 0.00117 -1.7509 65 10590060 CTD (carboxy-terminal domain, RNA polymerase II, polypept Ctdspl NM_133710 0.00117 -1.2646 66 10435345 myosin, light polypeptide kinase Mylk NM_139300 0.00128 -1.5537 67 10528227 guanine nucleotide binding protein (G protein), alpha inhi Gnai1 NM_010305 0.00133 -1.7590 68 10564857 isocitrate dehydrogenase 2 (NADP+), mitochondrial Idh2 NM_173011 0.00140 -1.4957 69 10353252 gene model 106, (NCBI) Gm106 BC147195 0.00146 -4.5062 70 10362201 connective tissue growth factor Ctgf NM_010217 0.00150 -2.1822 71 10607012 collagen, type IV, alpha 6 Col4a6 NM_053185 0.00150 -1.9944 72 10452316 complement component 3 C3 NM_009778 0.00150 1.3171 73 10575917 WAP four-disulfide core domain 1 Wfdc1 NM_023395 0.00155 -2.3232 74 10496036 collagen, type XXV, alpha 1 Col25a1 NM_029838 0.00155 1.5403 75 10423049 prolactin receptor Prlr BC096586 0.00161 -3.3879 76 10554863 synaptotagmin-like 2 Sytl2 NM_001040085 0.00161 -1.7122 77 10535956 StAR-related lipid transfer (START) domain containing 13 Stard13 NM_146258 0.00161 -1.7017 78 10413710 5'-nucleotidase domain containing 2 Nt5dc2 NM_027289 0.00161 -1.4739 79 10484389 pathway inhibitor Tfpi NM_011576 0.00161 -1.4325 80 10423109 a disintegrin-like and metallopeptidase (reprolysin typ Adamts12 NM_175501 0.00163 -1.6483 81 10504424 reversion-inducing-cysteine-rich protein with kazal motifs Reck NM_016678 0.00165 -1.7206 82 10409278 nuclear factor, interleukin 3, regulated Nfil3 NM_017373 0.00169 -1.7458 83 10489444 WAP four-disulfide core domain 15B Wfdc15b NM_138685 0.00169 -2.3955 84 10435305 integrin beta 5 Itgb5 NM_010580 0.00169 -1.8115 85 10421309 solute carrier family 39 (zinc transporter), member 14 Slc39a14 NM_144808 0.00169 -1.7089 86 10445688 cyclin D3 Ccnd3 NM_001081636 0.00169 -1.5107 87 10607124 chordin-like 1 Chrdl1 NM_001114385 0.00170 -2.1094 88 10381474 ADP-ribosylation factor-like 4D Arl4d NM_025404 0.00179 -3.5198 89 10480459 histamine N-methyltransferase Hnmt NM_080462 0.00180 -1.2373 90 10571601 PDZ and LIM domain 3 Pdlim3 NM_016798 0.00181 -2.4263 91 10540034 aldehyde dehydrogenase 1 family, member Aldh1l1 NM_027406 0.00185 -2.0315 92 10503334 GTP binding protein (gene overexpressed in skeletal muscle) Gem NM_010276 0.00185 -1.8807 93 10435641 follistatin-like 1 Fstl1 NM_008047 0.00185 -1.6501 94 10603099 c-fos induced growth factor Figf NM_010216 0.00204 -2.6289 95 10487238 histidine decarboxylase Hdc NM_008230 0.00205 -1.6634 96 10571142 G protein-coupled receptor 124 Gpr124 NM_054044 0.00212 -2.0865 97 10600169 biglycan Bgn NM_007542 0.00222 -1.9975 98 10402325 ankyrin repeat and SOCS box-containing 2 Asb2 NM_023049 0.00222 -1.6922

99 10493995 S100 calcium binding protein A10 (calpactin) S100a10 NM_009112 0.00222 -1.5769 100 10360270 ATPase, Na+ Atp1a2 NM_178405 0.00222 -1.4325 101 10564713 milk fat globule-EGF factor 8 protein Mfge8 NM_008594 0.00222 -1.2705 102 10432886 keratin 4 Krt4 NM_008475 0.00222 1.3094 103 10546829 oxytocin receptor Oxtr NM_001081147 0.00226 1.8956 104 10381122 FK506 binding protein 10 Fkbp10 NM_010221 0.00233 -1.6822 105 10500295 pleckstrin homology domain containing, family O member 1 Plekho1 NM_023320 0.00259 -1.9652 106 10568785 BCL2 Bnip3 NM_009760 0.00259 -1.9035 107 10357965 leucine-rich repeat-containing G protein-coupled recepto Lgr6 NM_001033409 0.00260 -1.8624 108 10599001 angiotensin II receptor, type 2 Agtr2 NM_007429 0.00260 2.1830 109 10511580 protein phosphatase 2C, magnesium dependent, catalytic Ppm2c NM_001098230 0.00269 -1.2527 110 10551293 cytochrome P450, family 2, subfamily f, polypeptide 2 Cyp2f2 NM_007817 0.00284 -1.7237 111 10386996 myocardin Myocd NM_145136 0.00286 -2.2671 112 10520304 ARP3 actin-related protein 3 homolog B (yeast) Actr3b NM_001004365 0.00286 -1.8454 113 10555027 growth factor receptor bound protein 2-associated protein 2 Gab2 NM_010248 0.00286 -1.7934 114 10355706 Indian hedgehog Ihh NM_010544 0.00298 -1.4082 115 10399505 gene regulated by estrogen in breast cancer protein Greb1 NM_015764 0.00298 -1.6983 116 10367440 integrin alpha 7 Itga7 NM_008398 0.00298 -1.4640 117 10469151 inter-alpha (globulin) inhibitor H5 Itih5 NM_172471 0.00307 -1.9988 118 10494445 Lix1-like Lix1l ENSMUST00000062058 0.00307 -1.7554 119 10409833 growth arrest specific 1 Gas1 NM_008086 0.00307 -1.7446 120 10368888 forkhead box O3a Foxo3a NM_019740 0.00307 -1.3542 121 10451665 apolipoprotein B mRNA editing enzyme, catalytic polypept Apobec2 NM_009694 0.00307 1.7882 122 10363157 phospholamban Pln NM_023129 0.00307 2.0327 123 10394068 secreted and transmembrane 1A Sectm1a NM_145373 0.00312 -2.4640 124 10544779 homeo box A7 Hoxa7 NM_010455 0.00312 -1.5350 125 10387922 solute carrier family 25 (mitochondrial carrier oxoglut Slc25a11 NM_024211 0.00312 -1.3500 126 10393944 RFNG O-fucosylpeptide 3-beta-N-acetylglucosaminyltransferas Rfng NM_009053 0.00315 -1.3367 127 10512499 tropomyosin 2, beta Tpm2 NM_009416 0.00319 -1.5068 128 10547641 solute carrier family 2 (facilitated glucose transporter) Slc2a3 NM_011401 0.00319 -1.4790 129 10468113 Kv channel-interacting protein 2 Kcnip2 NM_145703 0.00322 -2.4184 130 10399360 ras homolog gene family, member B Rhob NM_007483 0.00323 -1.8461 131 10599348 glutamate receptor, ionotropic, AMPA3 (alpha 3) Gria3 NM_016886 0.00332 -3.1449 132 10454514 LIM and senescent cell antigen like domains 2 Lims2 NM_144862 0.00332 -1.6947 133 10522467 RAS-like, family 11, member B Rasl11b NM_026878 0.00338 -2.3377

134 10549361 transmembrane 7 superfamily member 3 Tm7sf3 NM_026281 0.00346 -1.3105 135 10346843 2 Nrp2 NM_001077403 0.00354 -1.5443 136 10532819 potassium channel tetramerisation domain containing 10 Kctd10 NM_026145 0.00354 -1.3424 137 10387743 solute carrier family 2 (facilitated glucose transporter) Slc2a4 NM_009204 0.00358 -2.0634 138 10467425 sorbin and SH3 domain containing 1 Sorbs1 NM_178362 0.00358 -1.8178 139 10509280 perlecan (heparan sulfate proteoglycan 2) Hspg2 NM_008305 0.00358 -1.6176 140 10407319 ribosomal protein L34 Rpl34 NM_001005859 0.00358 -1.2583 141 10438822 ATPase type 13A5 Atp13a5 NM_175650 0.00358 1.4034 142 10509992 heat shock protein family, member 7 (cardiovascular) Hspb7 NM_013868 0.00362 -1.8702 143 10511881 mannosidase, endo-alpha Manea NM_172865 0.00376 -1.3856 144 10591626 dedicator of cytokinesis 6 Dock6 NM_177030 0.00378 -1.2787 145 10354111 AF4 Aff3 NM_010678 0.00396 -1.3728 146 10383731 smoothelin Smtn NM_013870 0.00412 -1.4527 147 10390381 aminopeptidase puromycin sensitive Npepps NM_008942 0.00420 -1.2282 148 10350136 cysteine and glycine-rich protein 1 Csrp1 NM_007791 0.00429 -1.5693 149 10449452 FK506 binding protein 5 Fkbp5 NM_010220 0.00453 -2.6835 150 10396831 arginase type II Arg2 NM_009705 0.00453 -1.7439 151 10373407 membrane bound C2 domain containing protein Mbc2 NM_011843 0.00453 -1.4961 152 10458663 dihydropyrimidinase-like 3 Dpysl3 NM_009468 0.00453 -1.4809 153 10480145 Ras suppressor protein 1 Rsu1 NM_009105 0.00463 -1.5635 154 10448836 transmembrane protein 204 Tmem204 NM_001001183 0.00465 -2.7066 155 10599962 mastermind-like domain containing 1 Mamld1 NM_001081354 0.00465 -1.5700 156 10559524 protein phosphatase 1, regulatory (inhibitor) subunit 1 Ppp1r12c NM_029834 0.00465 -1.3277 157 10554599 ADAMTS-like 3 Adamtsl3 ENSMUST00000094237 0.00465 1.6920 158 10576235 dipeptidase 1 (renal) Dpep1 NM_007876 0.00473 -4.0193 159 10523297 cyclin G2 Ccng2 NM_007635 0.00473 -1.5841 160 10375402 a disintegrin and metallopeptidase domain 19 (meltrin bet Adam19 NM_009616 0.00473 -1.5462 161 10572928 RASD family, member 2 Rasd2 ENSMUST00000041083 0.00493 -2.5325 162 10352905 CD34 antigen Cd34 NM_001111059 0.00493 -1.6356 163 10544756 homeo box A3 Hoxa3 NM_010452 0.00511 -2.1275 164 10500938 wingless related MMTV integration site 2b Wnt2b NM_009520 0.00513 -1.6802 165 10389719 serine carboxypeptidase 1 Scpep1 NM_029023 0.00513 -1.7945 166 10546725 PDZ domain containing RING finger 3 Pdzrn3 NM_018884 0.00525 -1.7491 167 10374453 glutamate-ammonia ligase (glutamine synthetase) Glul BC015086 0.00525 -1.7095 168 10468691 actin-binding LIM protein 1 Ablim1 NM_178688 0.00525 -1.7037

169 10380761 suppressor of cytokine signaling 7 Socs7 NM_138657 0.00525 -1.5970 170 10460968 RAS, guanyl releasing protein 2 Rasgrp2 NM_011242 0.00525 -1.3996 171 10533050 heat shock protein 8 Hspb8 NM_030704 0.00525 -1.8153 172 10550574 dystrophia myotonica-protein kinase Dmpk NM_032418 0.00526 -1.5677 173 10476702 SEC23B (S. cerevisiae) Sec23b NM_019787 0.00526 -1.4772 174 10442495 polycystic kidney disease 1 homolog Pkd1 NM_013630 0.00545 -1.6620 175 10483698 WAS Wipf1 NM_153138 0.00545 -1.4566 176 10346164 serum deprivation response Sdpr NM_138741 0.00548 -1.6910 177 10365482 tissue inhibitor of metalloproteinase 3 Timp3 NM_011595 0.00576 -2.0292 178 10509163 inhibitor of DNA binding 3 Id3 NM_008321 0.00577 -1.5353 179 10602105 collagen, type IV, alpha 5 Col4a5 NM_007736 0.00577 -1.5071 180 10453057 cytochrome P450, family 1, subfamily b, polypeptide 1 Cyp1b1 NM_009994 0.00585 -3.8766 181 10487894 Ras association (RalGDS Rassf2 NM_175445 0.00585 -1.9652 182 10549420 transmembrane and tetratricopeptide repeat containing 1 Tmtc1 NM_198967 0.00585 -1.6680 183 10584634 ubiquitin specific peptidase 2 Usp2 NM_198092 0.00585 -1.3186 184 10565002 CREB regulated transcription coactivator 3 Crtc3 NM_173863 0.00585 -1.1878 185 10501199 glutathione S-transferase, mu 7 Gstm7 NM_026672 0.00590 -1.8088 186 10498284 WW domain containing transcription regulator 1 Wwtr1 NM_133784 0.00607 -1.2869 187 10518526 angiopoietin-like 7 Angptl7 NM_001039554 0.00613 -1.8738 188 10453233 solute carrier family 8 (sodium Slc8a1 NM_011406 0.00613 -1.6683 189 10362538 laminin, alpha 4 Lama4 NM_010681 0.00613 -1.9715 190 10556005 integrin linked kinase Ilk NM_010562 0.00615 -1.6155 191 10536499 caveolin 1, caveolae protein Cav1 NM_007616 0.00615 -1.5217 192 10460616 cofilin 1, non-muscle Cfl1 NM_007687 0.00638 -1.2558 193 10576973 collagen, type IV, alpha 1 Col4a1 NM_009931 0.00646 -1.4346 194 10356088 collagen, type IV, alpha 4 Col4a4 NM_007735 0.00666 -1.4399 195 10499168 kin of IRRE like (Drosophila) Kirrel NM_130867 0.00679 -1.3951 196 10423654 odd-skipped related 2 (Drosophila) Osr2 NM_054049 0.00682 -2.3798 197 10475414 beta-2 microglobulin B2m NM_009735 0.00682 -1.6714 198 10557960 transforming growth factor beta 1 induced transcript 1 Tgfb1i1 NM_009365 0.00682 -1.5931 199 10558150 HtrA serine peptidase 1 Htra1 NM_019564 0.00682 -1.3784 200 10589889 galactosidase, beta 1 Glb1 NM_009752 0.00682 -1.2460 201 10431393 mitogen-activated protein kinase 12 Mapk12 NM_013871 0.00682 -1.2099 202 10578123 RNA binding protein gene with multiple splicing Rbpms NM_019733 0.00683 -1.5278 203 10517791 peptidyl arginine deiminase, type IV Padi4 NM_011061 0.00683 2.1473

204 10467420 PDZ and LIM domain 1 (elfin) Pdlim1 NM_016861 0.00685 -1.6825 205 10591576 dedicator of cytokinesis 6 Dock6 NM_177030 0.00685 -1.2645 206 10430006 solute carrier family 39 (zinc transporter), member 4 Slc39a4 NM_028064 0.00699 -1.6963 207 10368495 R-spondin 3 homolog (Xenopus laevis) Rspo3 NM_028351 0.00699 -1.4425 208 10357870 proline arginine-rich end leucine-rich repeat Prelp NM_054077 0.00706 -1.5494 209 10549222 branched chain aminotransferase 1, cytosolic Bcat1 NM_001024468 0.00716 1.1808 210 10422628 phosphatidylinositol-specific phospholipase C, X domain c Plcxd3 NM_177355 0.00722 -1.8508 211 10553788 ATPase, class V, type 10A Atp10a NM_009728 0.00722 -1.7732 212 10519770 piccolo (presynaptic cytomatrix protein) Pclo NM_011995 0.00728 1.3353 213 10392522 ATP-binding cassette, sub-family A (ABC1), member 8a Abca8a NM_153145 0.00729 -2.6601 214 10501699 amylo-1,6-glucosidase, 4-alpha-glucanotransferase Agl NM_001081326 0.00732 -1.5926 215 10369615 serglycin Srgn NM_011157 0.00741 -1.8827 216 10460400 pyruvate carboxylase Pcx NM_008797 0.00746 -1.4111 217 10606609 tetraspanin 6 Tspan6 NM_019656 0.00750 -1.3472 218 10600547 transducin (beta)-like 1 X-linked Tbl1x NM_020601 0.00753 -1.4319 219 10427436 complement component 7 C7 XM_356827 0.00754 -2.0240 220 10562927 prostate tumor over expressed gene 1 Ptov1 NM_133949 0.00761 -1.4029 221 10540248 microphthalmia-associated transcription factor Mitf NM_001113198 0.00762 -1.7654 222 10413086 adenosine kinase Adk NM_134079 0.00769 -1.5428 223 10406407 arrestin domain containing 3 Arrdc3 NM_001042591 0.00779 -1.5016 224 10445347 chloride intracellular channel 5 Clic5 NM_172621 0.00779 -1.4265 225 10512334 interleukin 11 receptor, alpha chain 2-like Il11ra2l NM_001099348 0.00779 -1.3251 226 10417617 glyceraldehyde-3-phosphate dehydrogenase Gapdh BC092267 0.00784 -1.2182 227 10556381 microtubule associated monoxygenase, calponin and LIM dom Mical2 NM_177282 0.00788 -1.4223 228 10354588 serine Stk17b NM_133810 0.00804 -2.0446 229 10436304 ABI gene family, member 3 (NESH) binding protein Abi3bp NM_001014423 0.00804 -1.8798 230 10369206 ribosomal protein S8 Rps8 NM_009098 0.00810 -1.3012 231 10443949 a disintegrin-like and metallopeptidase (reprolysin typ Adamts10 NM_172619 0.00810 -1.3280 232 10522024 TBC1 domain family, member 1 Tbc1d1 NM_019636 0.00815 -1.4008 233 10414333 sterile alpha motif domain containing 4 Samd4 NM_001037221 0.00816 -1.4939 234 10472212 plakophilin 4 Pkp4 NM_026361 0.00816 1.2828 235 10364072 gamma-glutamyltransferase 5 Ggt5 NM_011820 0.00839 -1.6206 236 10527713 relaxin Rxfp2 NM_080468 0.00866 1.4282 237 10475643 fibroblast growth factor 7 Fgf7 NM_008008 0.00875 -2.1519 238 10348537 receptor (calcitonin) activity modifying protein 1 Ramp1 NM_016894 0.00875 -1.9733

239 10455784 GRAM domain containing 3 Gramd3 NM_026240 0.00875 -1.8012 240 10406941 small glutamine-rich tetratricopeptide repeat (TPR)-contain Sgtb NM_144838 0.00875 -1.7965 241 10354741 raftlin family member 2 Rftn2 NM_028713 0.00875 -1.4955 242 10382243 guanine nucleotide binding protein, alpha 13 Gna13 NM_010303 0.00875 -1.2162 243 10429140 N- downstream regulated gene 1 Ndrg1 NM_008681 0.00880 -1.4378 244 10424370 tribbles homolog 1 (Drosophila) Trib1 NM_144549 0.00888 -1.4328 245 10476401 phospholipase C, beta 1 Plcb1 NM_019677 0.00896 -1.7746 246 10514088 Fras1 related extracellular matrix protein 1 Frem1 NM_177863 0.00897 -1.8520 247 10580635 carboxylesterase 3 Ces3 NM_053200 0.00897 -1.4429 248 10564527 nuclear receptor subfamily 2, group F, member 2 Nr2f2 NM_009697 0.00897 -1.3441 249 10470954 leucine rich repeat containing 8A Lrrc8a NM_177725 0.00897 -1.3108 250 10581132 cadherin 16 Cdh16 NM_007663 0.00901 1.7615 251 10489357 junctophilin 2 Jph2 NM_021566 0.00906 -1.4352 252 10419854 solute carrier family 7 (cationic amino acid transporter, Slc7a8 NM_016972 0.00912 -3.7650 253 10376778 microfibrillar-associated protein 4 Mfap4 NM_029568 0.00912 -1.6370 254 10521543 syntaxin 18 Stx18 NM_026959 0.00912 -1.4240 255 10423520 sema domain, seven thrombospondin repeats (type 1 and typ Sema5a NM_009154 0.00913 -1.5376 256 10607089 acyl-CoA synthetase long-chain family member 4 Acsl4 NM_207625 0.00913 -1.4415 257 10526241 claudin 3 Cldn3 NM_009902 0.00928 -2.1283 258 10392221 platelet Pecam1 NM_008816 0.00928 -1.3570 259 10530633 sarcoglycan, beta (dystrophin-associated glycoprotein) Sgcb NM_011890 0.00936 -1.3164 260 10440534 a disintegrin-like and metallopeptidase (reprolysin type Adamts5 NM_011782 0.00942 -2.1168 261 10488482 acyl-CoA synthetase short-chain family member 1 Acss1 NM_080575 0.00953 -1.5736 262 10360336 olfactory receptor 1406 Olfr1406 NM_146763 0.00953 1.2557 263 10542791 PTPRF interacting protein, binding protein 1 (liprin bet Ppfibp1 NM_026221 0.00953 1.2829 264 10399973 histone deacetylase 9 Hdac9 NM_024124 0.00959 -1.2328 265 10382802 sphingosine kinase 1 Sphk1 NM_011451 0.00959 1.2920

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