MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

2016

Rosie Sarah Griffiths

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

Supervisors:

Prof Sue KIMBER and Dr Matthew RONSHAUGEN

SCHOOL of BIOLOGICAL SCIENCES Division of Cell Matrix Biology & Regenerative Medicine Contents

List of Figures 8

List of Tables 9

List of Abbreviations 11

Abstract 12

Declaration 13

Copyright Statement 14

Acknowledgements 15

Dedication 16

1 Introduction 17 1.1 General Overview ...... 17 1.2 Articular Cartilage Cell Therapy ...... 17 1.3 Chondrogenesis ...... 20 1.3.1 Signaling Pathways Regulating Chondrogenesis ...... 21 1.3.2 Transcriptional Regulation of Chondrogenesis ...... 22 1.4 Embryonic Stem Cells ...... 23 1.4.1 Pluripotency control ...... 23 1.4.2 Extrinsic Factors Promoting Self-Renewal in ESCs ...... 24 1.4.3 ESC Characterisation ...... 25 1.4.4 ESC Culture ...... 25 1.4.5 Feeder-Free Culture ...... 26 1.5 MicroRNAs ...... 26 1.5.1 MicroRNAs in the Genome ...... 27 1.5.2 Biogenesis ...... 27 1.5.3 MicroRNA Silencing Mechanism ...... 30 1.5.4 Target Identification ...... 30

2 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

1.5.5 MicroRNAs in ESCs ...... 32 1.5.6 MicroRNAs involved in Differentiation ...... 33 1.5.7 Chondrogenic miRNAs ...... 34 1.5.8 Manipulating miRNAs ...... 39 1.6 Next Generation Sequencing and Bioinformatic Analysis ...... 41 1.6.1 Mapping to miRNAs ...... 42 1.6.2 Normalisation ...... 42 1.6.3 Differential Expression of miRNAs ...... 42 1.6.4 Co-expression Analysis ...... 43 1.7 Exosomes ...... 44 1.7.1 Exosome Isolation ...... 45 1.7.2 Exosome Characterisation and Quantification ...... 46 1.7.3 Exosome Composition ...... 47 1.7.4 Exosome Biogenesis ...... 48 1.7.5 Exosome Release ...... 51 1.7.6 Exosome Uptake ...... 52 1.7.7 Exosome Function ...... 52 1.7.8 Exosomal miRNAs ...... 54 1.7.9 Clinical Applications of Exosomes ...... 55 1.8 Research Aims ...... 57

2 Materials and Methods 58 2.1 Mouse Embryonic Fibroblast (MEF) Culture ...... 58 2.1.1 Defrosting active MEFs ...... 58 2.1.2 Culturing active MEFs ...... 58 2.1.3 Passaging active MEFs with TrypLE ...... 58 2.1.4 MEF Inactivation ...... 59 2.1.5 Inactivated MEF plating ...... 59 2.2 Human Embryonic Stem Cell culture ...... 60 2.2.1 Human Embryonic Stem Cell derivation ...... 60 2.2.2 Defrosting and Feeding hESCs ...... 60 2.2.3 Passaging hESCs with TrypLE ...... 61 2.2.4 Passaging hESCs with EDTA ...... 61 2.2.5 Feeder Free Culture of hESCs ...... 62 2.2.6 Chondrogenic differentiation of hESCs ...... 62 2.3 RNA Analysis ...... 63 2.3.1 RNA Extraction ...... 63 2.3.2 MicroRNA TaqMan Real-Time Polymerase Chain Reaction (RT-PCR) 63

Chapter 0 3 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

2.3.3 SYBR Green RT-PCR ...... 64 2.4 RNA Sequencing analysis ...... 64 2.4.1 RNA-Seq library preparation ...... 64 2.4.2 Galaxy ...... 65 2.4.3 Mapping miRNAs to miRBase ...... 65 2.4.4 Finding differentially expressed miRNAs ...... 66 2.4.5 miRComb ...... 66 2.5 Exosome methods ...... 67 2.5.1 Exosome free media preparation ...... 67 2.5.2 Exosome Isolation ...... 67 2.5.3 Exosomal RNA isolation ...... 68 2.5.4 Exosomal RNA quantification ...... 68 2.5.5 Dynamic Light Scattering ...... 69 2.5.6 Exosome labelling with PKH26 dye ...... 69 2.5.7 Electron microscopy of Exosomes ...... 69 2.5.8 Cartilage Digestion and Cartilage Exosome Isolation ...... 70 2.6 Molecular biology ...... 71 2.6.1 Agarose gel electrophoresis ...... 71 2.6.2 Ligations ...... 71 2.6.3 Transformation of plasmids into competent E.coli ...... 71 2.6.4 Plasmid Verification ...... 71 2.6.5 CD63-eGFP Fusion Protein plasmid ...... 72 2.7 Third Generation Lentiviral Production ...... 73 2.7.1 HEK293T cell culture ...... 73 2.7.2 Plasmid transduction ...... 73 2.7.3 Lentivirus collection and isolation ...... 74 2.7.4 Lentivirus quantification ...... 74

3 Results I - Whole Transcriptome and Small RNA-seq analysis of Chondrogenesis in hESCs 76 3.1 Aims and Introduction ...... 76 3.2 Results ...... 77 3.2.1 Small RNA-seq quality control ...... 77 3.2.2 Changes in miRome and Transcriptome variation during hESC directed chondrogenesis ...... 79 3.2.3 Highest expressed miRNAs in hESCs and hESC-derived chondroprogenitor cells ...... 83

Chapter 0 4 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

3.2.4 Differential expression analysis of miRome and transcriptome of hESCs undergoing directed chondrogenesis ...... 84 3.2.5 Biological variability in hESC directed chondrogenesis can be exploited to identify novel miRNAs ...... 89 3.2.6 Stage-wise differential expression analysis miRNAs ...... 92 3.3 Discussion ...... 97 3.3.1 Small RNA-seq technical variation ...... 97 3.3.2 Cell line variation ...... 98 3.3.3 Highest expressed miRNAs during hESC directed chondrogenesis . . 99 3.3.4 Summary ...... 101

4 Results II - Integrated miRomics and Transcriptomics analysis 103 4.1 Introduction and Aims ...... 103 4.2 Results ...... 104 4.2.1 Correlation Analysis ...... 104 4.2.2 Protein Network Analysis ...... 109 4.2.3 MicroRNA Target Interaction Network ...... 113 4.2.4 MicroRNA Functional Studies- miR-199a Inhibition ...... 116 4.3 Discussion ...... 117 4.3.1 Identification of novel regulators during hESC-directed chondrogenesis by co-expression network analysis ...... 117 4.3.2 MicroRNA Target Interaction Analysis ...... 127 4.3.3 Conclusion ...... 127

5 Results III - Exosomes 129 5.1 Aims and Introduction ...... 129 5.2 Results ...... 129 5.2.1 Exosome validation ...... 129 5.2.2 Expression of miR-302a in Pluripotent stem cell derived exosomes . . 131 5.2.3 Exosome qPCR optimisation ...... 132 5.2.4 Exosomal miRNAs in hESC directed chondrogenesis ...... 138 5.2.5 Exosomal Sequencing Quality ...... 139 5.2.6 RNA-seq Cluster Analysis ...... 142 5.2.7 Exosome-enriched miRNAs from hESCs and chondroprogenitors . . 144 5.2.8 Exosomal miRNA motif enrichment ...... 146 5.2.9 Pathway analysis of exosomal enriched miRNAs ...... 146 5.2.10 Cartilage Exosomes ...... 149 5.2.11 Exosome Uptake and Localisation ...... 150

Chapter 0 5 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

5.2.12 High-throughput Exosome Uptake Assay ...... 153 5.2.13 Pluripotent exosomes can effect gene expression ...... 154 5.2.14 Pluripotent exosomes promote proliferation of hESCs ...... 157 5.3 Discussion ...... 158 5.3.1 Exosome Validation and Quantification ...... 158 5.3.2 Accurate quantification of exosomal miRNA levels ...... 159 5.3.3 Exosomal enrichment of miRNAs ...... 160 5.3.4 Cartilage-derived exosomes ...... 161 5.3.5 Role of exosomal miRNAs during pluripotency and differentiation . . . 163 5.3.6 Conclusion ...... 165

6 Discussion 166 6.1 General Discussion ...... 166 6.1.1 Main findings ...... 166 6.1.2 Cartilage miRNA regulation during hESC-directed Chondrogenesis . . 167 6.1.3 Role of exosomes ...... 169 6.1.4 Candidate miRNAs identified ...... 171 6.2 Future Work ...... 172 6.2.1 Novel regulators of hESC-directed chondrogenesis ...... 172 6.2.2 Heterogeneity during hESC-directed chondrogenesis ...... 173 6.2.3 Investigating the role of exosomes during pluripotency and differentiation ...... 174 6.2.4 Cartilage Exosomes ...... 176

References 215

A Appendix 216 A.1 List of primers for RT-PCR, cloning and DNA sequencing ...... 216 A.2 Co-expressed miRNAs and protein-coding genes ...... 218

Word Count: 60,066

Chapter 0 6 List of Figures

1.1 Canonical microRNA biogenesis ...... 29 1.2 The TGFβ signaling pathway in chondrogenesis is targeted by many miRNAs 36 1.3 Number of exosome related published papers on PubMed ...... 44 1.4 Results of top 20 identified proteins in exosomes from ExoCarta ...... 48 1.5 Exosome Biogenesis ...... 51

2.1 Summary of Galaxy workflow for small RNA-seq library formatting for subsequent mapping ...... 66 2.2 Workflow of exosome isolation by ultracentrifugation ...... 68 2.3 Plasmid used to overexpressed CD63 tagged with eGFP ...... 73

3.1 Experimental Plan for small and whole transcriptome RNA-seq ...... 78 3.2 Quality assessment of small RNA libraries ...... 79 3.3 Spearman’s correlation matrix of hESC directed chondrogenesis ...... 81 3.4 Investigating the variability of hESC directed chondrogenesis ...... 82 3.5 Top expressed miRNAs in hESCs and hESC-derived chondroprogenitors . . 84 3.6 Analysis of differential expression correction methods ...... 85 3.7 Heat map of differentially expressed miRNAs with unsupervised hierarchical clustering ...... 87 3.8 Heat map of differentially expressed genes with unsupervised hierarchical clustering ...... 88 3.9 Enriched miRNAs in optimal hESCs directed chondrogenesis ...... 91 3.10 Stage-wise differential expression of miRNAs during DDP ...... 93 3.11 Differentially expressed miRNAs between each stage of Hues1 directed chondrogenesis ...... 94 3.12 Differentially expressed miRNAs between each stage of Man7 directed chondrogenesis ...... 95 3.13 Differentially expressed miRNAs between stage 0 and 3 of Man7 directed chondrogenesis ...... 96 3.14 Comparison of developing chondrocytes miRome with hESC directed chondrogenesis...... 101

7 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

4.1 Schematic of approach used to integrate miRome and transcriptome . . . . . 104 4.2 Pearson’s correlation analysis of all genes expressed during hESC-directed chondrogenesis ...... 107 4.3 Expression of miRNAs from co-expression clusters ...... 108 4.4 Protein-Protein interaction analysis of cluster 4 genes ...... 111 4.5 Protein-Protein interaction analysis of cluster 5 genes and their first neighbours112 4.6 MicroRNA-mRNA Interaction Network analysis using miRComb ...... 115 4.7 Inhibition of miR-199a-3p during directed chondrogenesis of hESCs . . . . . 117

5.1 Validation of exosomes isolated from pluripotent stem cells ...... 131 5.2 Presence of miRNAs in pluripotent stem cell-derived exosomes ...... 132 5.3 Correlation of hESC-exosomal RNA expression with total protein ...... 134 5.4 Expression of small RNA endogenous controls during hESC directed chondrogenesis ...... 137 5.5 Validation of hESC-directed chondrogenisis and isolation of exosomal miRNAs139 5.6 Exosomal small RNA-seq quality control ...... 141 5.7 Quality assessment of exosomal cellular small-RNA seq libraries by cluster analysis ...... 143 5.8 Pluripotent and chondrogenic exosomal enrichment of miRNAs ...... 145 5.9 Motif enrichment analysis of exosome-enriched miRNAs ...... 146 5.10 Target enrichment analysis of exosomal miRNAs ...... 148 5.11 MicroRNA content of cartilage-derived microvesicles ...... 150 5.12 Uptake analysis of exosomes ...... 152 5.13 Development of high-throughput exosome uptake assay ...... 154 5.14 Gene expression analysis of hESCs after growth factor replacement pluripotent-exosomes ...... 156 5.15 Effect of pluripotent stem cell derived exosomes of hESC proliferation . . . . 157

Chapter 0 8 List of Tables

1.1 Summary of miRNAs in cartilage ...... 37 1.2 Summary of different exosome isolation techniques ...... 46

2.1 Mouse embryonic fibroblast medium ...... 58 2.2 Different substrate coating procedures ...... 60 2.3 MEF plating densities ...... 60 2.4 Human embryonic stem cell medium ...... 61 2.5 Feeder-free hESC culture medium ...... 62 2.6 Directed Differentiation basal medium ...... 63 2.7 Directed Differentiation Protocol ...... 63 2.8 Human Articular Chondrocyte (HAC) Medium ...... 70 2.9 Herculase II Cycle for CD63 insert ...... 72 2.10 HEK293T medium ...... 75 2.11 HEPES-Buffered Saline ...... 75

6.1 Candidate miRNAs ...... 172

A.1 Table of primers ...... 217 A.2 Co-expressed clusters (1-3) of miRNAs and protein-coding genes ...... 218 A.3 Co-expressed clusters (4-6) of miRNAs and protein-coding genes ...... 222

9 List of Abbreviations

ACV : Articular Cartilage Vesicle ADAMTS : A Disintegrin And Metalloproteinase with Thrombospondin Motifs BMP : Bone Morphogenetic Protein BSA : Bovine Serum Albumin CDS : Coding sequence Chr : Chromosome DAPI : 4’,6-diamidino-2-phenylindole DDP : Directed Differentiation Protocol dH2O : Distilled H2O DLS : Dynamic Light Scattering DMEM : Dulbecco’s modified Eagle’s medium DMSO : Dimethyl Sulfoxide ECM : Extracellular Matrix EDTA : Ethylenediaminetetraacetic acid ESC : Embryonic Stem Cells FBS : Fetal Bovine Serum FGF : Fibroblast Growth Factor FN : Fibronectin GAG : Glycosaminoglycans Gel : Gelatin GO : Glycosaminoglycans GSK3 : Glycogen synthase kinase 3 GTCF : Genomic Technologies Core Facility HAC : human articular chondrocytes HDAC : Histone deacetylase HS : Heparin sulphate HSPGs : Heparin sulphate proteoglycans ILV : Intraluminal vesicle iPSC : Induced PLuripotent Stem Cells ITS : Insulin-Transferrin-Selenium KOSR : Knock-out Serum Replacement L-Glu : L-Glutamine LB : Luria-Bertani MEF : Mouse Embryonic Fibroblasts

10 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells miRNAs : microRNAs MMPs : Matrix metalloproteinases MPs : Metalloproteinases MS : Mass spectrometry MT : Mutant MVB : Multivesicular Bodies NEAA : Non-Essential Amino Acids NEB : New England BioLabs NGS : Next Generation Sequencing NSAIDS : Non steroidal anti-inflammatory drugs NT : Neurotrophin OA : Osteoarthritis PBS : Phosphate Buffered Saline PCA : Principal Component Analysis PFA : Paraformaldehyde PKA : Protein kinase A PNA : Peptide Nucleic Acid PSC : Pluripotent Stem Cell PTHrP : Parathyroid hormone related peptide RA : Retinoic acid RT-PCR : Real-Time Polymerase Chain Reaction Seq : Sequencing siRNA : Small interfering RNA TAE : Tris-acetate-ethylenediamine tetraacetic acid TBE : Tris-Borate-EDTA TE : Tris-EDTA TEMED : N,N’,N’-Tetramethylethylenediamine TGF-β : Transforming growth factor β TIMPs : Tissue inhibitors of metalloproteinases UTR : Untranslated region VTN : Vitronectin WNTs : Wingless-type MMTV integration site family members WT : Wild-type

Chapter 0 11 Abstract

There is a huge unmet clinical need to treat damaged articular cartilage such as that caused by osteoarthritis (OA) with an estimated 8.75 million people in the UK having sought treatment for OA (ARUK 2013). Embryonic stem cells (ESCs) offer a promising alternative therapeutic approach, potentially providing an unlimited source of chondrocytes capable of regenerating the damaged cartilage however this is limited by the efficiency of the chondrogenic differentiation protocol. An improved understanding of the posttranscriptional regulation of chondrogenesis by microRNAs (miRNAs) may enable us to improve hESC chondrogenesis. Also the recent discovery that miRNAs are selectively packaged into exosomes which can then be transferred to and be functionally active within neighbouring cells suggests they may have a role in cell-cell communication. This project investigated the regulation of miRNA expression in relation to the transcriptome during hESCs-directed chondrogenesis and the possible role for exosomes during differentiation and in stem cell maintenance of hESCs. Small RNA-seq and whole transcriptome sequencing was performed on distinct stages of hESC-directed chondrogenesis using the Directed Differentiation Protocol (DDP) developed in our lab. Also small RNA-seq was performed on exosomes isolated from hESCs and chondroprogenitors along with the donor cells that the exosomes originated from. This revealed significant changes in the expression of several miRNAs during hESC- directed chondrogenesis including: upregulation of miRNAs transcribed from the four Hox complexes, known cartilage associated miRNAs and the downregulation of pluripotency associated miRNAs. Overall miRome and transcriptome analysis revealed the two hESC lines exhibited slightly different miRome and transcriptome profiles during chondrogenesis, with Man7 displaying larger changes in miRNA and mRNA expression as it progressed through the DDP suggesting it may be more predisposed to undergo chondrogenesis. Integration of miRomes and transcriptomes generated during hESC-directed chondrogenesis identified four key functionally related clusters of co-expressed miRNAs and protein coding genes: pluripotency associated cluster, primitive streak cluster, limb development cluster and an extracellular matrix cluster. Further investigation of these gene/miRNA clusters allowed the identification of several potential novel regulators of hESC-directed chondrogenesis. In accordance with the reported literature the exosomal miRNAs from hESCs and hESC-chondroprogenitors were enriched with a guanine rich motif. Notably, several of these were enriched with targets associated with embryonic skeletal system development suggesting they may play a role in regulating differentiation. Preliminary functional experiments examining pluripotency-associated exosomes suggests they may have a role in regulating hESC stem cell maintenance. However the molecular mechanism by which this is achieved has not been investigated. This research identified main miRome and transcriptome changes during hESC-directed chondrogenesis leading to the identification of several potential novel regulators of chondrogenesis and pluripotency which can be further investigated. This project has also highlighted the potential of exosomal miRNAs to regulate hESC stem cell maintenance and differentiation.

12 Declaration

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

13 Copyright Statement

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14 Acknowledgements

Firstly I would like to express my very great appreciation to my supervisor, Prof Sue Kimber, for giving me the opportunity to work on this innovative research project and whose constant support and guidance has allowed me to progress in my research. I would like to give my thanks to my co-supervisor, Dr Matthew Ronshaugen, for his advice and support with the microRNA analysis and for all his comments regarding my thesis. I wish to express my thanks to my advisor Prof. Hilary Ashe for all her constructive comments during our meetings. I owe a massive thanks to all members (past and present) of the Kimber lab, this project wouldn’t have been as rewarding or as enjoyable without them. Firstly I would like to thank Nicola Bartley for teaching me all the stem cell culture techniques, also for her constant help and support and most importantly for not dropping me from the climbing wall. Thanks go to Dr Helen Smith for her assistance with all things bioinformatic also for making me laugh with all her hilarious lunch time stories. Thanks also to Dr Steven Woods for all our miRNA chats and the (several) pints we discussed them over. Steven performed the cartilage digestion for the cartilage-exosome isolation described in Chapter 5. Also I would like to thank Dr Ioannis Bantounas who taught me all my molecular cloning and lentivirus techniques and also some great board games. Thanks go to Dr Christopher Smith for providing me with samples for the exosome sequencing in Chapter 5 and also shoulder to cry on once. I would also like to thank Dr. Alan Kerby for all the times he fed my cells and for all our fun conversations, he was great desk buddy although he could have made me more teas. I would also like to thank Dr Edina Silajdzic for feeding me so well during my PhD and thanks to Dr Phil Lewis for some great G.o.T discussions and music recommendations for thesis writing (and for making me not the biggest nerd in the lab). I would like to thank Dr Aixin Cheng who provided the RNA-seq data in Chapter 3 without which this would be a very thin thesis. I am truly grateful for the amazing work environment everyone in the lab had contributed to. I couldn’t of asked for a better lab to work in and hope to remain in contact with all members of the lab. I would also like to thank all the staff at the University of Manchester Genomic Technologies Core Facility in particular Dr Andy Hayes, Stacey Holden and Michael Smiga for processing my samples for RNA-seq and TapeStation analysis. Also thanks go to Dr Thomas Jowitt from the Biomolecular Analysis Core Facility for providing training on the Malvern Zetasizer allowing me to perform Dynamic Light Scattering analysis of my exosome samples. I would also like to thank Gareth Hughes for providing the electron microscopy analysis of my exosomes samples. I would like to thank the army of thesis proof-readers (Katie, Frances, Sarah, Phil, Helen, Edina, Steven and Alan) for their help in making the following Eric Morecambe quote a lot less applicable to my thesis; ”I’m playing all the right notes, but not necessarily in the right order”. I owe a massive thanks to everyone I’ve met outside of the lab for making the four years in Manchester fly by. In particular Dr Sarah Ryan, Maria Lizio, Katie Roberts and Frances Smith, for all our amazing ’Scientist abroad’ trips and some intense board game nights. I would also like to thank my parents, for their constant support throughout my PhD and for dragging me to all Saturday morning dyslexia tutoring, without which this thesis wouldn’t of been possible. Also thanks to all my siblings Madlen, Tomos, Huw and Scott for all their support. For the funding for my PhD project I would like to acknowledge the BBSRC Doctoral Training Partnership without which this project would not be possible.

15 Dedication

Dedicated to the memories of my Grandmothers Dr Helen Camilla De Clery Roll (1928-2016) and Dr Mary Carlyon Griffiths (1925-2015).

16 Chapter 1

Introduction

1.1 General Overview

Osteoarthritis (OA) is the most common musculoskeletal condition in older people with an estimated 8.75 million people having sought treatment in the UK (ARUK 2013). There is currently no available cure however cell based therapies potentially provide a long-term treatment. There is a vast effort to improve chondrogenic differentiation protocols with the aim to efficiently and robustly generate chondrocytes for a cartilage cell-based therapy. Chondrogenesis has been well-studied for decades with the main transcription machinery (Sox9, L-Sox5 and Sox6) and signaling pathways (TGF-β signaling) having been uncovered (Lefebvre and Dvir-Ginzberg 2016; Danisoviˇ cˇ et al. 2012). However, since the recent discovery of small non-coding RNAs known as microRNAs (miRNAs) which are posttranscriptional regulators acting to fine-tune gene expression in nearly every biological processes (Filipowicz et al. 2008), these have been of great interest as regulators of chondrogenesis. Several miRNAs have already been identified to regulate chondrogenesis (Le et al. 2013), however the precise levels and exact timing of expression required of each during chondrogenesis to produce functional articular chondrocytes is unclear. The recent discovery that miRNAs are selectively packaged into exosomes (Villarroya-Beltri et al. 2013) has uncovered the potential of exosomes to act as cell-cell communicators during differentiation. This project aims to investigate the regulation of chondrogenesis by miRNAs and the possible role of exosomes in the maintenance of pluripotent stem cells and early differentiation using RNA-seq analysis.

1.2 Articular Cartilage Cell Therapy

Articular cartilage is a subset of hyaline cartilage found at the ends of bones in diarthrodial joints. It is a hypocellular, aneural, avascular tissue that allows pain-free frictionless movement of joints. It consists mainly of extracellular matrix (ECM) produced from the only cell type present in cartilage; chondrocytes. The extracellular matrix consists of collagen fibers, mainly type II collagen these provide tensile strength, and aggrecan that provides the shock adsorption property of cartilage. Aggrecan is a highly hydrophilic proteoglycan which produces an osmotic gradient that draws water inside cartilage this

17 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells can then be displaced when a compressive load is applied to the joint providing a cushioning effect (Becerra et al. 2010). Unfortunately cartilage has a very low regenerative capacity due to the inability of MSCs to migrate into the cartilage and give rise to new chondrocytes; this is due to its lack of blood supply and substantial ECM content. The main disease affecting articular cartilage is osteoarthritis (OA) and is a huge economic burden due to cost of treatment, disability and comorbidity. Osteoarthritis involves reduction in articular cartilage leading to functional failure of synovial joints. The loss of cartilage is caused by a combination of enzymatic degradation of the ECM and loss of articular chondrocytes due to apoptosis or differentiation to a hypertrophic phenotype which no longer expresses aggrecan or type II collagen. The pathogenesis of OA is complicated by multiple factors including mechanical injury, effect of ageing, genetic factors and inflammation (Goldring and Goldring 2010). Current therapies are limited to either pain relief or joint replacement for patients over 60 years with severe osteoarthritis. Some experimental treatments including microfracture and mosaicplasty have shown to provide a short-to-midterm improvement but have poor long term results as they generally rely on new cartilage being formed under unfavorable conditions (Mithoefer et al. 2009). Microfracture involves drilling 3mm deep holes into the bone marrow to stimulate cartilage growth whereas mosaicplasty works by removing several plugs of hyaline cartilage from a non-weight bearing area of the knee and implanted into the defected articular cartilage. Implanting healthy chondrocytes into the cartilage defect would be an ideal solution as they secrete and assemble all the components forming the extracellular matrix. Autologous chondrocyte implantation (ACI) is the first cell-based therapy used to treat articular cartilage defects. This involves removing chondrocytes from a patient’s non-defective cartilage and expanding them in vitro before implanting them into the patient’s cartilage defect. This was shown to be significantly better than mosaicplasty in a randomised clinical trial (Bentley et al. 2003). However this has many limitations including the problem that chondrocytes dedifferentiate in vitro and have very low proliferation (Darling and Athanasiou 2005; Nejadnik et al. 2010). Another source of chondrocytes would be to derive them from mesenchymal stem cells (MSCs). A study in 2010 showed MSC-derived chondrocytes to be as effective as autologous chondrocytes for articular cartilage repair (Nejadnik et al. 2010). However MSC-derived chondrocytes are prone to developing a hypertrophic phenotype in culture indicated by increased expression of type X collagen and decreased expression of Sox9 and type II collagen, this can lead to cell death or calcification when implanted (Oldershaw 2012; Barry et al. 2001). Embryonic stem cells (ESCs) can also differentiate into chondrocytes however the use

Chapter 1 18 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells of ESCs in therapy hinges on the development of an efficient GMP-grade differentiation protocol. Derivation of chondrocytes from hESCs was first achieved by co-culturing ESCs with primary chondrocytes (Vats et al. 2006; Bigdeli et al. 2009). In another co-culture system ESCs were cultured on stromal cells to induce mesenchymal differentiation, then the mesenchymal stem-like cells are FACS sorted for CD73+ cells (Barberi et al. 2005) or CD34+CD73-(Kopher et al. 2010) and then differentiated into chondrocytes via pellet culture supplemented with TGF-β3 (Barberi et al. 2005). None of these co-culture studies investigated these pro-differentiation signals released by the co-culturing cells (i.e. chondrocytes or stromal cells) therefore making the undefined differentiation protocol very challenging to reproduce. One way to derive chondrocytes from ESCs without the use of co-culture is by culturing ESCs in a 3D suspension as embryonic bodies with pro-chondrogenic growth such as TGF- β3, TGF-β1, IGF-I and BMP2 (Koay et al. 2007). However the cells produced fibrocartilage- like pellets with high expression of collagen type I and low expression of collagen type II, also the presence of undifferentiated cells or cells differentiated into other lineages during embryonic body (EB) formation was not assessed. One study was able to generate cartilage pellets from ESCs without the use of an intermediate embryonic body stage and without co-culture (Nakagawa et al. 2009). In this study single cell hESCs were plated onto gelatin coated plates which differentiated into fibroblastic-like cells after 3 weeks of culture, these cells were then cultured in a pellet culture system for 14 days in medium supplemented with TGF-β1 and BMP7. The hESC-derived cartilage pellets expressed collagen type II, aggrecan and produced sulfated glycosaminoglycans (Nakagawa et al. 2009). Although the intermediate fibroblastic-hESCs were not characterised they were assumed to be mesenchymal stem-like cells. However these methods are generally inefficient, have low reproducibility and require cell sorting. Another method for generating chondrocytes is by transdifferntiation of human dermal fibroblasts by retroviral transduction of two reprogramming factors (c-Myc and Klf4) and one chondrogenic factor (SOX9) (Outani et al. 2013). The induced chondrogenic (iChon) cells generated by this method showed low expression of fibroblast collagens COL1A1 and COL1A2 and high expression of cartilage markers COL2A1 and ACAN compared to their expression in fibroblast, iChon cells also displayed low expression of hypertrophic markers COL10A1 and MMP13 compared to chondrogenic differentiated MSCs. After 3 weeks of pellet culture iChon cells produced matrix containing type II collagen and no type I collagen also iChon cells could repair cartilage defects in SCID mice (Outani et al. 2013). However due to use of integrating vectors and overexpression of oncogenic c-Myc, there is a risk iChon cells may be turmorgenic, transition to integration-free vectors may be required

Chapter 1 19 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells before iChon cells are safe for use as a clinical therapy. A more efficient and reliable way of producing chondrocytes has been achieved using a chemically defined direct differentiation protocol developed by Oldershaw et al. which produces a chondroprogenitor population with 74%–97% of cells expressing Sox9 protein dependant on hESC line used. This approach uses a combination of growth factors to induce chondrogenic differentiation of hESCs in a step-wise manner producing chondroprogenitors via intermediate cell types distinct from mesenchymal stem cells (Oldershaw et al. 2010). Firstly, hESCs are signalled towards a primitive streak/mesoendoermal stage of cells via addition of Wnt-3a and Activin-A producing a population of cells expressing mesendoderm markers CDH1, GATA4 and GSC2 and early mesoderm marker T. Next cells undergo differentiation towards mesoderm by addition of BMP4 and Follistatin (Activin-A antagonist) leading to expression of mesoderm markers KDR and CXCR4, and loss of endoderm marker GATA4. In the last stage of the directed differentiation protocol cells are signalled to undergo chondrogenesis by addition of GDF5 generating cells expressing cartilage markers COL2A1, ACAN, SOX9 and SOX6, and producing sulfated glycosaminoglycan (Oldershaw et al. 2010). The chondroprogenitors produced by this method have also displayed functional properties by their ability to repair cartilage defects in rat models (Cheng et al. 2014).

1.3 Chondrogenesis

To fully understand how to produce chondrocytes in vitro it is helpful to understand how it occurs in normal human development. Chondrogenesis is an essential step in endochondral ossification where a cartilage template is produced and subsequently replaced with bone to give rise to long bones in development (Colnot 2005). This process begins with migration of undifferentiated MSCs to areas to become bone these MSCs produce an ECM rich in type I collagen, hyaluronan and fibronectin preventing intimate cell-cell contact. Next these MSCs undergo ‘condensation’, an essential step to allow chondrogenesis, for this to occur MSCs change their gene expression from type I collagen and hyaluronan to N-cadherin and other cell adhesion molecules such as NCam and Notch (Colnot 2005; Lefebvre and Bhattaram 2010; Hardingham et al. 2006). This leads to cell-cell contact and cell-matrix interactions involving fibronectin (Frenz et al. 1989) triggering pathways involved in chondrogenesis. The MSCs differentiate into chondrocytes which produce type II collagen and aggrecan and they stop expressing adhesion molecules leading to loss of cell-cell contact and a change in the composition of the ECM which encapsulates the chondrocytes. Two different populations of chondrocytes with different phenotypes arise from these encapsulated chondrocytes. One population gives rise to epiphyseal chondrocytes of the growth plate these proliferate and undergo further

Chapter 1 20 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells differentiation to produce hypertrophic chondrocytes characterised by expression of type X collagen with reduced expression of type II collagen. These then become vascularized allowing transportation of osteoblasts into the cartilage which replace the chondrocytes leading to mineralized bone (DeLise et al. 2000). The second population gives rise to articular chondrocytes at the end of the bone characterized by expression of type II collagen and a lower rate of cell division.

1.3.1 Signaling Pathways Regulating Chondrogenesis

The decision for cells to undergo chondrogenesis depends on signals arising from soluble factors including TGF-β growth factors and Wnt ligands as well as pathways activated by cell-cell contact or cell-matrix interactions. This leads to downstream signaling activating pro-chondrogenic transcription factors Sox9, Sox5 and Sox6 while also silencing the pro- osteogenic transcription factor Runx2. Understanding what key signals are involved in chondrogenesis is essential to produce an efficient chondrogenic protocol.

TGF-β family

TGF-β growth factors are involved in driving a variety of cellular processes they act by binding to their receptors leading to phosphorylation of a smad protein, which translocates to the nucleus and effects gene transcription (Figure 1.2). There are 5 receptor-regulated Smads (R-Smad), Smad 2 and 3 are activated by TGF-β, Activin and Nodal ligands while Smad1/5/8 are activated by BMP and GDF ligands (Weiss and Attisano 2013). TGF-β growth factors have been extensively investigated for their use in cartilage engineering, the most promising growth factors are TGF-β1, TGF-β3, BMP2, BMP4, BMP7 and GDF5 (Danisoviˇ cˇ et al. 2012). These growth factors may also lead to activation of the MAPK pathway leading to chondrogenesis. Inhibition of Erk1/2 activation prevented TGF-β1 induced chondrogenesis of MSCs (Arita et al. 2011). Many in vivo studies have shown the importance of the TGF-β family during chondrogeneisis. One in vivo study showed the importance of BMPs in cartilage development when its antagonist, Noggin, prevented skeletal development at two distinct stages: firstly by inhibiting the condensation of MSCs, and secondly by preventing differentiation of chondroprogenitors into chondrocytes (Pizette and Niswander 2000). Another TGF-β growth factor GDF-5, has also shown to be important in cartilage development, it was first identified as a potential cartilage regulator due to its distinct expression pattern in the developing mouse limb and both GDF-5 null mice and GDF5/BMP5 double-mutant mice had skeletal defects with the later case being more severe (Storm and Kingsley 1996). The role of GDF5 in limb formation was further examined by assaying the response of mouse and chick developing limbs to recombinant GDF5. This showed GDF5 protein stimulated cartilage development while inhibiting joint

Chapter 1 21 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells formation in the embryonic mouse limb (Storm and Kingsley 1999). The TGF-β growth factor GDF6 has also been shown to be required for normal skeletal development, loss of GDF6 led to mice developing skeletal abnormalities at sites distinct the ones observed in GDF5 mutant mice, also mice GDF5/GDF6 null mice exhibited more severe skeletal abnormalities including short limbs, joint fusion and altered cartilage in the intervertebral joints indicated by reduced Alcian Blue staining (Settle et al. 2003). A study examining the effects of GDF5 and BMP4 in mouse embryonic limb bud formation showed they both have distinct functions in promoting chondrogenesis. BMP4 induces chondrogenesis of mesenchymal cells to express cartilage markers whereas GDF5 enhanced cartilage formation by increasing Sox9 expression and promoting chondroprogenitor cell aggregation (Hatakeyama et al. 2004).

Fibroblast Growth Factor (FGF) Family

This large family of growth factors, consisting of 23 members FGF1-23, has shown to be involved in various cellular processes including proliferation, differentiation and motility. Of these members two, FGF-2 and FGF-18, have been identified as important in chondrogenesis. FGF-2 is involved in many processes and cell types, however its effects in cartilage homeostasis are subject to controversy. Many studies show FGF-2 promotes chondrocyte proliferation suggesting it may be useful in cartilage regeneration. However the chondrocytes produced are fibroblastic with increased expression of matrix-degrading enzymes and reduced matrix production leading to an overall reduction in matrix cartilage. FGF-18 is a well known prochondrogenic factor, it increases matrix formation and differentiation while inhibiting cell proliferation. FGF-18 suppresses expression of Noggin, a BMP antagonist, thereby increasing BMP activity and promoting chondrogenesis (Ellman et al. 2008).

1.3.2 Transcriptional Regulation of Chondrogenesis

The importance of Sox9, L-Sox5 and Sox6 in chondrogenesis have been highlighted in many reviews (Akiyama 2008; Ikeda et al. 2005; Lefebvre 2002; Lefebvre and Dvir-Ginzberg 2016). L-Sox5 and Sox6 work in co-operation to increase the efficacy of Sox9 binding to key cartilage genes including aggrecan and Col2a1 (Han and Lefebvre 2008; Ng et al. 1997). Sox9 also promotes chondrogenesis by inhibiting Runx2 a transcription factor essential for osteoblast lineage differentiation and hypertrophic differentiation of chondrocytes. This is done by either binding to Runx2 directly and preventing its function (Zhou et al. 2006) or by indirectly increasing expression of Nkx3.2 a Runx2 negative regulator (Yamashita et al. 2009; Lengner et al. 2005). Another way Sox9 promotes chondrogenesis is by preventing Wnt/beta-catenin signaling, a pathway know to inhibit chondrogenesis, by enhancing

Chapter 1 22 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells phosphorylation of beta-catenin leading to its degradation (Topol et al. 2009). Transcription factors Pax1 and Pax9 may also play an important role in chondrogenesis by activating transcription of Nkx3.2 (Rodrigo et al. 2003). Sox5 and Sox6 also act to promote chondrogenesis by reducing expression of Runx2 by an unknown mechanism (Hartmann 2009).

1.4 Embryonic Stem Cells

Human embryonic stem cells (ESCs) are derived from the inner cell mass (ICM) of the blastocyst. They are pluripotent and capable of rapid self-renewal providing a potentially unlimited source of cells for regenerative medicine. Pluripotency is the ability of a single cell to give rise to any cell of the three germ layers; mesoderm, ectoderm and endoderm. Self- renewal is the ability to give rise to a daughter cell identical to the mother. Understanding the molecular mechanism involved in maintaining pluripotency and undergoing selfrenewal is essential for efficient expansion of human ESCs, which are poised to differentiate.

1.4.1 Pluripotency control

Pluripotency in ESCs involves a complex regulatory network that maintains expression of pluripotent genes while also silencing genes involved in differentiation and lineage specification. It is mainly controlled by the pluripotency promoting transcription factors Sox2, Oct4 and Nanog. Oct4 and Nanog were identified as key pluripotency regulators due to their specific expression in ESCs and experiments showing their importance in maintaining pluripotency. Overexpression of Nanog can maintain pluripotency in mESCs independent of LIF (a cytokine essential for mESC maintenance) and Oct4-deficient embryos lose pluripotency indicated by all the ICM cells becoming restricted to differentiate to trophectoderm (Chambers et al. 2003; Nichols et al. 1998). It has been shown that a precise level of Oct4 is required to maintain pluripotency, if Oct4 is overexpressed in mESCs this causes differentiation into primitive endoderm or mesoderm and if Oct4 is repressed this causes differentiation to trophectoderm (Niwa et al. 2000). Sox2 is co-expressed with Oct4 in ESCs and forms a heterodimer with Oct4 to promote expression of ESC specific genes however its main function in pluripotency may be to maintain sufficient levels of Oct4 (Masui et al. 2007). Unlike Oct4 and Nanog, Sox2 is not specific to ESCs as it’s also found in neural precursors and other cell types (Avilion et al. 2003). This trio of transcription factors (Oct4, Sox2 and Nanog) acts in three ways to maintain pluripotency. Firstly each transcription factor binds to and activates its own promoter as well as the promoters of the other two members to maintain high levels of each transcription factor. Secondly specific members of the trio can interact with a small number of other transcription factors that regulates crucial early developmental fate decisions e.g. Cdx2,

Chapter 1 23 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Gata4, Gata6. Thirdly, the transcription factors co-occupy and regulate expression in two sets of genes, one set that is transcriptionally active in ESCs and is necessary to maintain the ESC state, and the other set of genes that are silenced in ESCs and are involved in differentiation and lineage specification (Boyer et al. 2006).

1.4.2 Extrinsic Factors Promoting Self-Renewal in ESCs

Many pathways involved in hESC self-renewal have been identified, they include TGF-β signaling via TGF-β, Nodal, BMP and Activin ligands, FGF growth factors leading to activation of PI3K/AKT signaling pathway and Wnts leading to beta-catenin signaling (Stewart et al. 2006). The two different branches of TGF-β signaling, Smad2/3 and Smad1/5, have opposing effects on hESC pluripotency. Activation of the Smad1/5 branch in hESCs by BMPs leads to rapid downregulation of Nanog and Oct4 resulting in loss of pluripotency (Beattie et al. 2005). Whereas TGF-β/Nodal/Activin ligands leading to Smad2/3 activation maintains pluripotency. Overexpression of Nodal maintains expression of pluripotent markers and prevents spontaneous differentiation of hESCs (Vallier et al. 2004). Also culturing hESCs in medium enriched with Activin A is capable of maintaining hESCs in a pluripotent state (Beattie et al. 2005). However overexpression of Activin A signaling can induce endoderm formation (D’Amour et al. 2005; Gadue et al. 2006). Another pathway known to be important in the maintenance of ESC self-renewal and pluripotency is FGF signaling. Addition of FGF2 to hESCs is essential for feeder-free maintenance of hESCs although how it is involved in ESC self-renewal is unclear. One way it could promote self-renewal is by antagonizing BMP signaling by inhibition of Smad1 (Xu et al. 2005) another is by activating PI3K/Akt signaling leading to MEK inhibition (Paling et al. 2004). The Wnt/beta-catenin pathway is a signaling pathway involved in cell proliferation and cell fate determination although its effects in ESCs have been contradictory. Binding of Wnt to its receptor, Frizzled, leads to activation of Disheveled which subsequently inhibits the destruction complex, which contains GSK-3 and is responsible for beta-catenin degradation. This leads to accumulation of beta-catenin which translocates to the nucleus where it can act as a transcriptional co-activator of the Lef/Tcf family of binding proteins and activate transcription. A study by Sato et al., showed activation of the Wnt pathway by use of BIO, a GSK-3 inhibitor, is sufficient to maintain self-renewal and sustains expression of Nanog and Oct4 in both mESCs and hESCs cultured in feeder-free systems (Sato et al. 2004). However this has been largely discredited by several studies including one which showed that the concentration of BIO used to maintain hESCs (2µM) in the Sato et al., study is not sufficient to activate the beta-catenin pathway in the absence of exogenous Wnt ligands (Davidson et al. 2012). Also many studies showed that the Wnt/beta-catenin pathway promotes differentiation and not self-renewal in hESCs. One

Chapter 1 24 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells study showed that BIO promoted differentiation of hESCs in a feeder-free system and that another structurally unrelated GSK-3 inhibitor, 1m, promoted differentiation of hESCs cultured feeder-free or on MEFs (Bone et al. 2011). Also activation of the pathway with Wnt3a led to loss of self-renewal and induction of mesoderm lineage genes and the hESCs with elevated beta-catenin signaling expressed higher levels of differentiation markers (Davidson et al. 2012).

1.4.3 ESC Characterisation

Before and after a differentiation protocol it is important to characterize the ESCs to show they have lost their pluripotency especially when considering using ESC derived cells for therapy as any pluripotent cells transplanted into the patient may give rise to teratomas. Pluripotency is mainly characterized by expression of the pluripotency-associated transcription factors Nanog, Sox2 and Oct4 and absence of differentiation markers including Brachyury, Myf5, MyoD1 and Gata4. The pluripotency associated cell surface markers Tra-1-60/1-80 and SSEA-3/4 can also be used to characterize ESCs (Draper et al. 2002). Other ways of analyzing pluripotency of ESCs include human telomerase enzyme, alkaline phosphatase, karyotype and proliferation rate (Stewart et al. 2006).

1.4.4 ESC Culture

The first ESC lines were derived from the inner cell masses of mouse embryos and cultured in medium conditioned by a teratocarcinoma cell line (Evans, Kaufman, et al. 1981). These cells were proven to be pluripotent by their ability to produce a teratoma and germ-line chimeras (Martin 1981; Bradley et al. 1984). It wasn’t until 1998 that the first human ESC line was reported and shown to be able to produce cells from all three germ layers (Thomson et al. 1998). The delay between the first derivation of mESCs and hESCs was due to hESCs requiring different culture conditions. Human ESCs were first cultured on MEFs with addition of animal-derived serum to the medium. However due to the undefined nature of serum and its large batch-to-batch variation reducing reliability of experiments, it is now standard practice to culture hESCs with a serum replacement such as KnockOut Serum Replacement (SR) or feeder-free. If hESCs are going to be used for therapeutic applications they have to be cultured in serum-free and feeder-free conditions completely devoid of animal products. This is to avoid any transmission of animal pathogens or immunogenic proteins such as nonhuman sialic acid (Martin et al. 2005). One way to achieve this is by use of human feeder cells either fibroblasts derived from hESCs (Stojkovic et al. 2005), human fetal fibroblasts or adult fibroblast (Richards et al. 2002). However these feeder lines do not support hESC growth equally leading to large experimental variability (Richards et al. 2003). Understanding what key signaling molecules secreted by the feeders are involved in maintaining self-renewal of hESCs is

Chapter 1 25 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells essential to develop efficient expansion of hESCs in feeder-free culture systems.

1.4.5 Feeder-Free Culture

The first feeder-free culture system for hESCs utilised MEF-conditioned medium supplemented with SR and were cultured on either laminin or a complex undefined mixture of laminin, type IV collagen and heparan sulphate known as Matrigel. These feeder-free cultured hESCs expressed the same properties to those cultured on MEFs, both exhibited a normal karyotype, proliferation rate and high telomerase activity (Xu et al. 2001). It was later shown hESCs could also be cultured on fibronectin in medium supplemented with SR and a combination of growth factors including TGF-β1, LIF and FGF-2 (Amit et al. 2004). Another feeder-free system involved supplementing the medium with Noggin, a BMP antagonist, and FGF-2 and culturing hESCs on Matrigel (Wang et al. 2005). These feeder-free culture systems have proven successful however despite the lack of feeders and animal serum they are not completely devoid of animal products as SR and Matrigel contain animal derived components. One hESC culture system completely free of animal products used human laminin to culture hESCs with serum-free medium supplemented with high concentrations of human FGF-2 (Li et al. 2005). It was later highlighted the importance of endogenous FGF-2 in maintaining hESC self-renewal (Dvorak et al. 2005). However several xeno-free culture media have been shown incapable of maintaining growth of different hESCs cell lines (Rajala et al. 2007). One feeder-free and serum-free culture system was capable of sustaining undifferentiated growth of multiple hESC lines. This involved culturing hESCs on fibronectin in media supplemented with FGF-2, Activin A and Neurotrophin-4 (Baxter et al. 2009). Another feeder-free system using medium (TeSR1) composed of DMEM/F12 base medium supplemented with human serum albumin, vitamins, antioxidants, trace minerals, specific lipids and cloned growth factors, with all proteins used derived from recombinant sources or purified from human material, could be used to derive and maintain hESCs for up to 16 passages (Ludwig et al. 2006). The TeSR1 medium was later simplified by removing several components in particular albumin to reduce batch variability, leading to a DMEM/F12 basal medium supplemented with only 7 components: insulin, selenium, transferrin, L-ascorbic acid, FGF2 and TGFβ and NaHCO3 to adjust the pH. Using E8 medium and vitronectin coated plates higher iPSC derivation efficiency could be achieved compared to TeSR1 (Chen et al. 2011).

1.5 MicroRNAs

MicroRNAs (miRNAs) are small non-coding RNAs that play an essential role modulating gene expression of targeted mRNAs. They bind 3’ UTR of mRNA by base pair interaction resulting in either mRNA degradation or translational repression (Filipowicz et al. 2008). Approximately 30% of all protein-coding genes are directly targeted by miRNAs and so

Chapter 1 26 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells it’s no surprise they have shown to play important roles in regulating almost all cellular processes including cell proliferation, apoptosis, differentiation, developmental timing and metabolic control (Filipowicz et al. 2008). This highlights the vast importance of miRNAs and their potential to control biological processes.

1.5.1 MicroRNAs in the Genome

Many miRNAs have been shown to be highly conserved across bilaterian animals. Over half of the miRNAs in C.elegans have homologues in both fly and human genomes (Iba´nez-Ventoso˜ et al. 2008) indicating they have an important role throughout evolution. MicroRNAs have some distinct genomic features that are important to keep in mind. Firstly miRNA loci are mainly found in non-coding transcripts implying they have independent transcription units (Lagos-Quintana et al. 2001). Of these miRNAs 40% are found in the introns while 10% are found in the exons. The rest of the miRNAs are mainly found in introns of protein-coding transcripts allowing a coordinated expression of miRNA and protein (Kim et al. 2009). Secondly miRNAs are highly clustered roughly 40% of miRNAs are found less than 10kb from another miRNA (Griffiths-Jones et al. 2008). These clustered miRNAs are located on a polycistronic transcript and are transcribed as a primary precursor. Thirdly a miRNA may appear at several loci throughout the genome. This is usually highlighted in the miRNAs name e.g. a miRNA with a similar sequence at different loci is given a lettered suffix (e.g. hsa-miR-302a and hsa-miR-302b) whereas miRNAs with identical sequences at different loci are identified by a numbered suffix (e.g. hsa-miR-129-1 and hsa-miR-129-2).

1.5.2 Biogenesis

The canonical miRNA biogenesis pathway, shown in Figure 1.1, begins with transcription by RNA polymerase II except for a small subset that are transcribed by RNA polymerase III (Borchert et al. 2006). This produces the primary miRNA (pri-miRNA) which contains a hairpin and can vary in length from 100 bases to tens of kilobases (Cai et al. 2004; Lee et al. 2004b). The hairpin from the pri-miRNA is then cleaved off by a microprocessor consisting of DGCR8, a double stranded RNA binding protein, and Drosha a RNase III enzyme (Lee et al. 2002; Zeng et al. 2003). DGCR8 recognises the stem of the pri-miRNA hairpin and positions the catalytic site of Drosha in place to cleave to pri-miRNA to produce a precursor miRNA (pre-miRNA) with a 2nt 3’ overhang. This 3’ overhang is recognised by Exportin-5 and Ran-GTP which exports the pre-miRNA out of the nucleus. Next, the pre-miRNA is cleaved to produce the mature duplex by another RNase III enzyme, Dicer, which interacts with the dsRBD protein TRBP, this recruits Ago2 forming the RNA-induced silencing complex (RISC) (Gregory et al. 2005). RISC then selectively incorporates the miRNA strand with the lower stability of base-pairing at its 5’ into RISC and the passenger

Chapter 1 27 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells strand is degraded (Schwarz et al. 2003). However for some miRNAs both strands may play roles in post-transcriptional regulation and have been termed ‘3p’ and ‘5p’ (Griffiths-Jones et al. 2006; Griffiths-Jones et al. 2008). When the mature miRNA is incorporated into RISC it can now target mRNAs by base pair interactions. Since the acceptance of the canonical miRNA biogenesis pathway many other non- canonical pathways have been discovered (Miyoshi et al. 2010). The first of which is the “mirtron” pathway, it involves splicing of short intronic hairpins found precisely at the end of introns. This bypasses the Drosha cleavage step and instead undergoes a debranching step (Westholm and Lai 2011).

Chapter 1 28 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Figure 1.1: Canonical microRNA biogenesis Synthesis of miRNAs begins with transcription by RNA polymerase II (RNA Pol II) producing the primary miRNA (pri-miRNA) containing a hairpin which is then cleaved off by a microprocessor consisting of DGCR8 and Drosha producing a precursor miRNA (pre-miRNA) (Cai et al. 2004; Lee et al. 2004b; Lee et al. 2002; Zeng et al. 2003). The pre-miRNA is then exported out of the nucleus by Exportin-5 and Ran-GTP where it is cleaved by Dicer to produce the miRNA duplex. The RNA-induced silencing complex (RISC) which contains Dicer, TRBP and Argonaute 2 (Ago2) is formed and one strand of the miRNA duplex is then selectively incorporated into Ago2 as the mature miRNA (Gregory et al. 2005; Schwarz et al. 2003). The mature miRNA can then interact with its target mRNA leading to either mRNA target cleavage, translational repression or mRNA degradation (Filipowicz et al. 2008).

Chapter 1 29 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

1.5.3 MicroRNA Silencing Mechanism

It has been known since the discovery of miRNAs that they act to silence translation but the mechanisms of how this is done remains disputed. Several functions of miRNAs have been identified including endonucleolytic cleavage, transcript degradation, translational inhibition and in very rare cases some miRNAs have been found to cause gene silencing (Kim et al. 2008) or translational activation (Vasudevan et al. 2007). One possible mechanism is endonucleolytic cleavage of targeted mRNAs similar to siRNA induced RNA interference. It has been shown that miR-196 can downregulate some Hox genes by endonucleolytic cleavage (Yekta et al. 2004). However this mechanism requires miRNAs to have extensive complementarity to their target and most miRNAs base-pair imperfectly so cannot induce endonucleolytic cleavage. Another suggested mechanism is translational inhibition of targeted mRNAs at distinct stages in the process. It was shown that let-7 inhibits translational initiation (Pillai et al. 2005) and some miRNAs could affect the elongation step, possibly by terminating translation prematurely (Petersen et al. 2006). The more understood mechanism involves miRNAs destabilizing mRNA via deadenylation and then decapping of the targeted mRNA leading to degradation (Wu et al. 2006; Standart and Jackson 2007). This mechanism is supported by a study showing that miRNAs predominately act by destabilizing target mRNAs and not by reducing translational efficiency (Guo et al. 2010).

1.5.4 Target Identification

To fully understand the function of a particular miRNA you need to know what transcripts it targets. Many tools have been developed to predict miRNAs targets which are then validated by use of several different experimental approaches.

Target Prediction

Many miRNA target prediction tools have been developed over the years, they mainly rely on three discoveries to predict targets. Firstly, the miRNA target is dictated by nucleotides 2-7 from the 5’ end of the miRNA known as the seed sequence. This was first thought to be important due its highly conserved nature but has since been shown that full complementarity at the seed sequence is crucial for predicting miRNA targets (Lewis et al. 2003). Secondly, miRNA target sites are found in the 3‘UTR of mRNAs. When the first miRNA was discovered, lin-4, it showed complementary binding to a site in the 3‘UTR of its target lin-14 (Lee et al. 1993; Wightman et al. 1993). Since then it’s been shown that the 3‘UTR contains motifs that mediate post-transcriptional regulation and are complementary to miRNAs (Xie et al. 2005; Lai 2002). Thirdly, most target sites within human 3‘UTR are conserved, in fact the miRNA target prediction tool TargetScan showed that over 60% of human protein coding genes have been under selective pressure to

Chapter 1 30 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells maintain miRNA targets sites (Friedman et al. 2009). From these discoveries several target prediction tools have based their predictions on strict seed pairing to conserved sites in the 3‘UTR these include TargetScan, PicTar and EIMMo (Agarwal et al. 2015; Krek et al. 2005; Gaidatzis et al. 2007). Using PicTar it was shown that miRNAs in vertebrates target roughly 200 transcripts each (Krek et al. 2005). However these tools only look at targeting in the 3‘UTR of transcripts but it has been found that miRNAs can also target other regions of the transcript including the 5‘ UTR (Lytle et al. 2007) and the coding sequence (Tay et al. 2008). To find non-conserved target sites it’s important to take into account other factors that affect binding site efficacy to minimize false positives. TargetScan does this by taking into account AU composition near the target site, proximity to residues pairing to miRNA nucleotides 13–16, proximity of co-expressed miRNAs to the target site and positioning within 3‘UTR at least 15nt from the stop codon (Grimson et al. 2007). Another target prediction tool PITA evaluates target accessibility to predict non-conserved targets (Kertesz et al. 2007). When predicting miRNA targets its generally advisable to use a combination of these prediction tools to find targets which are consistently predicted by different methods. Once such database which does this is miRWalk. It uses a combination of 10 different miRNA prediction tools as well as its own, which can find targets in other regions of transcripts including the promoter, 5‘UTR and the coding region (Dweep et al. 2011). There are also databases available with already experimentally validated targets (Dweep et al. 2011; Vergoulis et al. 2012).

Target Validation

The most widely used method for analysing mRNA-miRNA interactions is by use of a reporter gene assay. First the 3’-UTR of the predicted target gene is cloned immediately downstream of the reporter gene, luciferase or GFP, then missexpression of the miRNA of interest should lead to changes in reporter gene expression. This can be further verified by mutating the 3’UTR in the construct and showing the effect is lost (O’Donnell et al. 2005). Protein level analysis provides an approach to investigate targets regulated both by translational repression and transcript destabilization. One such strategy involves labeling amino acids with isotopes (SILAC), this method has identified 12 proteins downregulated by miR-1 (Vinther et al. 2006). Many other biochemical approaches have been used to identify mRNA-miRNA interactions including microarrays, immunoprecipitation of RISC components, high-throughput sequencing of RNAs isolated by crosslinking immunoprecipitation (HITS-CLIP) of Agonaute, photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP) and using qRT-PCR to monitor changes

Chapter 1 31 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells in mRNA after introduction of a miRNA or miRNA inhibitor (Huang et al. 2010).

1.5.5 MicroRNAs in ESCs

The importance of miRNAs in both human and mouse ESCs has been evaluated using DGCR8 and Dicer knockout models since both proteins are essential for miRNA biogenesis. Dicer-null mice die at early stages of development and Dicer-null mESCs exhibit reduced growth and severe differentiation defects in vitro and in vivo (Kanellopoulou et al. 2005). However Dicer is also required to produce other types of small RNAs whereas DGCR8 is specific for miRNA biogenesis thus DGCR8 knockout models may give a clearer picture of miRNA function in ESCs. The DGCR-knockout model of mouse ESCs showed defective cell cycle, leading to an accumulation of cells in the G1 phase, and an inability to differentiate. Even under strict differentiation conditions DGCR8 deficient mouse ESCs were unable to downregulate pluripotent markers and they still retained the ability to produce ESC colonies (Wang et al. 2007a). As with miRNA deficient mouse ESCs, Dicer- and Drosha- knockdown human ESCs showed reduced ability to self-renew and defective differentiation (Qi et al. 2009). These experiments demonstrate the importance of miRNAs for ES cell function.

ESC specific cell cycle-regulating miRNAs

Studies show ESCs have a distinct miRNA signature that is lost upon differentiation (Houbaviy et al. 2003; Suh et al. 2004). Deep sequencing and microarrays have been employed to further analyse the miRNA expression of hESCs before and after differentiation (Bar et al. 2008; Morin et al. 2008; Tzur et al. 2008; Lakshmipathy et al. 2007; Laurent et al. 2008; Ren et al. 2009). These have revealed several miRNA clusters that are consistently preferentially expressed in ESCs, including: miR-302 cluster, miR-17∼92 cluster, miR-371∼373 cluster and Chromosome 19 MicroRNA Cluster (C19MC). ChIP experiments showed that mESC specific miRNAs including the miR-302 cluster and the miR-290-295 cluster, which has the homologue miR-371∼373 in humans, have promoters occupied and activated by the pluripotent transcription factors Nanog, Sox2 and Oct4 (Marson et al. 2008). It was later shown that members of both the miR-290 and miR-302 cluster could rescue the ESC cycle defect from the DGCR8 knockout mESCs described earlier. These miRNAs have been termed ESC-specific cell cycle-regulating (ESCC) miRNAs and work by promoting the G1-S transition by suppressing cyclin E-Cdk2 inhibitors including p21, Rbl2 and Lats2 (Wang et al. 2008). In a later paper they demonstrated a Rb-independent mechanism of the miR-294/302 cluster to promote pluripotency by antagonising differentiation-inducing miRNAs (Wang et al. 2013b). These ESC-specific miRNAs have also shown to regulate reprogramming, one study

Chapter 1 32 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells showed the miR-290 family could increase the efficiency of Oct4, Sox2 and Klf4 induced reprogramming in mouse cells (Li et al. 2011) later they were shown to induce reprogramming of human cells without any of the Yamanaka factors (Miyoshi et al. 2011; Lin et al. 2010a). The exact mechanism by which the miR-302 cluster induces reprogramming isn’t fully understood however several mechanisms have been described, one such is by targeting epigenetic regulators AOF2, AOF1, MECP1-p66 and MECP2 (Lin et al. 2010a). A paper later showed the miR-302 cluster enhancement of reprogramming was in part due to it targeting RHOC and TGFBR2, resulting in inhibition of TGF-β–induced epithelial-mesenchymal-transition in human cells (Subramanyam et al. 2011). miR-302-367 Cluster

The miR-302-367 cluster is found on chromosome 4 and consists of 10 miRNAs, miR-302a-3p/5p, miR- 302b-3p/5p, miR-302c-3p/5p, miR-302d-3p/5p and miR-367-3p/5p. They are highly conserved in mammals and much evidence indicates their importance in ESCs. Firstly they are highly expressed in both human and mouse ESCs and are downregulated during differentiation (Suh et al. 2004). Secondly their promoters are regulated by the pluripotent transcription factors Oct4, Sox2 and Nanog (Marson et al. 2008; Barroso-del Jesus et al. 2009; Card et al. 2008). Thirdly they are important cell cycle regulators by posttranscriptionally regulating Cyclin D1 and Cdk1 (Card et al. 2008) and finally ectopic expression of miR-302 alone can reprogram somatic cells to pluripotency (Lin 2011; Kuo et al. 2012). miR-17∼92 Cluster

The miR-17∼92 cluster is found on chromosome 13 and includes; miR-17, miR-18a, miR- 19a, miR-20a, miR-19b-1 and miR-92a-1. Its function in ESCs has not been well examined. It was showed that c-Myc binds to and regulates the miR-17∼92 cluster and two miRNAs in this cluster miR-17-5p and miR-20a negatively regulate the transcription factor E2F1 which is also regulated by c-Myc (O’Donnell et al. 2005). Another pluripotency transcription factor Nanog has also been shown to directly promote expression of the miR-17-92 cluster in neural stem cells (Garg et al. 2013). One study showed that the miR-17 family member, miR-93, was specifically upregulated in the primitive endoderm and trophectoderm and miR-93 and miR-17-5p had high expression within the mesoderm of the embryo (Foshay and Gallicano 2009). Suggesting that the miR-17 family may play a more important role in differentiation rather than maintaining pluripotency.

1.5.6 MicroRNAs involved in Differentiation

Interestingly ESCC miRNAs were unable to rescue the differentiation defects from the DGCR8 null ESCs (Wang et al. 2008) but the miRNA let-7 could rescue this phenotype by

Chapter 1 33 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells targeting the ESC transcription factors Sall4, c-Myc and Lin28 Melton et al. 2010; Rybak et al. 2008). Also as with protein coding genes the pluripotent transcription factors not only bind ESC specific miRNAs but also co-occupy with Polycomb-group proteins a small set of miRNAs that are silenced in ESCs but poised for activation during differentiation (Marson et al. 2008). This smaller set includes miRNAs which are specifically expressed in differentiated cells including miR-155 found in B cells, miR-124 and miR-9 found in neural cells and miR-615 which is part of the Hox cluster. Suggesting miRNAs play an essential role in inducing differentiation and also in lineage specification.

Let-7 microRNA Family

In early mouse development primary transcripts of the Let-7 miRNA family are present at high levels but not their corresponding mature miRNAs indicating their maturation is being prevented (Thomson et al. 2006). It was later discovered that this was caused by Lin28 binding to a conserved sequence in the let-7 precursor loop inhibiting its processing (Viswanathan et al. 2008). Let-7 is also modulated by the RNA binding protein, KSRP, binding to a different sequence in pri-let-7 leading to increased processing of pri-let-7 (Trabucchi et al. 2009). The importance of Lin28 in pluripotency is highlighted by the fact ectopic expression of Lin28 can increase reprogramming efficiency of fibroblasts to pluripotent stem cells (Yu et al. 2007). Both let-7 and Lin28 promoters are occupied by the pluripotent transcription factors Sox2, Oct4, Nanog and Tcf3 and expression of pri-let-7g is dependent on Oct4 indicating a role in ESCs (Marson et al. 2008). It has been proposed that the ESCC miRNAs and let-7 have opposing effects on ESC self-renewal and act through a common pathway to either stabilise self-renewal or differentiation respectively. ESCC miRNAs possibly indirectly increase expression of Lin28 which in turns inhibits maturation of let-7 leading to stabilisation of the ESC-state. When differentiation is initiated this causes loss of ESCC miRNAs and Lin28 leading to a rapid increase in let-7 which targets ESC factors Sall4, c-Myc and Lin28, its own negative regulator, leading to a stabilised differentiation state (Melton et al. 2010).

1.5.7 Chondrogenic miRNAs

Conditional knockout of Dicer in cartilage leads to defects in skeletal development and produced chondrocytes with a dramatically reduced proliferation and accelerated differentiation into hypertrophic chondrocytes demonstrating the critical role of miRNAs in cartilage development (Kobayashi et al. 2008). miR-140 in cartilage

It was shown that miR-140 is specifically expressed in cartilage tissue in developing zebrafish and mouse embryos suggesting it is involved in chondrogenesis (Wienholds et al. 2005; Tuddenham et al. 2006). In humans, miR-140 is the most upregulated miRNA

Chapter 1 34 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells during chondrogenesis of hBM-MSCs (Miyaki et al. 2009), most abundant miRNA in adult articular cartilage (Crowe et al. 2016) and developing human cartilage tissue (McAlinden et al. 2013), and is reduced in OA tissue compared with normal cartilage (Miyaki et al. 2009). Since its identification as a cartilage-specific miRNA many of its targets have been identified including: HDAC4 (Tuddenham et al. 2006), CXCL12 (Nicolas et al. 2008), RALA (Karlsen et al. 2013), SMAD3 (Pais et al. 2010), SP1 (Yang et al. 2011), DNPEP (Nakamura et al. 2011a) and IGFBP-5 (Tardif et al. 2009). A recent transcriptome profiling experiment of MSC chondrogenesis identified miR-140-5p as the most functional miRNA regulating chondrogenesis indicated by a significant enrichment of downregulated genes during chondrogenesis containing the miR-140-5p seed sequence. Further analysis of miR-140-5p by overexpression identified several genes involved in Wnt signaling targeted by miR-140-5p and was able to promote Wnt signaling in the absence of Wnt ligand (Barter et al. 2015). Generation of miR-140 null mice in two separate studies both displayed short stature (Nakamura et al. 2011a; Miyaki et al. 2010) with one of the studies also showing the mice produced age-related OA-like articular cartilage (Miyaki et al. 2009) highlighting its importance in limb and cartilage development. Closer examination of miR-140 shows it resides within the intron of WWP2 which has been shown to control craniofacial development (Zou et al. 2011) and is directly regulated by Sox9 (Yang et al. 2011; Nakamura et al. 2011b; Barter et al. 2015) . Also two other chondrogenic transcription factors, L-Sox5 and Sox-6, have been shown to regulate miR-140 expression although they are dependent on Sox9 (Yamashita et al. 2012).

Other chondrogenic miRNAs

Since the identification of miR-140 several profiling experiments have been performed to identify: miRNAs regulating osteoarthritis pathogenesis (Iliopoulos et al. 2008; Jones et al. 2009; Le et al. 2016; Crowe et al. 2016), miRNAs regulating human cartilage development (McAlinden et al. 2013), age-related miRNAs (Ukai et al. 2012), mechanosensitive miRNAs (Guan et al. 2011) and in vitro models of chondrogenesis (Swingler et al. 2012; Guerit et al. 2013). From these experiments potential candidate miRNAs have been identified and their role in chondrogenesis and corresponding targets have been validated (summarised in Table 1.1). Several of these miRNAs have been shown target the TGF-β signaling pathway, a key chondrogenic promoting pathway, for example miR-455-3p which targets SMAD2 (Swingler et al. 2012), miR-337-3p which targets TGFBR2 (Zhong et al. 2012), miR-199a- 3p which targets SMAD1 (Lin et al. 2009b) and miR-146a-5p which targets SMAD4 (Jin et al. 2014) (summarised in Figure 1.2). The miR-17∼92 cluster has also been identified as containing cartilage regulating miRNAs, it was shown haploinsufficiency of the miR-17∼92 cluster in humans led to

Chapter 1 35 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells several developmental abnormalities including microcephaly, short stature and digital abnormalities which was further validated in mice models (Pontual et al. 2011). Furthermore selective deletions of individual miRNAs of the miR-17∼92 cluster in mice showed the miR-17 seed family controlled axial patterning and skeletal development shown by mesophalanx shortening and fusion of carpal bones (Han et al. 2015).

Figure 1.2: The TGFβ signaling pathway in chondrogenesis is targeted by many miRNAs MicroRNAs shown here have been reported in the literature to either inhibit (red) or promote (green) chondrogenesis. Pathway generated using Ingenuity Pathway Analysis (QIAgen).

Chapter 1 36 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Table 1.1: Summary of miRNAs in cartilage. Summary of miRNAs reported in the literature to have a role in regulating chondrogenesis, indicating any validated targets of the miRNA and the system it was studied in. OA, osteoarthritis; hACs, human articular chondrocytes; hBM-MSCs, human bone marrow derived MSCs; C3H10T1/2, mouse multipotential mesenchymal cells; HCS-2/8, human chondrosarcoma cell line; ATDC5, mouse embryonic chondrogenic cell line; SW1353, human chondrosarcoma cell line; T/C-28a2, human chondrocyte cell line.

miRNA Role Targets System References miR-1 Development HDAC4 primary chick Li et al. 2014 embryonic chondrocytes miR-9 Development PRTG chick embryo leg buds Song et al. 2013b miR-16 OA SMAD3 healthy and OA hACs Li et al. 2015b miR-18a Development CCN2 HCS-2/8 and Ohgawara et al. 2009 chicken sternum chondrocytes miR-20a Calcification ANKH human cartilage Liu et al. 2016 endplate miR-23b Development PKA hBM-MSCs Ham et al. 2012 miR-26 ECM - mouse primary Etich et al. 2015 epiphyseal chondrocytes miR-29 OA Wnt signaling OA hACs Le et al. 2016 family miR-29a Development FOXO3A hBM-MSCs Guerit´ et al. 2014 COL2A1 mouse MSCs Yan et al. 2011 miR-30a Development DLL4 rat BM-MSCs and Tian et al. 2016 SW1353 miR-30b OA ERG healthy and OA hACs Li et al. 2015c miR-34a Development EphA5 chick embryo leg buds Kim et al. 2011a RhoA/Rac1 chick embryo leg buds Kim et al. 2012 Bcl-2 human cartilage Chen et al. 2015 endplate miR-99a Development BMPR2 rat MSCs Zhou et al. 2016 miR-101 Development DNMT-3B chick embryo leg buds Kim et al. 2013b miR-105 OA RUNX2 OA hACs Ji et al. 2016 miR-125b OA ADAMTS4 OA hACs Matsukawa et al. 2013 miR-127 OA MMP13 healthy and OA hACs Park et al. 2013b miR-138 Development SP1, HIF2A healthy hACs and Seidl et al. 2015 SW1353 Continued on next page

Chapter 1 37 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Table 1.1 – continued from previous page miRNA Role Targets System References miR-139 OA EIF4G2, healthy and OA hACs Hu et al. 2016 IGF1R, MCPIP miR-140 Development HDAC4 mouse limb Tuddenham et al. 2006 CXCL12 C3H10T1/2 Nicolas et al. 2008 RALA hACs and hBM-MSCs Karlsen et al. 2013 Wnt signaling hBM-MSCs Barter et al. 2015 SMAD3 C3H10T1/2 Pais et al. 2010 IGFBP-5 OA hACs Tardif et al. 2009 DNPEP mice models Nakamura et al. 2011a SP1 mouse and chick limb Yang et al. 2011 bud mesenchymal cells miR-142 Development ADAM9 chick embryo leg buds Kim et al. 2011b miR-143 Development - bovine ACs Hong and Reddi 2013 miR-145 Development SOX9 hACs Martinez-Sanchez et al. 2012 miR-146a Apoptosis SMAD4 hACs Jin et al. 2014 miR-148a OA COL10A1, healthy and OA hACs Vonk et al. 2014 MMP13, ADAMTS6 miR-155 OA Autophage healthy hACs and D’Adamo et al. 2016 T/C-28a2 miR-181a Development CCN1 HCS-2/8 Sumiyoshi et al. 2013 miR-181b Development - chick embryo leg buds Song et al. 2013d miR-193b Development TGFBR3 hAd-MSCs Hou et al. 2015 miR-194 Development SOX5 hAd-MSCs Xu et al. 2012 miR-195 Apoptosis HIF1A ATDC5 Bai et al. 2015 miR-199a Development Smad1 C3H10T1/2 Lin et al. 2009b COX-2 OA hACs Akhtar and Haqqi 2012 miR-221 Development CDKN1B human and bovine Yang et al. 2015 ACs miR-222 OA HDAC4 healthy and OA hACS Song et al. 2015 miR-320a OA MMP13 ATDC5 and primary Meng et al. 2016 mouse chondrocytes Continued on next page

Chapter 1 38 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Table 1.1 – continued from previous page miRNA Role Targets System References miR-320c Ageing ADAMTS5 hACs Ukai et al. 2012 miR-337 Development TGFBR2 rat femoral head Zhong et al. 2012 cartilage miR-365 Hypertrophy HDAC4 primary chicken Guan et al. 2011 chondrocytes miR-375 Development Cadherin-7 chick embryo leg buds Song et al. 2013a miR-411 OA MMP13 healthy and OA hACs Wang et al. 2015a miR-449a Development LEF-1 hBM-MSCs Paik et al. 2012 miR-455 OA TGFb ATDC5 Swingler et al. 2012 signaling miR-483 ECM MAPK human and bovine Yang et al. 2015 pathway ACs miR-488 OA ZIP8 OA hACs Song et al. 2013c miR-574 Development RXR hMSCs Guerit et al. 2013 miR-558 OA COX-2 healthy and OA hACs Park et al. 2013a miR-602 OA SHH OA hACs Akhtar et al. 2015 miR-675 Development - hACs Dudek et al. 2010 miR-1247 Development SOX9 hACs Martinez-Sanchez and Murphy 2013

1.5.8 Manipulating miRNAs

To analyse the function of miRNAs it is necessary to manipulate their expression and then evaluate the phenotype produced. With proteins this is usually done by creating knockout models where the gene is deleted however as miRNAs are generally present at several loci each locus would have to be knocked out individually and the animals bred to generate the complete knockout strain making it very time consuming. Also the proximity of the miRNAs to other miRNAs within a cluster may make it difficult to delete one miRNA without affecting the others. Whereas making knockout models is the only way of guaranteeing complete loss of function many other approaches have come close. Antisense technology is widely used for knocking-down expression of proteins and miRNAs. However many aspects need to be considered when using this technology such as transfection method, sequence used, oligonucleotide modifications and appropriate controls.

Chapter 1 39 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

AntimiR Oligonucleotides

The most common method for knocking down specific miRNAs is by use of antimiR oligonucleotides these are single stranded antisense-oligonucleotides (ASOs) with sequence complementarity to the microRNA of interest. These act as competitive inhibitors presumably by base pairing to the mature microRNA and blocking its activity. These are useful for targeting a specific microRNA and can distinguish between members of the same miRNA family with as little as 2bp difference (Esau 2008). The main obstacle facing antimiR oligonucleotides is being able to deliver a high enough dose to saturate the microRNA of interest this is limited by efficiency of transfection and stability of ASO to nuclease degradation. Many methods have been used to try and overcome these obstacles. Chemical modifications of the ASO including 2’-O-methyl and locked nucleic acid (LNA) can improve stability of ASO and increase affinity to targeted microRNA. The backbone can also be modified to a phosphorothioate backbone. This has shown to reduce affinity to target RNA but significantly increases stability to nuclease degradation making it useful in long term assays (Esau 2008). It has also been shown that a 3’-terminal cholesterol group may improve delivery of ASOs to cells (Horwich and Zamore 2008). Transfection into cells generally employs a cationic lipid such as Lipofectamine but needs to be optimised for each cell line. Many considerations should be made when choosing the sequence for any type of antisense technology. Firstly it is important that the chosen sequence does not form any secondary structures as it may prevent its antisense effects; this can be done by using mFold (Zuker 2003) and secondly that it does not have any ‘off-target’ effects caused by base-pairing to mRNAs. This can be predicted by a BLAST search. Increasing the length of an ASO to make it more ‘target-like’ by adding flanking sequences onto either end of the target has been shown to increase the potency of the ASO although the results have been variable (Horwich and Zamore 2008). When using antisense oligonucleotides it is very important to use a good negative control to account for any possible ‘off-target’ effects. Most commonly used negative controls are a scrambled or mismatched control sequence possibly maintaining the same nucleotide composition.

MicroRNA Sponges

MicroRNA sponges are a vector mediated expression of transcripts from a strong promoter containing multiple bulged (i.e. non-cleavable) miRNA binding sites. These abundant RNAs compete with the endogenous targets and thus ‘soak-up’ the miRNAs of interest. MicroRNA sponges have the advantage of inhibiting the activity of a whole family of miRNAs sharing a common seed sequence unlike ASOs which target a specific miRNA (Ebert et al. 2007). However it is very time consuming to create the recombinant sponge vector and transfection

Chapter 1 40 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells is less efficient than for ASOs although this can be overcome by using a viral vector for difficult to transfect cells. An advantage of sponge technology is that they can be used to make transgenic animals as an alternative to genetic knockout models which is ideal for in vitro studies of miRNAs. However antisense technology is more promising from the perspective of using miRNAs to improve differentiation protocols for cell therapy.

Target Protectors

Target Protectors are ASOs designed to bind perfectly to the microRNA target site in the 3‘UTR of a specific targeted mRNA thereby protecting it from microRNA mediated repression. This was first achieved using morpholino target protectors to analyze the physiological role of miR-430 in zebrafish (Choi et al. 2007). Morpholino oligonucleotides are synthetic, uncharged, water-soluble analogs of nucleic acids that bind complementary RNA sequences and sterically inhibit protein binding. They have high stability, high specificity and low toxicity however delivery into cells is more challenging than with standard oligonucleotides due to their lack of a charged backbone. Many approaches have been used to deliver morpholinos including electroporation (Matter and Konig¨ 2005), cell-penetrating peptides (Wu et al. 2007) and Endo-Porter, a weak-base amphiphilic peptide (Summerton 2005). They are commercially available as a morpholino from Gene Tools or as a modified RNA transfectable with a lipid reagent from Qiagen. Target Protectors have shown to be a very useful tool for examining specific microRNA-mRNA interactions and their functional role in vitro and in vivo.

Gain of Function

Double stranded chemically modified RNA molecules designed to mimic endogenous mature miRNAs are widely available for all discovered human mature miRNAs listed in miRBase. They have been used in several studies to investigate gain-of-function effects on a microRNA and to identify and validate microRNA targets. It was recently shown that single stranded microRNA mimics with 5’-phosphorylated and 2’-fluoro modified oligonucleotides exhibit substantial miRNA seed-based activity in cells. However these single stranded modified oligonucleotides are less potent than the double stranded microRNA mimics (Chorn et al. 2012).

1.6 Next Generation Sequencing and Bioinformatic Analysis

Next Generation Sequencing (NGS) technologies have allowed rapid and inexpensive sequencing of DNA compared with conventional methods. There are currently three platforms in widespread use Illumina, Ion Torrent Personal Genome Machine (PGM) and Pacific Biosciences (PacBio) RS. Illumina is the most popular choice for NGS due to its

Chapter 1 41 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells high accuracy and sequencing depth. Illumina uses a sequencing-by-synthesis approach, firstly the DNA library is prepared by ligating adapters onto each end on the DNA sample. The second step involves clonal amplification of each DNA fragment. The final step is the sequencing of the DNA sample. In Illumina each end of the DNA fragments are ligated to adapters and then randomly attached to the surface of flow cell channels. While one end of the DNA is immobilised the other is free to bend over and hybridise with complementary adapters, which cover the surface of the flow cell, leading to bridge amplification of the DNA. After the amplification step the DNA is denatured to produce clusters of a ∼1000 identical single stranded DNA molecules ready to be sequenced. Sequencing begins with addition of DNA polymerase, primers and four differently labelled reversible terminator nucleotides. After the first nucleotide is incorporated laser excitation generates a signal for each flurophore from each cluster which is captured by a camera. Then the 3’terminator and flurophore are removed and the cycle is repeated until the whole DNA fragment is sequenced (Metzker 2010).

1.6.1 Mapping to miRNAs

To find the expression of miRNAs from sequenced DNA you need to map it to a database with all known miRNAs and their sequence such as miRBase. Many tools have been developed to allow mapping of sequences to genomes: one very popular tool, Bowtie, is a short read aligner designed to be ultrafast and memory-efficient for mapping sequences to the human genome (Langmead et al. 2009). A web based microRNA analysis tool miRanalyzer uses Bowtie to map sequences to miRBase and with any sequences which do not map to miRBase but map to the human genome are kept for novel microRNA prediction (Hackenberg et al. 2011).

1.6.2 Normalisation

It’s essential to normalise RNA-Seq data before analysing their differential expression as different samples generate different total read counts. An evaluation of seven commonly used normalisation methods showed that Trimmed Mean Method (TMM) performed the worst while Lowess and quantile normalisation worked the best for mammalian microRNA- Seq data (Garmire and Subramaniam 2012). Another evaluation showed that if you exclude potential differentially expressed genes before the normalisation factor is calculated this leads to a more accurate normalisation of RNA-Seq data (Kadota et al. 2012).

1.6.3 Differential Expression of miRNAs

The two most commonly used tools for finding differentially expressed miRNAs are the R software packages edgeR (Robinson et al. 2010) and DESEq (Anders and Huber 2010). A comparison of DESEq and edgeR showed that edgeR found more differential expressed genes than DESEq and not all of the genes found by DESEq were also found by edgeR

Chapter 1 42 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

(Yendrek et al. 2012) suggesting it may be advisable to use a combination of both tools to find a conserved list of differentially expressed genes. Both softwares also contain other tools for analysing count data. For example in edgeR you can plot the biological coefficient of variation and do a multidimensional scaling plot and in DESEq you can estimate dispersions, perform a principal component analysis and generate heatmaps.

1.6.4 Co-expression Analysis

The development of high-throughput gene expression analysis with the introduction of microarrays and more recently with RNA-sequencing has led to improve understanding of global gene regulation. However analysis of the large datasets produced from these methods still remains a major bottleneck for scientific discovery. Several new bioinformatic tools have been developed to identify biological meaning from the data. Co-expression analysis is a popular method for analysis of high-throughput data as it allows the identification of novel interactions between genes with similar expression profiles. For example in a large-scale yeast microarray experiment functionally related genes with correlated expression profiles were identified. Although many of the predicted interactions were non-functional it was able to predict more accurate relationships compared to another approach using hierarchical clustering (Zhou et al. 2002). To improve accuracy of predicted interactions datasets from different cell types and/or species can be analysed to find reliable co-expressed interactions. A study using 3182 DNA microarrays from several species identified 22,163 conserved co-expression relationships were identified of which some were experimentally validated (Stuart et al. 2003). Another study analysed 60 human data sets containing a total of 3924 microarrays and found co-expressed interactions which were found in several datasets (termed confirmed coexpression) were more likely to have a biological function (Lee et al. 2004a). Along with identifying novel interactions from reliably co-expressed genes, co-expression data can be used to generate large networks from which clusters of highly connected genes can be identified using network tools such as MCODE (Bader and Hogue 2003) or ModuLand (Szalay-Beko˝ et al. 2012). Functionality of these clusters can then be investigated by Gene Ontology enrichment analysis (Ashburner et al. 2000). Lee et al. using the approach described in the previous paragraph found several functionally related clusters such as a “epidermal differentiation” and ”cell junction” cluster of associated genes which may contain novel genes associated with these processes (Lee et al. 2004a). Another study identified several highly interconnected genes from cancer microarray data, such as a cluster of collagen genes which may be involved in the invasion and metastatic spread of tumours (Choi et al. 2005). A recent study used gene coexpression network analysis to identify coexpression clusters in human macrophage activation which were then further characterised (Xue et al. 2014).

Chapter 1 43 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Co-expression analysis allows the identification of novel interactions between genes with highly correlated expression. Also by use of bioinformatic methods such as network analysis (Bader and Hogue 2003; Szalay-Beko˝ et al. 2012) or Gene Ontology analysis (Ashburner et al. 2000) functionally related clusters from large co-expression networks can be identified leading to the identification of potential novel functions of genes in these clusters.

1.7 Exosomes

The term ”exosomes” was coined in 1981 by Trams et al. as exfoliated vesicles with ectoenzyme activity, then a few years later the origin of these vesicles from multivesicular bodies (MVBs) was discovered by electron miscroscopy experiments of maturing rat reticulocytes (Harding et al. 1983; Harding et al. 1984; Pan et al. 1985). However it was not until the recent discovery of exosomal miRNAs and their potential use as biomarkers that the exponential increase in exosome research was sparked (Figure 1.3). Exosomes are small extracellular vesicles, approximately 50–100 nm in diameter, containing specifically packaged proteins and RNAs. Exosomes are formed in multivesicular bodies (MVB) and are then released from the cell upon exocytic fusion of the MVB with the cell membrane releasing its contents, making them distinct from microvesicles which are formed by cell membrane budding. A multitude of exosome functions have been reported however current comprehensive understanding of exosome release, uptake and their molecular mechanism of function is still lacking.

Publications 1000 Exosome 800 Exosome Biomarker Exosome Cancer 600 Exosome miRNA

400

200 Number of Publications 0 1990 2000 2010 Year

Figure 1.3: Number of exosome related published papers on PubMed Shows the exponential growth of exosome-related research in research years

Chapter 1 44 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

1.7.1 Exosome Isolation

In initial experiments exosomes were isolated by ultracentrifugation of cell conditioned medium (Johnstone et al. 1987). Firstly, conditioned medium was centrifuged at low speed to remove cell debris and other contaminants. Next, the supernatant is ultracentrifuged at 100,000 g to pellet the exosomes (Johnstone et al. 1987; Raposo et al. 1996). An additional filtration step using a 0.22µm filter can in incorporated before ultracentrifugation to reduce contamination of larger microvesicles formed from cell shedding (Thery´ et al. 2001). Due to contamination of exosomes in Fetal Bovine Serum (FBS) it is important to first deplete serum containing medium of FBS-derived exosomes by ultracentrifugation (Stoorvogel et al. 2002, Wubbolts et al. 2003). Exosome preparations can be further purified by use of a continuous sucrose gradient (Raposo et al. 1996, Kleijmeer et al. 1998). Exosomes ‘float’ close to a density of 1.13 g/ml however this may vary depending of cell of origin (Stoorvogel et al. 2002). Due to high demand of exosome research many new exosome isolation kits are now commercially available. They allow rapid isolation of exosomes by several different methods including; size-exclusion, precipitation or by density gradient. Several comparisons for these different isolation methods have been performed. A comparison of the ability of four exosome isolation methods to isolate 100nm liposomes showed all methods isolated liposomes with similar size distributions and the liposomes were stably maintained during processing and purification; with the Exo-spin (Cell Guidance Systems) and Total Exosome Isolation Kit (Invitrogen) showing highest isolation efficiency (Lane et al. 2015). Another comparison of exosome isolation methods showed an ultrafiltration based methods had increased exosome isolation efficiency compared to the traditional ultracentrifugation method and was considerably less time consuming taking only 20mins to concentrate 150 ml of conditioned media compared to two rounds of ultracentrifugation of 90min each (Lobb et al. 2015). This study also compared commercially available kits for exosome isolation including qEV size exclusion columns (Izon science), ExoQuick precipitation based method (System Biosciences) and Exo-spin (Cell Guidance Systems) which uses a combination of precipitation and size-exclusion. Size exclusion columns displayed lower exosome yield compared to exosome isolation precipitation kits (ExoQuick and Exo-spin) however it showed highest purity even compared to density gradient purified exosomes (Lobb et al. 2015). Another comparison of exosome isolation methods, compared the efficiency of different methods using frozen human serum as use for biomarkers. Isolated exosomes were assessed by quantity, purity and miRNA expression. Precipitation method using polyethylene glycol (PEG) showed high isolation efficiency also isolation using ExoQuick

Chapter 1 45 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells and ultracentrifugation showed similar efficiencies while Exo-spin performed the worst. Exosomes isolated by PEG precipitation also showed highest expression of exosomal marker CD63 and allowed detection of exosomal miRNAs (Andreu et al. 2016). Many different methods are available for the isolation of exosomes from serum or conditioned culture media; summary shown in Table 1.2. Due to high demand of exosome research many new exosome isolation kits have been developed and are commercially available. They allow rapid isolation of exosomes by several different methods including; size-exclusion, precipitating or by density gradient without the need of ultracentrifugation. However, the increased isolation efficiency of some these kits may come at a cost of the purity of exosome preparation which is critical to allow true biological meaning to be applied to exosomes isolated.

Isolation Method Mechanism Efficiency Purity Time Reference Ultracentrifugation - Moderate Moderate 2hrs [1-2] Ultrafiltration - High Moderate 20 mins [1] Exo-spin (Cell P Low- Moderate O\N + 20 [1-2] Guidance Systems) Moderate mins ExoQuick (System P and SEC High- Low O\N + 15 [1-2] Biosciences) Moderate mins qEV (Izon Science) SEC Low High 15 mins [1] PEG P High High 1hr [2] OptiPrep (Sigma) DG Low High 18hrs [1]

Table 1.2: Summary of different exosome isolation techniques.SEC; size exclusion columns; P, Precipitation; DG, Density Gradient, O\N, overnight incubation,[1] Lobb et al. 2015; [2], Andreu et al. 2016.

1.7.2 Exosome Characterisation and Quantification

After isolation, accurate characterisation of exosome population is essential as several other extracellular-vesicles (EVs) are also secreted by cells and may be present in the isolated sample, including: exosomes, microvesicles, membrane particles and apoptotic bodies (Pol et al. 2012). Exosomes can be characterised by their morphology and biochemical composition. Electron microscopy of exosomes reveals they have a ‘cup shaped’ morphology with a diameter of 50-80-nm (Pan et al. 1985; Raposo et al. 1996). The observed ’cup shaped’ of exosomes is due to sample dehydration during conventional EM resulting in the exosomes collapsing. This can be overcome by using cryoelectron microscopy where samples are quickly vitrified preventing dehydration of samples, this showed exosomes had a round morphology (Yuana et al. 2013; Enderle et al. 2015). Further analysis of exosomal protein composition is required to show enrichment of exosomal proteins (CD63, CD81, CD9, LAMP1 and TSG101) (Mathivanan et al. 2010; Dignat-George and Boulanger 2011) and

Chapter 1 46 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells absence of cellular contaminants (such as beta actin or endoplasmic reticulum components e.g. calnexin). As many researchers use different isolation methods for exosomes isolation and purity of exosome samples with different extracellular-vesicles (EVs) depends on isolation method used and source of exosomes. The International Society for Extracellular Vesicles (ISEV) has listed a set of requirements for exosomes before functionality can be attributed to them. As there is currently no universal marker for exosomes, characterisation has to be performed by analysis of several markers. This includes presence of transmembrane markers (e.g. CD63, CD9, CD81), cytosolic proteins (TSG101, Annnexins), absence of cellular proteins associated with non-endosomal compartments (e.g endoplasmic reticulum markers, calnexin or Golgi proteins, GM130). Expression of these proteins should be performed at least semi-quantitatively and compared to expression of exosome donor cell if possible. Characterisation of the heterogeneity of the exosome population should also be performed by at least two methods such as biophysical analysis e.g. transmission electron microscopy, and size distribution analysis e.g. nanoparticle tracking analysis, dynamic light scattering or resistive pulse sensing (Lotvall¨ et al. 2014).

1.7.3 Exosome Composition

As eluded to earlier exosome protein composition is unique from their donor cell. The isolation of purified exosome preparations has allowed the proteome of exosomes derived from several different cell types to be profiled by mass spectrometry including: dendritic cells (Thery´ et al. 1999; Thery´ et al. 2001), mast cells (Skokos et al. 2001), intestinal epithelial cells (Van Niel et al. 2001) and mesenchymal stem cells (Vallabhaneni et al. 2015). Due to the large increase in extracellular vesicle (EV) profiling studies from various cell types and species. Several databases have been made to catalogue the results of all high-throughput EV related experiments; these include Vesiclepedia (Kalra et al. 2012), EVpedia (Kim et al. 2013a) and ExoCarta (Keerthikumar et al. 2016). While Vesiclepedia and EVpedia provide more curated studies which includes all classes of EVs (apoptotic bodies, exosomes, microparticles and shedding microvesicles), ExoCarta is currently the only database dedicated to exosome profiling experiments. A new feature of ExoCarta provides a check list for each exosomal study to assess if it meets the standards proposed by the International Society for Extracellular Vesicles, as mentioned in the previous section (Lotvall¨ et al. 2014). The check list includes the following criteria for exosome characterisation; biophysical analysis, detection of cytosolic exosomal proteins, detection of membrane proteins, lack of nonexosomal proteins and particle analysis. The most commonly identified proteins in exosome profiling experiments include (Figure 1.4): tetraspanins (CD9 and CD63), heatshock proteins (HSPA8, HSP90AA1 and

Chapter 1 47 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

HSP90AB1) and proteins involved in multivesicular body/exosome biogenesis (PDCD6IP/Alix, ANXA2/Annexin A2, ENO1/Enolase 1 and TSG-101). Many of the top commonly found proteins in exosomes also include many genes which are commonly used as housekeeping genes (HKGs), including: GAPDH, ACTB, EEF1A1, YWHAZ, PGK1 and EEF2. This is not surprising as HKGs are chosen due to their high and stable expression across several tissues, suggesting presence of HKG protein may be due to passive packaging of protein into exosome or due to microvesicle or apoptotic body impurities. Proteomic profiling of exosomes and larger microvesicles (MVs) showed higher expression of GAPDH, YWHAZ, and ACTB in the MV population compared to exosomes population suggesting they are not exosome-enriched proteins (Xu et al. 2015). Along with differences in protein composition compared to their donor cell exosomes also display a different membrane lipid composition compared to their donor cell membrane. Lipid analysis of exosomes showed they enriched with several lipids compared to their donor cell plasma membrane, including: cholesterol (Mobius¨ et al. 2002), saturated phospholipids, sphingomyelin and its metabolite ceramide (Trajkovic et al. 2008; Chaput and Thery´ 2011). However the molar ratio of these different lipids in exosomes is unknown. ExoCarta 100 Tetraspanin Heatshock Protein 90 Exo biogenesis

80

70

Number of mes idenfied 60

CD9 PKM CD63 ENO1 PGK1EEF2 HSPA8 ACTB LDHA GAPDHANXA2SDCBP TSG101 EEF1A1YWHAZ ALDOA PDCD6IP HSP90AA1 HSP90AB1

Figure 1.4: Results of top 20 identified proteins in exosomes Barchart of number of times each protein has been identified in exosomes from exosome-protein profiling studies on ExoCarta (29 July 2015).

1.7.4 Exosome Biogenesis

Exosomes were first described as extracellular vesicles with ectoenzyme activity (Trams et al. 1981) however it was not until electron microscopy of maturation of reticulocytes

Chapter 1 48 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells identified exosomes as endosomal in origin separating them from microvesicles shed from the cell membrane (Harding et al. 1984; Pan et al. 1985). These papers showed the formation of vesicles inside endosomes by inward budding leading to the generation of multivesicular bodies (MVBs) which could fuse with the cell membrane releasing its contents (Figure 1.5). Extracellular vesicles of endosomal origin is now the accepted definition of exosomes. Multivesicular bodies (MVBs) are characterised by the presence of vesicles in their lumen (intraluminal vesicles) formed by inward budding of their membrane. Three functions of MVBs have been proposed, firstly they can shuttle lipids and proteins to lysosomes for degradation, secondly they can act as temporal storage compartments and thirdly they can fuse with the cell membrane releasing their contents i.e. exosomes. The involvement of the ESCRT machinery for packaging of proteins into intraluminal vesicles (ILVs) of MVBs for subsequent lysosome degradation has been well characterised (Hanson and Cashikar 2012). However whether the same mechanism is used to package proteins for exosomal release is more controversial. The ESCRT machinery consists of four complexes ESCRT-0-III. First ESCRT-0, a heterodimer of Hrs and STAM, recognises ubiquinated proteins which are then recruited to endosomal membrane via interactions of Hrs with the phospholipid PtdIns3P. Next ESCRT-0 recruits ESCRT-I through interaction of Hrs with the ESCRT-I component Tsg-101, this leads to ESCRT-II recruitment and eventual ESCRT-III recruitment and activation leading to vesicle budding which requires the adaptor protein Alix (Henne et al. 2011). Proteomic profiling of exosomes and knowledge of their MVB-origin, has led to many exosome-enriched proteins to be linked to the ESCRT machinery. Early proteomic experiments identified TSG-101 and Alix (PDCD6IP) as proteins enriched in exosomes (Thery´ et al. 2001; Figure 1.4). TSG-101 has been identified as a member of the ESCRT-I which is responsible for recognising ubiquinated MVB cargo (Katzmann et al. 2001; Katzmann et al. 2002) and Alix acts to link ESCRT-II and ESCRT-III complexes and later functioning in vesicle budding (Von Schwedler et al. 2003). Baietti and colleagues recently showed the importance of syndecan binding protein (SDCBP), Alix and Sydecan in exosome release, suggesting a ESCRT-dependant mechanism for exosome release (Baietti et al. 2012). They showed SDCBP directly interacts with Alix and release of SDCBP exosomes was dependant of heparan sulphate, syndecans, Alix and ESCRT proteins (TSG101, VPS22 and CHMP4A/B/C). The role of heparan sulphate in exosome release was later confirmed by experiments showing heparanase enhances exosome secretion (Thompson et al. 2013). Another protein which has been identified for its role in exosome release is SIMPLE

Chapter 1 49 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

(small integral membrane protein of the lysosome/late endosome). It was shown a mutation in its PTAP motif, which mediates it TSG-101 interaction, reduces exosome release (Zhu et al. 2013). This study also showed SIMPLE could bind to Nedd4 type E3 ubiquitin ligases via a PPxY motif and a mutation in this motif increased exosome secretion of SIMPLE, possibly by impairing its lysosome degredation. The involvement of Nedd4 in exosome secretion had been shown in earlier experiments, overexpression of Ndfip1 (Nedd4 family- interacting protein 1) increased exosome release (Putz et al. 2008). Many ESCRT-independent mechanisms of exosome release have also been described. Inhibition of ESCRT proteins Hrs, Tsg101, or Alix had no effect on proteolipid (PLP)-positive exosome release, however use of a neutral sphingomyelinase inhibitor could reduce their release. Suggesting a sphingolipid ceramide dependant mechanism of release (Trajkovic et al. 2008). A similar mechanism of release has been reported for microglia-derived (Yuyama et al. 2012) and T cell-derived exosomes (Mittelbrunn et al. 2011). Sphingomyelin is cleaved by sphingomyelinases producing phosphorylcholine and ceramide which can be further catabolised by sphingosine kinase (SphK) to sphingosine 1-phosphate (S1P); members of this metabolism pathway have been implicated in exosome release. Depletion of S1P signaling by siRNA knockdown of SphK2 or S1P1 receptor reduced the number of CD63-positive exosomes released by erythroid-differentiated (K562) cells (Kajimoto et al. 2013). Another lipid metabolite diacylglycerol (DAG) has shown to be involved in exosome release, inhibition of its degradation by DGK induced release CD63-positive exosomes from T cells (Alonso et al. 2005). The phospholipid lysobisphosphatidic acid (LBPA) is another metabolite of interest in exosome biogenesis. It is highly expressed in ILVs and MVBs (Kobayashi et al. 1998) and can control formation of ILVs in acidic liposomes via interactions with Alix (Matsuo et al. 2004). Overexpression of PLD2, an enzyme involved in LBPA biosynthesis (Bollag et al. 2007), promoted exosome release from mast cells (Laulagnier et al. 2004). Recently PLD2 and the small GTPase ADP ribosylation factor 6 (ARF6) were identified as regulators of syntenin and CD63-positive exosome release from breast cancer cells, immunoflourescence showed their involvement in the budding of ILVs into MVBs (Ghossoub et al. 2014). Tetraspanins (CD63, CD9, CD81) are highly enriched in exosomes and are consistently found in exosomes released from virtually all cell types (Figure 1.4). However not much is known about their function in exosome biogenesis or release. Recent evidence showed CD63 can load LMP1 an Eppstein-Barr virus protein into exosomes (Verweij et al. 2011). Also CD63 has been shown to load premelanosome protein (PMEL)

Chapter 1 50 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells into ILVs during melanosome maturation (Niel et al. 2011).

Exosomes

Microvesicles

Rabs Multivesicular Body SNAREs Lysosome ESCRT-Dependant Hrs, Alix, TSG-101, Degradation Syndecan, SIMPLE ILVs

RNA loading hnRNPA2B1, Annexins ESCRT-Independant Lipids - ceramide, DAG, LBPA Tetraspanins - CD63

Figure 1.5: Exosome Biogenesis Schematic representation of the biogenesis of exosomes in multivesicular bodies. Intraluminal vesicles (ILVs) are first formed by inward budding of their membrane. During this process specific proteins, lipids and RNAs get packaged within them. Several mechanisms have been described for the formation of these vesicles; ESCRT-dependent mechanism which requires Hrs, ALix and TSG-101, ESCRT- independent mechanism which involves LBPA, DAG and ceramide, also a mechanism of RNA loading involving hnRNPA2B1 (Villarroya-Beltri et al. 2013) has also been described. Multivesicular bodies either enter the degredation pathway and fuse with lysosome or fuse with the cell membrane leading to release of their ILVs as exosomes into the extracellular medium. LBPA, lysobisphosphatidic acid; DAG, diacylglycerol; ILVs, Intraluminal vesicles; MVBs, Multivesicular Bodies.

1.7.5 Exosome Release

Once exosomes are packaged with proteins, lipids and RNA molecules they are then released upon fusion of the MVB with the cell membrane. The involvement of Rab proteins (Stenmark 2009) and their effector proteins (Barr and Lambright 2010) in vesicle trafficking has been well reviewed. In summary, Rabs reversibly bind to membranes where they can regulate vesicle transport along the cytoskeleton by recruiting motor adaptors. Vesicles can then be tethered to membranes via Rab interactions with tethering factors such as SNAREs (Soluble N-ethylmaleimide- sensitive factor attachment protein receptors) leading to membrane fusion and eventual exocytosis (Stenmark 2009). Many Rabs have already been described for their role in exosome release, for example: Rab35 and its GTPase-activating protein TBC1D10A–C are required for oligodendrocyte- exosome release (Hsu et al. 2010), Rab11 regulates exosome release in erythroleukemia cells (Savina et al. 2002), Rab27a and Rab27b are required for the final stage of exosome release in HeLa cells functioning in MVB tethering at the cell membrane (Ostrowski et al.

Chapter 1 51 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

2010). Also proteins involved in SNAREs disassembly, VAMP7 and ATPase NSF have been implicated in fusion of MVBs with the plasma membrane to release exosomes (Fader et al. 2009).

1.7.6 Exosome Uptake

The mechanism of exosome targeting and uptake into recipient cells is of great interest as it could be exploited to aid targeted drug delivery. However it is still unclear whether exosomes from specific cell types are targeted to certain cells for uptake. Some studies suggest that this could occur via interactions involving integrins expressed on the surface of exosomes. Proteome profiling studies have identified several integrin subunits in exosomes, including: α1 (ITGA1), α2 (ITGA2), αM (ITGAM), β2 (ITGB2) and β3 (ITGB3) (Keerthikumar et al. 2016). The mechanism by which exosomes are targeted to immune cells has been investigated by blocking cell surface proteins with monoclonal blocking antibodies. It was shown that vesicles derived from antigen presenting cells could stimulate a strong proliferative effect in T cells which required vesicles to express both ICAM-1 (LFA-1 ligand) and CD80. Blocking the ICAM-1 ligand (αL/β2/LFA-1) prevented the proliferative effect (Hwang et al. 2003). Similarly, another study showed simultaneous inhibition of ICAM-1 and its ligand αL or blocking α5/β3 decreased dendritic-exosome uptake by dendritic cells (Morelli et al. 2004). Suggesting exosomes can be targeted to cells via interactions with integrins, this is not exclusive to immune cells . A study showed exosomes-derived from cancer cells over-expressing tetraspanin 8 (Tspan8), which forms a complex with integrin

α4, were more efficiently taken up by endothelial cells than exosomes lacking Tspan8 and this occurs via interactions with VCAM-1 (Nazarenko et al. 2010). Cells may also bind exosomes via interactions with their lipids, a study showed B cells expressing the phosphatidylserine receptors Tim1 or Tim4, can bind exosome-phosphatidylserine leading to exosome uptake (Miyanishi et al. 2007). Heparan sulphates (HS) have also been shown to aid exosome uptake, HS was mentioned earlier to be involved in exosome release. In experiments with glioblastoma-exosomes depletion of cell-surface heparan sulfate proteoglycans (PG) or inhibition of PG biosynthesis reduced exosome uptake in glioblastoma cells (Christianson et al. 2013). These in vitro experiments demonstrate the potential of exosomes to be targeted to certain cell types via interactions with integrins and other molecules, however whether exosomes display similar targeting ability in vivo has yet to be elucidated.

1.7.7 Exosome Function

First studies of exosomes showed their role in removing transferrin receptor during reticulocyte maturation (Pan et al. 1985; Johnstone et al. 1991). This excretory function of

Chapter 1 52 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells exosomes was suggested as a more efficient mechanism for degradation in cells with limited lysosome capacities, such as maturing reticulocytes where lysosomes are also being degraded during maturation (Johnstone 2006). However, exosomes are released from many cells with functioning lysosome systems. Also recently their considerable conservation has been uncovered having been found in bacteria (Rivera et al. 2010), fungi (Silva et al. 2015), parasites (Silverman et al. 2010) and yeast (Oliveira et al. 2010); suggesting they may have a more vital role than just a compensatory lysosome like-function. Many more functions of exosomes have since been revealed and the specific function of exosomes may be dependant on their cell-origin. Immune cell derived-exosomes have been shown to have functions in: direct antigen presentation (Thery´ et al. 2009; Raposo et al. 1996), activating natural killer cells (Simhadri et al. 2008) and signaling T cells for apoptosis (Monleon´ et al. 2001). Functions of exosomes have also been found in several other cell types. Platelet-derived microvesicles can stimulate angiogenesis in lung cancer cells (Janowska-Wieczorek et al. 2005). Exosomes are also released from cells of the nervous system including oligodendrocytes (Kramer-Albers¨ et al. 2007), neurones and astrocytes (Faure´ et al. 2006) although their function in these cells has yet to be characterised. Exosomes may also have a role in development, the role of endocytosis in embryonic development of Drosophila has been well studied (Dudu et al. 2004) and work in C.elegans noted a apical secretion of exosomes containing Hedgehog-related proteins (Liegeois´ et al. 2006) suggesting a mechanism for generating a morphogen gradient. A more concerning discovery showed cancer cell-derived exosomes could spread oncogenic activity. Glioma cells expressing an oncogenic receptor, known as EGFRvIII, could be transferred to non-EGFRvIII expressing cells via microvesicles, leading to oncogenic activity in the target cells, such as: activation of downstream pathways, morphological changes and increased growth activity (Al-Nedawi et al. 2008). These oncogenic properties of cancer-exosomes were later validated in vivo, a study showed exosomes isolated from serum of patients with breast cancer when mixed with non-tumourgenic epithelial cells could instigate tumours in nude mice while no tumours were found in mice injected with cells mixed with exosomes from healthy patients (Melo et al. 2014). Microvesicles isolated from mESCs when incubated with hematopoietic progenitor cells they were able to improve expansion of the progenitor cells, upregulate expression of pluripotency genes (Oct-4, Nanog and Rex-1) and early hematopoietic markers (Scl, HoxB4 and GATA 2) and activation of MAPK signaling (Ratajczak et al. 2006). Analysis of the mESC-microvesicles showed they contained Wnt-3 protein and several mRNAs for

Chapter 1 53 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells pluripotency transcription factors. Another study showed glioblastoma-derived exosomes containing mRNAs, miRNAs and angiogenic proteins could stimulate tubule formation by endothelial cells (Skog et al. 2008). However in both these studies, whether the effects of exosome addition observed were due to transfer of exosomal RNAs or proteins to recipient cells was not investigated. A recent study showed exosomes could provide protective messages. Exosomes isolated from mouse mast cells exposed to oxidative stress could provide a protective effect against oxidative stress in mast cells. Importantly they showed this effect was lost after exosomes were exposed to UV for 1 hr suggesting the effect is RNA-dependent, however UV irradiation can also damage proteins. Profiling of exosomes identified several mRNAs which may be responsible for the protective effect (Eldh et al. 2010). Many of the functions of exosomes have been attributed to transfer of exosomal-proteins e.g. CD41 in angiogenesis (Janowska-Wieczorek et al. 2005), EGFRvIII in oncogenesis (Al-Nedawi et al. 2008), or by direct activation of acceptor cell receptors by exosome-surface proteins e.g. antigen-presentation (Thery´ et al. 2009; Raposo et al. 1996). These mechanisms lead to activation of downstream pathways resulting in phenotypical changes in acceptor cells. However, since recent RNA profiling experiments of exosomes and their donor cells have shown they have distinct RNA profiles (Valadi et al. 2007; Crescitelli et al. 2013) many functions of exosomes are now being attributed to the transfer of these RNAs (Valadi et al. 2007;Eldh et al. 2010). The mechanism by which these RNAs are packaged into exosomes and their possible function of exosomal miRNAs will be discussed in the next section.

1.7.8 Exosomal miRNAs

In a microarray experiment, it was discovered that mast cell-derived exosomes contained a unique set of 1,300 mRNAs and 100 miRNAs different to their donor cell suggesting a selection mechanism for packaging RNA. More importantly, they showed the exosomal- mRNAs were biologically active and could be translated in the recipient cell (Valadi et al. 2007). The biological activity of taken up exosomal miRNAs has also been demonstrated by use of 3’UTR luciferase assays. Pegtel and colleagues showed B-cells infected with Epstein–Barr virus (EBV) secreted exosomes containing mature EBV-miRNAs, which could be taken up by dendritic cells leading to a dose-dependant repression of validated EBV- miRNA targets in the acceptor cells (Pegtel et al. 2010). The transfer of exosomal T cell-derived miRNAs has been shown during immune synapsis to regulate specific mRNAs in target antigen presenting cells (Mittelbrunn et al. 2011). Notably, in this paper microarray analysis of cellular and exosomal RNA isolated from the same cells had surprisingly low correlation suggesting exosomes had a selective mechanism for packaging miRNAs.

Chapter 1 54 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Many more papers have shown the enrichment of specific miRNAs in exosomes and that they are not just a reflection of their donor cell contents. However it was not until recently that the mechanism by which miRNAs are sorted into exosomes was uncovered. Villarroya-Beltri and colleagues identified sumoylated-hnRNPA2B1 as a key protein regulating the loading of miRNAs into exosomes binding miRNAs with the motif ’GGAG’ (Villarroya-Beltri et al. 2013). A paper published earlier this year showed that the guanine-rich sequence of exosome-enriched miRNAs is conserved across mammalian species and donor cell types. Exosomal miRNAs from human tumor cells, murine T cells, murine cytotoxic T lymphocytes and murine macrophages exhibited a significantly positive correlation for guanine in miRNA sequences (Momose et al. 2016). Annexins are calcium-dependent phospholipid-binding proteins, which may also play a role in regulating RNA loading of exosomes. Annexins-1,2,4,5,6,11 have all been found in exosomes (Keerthikumar et al. 2016). Annexin-2 is the most commonly found annexin in exosomes (Figure 1.4) and has been reported to recognise sequence elements within the 3’UTR of c-myc (Filipenko et al. 2004; Mickleburgh et al. 2005; Hollas˚ et al. 2006). Recent evidence showed Annexin-2 is involved in exosomal-miRNA loading. Annexin-2 can bind to miRNAs in the presence of Ca2+ and inhibition of Annexin-2 or Annexin-5 reduced miRNA content of exosomes. Notably, Annexin-5 silencing effected exosome miRNA profiles suggesting its role in sequence specific loading of miRNAs (Hagiwara et al. 2015).

1.7.9 Clinical Applications of Exosomes

Exosomes have huge promise in the clinic for use as non-invasive biomarkers (Reid et al. 2011). MicroRNA profiling has identified several miRNAs elevated in serum samples of patients with various pathological states and thus could be potential biomarkers for these states e.g. miR-193–3p in malignant pleural mesothelioma (Benjamin et al. 2010), miR-205 and miR-21 in ovarian cancer (Taylor and Gercel-Taylor 2008) and miR-155 and miR-210 in diffuse large B-cell lymphoma (Lawrie et al. 2008). As well as serum-miRNAs, urinary- exosomes have also been investigated as a source of biomarkers, with many potential biomarkers already identified for kidney and genitourinary tract related pathologies (Street et al. 2016). A large bottle-neck for the clinical translation of exosomal-miRNAs for use as biomarkers, is the need for a more accurate and standardised method of exosome isolation. Current methods of exosome isolation and subsequent analysis of exosomal miRNAs are time-consuming and labourious, taking at least a day to perform exosome isolation by ultracentrifugation and RNA analysis by RT-PCR. Also the several steps involved increases the chance of human-error and provides more sources of technical variation. The increasing popularity of exosome research has led to the development of several new technologies, such as qEV size-exclusion columns (mentioned in Section

Chapter 1 55 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

1.7.1) which allow rapid isolation of exosomes from serum in 15mins (Lobb et al. 2015). Also discovery of ’molecular beacons’ which are oligonucleotide hybridization probes that report the presence of specific nucleic acids allows rapid miRNA analysis of exosomes, detecting multiple miRNAs in exosomes within 1 hr (Lee et al. 2016). A combination of these techniques could allow rapid analysis of patient samples for diagnostic potential. However rigorous testing of the reproducibility and accuracy of any method chosen for biomarker analysis will have to be performed before it could be used in a clinical setting. Although biomarker use has been the main clinical focus of exosomes, they have also been investigated as potential therapies. Mesenchymal stem cell-derived exosomes have been shown to reduced infarct size in a mouse model of myocardial ischemia injury, however the mechanism of action is unknown (Lai et al. 2010). It was recently shown that exosomes could be engineered to target cells expressing specific receptors. Exosomes have been engineered to target EGFR-expressing breast cancer cells by expressing the transmembrane domain of PDGFR fused to a GE11 peptide an EGFR ligand. Injection of exosomes could deliver an anti-tumor miRNA let-7 to EGFR-expressing xenograft breast cancer tissue in mice reducing tumour growth (Ohno et al. 2013). Early experiments showed dendritic cell-derived exosomes could stimulate a strong antitumor effect in mice (Zitvogel et al. 1998). Since then the potential use of these dendritic-exosomes termed ”dexosomes”, has been investigated as a potential cancer therapy acting as a ’cancer vaccine’. Phase I clinical trials of dexosome therapy, where by a patients monocytes are isolated and differentiated into dendritic cells from which ”dexosomes” are isolated and loaded with peptides and then administered back to the patient, showed signs of immune activation and no serious adverse events (Le Pecq 2005; Chaput et al. 2005; Morse et al. 2005). Despite these positive findings studies have shown cancer-derived exosomes can induce T cell apoptosis (Abusamra et al. 2005) and may contribute to cancer immune evasion (Clayton and Tabi 2005). Further comprehensive understanding of the molecular mechanisms regulating exosome biogenesis including protein and RNA packaging, exosome release, uptake and its subsequent function in donor cell, can help lead to new exosome-based therapies.

Chapter 1 56 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

1.8 Research Aims

This projected aimed to investigate the following hypotheses;

1. Several key miRNAs are involved in regulating human chondrogenesis

2. Exosome-enriched miRNAs act to promote hESC pluripotency and/or differentiation to chondrogenic cells

I aimed to address these hypothesis by performing the following experiments:

1. Aim 1: Investigate changes in miRNA and mRNA expression at different stages of hESC-directed chondrogenesis • Use RNA-seq to profile small RNAs and the transcriptome of different stages of hESC-directed chondrogenesis using the directed differentiation protocol (Oldershaw et al. 2010; Cheng et al. 2014). • Evaluate global transcriptome and miRome variation during hESC-directed chondrogenesis. • Identify differentially expressed miRNAs during hESC-directed chondrogenesis.

2. Aim 2: Investigate the co-regulation of miRNAs and genes during hESC-directed chondrogenesis • Identify functionally related clusters of co-expressed genes and miRNAs during hESC-directed chondrogenesis. • Using bioinformatic approaches identify potential novel regulators of hESC-directed chondrogenesis. • Perform miRNA-mRNA target network analysis to identify key miRNA-target interactions which may be regulating hESC-directed chondrogenesis. • Develop an assay to validate function of miRNAs during hESC-directed chondrogenesis.

3. Aim 3: Investigate role of exosomal miRNAs during hESC-directed differentiation • Isolate and characterise pluripotent stem cell derived exosomes. • Identify exosomal enriched miRNAs in hESCs and hESC-chondroprogenitors. • Using bioinformatic approaches, investigate potential function of exosomal enriched miRNAs during hESC-directed chondrogenesis. • Investigate exosomes released from healthy articular cartilage. • Develop a quantifiable assay to investigate exosome uptake. • Investigate the function of hESC-derived exosomes in maintenance of pluripotent stem cells and early differentiation.

Chapter 1 57 Chapter 2

Materials and Methods

2.1 Mouse Embryonic Fibroblast (MEF) Culture

2.1.1 Defrosting active MEFs

A vial of passage 0 active mouse embryonic fibroblasts (MEFs) was defrosted in the water bath at 37°C until a sliver of ice could be seen. Cells were then placed in a 50ml centrifuge tube and diluted with 10ml cold MEF medium (Table 2.1). Cells were then centrifuged at 800×g for 2min and the supernatant was discarded. The cell pellet was resuspended by tapping the bottom of the centrifuge tube and 13ml MEF medium was added. Cell suspension was pipetted up and down several times before all 13ml was added to a T75

flask which was then placed in the incubator at 37°C with 5% CO2.

Component Volume Source DMEM without L-glutamine 442.5ml Gibco L-Glutamine (2mM) 5ml Gibco Pen-strep 2.5ml Gibco FBS (heat inactivated) 50ml Gibco

Table 2.1: Mouse embryonic fibroblast medium. MEF media was kept at 4 °C and used within 2 weeks.

2.1.2 Culturing active MEFs

MEF medium on active MEFs was changed once every 3-4 days. MEF medium was removed from the corner of the flask, to avoid disturbing cells, and then discarded. Pre-warmed MEF medium (Table 2.1) was then added to the side of the flask so as not to disturb the cells; 13ml was added for a T75 flask and 20ml for a T225 flask. The flask was then placed back in the incubator at 37°C with 5% CO2.

2.1.3 Passaging active MEFs with TrypLE

Once active MEFs reached a confluency of 80-90%, they were passaged at a ratio of 1:3. Medium was removed from the cells and they were washed twice with 10ml phosphate buffered saline (PBS) without Ca2+/Mg2+. Then 1ml of TrypLE (Gibco) was added to a T75 flask or 2ml to a T225 flask and the flask was gently rocked back and forth to cover cells. The flask was then incubated for 2-3min at 37°C. After incubation, cells were then checked

58 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells under the microscope to see if they had ‘balled up’ and therefore were detaching from the substrate; if not, the flask was placed back in the incubator until they started to detach. Once cells had ‘balled up’ the flask was then given a hard knock to detach all the cells and 10ml of pre-warmed MEF medium was added to the flask to inactivate the TrypLE. The MEF medium was pipetted up and down the flask to detach all the cells, which were then collected into a 50ml centrifuge tube and centrifuged at 800×g for 2min. The supernatant was discarded and the cell pellet was resuspended by tapping the bottom of the tube. At each passage, MEFs were split at a 1:3 ratio. Cells were resuspended in the appropriate amount of media and cell suspension was added to each flask. MEF medium was added to each flask to make it up to the required amount; 13ml for T75 and 22ml for T225. Flasks were then placed in the incubator at 37°C with 5% CO2.

2.1.4 MEF Inactivation

MEFs were inactivated at passage 4 when they reached a confluency of 90%. From each flask medium was aspirated and discarded, and then 20ml of 10ug/ml mitomycin-C (Sigma-Aldrich) in MEF media was added. Flasks were then incubated at 37°C with 5%

CO2 for 2.5-3h. After incubation, medium was removed and each flask was washed once with 20ml MEF medium and then twice with 20ml PBS. Then 1.5ml TrypLE was added to each flask and incubated for 2-3min. Once cells began to detach, flasks were tapped to further detach cells and then 10ml of MEF medium was added to each flask and collected in a 50ml centrifuge tube. Cells were then centrifuged at 800×g for 2min, the supernatant was discarded and cells were resuspended in 10ml MEF medium then counted using a haemocytometer to determine total cell number. Cells were centrifuged at 800×g for 2min and resuspended in MEF media and Profreeze (Lonza) at a 1:1 ratio to achieve a final concentration of 1 × 106cells/ml. The cell suspension was aliquotted into 1.5ml cryovials, which were kept on ice, and then stored at -80°C in a freezing container for 24-48hrs before transferring to liquid nitrogen.

2.1.5 Inactivated MEF plating

A vial of inactivated MEFs was thawed in a water bath at 37°C, transferred to a 50ml centrifuge tube and diluted with 10ml cold MEF medium (Table 2.1). Cells were then centrifuged at 800×g for 2min and the supernatant was discarded. The cells were then resuspended in 5ml MEF medium and counted using a haemocytometer. Cells were resuspended in the required volume of medium to achieve the appropriate concentration for plating in a 6- or 24-well plate (Table 2.3), and plated on plastic cell culture plates pre-coated with gelatin (Table 2.2). These were then placed in the incubator at 37°C 5% with CO2 for 24hr. Inactivated MEFs can sustain ESC growth for up to 10 days, however after this time they were considered not to be supportive and were discarded.

Chapter 2 59 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Substrate Solution Plate incubation

Gelatin 0.1% gelatin (Sigma) in sterile dH2 O 1hr at 37 °C Fibronectin 16µg/ml fibronectin (Millipore) in PBS 30min at 37 °C Vitronectin 5µg/ml vitronectin (VTN-N) (Gibco) in PBS 1hr at RT

Table 2.2: Different substrate coating procedures. Cell culture plates were prepared in advance of passaging cells by adding enough substrate solution to cover each well and incubated at 37 °C for the required duration.

Number cells plated Volume of Plating Density Plate Type per well (cells/well) medium/well (cells/cm2) 6-well plate 2.8 − 3 × 105 2ml 3×104cells/cm2 24-well plate 6 × 104 0.5ml 3×104cells/cm2

Table 2.3: MEF plating densities. Inactivated MEFs were plated onto gelatin coated plates 24hrs before hESC were passaged.

2.2 Human Embryonic Stem Cell culture

2.2.1 Human Embryonic Stem Cell derivation

Several different human embryonic stem (hESC) lines were used during this project mainly Hues1, Hues7 and Man7. The Hues1 and Hues7 stem cell lines were derived by Cowan and colleagues at Harvard University as described in Cowan et al. 2004 and Klimanskaya and McMahon 2004. Briefly, frozen and thawed cleaved embryos (6 to 12 cells each) were cultured to the blastocyst stage, and frozen and thawed blastocysts were allowed to re-expand in culture, whereupon they were treated with Tyrode’s solution to remove the zona pellucida, followed by immunosurgery to isolate inner cell masses (ICM) which was then plated onto inactivated mouse embryonic fibroblasts (MEFs). After several days of culture as soon as 2-3 colony pieces can be obtained from the ICM outgrowth is passaged and plated onto inactivated MEFs giving rise to hESC colonies. The Man7 hESC line was derived at Manchester University as described in Camarasa et al. 2010. For whole cell RNA-sequencing experiments Man7 p27 and Hues1 p32 were used.

2.2.2 Defrosting and Feeding hESCs

In preparation for ESC culture, inactivated MEFs were plated 24h in advance at the appropriate cell density to achieve approximately 80% confluency, on the day of ESC plating. A vial of ESCs was defrosted in the water bath at 37°C then transferred into a 50ml centrifuge tube and diluted with 10ml cold hESC medium (Table 2.4). Cells were then centrifuged at 700×g for 3min and the supernatant was discarded. Cells were gently resuspended into small cell clusters by tapping the bottom of the tube and then the required amount of medium was added; 2ml for 1 well of a 6-well plate. Y-27632 (Sigma),

Chapter 2 60 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells a ROCK (Rho-associated coiled coil forming protein serine/threonine kinase) inhibitor, was added to the suspension at a final concentration of 10µM to aid in cell adhesion then cells were added to the MEF coated plates, which were then carefully placed in the incubator. Media on hESCs was changed daily.

Component Volume Final Concentration Source F12 DMEM 152.6ml - Gibco NEAA (100X) 2ml 1% Gibco Pen-Strep (5,000U/ml) 1ml 25U/ml Gibco L-glutamine (200mM) 2ml 2mM Gibco ITS Supplement 2ml 1% Gibco KnockOut Serum Replacement 40ml 20% Gibco FGF2 (100µg/ml) 20µl 10ng/ml Peprotech

Table 2.4: Human embryonic stem cell medium. Human ESC media without FGF2 was filter sterilised with 0.22µm filter into 50ml tubes and stored at -20°C until required. When thawed, FGF2 was added to the media and the complete media was kept at 4 °C and used within 2 weeks. NEAA, Non-Essential Amino Acids; ITS, Insulin-Transferrin-Selenium; Pen-Strep; Penicillin-Streptomycin.

2.2.3 Passaging hESCs with TrypLE

Once hESCs reached a confluency of 80% they were passaged. Medium was removed from the cells and they were carefully washed twice with PBS without Ca2+/Mg2+. Then 0.5ml of TrypLE was added and cells were incubated for 2-3min. After incubation, 2ml of hESC medium (Table 2.4) was added and pipetted up and down to dislodge all cells, which were then collected into a 15ml centrifuge tube. Cells were centrifuged at 700×g for 3min and the supernatant was discarded. Then cells were gently resuspended in hESC medium containing 10µM Rock inhibitor. Cells were passaged at a ratio of 1:3-5 (depending on number of colonies in original plate) and plated onto MEF-coated plates and then placed in the incubator at 37°C.

2.2.4 Passaging hESCs with EDTA

Medium was removed from the cells and each well was washed with 0.5ml 0.5mM UltraPure Ethylenediaminetetraacetic acid (EDTA) solution (Invitrogen) solution in PBS. Then 0.5ml EDTA solution was added to each well for 2-5min, during which cells were observed under the microscope until they began to separate and round up at which point the EDTA was removed. Then 1ml of hESC medium (Table 2.4) was added to each well and was pipetted up and down to dislodge all cells, which were then collected into a centrifuge tube. The appropriate amount of medium was added for the required number of wells and Rock inhibitor was also added at a final concentration of 10µM. Cells were then plated onto pre-prepared plates and placed in the incubator at 37°C.

Chapter 2 61 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

2.2.5 Feeder Free Culture of hESCs

Human ESCs were first cultured on MEFs for cell expansion, and when enough colonies were produced they were passaged into a feeder-free culture system to begin the chondrogenic protocol. Feeder free culture of hESCs was the same as hESC culture on MEFs except that hESCs were cultured in feeder-free medium (Table 2.5), plated onto fibronectin plates (Table 2.2) and passaged at a 1:3 ratio once they reached 100% confluency, using EDTA.

Component Volume Final Concentration Source Advanced DMEM/F12 420ml - Gibco NEAA (100X) 5ml 1% Gibco L-glutamine (200mM) 5ml 2mM Gibco Bovine Serum Albumin (BSA) 1% in PBS 50ml 0.1% Sigma Beta-Mercaptoethanol (50mM) 1ml 0.1mM Gibco Lipid Supplement (100X) 5ml 1% Gibco N2 Supplement (100X) 5ml 1% Gibco B27 Supplement (50X) 5ml 2% Gibco NT4 (10µg/ml) 100µl 2ng/ml Peprotech FGF2 (100µg/ml) 100µl 20ng/ml Peprotech Activin-A (100µg/ml) 50µl 10ng/ml Peprotech

Table 2.5: Feeder-free hESC culture medium. Feeder-free hESC media without growth factors was filter sterilised with 0.22µm filter into 50ml tubes and stored at -20°C until required. When thawed the growth factors were added to the media and the complete media was kept at 4 °C and used within 2 weeks

2.2.6 Chondrogenic differentiation of hESCs

For the differentiation of hESCs into chondrocytes the directed differentiation protocol (DDP) was used, as previously described (Oldershaw et al. 2010). Protocol was modified by removing NT4 and cells were not split on day 12 of the protocol. Human ESCs were grown in feeder free culture on fibronectin, as described is Section 2.2.5, until they reached a confluency of 80% at which point the protocol was started by supplementing DDP basal medium (DDP-BM) (Table 2.6) with growth factors (Table 2.7). Cell were passaged with TrypLE (Section 2.2.3) at days 4 and 8 of the protocol, in a split ratio of 1:4 and 1:2 respectively.

Chapter 2 62 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Component Volume Final Concentration Source DMEM/F12 420ml - Gibco NEAA (100X) 5ml 1% Gibco L-glutamine (200mM) 5ml 2mM Gibco Bovine Serum Albumin (BSA) 1% in PBS 50ml 0.1% Sigma Beta-Mercaptoethanol (50mM) 1ml 0.1mM Gibco Lipid Supplement (100X) 5ml 1% Gibco B27 Supplement (50X) 5ml 2% Gibco

Table 2.6: Directed Differentiation basal medium (DDP-BM). DDP-BM was filter sterilised with 0.22µm filter into 50ml tubes and stored at -20°C until required. When thawed the growth factors were added to the media and the complete media was kept at 4 °C and used within 2 weeks

Stage Stage 1 Stage 2 Stage 3 Day of Protocol 1 2 3 4 5 6 7 8 9 10 11 12 13 10µg/ml Wnt3a 25 25 25 ------20µg/ml ActA 50 25 10 ------20µg/ml FGF2 - 20 20 20 20 20 20 20 20 20 20 20 20 40µg/ml BMP4 - - 40 40 40 40 40 40 20 20 - - - 100µg/ml Fol - - - 100 100 100 100 ------20µg/ml GDF5 ------20 20 40 40 40 Substrate FN (16µg/ml) FN (8µg/ml) and 0.05% Gel

Table 2.7: Directed Differentiation Protocol Shows amount of each growth factor added at each day of the directed differentiation protocol (DDP). Numbers indicate final concentration of growth factors used for each day (ng/ml). Media was changed daily and complete media was made on the day by adding required amount of growth factors to the DD-BM. FN; Fibronectin (Millepore); Gel, Gelatine (Sigma); Wnt3A (R&D, 1324-WN); ActA, Activin A (Peprotech, 120-14); FGF2 (Peprotech, 100-18B), BMBP4 (Peprotech, 120-05); Fol, Follistatin (Peprotech, 120-13); GDF5 (Peprotech, 120-01).

2.3 RNA Analysis

2.3.1 RNA Extraction

Cell lysate for RNA extraction was harvested by adding 300ul of miRvana lysis buffer to a well of a 24-well plate or 600µl to a well of a 6-well plate. Then RNA was isolated from lysates by phenol extraction followed by purification on a glass fiber filters using the miRvana miRNA isolation kit (Ambion) following manufacturer’s instructions. Isolated RNA was stored at -80°C.

2.3.2 MicroRNA TaqMan Real-Time Polymerase Chain Reaction (RT- PCR)

MicroRNA qPCRs were performed using TaqMan microRNA assays (Appendix) following manufacturer’s instructions. For each RNA sample, U6 or RNU19 was used as a small RNA

Chapter 2 63 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells control. For each 15µl reverse transcription reaction, 10ng of total RNA was used. For each qPCR reaction, half volumes were used; 10µl total volume instead of 20µl total volume per reaction. Once prepared, qPCR reaction plates were loaded into a Life Technologies StepOne Real Time PCR instrument and results were analysed using StepOne software.

2.3.3 SYBR Green RT-PCR

RNA concentrations were quantified by UV-Vis spectroscopy measuring absorbance at 260nm using a Nanodrop 2000c (Thermo Scientific). Then in a microcentrifuge tube, 2µg of RNA, 1µg of random primers (Promega) and dH20 to total volume of 15µl were mixed together and incubated at 70°C for 5mins. Then the RNA primer mixture was placed on ice and 5µl M-MLV-RT 5X reaction buffer (Promega), 2µl 25mM dNTP mix (Bioline), 25 units of RNAse Inhibitor (Invitrogen) and 200 units M-MLV-RT (Promega) were added to it and diluted in dH2O to achieve a total volume of 25µl. The mixture was then incubated for 60min at 37°C to generate the cDNA. The cDNA product was stored at -20°C. Gene expression analysis was performed using SYBR green RT-PCR. The following was added to each well of a 384 well plate: 2µl cDNA (2ng/µl), 5µl power SYBR green PCR master mix (Applied Biosystems), 0.4µl 10mM forward primer (Appendix), 0.4µl 10mM reverse primer (Appendix), 2.2µl dH20. Plates were sealed, vortexed and centrifuged briefly before being loaded into a Biorad CFX384 or CFX96 Real-Time PCR detection system.

2.4 RNA Sequencing analysis

2.4.1 RNA-Seq library preparation

Small RNA samples were quantified by UV-Vis spectroscopy measuring absorbance at 260nm using a Nanodrop 2000c (Thermo Scientific). Three batches of RNA sequencing were performed, two batches of small RNA sequencing using Illumina HiSeq 2000, Man7 p27 (n=2) and Hues1 p32 (n=2) samples were sequenced externally at GATC Biotech in 2012 then additional Man7 (n=2) samples were sequenced at the Genomic Technologies Core Facility (GTCF) at the University of Manchester in 2015. The third batch of small RNA sequencing was performed for the exosome experiment this was sequenced internally at the GTCF using a Illumina NextSeq 500. Small RNA libraries were prepared by ligating adapters, reverse transcribing followed by amplification using TruSeq Small RNA Library Prep Kit (Illumina) following manufacturer’s instructions. The cDNA construct was then purified by gel electrophoresis at 100V for 60 minutes or until the blue front dye left the gel. The gel was visualised using SYBR Gold Nucleic Acid Gel Stain (ThermoFisher), briefly working solution SYBR gold stain was made by diluting with TE buffer 1:10,000 then gel was incubated in enough stain (50ml) to

Chapter 2 64 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells cover for 10 mins before visualisation using a blue-light transilluminator. The correct size band was identified using the custom ladders provided and then sliced out of the gel and placed into gel breaker tubes and centrifuged at 20,000xg for 2mins. To the elutant 300µl of ultrapure water was added and was left to shake overnight. Afterwards the gel debris was added to the top of a 5µm filter and centrifuged for 10s at 600xg. To concentrate the library the following was added to the elutant 30µl 3M NaOAc (Sigma), 2µl GlycoBlue Coprecipitant (ThermoFisher) and 975µl 100% ethanol. Then it was centrifuged at 20,000xg on a benchtop microcentrifuge at 20mins at 4°C. The supernatant was removed and the pellet was washed with 500µl of 70% ethanol. Then it was centrifuged again at 20,000xg for 2mins and the supernatant removed. With the lid open the tube was left at 37°C in a heat block until the pellet was dry and the pellet was resuspended in 10µl of ultrapure water.

2.4.2 Galaxy

Sequencing data was uploaded to the Galaxy server (Goecks et al. 2010; Blankenberg et al. 2010a) and converted to the correct format by using the FASTQ Groomer (version 1.0.4) tool and selecting the Sanger input option (Blankenberg et al. 2010b). Next the adaptor sequence (supplied by GATC Biotech) was clipped from the 3’ end of each read using the Clip tool (version 1.0.1)(Blankenberg et al. 2010b). Only clipped sequences were outputted to the Galaxy server. Then datasets were filtered by quality and length using the Filter FASTQ (version 1.0.0) tool in Galaxy (Blankenberg et al. 2010b) using the following parameters; minimum size 17 nucleotides, maximum size 26 nucleotides and minimum quality score 20. Finally datasets were converted to the correct format for upload to miRanalyzer. To do this they were converted from FASTQ format to FASTA format using the tool FASTQ to FASTA (version 1.0.0); this removed the quality score so only the sequence was left (Blankenberg et al. 2010b). Then each dataset was compacted so each identical sequence only appeared once with the number of repetitions next to it; this was done using Collapse (version 1.0.0). Afterwards datasets were converted to a tabular format using FASTA-to-Tabular (version 1.1.0) using default settings. Then all dashes were converted to TABs using Convert (version 1.0.0) selecting Dashes under ‘Convert all’. Finally the columns were reordered using Cut (version 1.0.1) and selecting ‘Cut columns c3,c2’ and ‘Deliminated by Tab’. This is summarised in Figure 2.1.

2.4.3 Mapping miRNAs to miRBase

Once datasets were formatted in Galaxy they were downloaded and subsequently uploaded to miRanalyzer (http://bioinfo2.ugr.es/miRanalyzer/miRanalyzer.php) (Hackenberg et al. 2009; Hackenberg et al. 2011). Hg19 was selected as the genome assembly and the following default settings were used; number of mismatches (known

Chapter 2 65 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Figure 2.1: Summary of Galaxy workflow for small RNA-seq library formatting for subsequent mapping. Raw reads were uploaded to the Galaxy server to be formatted for mapping to miRbase. This involved the following sequential steps; FAST Groomer to convert to correct format, Clip to remove adaptor sequence, Filter to remove poor quality and incorrect length reads, Format for correct format for miRanalyzer upload. miRNA) 1, number of mismatches (libraries) 1, number of mismatches (genome) 1, threshold of the posterior probability 0.9, minimum number of models which predict the miRNA 3. The program was launched and results were downloaded.

2.4.4 Finding differentially expressed miRNAs

The free statistical software R and the bioconductor package edgeR was used to find the differentially expressed miRNAs from the datasets (Team et al. 2013; Robinson et al. 2010). Raw read counts of mature miRNAs from miRanlyzer were inputted into edgeR. MicroRNAs with less than 1 reads per million in less than 2 samples were filtered out. The library size was then reset and normalised using upperquartile method.

2.4.5 miRComb

The miRComb analysis was performed in R following the miRComb vignette (Vila-Casadesus´ et al. 2016, mircomb.sourceforge.net/docs/miRComb-vignette.pdf). First miRNA and mRNA raw count tables were filtered for mRNAs and miRNAs with a median count of at least 5. Then reads were log2 transformed and normalised using ’normalize.quantiles’ function from the preprocessCore package. Differential expression analysis was performed between stages 0 and 3 using the ’limma’ method. Then miRNAs and mRNAs which were not differentially expressed between stages 0 vs. 3 were filtered out using the following parameters p-value<0.05 (Benjamini–Hochberg corrected) and fold change>1.5. Next the Pearson’s correlations and their p-value were computed between all mRNAs and miRNAs and only negative correlations were kept. Target prediction information was then added to the matrix using microCosm (version 5) and TargetScan

Chapter 2 66 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

(version 6.2) target prediction databases. The correlation p-value was corrected for false discovery using the Benjamini–Hochberg method and an interaction score calculated for each interaction (see below). This score is aimed to reflect the possible biological relevance of the miRNA; the larger the score the more the miRNA-mRNA interaction is deregulated.

InteractionScore = −2(logratio(miRNA) × logratio(mRNA))

2.5 Exosome methods

2.5.1 Exosome free media preparation

SW1353 cells and human articular chondrocytes (HAC) were cultured in medium depleted of bovine exosomes. Dulbecco’s Modified Eagle Medium (DMEM) was supplemented with 20% fetal bovine serum (FBS), 10% L-glutamine (200mM) and 5% penicillin-streptomycin (5,000U/ml). The medium was then ultracentrifuged overnight (16hr minimum) at 110,000xg at 4°C using a 45Ti rotor with polycarbonate tubes (Beckman Coulter, 355622). The supernatant was then filter sterilise with 0.22µm filter. The filtered was diluted with DMEM in a 1:1 ratio. Medium was then aliquotted and stored at 20°C once thawed it was kept at 4°C for up to 4 weeks.

2.5.2 Exosome Isolation

Exosomes were isolated by serial centrifugation steps. First, the supernatant was centrifuged at 500×g for 10min at 4°C to remove dead cells. The supernatant was then carefully transferred to another tube and spun at 1200×g for 20min at 4°C to remove cell debris. Supernatant was filtered through a 0.22µm filter (Millipore, SLGP033RS) to remove large microvesicles. For volumes of media greater than 4mls, the filtered supernatant was then ultracentrifuged at 110,000×g for 70min at 4°C in a polyallomer tube (Beckman Coulter, 331374) or Ultra-Clear tube (Beckman Coulter, 344060), using a SW40 rotor (Beckman Coulter) with a L-90k (Beckman Coulter) or Discovery 100SE (Sorvall) ultracentrifuge. Supernatant was carefully discarded and 10ml of ice-cold 0.22µm filtered PBS was added to the exosome pellet to wash it. The exosomes with PBS were then ultracentrifuged again under the same conditions as before, and afterwards the supernatant was carefully discarded and tubes were tapped on blue roll to remove residual PBS. To the exosome pellet, either 100µl of ice cold 0.22µm filtered PBS per 1ml of conditioned media was added, or direct RNA or protein lysis was performed on the pellet. If PBS was added, the tube was incubated at room temperature for 10 mins to allow the exosome pellet to resuspend. After incubation, the PBS was gently pipetted up and down to resuspend the exosome pellet, and transferred to a 1.5ml centrifuge tube and

Chapter 2 67 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells stored at -80°C. For volumes of medium less than 4mls, the filtered supernatant was then ultracentrifuged at 110,000×g for 70min at 4°C in a microfuge tube (Beckman Coulter, 357448) with a TLA-55 rotor (Beckman Coulter) in a Optima MAX-XP tabletop ultracentrifuge (Beckman Coulter) to pellet the exosomes. The supernatant was carefully removed and 1ml of ice-cold 0.22µm filtered PBS was added to the exosome pellet to wash them. The exosomes with PBS was then ultracentrifuged again under the same conditions as before and afterwards the supernatant was discarded and residual PBS in the tube was carefully removed with a pipette. To the exosome pellet, either 100µl of ice-cold 0.22µm filtered PBS per 1ml of conditioned media was added or direct RNA or protein lysis was performed on the pellet. This is summarised in Figure 2.2.

Conditioned media

Removes cells and Centrifuge (500xg,10mins, 4ºC) cell fragments Centrifuge (1200xg,20mins, 4ºC)

Removes larger microvesicles Filter (0.22um filter unit)

Ultracentrifuge (110,000xg, 70mins, 4ºC)

Wash with PBS and Ultracentrifuge (110,000xg, 70mins, 4ºC) to remove excess culture media

Resuspend (in 10ul PBS/ml of conditioned media and store -80ºC)

Figure 2.2: Workflow of exosome isolation by ultracentrifugation. Conditioned media was collected from cells and cleared of cell debris and larger vesicles by a series of centrifugation steps followed by filtration. The supernatant was ultracentrifuged to pellet the exosomes. Pelleted exosomes were either resuspended in PBS or RNA or protein lysis was performed directly on the pellet for downstream analysis.

2.5.3 Exosomal RNA isolation

Exosomal RNA was isolated by phenol extraction using miRvana miRNA isolation kit (Ambion) and eluted with 100ul elution solution provided with the kit. RNA was then concentrated using the RNeasy MinElute Cleanup Kit (QIAgen) to a final volume of 14µl.

2.5.4 Exosomal RNA quantification

Exosomal RNA was quantified by fluorometric based method using the QuantiFluor RNA assay (Promega) following manufacturer’s instructions were followed with the following

Chapter 2 68 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells alteration; the RNA dye was used at a 1:2000 dilution. RNA samples were diluted 1:200 with Tris-EDTA (TE) 1X buffer (Promega) and the recommended low RNA concentration standard curve was performed. The plate was loaded onto a GloMax Multi+ Detection System (Promega) for quantitation.

2.5.5 Dynamic Light Scattering

Size distribution of exosomes was calculated by dynamic light scattering using a Zetasizer Nano (Malvern). A minimum of 100µl of exosome sample suspended in PBS (as prepared is Section 2.5.2) was loaded into the instrument and 3 × 15 measurement runs were performed for each sample.

2.5.6 Exosome labelling with PKH26 dye

For the labelling of one exosome sample and control the following was done. Spin columns (Life Technologies, 4484449) for removing excess dye were first prepared by adding 650µl of PBS to the column which were then capped and vortexed. The columns were then tapped to remove air bubbles and incubated at room temperature for 10-15mins. After incubation columns were centrifuged at 800xg for 2mins. Before columns were removed from centrifuge the orientation of them in the centrifuged was marked on the columns. Dye mix for exosome labelling was made by combing 0.4µl of PKH26 dye (Sigma, MINI26-1KT) with 100µl of Solution C from the PKH26 kit (Sigma). For each sample 50µl of dye mix was added and left to incubate at room temperature for 5mins. Exosome mixture was then added to a spin column and columns were placed in the centrifuge at the same orientation they were prepared at, then they were centrifuged for 800xg for 2mins. Labelled exosomes were in the elution.

2.5.7 Electron microscopy of Exosomes

Exosomes were visualised using transmission electron microscopy (TEM). Two microlitres of exosome suspended in PBS was transferred onto a Formvar-carbon coated electron microscopy grids. Membranes were covered for 20mins. A 100 µl drop of PBS was placed on a sheet of parafilm and grids transferred with the sample membrane side facing down using clean forceps for 2mins. The grids were transferred to a 50µl drop of 1% glutaraldehyde for 5mins before being transferred to a 100µl drop of distilled water for 2mins. This was repeated 2 times for a total of 3 water washes. To contrast the samples, grids were transferred to a 50µl drop of uranyl-oxalate solution, for 5mins before being transferred to a 50µl drop of methyl-cellulose-UA (a mixture of 4% uranyl acetate and 2% methyl cellulose in a ratio of 100µl/900µl, respectively) for 10mins. The grids were removed and excess fluid was removed by blotting gently on filter paper and the grids were left to dry. The grids were visualised with a FEI Tecnai 12 Twin Transmission Electron Microscope.

Chapter 2 69 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

2.5.8 Cartilage Digestion and Cartilage Exosome Isolation

Human articular chondrocytes were isolated from a donated healthy knee joint with consent. All steps were performed in sterile environment in a class II culture hood. PBS used during wash steps contained 2.5µg/ml amphotericin B (Sigma) and 100U/ml penicillin (Life Technologies) and 100µg/ml streptomycin (Life Technologies). First large chunks of cartilage were removed from bone using a sterile scalpel and washed twice in PBS. Next the cartilage chunks were transferred to a 50ml centrifuge tube with HAC media and incubated at 4°C overnight. The next day the cartilage was finely chopped and the washed in PBS. The PBS washes were kept for exosome isolation; exosomes isolated from these washes were termed ’Cutting’. The diced cartilage was then digested with 0.25% trypsin (20ml/5g cartilage) (Sigma-T4424-500ml) at 37°C for 30mins on a flatbed shaker. The supernatant was removed and kept for exosome isolation (’Trypsin’). The cells were washed twice in HAC media to inactivate the trypsin. Next the cartilage was incubated with 3mg/ml HAC media collagenase type I (12 mg of collagenase/1g cartilage tissue) (Sigma-C0130-1G) overnight at 37°C (approx 15hrs) on a flatbed shaker. Next the cells were passed through a a 70µm cell strainer (Fisher Scientific-FB35181) and centrifuged at 400g for 10mins. The supernatant was kept for exosome isolation (’collagenase’). The cell pellet was washed in 10ml of serum-free media and centrifuge at 400g for 10mins, the supernatant was discarded and the wash step repeated for a total of two washed. The cell pellet was resuspended in about 20m HAC media/5g initial cartilage. Cell were counted and viability was assessed using trypan blue exclusion stain on the Countess cell counter (Life Technologies). Cells were plated into T75 flasks (about 3 million cells/flask) and maintained in HAC media at 5% CO2 and 37°C. Media was changed after 2 days then every 2-3 days thereafter. Exosomes were isolated from the washes using method in Section 2.5.2.

Component Final Conc. Source DMEM/F12 - Life Technologies Heat inactivated FBS 10% Life Technologies L-glutamine 2mM Life Technologies Penicillin 100U/ml Life Technologies Streptomycin 100µg/ml Life Technologies Amphotericin B 2.5µg/ml Sigma Ascorbic acid 50µg/ml

Table 2.8: Human Articular Chondrocyte (HAC) Medium. Medium used to culture HACs was stored at 4°C for up to 4 weeks. FBS, fetal calf serum.

Chapter 2 70 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

2.6 Molecular biology

2.6.1 Agarose gel electrophoresis

DNA fragments were separated by electrophoresis on 1% agarose gels in UltraPure Tris-Borate-EDTA (TBE) buffer (Invitrogen) containing 10µl SYBR Safe DNA Gel Stain (Invitrogen). DNA samples were mixed with 6X DNA loading buffer (NEB) prior to loading. Gels were run at 90V until adequate separation of the required bands was observed. Bioline hyperladders 1kb+ and 100bp were used to identify band sizes. Bands were visualised using a blue light transilluminator and excised if required. Where required, DNA was extracted from excised bands using the QIAquick Gel Extraction kit (QIAgen).

2.6.2 Ligations

All digestions were performed at 37°C for 1 hour, then digested DNA was purified using the QIAquick PCR Purification Kit (QIAgen). The concentrations of purified vectors and inserts were determined by NanoDrop. Vector and insert fragments were combined in a molar ratio of 3:1 respectively for ligations. The ligation reaction mix contained 1µl T4 DNA Ligase (NEB), 50ng vector, insert, 2µl 10X T4 DNA Ligase Buffer and 1µl T4 DNA ligase (NEB) made up to a total volume of 21µl of nuclease-free water. The ligation mixture was incubated at room temperature overnight.

2.6.3 Transformation of plasmids into competent E.coli

For all transformations, One Shot Stbl3 chemically competent E.coli (Invitrogen) were used. Competent cells were thawed on ice and 5µl of ligation product or plasmid was added. Cells were mixed gently by flicking and incubation on ice for 30min before heat-shocking at 42°C for 30s and incubated on ice for a further 2min. Then 250 µl of pre-warmed S.O.C. medium was added to each transformation. Cells were then incubated at 37°C for 1h with horizontal shaking at 225rpm. The transformation mix was spread on Luria-Bertani (LB) agar plates containing ampicillin at 100µg/ml and incubated overnight at 37°C.

2.6.4 Plasmid Verification

2ml of LB media containing ampicillin at 100µg/ml was inoculated with an individual plasmid colony and incubated for 12-18h with shaking at 225rpm and at 37°C . Plasmid DNA was isolated from bacterial cultures using the QIAprep Spin Miniprep Kit (QIAgen). Purified plasmid DNA was checked for incorporation of the insert by digesting with an appropriate enzyme to result in a distinct fragment pattern by gel electrophoresis when compared to an empty vector control. Plasmids with inserts were then further verified by DNA sequencing. All DNA sequencing was performed by the University of Manchester Sequencing Service using primers shown in A.1.

Chapter 2 71 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

2.6.5 CD63-eGFP Fusion Protein plasmid

For the live imaging of exosomes the plasmid shown in Figure 2.3 was constructed. To generate the CD63 insert, PCR was performed on a CD63 cDNA clone (IRAUp969A121D, Genome Cube) using primers shown in A.1. The PCR mixture contained 0.5µl CD63 cDNA, 0.5µl 100nM dNTP mix (Invitrogen), 0.5µl 10µM forward primer, 0.5µl 10µM reverse primer, 0.5µl Herculase II Fusion DNA Polymerase (Agilent), 5µl 5× Herculase II Reaction Buffer (Agilent) and 17.5µl of nuclease-free water. The PCR was performed using the cycling conditions shown in Table 2.9. To generate plasmid with CMV and EF1a promoter different restriction enzymes were used (see below). After vector and insert digestion they were ligated as described is Section 2.6.2. Two different vectors were used one contained a CMV promoter the other a EF1a promoter, they are 3rd generation lentiviral plasmid expressing eGFP which were kindly donated by Dr. Ioannis Bantounas from the lab (original plasmid pRRLSIN.cPPT.PGK-GFP.WPRE was from Didier Trono, Addgene plasmid 12252). After ligation the plasmid was transformed into E.coli as described is Section 2.6.3. Plasmid was verified by restriction digest with Sac II (NEB) followed by DNA sequencing with primers as described in Section 2.6.4.

CD63-eGFP Fusion Protein plasmid driven by EF1a

To generate the insert for the plasmid containing a EF1a promoter, it was digested with BamHI (NEB) and XbaI (NEB) and purified using the QIAquick PCR Purification Kit (QIAgen). The vector with EF1a promoter was digested with BamHI (NEB) and XbaI (NEB) then gel purified.

CD63-eGFP Fusion Protein plasmid driven by CMV

To generate the insert for the plasmid containing the CMV promoter, it was then digested with NheI (NEB) and AgeI (NEB) and purified using the QIAquick PCR Purification Kit (QIAgen). The vector with CMV promoter was digested with NheI (NEB) and AgeI (NEB) then gel purified.

Number of Cycles Temperature Duration 1 95°C 2min 95°C 20s 30 70°C 20s 72°C 49s 1 72°C 5min

Table 2.9: Herculase II Cycle for CD63 insert

Chapter 2 72 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Figure 2.3: Plasmid used to overexpressed CD63 tagged with eGFP

2.7 Third Generation Lentiviral Production

2.7.1 HEK293T cell culture

Low passage healthy HEK293T cells (ATCC®CLR-3216) were used for lentiviral production. Cells were cultured in HEK293T media (Table 2.10). When cells reached 70-80% confluency they were passaged using TrypLE as described in Section 2.2.3. Media was changed very carefully as the cells detach very easily.

2.7.2 Plasmid transduction

On day 1, HEK293T cells were split into 10 x 15cm2 dishes (Corning, 430599) per lentiviral preparation at a cell density of 8x106 cells/dish in a final volume of 15ml HEK293T medium per dish. Then, 24hrs later, cells were transfected. The plasmid transfection mix for 10 dishes contained 105µg shuttle plasmid, 105µg pMDLg-pRRE (Gag/Pol) plasmid, 35.7µg pMD2.G (Env-VSVg) plasmid, 21µg pRSV-Rev plasmid and

1.2ml 2.5M CaCl2 made up to a total volume of 13.1ml with nuclease-free water. In another tube 13.1ml of 2XHBS (2.11) was added, to which the transfection mix was added dropwise whilst pipetting bubbles into the HBS solution using a second pipette controller for efficient mixing. The transfection mixture was left at room temperature for 30min then 2.5ml was added dropwise to each dish making sure it was evenly distributed throughout the dish. All plasmids used for the production of third generation lentivirus were generated

Chapter 2 73 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells and donated by Dr. Ioannis Bantounas.

2.7.3 Lentivirus collection and isolation

On day 3 of the protocol, medium was aspirated and discarded from cells and replaced with 15ml/dish of HEK293T medium containing 10mM sodium butyrate and incubated for 6-8hrs at 37°C with 5% CO2. After incubation medium was collected and replaced with 20ml/dish of HEK293T medium without sodium butyrate. All collected medium was stored at 4°C in the dark. Twenty-four hours later medium was collected from cells and combined with the first collection. In the hood Virkon was added to cells and were placed under UV for 20min then discarded into autoclave bags. Collected medium was filtered through a 0.45µm filtration system (Millepore, SCHVU05RE) then centrifuged overnight at 6,000xg at 4°C using a F10BA-6x500y rotor (Fiberlite) in 500ml tubes (Beckman Coulter, 355605) with a Avanti J20 centrifuge. The supernatant was discarded and tubes were rinsed carefully with 10ml of sterile ice-cold PBS. The PBS wash was aspirated and the pellet was resuspended in 10ml of ice-cold sterile PBS by pippetting. The suspension was ultracentrifuged for 90min at 20,000rpm at 4°C using Ultra-Clear tubes (Beckman Coulter, 344060) with a SW40 rotor (Beckman Coulter) in a L-90k (Beckman Coulter) ultracentrifuge. The supernatant was carefully removed and 150µl of ice-cold PBS was added incubated on ice for 3hrs in the dark to allow resuspension of pellet. After incubation 50µl of PBS was added and the suspension was centrifuged in a microfuge tube for 2min at 4°C at 1,000rpm to pellet any unsuspended protein. The supernatant was then aliquotted and stored at -80°C.

2.7.4 Lentivirus quantification

Lentivirus was quantified by titration followed by calculation of GFP postive cells by flow cyctometry. HEK293T cells were plated at 7.5x104 cells/well into all wells of a 12 well plate (Corning) ina total volume of 1ml of HEK293T medium per well. The next day one well of the 12 well plate was trypsinised and counted using a heamocytometer. The following treatments were given; 1:10-2 virus dilution (n=1), 1:10-3 virus dilution (n=2), 1:10-4 virus dilution (n=2), 1:10-5 virus dilution (n=2), 1:10-6 virus dilution (n=2) and no virus (n=2). Each condition was given in a total volume of 0.5ml of HEK293T medium. The next day the medium was topped up to 1ml. Three days after the virus was added to cells they were trypsinised with 200µl of TrpLE and incubated for 3min at 37°C. After incubation 600µl of HEK293T medium was added to cells to stop the trypsin and cell suspension was pelleted by centrifugation at 800xg for 2min. The supernatant was discarded and 1ml PBS was added then cells were centrifuged at 800xg for 2min. The supernatant was discarded and the cells were resuspended in 200µl of 4% PFA and incubated at room temperature for 15min. After incubation cells were centrifuged at 800xg for 2min and the supernatant was

Chapter 2 74 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells discarded and resuspended in 1ml of PBS then re-centrifuged at 800xg for 2min. The cell pellet was then resuspended in 400µl of PBS and percentage of eGFP positive cells were calculated using a LSR Fortessa (BD Bioscience) cell analyser instrument. The virus titre was calculated using the following equation;

(%eGF P positive cells) × (Dilution factor) × (T otal cells transduced) T itre = (V olume of viral dilutent added to cells)

Component Volume Final Concentration Source DMEM without L-glutamine 437.5ml - Gibco L-Glutamine (200mM) 5ml 2mM Gibco Pen-strep (5,000U/ml) 2.5ml 25U/ml Gibco NEAA 5ml 1% Gibco FBS (heat inactivated) 50ml 10% Gibco

Table 2.10: HEK293T medium. Medium used to culture HEK293T cells was stored at 4°C for up to 4 weeks.

Component Amount Final Conc. Source NaCl 16.4g 0.283M Sigma HEPES acid 11.9g 23mM Sigma

Na2HPO4 0.21g 1.5mM Sigma Water to 1L - -

Table 2.11: HEPES-Buffered Saline (2XHBS). Bring pH to exactly 7.10 with NaOH. 2X HBS was filter sterilised with 0.22µm filter, aliquotted and stored at -20°C.

Chapter 2 75 Chapter 3

Results I - Whole Transcriptome and Small RNA-seq analysis of Chondrogenesis in hESCs

3.1 Aims and Introduction

MicroRNAs are key regulators during differentiation, acting to fine-tune gene expression in nearly every biological processes. Among these process is chondrogenesis, where precise control of gene expression is critical for appropriate differentiation of precursor cells. A number of miRNAs have been previously identified as important in regulating chondrogenesis (summarised in Table 1.1). The majority of these studies were performed by either differentiating MSCs into chondrocytes, which does not capitulate normal human development of articular cartilage, or by using non-human models such as the chick embryo limb bud model. Here we use a human in vitro model of cartilage development and preform a whole genome analysis of miRNAs involved in cartilage differentiation. Human ESCs were differentiated into chondrocytes using the directed differentiation protocol (DDP) as previously described (Oldershaw et al. 2010). This is a good model of cartilage development as cells progress through several distinct stages of differentiation, initially through a primitive streak/mesoendoermal population characterised by expression of mesendoderm markers MIXL1, CDH1, GATA4 and GSC, early mesoderm marker T and early endoderm marker FOXA2. Next, cells progress into a mesoderm population characterised by loss of expression of endoderm markers GATA4 and FOXA2 and gain of mesoderm markers KDR and PDGFRB. In the last of the stage of the DDP cells acquire a chondrogenic phenotype characterised by expression of COL2A1, ACAN, SOX9 and SOX6, and production of sulfated glycosaminoglycan (Oldershaw et al. 2010), these cells are termed chondroprogenitors. The chondroprogenitors produced by the DDP have displayed functional properties by their ability to repair cartilage defects in rat models (Cheng et al. 2014). Although cells produced by the DDP are immature chondrocytes and lack expression of the complete set of ECM genes that are expressed by mature chondrocytes, it is possible that this is due to

76 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells expression of specific miRNAs acting as checkpoints during the process of differentiation, limiting the maturation of the chondrocytes produced in this differentiation protocol. By identifying the miRNAs that direct chondrogenesis and differentiation of pluripotent stem cells the protocol could be improved with the aim of using these cartilage cells therapeutically. This chapter describes a complete characterisation of microRNA expression throughout the differentiation protocol. We examine the hypothesis that several key miRNAs are involved in regulating human chondrogenesis.

3.2 Results

3.2.1 Small RNA-seq quality control

To identify miRNAs regulated during hESC chondrogenesis, two hESC lines (Man7, n=4; Hues1, n=2) were differentiated into chondrocytes using the directed differentiation protocol (DDP) (Figure 3.1A, top) as previously described (Oldershaw et al. 2010; Cheng et al. 2014). At the end of the protocol cells acquired a chondrogenic phenotype as shown by the increased expression of cartilage markers SOX9, COL2A1, ACAN and COL11A1 along with a loss of pluripotency associated genes, OCT4 and NANOG (Figure 3.1B-G). RNA samples were collected at the end of each of the three stages in the protocol and small RNA libraries generated. In addition, whole transcriptome libraries were produced for stages 0, 2 and 3 (summarised in Figure 3.1H). This work was performed by Dr. Aixin Cheng. The Illumina adapter sequence was first trimmed from all small RNA-seq reads and the sequencing quality of trimmed reads was assessed using the FASTQC tool (Andrews et al. 2010) which showed 97.63% of all sequences had a Phred score (sequence quality score of a given base) greater than or equal to 30, indicating an accuracy of each base call of at least 99.99% (Figure 3.2A). Sequences with a Phred score of less than 30 were removed, allowing confidence in all base calls. After adapter trimming, the sequence length distribution of all samples showed a peak at 22-23bp, this is within the expected size range for mature miRNAs (Figure 3.2B). Analysis of the small RNA libraries showed an acceptable percentage of the total read count mapping to mature miRNAs consistent with reported literature (Tam et al. 2015), with 22.35% and 5.24% of raw sequencing reads mapping to mature miRNAs in the 2015 and 2012 samples respectively (Figure 3.2C). Samples M2.a and M0.b, however, both showed a low percentage of reads mapping to mature miRNA, only 0.27% and 0.82% respectively (Figure 3.2C), suggesting the RNA may have degraded before the sequencing took place. Sample M0.b clustered with other stage 0 samples in PCA plots (Figure 3.4B) conversely M2.a showed up as an outlier and therefore was omitted from further analysis. Overall these QC analysis indicate that sample sequencing was largely of high quality and reads mapped to mature miRNAs and therefore could be used for further downstream

Chapter 3 77 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

A B 0.08 SOX9 C 0.015 COL2A1

0.06 0.010

0.04

0.005 0.02 Relative to GAPDH Relative to GAPDH

0.00 0.000

Day 0 Day 4 Day 8 Day 0 Day 4 Day 8 Day 13 Day 13 ACAN D 0.025 E 0.008 COL11A1

0.020 0.006

0.015 H 0.004 0.010 Hues1 (H) n=2 Man7 (M) n=4 0.002 0.005

Stage Relative to GAPDH (a) (b) (a) (b) (c) (d) Relative to GAPDH 0.000 0.000 Batch 2012 (GATC) 2015 (UoM)

Day 0 Day 4 Day 8 Day 0 Day 4 Day 8 Stage 0 Day 13 Day 13 H0.A H0.B M0.A M0.B M0.C M0.D F G NANOG 0.008 OCT4 0.10 Stage 2 H2.A H2.B M2.A M2.B M2.C M2.D

mRNA mRNA 0.08 Stage 3 H3.A H3.B M3.A M3.B M3.C M3.D 0.006 Stage 0 0.06 H0.a H0.b M0.a M0.b M0.c M0.d 0.004 Stage 1 H1.a H1.b M1.a M1.b M1.c M1.d 0.04 0.002 Stage 2 0.02 Relative to GAPDH H2.a H2.b M2.a M2.b M2.c M2.d Relative to GAPDH miRNA miRNA Stage 3 H3.a H3.b M3.a M3.b M3.c M3.d 0.000 0.00

Day 0 Day 4 Day 8 Day 0 Day 4 Day 8 Day 13 Day 13

Figure 3.1: Experimental Plan for small and whole transcriptome RNA-seq. (A) Overview of directed differentiation protocol (DDP). HESCs were differentiated into chondrocytes by adding specific combinations of growth factors at each stage of the protocol. RNA was then extracted from the cells at the end of each stage on days 0, 4, 9 and 14. (B-G) Validation of chondrogenesis of Man7 by RT-qPCR during the DDP as shown in (A). Shows upregulation of chondrogenic markers (B-E) and loss of pluripotency markers (F-G) as cells progress through the DDP. Expression relative to GAPDH. (H) Table of all samples sent for RNA-sequencing. GFs, growth factors; ActA, Activin-A; Fol, Follistatin; UoM, University of Manchester; GATC, GATC Biotech. analysis.

Chapter 3 78 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

A Quality Score B Sequence Length Diustribution C Total reads Percentage of Raw reads mapped to reads mapped 1.0 100 2012 Sample 2015 total mature to mature miRNAs miRNAs 80 H0.a 2.38E+07 1.02E+06 4.18% 60 H1.a 1.85E+07 6.54E+05 3.46% 0.5 H2.a 2.13E+07 8.79E+05 3.98% 40

Percentage H3.a 2.01E+07 1.55E+06 7.65% 20 H0.b 2.19E+07 1.21E+06 5.40%

Cumulative Distribution H1.b 2.03E+07 6.36E+05 3.04% 0.0 0 H2.b 1.98E+07 5.77E+05 2.83% 25 30 35 40 15 20 25 30 35 40 H3.b 2.31E+07 1.05E+06 4.45% Per sequence quality score Sequence Length M0.a 2.55E+07 1.20E+06 4.39% M1.a 2.11E+07 5.47E+05 2.46% D All Datasets UoM 2015 Datasets GATC 2012 Datasets M2.a 2.67E+07 7.75E+04 0.27% M3.a 2.55E+07 6.24E+06 24.19% 6.41% 1.88% 15.08% 3.64% 0.82% M0.b 1.99E+07 1.87E+05 0.82%

3.74% 26% M1.b 2.34E+07 8.33E+05 3.47%

41.12% M2.b 2.45E+07 1.18E+06 4.77% 7.91% M3.b 3.14E+07 1.39E+06 4.38%

1.34% 2.90% M0.c 2.60E+07 3.65E+06 13.69% M1.c 2.77E+07 5.58E+06 19.77% 72% 20.72% M2.c 2.17E+07 4.97E+06 22.45% 87% 9.31% M3.c 2.07E+07 6.08E+06 28.88% M0.d 1.96E+07 3.20E+06 16.07% M1.d 2.29E+07 5.42E+06 23.22% Mature miRNAs RefSeq RepBase16 Unassigned Reads M2.d 2.02E+07 5.98E+06 29.07% M3.d 2.42E+07 6.04E+06 24.37% Other RNAs (tRNA, piRNA, Rfam, other species miRNA)

Figure 3.2: Quality assessment of small RNA libraries (A) Cumulative distribution of quality of scores of each sequence in the small RNA-seq libraries generated in 2012 (black) and 2015 (grey). (B) Sequence length distribution of small RNA-seq libraries generated in 2012 (black) and 2015 (grey) after adaptor removal. Shows peaks at 22bp for both batches of samples. (C) Small RNA-Seq read count summary. Total number of reads refers to the total number of raw reads before any filtering. Percentage of reads mapped to mature miRNAs are the total number of reads post filtering that mapped to mature miRNAs in miRbase 21. (D) Pie charts of percentage of filtered reads mapping to miRNAs and other RNA species. piRNA, Piwi-interacting RNA; Rfam, database of non-coding RNAs; RepBase16, database of repetitive sequences.

3.2.2 Changes in miRome and Transcriptome variation during hESC directed chondrogenesis

A Spearman’s correlation matrix was generated for both miRome and transcriptome libraries to investigate the degree of variability between samples during the protocol (Figure 3.3A-B). As expected, as the cells progress through the protocol the miRome and transcriptome profiles of samples become increasingly more different compared to stage 0 samples, as indicated by a decreasing Spearman’s correlation coefficient between the samples (Figure 3.4A). Using Spearman’s correlation analysis also indicated the hESC cell line Man7 has a larger increase in variation during differentiation, in both miRNA and mRNA expression, compared with the cell line Hues1 (Figure 3.4A). This analysis also indicates a greater variability in the miRome compared with the transcriptome of samples. To further evaluate sources and degree of variation between all samples, a principal component analysis (PCA) was performed (Figure 3.4B). Principal component analysis reduces the number of variables (e.g. gene or miRNA expression) to a small set of principal components which can explain the maximum amount of variance in the data, with the first component (x-axis) accounting for as much as the variation as possible. The distance between each point in a PCA plot gives an indication of the variance between those datasets; the closer they are to each other the more similarities they have. Figure

Chapter 3 79 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

3.4B shows how the samples separate out by stage of the protocol for both miRNA and mRNA datasets as indicated by arrows. PCA shows reasonable clustering of biological repeats. Interestingly, in the miRome PCA the samples also separate out by batch. Due to this separation the batch variation was taken into account when performing the differential expression analysis.

Chapter 3 80 1 M3.d

0.8 0.7 0.7

0.83 0.81 0.74 0.84 0.84 0.84 0.83 0.72 0.77 0.77 0.76 0.73 0.69 0.72 0.73 0.75 0.69 0.72 0.75 1 M3.c

0.7

0.78 0.69 0.79 0.81 0.78 0.91 0.75 0.75 0.74 0.77 0.71 0.74 0.73 0.73 0.69 0.73 0.72 0.66 0.67 0.71

1 M3.b

0.7 0.88 0.88 0.89 0.75 0.76 0.78 0.81 0.81 0.82 0.71 0.68 0.74 0.75 0.76 0.76 0.67 0.65 0.73 0.78 M3.d 1

0.8 0.7 0.7 0.83 0.81 0.74 0.84 0.84 0.84 0.83 0.72 0.77 0.77 0.76 0.73 0.69 0.72 0.73 0.75 0.69 0.72 0.75

1 M3.a

0.8 0.6 0.7 1 M3.c 0.79 0.69 0.68 0.72 0.75 0.76 0.77 0.66 0.63 0.71 0.71 0.73 0.73 0.62 0.66 0.74

0.7

0.78 0.69 0.79 0.81 0.78 0.91 0.75 0.75 0.74 0.77 0.71 0.74 0.73 0.73 0.69 0.73 0.72 0.66 0.67 0.71

1 H3.b 1 M3.b 0.8 0.8

0.91 0.81 0.82 0.83 0.87 0.87 0.76 0.74 0.79 0.81 0.83 0.75 0.71 0.76 0.81 0.83 0.7

0.88 0.88 0.89 0.75 0.76 0.78 0.81 0.81 0.82 0.71 0.68 0.74 0.75 0.76 0.76 0.67 0.65 0.73 0.78

1 H3.a 1 M3.a

0.8 0.8

0.8 0.6 0.7 0.81 0.81 0.82 0.85 0.87 0.75 0.73 0.79 0.79 0.82 0.73 0.69 0.74 0.79 0.81 0.79 0.69 0.68 0.72 0.75 0.76 0.77 0.66 0.63 0.71 0.71 0.73 0.73 0.62 0.66 0.74

M2.d 1 H3.b 1

0.8 0.8 0.8 0.82 0.76 0.79 0.82 0.88 0.86 0.77 0.77 0.78 0.79 0.85 0.83 0.78 0.77 0.78 0.91 0.81 0.82 0.83 0.87 0.87 0.76 0.74 0.79 0.81 0.83 0.75 0.71 0.76 0.81 0.83

H3.a 1 M2.c 1

0.8 0.8 0.7

0.81 0.81 0.82 0.85 0.87 0.75 0.73 0.79 0.79 0.82 0.73 0.69 0.74 0.79 0.81 0.76 0.78 0.78 0.79 0.76 0.81 0.74 0.75 0.72 0.73 0.79 0.79 0.71 0.74

1 M2.d 1 M2.b 0.8

0.82 0.76 0.79 0.82 0.88 0.86 0.77 0.77 0.78 0.79 0.85 0.83 0.78 0.77 0.78 0.8

0.84 0.87 0.86 0.73 0.75 0.87 0.87 0.82 0.83 0.74 0.72 0.77 0.82

1 M2.c 0.7 M2.a 1 0.76 0.78 0.78 0.79 0.76 0.81 0.74 0.75 0.72 0.73 0.79 0.79 0.71 0.74 0.8 0.8

0.87 0.85 0.73 0.74 0.79 0.78 0.79 0.73 0.72 0.76 0.75

1.0

1 M2.b

0.8 1 H2.b 0.84 0.87 0.86 0.73 0.75 0.87 0.87 0.82 0.83 0.74 0.72 0.77 0.82

0.9 0.9 0.8

0.79 0.84 0.84 0.87 0.86 0.79 0.76 0.81 0.84 0.87

1 M2.a

0.8 0.8 0.8 0.87 0.85 0.73 0.74 0.79 0.78 0.79 0.73 0.72 0.76 0.75 H2.a 1 1.0 0.77 0.75 0.82 0.82 0.84 0.85 0.77 0.71 0.77 0.83 0.87

0.7 1 H2.b

0.9

0.9 0.8 0.79 0.84 0.84 0.87 0.86 0.79 0.76 0.81 0.84 0.87 1 M1.d 0.9 0.8 0.78 0.78 0.82 0.81 0.91 0.89 0.84 0.81

0.6

0.8 1 H2.a

Spearman's Correlation 0.77 0.75 0.82 0.82 0.84 0.85 0.77 0.71 0.77 0.83 0.87 1 M1.c 0.8

0.81 0.81 0.79 0.88 0.93 0.85 0.78 0.79

0.5 0.7 1 M1.d

0.9 0.8 0.78 0.78 0.82 0.81 0.91 0.89 0.84 0.81 1 M1.b 0.6 0.93 0.88 0.88 0.78 0.79 0.85 0.83 0.85

Spearman's Correlation 1 M1.c

0.8

0.81 0.81 0.79 0.88 0.93 0.85 0.78 0.79 0.5 1 M1.a

0.89 0.88 0.78 0.79 0.84 0.83 0.85 1 M1.b

0.93 0.88 0.88 0.78 0.79 0.85 0.83 0.85 1 H1.b

0.91 0.82 0.78 0.85 0.87 0.88 1 M1.a

0.89 0.88 0.78 0.79 0.84 0.83 0.85 1 H1.a

0.81 0.76 0.83 0.88 0.88 1 H1.b

0.91 0.82 0.78 0.85 0.87 0.88 1 M0.d

0.89 0.85 0.81 0.83 1 H1.a

0.81 0.76 0.83 0.88 0.88 1 M0.c

0.85 0.75 0.77 1 M0.d

0.89 0.85 0.81 0.83 1 M0.b

0.83 0.87 1 M0.c

MicroRNA Regulation of Chondrogenesis in0.85 Human0.75 0.77 Embryonic Stem Cells 1 H0.b

0.88 1 M0.b

0.83 0.87

1 H0.a 1 H0.b

0.88 1 H0.a

H3.b H3.a H2.b H2.a H1.b H1.a H0.b H0.a M3.c M2.c M1.c M0.c M3.d M3.b M3.a M2.d M2.b M2.a M1.d M1.b M1.a M0.d M0.b

1 M3.d

0.8 0.7 0.7 1 M3.D 0.83 0.81 0.74 0.84 0.84 0.84 0.83 0.72 0.77 0.77 0.76 0.73 0.69 0.72 0.73 0.75 0.69 0.72 0.75

0.86 0.85 0.85 0.94 0.89 0.94 0.89 0.89 0.91 0.87 0.86 0.79 0.88 0.88

H3.b H3.a H2.b H2.a H1.b H1.a H0.b H0.a M3.c M2.c M1.c M0.c M3.d M3.b M3.a M2.d M2.b M2.a M1.d M1.b M1.a M0.d M0.b 1 M3.c

0.7 0.78 0.69 0.79 0.81 0.78 0.91 0.75 0.75 0.74 0.77 0.71 0.74 0.73 0.73 0.69 0.73 0.72 0.66 0.67 0.71 1 M3.C

0.9 0.9 0.8 0.8

0.78 0.78 0.86 0.96 0.85 0.81 0.72 0.79 0.81 1 M3.b

0.7

0.88 0.88 0.89 0.75 0.76 0.78 0.81 0.81 0.82 0.71 0.68 0.74 0.75 0.76 0.76 0.67 0.65 0.73 0.78 1 M3.a

0.8 0.6 0.7 0.79 0.69 0.68 0.72 0.75 0.76 0.77 0.66 0.63 0.71 0.71 0.73 0.73 0.62 0.66 0.74 1 M3.B

0.99 0.86 0.85 0.85 0.83 0.85 0.86 0.84 0.84 0.82 0.85 0.85 1 H3.b

0.8 0.8 0.91 0.81 0.82 0.83 0.87 0.87 0.76 0.74 0.79 0.81 0.83 0.75 0.71 0.76 0.81 0.83

1 M3.A 0.87 0.84 0.85 0.83 0.85 0.86 0.85 0.84 0.81 0.85 0.85 H3.a 1

0.8 0.8

0.81 0.81 0.82 0.85 0.87 0.75 0.73 0.79 0.79 0.82 0.73 0.69 0.74 0.79 0.81 1 M2.d

0.8

0.82 0.76 0.79 0.82 0.88 0.86 0.77 0.77 0.78 0.79 0.85 0.83 0.78 0.77 0.78 1 H3.B

0.9 0.9

0.94 0.95 0.96 0.96 0.92 0.84 0.93 0.93 1 M2.c

0.7

0.76 0.78 0.78 0.79 0.76 0.81 0.74 0.75 0.72 0.73 0.79 0.79 0.71 0.74

1 H3.A 0.8 M2.b 1

0.92 0.92 0.89 0.93 0.88 0.86 0.88 0.91 0.8

0.84 0.87 0.86 0.73 0.75 0.87 0.87 0.82 0.83 0.74 0.72 0.77 0.82 1 M2.a 0.8 0.8

0.87 0.85 0.73 0.74 0.79 0.78 0.79 0.73 0.72 0.76 0.75 1.0

1.0 1 M2.D

0.9 0.9 0.9 0.9

0.94 0.91 0.93 0.82 0.9 H2.b 1 0.9 0.9 0.8 0.79 0.84 0.84 0.87 0.86 0.79 0.76 0.81 0.84 0.87

0.8

0.8 1 M2.C 1 H2.a 0.9 0.86 0.86 0.87 0.79 0.85 0.87 0.77 0.75 0.82 0.82 0.84 0.85 0.77 0.71 0.77 0.83 0.87

0.7 0.7 1 M1.d 0.9 0.8 0.78 0.78 0.82 0.81 0.91 0.89 0.84 0.81

0.6 0.6 H2.B 1 0.96 0.95 0.93 0.89 0.95 0.95

Spearman's Correlation Spearman's Correlation 1 M1.c 0.8 0.5

0.81 0.81 0.79 0.88 0.93 0.85 0.78 0.79 0.5

miRNA

H2.A 1 M1.b 1

0.94 0.91 0.86 0.94 0.95 0.93 0.88 0.88 0.78 0.79 0.85 0.83 0.85 1 M1.a

0.89 0.88 0.78 0.79 0.84 0.83 0.85 1 M0.D

0.95 0.93 0.99 0.97 1 H1.b

0.91 0.82 0.78 0.85 0.87 0.88

1 H1.a 1 M0.C

0.81 0.76 0.83 0.88 0.88 0.92 0.94 0.93 1 M0.d

0.89 0.85 0.81 0.83 1 M0.B

0.91 0.92 1 M0.c

0.85 0.75 0.77

1 M0.b 1 H0.B

0.83 0.87

0.98 1 H0.b

0.88

B H0.A 1 1 H0.a

H3.b H3.a H2.b H2.a H1.b H1.a H0.b H0.a

M3.c M2.c M1.c M0.c H3.B H3.A H2.B H2.A H0.B H0.A M3.d M3.b M3.a M2.d M2.b M2.a M1.d M1.b M1.a M0.d M0.b M3.B M3.A M0.B M3.D M3.C M2.D M2.C M0.D M0.C 1 M3.D 0.86 0.85 0.85 0.94 0.89 0.94 0.89 0.89 0.91 0.87 0.86 0.79 0.88 0.88

Spearman’s correlation matrix of all mRNA libraries (A) and miRNA libraries (B). Each value refers to the 1 M3.C

0.9 0.9 0.8 0.8 0.78 0.78 0.86 0.96 0.85 0.81 0.72 0.79 0.81 1 M3.B

0.99 0.86 0.85 0.85 0.83 0.85 0.86 0.84 0.84 0.82 0.85 0.85 1 M3.A

0.87 0.84 0.85 0.83 0.85 0.86 0.85 0.84 0.81 0.85 0.85 1 H3.B

0.9 0.9

0.94 0.95 0.96 0.96 0.92 0.84 0.93 0.93 1 H3.A 0.8 0.92 0.92 0.89 0.93 0.88 0.86 0.88 0.91

1.0 1 M2.D 0.9 0.9 0.9 0.9 0.94 0.91 0.93 0.82 0.9

0.8 1 M2.C 0.9 0.86 0.86 0.87 0.79 0.85 0.87 0.7

0.6 1 H2.B 0.96 0.95 0.93 0.89 0.95 0.95 Spearman's Correlation

0.5 1 H2.A

0.94 0.91 0.86 0.94 0.95 1 M0.D 0.95 0.93 0.99 0.97

mRNA 1 M0.C

0.92 0.94 0.93 1 M0.B

0.91 0.92 1 H0.B

0.98 1 H0.A A Figure 3.3: Spearman’s correlationSpearman’s matrix correlation of coefficient (rho) hESC between directed the chondrogenesis. two corresponding samples. H3.B H3.A H2.B H2.A H0.B H0.A M3.B M3.A M0.B M3.D M3.C M2.D M2.C M0.D M0.C

Chapter 3 81 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells 150 100 50 100 0 50 − 50 PC3 PC1 26.6% Variance PC2 20.76% Variance 0 − 100 − 50 − 150 0 0

50 50

100 100 − 50 − 50 PC3 13.08% Variance 13.08% PC3 Variance 13.08% PC3 100 M0.b 20 50 10 0 0 M2.a − 50 PC2 − 10 PC1 26.6% Variance PC2 12.87% Variance mRNA − 100 − 20 − 150 0 0

50 20

150 100 − 50 − 20 − 40 PC2 20.76% Variance 20.76% PC2 Variance 9.91% PC3 2015 30 30 20 20 2012 10 10 M0.b 0 0 M0.b PC1 PC1 16.64% Variance PC1 16.64% Variance − 10 − 10 M2.a M2.a B

Stage 1 Stage 0 Stage 2 Stage 3 − 20 − 20

0 0

20 10 20

− 10 − 20 − 20 − 40 PC2 12.87% Variance 12.87% PC2 Variance 9.91% PC3 miRNA

(A) Average Spearman’s correlation coefficient between stage 0 and each stage of the protocol for Hues1 (blue)

Stage 3 Stage Stage 2 Stage

mRNA Man7 Stage 0 vs. mRNA Hues1 Stage 0 vs.

Stage 1 Stage Stage 0 Stage

1.0 0.9 0.8 0.7 0.6 A (rho) coeffiecient

miRNA Man7 Stage 0 vs. miRNA Hues1 Stage 0 vs. Spearman's correlation Spearman's Figure 3.4: Investigating the variabilityand of Man7 hESC (purple) directed for chondrogenesis. bothand mRNA transciptome (solid profiles line) at and differenttranscriptome miRNA stages PC1 (dotted of vs. line) chondrogenesis. PC2 samples.the PCA (middle Error plots more top), bars generated PC1 similarities indicate for vs. they the miRomeM2.a PC3 have. standard PC1 which (top deviation. All vs. was right) (B) excluded datasets PC2 and Principal from separate (middle PC2 component further left), out vs. analysis analysis. PC1 by (PCA) PC3 PC, vs. stage shows (middle Principal changes PC3 of right). component. in (bottom the Datasets miRome left) protocol are and as separated PC2 out indicated vs. in by PC3 2D arrows. (bottom space Samples middle) by and their show variability; reasonable the clustering closer of they biological are replicates to except each for other the dataset

Chapter 3 82 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

3.2.3 Highest expressed miRNAs in hESCs and hESC-derived chondroprogenitor cells

Examining the highest expressed miRNAs in hESCs and hESC-derived chondroprogenitors revealed how only a few miRNAs account for the majority of the sequencing reads. Also a majority of these highly expressed miRNAs are transcribed as polycistronic miRNAs from clusters (Figure 3.5D). In hESCs, the highest expressed miRNAs are those from the miR- 302 cluster and miR-17-92 cluster which, along with miRNAs miR-21 and miR-92b, account for 52% of all mature miRNAs in hESCs (Figure 3.5A). The miR-302 and miR-17-92 have previously been found to be highly expressed in pluripotent stem cells (Wilson et al. 2009) also the role of miR-302 regulating hESC pluripotency has been well characterised (Card et al. 2008; Subramanyam et al. 2011). High expression of the miR-302 cluster is lost as cells undergo chondrogenesis while high miR-17-92 cluster expression is maintained in hESC-derived chondroprogenitors (Figure 3.5D). The highest expressed miRNAs in hESC-derived chondroprogenitors are those transcribed from Hox genes and the miR-17-92 cluster along with miR-21 accounting for 65% of all expressed mature miRNAs in hESC-derived chondroprogenitors (Figure 3.5B). The miR-17-92 has been implicated in several cancers (Olive et al. 2010), suggesting the high expression of the miR-17-92 cluster in both hESCs and hESC-derived chondroprogenitors may be indicative of proliferating cells. The Hox miRNAs do not display similar high expression in hESCs with several of the Hox miRNAs not being expressed in hESCs (Figure 3.5D). In summary, a majority of the miRNA sequencing reads are accounted for by small number of miRNAs which are mainly transcribed as polycistronic clusters. The miRome of hESCs is characterised by high expression of miR-302 cluster miRNAs corresponding to literature (Wilson et al. 2009; Morin et al. 2008; Morin et al. 2008) and the miRome of hESC-derived chondroprogenitors is characterised by high expression of miRNAs transcribed from Hox genes.

Chapter 3 83 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Stage 0 Stage 3 A B C 0.3% Top 30 hESCs Top 30 Chondro 8% 3% miR-92a-3p miR-10a-5p 18% miR-302 cluster miR-92b-3p miR-10b-5p 30% miR-17-92 cluster miR-302a-5p miR-92a-3p 45% miR-99b cluster miR-21-5p miR-21-5p Hox miRs miR-302d-3p miR-148a-3p 18% miR-26a-5p miR-26a-5p miR-21 1% miR-148a-3p miR-191-5p 8% 49% miR-92b 3% miR-182-5p miR-22-3p 7% Other miRNAs 9% 1% miR-302b-3p miR-146b-5p miR-191-5p miR-99b-5p -5p arm miR-99b-5p miR-92b-3p D -3p arm miR-302 cluster Hox miRs miR-17-92 cluster miR-302a-3p miR-27b-3p miR-146a-5p miR-30a-5p 10000 10000 10000 miR-30a-5p miR-181a-5p miR-302c-3p miR-125a-5p 100 100 100 miR-151a-3p miR-16-5p miR-22-3p miR-30e-5p Stage 0 miR-30e-5p miR-151a-3p 1 1 1 A B C D miR-186-5p miR-143-3p chr4 chr13

miR-125a-5p miR-151a-5p miR−302b miR−302c miR−302a miR−302d miR−367 miR−196b miR−10a miR−196a miR−615 miR−10b miR−17 miR−18a miR−19a miR−20a miR−19b miR−92a miR-371a-5p miR-186-5p miR-27b-3p let-7a-5p miR-151a-5p miR-30d-5p

miR-16-5p miR-100-5p 10000 10000 10000 miR-21-3p miR-222-3p miR-372-3p miR-30c-5p miR-486-5p miR-25-3p 100 100 100

miR-25-3p miR-21-3p Stage 3 miR-30c-5p miR-182-5p 1 1 1 miR-146b-5p miR-103a-3p A B C D chr4 chr13

miR−302b miR−302c miR−302a miR−302d miR−367 miR−196b miR−10a miR−196a miR−615 miR−10b miR−17 miR−18a miR−19a miR−20a miR−19b miR−92a

Figure 3.5: Top expressed miRNAs in hESCs and hESC-derived chondroprogenitors. (A) List of top 30 expressed miRNAs in hESCs (left) and hESC-derived chondroprogenitors (right) in descending order. miRNAs transcribed as clusters are highlighted in bold and those from the same clusters are highlighted in the same colours. Pie charts displaying percentage of total reads accounted for by top expressed miRNAs in hESCs (B) and hESC-derived chondroprogenitors (C). (D) Bar charts showing expression of highly expressed miRNA clusters in hESCs (top) and hESC-derived chondroprogenitors (bottom). The 5’ arms (-5p) of the miRNA are shaded darker while 3’ arms (-3p) are shaded lighter.

3.2.4 Differential expression analysis of miRome and transcriptome of hESCs undergoing directed chondrogenesis

Taking into account different sources of variation can aid to identify more biologically relevant results by normalising out known variations (McCarthy et al. 2012). As described in section 3.2.2, the Spearman’s correlation matrix indicated differences in variation between the two different cell lines (Figure 3.4A) and the PCA (Figure 3.4B) indicated differences in the two batches. Using a generalised linear method in edgeR, different additive models were applied to the miRome data to perform the differential expression analysis between each stage of the protocol. An additive model will adjust for baseline differences between variables such as cell line or batch making the comparisons between the stages more precise (McCarthy et al. 2012). These models were compared by number of differentially expressed miRNAs (FDR<0.05) identified for different stage comparisons of the DDP. By taking into account both the cell line and batch of each sample this allowed the discovery of more differentially expressed miRNAs at all stages of chondrogenesis (Figure 3.6A), therefore this model was used for the differential expression analysis. After filtering reads for a minimum of 1 read per million in at least 2 samples, 1,268

Chapter 3 84 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Batch and Cell line corrected 400 Batch corrected only Cell line corrected only 300 No correction

200

100

Number DE miRNAs (FDR<0.05) 0

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

Figure 3.6: Analysis of differential expression methods Bar chart comparing different additive models used in edgeR by number of differentially expressed miRNAs for each stage comparison (FDR<0.05). miRNAs and 14,397 protein coding genes were detected during directed hESC chondrogenesis. Differential expression analysis of RNA-seq samples, found 331 miRNAs and 3,761 protein coding genes to be differentially expressed between stages 0 and 3 of the protocol (FDR<0.05). Heat maps were generated for the top 100 differentially expressed miRNAs (Figure 3.7) and the top 200 differentially expressed genes (Figure 3.8). Unsupervised hierarchical clustering of miRNA-seq samples (Figure 3.7, top) shows samples firstly separating into a pluripotency associated (pluri) which contains all Man7 stage 0 samples and shows high expression of pluripotency associated miRNAs (highlighted in red) and low expression of miRNAs transcribed from Hox genes (highlighted in orange). The second group further divides samples into an intermediate group (inter) containing a mixture of stage 1 and 2 samples showing lower expression of pluripotency associated miRNAs and a chondrogenic group (chon) containing all stage 3 samples that show low expression of pluripotency associated miRNAs, and high expression of Hox miRNAs along with miR-99a which has previously been reported to be upregulated during early chondrogenesis in rat MSCs (Zhou et al. 2016). Together, this indicates a clear trend where the miRome of the samples is switching from a pluripotent state towards a chondrogenic state with good clustering of biological replicates. Similarly for the transcriptome (Figure 3.8, top) unsupervised clustering shows samples first dividing into a pluripotent group (pluri) containing all stage 0 samples and a chondrogenic group (chon) with all stage 2 and stage 3 samples. The chondrogenic associated group contained several genes implicated in limb development including; TBX2 (Gibson-Brown et al. 1998), HAND2 (Osterwalder et al. 2014) and several Hox genes (Zakany and Duboule 2007). Interestingly this chondrogenic group further divides into a group containing only differentiated Man7 samples for the biological replicate ’c’, this

Chapter 3 85 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells group appears to be distinct from other samples by its high expression of the following genes; ART4, BMP10, CCL7, CFI, COL15A1, CLEC2B, DCN, HTR2B, IL18R1, IL33, MGP, SELE, TBX20. To investigate the global transcriptome changes that occurred during directed chondrogenesis of hESCs, gene ontology (GO) analysis was performed on gene clusters generated by unsupervised hierarchical cluster analysis of the top 200 differentiated genes between stages 0 and 3 of the DDP (Figure3.8, left). Hierarchical clustering identified four clusters of genes. One of the clusters enriched with genes associated with the GO term ‘embryonic skeletal system development (p=3.16x10-33) was significantly upregulated during hESC-directed chondrogenesis including TBX2, HAND2 and several Hox genes. This strongly indicates that these cells were undergoing differentiation towards cartilage. Two of the downregulated gene clusters were significantly enriched with genes associated with ‘stem cell maintenance’ (p=7.38x10-3) strongly indicating loss of stem cell identity during hESC-directed chondrogenesis. Genes in the last cluster were significantly enriched with genes associated with ’anterior/posterior pattern specification’ (p=6.04x10-3) this includes several Hox genes, this corresponds to upregulation of several Hox miRNAs observed in the miRome during hESC-directed chondrogenesis.

Chapter 3 86 Color Key and Histogram MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells 30 20 Count 10

5 Hues1 Man7 high low Color Key and Histogram 0 35 Stage 0 Stage 0 pluri chon

25 inter −3 −1 Stage 1 1 2 3 Stage 1 Count 15 Row Z−Score Stage 2

5 Stage 2 0 −3 −1 1 3 Row Z−Stage 3 Score Stage 3

miR−517a−3p miR−520a−3p miR−518c−3p miR−518a−3p n=100miR−525−5p miR−520c−3p miR−518b miR−1911−5p miR−516b−5p miR−519c−3p miR−1323 miR−448 miR−515−5p miR−−517a1283−3p miR−512−3p miR−1298−5p miR−−520a302d−−3p5p miR−302b−5p miR−196b−5p miR−99a−5p miR−−518c196a−−3p5p miR−615−3p miR−1269b miR−−518a10a−−3p3p miR−542−5p miR−302c−5p miR−−525367−−5p3p miR−371a−5p miR−100−5p miR−450b−5p miR−−520c302d−−3p3p miR−302b−3p miR−302a−5p miR−−518b302a−3p miR−302c−3p miR−10a−5p miR−10b−5p miR−−1911520d−−5p5p miR−520d−3p miR−518f−3p miR−−516b1298−−5p3p miR−522−3p miR−519c−5p miR−526b−5p miR−−519c520a−−3p5p miR−517−5p miR−524−5p miR−−1323302e miR−1272 miR−141−5p miR−518e−3p miR−−448520g−3p miR−518d−3p miR−367−5p miR−−515498−5p miR−524−3p miR−519d−3p miR−−12831912 miR−1911−3p miR−1264 miR−205−3p miR−−512124−−3p3p miR−517c−3p miR−519b−3p miR−−1298519d−−5p5p miR−518a−5p miR−520e miR−520f−5p miR−−302d3937−5p miR−523−3p miR−518f−5p miR−−302b373−−5p5p miR−526b−3p miR−512−5p miR−515−3p miR−−196b4433−−5p5p miR−526a miR−518c−5p miR−−99a525−−5p3p miR−10b−3p miR−615−5p miR−490−3p miR−−196a196b−−5p3p miR−196a−3p miR−216a−3p miR−−6151224−3p−3p miR−6500−3p miR−3918 miR−519e−5p miR−−1269b4731−3p miR−490−5p miR−6888−3p miR−−10a4647−3p miR−4668−5p miR−4652−3p miR−−54219b−−5p2−5p miR−520f−3p miR−200b−5p miR−519e−3p miR−−302c378h−5p miR−367−3p miR−371a−5p H3.a H3.b H2.a H2.b H0.a H1.a H1.b H0.b M1.c M0.c M2.c M3.c M0.a M0.b M1.d M0.d M3.a M3.b M3.d M2.d M2.b M1.a M1.b miR−100−5p miR−450b−5p miR−520d−5p miR−520d−3p miR−518f−3p miR−1298−3p miR−522−3p miR−519c−5p miR−526b−5p miR−520a−5p miR−517−5p miR−524−5p miR−302e miR−1272 miR−141−5p miR−518e−3p miR−520g−3p miR−518d−3p miR−367−5p miR−498 miR−524−3p miR−519d−3p miR−1912 miR−1911−3p miR−1264 miR−205−3p miR−124−3p miR−517c−3p miR−519b−3p miR−519d−5p miR−518a−5p miR−520e miR−520f−5p miR−3937 miR−523−3p Pluripotency associated miRNAs Car7lage associated miRNAs miRNAs transcribed from HOX cluster miR−518f−5p miR−526b−3p miRNA Groups miR−512−5p miR−515−3p miR−526a miR−518c−5p miR−525−3p miR−4433−5p miR−373−5p miR−10b−3p miR−615−5p miR−490−3p miR−196b−3p miR−196a−3p miR−216a−3p miR−1224−3p miR−6500−3p miR−4731−3p miR−490−5p miR−6888−3p miR−4647 miR−4652−3p miR−4668−5p miR−3918 miR−519e−5p miR−200b−5p miR−520f−3p miR−378h miR−519e−3p miR−19b−2−5p miR−302d−3p miR−302b−3p miR−302a−5p miR−302a−3p miR−302c−3p miR−10a−5p miR−10b−5p H3.a H3.b H2.a H2.b H0.a H1.a H1.b H0.b M1.c M0.c M2.c M3.c M0.a M0.b M1.d M0.d M3.a M3.b M3.d M2.d M2.b M1.a M1.b

Figure 3.7: Heat map of differentially expressed miRNAs with unsupervised hierarchical clustering. Heatmap of read counts for the top 100 differentially expressed miRNAs for all samples. Samples (columns) are highlighted by cell line and stage of the protocol. Hierarchical clustering of samples shows they separated out into a pluripotent (pluri), an intermediate (inter) and a chondrogenic (chon) group. MicroRNA rows are highlighted by miRNA group which have been manually curated from the literature (Table 1.1).

Chapter 3 87 Color Key and Histogram 100 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells 80 60 Count 40 20

0 pluri chon high low −3 −Hues1 1 1 Man7 3 Row Z−Score n=200 Stage 0 Stage 0 Stage 2 Stage 2 Stage 3 Stage 3

NMRK2 TNFRSF8 POU5F1B APELA ZSCAN10 NANOG PIPOX FAM124A KLHDC7A SYT6

-2 GABRA5 GRM4 TMPRSS11E SOX3 EOMES NKX1−2 FOXH1 GRID2 VSNL1 SCGB3A2 RAB17 HHLA1 ABHD12B LCK PRDM14 NODAL LEFTY1 CER1 GDF3 TDGF1 pval=4.39x10 EPHX3 A2ML1 NLRP7 CHGA KLRG2 GLB1L3 POU2F3 -3 KLKB1 C9orf135 VENTX ST8SIA3 GYLTL1B TFCP2L1 RPL39L FGF19 T PRODH SCNN1A B3GNT7 ESRP1 MUC4 EPHA1 HAS3 SHISA9 USP44 SP5 pval=7.38x10 ZIC3 SOX2 ZIC2 FST L1TD1 POU5F1 SFRP2 VRTN HOXA7 -33 HOXC9 HOXA5 HOXA3 HOXB7 HOXC4 HOXA11 HOXD9 HOXD11 HOXC10 HOXD4 HOXD3 HOXD10 GUCY1A3 ALDH1A2 TBX2 HOXB4 HOXB5 HOXA10 HOXA9

pval=3.16x10 HOXC8 HOXA13 HOXB8 HOXC6 HAND2 GPRC5A DLX1 HOXB3 HOXB9 HOXB6 LOX RTP1 CHST4 INSM1 FUT2 CAPN13 SEZ6 PNPLA5 FOXB1 FOXI2 SOX14 VSTM1 CH25H HES3 F13A1 CASP4 PDX1 FOXA2 EN1 CHRM2 IGF1 ACTBL2 GBP1 SLN EMCN SERPINB2 CYSLTR2 MYOZ2 CR1L C4orf51 IDO1 KLK5 LHFPL4 CCDC172

-3 DSCAM ADGRF2 DAZL OLIG3 HMX3 MAB21L1 HOXC12 EMX2 HOXC11 CGA CBLC stem cell maintenance (GO:0019827) embryonic skeletal system development (GO:0048706) anterior/posterior paBern specificaDon (GO:0009952) SLC52A3 SEMG1

GO Term HTR3A CCDC64B VIL1 CCDC129 SLC34A2 LGALS12 CCR7 pval=6.04x10 CST2 FAM83F KDF1 MACC1 ZNF578 NECAB1 HRASLS5 AADACL3 CALB1 HPDL TNS4 C1orf94 NLRP12 SPIB UTF1 FAM71F1 GLIPR1L1 HOXA6 HOXC5 HOXD8 HOXA4 DCAF12L1 SLC51A LY75 CSH1 CD207 KRTAP19−1 VAX2 HTR2B CLEC2B PLSCR5 CNTNAP4 BRINP3 SFTA3 DMRT3 NKX2−6 TRIM43 CSH2 TMEM30B LECT1 MT1G BMP10 CCL7 TBX20 ART4 DCN COL15A1 IL18R1 SELE IL33 CFI MGP H0.a H0.b H2.a H2.b H3.b H3.a M0.c M2.c M3.c M0.b M0.d M3.d M3.b M3.a M2.d

/

Figure 3.8: Heat map of differentially expressed genes with unsupervised hierarchical clustering. Heatmap of read counts for the top 200 differentially expressed genes for all samples. Samples (columns) are highlighted by cell line and stage of the protocol. Hierarchical clustering of samples shows they separated out into a pluripotent (pluri) and a chondrogenic (chon) group. Top four gene clusters from unsupervised hierarchical classification were uploaded to the PANTHERdb web server for Gene Ontology analysis and p-values (Bonferroni corrected) for top GO terms (over 5 fold enriched) for each cluster are shown above each highlighted cluster.

Chapter 3 88 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

3.2.5 Biological variability in hESC directed chondrogenesis can be exploited to identify novel miRNAs

As observed in the hierarchical clustering of the transcript libraries, stage 2 and stage 3 samples for the Man7 biological replicate ’c’ cluster together distinct from other samples. Further analysis of these samples shows very low expression of key ECM markers, COL2A1 and ACAN, along with lower expression of the main cartilage miRNA, miR-140 (Figure 3.9A-C), suggesting cells in this biological replicate differentiated poorly or differentiated to other lineages. To verify chondrogenesis had taken place during this biological replicate differential expression analysis was performed comparing Man7 ’c’ chondrogenic samples (stage 2 and stage 3) with all pluripotent samples. This analysis identified 904 genes upregulated in the chondrogenic samples (logFC>2, FDR<0.05). Gene ontology analysis of these genes revealed they are enriched for the following GO terms ’positive regulation of chondrocyte differentiation’ and ’positive regulation of cartilage development’(Figure 3.9D), suggesting differentiation towards a chondrogenic state had occurred. To further investigate the differences between the Man7 ’c’ replicate and other samples, differential expression analysis was performed between the Man7 ’c’ replicate with all other replicates, grouping stages 2 and 3 together as a chondrogenic group. This analysis revealed 884 differentially expressed protein coding genes between the Man7 ’c’ replicate and the other replicates. Gene ontology analysis of genes upregulated in the more successful replicates revealed enrichment for genes belonging to the GO terms ’DNA metabolic process’ (p value=1.96x10-6) and ’Cell cycle G1/S phase transition’ (p value=1.96x10-6)(Figure 3.9F) which are associated with cell proliferation (Whitfield et al. 2006). Genes upregulated in the Man7 ’c’ replicate revealed an enrichment for genes belonging to the GO terms ’Collagen catabolic process’ (p value=3.29x10-3) (Figure 3.9E). For the miRome libraries, the same differential expression analysis was performed and revealed 61 differentially expressed miRNAs (FDR<0.05)(Figure 3.9G). Interestingly, of the 27 miRNAs enriched in the Man7 ’c’ run, miRNAs miR-145, miR-29a and miR-574 have previously been reported to inhibit chondrogenesis in MSCs when overexpressed (Martinez-Sanchez et al. 2012; Guerit´ et al. 2014; Guerit et al. 2013). Also miR-146a has been reported to be upregulated in OA cartilage and its upregulation can induce apoptosis in chondrocytes (Jin et al. 2014). Expression of these inhibitory miRNAs may be partly the cause of the poor chondrogenesis observed in the Man7 ’c’ replicate by targeting chondrogenic regulators including: Sox9 (Guerit et al. 2013), FoxO3a which promotes Sox9 expression (Guerit´ et al. 2014) and retinoid X receptor (Guerit et al. 2013). Both genes and miRNAs enriched in the Man7 ’c’ replicate compared with other replicates appear to negatively regulate chondrogenesis. If the opposite is true for miRNAs enriched

Chapter 3 89 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells in the more successful chondrogenesis replicates then they may be novel positive regulators of chondrogenesis. Such as miR-98 which is enriched in the successful chondrogenesis replicates (Figure 3.9G), has been validated to interact with PRTG (proteogenin) by cross-linking immunoprecipitation (Vlachos et al. 2015; Karginov and Hannon 2013). A study recently showed overexpression of PRTG in chick chondroprogenitors promoted apoptosis which could be prevented by co-treatment with miR-9 which directly targets PRTG (Song et al. 2013b), suggesting miR-98 may have a similar function. MicroRNA-98 also been shown to target Fas a death receptor which once activated signals for apoptosis (Wang et al. 2011), further supporting the role of miR-98 promoting chondroprogenitor cell survival. Other miRNAs enriched in the Man7 ’c’ replicate may also have a chondroprotective role.

Chapter 3 90 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

A COL2A1 B ACAN C miR-140-3p Rest 50000 800 Rest 5000 Rest M7.c M7.c M7.c 40000 4000 600 30000 3000 400 20000 2000 Read count Read count Read count 200 10000 1000

0 0 0

Stage 0 Stage 2 Stage 3 Stage 0 Stage 2 Stage 3 Stage 0 Stage 1 Stage 2 Stage 3 D Man7 (c) replicate vs. pluripotent G

Fold GO biological process complete Enrichment P-value positive regulation of chondrocyte differentiation (GO:0032332) 9.24 1.59E-03 complement activation (GO:0006956) 7.74 2.26E-03 positive regulation of cartilage development (GO:0061036) 7.69 2.12E-04 collagen fibril organization (GO:0030199) 7.39 9.10E-07 collagen catabolic process (GO:0030574) 6.96 2.78E-09 Rest enriched E Man7 (c) replicate enriched Fold GO biological process complete Enrichment P-value collagen catabolic process (GO:0030574) 16.97 3.29E-05 multicellular organism catabolic process (GO:0044243) 15.51 7.10E-05 collagen metabolic process (GO:0032963) 14.5 1.25E-04 multicellular organismal macromolecule Man7 (c) enriched metabolic process (GO:0044259) 13.63 2.12E-04 multicellular organism metabolic process (GO:0044236) 11.99 6.22E-04 F Succesful replicates enriched Fold GO biological process complete Enrichment P-value DNA replication initiation (GO:0006270) 43.48 9.42E-04 cell cycle G1/S phase transition (GO: 0044843) 19.39 7.49E-06 G1/S transition of mitotic cell cycle (GO: 0000082) 19.39 7.49E-06 DNA replication (GO:0006260) 12.66 7.62E-06 DNA metabolic process (GO:0006259) 6.21 1.96E-06

Figure 3.9: Enriched miRNAs in optimal hESCs directed chondrogenesis Bar charts of read counts of COL2A1 (A), ACAN (B) and miR-140-3p (C) in Man7 ’c’ replicate compared with all other biological replicates. (D) Gene ontology analysis of genes upregulated in Man7 replicate ’c’ chondrogenic samples (stage 2 and stage 3) in comparison to all pluripotent samples. Gene list was filtered using following parameters; FDR<0.05, logFC>2. (E) Gene ontology analysis of genes enriched in chondrogenic Man7 (c) samples compared with all other chondrogenic samples. Gene list was filtered using following parameters; FDR<0.05, logFC>2, logCPM>5. (F) Gene ontology analysis of genes enriched in more successful chondrogenic samples compared with chondrogenic Man7 ’c’ samples. Gene list was filtered using following parameters; FDR<0.05, logFC>2, logCPM>5. (G) Bar plot of miRNAs differentially expressed between chondrogenic Man7 ’c’ samples compared with all other chondrogenic samples (FDR<0.05). MicroRNAs which have been previously reported to be involved in chondrogenesis are highlighted in blue and those involved in pluripotency are highlighted in red. All p-values for the gene ontology analysis are Bonferroni corrected. Reference genes used for gene ontology analysis was all genes expressed in samples tested with at least 1 count per million in at least 2 of the samples.

Chapter 3 91 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

3.2.6 Stage-wise differential expression analysis miRNAs

Differential expression analysis was performed for all stage-wise comparisons during the DDP for both cell lines independently; summary shown in Figure 3.10A. There were more differentially expressed miRNAs for all stage-wise comparisons with the Man7 cell line compared with Hues1, this is consistent to earlier observed differences in the two lines from Spearman’s correlation analysis (Figure 3.4A). Despite these differences there is still good overlap between the two cell lines, with 48 of the of the 84 differentially expressed miRNAs between stages 0 and 3 of the DDP in Hues1 also being differentially regulated in Man7 (Figure 3.10B). Of these 47 shared differentially regulated miRNAs, 14 downregulated miRNAs are associated with pluripotency (Figure 3.10C, highlighted in red), three upregulated miRNAs have been reported to be involved in chondrogenesis (Figure 3.10C, highlighted in blue), miR-181b shown to be a negative regulator of cartilage development (Song et al. 2013d), miR-99a is a negative regulator of early chondrogenesis by targeting BMPR2 (Zhou et al. 2016) and miR-483 stimulates proteoglycan and collagen synthesis in bovine chondrocytes (Yang et al. 2015). Also nearly all Hox miRNAs were upregulated in both cell lines between 0 and 3 (Figure 3.10C, highlighted in orange). Several of the miRNAs upregulated between stages 0 and 3 in both cell lines have yet to be reported to have a role in chondrogenesis and may be novel regulators of chondrogenesis. As well as displaying more differentially regulated miRNAs than Hues1, Man7 also exhibits differences in the timing of miRNA expression. Upregulation of Hox miRNAs occurs earlier in the Man7 cell line, with all 10 Hox miRNAs being upregulated by stage 2 of the differentiation protocol, whereas in Hues1 upregulation of the majority of Hox miRNAs does not occur until stage 3 of the DDP. Pluripotency miRNAs were gradually downregulated during the DDP in the Man7 cell line: 51 pluripotency associated miRNAs (highlighted in red) were downregulated between stages 0 and 2 and 37 of these miRNAs were further downregulated between stages 2 and 3 of the protocol along with another 8 pluripotency associated miRNAs. Many miRNAs reported to regulate chondrogenesis were upregulated during the DDP (highlighted in blue, Figure 3.11- 3.13). There were considerably more of these cartilage miRNAs upregulated at the end of the DDP in Man7 (21 miRNAs) compared with Hues1 (3 miRNAs). This is still higher even after taking into account the total number of upregulated miRNAs, with 14% of total upregulated miRNAs between stages 0 and 3 being associated with chondrogenesis in Man7 compared with only 7% in Hues1.

Chapter 3 92 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

A C Down Up Stage wise 0 vs. 2 0 vs. 3 2 vs. 3 Comparison Down Up Down Up Down Up miR-1298-3p miR-100-3p miR-1298-5p miR-100-5p Man7 85 81 134 154 60 13 miR-1323 miR-10a-3p Hues1 5 1 43 41 9 13 miR-184 miR-10a-5p miR-187-3p miR-10b-3p miR-1911-5p miR-10b-5p B 0 vs. 3 miR-1912 mir-152-3p 12 miR-302a-3p miR-152-5p miR-302b-3p miR-181b-5p

● miR-302b-5p miR-188-3p ● ● 8 ● ● miR-302c-3p miR-196a-3p ● ● ● ● miR-302c-5p miR-196a-5p ● ● miR-302d-3p miR-196b-5p 4 ● ● ●●● miR-302d-5p miR-199b-5p ●●● ●● ● ●

Fold Change miR-367-3p miR-3065-5p 2 0 miR-448 miR-362-5p

● let-7f-5p ● ● ●● miR-512-3p miR-4473 ● ●● ● ● ●● miR-515-5p miR-483-3p ● ● ● let-7fg5p −4 ● ● ● ● ● miR-517-5p miR-500a-3p

●● Hues1 Log ● miR-518c-3p miR-500a-5p −8 miR-520c-3p miR-502-3p miR-548g-3p miR-615-3p miR-653-5p miR-615-5p −12 miR-660-5p −12 −8 −4 0 4 8 12 miR-99a-5p

Man7 Log2 Fold Change

Figure 3.10: Stage-wise differential expression of miRNAs during DDP (A) Table showing number of differentially regulated miRNAs for each stage-wise comparison during the DDP (FDR<0.05). (B) X-Y scatter of all miRNAs found to be differentially regulated between stages 0 and 3 during Hues1 and Man7 directed chondrogenesis (FDR<0.05), with their log2(fold change) between stages 0 and 3 of Man7 chondrogenesis (x- axis) plotted against their log2(fold change) during Hues1 chondrogenesis (y-axis). (C) List of all differentially downregulated (left) and upregulated (right) found in both Man7 and Hues1. MicroRNAs highlighted in red have been associated with pluripotency, those in blue have been associated with chondrogenesis and miRNAs highlighted in orange are transcribed from Hox genes.

Chapter 3 93 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Hues1 A 0 vs. 2 C 0 vs. 3

-6 -3 0 3 6

Log2 Fold Change

B 2 vs. 3

-6 -3 0 3 6 -12 -9 -6 -3 0 3 6 9 12

Log2 Fold Change Log2 Fold Change

Figure 3.11: Differentially expressed miRNAs between each stage of directed chondrogenesis of Hues1. Stage wise comparisons for differential expression analysis of miRNAs during chondrogenesis of Hues1. Shows comparisons between stage 0 and 2 (A), stage 2 and 3 (B) and between stage 0 and 3 (C). MicroRNAs highlighted in red have been associated with pluripotency, those in blue have been associated with chondrogenesis and miRNAs highlighted in orange are transcribed from Hox genes.

Chapter 3 94 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Man7 0 vs. 2 2 vs. 3 A miR−326 miR−196b−3p B miR−135b−3p miR−519a−3p miR−10a−3p miR−138−1−3p miR−548g−3p miR−10a−5p miR−1298−5p miR−338−5p miR−1272 miR−615−3p miR−4433−5p miR−490−3p miR−302b−5p miR−1283 miR−196a−3p miR−448 miR−4787−3p miR−10b−5p miR−141−3p miR−448 miR−490−5p miR−4792 miR−143−3p miR−203a miR−520f−5p miR−615−5p miR−7975 miR−1264 miR−203b−3p miR−10b−3p miR−504−5p miR−524−5p miR−211−5p miR−216a−3p miR−92b−5p miR−4804−5p miR−517c−3p miR−302b−3p miR−196b−5p miR−518a−3p miR−4731−3p miR−526b−5p miR−522−3p miR−1972 let−7f−1−3p miR−1250−5p miR−524−5p miR−143−5p miR−520a−5p miR−5008−3p miR−146b−5p miR−1283 miR−519c−5p miR−208b−3p miR−518c−5p miR−100−5p miR−518b miR−302c−3p miR−483−3p miR−520a−3p miR−302e miR−4423−5p miR−1269b miR−187−5p miR−122−5p miR−518a−5p miR−3960 miR−483−5p miR−519a−3p miR−548ad miR−145−5p miR−409−5p miR−302d−3p miR−4474−3p miR−520a−5p miR−125b−1−3p miR−1911−5p miR−302a−5p miR−199a−3p miR−520g−3p miR−3659 miR−6500−3p let−7e−5p miR−516b−5p miR−1298−3p miR−135a−3p miR−2113 miR−1263 miR−519d−5p miR−125b−5p miR−517−5p miR−99a−5p miR−520f−5p miR−152−3p miR−518a−3p miR−520d−3p miR−517c−3p miR−152−5p miR−518f−5p miR−3605−5p miR−519c−5p miR−3617−5p miR−367−3p miR−181a−3p miR−302d−5p miR−1298−5p miR−6735−5p miR−519c−3p miR−196a−5p miR−517a−3p miR−525−3p miR−99b−5p miR−518c−3p miR−518f−3p miR−29b−3p miR−516a−5p miR−518d−3p miR−362−3p miR−338−3p miR−515−3p miR−100−3p miR−372−5p miR−516b−5p miR−944 miR−302e miR−92a−2−5p miR−4473 miR−1323 miR−146b−3p miR−1912 miR−4492 miR−585−5p miR−302c−5p miR−150−5p miR−29a−3p miR−519c−3p miR−488−3p miR−512−5p miR−22−3p miR−3617−5p miR−24−3p miR−520e miR−124−5p miR−592 miR−519d−3p miR−1323 miR−512−3p miR−181b−3p miR−517−5p miR−520a−3p miR−203a miR−660−3p miR−518f−3p miR−524−3p miR−3200−3p miR−526b−3p miR−574−3p miR−515−3p miR−181b−5p miR−519b−3p miR−519b−3p miR−518b miR−660−5p miR−515−5p miR−181a−5p miR−520c−3p miR−517a−3p miR−642a−5p miR−515−5p miR−363−5p miR−27b−3p miR−5583−5p miR−125a−5p miR−302b−3p miR−450b−5p miR−520d−3p miR−215−5p miR−367−3p miR−518a−5p miR−362−5p miR−525−5p miR−518e−3p miR−4662a−5p miR−378f miR−3126−5p miR−524−3p miR−520f−3p miR−542−5p miR−4708−3p miR−520g−3p miR−501−3p miR−196a−5p miR−373−5p miR−7706 miR−526b−5p miR−1246 miR−23b−3p miR−512−3p miR−302b−5p miR−574−5p miR−526a miR−520e miR−99b−3p miR−523−3p miR−365a−3p miR−302a−3p miR−302c−5p miR−302d−5p miR−188−5p miR−302a−5p miR−450a−5p miR−4508 miR−125b−2−3p miR−302c−3p miR−500a−3p miR−520d−5p miR−302d−3p miR−4652−3p miR−502−3p miR−767−3p miR−766−3p miR−519d−3p miR−532−5p miR−519e−5p miR−518e−3p miR−520c−3p miR−194−5p miR−504−3p miR−190b miR−1911−3p miR−551b−3p miR−498 miR−324−5p miR−205−5p miR−367−5p miR−500a−5p miR−302f -6 -3 0 3 6 −12 −9 −6 −3 3 6 9 − 12 − -99 −-66 −-33 0 33 66 99 12 Log2 Fold Change Log2 Fold Change

Figure 3.12: Differentially expressed miRNAs between each stage of Man7 directed chondrogenesis. Stage wise comparisons for differential expression analysis of miRNAs during chondrogenesis in Man7 between stage 0 and 2 (A) and between stage 2 and 3 (B). MicroRNAs highlighted in red have been associated with pluripotency, those in blue have been associated with chondrogenesis and miRNAs highlighted in orange are transcribed from Hox genes.

Chapter 3 95 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Man7 0 vs. 3 miR−25−5p miR−10b−3p miR−135b−3p miR−615−3p miR−1972 miR−196b−3p miR−1269b miR−326 miR−10a−5p miR−184 miR−196a−3p miR−3171 miR−10b−5p miR−4735−5p miR−490−5p miR−548ad miR−10a−3p miR−200b−3p miR−196b−5p miR−429 miR−490−3p miR−615−5p miR−3145−5p miR−196a−5p miR−3116 miR−6888−3p miR−1290 miR−99a−5p miR−138−1−3p miR−6500−3p miR−1243 miR−216a−3p miR−942−3p miR−3126−3p miR−146b−3p miR−187−5p miR−216a−5p miR−363−5p miR−450b−5p miR−4792 miR−146b−5p miR−96−5p let−7e−5p miR−548g−3p miR−143−3p miR−182−5p miR−143−5p miR−200a−3p miR−542−5p miR−199a−5p miR−885−5p miR−7975 miR−7704 miR−1250−5p miR−653−3p miR−100−5p miR−20b−3p miR−145−5p miR−150−5p miR−199a−3p miR−5008−3p miR−6728−5p miR−6881−3p miR−135a−3p miR−208b−3p miR−4699−3p miR−450a−5p miR−548ah−5p miR−338−5p miR−1263 miR−1224−3p miR−203b−3p miR−3613−3p miR−204−5p miR−181a−3p miR−2113 miR−4423−5p miR−125b−5p miR−3934−5p miR−542−3p miR−653−5p miR−125b−1−3p miR−200c−3p miR−152−3p miR−489−3p miR−181b−3p miR−200a−5p miR−338−3p miR−1246 miR−215−5p miR−187−3p miR−214−5p miR−4662a−5p miR−141−3p miR−5696 miR−92a−2−5p miR−214−3p miR−200b−5p miR−424−5p miR−211−5p let−7f−2−3p miR−124−5p miR−218−5p miR−373−5p let−7e−3p miR−1272 miR−3613−5p miR−6735−5p miR−520f−3p miR−362−3p miR−141−5p miR−483−3p miR−205−5p miR−99b−5p miR−19b−2−5p miR−450a−2−3p miR−3937 miR−125b−2−3p miR−4433−5p miR−181a−5p miR−6516−3p miR−124−3p miR−301b miR−378h miR−145−3p miR−4668−5p miR−5006−3p miR−1264 miR−6513−3p miR−4652−3p miR−100−3p miR−519e−3p miR−3681−5p miR−219a−2−3p miR−383−5p miR−152−5p miR−1911−5p miR−449b−5p miR−519e−5p miR−2114−5p miR−1298−3p miR−503−5p miR−371a−3p miR−4474−3p miR−3918 miR−642a−3p miR−205−3p miR−6895−3p miR−525−3p let−7f−5p miR−99a−3p miR−516a−5p miR−449c−5p miR−522−3p miR−660−3p miR−448 miR−7706 miR−1912 miR−3605−5p miR−3659 miR−324−5p miR−519a−3p miR−941 miR−373−3p miR−1301−3p miR−6818−5p miR−1298−5p miR−181b−5p miR−1283 miR−424−3p miR−372−3p miR−126−5p miR−512−5p miR−4473 miR−518d−3p miR−3127−5p miR−524−5p miR−876−5p miR−503−3p miR−520f−5p miR−1468−5p miR−372−5p let−7g−5p miR−519d−5p miR−548a−3p miR−518c−3p miR−15a−5p miR−371a−5p miR−126−3p miR−498 miR−574−3p miR−520a−5p miR−1287−5p miR−3688−3p miR−518c−5p miR−125a−5p miR−517c−3p miR−449a miR−518a−3p miR−181a−2−3p miR−519c−5p miR−362−5p miR−525−5p let−7a−5p miR−302e miR−3065−5p miR−1911−3p miR−199b−5p miR−27b−3p miR−526b−3p miR−194−5p miR−526a miR−1226−3p miR−516b−5p miR−26b−5p miR−518f−5p miR−652−3p miR−302b−3p miR−642a−5p miR−302a−3p miR−190b miR−181c−3p miR−520a−3p miR−301a−3p miR−519c−3p miR−147b miR−302b−5p miR−224−5p miR−518b miR−346 miR−517−5p miR−6784−3p miR−526b−5p miR−181d−5p miR−520d−5p miR−99b−3p miR−660−5p miR−1323 miR−3139 miR−518a−5p miR−23b−3p miR−517a−3p miR−501−3p miR−518f−3p miR−3661 miR−520d−3p miR−873−5p miR−367−3p miR−873−3p miR−515−3p miR−192−5p miR−500a−3p miR−520g−3p miR−454−3p miR−302c−3p miR−16−5p miR−523−3p miR−188−3p miR−302a−5p miR−502−3p miR−302d−3p miR−107 miR−519b−3p miR−629−5p miR−367−5p miR−148b−3p miR−1228−3p miR−302d−5p miR−766−3p miR−524−3p miR−6511a−3p miR−512−3p miR−328−3p miR−515−5p miR−589−5p miR−520e miR−574−5p miR−302c−5p miR−345−5p miR−500a−5p miR−302f miR−1180−3p miR−519d−3p miR−342−5p miR−518e−3p miR−361−5p miR−520c−3p miR−30d−5p −12 −9 −6 −3 0 5 10 -12 -9 logFC -6 -3 0 3 6 logFC 9 12

Log2 Fold Change

Figure 3.13: Differentially expressed miRNAs between stage 0 and 3 of Man7 directed chondrogenesis. Stage wise comparisons for differential expression analysis of miRNAs during chondrogenesis in Man7 between stages 0 and 3. MicroRNAs highlighted in red have been associated with pluripotency, those in blue have been associated with chondrogenesis and miRNAs highlighted in orange are transcribed from Hox genes.

Chapter 3 96 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

3.3 Discussion

RNA-sequencing has previously been used to uncover whole transcriptome and miRome changes during differentiation of stem cells to aid our understanding of these processes (Wu et al. 2010a; Ja¨ager¨ et al. 2012). Here we utilised RNA-sequencing to reveal transcriptome and miRome changes during chondrogenesis of two hESC lines, Man7 and Hues1, using the Directed Differentiation protocol developed in our lab (Oldershaw et al. 2010). This revealed large changes in the expression of several miRNAs during hESC-directed chondrogenesis including; upregulation of miRNAs transcribed from the four Hox complexes, known cartilage associated miRNAs and the downregulation of several pluripotency associated miRNAs. Notably, around half of all the sequencing reads for hESCs and hESC-derived chondroprogenitors were accounted for by only a few miRNAs, with the majority of these being transcribed as clusters. Overall miRome and transcriptome analysis revealed the two hESC lines exhibited slightly different miRome and transcriptome profiles during chondrogenesis, with Man7 displaying larger changes in miRNA and mRNA expression as it progressed through the DDP. These findings provide an improved understanding of miRNA regulation during hESC-chondrogenesis which may enable us to improve the current chondrogenesis differentiation protocol.

3.3.1 Small RNA-seq technical variation

It is important to assess the quality of sequencing before further downstream analysis can take place to verify that technical variation is not affecting the biological effects seen. The RNA-seq libraries generated in 2012 and the libraries generated in 2015 both showed high quality of sequencing reads as shown by high Phred scores and good sequencing depth with an average of 2.29x107 raw reads per sample. After mapping to miRBase, samples sequenced at University of Manchester in 2015 showed over a 4-fold higher number of reads mapping to mature miRNAs than those sequenced by GATC Biotech in 2012. Examination of processed reads from 2012 samples shows libraries contain an 22nt overrepresented sequence, ’GAATTCCACCACGTTCCCGTGG’, this is the same sequence of the stop oligo used in the small RNA library preparation. The incorporation of stop oligo sequence in the 2012 batch may be due to poor RNA quality or too low a concentration. One reason for improved mapping in 2015 batch samples may be due to the the incorporation of a pre-sequencing quality assessment check by the University of Manchester Genomic Technology Core Facility (GTCF). Samples were first quantified by Qubit, then quality was assessed by size distribution on a Tapestation and finally qPCR was performed to assess correct ligation of adaptors to miRNAs. RNA of poor quality would have been identified by the TapeStation which quantifies the RNA quality of

Chapter 3 97 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells samples by analysing its size distribution (Schroeder et al. 2006). However, if the incorporation of stop oligo sequences into the 2012 batch samples was not caused by poor RNA quality, it may be best to avoid the use of the oligo altogether. Another Illumina small RNA library preparation kit is available from New England Biotech (NEB), which uses heat inactivation of the T4 ligase to terminate the reaction after 3’ adaptor ligation. This could be implemented in the Illumina small RNA preparation kit or the NEB kit could be used, as to avoid sequencing of the stop oligo leading to improve sequencing depth.

3.3.2 Cell line variation

As previously reported, different hESC lines have been shown to possess unique gene expression signatures (Abeyta et al. 2004) along with differences in their differentiation propensities (Osafune et al. 2008). Similarly, we find differences between the two hESC lines, Hues1 and Man7, in their miRome at pluripotency and during directed chondrogenesis. Hierarchical clustering of top differentially regulated miRNAs during chondrogenesis showed the miRome of pluripotent Hues1 and Man7 cells separating out, with Hues1 clustered with stage 1 samples. The same effect was seen in the PCA for the miRome. Interestingly, this separation was not observed in the trancriptome. Both the hierarchical clustering of top differentially regulated mRNAs and the PCA showed all stage 0 transcriptome libraries clustering together irrespective of cell line. This suggests that the two different cell lines have unique miRome profiles but not a unique transcriptome profile. The two cell lines may still have unique genetic signatures that are masked by other variations. These different miRome profiles of the hESC lines will lead to differences in protein expression despite them having similar transcriptomes due to the posttranscriptional regulation of the miRNAs, this may account for differences in phenotypes observed. The two cell lines also displayed differences when undergoing differentiation during chondrogenesis. Spearman’s correlation analysis showed the Man7 line displayed a greater change in variation as it progressed through the protocol compared with Hues1. Also Man7 was shown to have more differentially expressed miRNAs for all stage comparisons of the DDP and had a higher percentage of upregulated miRNAs during chondrogenesis being associated with cartilage development. These findings seem to suggest that Man7 undergoes differentiation more easily or completely when compared to Hues1. This may be due to Hues1 being more culture adapted and less responsive to differentiation cues. The higher upregulation of cartilage related miRNAs in Man7 suggests it may be more predisposed to undergo chondrogenesis than Hues1. However, this could be an due to Man7 being more predisposed to differentiate into any lineage compared to Hues1. To validate if Man7 is more predisposed to undergo chondrogenesis

Chapter 3 98 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells compared with other differentiation pathways, further lineage differentiation will have to be performed. Both lines have been shown by the Kimber lab to successfully differentiate into definitive endoderm and neurons along with forming embryonic bodies with all three germ layers present suggesting neither hESC line has a severe restriction in differentiation capability. These differences in hESC lines may be due to differences in the genetic backgrounds of the cell lines as well as differences in hESC derivation.

3.3.3 Highest expressed miRNAs during hESC directed chondrogenesis

ESC miRNAs

As expected, the hESC-specific miRNAs from the the miR-302 cluster are the highest expressed miRNA cluster in hESCs accounting for 18% of all miRNAs in hESCs. The miR-302 cluster was first identified in hESC by cDNA cloning (Suh et al. 2004). Since then, improved technologies have allowed the whole miRome of hESCs to be profiled. MicroRNA microarray profiling of hESCs and iPSCs identified miR-302 and miR-17-92 miRNA clusters as a signature group of miRNAs distinguishing PSCs from fibroblasts (Wilson et al. 2009). We found similar high expression of miR-302 and miR-17-92 cluster in the two hESC lines examined in this study. However, while previous research found loss of these clusters in fibroblasts we observed high expression of the miR-17-92 cluster in the chondroprogenitors. The miR-17-92 cluster has been implicated in many cancers due to its high level of expression in these proliferating cells (Olive et al. 2010). This suggests that the miR-17-92 cluster are not solely pluripotency related miRNAs but associated with proliferation. Wilson et al. also observed large upregulation of miR-10a in fibroblasts compared with PSCs suggesting it is a miRNA associated with differentiated cells. We observed the same effect in our differentiation protocol, with miR-10a-5p being the highest expressed miRNA at the end of the differentiation protocol. Another microarray study comparing the miRome of 3 different hESC lines to several differentiated cell types found miR-302 to be upregulated in hESCs compared with differentiated cells along with a cluster of miRNAs on chromosome 19 (CM19C) (Ren et al. 2009). We also found large downregulation of this CM19C during differentiation. However, it is expressed at very low levels in hESCs accounting for less than 0.01% of total mapped reads, suggesting it may have a very limited function in hESCs. Although many studies have evaluated the functional properties of the miR-302 cluster (Card et al. 2008;Subramanyam et al. 2011) very little is known about the functional properties of CM19C miRNAs in PSCs. Ren et al. 2009 noted that members of the CM19C had similar sequences to miR-302 cluster sharing a consensus seed sequence ’AAGUGC’ and therefore may have similar targets. This has yet to be experimentally validated.

Chapter 3 99 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Chondroprogenitor miRNAs

Comparison of the top 30 expressed miRNAs in hESC-derived chondroprogenitors with the top 30 expressed miRNAs expressed in developing human cartilage (McAlinden et al. 2013) revealed seven miRNAs were found highly expressed in both the hESC-chondroprogenitors and developing cartilage (miR-92a-3p, miR-26a-5p, miR-191-5p, miR-99b-5p, miR-27b-3p, miR-100-5p and miR-30c-5p). Further examination of the top 30 expressed miRNAs in hESC-derived chondroprogenitors revealed many of them have been functionally characterised to regulate chondrogenesis including: miR-26a which targets hypertrophic related genes in chondrocytes (Etich et al. 2015), miR-30a which is a positive regulator of chondrogenesis in MSCs (Tian et al. 2016), miR-181a (Sumiyoshi et al. 2013), miR-16 (Li et al. 2015b), miR-143 (Hong and Reddi 2013) and miR-222 (Song et al. 2015). This evidence highly suggests the miRome of the hESC-derived chondroprogenitors resembles known chondrocyte miRomes and contains chondrogenic regulators. However miR-140-5p which has been reported to be the most upregulated and functionally active miRNA during MSC chondrogenesis (Barter et al. 2015) and is the highest expressed miRNA in precursor and differentiated chondrocytes of developing human cartilage (McAlinden et al. 2013) was not highly expressed in the hESC-derived chondroprogenitors. This may be due to the immaturity of the hESC-derived chondroprogenitors as miR-140 may be a marker of chondrocyte maturation. Evaluation of the 25 miRNAs which were upregulated during chondrogenesis of Man7 and Hues1, revealed only one miRNA (miR-152-3p) which was also upregulated during chondrogenesis of hBM-MSCs (Barter et al. 2015). However five of these hESC-chondrogenic miRNAs (miR-100-5p, miR-502, miR-660-5p, miR-10b-3p and miR-196b-5p) were found to be significantly upregulated in precursor chondrocytes compared to both hypertrophic and differentiated chondrocytes of developing human cartilage (McAlinden et al. 2013). Suggesting the miRome of the hESC-derived chondroprogenitors more closely resembles the miRome of developing chondrocytes than that of MSC-derived mature chondrocytes. Further analysis of all the miRNAs significantly upregulated during Man7 chondrogenesis revealed 28 miRNAs which were also reported to be differentially expressed between different distinct regions of cartilage development (Figure 3.14A) (McAlinden et al. 2013), these include: ten miRNAs differentially upregulated in precursor chondrocytes compared with hypertrophic and differentiated chondrocytes (miR-146b-5p, miR-199a-3p, miR-100-5p, miR-10b-3p, miR-99b-5p, miR-99b-3p, miR-660-5p, miR-224-5p, miR-454-3p and miR-30d-5p), twelve miRNAs differentially upregulated in precursor chondrocytes compared with hypertrophic chondrocytes (miR-1180-3p,

Chapter 3 100 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells miR-125b-5p, miR-214-3p, miR-483-3p, miR-301b, miR-125a-5p, miR-199b-5p, miR-27b-3p, miR-26b-5p, miR-16-5p, miR-502-3p and miR-1180-3p), four miRNAs upregulated in differentiated chondrocytes compared with hypertrophic chondrocytes (miR-542, miR-483-3p, miR-660 and miR-125a-5p) and only two miRNAs upregulated in hypertrophic chondrocytes compared with precursor chondrocytes (miR-126-3p and miR-181a-2). A similar pattern was also observed for the miRNAs upregulated during chondrogenesis of Hues1 (Figure 3.14B) with nine of the miRNAs upregulated during Hues1 chondrogenesis also reported to be differentially upregulated in precursor chondrocytes compared with hypertrophic and differentiated chondrocytes (miR-10b-3p, miR-100-5p, miR-196b-5p, miR-660-5p, miR-532-5p, miR-532-3p, miR-502-3p, miR-335-3p and miR-335-5p) and two miRNAs upregulated in precursor chondrocytes compared with hypertrophic chondrocytes (miR-483-3p and miR-199b-5p)(McAlinden et al. 2013). This highly suggests the miRNA expression of the chondroprogenitors produced from hESC-chondrogenesis more closely resembles the miRNA expression of precursor chondrocytes found at the most proximal end of the developing human tibia compared with more differentiated chondrocytes located further down the developing limb termed differentiated chondrocytes and terminally differentiated hypertrophic chondrocytes.

A Man7 B Hues1

24 miRNAs ● 11 miRNAs Upregulated in Upregulated in 4 Stage 3 and PC 4 Stage 3 and PC ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Fold Change Fold Change 2 2 0 0

● ● ●

● HYP vs. PC Log HYP vs. PC Log

−4 ● −4

−4 0 4 8 −4 0 4 8

Man7 0 vs. 3 Log2 Fold Change Hues1 0 vs. 3 Log2 Fold Change

Figure 3.14: Comparison of developing chondrocytes miRome with hESC directed chondrogenesis.X-Y scatter graphs of differentially regulated miRNAs between hypertrophic and precurosor chondrocytes (McAlinden et al. 2013) and those differentially regulated between stage 0 and 3 of chondrogenesis of Man7 (A) or Hues1 (B). PC, precursor chondrocyte; HYP, hypertrophic chondrocyte.

3.3.4 Summary

This chapter investigates changes in the miRome during hESC directed chondrogenesis with the aim of discovering novel regulators of cartilage development. We find the two

Chapter 3 101 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells hESC lines, Man7 and Hues1, display unique miRome signatures. We also show that the highest expressed miRNAs in ESCs are comparable to what has been observed in previous profiling of PSCs with the ESC-specific miR-302 cluster being the highest expressed miRNA cluster in hESCs profiled. Despite many cartilage related miRNAs being highly expressed in the chondroprogenitors the most well researched cartilage miRNA, miR-140, is not highly expressed in the chondroprogenitors. This may be because the chondroprogenitors produced are immature. This immaturity may be partly due to expression of miRNAs which limit the maturation rate of the hESCs. Many miRNAs regulated during chondrogenesis have been highlighted in this chapter as potential novel regulators of chondrogenesis. Further experimental work is necessary to validate these miRNAs. The list of miRNAs that could be potential regulators can be initially narrowed by using target prediction algorithms along with other bioinformatic tools available, as to experimentally validate only the most promising of candidates. The work presented in the next chapter aims to do this.

Chapter 3 102 Chapter 4

Results II - Integrated miRomics and Transcriptomics analysis

4.1 Introduction and Aims

This chapter aims to further elucidate and correlate changes in the miRome and transcriptome during hESC-directed chondrogenesis by using network analysis. Networks were generated with genes and miRNAs expressed during hESC-directed chondrogenesis and using the following interactions; co-expression, protein-protein interactions and predicted miRNA-target interaction (Figure 4.1A). In this chapter two separate approaches were used. Firstly, a combinatorial network analysis approach, using co-expression and gene ontology enrichment analysis followed by protein-protein interaction analysis of identified clusters of genes (Figure 4.1B). Secondly, miRNA-mRNA target interaction analysis that incorporates; correlation data, target-prediction algorithms and differential expression analysis (Figure 4.1C). By using this approach we hope to identify; i) clusters of genes/miRNAs associated with a biological function, ii) potential novel genes/miRNAs associated with biological function identified, iii) co-regulated genes/miRNAs, and iv) potential miRNA-mRNA interactions regulating hESC-chondrogenesis.

103 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

mRNA and miRNA A B Expression data Co-expression Analysis Protein Protein Interaction (Pearson’s Correlation) miRNA Target Interaction Co-expression (Pearson's correlation) Clusters of co-expressed miRNAs and genes

mRNA-seq miRNA-seq Protein-Protein Network Analysis (BioGRID and ModuLand)

Highly connected gene from cluster Network Analysis

C mRNA and miRNA Differential expression

mRNA and miRNA (FC>1.5 and FDR<0.05)

miRNA-mRNA miRNA-mRNA Correlation Target Prediction

Negative Pearson’s Predicted by TargetScan correlations and microCosm miRNA-mRNA Network

Figure 4.1: Schematic of approach used to integrate miRome and transcriptome of hESC-directed chondrogenesis. (A) Workflow of all types of interactions used during network analysis of Hues1 and Man7 hESC-directed chondrogenesis. (B) Workflow of combinatorial network analysis approach. Co-expression analysis is first performed on expression data to identify clusters of co-expressed genes and miRNAs, next protein- protein interaction analysis of each is performed to identify potential regulators of each cluster. (C) Workflow used for miRNA-mRNA target interaction network analysis. First differentially expressed miRNAs and genes were identified during Hues1 and Man7 hESC-directed chondrogenesis. Networks were generated using Pearson’s correlations for each miRNA and mRNA pair and target prediction information using target prediction databases TargetScan and microCosm databases.

4.2 Results

4.2.1 Correlation Analysis

To identify miRNAs and protein coding mRNAs that play novel roles during chondrogenic differentiation in the RNA-seq data we employed a co-expression strategy on the assumption that genes with similar expression patterns to previously identified/known cartilage genes may be either: (i) regulated by these cartilage genes, (ii) regulators of these genes or (iii) regulated by a similar mechanism. Co-expression networks have been shown to be useful for describing pairwise relationships among gene transcripts and can identify modules of genes with similar functions (summarised in Section 1.6.4). Here we

Chapter 4 104 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells performed a Pearson’s correlation analysis using BioLayout (Theocharidis et al. 2009) to identify gene and miRNA clusters with similar expression patterns during hESC-directed chondrogenesis. Six clusters of genes and miRNAs with similar expression patterns were generated (Figure 4.2A). Expression pattern for each gene/miRNA cluster are shown in Figure 4.2C and list of all genes and miRNAs found in each cluster is given in the Appendix (Table A.3 and Table A.3). For each cluster, Gene Ontology (GO) enrichment analysis was performed to determine whether genes in the same cluster had a similar function. This revealed that four of the six clusters contained a significant number of genes associated with a GO terms (Figure 4.2B). Cluster 1 contained genes down-regulated during the DDP (Figure 4.2C). This cluster was very mixed and was not significantly enriched for any particular GO terms, however this may be due to the absence of a number of GO annotations. Although the strong reduction in expression of cluster 1 members during differentiation may suggest novel pluripotency associated genes. However although gene ontology analysis showed that cluster 1 was not enriched with pluripotency related genes, it was enriched with pluripotency associated miRNAs. Of the 48 miRNAs in cluster 1, 28 are well known pluripotency associated miRNAs. These include a large cluster of miRNAs on chromosome 19 (CM19C) and miR-302a-5p (Figure 4.3A-B). Cluster 2 was significantly enriched with genes belonging to the gene ontology term ’primitive streak formation’ (Bonferri corrected p-value=0.000435; Figure 4.2B). RNA-seq expression analysis of these genes during directed-chondrogenesis of hESCs shows they are downregulated at stage 2 of the protocol and remain at low expression until the end of the protocol (Figure 4.2C). Cluster 2 also contained several miRNAs from the miR-200 family (miR-200a/b/c, miR-141 and miR-426) and miR-371-3 cluster (Figure 4.2C-D). Gene Ontology (GO) enrichment analysis identified that cluster 4 contained a significant number of genes associated with the GO term ‘extracellular matrix (ECM) organization’ (p= 6.22x10-22) and that clusters 5 contained a significant number of genes associated with the GO term ‘embryonic limb morphogenesis’ (p=8.83x10-6). Suggesting cluster 4 and 5 are both of potential interest in cartilage development and require further investigation. Clusters 4 and 5 both showed slightly different expression profiles during hESC-directed chondrogenesis in the two hESC lines. Cluster 4 genes and miRNAs were upregulated between stages 0 and 2, and then showed slight downregulation between stages 2 and 3 during directed chondrogenesis of the hESC line Man7. Conversely during directed chondrogenesis of Hues1, cluster 4 genes and miRNAs showed constant expression between stages 0 and 2 and were slightly upregulated between stage 2 and 3 (Figure 4.2C panel 4 and Figure 4.3F). Similarly, cluster 5 genes and miRNAs also showed earlier upregulation during the directed chondrogenesis of the Man7 hESC line

Chapter 4 105 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells compared with Hues1 (Figure 4.2C panel 5 and Figure 4.3G). The average read counts of genes and miRNAs in both clusters were higher in Man7 than Hues1 in all stages of directed chondrogenesis (Figure 4.2C). The earlier upregulation and higher expression of cartilage related genes during Man7-directed chondrogenesis compared with Hues1 suggests that Man7 is more predisposed to undergo chondrogenesis. The miRNAs contained within these clusters may also have a role in some of the enriched GO terms. For example the miR-200 family and miR-371-3 cluster of miRNAs are co-expressed with ’primitive streak’ related genes during hESC-directed chondrogenesis and therefore may have a similar function. Similarly miR-22-3p and miR-143-3p may have a role in ECM organisation and miRNAs miR-181a-2-3p and miR-99b-3p may be involved in embryonic limb morphogenesis. In summary co-expression analysis of miRNA and mRNA expression data during hESC-directed chondrogenesis has identified several clusters containing highly correlated genes and miRNAs. Gene ontology analysis identified two of these clusters were enriched with cartilage-related genes and therefore should be investigated further. MicroRNAs co-expressed in these clusters may also have a role in regulating chondrogenesis. For the remainder of this thesis, reference cluster 4 and 5 will be termed ’ECM cluster’ and ’limb development cluster’, respectively.

Chapter 4 106 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Stage of Highest Expression P value A Cluster 1 Stage 0 B Cluster GO Term (Bonferri Stage 2 corrected) Stage 3 1 N/A miRNA mRNA primitive streak formation (GO:0090009) 4.35E-04 Cluster 2 somite rostral/caudal axis specification (GO:0032525) 2.64E-02 signal transduction involved in regulation of gene expression 4.47E-03 (GO:0023019) gastrulation with mouth forming second (GO:0001702) 1.91E-02 2 embryonic axis specification (GO:0000578) 4.30E-02 anterior/posterior axis specification (GO:0009948) 4.36E-03 Cluster 5 embryonic pattern specification (GO:0009880) 1.18E-02 somitogenesis (GO:0001756) 1.41E-02 somite development (GO:0061053) 3.35E-02 gastrulation (GO:0007369) 4.89E-04 neuron fate specification (GO:0048665) 1.31E-07 Cluster 4 neuron fate commitment (GO:0048663) 2.61E-09 Cluster 3 spinal cord motor neuron differentiation (GO:0021522) 8.86E-03 3 cell fate specification (GO:0001708) 4.01E-05 cell differentiation in spinal cord (GO:0021515) 1.97E-03 ventral spinal cord development (GO:0021517) 7.25E-03 Cluster 6 cell adhesion mediated by integrin (GO:0033627) 4.73E-03 protein activation cascade (GO:0072376) 1.01E-02 regulation of acute inflammatory response (GO:0002673) 6.70E-04 C collagen catabolic process (GO:0030574) 1.99E-04 extracellular matrix disassembly (GO:0022617) 1.82E-07 1 2 3 multicellular organismal catabolic process (GO:0044243) 4.56E-04 Man7 collagen metabolic process (GO:0032963) 7.27E-04 Hues1 multicellular organismal macromolecule metabolic process 4 1.51E-03 (GO:0044259) multicellular organismal metabolic process (GO:0044236) 2.27E-03 extracellular matrix organization (GO:0030198) 6.22E-22 extracellular structure organization (GO:0043062) 7.11E-22 response to amino acid (GO:0043200) 1.55E-02 glycosaminoglycan biosynthetic process (GO:0006024) 1.72E-02 Average read counts aminoglycan biosynthetic process (GO:0006023) 1.92E-02 4 5 6 receptor-mediated endocytosis (GO:0006898) 5.87E-04 embryonic limb morphogenesis (GO:0030326) 8.83E-06 embryonic appendage morphogenesis (GO:0035113) 8.83E-06 limb morphogenesis (GO:0035108) 2.63E-05 appendage morphogenesis (GO:0035107) 2.63E-05 5 limb development (GO:0060173) 5.87E-05 appendage development (GO:0048736) 5.87E-05 embryonic morphogenesis (GO:0048598) 8.85E-04 Average read counts regulation of neuron differentiation (GO:0045664) 1.69E-02 regulation of nervous system development (GO:0051960) 3.18E-02 Stage 0 Stage 2 Stage 3 Stage 0 Stage 2 Stage 3 Stage 0 Stage 2 Stage 3 6 N/A

Figure 4.2: Pearson’s correlation analysis of all genes expressed during Hues1 and Man7 hESC- directed chondrogenesis (A) Top clusters of miRNAs and mRNAs using BioLayout with a Pearson’s correlation >0.98. Each node represents a gene or miRNA with connecting lines representing their correlation with other genes/miRNAs. Nodes have been highlighted based of their stage of highest expression with values being averaged over cell lines and replicates. (B) Expression profiles of clusters 1-6 from BioLayout. Violin plots of the average read count of each gene/miRNA for all biological replicates (y-axis) in each stage (x-axis). (C) Summary of Gene Ontology analysis of gene clusters from BioLayout. Bonferri corrected p-values.

Chapter 4 107 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

CM19C Cluster 1 miRNAs A B (exc. CM19C) 2000 100000 Stage 0 Stage 0 Stage 1 Stage 1 80000 Stage 2 1500 Stage 2 miR-512-3p miR-302a-5p Stage 3 Stage 3 60000 1000 40000 Read count Read count 500 20000 miR-1246 0 0

Hues1 Man7 Hues1 Man7 C miR-200 family D miR-371-3 cluster E Other Cluster 2 miRNAs 1500 20000 30 Stage 0 miR-367-5p Stage 0 Stage 0 miR-371a-5p miR-200c-3p Stage 1 Stage 1 Stage 1 Stage 2 Stage 2 15000 Stage 2 1000 20 Stage 3 Stage 3 Stage 3 miR-429 10000

500 10 miR-519b-3p Read count Read count 5000 Read count

0 0 0

Hues1 Man7 Hues1 Man7 Hues1 Man7

F Cluster 4 miRNAs G Cluster 5 miRNAs 150000 2500 Stage 0 miR-22-3p Stage 0 miR-181a-2-3p Stage 1 Stage 1 Stage 2 2000 Stage 2 100000 Stage 3 Stage 3 1500

miR-143-3p 1000 miR-181a-2-3p 50000 Read count Read count miR-22-3p miR-99b-3p 500

0 0

Hues1 Man7 Hues1 Man7

Figure 4.3: Expression of miRNAs from co-expression clusters during Hues1 and Man7 hESC-directed chondrogenesis. Expression of chromosome 19 cluster (CM19C) miRNAs found in cluster 1 (A) all other miRNAs in cluster 1 (B). Expression of miR-200 family miRNAs found in cluster 2 (C), miR-371-3 cluster miRNAs found in cluster 2 (D) and all other miRNAs in cluster 2 (E). Expression of miRNAs in cluster 4 (F) and cluster 5 (G).

Chapter 4 108 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

4.2.2 Protein Network Analysis

To further investigate the relationship between genes in the ’ECM’ and ’limb development’ clusters, protein interaction networks were generated using BioGrid (Stark et al. 2006), a curated database of protein-protein interactions. As there were no protein-protein interactions between any of the genes in the ’limb development’ cluster, a protein-protein interaction network was generated with genes in the cluster including connecting genes expressed during the DDP (first neighbours). ’ECM’ cluster genes generated a protein-protein interaction network with 232 genes and 121 interactions, 181 of these genes had no secondary interaction with other gene in the cluster (Figure 4.4A). ’Limb development’ cluster genes with their first neighbours generated a network with 244 genes (28 genes from the cluster and 216 neighbouring genes) with 4146 interactions (Figure 4.5A). Using these protein-protein interaction networks ModuLand analysis was performed to identify crucial genes in overlapping networks (Szalay-Beko˝ et al. 2012). ModuLand determines overlapping network modules and determines meta-genes, key genes in each module bridging overlapping networks. On the assumption that these highly-connected meta-genes are more likely to have functional importance in the network than other network genes, ModuLand analysis was employed to identify potential chondrogenic regulators from the ’ECM’ and ’limb development’ clusters of genes. ModuLand analysis of the ’ECM’ cluster genes identified FN1, FAM46A, COL1A1, CKAP4 and TGM2 as metanodes in the network (Figure 4.4B). Of these genes only FAM46A, FN1 and TGM2 were significantly upregulated during chondrogenesis. Fibronectin 1 (FN1) was the highest expressed gene in stage 3 samples and was significantly upregulated, by 4-fold, during hESC directed chondrogenesis (Figure 4.4C). FAM46A (Family With Sequence Similarity 46 Member A) showed gradual upregulation during hESC-directed chondrogenesis (Figure 4.4D) while TGM2 (Transglutaminase 2) was upregulated between stages 0 and 2 but then downregulated between stages 2 and 3 in Man7, though overall it was upregulated across completed hESC-directed chondrogenic differentiation (Figure 4.4E). The protein-protein network generated for the ’limb development’ cluster genes and their first neighbours was much larger than the ’ECM’ network, as all genes contained interactions whereas the ’ECM’ cluster contained 181 non-connected genes (Figure 4.5A). It is large networks like this where network analysis tools such as ModuLand are most powerful, as they allow unbiased computational analysis of hundreds of nodes down to a few key metanodes. ModuLand analysis identified several highly connected genes from the ’limb development’ network (Figure 4.5B). Of these metanodes identified, only MEIS2 and DCX are ’limb development’ cluster genes while the rest are first neighbours of ’limb

Chapter 4 109 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells development’ cluster genes. Doublecortin (DCX) showed large upregulation in only one of the biological replicates during hESC directed chondrogenesis (Figure 4.5C). MESI2 was gradually upregulated during hESC-directed differentiation (Figure 4.5D). Neighbouring genes may also be of interest as they could be regulating the expression of several ’limb development’ cluster genes. Several of these metanode neighbouring genes are significantly upregulated during hESC-directed chondrogenesis, these include; B3GAT3, LZTR1, CDK6 and APBB1. In summary, large lists of candidate genes to be investigated were narrowed down and prioritised to manageable numbers of candidates by use of protein-protein interaction networks. Using this approach 232 ’ECM’ cluster genes and 244 ’limb development’ cluster genes and their first neighbours were narrowed down to a small networks of 5 and 17 genes respectively. Genes in these networks may be novel regulators of chondrogenesis, for example FAM46A, FN1 and TGM2 may have roles in ECM organisaton and MEIS2, DCX, B3GAT3, LZTR1, CDK6 and APBB1 may be involved in limb development. Further work is required to validate the role of these genes in chondrogenesis.

Chapter 4 110 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

A TXNDC5

LRP10 PTGS2 CFI P4HB TGM2 TGFBR2 C1S C3 TGFBI P4HA2 NUCB1 RCN1 TGFBR3

PDLIM5 FN1 HSPG2 HTRA1 COL4A1 CD93 STOM NID2 COL4A2 VCAM1 FAM46A FBLN2 IGFBP3 FBN1 TBX4 PRELP

CKAP4 LTBP1 COL1A1 ADAM12

DPP10 OSMR SDF4 FKBP10 TNFAIP3 MATN2 FKBP7 COL1A2 SPARC

COL3A1 COL5A1 KCND3 HGF IL6ST FOXF1 ECE1 TRIM8 + 181 non-connected genes ModuLand B C FN1

6 CKAP4 COL1A1 2.0×10 Stage 0 1.5×106 Stage 2 FN1 Stage 3 1.0×106 FAM46A

TGM2 Read count 5.0×105

0.0

Man7 D FAM46A E Hues1 TGM2

4000 40000 Stage 0 Stage 0 3000SYT10 StageCREB3L1 2 RELN F530000 CCL7 Stage 2PLOD1 EHD3 CD55 Stage 3 Stage 3 2000 20000 Read count 1000 Read count 10000 CXCL1 PLOD2 CCL2 TGFBR2 COPZ2 TNFRSF9 DPP10 HGF 0 0

Hues1 Man7 Hues1 Man7

NFATC2 SNCAIP IFIT3 DYNLT3 TDO2 PITX2 LTBR P4HB Figure 4.4: Protein-Protein interaction analysis of cluster 4 genes (A) Protein-protein interaction network of cluster 4 genes generated using curated interactions from BioGrid (Stark et al. 2006). (B) Network of key meta- nodes from overlapping networks in network (A) identified using ModuLand analysis (Szalay-Beko˝ et al. 2012). Expression of meta-nodes during hESC-directed chondrogenesis from RNA-seq data for FNA1 (C), FAM46A (D) ECE1 FOXF1 IL6ST TYMP SDPR and TGM2 (E). PTGS2 TNFAIP3

Chapter 4 111 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

ZNHIT3 PBX3 A PBX4

NUFIP1 CCDC102B HOXB8 OSGIN1 C1orf94 MID2

DCLK1 MEIS2 EN1 ARNT2 PIGLDGCR6 MAB21L2 GNB4 HOXD9 LURAP1L KIFC3 PKNOX1 TRIM25 MEOX1 MEIS3 HOXA9 RAP1GAP UCHL3 NMNAT3 CCDC106 HOXB7PBX2 TRMT10B TRIM23 HOXC8 SORCS1 SLC5A7 SPP1 MEIS1 ZBTB5 DCX SHMT2 PNMA1 CNR1 GNAI1 CALCOCO2NFX1 PDX1 APOE PIAS4 PAWR SPAG5 TRIM27 TLE1 GNAI3 RINT1GOLGA2 UBQLN4 INA TCF4 ETS1SMAD1PBX1 HAX1 SRPK2 APP TRAF2 AXIN2 BMI1 MX1 RABGAP1L ACD BDNF NEFMDISC1 HOXA10 USP9X MBD3SMARCE1 TINF2 GNAI2 SORT1 ANXA1 ARID1ATCF3 TERF1 NEDD4L SMAD4 CTBP1 IKZF1 IQCB1 MYH10 SART3 PRMT1 ZP3 APC2 PARK2 CCNH KAT2A NEDD4ELAVL1 PNRC1 HRSIN3B SMARCD3 DIS3 COPS5 POU2F1 PCDH17 NMNAT1 TRAF6 SMAD3 CRTC1 CRISPLD2 PAFAH1B1 POT1 SIRT7 SMAD2 SOX2 SRPK1 CDK5 RANBP9 KAT2B SHC3 HOXD13 TP53 HDAC4 NCOA1 FOS HOXB2 FUS UBE2ICREBBP SQSTM1 CTNNB1MDM2 HLA-DPA1 SHC1 TNK2 CENPB CRBN MECOM HOXB1 FBXO25NCK2NTRK1 CUL1DDX5 HDAC1 HSP90AB1 SIRT1 EP300 GATA3 GIPC1 TNIKCDK2 RB1 SMARCA4 EHMT2 RARB PPP1R9BDAPK1 NPM1 HOXD4 MAP6 TXN2 HAND2 CREB1 HACE1 NTF4 NTRK2 KIF26B EGFR PPP1CA RXRA APBB1 PSMC5 NR3C1SP1 NCOR2 AP1B1 GOLIM4 HSP90AA1ABL1 CDK1 CEBPB NR1H2 SH2B1 ITGB1BP2 PML HDAC3 FYN ACTA1 MYC RXRB UNC5C PLCG1 PRKCAGTF2I SUV39H1 EFNA1PTPN1 ERBB3 CDKN2APRKACA PRKD2 RXRG EFNA3 PPP2R5D FRS2 ERBB2 LIN7C GATA4 SYNE4 CRK SRC ASB8 CDK6 PHOX2A EPHA3 PIK3R1 LZTR1 EGR1 EFNB1 TBX2 SLC39A4 MAP4K4 PIK3R3 EFNA4TMEM17 RAD51 RBM18 POLR2G TSHZ2 PYCARD TMEM231 B3GAT3 HAUS7

TXK PCSK1N EFNA5 PRRX1 EFNB2

ST3GAL4 SAMD11 Log2FC

ModuLand -6 -4 -2 0 2 4 6

B NTRK1 RXRA PAFAH1B1

DCX LZTR1 CDK6 TRAF6

TERF1 TP53 APBB1

B3GAT3 MEIS2 GNAI3 PARK2

HDAC3 POU2F1 SMAD4 DCX MEIS2

C 4000 D 15000 Stage 0 3000 Stage 0 Stage 2 Stage 2 2000 10000 Stage 3 Stage 3 1000 500 400 5000 Read count 300 Read count 200 100 0 0

Man7 Hues1 Hues1 Man7

Figure 4.5: Protein-Protein interaction analysis of cluster 5 genes and their first neighbours (A) Protein- protein interaction network of cluster 5 genes and their first neighbours generated using curated interactions from BioGrid (Stark et al. 2006). (B) Network of key meta-nodes from overlapping networks in network (A) identified using ModuLand analysis (Szalay-Beko˝ et al. 2012). Expression of meta-nodes during hESC-directed chondrogenesis from RNA-seq data for DCX (C) and MEIS2 (D)

Chapter 4 112 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

4.2.3 MicroRNA Target Interaction Network

MicroRNA-target interaction network analysis was performed in order to identify miRNAs that may be key regulators of hESC-directed chondrogenesis. The miRcomb ’R’ package was chosen to perform miRNA-mRNA target interaction analysis as it generates networks of highly potential miRNA-mRNA interactions based on co-expression data, miRNA target prediction databases and differential expression analysis (Vila-Casadesus´ et al. 2016). For miRComb analysis mRNAs and miRNAs were filtered for only those differentially regulated between stage 0 and 3 of the protocol. Next, all miRNAs and mRNAs were correlated against each other to identify miRNA-mRNA pairs with negative Pearson’s correlation. Finally target prediction information was added using the TargetScan and microCosm databases (Figure 4.6A; Section 2.4.5). Networks were then generated with miRNA-mRNA interactions which had both a strong negative correlation and interaction was predicted by one of the target prediction databases used (TargetScan and microCosm). MicroRNA-mRNA networks were generated for miRNAs downregulated (Figure 4.6B) and miRNAs upregulated (Figure 4.6C) during hESC-directed chondrogenesis. The miRComb analysis identified eight downregulated miRNAs (miR-448, miR-512-3p, miR-515-5p, miR-516a-5p, miR-518b, miR-519c-3p, miR-525-5p and miR-1323) during chondrogenesis as miRNAs with likely potential interactions with upregulated mRNAs. All of these miRNAs except miR-448 are transcribed from the large cluster of miRNAs on chromosome 19 (CM19C). Gene Ontology (GO) analysis revealed predicted targets were enriched with ’histone methylation’ related genes (Bonferroni corrected p-value=0.00975 and fold enrichment=13.34), these genes included; ARID4A, ARID4B, SETD7, PRDM16, MECP2, ASH1L and TET2. It was suggested that these miRNAs may have role in modulating the epigenetic regulation of hESCs. For example, TET2 is an important epigenetic regulator in development and is a predicted target of miR-488. Other key genes involved in development are the ARID family of DNA binding proteins (Wilsker et al. 2002); ARID5A and ARID5B are both predicted targets of miR-519c-3p. Another epigentic regulator SETD7, a methyltransferase and predicted target of miR-525-5p, has been identified as a key gene regulating differentiation of hESCs (Castano˜ et al. 2016). MiRComb analysis of miRNAs upregulated during hESC-directed chondrogenesis generated a smaller network with only six miRNAs with likely potential interactions with downregulated mRNAs. Predicted targets were not enriched for any particular GO term. The hox miRNA miR-615-3p was identified as a key miRNA with several highly potential interactions with downregulated genes during chondrogenesis. Both arms of the microRNA miR-542 were also identified as key miRNAs, both with likely potential interactions with genes involved in ECM degradation including MMP24 and TIMP4; matrix

Chapter 4 113 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells metalloproteinase (MMPs) degrade ECM proteins while TIMPs are inhibitors of MMPs. Both arms are also predicted to target HYAL1 (not shown), a hyaluronidase which degrades hyaluronan a major glycosaminoglycans in the extracellular matrix (ECM) known to be important during chondrogenesis (Wu et al. 2010b; Wu et al. 2013b). In summary, by using miRComb, an integrated miRNA-mRNA analysis tool, large lists of thousands miRNA-mRNA predicted interactions can be narrowed down to more manageable size networks containing more likely potential interactions. However these interactions still require experimental validation. The networks generated can give an overview of the role of miRNAs in different physiological states. Key miRNAs which are downregulated upon differentiation in hESCs appear to target several epigenetic regulators such as TET2 and SETD7. Nearly all key miRNAs in hESCs identified using miRComb were from the large cluster of miRNAs on chromosome 19 (CM19C) this isn’t surprising as miRComb uses co-expression analysis and miRNAs transcribed from the same cluster will have very similar expression profiles as they likely arise from a common primary transcript, as will different arms of the same miRNA e.g. miR-542-3p and miR-542-5p. Key miRNAs identified in the hESC-chondroprogenitors include; miR-615-3p which has several likely potential interactions with downregulated genes and both arms of miR-542 which may be regulating ECM related genes.

Chapter 4 114 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

FGD4 A C SALL4 TRIM71 mRNA and miRNA hsa-miR-450b-5p hsa-miR-3613-5p Differential expression DSEL MMP24 NTS

mRNA and miRNA ZIC3 CHCHD4 (FC>1.5 and FDR<0.05) TUBB2B MARVELD2 hsa-miR-542-3p UTP20 YBX2 CNKSR1 hsa-miR-190b miRNA-mRNA miRNA-mRNA UNC5D IRX2 Correlation Target Prediction NUDC

ZNF593 hsa-miR-615-3p Negative Pearson’s Predicted by TargetScan FAM46B hsa-miR-542-5p correlations and microCosm DOHH ELAC2 COL23A1 miRNA-mRNA TIMP4 GLI1 GAL USP7 ATAD3B Network PDZD4 POLR3B ARRB1 RRP12 GDPD5 NUP35 Log2FC C16orf74 MYBBP1A RUVBL1 DDX49

-8 -4 0 4 8 EIF4G3 SBF1 EBF4 C6orf89 B ALG9 TMEM164 ST3GAL3 BVES ULK2 FBN1 PDE10A RBM5 RBL2 ATXN1 PDE8A ZNF555 SPOP GDF6 B3GAT3 ZC3H12C FAM168A NIPSNAP3A CSGALNACT2 APPBP2 TTC28 hsa-miR-515-5p GSTM3 TET2 REV3L ZFP1 PLCE1 TMF1 DUSP3 AHRR LYST SERTAD2 CSAD ZNF77 hsa-miR-512-3p hsa-miR-448 DSTYK RABGAP1 PPARD KIAA0430 CDK19 PRDM16 DENND1B PHF21A DYRK4 TANC2 ABTB1 TTLL7 ASB7 HCFC2 CCNG2 GATAD2B ZNF704 MAGED2 ITCH SMAD9 MXD1 LCOR IL13RA1 FAM199X C7orf60 ASH1L USP47 NF1 MBNL2 TOM1L2 IL11RA GSTM2 hsa-miR-525-5p DFNA5 FBXL17 GPR137C CRYL1 DCLK2 MXRA7 ZNF148 ARID4A CGGBP1 IRF2BP2 KLHL28 ARID4B SETD7 BMPR2 MEF2C BTG3 ZADH2 MECP2 CLIP4 IDH2 PPP1R9B ZDHHC1 hsa-miR-519c-3p GIPR NR2F2 GPR137B NIN RAB22A AKT3 TIMP2 BACH2 MAPRE3 MBNL1 ATP6AP1 HIPK3 PRKAA1 AHI1 SLC25A42 UVRAG HECA THRA hsa-miR-1323 PNRC1 TNRC18 IRAK2 SEC31B hsa-miR-518b BCORL1 ZBTB41 hsa-miR-516a-5p P2RX4 TMEM117 SCARF2 SRSF12 SH3TC1 ZNF70 C5orf42 TRAF3 RIT1 DMPK ADCY7 FOXK1 XRN1

Figure 4.6: MicroRNA-mRNA Interaction Network analysis using miRComb (A) Workflow used for miRComb analysis. Differential expression was first performed on miRNAs and miRNAs between stage 0 and stage 3 of the DDP; miRNAs and mRNAs with log2(fold change)<1.5 and FDR>0.05 were filtered out. Next Pearson’s correlations were calculated for each miRNA and mRNA pair and target prediction information was added using predictions from TargetScan and microCosm databases. miRComb network for miRNAs downregulated (B) and upregulated (C) during DDP, miRNA-mRNA interactions were filtered for interactions with Interaction Score >10, correlation adjusted p-value<0.01 and predicted by at least one target prediction database. Genes were also filtered out if they had expression <6.

Chapter 4 115 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

4.2.4 MicroRNA Functional Studies- miR-199a Inhibition

As miRNA inhibition during hESC-directed chondrogenesis using the DDP had not been performed previously for initial functional analysis of miRNAs, a previously identified chondrogenic miRNA was chosen for inhibition in order to validate the miRNA inhibition assay. MicroRNA miR-199a-3p was chosen as it has been reported to negatively regulate chondrogenesis (Lin et al. 2009b; Akhtar and Haqqi 2012) and several of its targets have been validated including Smad1 (Lin et al. 2009b), CD44 (Henry et al. 2010) and COX-2 (Akhtar and Haqqi 2012). MicroRNA-199a-3p showed high expression in both hESC lines during directed-chondrogenesis with it showing significant upregulation during Man7-directed chondrogenesis (Figure 4.7A). The hESC line Hues7 was transfected with 200nM miR-199a-3p anti-sense inhibitor (Life Technologies) by Nucleofection (Lonza) on day 8 of the DDP (Stage 2/3 split) (n=2). The effect of miR-199a-3p inhibition during hESC-directed chondrogenesis was assessed 48hrs post-transfection. Inhibition of miR-199a-3p showed slight increase in protein expression of its validated target Smad1 (Lin et al. 2009b) as shown by Western blot (Figure 4.7C) and quantified by densitometry (Figure 4.7D). Similarly, gene expression of another validated target of miR-199a-3p, CD44 (Henry et al. 2010) also showed increased levels (Figure 4.7B). Gene expression of downstream targets of Smad1 were also increased, COL2A1 was significantly upregulated 48hrs post-miR-199a inhibition also COL11A1 also showed a slight upregulation after miR-199a-3p inhibition (Figure 4.7B). In summary, inhibition of miR-199a-3p during hESC-directed chondrogenesis at the stage 2/3 transition led to increased COL2A1 expression in chondroprogenitors produced, possibly via de-repression of Smad1 protein. Using this approach the role of other miRNAs during hESC-directed chondrogenesis can be investigated.

Chapter 4 116 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

miR-199a-3p

10000 1.4 A Stage 0 B Stage 1 Stage 2 1.2 Stage 3 * 5000

1.0 Read count

0 0.8 Expression relative to control

Hues1 Man7 OCT4 HIF1A SOX9 CD44 COL2A1 COL11A1 D Smad1 C 2.0

anti-miR-199a Control 1.5

SMAD1 1.0

0.5 GAPDH Relative Density 0.0 Density 1.40 1.59 1.21 0.79

Control

anti-miR-199a

Figure 4.7: Inhibition of miR-199a-3p during directed chondrogenesis of hESCs (A) Expression of miR-199a- 3p from RNA-seq data of Hues1 and Man7 hESC-directed chondrogenesis. (B) RT-PCR of genes 48hrs-post miR- 199a-3p inhibition. Expression relative to negative scrambled control treatment. (C) Western blot of Smad1 and GAPDH protein 48hrs-post treatment with miR-199a-3p inhibitor (anti-miR-199a) or negative scrambled control. (D) Densitometry analysis of Smad1 expression relative to loading control (GAPDH) from Western blot in (C).

4.3 Discussion

This chapter aimed to identify several novel regulators of hESC-directed chondrogenesis by using a combination of co-expression analysis, gene ontology enrichment analysis, protein-protein network analysis and miRNA-mRNA target interaction analysis. The integration of mRNA-seq and miRNA-seq data allows identification of co-expressed miRNAs and genes which may be regulated by a similar mechanism and/or have related a function. Also with use of target prediction algorithms, miRNAs and mRNAs with strong negative correlation can be used to identify key highly likely miRNA-mRNA interactions regulating hESC-directed chondrogenesis.

4.3.1 Identification of novel regulators during hESC-directed chondrogenesis by co-expression network analysis

Gene co-expression network analysis has previously been used to identify functionally related genes from yeast (Zhou et al. 2002) and human DNA microarrays (Lee et al. 2004a). The topology of gene co-expression networks represents clusters of genes with similar expression patterns and these clusters have been shown in some cases to be

Chapter 4 117 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells enriched for genes with biologically related functions in the literature e.g. macrophage activation cluster (Xue et al. 2014), protein biosynthesis cluster and cell cycle cluster in cancer (Choi et al. 2005). Using a similar approach co-expression analysis was used to identify novel regulators of hESC-directed chondrogenesis.

Pluripotency cluster genes and miRNAs

Gene Ontology (GO) analysis of cluster 1 failed to identify a significant enrichment for genes associated with any particular GO term. The analysis of the cluster 1 did however shows it contains genes and miRNAs highly expressed in both pluripotent Man7 and Hues1 cells which were then downregulated during hESC-directed chondrogenesis (Figure 4.2C and Figure 4.3A-B). Furthermore cluster 1 contains Nanog and Oct4 two key pluripotency regulators (Chambers et al. 2003; Nichols et al. 1998; Niwa et al. 2000; Section 1.4.1) along with pluripotency-associated miRNAs from the CM19C and miR-302a-5p (Section 1.5.5). This suggests that cluster 1 is a ’pluripotency’ enriched cluster and other genes and miRNAs contained within the cluster could be novel pluripotency regulators. Evaluation of cluster 1 shows it contains 24 members of the krueppel C2H2-type zinc-finger protein family which bind DNA and regulate gene transcription (Dang et al. 2000), including ZFP42, ZFP57, ZNF208, ZNF492 ZNF649 and ZNF880. Several zinc finger proteins have already been implicated in ESC pluripotency including; ZFP42 (also known as Rex-1), ZFP57, ZNF206, ZNF296, ZNF322 (Wang et al. 2007b; Yu et al. 2009; Fischedick et al. 2012; Ma et al. 2014; Akagi et al. 2005; Scotland et al. 2009). In all these studies they showed the zinc finger gene of interest inhibited ESC differentiation suggesting its role in maintaining pluripotency. However in these studies after knockdown/knockout of the gene of interest, ESCs still expressed pluripotency genes and could self-renew, this could be due to the compensatory effect of other zinc fingers expressed. Several studies also showed the ability of ZNFs (ZNF206, Wang et al. 2007b; Yu et al. 2009; ZNF296, Fischedick et al. 2012; ZFP322, Ma et al. 2014) to activate transcription of Oct and Nanog in ESCs. Many of the zinc-finger proteins found in this pluripotency enriched cluster could be novel pluripotency regulators, such as ZNF649 which acts as a transcriptional repressor of mitogen-activated protein kinase (MAPK) signalling pathway genes (Yang et al. 2005). Notably a known pluripotency promoting zinc-finger ZNF322 has also been shown to repress several MAPK pathway genes in mESCs (Ma et al. 2014). The cluster also contains several miRNAs which may be novel regulators of pluripotency, such as miR-1246 which has recently been shown to be regulated by Oct4 and promote stemness of liver cancer stem cells by activating Wnt signalling via directly targeting AXIN2 and GSK3, members of the beta-catenin destruction complex (CHAI et al. 2016). The involvement of Wnt signalling in ESC maintenance has been well-studied

Chapter 4 118 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

(Sokol 2011, Section 1.4.2). Another pluripotency enriched cluster miRNA of interest is miR-7641, which is downreglated during hESC differentiation to endothelial cells and targets chemokine CxC ligand, CXCL1 (Yoo et al. 2013) a potent agonist for the C-X-C Motif Chemokine Receptor 2 (CXCR2) which was recently shown to promote hPSC self-renewal and pluripotency (Jung et al. 2014). In summary, and as expected, a large cluster of co-expressed pluripotency-associated genes and miRNAs are downregulated during hESC-directed chondrogenesis. This cluster includes several well known pluripotency regulators such as Nanog, Oct4 and miR-302a-5p. Importantly, through cluster association we have also discovered a number of potentially novel pluripotency regulators such as the zinc finger gene ZNF649 that is a known repressor of the MAPK signalling pathway, ZNF322a a zinc finger protein with the same ability inhibits differentiation of mESCs (Ma et al. 2014). Two miRNAs coregulated with pluripotency genes may be novel negative regulators of pluripotency, miR-1246 which activates Wnt signalling, a pro-differentiation signal in hESCs (Davidson et al. 2012), and miR-7641 which targets CXCL1 a potential pluripotency promoting ligand. Further experimental validation of these potential novel pluripotency regulators is required before any function can be applied to them.

’Primitive streak’ Cluster of genes and miRNAs (Cluster 2)

During early development the three germ layers are formed during gastrulation, a process involving the movement of epiblast cells to create the primitive streak, a linear structure that bisects the embryo. Next, primitive streak cells undergo epithelial-mesenchymal transition (EMT) to generate the mesoderm and endoderm, in a process known as regression marked by loss of cell surface E-cadherin and gain of N-cadherin, Slug and Snail (Ferrer-Vaquer et al. 2010; Eastham et al. 2007). The directed differentiation protocol (DDP) aims to recapitulate normal human cartilage development in vitro by first directing cells through a primitive streak-mesendoderm stage (Stage 1 of DDP) (Oldershaw et al. 2010). Cluster 2 contains many genes that are expressed in the primitive streak and/or have roles in early lineage specification, including: Mixl1 (Izumi et al. 2007), Eomes (Izumi et al. 2007), T (Izumi et al. 2007; Wilkinson et al. 1990), Foxa2 (Perea-Gomez´ et al. 1999; Kinder et al. 2001; Gadue et al. 2006), Cerberus-1 (Belo et al. 1997; Kinder et al. 2001), Otx2 (Ang et al. 1994; Kinder et al. 2001) and GDF3 (Chen et al. 2006; Andersson et al. 2007). These genes would be expected to peak at stage 1 of the DDP. Unfortunately transcriptome profiling of this stage of the DDP was not performed. However, previous RT-PCR analysis of the DDP shows that several of these genes, including Foxa2, T and Mixl1, peak during early stages of the DDP and are downregulated at later stages of hESC-directed chondrogenesis (Oldershaw et al. 2010). Along with primitive steak-associated genes, cluster 2 also contains miRNAs, such as

Chapter 4 119 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells the miR-200, that may regulate early lineage specification. The role of the miR-200 family in the regulation of EMT has been well investigated; the miR-200 family is repressed by several EMT regulators including Snail (Gill et al. 2011), ZEB1 and ZEB2 (Bracken et al. 2008; Wellner et al. 2009), loss of miR-200 family promotes EMT and early mesoderm differentiation of mESCs (Gill et al. 2011) and induces EMT in epithelial cells (Gregory et al. 2008). Inhibition of Activin signalling during mESC differentiation lead to downregulation of miR-200 family miRNAs miR-200b and miR-141 and promoted EMT (Gill et al. 2011). Similarly, downregulation of miR-200 family members is observed after addition of follistatin (Activin-A antagonist) during stage 1 of the DDP, with downregulation of miRNAs miR-200a/b, miR-141 and miR-429 between stages 1 and 2. The miR-200 family also plays a role in stem cell self-renewal by targeting the polycomb-repressor Bmi1 (Park et al. 2004) and can inhibit differentiation of mESCs by targeting pro-differentiation genes including Cadherin-11, Neuropilin-1 and Transforming Growth Factor Beta Receptor 3 (TGFBR3) (Lin et al. 2009a). However, the highest expressed member of the miR-200 family miR-200c-3p maintained its high expression until stage 2 and is then subsequently downregulated, although this high expression of miR-200c-3p at stage 2 of the DDP was only observed in one biological replicate (Figure 4.3C). The miR-371-3 cluster is a known group of pluripotency-associated miRNA with several articles reporting its high expression in ESCs (Suh et al. 2004; Wilson et al. 2009). Its mouse homolog has been shown to be regulated by the pluripotent transcription factors Nanog, Sox2 and Oct4 (Marson et al. 2008). However, its specific role in pluripotency is still unknown. A recent report showed that the level of expression of the miR-371-3 cluster in pluripotent stem cells (PSCs) could be used to predict the neuronal propensity of hPSC lines, suggesting that hPSC lines with lower miR-371-3 expression could undergo neural differentiation more efficiently (Kim et al. 2011c). However, the molecular mechanism by which the miR-371-3 cluster affects hPSC differentiation remains unclear. Other cluster 2 miRNAs include a chromosome cluster 19 (CM19C) miRNA miR-519b-3p, a member of miR-302 cluster miR-367-5p and miR-205-3p, an EMT regulating miRNA (Gregory et al. 2008). These are all expressed at low levels during hESC-directed chondrogenesis (Figure 4.3E). In summary, cluster 2 contains several genes and miRNAs known to regulate fate decisions during early development, including MixL1, T, Eomes and the miR-200 family of miRNAs. Although transcriptome profiling was not performed at stage 1 of the DDP, previous RT-PCR data suggests genes in this cluster would peak at stage 1 of the DDP and become downregulated during final stages of chondrogenesis. Other genes and miRNAs contained within this cluster may be novel early development regulators such as

Chapter 4 120 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells the miR-371-3 cluster which is well-known to be expressed in hESCs, however its role in pluripotency has yet to be reported. Relative expression levels of miR-371-3 could affect the differentiation propensity of PSCs suggesting it may have a role in early fate specification.

’Extracellular Matrix (ECM)’ cluster of miRNAs and genes (Cluster 4)

Co-expression analysis identified two highly correlated clusters of miRNAs and genes which were upregulated during hESC-directed chondrogenesis. Gene ontology enrichment analysis found two of these were enriched for cartilage-related genes, these clusters were termed the ’ECM’ cluster and ’limb development cluster’. The ’ECM’ cluster contains several genes encoding collagens and involved in ECM organisation which were upregualted during hESC-directed chondrogenesis (Figure 4.2C). Further analysis of this cluster using protein-protein interaction network analysis, identified several genes which are key regulators of these ECM genes; Fibronectin 1 (FN1), Transglutaminase 2 (TGM2) and Family With Sequence Similarity 46 Member A (FAM46A) (Figure 4.4B). FAM46A was identified from protein-protein interaction analysis due to its interactions with TBX4, CD93, HTRA1 and COL4A2 (Figure 4.4A), its expression is upregulated during hESC-directed chondrogenesis (Figure 4.4C). It was recently shown that a homozygous loss-of-function mutation in FAM46A leads to skeletal abnormalities including short stature in developing mice (Diener et al. 2016). Also yeast two-hybrid screens identified its interaction with ZFYVE9 protein which recruits of unphosphorylated forms of SMAD2/SMAD3 to the TGF-β receptor (Colland et al. 2004), suggesting it may promote TGF-β signalling a key pathway involved in chondrogenesis (Section 1.3.1). However its function during cartilage development has yet to be directly examined. Fibronectin 1 (FN1) was the most highly expressed gene in the hESC-chondroprogenitors (Figure 4.4C) and has several known interactions with proteins whose gene falls within the ’ECM’ cluster (Figure 4.4A). Its role in chondrogenesis has been investigated (reviewed in Singh and Schwarzbauer 2012), inhibition of fibronectin–fibronectin interactions with a peptide reduced the number of condensations in mouse chondrogenic cells and during micromass cultures of MSCs (Singh and Schwarzbauer 2014). Another gene of interest identified from protein-protein interaction network analysis was transglutaminase 2 (TGM2) which has been reported to interact with FN1 (Figure 4.4A). In contrast to FAM46A and FN1 which both increase throughout the DDP (Figure 4.4C-D) TGM2 is upregulated between stages 0 and 2 and then becomes downregulated between stages 2 and 3 of the DDP (Figure 4.4B). Transglutaminase has been shown to be expressed in the epiphyseal growth plate of developing long bones of rats, its activity was also present in the growth plate but not in articular cartilage (Aeschlimann et al.

Chapter 4 121 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

1993). Transglutaminase-2 has also been reported to mediate cell adhesion and spreading. One study showed cell surface expressed transglutaminase-2 could act as a integrin-binding co-receptor for fibronectin to mediate adhesion and spreading of fibroblasts on fibronectin fragments lacking integrin-binding motifs (Akimov et al. 2000). Transglutaminase-2 can also bind heparan sulphate chains of the syndecan-4 cell surface receptor, via its heparin binding domain (Lortat-Jacob et al. 2012), leading to activation of focal adhesion kinase and MAPK pathway (Telci et al. 2008). Transglutaminase-2 has been investigated for its use in tissue engineering to improve stability of collagen scaffolds due to its ability to catalyse the crosslinking of proteins by isopeptide bonds. It was shown that transient treatment of collagen type XI scaffolds with transglutaminase resulted in increased attachment, enhanced cell aggregation and improved chondrogenesis of MSC compared to untreated scaffolds (Shanmugasundaram et al. 2012). Along with ECM genes the cluster also contains miRNAs which have a role in ECM organisation or chondrogenesis. Nearly half (10/24) of ECM cluster miRNAs have previously been implicated in cartilage development. The majority of these miRNAs inhibit chondrogenesis by targeting key chondrogenesis regulators or signalling pathway genes, these include: miR-145 which targets Sox9 (Martinez-Sanchez et al. 2012), miR-193b which targets TGFB2 and TGFBR3 (Hou et al. 2015), miR-199a which targets SMAD1 (Lin et al. 2009b), miR-29a which targets FOXO3A (Guerit´ et al. 2014) and COL2A1 (Yan et al. 2011) and miR-574 which targets RXR (Guerit et al. 2013). Some ’ECM’ cluster miRNAs have also been shown to positively regulate cartilage, such as miR-675 which promotes Col2a1 expression in human articular chondrocytes although mechanism is currently unknown (Dudek et al. 2010). McroRNA-143 has been shown to target MMP13 in several cancers therefore may promote ECM maintenance by inhibiting its degradation (Wu et al. 2013a; Osaki et al. 2011). The ’ECM’ cluster may also contain novel chondrogenic miRNAs. For example miR-22- 3p is the microRNA in the ’ECM’ cluster with the highest expression during hESC-directed chondrogenesis, and has been reported to promote osteogenesis and inhibit adipogenesis of hADMSCs by targeting HDAC6 (Huang et al. 2012). Notably, HDAC6 is a co-repressor of RUNX2 target genes, as is HDAC4 (Westendorf 2006). HDAC4 was the first validated target of miR-140 the main cartilage related miRNA (Tuddenham et al. 2006). Suggesting miR- 22-3p may function in hESC-directed chondrogenesis in a similar way to miR-140 functions in other models of chondrogenesis. Along with miR-22 other ’ECM’ cluster miRNAs have been shown to regulate osteogenesis such as miR-188 which inhibits bone formation by targeting HDAC9 and RICTOR (Li et al. 2015a) and miR-335-5p which promotes osteogenesis by targeting Wnt anatagonist DKK1 (Zhang et al. 2011a). MicroRNA-214 has already shown to have roles

Chapter 4 122 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells in several mesoderm lineages, e.g. promoting skeletal muscle differentiation by targeting Ezh2 and N-ras (Juan et al. 2009; Liu et al. 2010), inhibiting osteogenesis by targeting ATF4 (Wang et al. 2013a) and Osterix (Shi et al. 2013). The role of miR-335-5p and miR-214 in chondrogenesis has not yet been reported. A comparison of the ’ECM’ cluster miRNAs with the previously published miRome of distinct regions of developing human cartilage, including progenitor, differentiated and hypertrophic chondrocytes, showed ’ECM’ cluster miRNAs were predominantly expressed in progenitor chondrocytes (McAlinden et al. 2013). MicroRNAs miR-214, miR-675 and miR-335-5p from the ’ECM’ cluster all showed significantly higher expression in progenitor chondrocytes than hypertrophic chondrocytes (McAlinden et al. 2013), perhaps suggesting cells at the end of stage 3 are ‘chondro-progenitors’ and are not hypertrophic. In summary, a combination of co-expression analysis, gene ontology analysis and protein-protein network analysis identified a large cluster of genes and miRNAs upregulated during hESC-directed chondrogenesis and contained several members with known roles in ECM organisation including Fibronectin 1 (FN1), Transglutaminase 2 (TGM2) and Family With Sequence Similarity 46 Member A (FAM46A). Notably, several co-expressed miRNAs in this cluster are known regulators of chondrogenesis with the majority being inhibitory to chondrogenesis. Several of the ’ECM’ cluster miRNAs are also expressed in progenitor cells of developing cartilage (McAlinden et al. 2013). Two miRNAs from the cluster, miR-675 and miR-574 are both regulated by Sox9 (Guerit et al. 2013; Dudek et al. 2010), suggesting other co-expressed miRNAs may also be regulated by the same mechanism. Novel miRNA chondrogenic regulators may also be co-expressed with these ’ECM’ miRNAs. Several have already been shown to have functions in other mesodermal lineages such as miR-22 in MSCs osteogenesis (Huang et al. 2012), miR-214 in myoblasts (Liu et al. 2010) and miR-335 in osteoblasts (Zhang et al. 2011a), however the function of these miRNAs in cartilage development has yet to be investigated.

’Limb development’ cluster of genes and miRNAs (Cluster 5)

Along with the ’ECM’ cluster of genes and miRNAs another smaller cluster of genes and miRNAs was upregulated during hESC-directed chondrogenesis which contained a significant number of genes associated with limb development, including; HAND2, RARB (Dolle´ et al. 1989), TBX2 (Gibson-Brown et al. 1998), MEIS2 (Capdevila et al. 1999) and EN1 (Adamska et al. 2004). Notably, several of these genes have been reported to be expressed in discreet proximal regions during in limb development, including; RARB (Dolle´ et al. 1989), MEIS2 (Capdevila et al. 1999) and HAND2 (Osterwalder et al. 2014). Also MEIS2 represses expression of distal genes, Bmps and Hoxd (Capdevila et al. 1999). Suggesting that the cluster of genes may be associated with proximal-distal patterning in

Chapter 4 123 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells limb development. This ’limb development’ cluster of miRNAs and genes showed slightly different expression pattern during hESC-directed chondrogenesis compared to the ’ECM’ cluster, as its expression of genes and miRNAs were maintained between stage 2 and 3 whereas the ’ECM’ genes and miRNAs showed slight downregulation during this stage (Figure 4.2C and Figure 4.3F-G). In contrast to the ‘ECM’ cluster there were no reported interactions between any of the proteins encoded by genes belonging to the ‘limb development’ cluster, most likely due to the small size of this cluster. Therefore, ‘first neighbours’ were added and protein-protein network analysis performed again. This analysis identified several highly connected genes including Meis Homeobox 2 (MEIS2) and Doublecortin (DCX) which are part of the ’limb development’ cluster list, and ‘first neighbours’ genes Beta-1,3-Glucuronyltransferase 3 (B3GAT3) and Leucine-Zipper-Like Transcription Regulator 1 (LZTR1). B3GAT3 and LZTR1 were both also significantly upregulated during hESC-directed chondrogenesis (Figure 4.5B). Doublecortin (DCX) has mostly been examined in neurogenesis, it binds to microtubles and aids in neuronal migration (Brown et al. 2003). Recently it was shown to be expressed in mesenchymal cells in the mouse embryonic limb buds which maintained expression of Dcx after differentiation into joint interzone cells and articular chondrocytes (Zhang et al. 2011b). Also overexpression of DCX during chondrogenic pellet culture of human adipose stem cells led to decrease in COL2A1 expression and increase in ACAN, MATN2 and GDF5 (Ge et al. 2014) suggesting it has a role in regulating cartilage phenotype, although the molecular mechanism behind this is unclear. Another gene identified from protein-protein network analysis of the ’limb development’ cluster of genes is B3GAT3, a glucuronyltransferase which has been implicated in proteoglycan synthesis and skeletal development. A mutation in B3GAT3 was recently shown to cause skeletal dysplasia (Budde et al. 2015; Oettingen et al. 2014). Also it has been reported IL-1β treatment resulted in a marked inhibition of B3GAT3 expression and activity in rat articular chondrocytes leading to a decrease in proteoglycan synthesis (Gouze et al. 2001). Only three miRNAs, miR-181a-2-3p, miR-99b-3p and miR-6800-3p, were found to be co-expressed with ’limb development’ related genes. They all showed gradual upregulation during hESC-directed chondrogenesis (Figure 4.3G) and miRNAs, miR-181a-2-3p and miR-99b-3p are both expressed in developing cartilage (McAlinden et al. 2013). Similar to many miRNAs in the ’ECM’ cluster these two miRNAs have previously been reported to inhibit chondrogenesis. Overexpression of miR-181a in chick chondrocytes led to reduction in COL2A1 and ACAN expression by targeting CCN1 (Sumiyoshi et al. 2013). Another miR-181 family member which has the same seed,

Chapter 4 124 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells miR-181b has also shown to regulate chondrogenesis, overexpression of miR-181b inhibited chondrogenesis of chick mesenchymal cells and led to upregulation of several MMPs including MMP2, MMP9, MMP12 and MMP13 (Song et al. 2013d). MicroRNA-99b has the same seed as miR-99a which has been implicated in chondrogenesis, miR-99a inhibition in rat MSCs promoted chondrogenesis leading to increased Collagen Type II and Aggrecan deposition by targeting BMPR2 (Zhou et al. 2016). The remaining miRNA of the cluster miR-6800-3p, is expressed at very low levels, only annotated in humans and has no reported function or identified targets in any system, suggesting it is unlikely to be functional. In summary, the ’limb development’ cluster of genes contains several genes known to be expressed during limb development, specifically many have been reported to have discreet expression in the proximal region of the developing limb bud. Several co-expressed genes in this cluster may also have roles in limb development, such as doublecortin which has been shown to effect chondrogenesis of MSCs, and B3GAT3 which has been implicated in proteoglycan synthesis. MicroRNAs co-expressed may also have roles in chondrogenesis such as miR-181a and miR-99b which both have family members reported to regulate chondrogenesis.

Summary

By implementing a combination of co-expression analysis, gene ontology enrichment analysis and protein-protein network analysis, four key clusters of functionally related co-expressed miRNAs and genes regulated during hESC-directed chondrogenesis have been identified. These include a pluripotency cluster, primitive-streak cluster, ECM cluster and a limb development cluster. Further analysis of genes and miRNAs within each of these clusters has identified several potential novel regulators of hESC-directed chondrogenesis however further experimental validation is required to confirm their role during hESC-directed chondrogenesis. This approach is ideal for large-scale high-throughput data to efficiently narrow down thousands of regulated genes during hESC-differentiation to more manageable numbers which can then be investigated individually. However this approach has several limitations. Firstly it depends very heavily on already known literature for both the gene ontology enrichment analysis and protein-protein interaction network analysis. For example gene ontology enrichment analysis failed to identify cluster 1 as a pluripotency associated cluster despite it containing several already well known pluripotency regulators including; Oct4, Nanog, ZFP42, ZFP57, Dnmt3a (Li et al. 2007) and Nodal signalling genes including Nodal, Lefty1 and Lefty2 (Vallier et al. 2005). This may be due to the lack of a specific ’pluripotency maintenance’ GO term or similar, currently the closest GO term available which characterises pluripotent stem cells is ’stem cell population maintenance’. This GO

Chapter 4 125 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells term contains 164 annotations many of which are not associated with pluripotent stem cells such as hepatocyte nuclear factor 1-beta (HNF1B) which is a liver specific transcription factor. The large number of non-pluripotency related genes in this GO term will reduce the likelihood for gene ontology enrichment analysis to identify a cluster of pluripotency related genes to be enriched with the ’stem cell population maintenance’ GO term, this can be overcome by introduction of a pluripotency specific GO term. Similarly the protein-protein network analysis also heavily depends on already cited interactions. In this analysis the latest version of the interaction database BioGRID (version 3.4.140) which contains 1,072,173 protein and genetic interactions curated from 57,058 publications (Stark et al. 2006) was used. However no curated database of protein-protein interactions is complete or entirely accurate. Although this method aimed to identify novel regulators of hESC-directed chondrogenesis as it requires already curated interactions with genes already associated with cartilage development any genes identified are likely to have already been associated with chondrogenesis such as transglutimase and fibronectin however it may elude to previously overlooked genes which may be more important than once thought. Also it can identify novel roles of genes which have been highly cited in a different system for example doublecortin (DCX) has been well know to be involved in neuronal migration but its role in chondrogenesis is unclear. As highlighted by gene ontology enrichment analysis several co-expressed genes in each cluster have similar function e.g. pluripotency and limb development. Notably, the co-expressed miRNAs in the cluster also appear to have a similar function to their co-expressed genes. For example the pluripotency promoting miRNA miR-302a-5p (Barroso-del Jesus et al. 2009) is co-expressed with several pluripotency promoting genes in the pluripotency cluster (cluster 1), similarly the primitive streak cluster (cluster 2) contains genes and miRNAs that regulate gastrulation, including the miR-200 family which regulates epithelial-mesenchymal transition (EMT) and several regulators of mesendoderm differentiation including T, MixL1 and Eomes (Izumi et al. 2007). Along with identifying genes and miRNAs with similar functions this analysis also enables identification of miRNAs regulated by a similar mechanism. For example members of the miR-200 family which are all found in the primitive streak cluster (cluster 2) are regulated by c-Myc (Lin et al. 2009a). Also both miR-675 and miR-574 from the ’ECM’ cluster are both regulated by Sox9 (Guerit et al. 2013; Dudek et al. 2010). Many other miRNAs in these cluster may also be regulated by a similar mechanism. However this analysis was not able to identify the mechanism of regulation and both Sox9 and c-Myc were not co-expressed with the miRNAs they regulated.

Chapter 4 126 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

4.3.2 MicroRNA Target Interaction Analysis

MicroRNA-target interaction analysis was used to identify miRNAs that may be key regulators of hESC-directed chondrogenesis. In order to overcome large number of false-positive miRNA-mRNA interactions predicted by current target prediction algorithms, co-expression data was included (Vila-Casadesus´ et al. 2016), knowing miRNAs predominately act to promote target mRNA degradation (Guo et al. 2010), it was assumed miRNA-mRNA pairs will be negatively correlated. This analysis identified several confidently predicted miRNA-mRNA interactions in hESCs and hESC-derived chondroprogenitors (Figure 4.6B-C). Mainly miRNAs transcribed from the large cluster of miRNAs on chromosome 19 (CM19C) were identified with highly likely interactions in hESCs (Figure 4.6B), gene ontology enrichment analysis identified targets were enriched with ’epigenetic regulators’. Also both arms of the miR-542 miRNA were identified with highly likely interactions, possibly acting to modulate ECM organisation. However there are several limitations with the approached used, such as that it will fail to identify several other types of miRNA-mRNA interactions, including: miRNA-mRNA interactions which are co-expressed e.g. several miRNAs transcribed from Hox genes target Hox mRNAs (Yekta et al. 2008) and miR-mRNA interactions which lead to decreased translational efficiency rather than mRNA degradation. Notably, it failed to identify any already know regulators of hESC pluripotency or chondrogenesis e.g miR-302a cluster which regulates the pluripotency state. Another consideration is, whether the interactions identified from this analysis are more likely to be real targets and have biological significance, this has yet to be validated. One way this method could be tested for its ability to predict more accurate miRNA-mRNA targets, is by comparing results from real-biological data to randomised data, and verifying the number of accurately predicted miRNA-mRNA interactions using databases of previously validated miRNA-mRNA interactions, such as TarBase (Vergoulis et al. 2012). This analysis may not be appropriate for the analysis of hESC-directed differentiation as the two states examined, hESCs and hESC-directed chondroprogenitors, may be too different. Many of the genes with strong negative correlation to hESC-miRNAs may not be expressed in hESCs. It may be more appropriate for analysis of subtle changes between the intermediate stages of hESC-directed chondrogenesis i.e. between stage 0 and 2, and stage 2 and 3 of the DDP.

4.3.3 Conclusion

In summary, using a combination of co-expression, gene ontology enrichment analysis and protein-protein network analysis of hESC-directed chondrogenesis identified the

Chapter 4 127 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells following; i) several clusters of highly co-expressed genes and miRNAs with similar biological functions including a ’pluripotency’ cluster, ’primitive streak’ cluster, ’ECM’ cluster and ’limb development’ cluster, ii) several co-expressed miRNAs which were regulated by a similar mechanism and iii) several potential novel regulators of hESC-directed chondrogenesis.

Chapter 4 128 Chapter 5

Results III - Exosomes

5.1 Aims and Introduction

The previous two chapters have highlighted the large regulation genome wide trends in the change in miRNA expression during hESC chondrogenesis. In this chapter we investigated the role of exosomal miRNAs during hESC directed chondrogenesis and during pluripotency as they may be novel regulators of these processes. Exosomes are small extracellular vesicles formed in multivesicular bodies (MVB) and subsequently released from cells upon fusion of MVBs with cell membrane. Unlike microvesicles, which are formed from the shedding of the cell membrane, exosomes are enriched with specific proteins, mRNAs, miRNAs and lipids (Section 1.7.3). As mentioned in Section 1.7.7, exosomes have been shown to have a plethora of functions, most recently their role in cell-cell communication has been studied as it has been shown that exosomes can transfer miRNAs to neighbouring cells and that these miRNAs can subsequently target mRNAs in the acceptor cells leading to downstream effects (Thery´ et al. 2002). We hypothesise that specific miRNAs may be packaged into exosomes during chondrogenesis and that they may aid the differentiation of hESCs. These exosomal-enriched miRNA they may aid in promoting consistent differentiation during the process of chondrogenesis. To this end small RNA sequencing was performed on RNA isolated from exosomes derived from pluripotent stem cells and hESC-derived chondroprogenitors as well as the cells exosomes were isolated.

5.2 Results

5.2.1 Exosome validation

Exosomes were isolated from pluripotent stem cell culture medium by ultracentrifugation and efficiency was validated using several techniques. Western blot analysis confirmed the presence of the well-established exosomal marker CD63 and the lack of cellular marker GAPDH in exosomal lysates, with the reverse of this observed for cellular lysates from Hues1 hESCs (Figure 5.1A). Transmission electron microscopy verified the enrichment and purity of exosomes derived from Hues7 hESCs, which exhibited a similar size and morphology to the exosomes from previous reports (Pan et al. 1985), showing a

129 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells cup-shape morphology and a diameter of roughly 100nm (Figure 5.1B). Dynamic Light Scattering (DLS) verified that exosomes isolated from several different pluripotent stem cell lines (hESC lines Hues7, Man7, Man11 and Man13; iPSC lines SW144M and TS141G) and hESC-derived chondroprogenitors showed similar size distribution range between 100-200nm (Figure 5.1C). Exosomes isolated from iPSC lines TS141G (generated by Dr Steven Woods and Thameenah Choudhury from HDFs) and SW144M (generated by Dr Steven Woods from COMP mutant ligament cells) were smaller (highlighted in green) compared to exosomes isolated from Hues1-derived chondroprogenitors and embryonic stem cell lines Man7, Man11 and Man13 (Figure 5.1C). A smaller peak was observed in most samples at 8000nm possibly due to sample aggregation, it is unlikely to be from larger microvesicles as conditioned medium is filtered during exosome isolation protocol to remove particles larger than 0.22µm. In future experiments samples could be pipetted or vortex before DLS measurements are taken as to remove larger peaks caused by aggregation. During the course of experiments exosomes were stored at -80°C for long periods of time. To verify this did not affect sample quality, the size distribution of exosome samples was assessed after storage at -80°C. Figure 5.1D shows there was no change in size distribution of exosomes stored for 5 weeks or 47 weeks at -80°C. It was concluded that the preparations isolated may be considered a pure population consistent with exosomes reported in the literature and remained stable up to 47 weeks when stored at -80°C.

Chapter 5 130 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

A Hues1 B Hues7

C D Cell.Line 16 16 Hues7 (n=4) Storage Man7 (n=3) 47 weeks Man11 (n=3) 5 weeks Man13 (n=6) Cell.Line Hues1−Chondro (n=2) Man11 (n=1) 12 12 SW144M (n=3) Man13 (n=1) TS141G (n=3)

8 8 Percentage Percentage

4 4

0 0 10 100 1000 10 100 1000 Size (nm) Size (nm)

Figure 5.1: Validation of exosomes isolated from pluripotent stem cells (PSCs). (A) Western blot of exosome and cell lysate from Hues1 hESCs shows enrichment of exosomal marker CD63 in exosome samples. GAPDH used as loading control. (B) Transmission electron micrograph of exosomes isolated from Hues7 hESCs grown feeder-free showing exosome morphology and size. (C) Dynamic Light Scattering of exosomes isolated from embryonic stem cells (Man7, Man11 and Man13), iPSC lines (SW144M and TS141G, highlighted in green) and Hues1-derived chondroprogenitors (in red). Shows size distribution of exosome preparations from various cell types is between 100-200nm. (D) Dynamic Light Scattering of exosomes isolated from embryonic stem cells (Man11 and Man13) after different durations of storage at -80°C.

5.2.2 Expression of miR-302a in Pluripotent stem cell derived exosomes

As mentioned in Section 1.7.7, many studies have investigated the ability of exosomes to shuttle miRNAs between cells. Therefore, to identify exosomal-enriched miRNA and their role in differentiation of pluripotent stem cells, miRNA expression was investigated in exosomes derived from pluripotent stem cells. Exosomes were isolated from the three different hESC lines, Man7 (n=2), Hues1 (n=2), Hues7 (n=4), and two iPSC lines, TS141G (n=3) and SW144M (n=2), along with two hESC line-derived chondroprogenitors, Man7-chondroprogenitors (n=2) and Hues1-chondroprogenitors (n=1) using the DDP. Real-Time PCR showed high levels of the pluripotency associated miRNA, miR-302a-5p, in exosomes from pluripotent stem cells and loss of miR-302a-5p as the cells undergo chondrogenic directed differentiation (Figure 5.2A). This corresponds to what is observed in the cell RNA from the whole cell RNA-seq data (Figure 5.2B). Interestingly the level of miR-302a appeared lower in exosomes derived from iPSCs although this was not statistically significant.

Chapter 5 131 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

A miR-302a-5p B miR-302a-5p

1500 hESCs 150000 hESCs 1000 iPSCs Chondro-hESCs 500 Chondro-hESCs

100000 60

40 50000 Read count 20

0 0 Expression Relative to RNU19

Man7 (n=4) Hues7 (n=4)Hues1 (n=2)Man7 (n=2) Hues1 (n=2) TS141GSW144M (n=3) (n=2)

Man7 Stage 3 (n=4) Man7 StageHues1 3 Stage(n=2) 3 (n=1) Hues1 Stage 3 (n=2)

Figure 5.2: MicroRNA expression of pluripotent stem cell-derived exosomes (A) RT-qPCR of exosomes isolated from pluripotent hESCs, iPSCs and hESC-chondroprogenitors (B) Expression of miR-302a in hESCs during directed chondrogenesis.

5.2.3 Exosome qPCR optimisation

For initial exosome experiments, RNA was isolated from exosomes suspended in PBS by direct lysis (Figure 5.3A, right). This allowed for fast RNA isolation and the remaining exosome sample could be used for further downstream analysis. However, as the RNA was not purified it could not be accurately quantified. It was assumed that little variation existed in; RNA content between exosomes, the number of exosomes within medium conditioned for a specified amount of time, and the rate at which different cell types release exosomes. Therefore for initial exosome experiments, RNA was isolated from exosomes conditioned in a consistent volume of medium (2ml) and for a specified length of time (24hrs). Based on these assumptions, the quantity of RNA could then be compared between samples and the relative miRNA levels could be assessed by RT-PCR. This was an adequate method for determining whether specific miRNAs were found in exosomes. However, large error bars prevent subtle differences from being detected seen in Figure 5.2A. This large variation between biological replicates is likely attributable to variation in initial RNA concentration and/or use of a unsuitable RNA control to normalise the differences in RNA levels. To evaluate if our assumptions in the previous paragraph were correct, we quantified exosomes isolated from hESCs and iPSCs by protein assay. This showed values ranging from 1.00-5.83µg/ml of exosomal protein isolated per volume of conditioned medium (n=7). This strongly suggests that the quantity of exosomes isolated were significantly different between different cell lines, with significantly more exosomal protein isolated from similar volumes of conditioned medium for Hues7 compared with iPSCs (p=0.003) and Hues1 (p=0.0471) (Figure 5.3B). However, this may

Chapter 5 132 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells also be due to differences in cell confluency as values where not normalised to cell numbers. The iPSCs were particularly low confluency at time of medium collection (10-20%) compared with hESCs, as they were grown as colonies and not a monolayer as for Hues1 and Hues7. Medium from the two hESCs lines, Hues7 and Hues1 was added to cells when they were at similar cell confluency (80-90%) but cell numbers at time of medium collection may have differed. Therefore, the observed differences may not be biologically relevant but rather methodological and a reflection mainly in differences between hESC line proliferation rates and not of exosome release. Due to the observed variation in exosome quantity it was essential to use a suitable small RNA control to normalise RNA levels. In initial experiments RNU19 was used as a small RNA control as it had previously been able to normalise cellular RNA levels effectively as it showed high and stable expression during chondrogenesis (data not shown). However Ct values of RNU19 for exosomal RNA samples showed large variation in levels especially in comparison to miR-302a-5p, and it was detected at low levels with an average Ct value of 33.95 (Figure 5.3C-D). We further assessed the use RNU19 as a small RNA control for exosomal RNA by comparing its relative expression to the exosomal protein concentrations from the same samples. Interestingly, the exosome concentration for a given sample did not correlate to relative expression of RNU19, which should have consistent expression levels across different samples (Figure 5.3E). However, exosomal protein was correlated to the relative expression of miR-302a-5p (R2=0.8662, omitting one outlier) (Figure 5.3F). This data from exosomes isolated from hESCs and iPSCs where miR-302a expression is expected to remain relatively constant as it had previously been shown to be consistently expressed in pluripotent stem cells (Wilson et al. 2009; Ren et al. 2009; Morin et al. 2008).

Chapter 5 133 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Conditioned media A B 8 * * ** Exosome Isolation 6

Direct RNA lysis Resuspend 4 (miRvana RNA isolation kit) (in 10ul PBS/ml of conditioned media and store -80ºC) 2 Quantify RNA RNA lysis Exosomal Protein isolated per (QuantiFlour RNA) (10ul exosome prep + 12.3ul lysis buffer) 0 Volume of Conditioned media (ug/ml) media Conditioned of Volume

1ng 5ul

Hues1 (n=2) Hues7 (n=2) iPSCs (n=3) TaqMan qPCR C D RNU19 miR-302a-5p 40 40

35 35

30 30 Ct value Ct value 25 25

20 20

Hues7 (n=4)Hues1 (n=2)Man7 (n=2) Hues7 (n=4)Hues1 (n=2)Man7 (n=2) TS141GSW144M (n=3) (n=2) TS141GSW144M (n=3) (n=2)

Man7 StageHues1 3 Stage(n=2) 3 (n=1) Man7 StageHues1 3 Stage(n=2) 3 (n=1) E F RNU19 miR-302a-5p 4×10-11 outlier 1×10-8

3×10-11 R2=0.8662 -11 2×10 5×10-9

-Ct RNU19 2

R =0.1553 -Ct miR-302a 2 -11 1×10 2

0 0 0 2 4 6 0 2 4 6 ug exosomes/ml media ug exosomes/ml media

Figure 5.3: Correlation of hESC-exosomal RNA expression with total protein (A) Workflow diagram showing different methods of exosomal RNA isolation used. (B) Barchart of exosomal protein isolated per volume of conditioned medium from different pluripotent stem cell lines. Error bars represent s.d. (n=3). Student’s t-test; *P-value<0.05; **P-value<0.01. Ct values of RNU19 (C) and miR-302a-5p (D) from exosomes. Correlation of exosome protein isolated with relative expression of RNU19 (E) and miR-302a-5p (F).

Chapter 5 134 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Due to variation in exosome isolation between samples it was important to be able to accurately quantify the exosomal RNA isolated. Therefore, in following experiments exosomal RNA isolations were performed by phenol extraction followed by purification on a glass fibre filters, as shown in Figure 5.3A, then RNA concentrations were quantified by a flourometric assay. In addition to improved quantification of RNA concentrations, a better small RNA control than RNU19 was also needed. Ideally a small RNA control would have high and stable expression across all samples. RNU19 is a small nucleolar RNA (snRNA) and as such is localised in the nucleus and this may prevent it from getting packaged into exosomes at the same rate as cytoplasmic miRNAs. The detection of RNU19 in exosomal RNA samples may be from contaminating apoptotic bodies and not exosomes. It has been shown the snRNA U6 is a poor endogenous control for serum miRNA levels (Xiang et al. 2014). Therefore, a better choice for a small RNA control would be a miRNA, miR-16 has been shown to be a suitable small RNA control for normalising RNA levels in cancer cells (Davoren et al. 2008; Peltier and Latham 2008) and has been used for normalising exosomal serum levels (Matsumura et al. 2015) and its expression in serum is unaltered by freeze-thaw cycles (Xiang et al. 2014). To evaluate the use of miR-16 as a small RNA control for normalising exosomal RNA during chondrogenesis, cells were differentiated into chondroprogenitors using the DDP (this was performed by Dr. Christopher Smith) and exosomes were isolated on days 0, 5, 9 and 13 of the protocol and relative expression levels of miR-16 and RNU19 were analysed. Two parallel experiments were performed: in one the cells were cultured on vitronectin coated plates and in the other cells were cultured on fibronectin coated plates (n=1 for each). In both experiments, miR-16 showed much higher levels of expression than RNU19 and showed less variable expression throughout the protocol (Figure 5.4A-B). By day 5 of the protocol, there was sufficient medium to perform two exosome isolations. To assess which small RNA would better normalise differences in technical variation, the fold change of miRNAs between the two batches normalised to either miR-16 or RNU19 was compared (Figure 5.4C-D). Lower mean fold change was observed for the batch-to-batch comparison, in both the fibronectin (Figure 5.4C) and vitronectin (Figure 5.4D) experiment, when miRNA expression was normalised to miR-16 compared to RNU19. Therefore, miR-16 was better able to normalise the technical variability between the two batches than RNU19. The importance of using a good small RNA control was particularly apparent when examining the exosome miRNA expression pattern during chondrogenesis observed using different small RNA controls (Figure 5.4E-F). Normalising exosomal miRNA expression to miR-16 showed the expression pattern of miR-302a and miR-145 was not affected by

Chapter 5 135 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells culture on vitronectin or fibronectin. However, exosomal miR-145 expression increased between day 9 and 13 during DDP culture on vitronectin and the opposite was seen when culture on fibronectin (Figure 5.4E). Whereas, when miRNA expression was normalised to RNU19 all miRNAs assayed showed increased expression at day 13 when cultured on fibronectin compared to vitronectin (Figure 5.4F). In summary, we showed that variation existed in the quantity of exosomes isolated from same volume of medium conditioned for the same duration of time. This may be accounted for by normalising to cell number or may be cell line dependant. Due to these variations, it is important to quantify exosomal RNA isolated and to use a suitable small RNA control to normalise RNA levels especially since the choice of small RNA control used can affect the miRNA expression profile observed. Here we show the following reasons why miR-16 is a better small RNA control than RNU19 to normalise exosomal miRNA expression levels to; it had a higher level of expression, its expression was less variable in hESCs and during hESC directed chondrogenesis, its expression correlated to exosome quantity, it can more effectively normalise out technical variation.

Chapter 5 136 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

A miR-16 B Fibronectin (n=1) Vitronectin (n=1) miR-16 RNU19 40 40 RNU19

35 35 Ct Value Ct Value 30 30

0 5 9 13 0 5 9 13 Day of DDP Day of DDP C D FN miR-145 VTN miR-145 1.5 miR-205 1.5 miR-205 miR-302a miR-302a 1.0 1.0

0.5 0.5

0.0 0.0 (Batch1/Batch2) (Batch1/Batch2) Log2 Fold Change Log2 Fold Change

-0.5 -0.5

RNU19 miR-16 RNU19 miR-16 FN VTN E F miR-205 miR-205 6 miR-145 miR-145 2000 miR-302a miR-302a 5 1500 4 3 1000 2 500 1 60 0.2 40 0.1 20 0.0 0 Expression relative to RNU19 Expression relative to miR-16 0 5 9 0 5 9 13 13 Day of DDP Day of DDP

Figure 5.4: Expression of small RNA endogenous controls during hESC directed chondrogenesis. Ct values of miR-16 and RNU19 from exosomes isolated during hESC directed chondrogenesis culture on fibronectin coated plates (A) or vitronectin coated plates (B). Log2 fold change of batch variation of miR-145 (green), miR- 205 (orange) and miR-302a (red) relative to either RNU19 or miR-16 at day 5 of the directed differentiation protocol (DDP) cultured on fibronectin coated plates (C) or vitronectin cultured plates (D). MicroRNA expression profile of miR-145 (green), miR-205 (orange) and miR-302a (red) during the DDP cultured on fibronectin coated plates (dashed line) or vitronectin coated plates (solid line) expression relative to miR-16 (E) or RNU19 (F). FN, fibronectin; VTN, vitronectin.

Chapter 5 137 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

5.2.4 Exosomal miRNAs in hESC directed chondrogenesis

To identify novel chondrogenic miRNAs enriched in exosomes, RNA-seq was performed on exosomes and their donor cells for both pluripotent hESCs and hESC-derived chondroprogenitors. Cultures of the hESC line Man7 were differentiated into chondroprogenitors using the directed differentiation protocol (n=3). Exosomal RNA and cellular RNA was isolated from starting stem cells and cells from the end stage of the protocol (Figure 5.5A). Real-Time PCR of cellular RNA was used to confirm that chondrogenesis had taken place, as shown by the gain of cartilage markers SOX9, ACAN and COL2A1, along with loss of pluripotency associated markers Nanog and miR-302a-5p (Figure 5.5C). Real-Time PCR confirmed an enrichment of the previously identified exosomal miRNAs miR-205 and miR-125b-1-3p (Villarroya-Beltri et al. 2013) in RNA isolated from exosomes compared with RNA isolated from donor cell, and is good evidence supporting that the isolated RNA is exosomal (Figure 5.5B). However, enrichment of two miRNAs that had been previously reported to not to be enriched in exosomes, miR-181a and miR-302a (Taylor and Gercel-Taylor 2008; Villarroya-Beltri et al. 2013), was also observed in isolated RNA. This may be an artifact of the miRNA used to normalise miRNA expression; if miR-16 was cell enriched, exosomal enrichment of miRNAs would appear higher in comparison. Examining the amount of exosomal enrichment shows miR-205-5p and miR-125b-1-3p are exosomal enriched in RNA samples. Exosomal enrichment of miR-205-5p and miR-125b-1-3p, were significantly higher than exosomal expression of miR-302a in pluripotent-derived exosomes (p=0.0077, p=0.0432 respectively). Similarly, exosomal enrichment of miR-125b-1-3p, was significantly higher than miR-181a-5p in chondroprogenitor-derived exosomes (p=0.0239). All cellular RNA was shown to be high quality when assessed by size distribution on a TapeStation (Agilent). Based on the size distribution of each sample, an RNA Integrity Number (RIN) is given, RINs rate RNA quality on a scale ranging from 1 (worst) to 10 (best) (Schroeder et al. 2006). All cellular RNA samples were of a high quality with an average RIN of 9.82 and a range of 9.5-10.0 (Figure 5.5B). The Real-Time PCR and TapeStation analysis described above provide strong evidence that successful chondrogenesis had taken place and that the cellular RNA samples were of a high quality. The constitution of the exosomal RNA samples was consistent with previously reported exosome miRNA expression. Therefore, these samples were of a good enough quality to proceed with small RNA-sequencing.

Chapter 5 138 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

A B bio.rep 1 bio.rep 2 bio.rep 3 L d0 d14 d0 d14 d0 d14 Pluri exo (n=3) Chon exo (n=3)

6000 4000 DDP hESCs Chondroprogenitors 2000 1000

Pluri cell (n=3) 500 Chon cell (n=3) 200

25 RIN 10.0 9.8 9.5 9.9 9.9 9.8 C D Stage 3 vs. Stage 0 Exosomes vs. Cell Stage 0 5 * 15 * * Stage 3 10 * 0 *

5 * * -5 0 Log2 Fold Change Log2 Fold Change

-10 * -5

Nanog ACAN SOX9 COL2A1 miR-205-5p miR-302a-5p miR-181a-5p miR-302a-5p miR-125b-5p miR-125b-1-3p

Figure 5.5: Validation of hESC-directed chondrogenisis and isolation of exosomal miRNAs (A) Experimental plan for RNA-sequencing of exosomes during hESC-directed chondrogenesis. (B) Tapestation analysis of cellular RNA quality. All samples analysed showed high RNA quality as indicated by high RNA Integrity Number (RIN) values. (C) RT-PCR of key cartilage markers (COL2A1, ACAN and SOX9) and pluripotency markers (Nanog and miR-302a-5p) of stage 3 cell samples relative to stage 0. Shows cells gain a chondrogenic phenotype and a loss of pluripotency. (D) TaqMan RT-PCR of miRNA expression in exosomes during DDP relative to cell. Student’s paired t-test; *P-value<0.05. Error bars indicate standard error of mean (SEM). Gene expression relative to GAPDH. MicroRNA expression relative to miR-16-5p.

5.2.5 Exosomal Sequencing Quality

Analysis of the sequencing quality showed that 96.23% of sequences had a Phred score greater than or equal to 30 indicating a base call accuracy of at least 99.99% (Figure 5.6A). After adapter trimming, all cellular RNA samples had a major size peak at 22bp, the expected size of mature miRNAs. Conversely, exosomal RNA samples showed a major size peak at 16bp, outside the range expected for miRNAs (Figure 5.6B). Examining the top overrepresented sequences in all samples revealed 40.91% of exosomal RNA reads contained the sequence ’GTTCCCGTGG’. This is significantly higher than the 1.44% observed in the cellular RNA samples (Figure 5.6C). This sequence is contained within the Illumina stop oligo (Figure 5.6C) which is added after the 3’ adapter ligation step of the

Chapter 5 139 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells small RNA sample preparation suggesting that its increased abundance may be due to the small amount of starting RNA for the exosome samples. Trimmed and filtered reads were then mapped to miRbase 21, for the exosomal samples only 1.29% of the filtered reads mapped to miRBase compared to 28.31% in cellular RNA samples (Figure 5.6D). This 22-fold change difference in mapping is possibly due to large percentage of exosomal reads being accounted for by the stop oligo. Despite these large differences in miRNA read depth, after filtering for miRNAs with at least 1 read per million in at least 3 samples 965 miRNAs were found to be present in exosomes. Of these, 559 were present in at least one exosome sample with at least 1 count per million. Libraries were normalised using the Trimmed Mean of M values (TMM) method to account for differences in sample miRNA read depths. In summary, all sequencing reads show good quality however there is a large difference in miRNA read depth between libraries for cell and exosome samples, possibly due to the limited amount exosomal RNA available as starting material.

Chapter 5 140 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Figure 5.6: Exosomal small RNA-seq quality control. (A) Cumulative distribution of the per sequence Phred quality score of all samples. Shows both exosomal RNA (black) and cellular RNA (grey) samples showed a similar quality of sequencing with the Phred quality score of the majority of reads greater than 30. B. Size distribution of sequencing read lengths after adapter trimming. Exosomal RNA (black) trimmed reads size show a peak at 16bp in comparison to cellular RNA (grey) samples at 22bp. (C) Percentage of adapter trimmed reads containing part of the Illumina stop oligo sequence (below, section highlighted in bold). Exosomal RNA reads show a significantly higher amount of reads containing the stop oligo sequence. The top overrepresented sequence in exosomal reads is a 16bp section of the stop oligo (underlined). (D) Summary of the mapping of filtered reads to miRbase 21. Exosomal RNA samples display much lower mapping to mature miRNAs possibly due to a larger quantity of the reads mapping to the Illumina stop codon.

Chapter 5 141 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

5.2.6 RNA-seq Cluster Analysis

Despite the low miRNA total read count for the exosome samples, Principal Component Analysis (PCA) revealed good clustering of biological repeats as shown in Figure 5.7A. Similarly, hierarchical clustering of the 30 top expressed miRNAs also showed good clustering of biological replicates, with the samples first separating out by stage of the protocol and then by sample type (Figure 5.7B). The 30 top expressed miRNAs in the exosome sequencing data included many of the miRNAs found to be top expressed in the previous RNA-seq experiment from cellular RNA (Figure 3.5A). These included miR-92b, miR-21-5p, miRNAs from the miR-302 cluster (miR-302a/b/c/d-3p and miR-302a-5p), Hox miRNAs (miR-10a-5p and miR-10b-5p) and miRNAs from the miR-17-92 cluster (miR-19b-3p and miR-92a-3p) (Figure 5.7B, right). Differential expression analysis of the cell samples revealed 219 miRNAs which were significantly modulated between stage 0 and stage 3 of the DDP (FDR <0.05). This new sequencing data showed substantial overlap with the earlier cell RNA-seq experiment. When data was filtered for miRNAs differentially expressed by a fold change of at least 4 and with a FDR <0.05, 43 upregulated miRNAs and 110 downregulated miRNAs between stage 0 and stage 3 of the DDP were revealed, of which 28 and 78 of these respectively were differentially expressed between stage 0 and 3 of the DDP in the earlier RNA-seq experiment of Man7 chondrogenesis (Figure 5.7C-D). In summary, this showed that samples clustered well with their biological replicates and cellular RNA samples showed good overlap with findings of previous cell RNA-seq experiment (Figure 3.5A). Therefore, there was enough confidence in the quality of the RNA-seq samples to proceed with further downstream analysis.

Chapter 5 142 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells 12 ● ● ● 8 ● ● ● ● ● ● ● ● 74 ● 4 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Orginal data ● ● ● ● ● ● ● ● ● ● ● ● ● ● − 4 Fold Change (0 vs. 3) ● ● ● ● ● ● 2 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Log ● ● ● ● ● − 8 ● ● ● ● ● ● 86 − 12 8 4 0

12 − 4 − 8

2 2 − 12 Fold Change (0 vs. 3) vs. (0 Change Fold Log C data New (A) Principal component analysis (PCA) of exosomal and cellular samples. Shows 0.05). (D) Venn diagram showing overlap of earlier RNA-seq experiments with exosome RNA-seq < cell exo Chon cell exo Pluri B a cell exo c Chon 65 20 b cell exo new Pluri 86 10 Down c a original 45 c b ● a ● 0 86 ● new PC1 21.98% Variance 74 b Up − 10 c 126 ● original b a ● ● − 20 D 0

20 10

− 10 PC2 19.26% Variance 19.26% PC2 A Figure 5.7: Qualitysamples assessment separating of out exosomal by both cellularUnsupervised RNA small-RNA origin clustering seq and of cell libraries sample typemiRNAs by with differentially shows cluster expressed good samples in clustering analysis. both separating of theexperiment. biological out original repeats. data first (B) (x-axis) by Heatmap and of stage new the data of log (y-axis) the transformed (FDR normalised protocol readcounts then of by the top type 30 (top). expressed miRNAs. (C) X-Y scatter graph of the log2 fold change between stage 0 and 3 of

Chapter 5 143 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

5.2.7 Exosome-enriched miRNAs from hESCs and chondroprogenitors

Differential expression analysis was performed to find miRNAs enriched or reduced in abundance in exosomes compared with the cell population from which they were derived. This revealed 71 miRNAs enriched in pluripotent exosomes compared with their donor cells and 55 miRNAs enriched in chondrogenic exosomes compared to their donor cells (Figure 5.8A-B). Possibly due to the low read count for the exosome samples, many of the miRNAs expressed in cell samples were not expressed in any of the exosome samples. Examination of miRNAs with an expression level of at least 1 count per million revealed 679 miRNAs that were expressed in the pluripotent cellular samples and not found to be present in pluripotent exosome samples (Figure 5.8C). Similarly, 577 miRNAs expressed in the chondrogenic cellular samples had were not present in any chondrogenic exosome samples (Figure 5.8D). Analysis of exosome enrichment in hESCs showed the main pluripotency-associated miRNAs, the miR-302 cluster (Card et al. 2008; Subramanyam et al. 2011), were significantly cell-enriched (Figure 5.8A). Similarly the most well characterise cartilage miRNA, miR-140 (Tuddenham et al. 2006) was also cell-enriched in hESC-chondroprogenitors (Figure 5.8B), possibly suggesting more functional miRNAs are retained within the cell. If true the other cell-enriched miRNAs may be also be functional. For example, the other chondroprogenitor cell-enriched miRNA identified miR-331-3p may also have a role in regulating chondrogenesis (Figure 5.8B). MicroRNA-331-3p may regulate chondrogenesis by targeting ERBB2 (Epis et al. 2009; Epis et al. 2011) an epidermal growth factor receptor which has been shown to regulate chondrocyte proliferation and maturation (Fisher et al. 2007).

Chapter 5 144 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

A Pluripotent B Chondro no reads in exosome samples

miRNA Key Pluripotency Cartilage Cell enriched Cell enriched Exosome enriched Exosome enriched

log2Fold Change log2Fold Change Pluripotent D Chondro C Cell Exo Cell Exo

679 361 54 577 497 42

Figure 5.8: Pluripotent and chondrogenic exosomal enrichment of miRNAs Barchart displaying all differentially expressed miRNAs between exosomes and cell RNA from pluripotent (A) and chondrogenic (B) samples (FDR<0.05). miRNAs with an increased fold change are enriched in cell in comparison to their derived exosomes. miRNA bars have been highlighted blue or red if they have been associated with pluripotency or cartilage, respectively, in the literature.

Chapter 5 145 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

5.2.8 Exosomal miRNA motif enrichment

It has been previously reported that exosomal miRNAs are enriched for the motif ’GGAG’ predominantly found in the 3’ half of the miRNA (Villarroya-Beltri et al. 2013). This motif acts as a recognition site for hnRNPA2B1 to direct the packaging of specific miRNAs into exosomes. To test whether the same motif was observed in our data, motif discovery analysis was performed on miRNAs enriched in pluripotent exosomes only (n=38), chondrogenic exosomes only (n=22) or found enriched in both pluripotent and chondrogenic exosomes (n=33) (Figure 5.9A). Of these three groups of miRNAs, an enriched motif was only discovered in the miRNAs enriched in both pluripotent and chondrogenic cells (Figure 5.9B). This significantly enriched motif, ’CGGSG’, is very similar to the previously reported exosomal motif ’GGAG’ (Villarroya-Beltri et al. 2013). Motif distribution analysis showed that the ’CGGGG’ motif was most likely to occur in the 5’ end of the miRNA whereas the ’CGGCG’ motif was equally distributed throughout the miRNA (Figure 5.9C). In summary, miRNAs that are found to be upregulated in both pluripotent and chondrogenic derived exosomes compared with their donor cell expression were enriched with the motif ’CGGCG’ or ’CGGGG’, of which the latter is most likely to occur in the 5’ end of the miRNA compared with other locations.

A B C 6 Motif Distribution Pluri Chon Common CGGGG n=71 n=55 CGGCG 4

38 33 22 2 Occurance of motif

E value = 0 1.0e-6 2 4 6 8 10 12 14 16 18 20 22 Postion in miRNA

Figure 5.9: Motif enrichment analysis of exosome-enriched miRNAs (A) Venn diagram showing the overlap of significantly enriched (FDR<0.05) exosomal miRNAs from pluripotent stem cells and chondroprogenitors. (B) Over-represented motifs in exosome-enriched miRNAs. DREME analysis used to discover short, ungapped motifs that are relatively enriched in both pluripotent and chondrogenic exosomes (n=33, Common), in comparison to all miRNAs expressed (n=965). E-value shown below motif. (C) Histogram showing motif distribution of the two motifs; ’CGGCG’ (blue) and ’CGGGG’(yellow).

5.2.9 Pathway analysis of exosomal enriched miRNAs

To investigate the function of these enriched exosomal miRNAs (n=33), their targets were predicted using the following target prediction algorithms; TargetScan (context score <- 0.4), DIANA microT-CDS (miTG score >0.9) and miRanda (miRsvr score<-1.1). The list of

Chapter 5 146 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells predicted targets (n=5115) were then upload to the Pantherdb web server for gene ontology (GO) analysis. Gene ontology analysis revealed the predicted targets were most enriched with genes with the GO term ’Embryonic skeletal system development’ (fold enrichment = 2.04, p=0.00228 Bonferri corrected). The network of all exosome-enriched miRNAs which contain target genes that belong to the GO term ’Embryonic skeletal system development’ is shown in Figure 5.10A. Of particular interest were miRNAs, miR-1323, miR-744-5p and miR-877-3p, which had the most predicted targets belonging to the GO term ’Embryonic skeletal system development’ suggesting they may be regulating chondrogenesis (Figure 5.10B). For example, miR-1323 may be inhibiting chondrogenesis by targeting COL11A1, a collagen essential for cartilage collagen fibril formation (Li et al. 1995). However miR-1323 and COL11A1 were both downregulated during chondrogenesis suggesting this interaction was not present in the chondroprogenitors. Analysis of upregulated targets of miR-1323 shows they all have roles in lineage specification, this includes: HOXD3 a member of the HoxD cluster which regulates limb development (Zakany and Duboule 2007), GLI3 a mediator of Sonic Hedgehog signaling which also regulates limb development (Barna et al. 2005; Welscher et al. 2002) and MEF2C a transcription factor which marks skeletal muscle specification (Edmondson et al. 1994) and controls bone development (Arnold et al. 2007). Suggesting loss of miR-1323 during hESC-differentiation may promote mesodermal differentiation but not specifically chondrogenesis.

Chapter 5 147 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells -0.4), DIANA microT-CDS (miTG 59 51 39 37 34 834 676 583 315 250 6030 6001 1383 1315 Reads 96996 96089 83080 75618 56268 50258 46160 30947 17853 449641 333061 254139 < Exosome 2 3 4 1 3 2 36 58 33 10 20 28 49 16 25 10 57 10 Cell 209 135 101 698 120 301 143 154 reads

Chon.exo Chon.cell Pluri.exo Pluri.cell

% 1.1 3.7 1.4 1.3 1.5 1.4 2.4 2.6 2.4 1.0 1.2 1.2 3.8 2.0 2.8 0.5 2.4 1.9 0.8 1.8 0.7 0.7 1.3 0.9 1.8 1.3 hsa-miR-4497 0.05). The top three microRNAs with the most 84 56 80 184 108 143 310 131 370 296 156 292 103 337 106 100 145 188 413 312 488 789 143 419 613 433 < Targets Targets of Predictedof Total number Total

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

10 14 hsa-miR-7704 GO term GO targetsin Numberof

0 hsa-miR-3960

50 40 30 20 10 Percentage of Total Reads Total of Percentage miRNA miRNA hsa-miR-7704 hsa-miR-3960 hsa-miR-4497 hsa-miR-1246 hsa-miR-4508 hsa-miR-6087 hsa-miR-3196 hsa-miR-4492 hsa-miR-4532 hsa-miR-7641 hsa-miR-4516 hsa-miR-4488 hsa-miR-3195 hsa-miR-3656 hsa-miR-4449 hsa-miR-877-5p hsa-miR-744-5p hsa-miR-320b hsa-miR-1273g-3p hsa-miR-1323 hsa-miR-3651 hsa-miR-342-5p hsa-miR-877-3p hsa-miR-1248 hsa-miR-4787-3p hsa-miR-1285-5p C B HOXB2 OSR1 TULP3 hsa-miR-7704 hsa-miR-4449 HOXA9 PAX5 HOXB9 HOXC5 SHH hsa-miR-7641 hsa-miR-1285-5p SOX11 OSR2 FC 2 PRRX1 hsa-miR-3651 MMP14 hsa-miR-4532 Log SLC39A3 hsa-miR-3656 hsa-miR-877-5p SIX1 hsa-miR-3960 DLX2 hsa-miR-4787-3p HOXB8 -12 -8 -4 0 4 8 12 WNT5A hsa-miR-4492 MEN1 PAX7 TFAP2A HOXA3 SIX2 HOXD9 SP1 HOXB1 SMAD3 hsa-miR-744-5p GSC MEF2C TBX15 HOXD3 HOXC11 hsa-miR-3196 GLI3 BMP4 hsa-miR-4488 HSPG2 SULF1 .(A) MicroRNA target pathway analysis. Targets predicted with; TargetScan (context score TBX1 ALX4 NOG DLK1 FGFR2 hsa-miR-4516 HOXC6 hsa-miR-6087 MYCN hsa-miR-1323 PBX1 hsa-miR-342-5p PRRX2 SULF2 hsa-miR-3195 HOXB6 MTHFD1L hsa-miR-4508 SP3 SHOX2 hsa-miR-1273g-3p ACVR2A COL11A1 WNT9B BMI1 TWIST2 NKX3-2 T FOXC2 hsa-miR-4497 NODAL hsa-miR-320b SATB2 -1.1). Genes with a thick border are differentially expressed between stages 0 vs. 3 of the DDP (FDR HOXD4 < HOXA5 hsa-miR-877-3p MMP16 RUNX2 MBTD1 SETD2 hsa-miR-1248 EIF4A3 NIPBL DLX1 DLG1 A hsa-miR-1246 0.9) and miRanda (miRsvr score > predicted targets in thetotal GO number term of genes have each beenexsome miRNA reads circled.(B) targets is Table in of the the average all GO normalised term, exosomal (TMM) total miRNAs readcount number which of of target genes each expressed miRNA. genes during (C) belonging DDP Barchart to miRNAs of are the top predicted GO miRNAs to term expressed target, in percentage ’Embryonic exosome of skeletal samples. total system genes development’. targeted are Tables in shows the GO term, score Figure 5.10: Target enrichment analysis of exosomal miRNAs

Chapter 5 148 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

5.2.10 Cartilage Exosomes

It is well know that chondrocytes in articular cartilage have very little cell-cell contact as they are surrounded by dense extracellular matrix (Section 1.2). Therefore I propose that exosomes may provide a novel method of communication between articular chondrocytes. To test this hypothesis exosomes isolated from different stages of cartilage digestion and from human articular chondrocytes (HACs) in 2-D culture (p0) were examined (2.5.8). Exosomes were isolated from healthy cartilage tissue (n=1). Due to limited studies on the release of exosomes from cartilage tissue at the time of this study, the optimal method for cartilage exosome isolation was unknown. Therefore, exosomes were isolated from several stages of cartilage digestion as shown in Figure 5.11A. Cartilage digestion was performed by Dr. Steven Woods. Due to limited sample amount, the microvesicles isolated were not fully characterised to validate them as microvesicles however they did show similar size distribution as exosomes ranging from 10-100nm (Figure 5.11B) by Dynamic Light Scattering (DLS). The microvesicles isolated from human articular chondrocytes in culture (HACs) and microvesicles isolated after the mechanical digestion step (cutting) had a similar size distributions with peaks at 10-30nm. The size distribution was smaller than that observed for microvesicles isolated after the enzymatic digestion steps, with microvesicles isolated after the trypsin stage showing a major peak in particle size at 60nm and microvesicles isolated at the collagenase stage showing a major size peak at 100nm (Figure 5.11B). Microvesicles isolated after enzymatic digestion steps also showed a broad size distribution range possibly indicating contamination of cytoplasmic fragments also being isolated. Next, the miRNA content of the microvesicles was evaluated by RT-PCR. Due to a limited amount of sample, RNA concentrations were not quantified and instead equal volumes of exosomal RNA were used for each RT-PCR reaction. Examining the mean Ct values for all miRNAs analysed revealed microvesicles isolated after the collagenase step had much greater miRNA content as compared to all other microvesicle samples, suggesting more microvesicles were isolated during this step (Figure 5.11C). Notably, the relative expression of several miRNAs depended on the stage of microvesicle isolation. Due to the limited quantity of RNA many miRNAs were undetectable, but of the detectable miRNAs their expression varied depending on the stage of the cartilage digestion they were isolated from. For the enzymatic digestion isolations (typsin and collagenase), miR-145-5p, miR-34a-5p and miR-199a were all detectable in the microvesicle RNA samples isolated. With the microvesicles isolated after trypsin digest showing higher levels of miR-34a-5p and miR-199a and lower levels of miR-145-5p compared with microvesicles isolated after collagenase digest (Figure 5.11D-F). While

Chapter 5 149 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells microvesicles isolated from HACs and after the cartilage cutting showed a similar miRNA pattern; both showed undetectable levels of miR-145-5p and miR-34a-5p and both expressed similar levels of miR-199a (Figure 5.11D-F). In summary, this indicated that the type of microvesicle released from healthy cartilage tissue depended on the stage of cartilage digestion, with smaller microvesicles (10-30nm) isolated from HACs in culture and after the surgical removal of cartilage and larger microvesicles (60-100nm) isolated after the enzymatic digestion steps. Microvesicles isolated after enzymatic steps showed a similar size distribution and miRNA expression. Microvesicles isolated from human articular chondrocytes grown in 2D culture showed a similar size distribution and miRNA expression to those isolated after the surgical removal of cartilage from bone.

A

B 30 C HAC Chunks HACs n.d 25 Cutting Trypsin miR-125b-1 20 Collagen Digest 35 miR-34a miR-145

15 miR-199a 30 miR-16 Ct Values

Number (%) 10

25 5

0 HAC 0 20 40 60 80 100 120 140 160 180 200 Cutting Trypsin Size (d.nm) Collagenase HAC chunks

D miR-145-5p E miR-34a-5p F miR-199a 0.3 0.015 0.4

0.3 0.2 0.010

0.2

0.1 0.005 0.1 Relative to miR-16 Relative to miR-16 Relative to miR-16

n.d n.d n.d n.d n.d 0.0 0.000 0.0

HAC HAC HAC Cutting Trypsin Cutting Trypsin Cutting Trypsin

Collagenase HAC chunks Collagenase HAC chunks Collagenase HAC chunks

Figure 5.11: MicroRNA content of cartilage-derived microvesicles (A) Workflow of human articular chondrocyte isolation. Shows at what stages exosomes were isolated for further analysis. (B) Size distribution of exosomes isolated during chondrocyte isolation. (C) Ct values of all miRNAs assayed in cartilage derived exosomes. Line indicates the overall mean of all Ct values for each sample. RT-qPCR of miR-145-5p (D), miR- 34a.5p and miR-199a (E) for exosomes isolated from each stage of cartilage digestion. All expression levels are relative to miR-16. HACs, human articular chondrocytes; n.d, not detected.

5.2.11 Exosome Uptake and Localisation

For initial exosome uptake experiments, assays were performed by first labelling the exosomes by incubation with PKH26 membrane dye (Sigma). Labelled exosomes were then incubated with hESCs for 24hrs and uptake was assessed by fluorescent microscopy.

Chapter 5 150 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

An increase in the fluorescence vesicles in the cytoplasm was observed after incubation with labelled exosomes compared to a PBS control, indicating that labelled exosomes were taken up into Hues1 cells (Figure 5.12A-B). This assay is suitable for simple exosome uptake analysis however it has several limitations, such as; it does not allow live cell imaging of exosome release from donor cells, exosomes have to be isolated and labelled first which is time-consuming, PKH26 membrane dye will label all vesicles isolated not specifically exosomes and a PBS control has to be performed to assess no excess membrane dye was carried over during the exosome labelling process. To overcome these limitations a lentiviral construct was created to overexpress the exosomal marker CD63 tagged with eGFP (plasmid diagram shown in Figure 5.12C). Using this lentivirus, cells can be transduced to express the fusion CD63-eGFP protein which will then be incorporated into the exosomes, allowing them to be tracked in live cells by fluorescence imaging. To confirm the function of the lentiviral construct, the chondrosarcoma cell line SW1353 was transduced with the lentivirus. Fluorescence imaging of these cells showed the eGFP was localised within small vesicles, most likely to be multivesicular bodies (MVB) where exosomes are made (Figure 5.12E). It was important to verify that the fluorescent signal arising from isolated exosomes is from eGFP-CD63 incorporated into exosomes rather than from microvesicles containing cytoplasmic eGFP-CD63. To confirm this, exosomes were isolated from SW1353 cells expressing EF1a driven CD63-eGFP (Figure 5.12E) or CMV driven eGFP (Figure 5.12F). A stronger fluorescence signal was measured from exosomes isolated from CD63-eGFP expressing cells compared to exosomes isolated from cell expressing eGFP (Figure 5.12D). If the detected fluorescent signal in exosome preparations was from microvesicles containing cytoplasmic localised eGFP then a higher signal would be expected from the CMV-eGFP exosome samples due to the increased protein expression from a stronger promoter, and cytoplasmic localisation of uncoupled eGFP (Figure 5.12E-F). This strongly supports the suggestion that the eGFP signal arising from isolated exosomes is from the eGFP-CD63 in the cell membrane of exosomes rather than localised to the cytoplasm. In summary I have developed a lentiviral system for tracking exosomes in live cells. Exosomes appear localised to vesicles and fluorescent signal from isolated exosome samples is from eGFP incorporated into exosomes rather than cytoplasmic eGFP in microvesicles.

Chapter 5 151 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

B

C D 30

20

10

Flourescence – PBS blank 0

CD63-GFP GFP control EF1a CMV E CD63 eGFP F eGFP

Figure 5.12: Uptake analysis of exosomes (A) Immunofluorescence shows uptake of labelled exosomes by Hues1 cells (hESCs), red: PKH26 labelled exosomes, green: Tra-1-60 (pluripotency marker), blue: DAPI (nuclear stain). (B) PBS was used as a control to show no excess dye was carried over. (C) Schematic of plasmid for lentiviral expression of eGFP-CD63. (D) Barchart of relative flourescent signal from exosomes isolated from SW1353 cells expressing eGFP only or CD63-eGFP.Error bars represent standard deviation. Composite of phase and fluorescence images of SW1353 cells expressing CD63-eGFP driven by EF1a promoter (E) and SW1353 cells expressing eGFP driven by CMV promoter (F). Scale bar: 20µm.

Chapter 5 152 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

5.2.12 High-throughput Exosome Uptake Assay

When investigating the role of exosomes in cell-cell communication it is important to be able to efficiently and accurately assay the uptake of exosomes. Here we developed a high-throughput exosome uptake assay which utilises cells expressing eGFP-CD63 and high content image acquisition and analysis that can be used in either a co-culture system or by supplementation of cell culture medium-isolated exosomes. SW1353 cells are normally grown in DMEM supplemented with 10% FBS which is know to contain bovine exosomes (Stoorvogel et al. 2002). Therefore medium for exosome related SW1353 experiments was depleted of FBS-derived exosomes by an overnight ultracentrifugation as described in Section 2.5.1; this medium was termed exosome-depleted medium. Co-culture exosome uptake experiments were performed by culturing SW1353 cells in the lower compartment of a co-culture plate and, 24hrs later, plating SW1353 cells expressing eGFP-CD63 in the upper compartment (Figure 5.13A). Cells were then cultured in exosome-depleted medium for 5 days. After incubation, cells in the lower compartment were fixed with PFA and nuclei were stained with DAPI, then high content analysis of cells was performed using a Cell Insight CX5 high content screening platform (Life Technologies). This analysis showed significantly increased exosome uptake in SW1353 cells co-cultured with SW1353 cells expressing eGFP-CD63 compared to SW1353 cells cultured alone (Figure 5.13B). Next the uptake of exosomes isolated from cell culture medium was assayed. eGFP-CD63 containing exosomes were isolated from eGFP-CD63 SW1353 cells cultured in exosome-depleted medium for 3 days after which exosomes were isolated. Isolated exosomes were incubated with SW1353 cells for 3hrs in either exosome-depleted medium or medium without exosome depletion (n=4). This showed significantly more CD63-eGFP exosomes were taken up by SW1353 cells culture in exosome-depleted medium compared to exosomes taken up in medium without exosome depletion (p-value=0.0054); indicating SW1353 exosome uptake was out-competed by FBS-derived exosomes (Figure 5.13C). One of the analysed images is shown in Figure 5.13D, with focus on exosomes taken up by a SW1353 cell. In summary, we have developed a high-throughput exosome uptake assay using high content analysis and cells expressing eGFP-CD63. Using this method it is possible to quickly assay the effect different treatments have upon exosome uptake. This could aid our understanding of the dynamics of exosome uptake also using the other florescence sensors available co-localisation studies could be performed.

Chapter 5 153 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

A B p=0.0237

0.015 n=3

0.010 n=9

0.005 exosomes per cell Average number of number Average

0.000

Co-culture SW1353 only C D 0.4 p=0.0054

0.3

0.2

0.1 exosomes per cell Average number of number Average

0.0

normal

Exo-free media

Figure 5.13: Development of high-throughput exosome uptake assay (A) Schematic showing co-localisation experiment with SW1353 cells expressing eGFP-CD63. (B) Barchart showing significant increase in exosome uptake of co-culture with SW1353 cells expressing CD63-GFP compared to just SW1353 cells alone. (C) Barchart showing significant increases in exosome uptake of SW1353 incubated with CD63-eGFP SW1353 exosomes in FBS-exosome depleted exosome compared to normal DMEM with 10% FBS. (D) Immunofluorescence image from exosome incubation experiment showing uptake of eGFP-CD63 exosomes. Green, eGFP-CD63 (exosome); blue, DAPI (nuclear stain). Error bars represent standard deviation.

5.2.13 Pluripotent exosomes can effect gene expression

Very little is known about the role of hESC-derived exosomes. They have been shown to contain pluripotency associated miR-302a-5p (Figure 5.2A) and mESC-exosomes have been reported to contain mRNAs for pluripotency-associated transcription factors (Ratajczak et al. 2006). Therefore, we hypothesise that hESC-derived exosomes may play a role in promoting pluripotency. To investigate this hypothesis, pluripotency-promoting factors FGF2 or Activin A were withdrawn from our in-house feeder-free hESC medium (Section 2.2.5) to promote spontaneous differentiation, and replaced with hESC-derived exosomes (4X) (n=2). At 24hrs and 72hrs post growth factor withdrawal, RNA samples were harvested and RT-PCR was performed for pluripotency associated factors (Figure 5.14A-C), early differentiation

Chapter 5 154 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells markers (Figure 5.14D-E) and targets of miR-302a (Figure 5.14F-K). As exosomes were suspended in PBS, an equal volume of PBS was used as a negative control. There was little evidence hESCs had undergone spontaneous differentiation after growth factor withdrawal, with pluripotency transcription factors Sox2 and Oct4 showing increased expression in all samples three days post-growth factor withdrawal. However transient increases in pluripotency expression has previously been observed in ESCs during differentiation (Ahn et al. 2014) and further culture of hESCs may be required before loss of pluripotency factors is observed. There was no significant difference in expression of pluripotency associated genes (Oct4, Nanog and Sox2) in any exosome treatments. However Nanog and Oct4 expression showed a trend where their levels increased in exosome treated compared with PBS control cells 24hrs post-growth factor withdrawal (Figure 5.14A-C). There was no significant change in early differentiation markers, although addition of exosomes appears to prevent early upregulation of Brachyury (T) however this effect is lost at 3 days post growth factor withdrawal (Figure 5.14E). The most significant effects were seen when examining the change in expression of targets of miR-302a (Figure 5.14F-K; Subramanyam et al. 2011). All genes examined showed a decrease in expression after three days of Activin A substitution with hESC- exosomes, and the most significant change was observed in TGFBR2 (Figure 5.14G). In summary incubation of hESCs undergoing differentiation with pluripotent exosomes can effect gene expression. The most significant change was observed in expression of TGFBR2, a validated target of miR-302a-5p (Subramanyam et al. 2011). Further longer- term experiments could examine whether complete differentiation can be prevented with exosome addition.

Chapter 5 155 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

A OCT4 B SOX2 C NANOG

6 15 8

6 4 10

4

2 5 2 Relative to Day 0 Relative to Day 0 Relative to Day 0

0 0 0 Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo -FGF2 -ActA -FGF2 -ActA -FGF2 -ActA -FGF2 -ActA -FGF2 -ActA -FGF2 -ActA Day 1 Day 3 Day 1 Day 3 Day 1 Day 3

D GATA4 E T 1.5 20

15 1.0

10

0.5 5 Relative to Day 0 Relative to Day 0

0.0 0 Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo -FGF2 -ActA -FGF2 -ActA -FGF2 -ActA -FGF2 -ActA Day 1 Day 3 Day 1 Day 3

F TGFBR2 G RHOC H RBL2

1.5 2.0 4

* 1.5 3 1.0

1.0 2

0.5 0.5 1 Relative to Day 0 Relative to Day 0 Relative to Day 0

0.0 0.0 0 Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo -FGF2 -ActA -FGF2 -ActA -FGF2 -ActA -FGF2 -ActA -FGF2 -ActA -FGF2 -ActA Day 1 Day 3 Day 1 Day 3 Day 1 Day 3

I NR2F2 J CDKN1A K YWHAZ 15 2.5 p=0.0506 2.0

2.0 1.5 10 1.5 1.0 1.0 5 0.5 Relative to Day 0 Relative to Day 0 0.5 Relative to Day 0

0 0.0 0.0 Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo Con Exo -FGF2 -ActA -FGF2 -ActA -FGF2 -ActA -FGF2 -ActA -FGF2 -ActA -FGF2 -ActA Day 1 Day 3 Day 1 Day 3 Day 1 Day 3

Figure 5.14: Gene expression analysis of hESCs after growth factor replacement pluripotent-exosomes. RT-PCR for pluripotency associated factors (A-C), early differentiation markers (D-E) and validated targets of miR- 302a (F-K) after substitution of Activin A (ActA) or FGF2 with pluripotent exosomes for 1 day or 3 days. ActA, Activin A. Con, PBS control; Exo, Pluripotent exosomes (4X). Student’s paired t-test; *P-value<0.05. Error bars indicate standard error of mean (SEM).

Chapter 5 156 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

5.2.14 Pluripotent exosomes promote proliferation of hESCs

In order to assess whether exosomes had a functional effect, proliferation of hESCs incubated with varying concentrations of pluripotent exosomes was examined. Functional effect of pluripotent exosomes were evaluated by change in proliferation, as it was hypothesised pluripotent exosomes will function by transfer of pluripotency-associated miRNA, miR-302a which has been found in pluripotent stem cells (Figure 5.2A) and targets cell cycle regulators (Card et al. 2008; Lin et al. 2010b). The hESC line Hues1 was plated at a cell density of 3000 cells/well in a 96-well plate. During plating, exosomes isolated from iPSCs were added at varying doses (1X, 2X, 4X, 10X) and exosomes isolated from the chondrosarcoma cell line SW1353 (SW 4X) and PBS was used as a non-treated control (n=4). After 36hrs the number of viable cells was assessed using a Cell Titer Glo 2.0 assay (Promega). There was a significant increase in final viable cell number when the highest concentration of pluripotent exosomes was added (10X) compared to all other concentrations (1X, 2X and 4X) (Figure 5.15A). Also there was a slight increase in viable cells when a similar amount of pluripotent-exosomes (4X) was added to hESCs compared to SW1353-derived exosomes (SW 4X). Unfortunately the PBS control gave an equal effect as the highest concentration of pluripotent exosomes, which may be due to some inhibitory contaminant of exosome preparations. In spite of this, the relative exosome concentration added correlated linearly with the number of cells at the end point, suggesting pluripotent-derived exosomes promote cell proliferation (Figure 5.15B). Before any conclusions can be made further experiments are required using a ’mock control’; an exosome sample isolated from non-conditioned media to account for any potential contaminants isolated from media during exosome isolation procedure.

A 3000 B 2600 2500 R2=0.959 * 2400 2000 ** ** 2200

2000 Cell Number 1500 1800 Cell Number

1000 1600

1X 2X 4X 1400 10X PBS 0 2 4 6 8 10 Exosome conc. SW1353 4X

Figure 5.15: Effect of pluripotent stem cell derived exosomes of hESC proliferation. (A) Barchart showing number of viable cells of Hues1 hESCs after addition of iPSC-exosomes (red), SW1353-exosomes (blue) or PBS (grey); n=4 for each treatment. (B) X-Y scatter graph showing linear correlation of iPSC-exosome relative concentration (x-axis) with number of viable cells (y-axis). Error bars represent standard deviation (SD). Unpaired t-test; *P-value<0.05; **P-value<0.01

Chapter 5 157 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

5.3 Discussion

The field of exosome research is expanding, particularly following the observation of serum exosomal miRNAs and their potential to be used as biomarkers. Many biological functions for exosomes have been well-characterised (summarised in Section 1.7.7) however, the role of exosomes in pluripotent stem cell differentiation is yet to be clearly understood. In this study, several miRNAs were found to be enriched in exosomes of hESCs and hESC- derived chondroprogenitors that may be involved in regulation of hESC differentiation.

5.3.1 Exosome Validation and Quantification

When studying a molecular species of interest (i.e. exosomes, proteins, miRNA), correct validation and accurate quantification is essential but these criteria are not always met in exosome research. Currently, the most commonly used method for exosome quantification is by protein assay due to wide availability of reagents and ease of use. In our studies we used this method but found large variability, with a range of 1.00-5.83µg of total exosomal protein isolated per ml of conditioned medium for hESC-derived exosomes. The large range in exosomal protein quantification could be due to differences in cell number at time of isolation, differences in storage conditions before and after isolation or technical variability during exosome isolation. Other problems with the protein assay include poor sensitivity. To overcome this the microBCA protein assay (Life Technologies) was used, which allows detection of protein down to as low as 2µg/ml but requires 100µl of sample. Due to limitations in sample size and the fact that samples cannot be re-used after protein assay, samples were thus diluted 10-fold. Additionally, protein assays only provide semi-quantitative information. As exosome research has become more active new methods have been developed to allow rapid absolute quantification of exosomes. One such method is Nanoparticle Tracking Analysis (NTA), which allows detection, real-time visualisation and analysis of microvesicles in liquids. By monitoring particle Brownian motion (Dragovic et al. 2011) the size distribution and concentration of exosomes isolated from conditioned medium or biological fluids can be determined (Soo et al. 2012; Gercel-Taylor et al. 2012). In addition, exosomes labeled with fluorescent antibodies can be detected by NTA, providing information about their biochemical composition (Dragovic et al. 2011; Zhang et al. 2016). When comparing results to the literature it is important to bear in mind different techniques may report slightly different results. One study showed a variety of different size distribution and concentration for the same vesicle sample using transmission electron microscopy (TEM), conventional flow cytometry, flow cytometry dedicated to detecting submicrometer particles, nanoparticle tracking analysis (NTA) and resistive pulse sensing (RPS) (Pol et al. 2014). Another factor effecting observed sample size

Chapter 5 158 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells distribution is the flow speed used in instruments. For example different flow speeds used during NTA gave different concentrations and size distributions of samples, and as such all studies should state the flow speed used during NTA (Tong et al. 2016). New techniques such as NTA allow for more accurate quantitation and size distribution analysis of exosome samples. Together with fluorescent antibodies, proteins within samples can also be analysed. Therefore samples can be more quickly validated and simultaneously quantified in comparison to other traditional methods. Also the new methods use lower sample amounts, which is particularly beneficial for exosome studies using patient samples such as cartilage tissue. Therefore NTA would be useful in future work to allow for more accurate absolute quantification and validation of samples.

5.3.2 Accurate quantification of exosomal miRNA levels

Exosome research provides many challenges, one of which is accurately quantifying the miRNA content of exosomes. In RT-PCR gene expression is normalised to a ’house keeping gene’ that should consistently expressed at a high level across all samples. Many statistical methods have been developed to identify the best gene for normalisation (Vandesompele et al. 2002; Andersen et al. 2004; Pfaffl et al. 2004; Szabo et al. 2004). As mRNAs are much longer than miRNAs they will have different purification and amplification efficiencies compared to the target miRNA and therefore normalisation to miRNAs will not accurately reflect the levels of miRNAs. Instead, small RNAs such as miRNAs, ribosomal RNA and small nuclear RNA (snRNA) are preferentially used to normalise miRNA levels. In cellular analysis of miRNAs, RT-PCR is performed with the use of a small nuclear RNA (snRNA), such as U6 or RNU19 as a ’house keeping RNA’ to perform delta Ct analysis. However we found that RNU19 was present at exceedingly low and/or variable levels in exosome RNA samples and was therefore not suitable for use in normalisation of exosome RT-PCR (Figure 5.3 and Figure 5.4). Also RNU19 expression did not correlate to exosome quantity (Figure 5.3E). Other studies have reported similar findings for the use of snRNAs as normalisers for RT-PCR (Xiang et al. 2014; Benz et al. 2013). For example, the small nuclear RNA U6 is not expressed consistently across different patient serum RNA samples and is affected by freeze-thaw cycles (Xiang et al. 2014; Benz et al. 2013). Another problem with snRNAs is their low exosome loading compared to the levels of expression in the cell. This may have skewed the results by making miRNAs appear more exosome-enriched than they are. For example, a study showed miR-214 was enriched in endothelial-derived exosomes compared with their donor cells however miRNA expression was normalised to RNU19 and no other miRNAs were assayed (Balkom et al. 2013). Therefore it is only possible to state miR-214 is more enriched in endothelial-exosomes compared with their donor cells than the snRNA RNU19 and it is not conclusive evidence

Chapter 5 159 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells of exosomal enrichment of miR-214. The low and variable exosome levels of snRNAs may be because they are nuclear localised so are not packaged into exosomes. Moreover detected snRNAs may be from microvesicles or isolated apoptotic bodies rather than exosomes. Therefore, a better choice for a small RNA normaliser for RT-PCR would be a miRNA. Peltier et al identified the small RNAs miR-191 and miR-16 as candidates for miRNA RT-PCR data normalisation. They were more stably expressed than U6 in normal and cancer tissue (Peltier and Latham 2008). This has also been used for normalising exosomal serum levels and is unaltered by freeze-thaw cycles (Davoren et al. 2008; Peltier and Latham 2008) and has been used for normalising exosomal serum levels (Matsumura et al. 2015; Xiang et al. 2014). Similarly, miR-16 was a good normaliser for exosome miRNA expression analysis in our data as it had high a stable exosomal expression during hESC-directed chondrogenesis (Figure 5.4). However, miR-16-5p was significantly cell-enriched in the hESCs in our exosome RNA-seq experiment (Figure 5.8A). Validation of exosomal RNA samples by RT-PCR showed miRNAs miR-181a-5p and miR-302a-5p were enriched in exosome samples compared to cell samples (Figure 5.5D) despite having previously being reported to be cell-enriched or not exosome-enriched (Taylor and Gercel-Taylor 2008; Villarroya-Beltri et al. 2013). This may be because results were skewed to make them appear more exosome-enriched as a result of normalising miRNA expression. By comparing the degree of exosomal enrichment of two previously reported miRNAs (miR-205-5p and miR-125b-1-3p) to other miRNAs assayed, the RNA samples in the present study were conclusively validated as exosomal. Therefore it is important when stating if a miRNA is exosome-enriched to compare it to several non-exosome enriched miRNAs as the endogenous control may be cell-enriched and skew results. In summary small nuclear RNAs are not suitable as endogenous controls for normalising RT-PCR for exosomal miRNA expression during chondrogenic differentiation. MicroRNA-16 appears to be an adequate normaliser for exosomal RNA however it is cell enriched therefore care should taken when stating miRNAs are exosomal enriched after normalisation to miR-16-5p. This can be overcome by comparing cell enrichment to other non-exosomal miRNAs.

5.3.3 Exosomal enrichment of miRNAs

Many papers have shown the enrichment of specific miRNAs in exosomes and that they are not just a reflection of their donor cell contents (Mittelbrunn et al. 2011; Valadi et al. 2007; Eldh et al. 2010). Villarroya-Beltri and colleagues identified hnRNPA2B1 as a key protein that regulates the loading of miRNAs into exosomes binding miRNAs with the motif ’GGAG’ (Villarroya-Beltri et al. 2013). We show a similar enriched motif in our exosomal miRNAs ’CGGCG’.

Chapter 5 160 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

In the paper by Villarroya-Beltri et al., the Human miRNA Microarray V3 (Agilent) was used for miRNA profiling, which contains probes from miRbase 12.0; this includes 866 human and 89 human viral miRNAs. In contrast we mapped our sequencing data to the most recent release of miRBase (21) which has 1881 annotated human microRNAs. Of the 71 pluripotent exosome-enriched miRNAs, 51 were not present in the Human miRNA Microarray V3. Similarly 37 of the 55 chondrogenic exosome-enriched miRNAs were not present in the microarray used in the earlier study. This shows that the technology used in our work allowed for more in-depth analysis of exosomal-miRNA enrichment. In the study by Villarroya-Beltri et al., to show involvement of the ’GGAG’ motif in the selective enrichment of miRNAs in exosomes, as when the ’GGAGG’ motif was mutated to ’GCACG’ in the exosome-enriched miR-601. As a consequence the exosome enrichment of miR-601 was reduced, indicating the importance of the motif in exosome enrichment and in particular the guanine bases. A paper published earlier this year showed the guanine- rich sequence of exosome-enriched miRNAs is conserved across mammalian species and donor cell types. More specifically, exosomal miRNAs from human tumor cells, murine T cells, murine cytotoxic T lymphocytes and murine macrophages exhibited a significantly positive correlation for G in miRNA sequences (Momose et al. 2016). Villarroya-Beltri et al. noted that the distribution of the ’GGAG’ exosome motif was more commonly found in the 5’ end of the exosomal enriched miRNA. Contrarily we found our enriched exosomal motif ’CGGCG’ was more often found in the 3’ end of exosomal miRNAs. Momose et al. did not report on the distribution of the motif in exosomal enriched miRNAs. This leads us to conclude the location of the exosome motif may not be important and is functional at either end of the miRNA. In summary miRNAs containing guanine rich motifs are more likely to be specifically enriched in exosomes. Also the location of the motif in the miRNA may not be important in determining selective exosomal enrichment of the miRNA.

5.3.4 Cartilage-derived exosomes

As described in Section 5.2.10 different populations of microvesicles, displaying differences in miRNA expression and size distribution, are isolated depending on which stage of cartilage digestion they were isolated from. Unfortunately microvesicles were only validated by size distribution in the present study due to limited sample size. Further characterisation of the microvesicles would have to be performed, such as protein analysis of exosome markers (CD63, CD9 and TSG101), to conclusively state if they are exosomes. Smaller microvesicles (10-30nm) were isolated from HACs in culture and during the surgical removal of cartilage whereas larger microvesicles (60-100nm) were isolated during the enzymatic digestion steps. A higher number of microvesicles were also isolated during

Chapter 5 161 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells enzymatic digestion as shown by lower Ct values of miRNAs assayed. Currently no studies have reported the release of exosomes from articular cartilage however some have examined microvesicles isolated after collagenase digestion of articular cartilage. The resultant isolated microvesicles are termed articular chondrocyte vesicles (ACVs). One paper performed proteomic analysis on ACVs and showed they had very few similarities with exosomal proteomes (Rosenthal et al. 2011). Many key components of exosomes such as heterotrimeric G proteins, Hsp70 and Hsp90, and members of the tetraspanin family were not seen in the articular chondrocyte vesicles however lactahererin and ubiquitin were found in ACVs and have previously been found enriched in exosomes (Buschow et al. 2005; Veron´ et al. 2005). A study showed ACVs and MVs from HACs in culture contained RNA which was protected by RNAse digestion (Mitton et al. 2009). Here, the expression of only four cartilage-related miRNAs was investigated: miR-125b- 1, miR-34a, miR-145 and miR-199a. One of these, miR-125b-1 was only expressed in one sample. To further evaluate the differences in these cartilage microvesicles, more miRNAs would have to be examined such as miRNAs with high expression in chondrocytes. A recent paper profiled the miRome of chondrocytes isolated from human osteoarthritic (OA) knee cartilage and identified several highly expressed miRNAs in the chondrocytes including miR-140-3p, miR-10b, miR-101 and miR-140-5p (Crowe et al. 2016). By comparing the miRome of the microvesicles isolated from cartilage to this published chondrocyte miRome may indicate their cell of origin. However, there will be differences in the miRome between the cartilage the microvesicles were isolated from to the cartilage the chondrocytes were isolated from in the Crowe et al. study, due to different patient genetic backgrounds, patient age and disease state of cartilage (osteoarthritic vs. normal). Chondrocytes are not the only cell type present in the knee joint, several other cell types in the joint may be releasing these vesicles into the synovial fluid which has been reported to contain exosomes (Skriner et al. 2006), which subsequently get trapped in the cartilage. To support this hypothesis, it was reported that the miRNA expression of synovial fluid from OA patients was similar to the miRNAs secreted by synovial tissues (Murata et al. 2010). In a recent paper costochondral cartilage cells were isolated from rats and cultured up to 4 passages at which point microvesicles (MVs) were isolated from the medium (Lin et al. 2016). Small RNA-seq of MVs isolated and their donor cells showed an enrichment of miRNAs in the MVs. Similarly to our findings, they found less of the small RNA reads mapping to miRNAs in the exosome libraries compared to the cell libraries. Additionally exosome reads did not show a prominent peak of reads at 22bp that was observed with cell libraries. Before any definitive conclusions are made more biological replicates are required.

Chapter 5 162 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

This may be problematic as donated healthy human cartilage is in limited supply. Fortunately, exosomes can be isolated during steps of chondrocyte isolation from waste products (wash or medium) without effecting the chondrocytes. This means that chondrocytes can be used for further downstream experiments. Future work needs to correctly characterise the microvesicles isolated by protein analysis for exosomal markers.

5.3.5 Role of exosomal miRNAs during pluripotency and differentiation

A multitude of exosome functions have been studied (summarised in Section 1.7.7). They have been investigated as facilitators of the immune response (Thery´ et al. 2009) and as cell communicators, transporting RNAs and protein. A study of mast cell exosomes showed they can transport mRNAs to neighbouring cells, and once taken up could be translated in the recipient cell (Valadi et al. 2007). Another study showed glioblastoma exosomes containing mRNAs, miRNAs and angiogenic proteins, could stimulate tubule formation by endothelial cells (Skog et al. 2008). Very few studies have been performed examining the role of pluripotent stem cell derived exosomes. One study showed mESC-derived microvesicles had high expression of Wnt-3 protein and contained several mRNAs for pluripotency transcription factors. Furthermore when mESC-derived microvesicles were added to hematopoietic progenitor cells they were able to improve their expansion, upregulate expression of pluripotency genes (Oct-4, Nanog and Rex-1) and early hematopoietic markers (Scl, HoxB4 and GATA 2) and activate MAPK signaling (Ratajczak et al. 2006). Pluripotent exosomes have also been shown to have beneficial cardiac effects; exosomes from iPSCs have been shown to protect against myocardial ischemia (Wang et al. 2015b) and mESC exosomes have been shown to improve cardiomyocyte survival (Khan et al. 2015). These studies highlight the role of exosomes acting as cell communicators, therefore I investigated the hypothesis that hESC-derived exosomes may act to promote pluripotency in neighbouring cells via exosomal miRNA signalling. In initial functional exosome experiments, pluripotent exosomes were added to hESCs after growth factor withdrawal and the effect was evaluated by gene expression analysis. Since these exosomes contained miR-302a-5p (Figure 5.2), which has been well characterised to promote pluripotency (Subramanyam et al. 2011), I surmised it is likely that any effect from addition of pluripotent exosomes may be partly due to the uptake of exosomal miR-302a. Therefore the expression of miR-302a validated targets was evaluated. Of the five targets analysed (TGFBR2, RHOC, RBL2, NR2F2 and CDKN1A; Subramanyam et al. 2011), only two showed substantial change when Actvin A growth factor was replaced with pluripotent exosomes (TGFBR2 and CDKN1A, Figure 5.14). Interestingly these two genes are also predicted targets of miR-7704, the top expressed

Chapter 5 163 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells miRNA in hESC-derived exosomes, whereas all other genes examined are not predicted targets of miR-7704 (RHOC, RBL2, NR2F2, OCT4, SOX2, NANOG, GATA4 and YWHAZ) (targets predicted with TargetScan 7.1, Agarwal et al. 2015). Notably, one of the top targets of miR-7704 predicted by TargetScan is LEF1 a downstream mediumtor of Wnt signalling. The involvement of Wnt signalling in maintaining stem cell pluripotency has been well studied (Sokol 2011, Section 1.4.2). Activation of Wnt signalling leads to beta-catenin binding to LEF1 or other TCF/LEF family members activating downstream genes. Many studies have shown Wnt signalling promotes differentiation of ESCs (Bone et al. 2011; Davidson et al. 2012; Davidson et al. 2012). Therefore miR-7704 may inhibit differentiation and promote pluripotency by targeting LEF1. The role of exosomal miR-7704 in cell-cell communication in pluripotent stem cells should be further investigated. In future studies, RT-PCR for the LEF1 gene could be performed to examine if its expression is altered after substitution of pluripotency promoting growth factors with pluripotent exosomes. In preliminary experiments either FGF2 or Activin A was substituted with exosomes however in future experiments by removing both growth factors better spontaneous differentiation would be achieved. Very little is known about the role of exosomes during stem cell differentiation. We used a hESC-directed differentiation protocol to examine the role of exosomes during chondrogenesis. We aimed to investigate the hypothesis that exosomes may act as cell communicators signalling via exosomal miRNAs to promote chondrogenesis. Pathway analysis of exosome-enriched miRNAs showed a significant enrichment of their predicted targets belonging to the Gene Ontology (GO) term ’Embryonic skeletal system development’ (Figure 5.10A), suggesting a possible role in regulating differentiation. Further work is required to validate these predicted targets. One of the exosomal miRNAs miR-1323 which targets 14 genes in the GO ’Embryonic skeletal system development’ (Figure 5.10B), was also identified in earlier mRNA-miRNA interaction network analysis (Figure 4.5A) as a key pluripotent miRNA targeting several genes upregulated during chondrogenesis. It is also a member of the large cluster of pluripotency associated miRNAs on chromosome 19 (CM19C). In a study which performed miRNA profiling of placental tissue, maternal blood cells and cord blood cells, miR-1323 was identified as a placental specific miRNA from these tissues and was also detected in cell-free plasma. Its expression in the placenta was significantly higher in uncomplicated pregnancy compared with fetal growth restriction pregnancy (Higashijima et al. 2013). The placental expression of miR-1323 was later shown to be predominantly expressed from the villous trophoblast cells of the placenta (Kurashina et al. 2014). In summary, studies have shown when incubated with cells, pluripotent stem cell

Chapter 5 164 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells derived exosomes can affect cellular behaviour, with increased proliferation of acceptor cells a common theme (Ratajczak et al. 2006; Khan et al. 2015). Several studies have highlighted enriched miRNAs in PSC-exosomes which may be causing these effects, however miRNA profiling of human pluripotent stem cell derived exosomes has not been reported. We have profiled exosomes isolated from hESCs and hESC-derived chondroprogenitors using small RNA-seq and identified several exosome-enriched miRNAs. The most highly expressed miRNA in exosomes was miR-7704 which may promote pluripotency by inhibiting Wnt signalling, a key pathway promoting ESC differentiation (Bone et al. 2011; Davidson et al. 2012; Davidson et al. 2012). Another exosomal miRNA identified from miRNA-profiling experiments identified miR-1323 as a miRNA which may be important regulating development as it targets several genes with the GO term ’Embryonic skeletal system development’. MicroRNA-1323 expression has also been linked to fetal growth restriction pregnancy. Further functional analysis of these miRNAs is required to validate their role in pluripotency and chondrogenesis.

5.3.6 Conclusion

Here we aimed to further elucidate the function of exosomes in hESCs and during hESC- directed chondrogenesis. During initial experiments, protein assays were used to quantify exosomes and RNU19 was used to normalise exosomal miRNA expression to. Here we highlight reasons why these two methods are poor choices and advise use of Nano Tracking Analysis (NTA) (or similar method) for exosome quantification and miR-16-5p as a suitable small RNA control for exosome miRNA expression analysis. MicroRNA profiling of exosomes from hESCs and hESC-derived chondroprogenitors showed exosome-miRNAs were enriched with a guanine-rich motif as previously reported (Villarroya-Beltri et al. 2013; Momose et al. 2016). We have identified several miRNAs which are highly enriched in exosomes for further investigation. One of these is miR-7704, the most highly expressed miRNA in hESC-exosomes which may have a role in promoting stem cell pluripotency by targeting wnt. Another exosomal miRNA of interest is miR-1323 which may be involved in regulating skeletal development. Along with investigating exosome miRNA enrichment we have developed a high-throughput assay to investigate exosome uptake using high content analysis and lentiviral transduction of eGFP-CD63. This could be used in further experiments to investigate the dynamics of exosome uptake.

Chapter 5 165 Chapter 6

Discussion

6.1 General Discussion

6.1.1 Main findings

This project investigated the regulation of miRNAs expression during hESCs-directed chondrogenesis and a possible role for exosomes during differentiation and in maintenance of pluripotent stem cells. In Chapter 3 the miRNA regulation during hESC-directed chondrogenesis was investigated by RNA-seq in two hESC lines, Man7 and Hues1, during chondrogenesis using the Directed Differentiation protocol developed in our lab (Oldershaw et al. 2010). This revealed pronounced changes in the expression of several miRNAs during the progression of hESC-directed chondrogenesis including; upregulation of miRNAs transcribed from the four Hox complexes, known cartilage associated miRNAs and the downregulation of several pluripotency associated miRNAs. Overall miRome and transcriptome analysis revealed the two hESC lines exhibited slightly different miRome and transcriptome profiles during chondrogenesis, with Man7 displaying larger changes in miRNA and mRNA expression as it progressed through the DDP. Chapter 4 discussed correlated changes in the expression of miRNAs and protein-coding mRNAs during hESC-directed chondrogenesis. Significant changes in the expression of several highly co-expressed clusters of miRNAs and functionally related mRNAs were identified during differentiation. Further investigation of these gene/miRNA clusters allowed the identification of several potential novel regulators of hESC-directed chondrogenesis. Chapter 5 investigated the potential role of exosomes during hESC-directed chondrogenesis and hESC maintenance. Specifically we investigated miRNA loading into exosomes and the functional effects of exogenous addition of exosomes to a differentiation protocol. Exosomes isolated from hESCs and hESC-chondroprogenitors were characterised and miRNA content of exosomes and donor cells was profiled by small RNA-seq. This revealed miRNAs with a guanine rich motif were enriched in exosomes compared with their donor cells strongly reminiscent of motifs directing loading of miRNAs into exosomes identified in previously published work (Villarroya-Beltri et al. 2013; Momose et al. 2016). Preliminary functional experiments suggest exosomes may have a role in promoting hESC pluripotency however the molecular mechanism by which this is

166 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells achieved has not been investigated. The implications of the findings presented in this thesis will be discussed in this chapter and potential experiments to further investigate them are suggested.

6.1.2 Cartilage miRNA regulation during hESC-directed Chondrogenesis

In Chapter 4 we identified a large cluster of co-expressed miRNAs and protein-coding mRNAs upregulated during hESC-directed chondrogenesis. This cluster was enriched in extracellular matrix (ECM) associated genes, termed the ’ECM’ cluster, and was investigated for novel regulators of chondrogenesis. Interestingly, the majority of chondrogenesis regulating miRNAs identified in this cluster are thought to inhibit rather than promote chondrogenesis. In the majority of these studies the investigated miRNA was concluded to inhibit chondrogenesis due to an observed reduction in COL2A1 gene expression (Martinez-Sanchez et al. 2012; Hou et al. 2015; Hou et al. 2015; Lin et al. 2009b). These studies did not asses other collagen-encoding genes or the overall composition, quality and organisation of the ECM produced (Martinez-Sanchez et al. 2012; Hou et al. 2015; Hou et al. 2015; Lin et al. 2009b), which are essential for determining the functional properties of the cartilage (Fox et al. 2009). In another study for example, miR-29a was shown to inhibit chondrogenesis of hMSCs in pellet culture by reduction in expression of COL2A1, however osteonectin and several other genes encoding collagens were also significantly decreased, including COL1A1 and COL4A2, and potentially COL10A1 a marker of hypertrophy. (Guerit´ et al. 2014). Furthermore a study using MSCs, miR-574 reduced the expression of chondrogenic genes ACAN and COL2A1 as well as COL10A1 (Guerit et al. 2013). In conclusion the role of many of these miRNAs in regulating articular chondrocyte formation has not been well-evaluated, and some studies suggest the investigated miRNA may well be inhibiting hypertrophic differentiation. The majority of current MSC chondrogenesis models produces chondrocytes with a hypertrophic phenotype characterised by expression of type X collagen and has tendency to give fibrocartilage indicated by expression of type I collagen (Johnstone et al. 1998; Yoo et al. 1998; Mwale et al. 2006; Sekiya et al. 2002; Pelttari et al. 2008). Therefore the functional properties of miRNAs investigated in these models may indicate their role in hypertrophic chondrogenesis rather than during hESC-directed chondrogensis which produces non-hypertrophic chondroprogenitors. For example, miR-145 is reported to inhibit chondrogenesis by directly targeting SOX9 (Martinez-Sanchez et al. 2012), however it is likely that fine modulation of SOX9 will be required to produce and maintain a non-hypertrophic mature chondrocyte. To support this hypothesis it has recently been reported that SOX9 is required for hypertrophy in chondrocytes (Dy et al. 2012; Ikegami

Chapter 6 167 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells et al. 2011). These results all indicate the subsequent evaluation of miRNA overexpression/inhibition should be undertaken in the context of the quality of the cartilage produced and not just change in gene expression of a select few cartilage markers (i.e. COL2A1, SOX9 and ACAN), for the following reasons i) gene-expression does not always correlate to protein expression, ii) proteins once transcribed also require correct processing and trafficking, iii) the organisation of different ECM molecules in deposited matrix is also critical to function. However, evaluation of protein composition in deposited extracellular matrix and its organisation is time-consuming, requires substantially more material and current comprehensive understanding of the ’correct’ composition and organisation of articular ECM is lacking. Expression of several of the ’ECM’ cluster miRNAs were found to be enriched in progenitor chondrocytes compared to hypertrophic chondrocytes in previously published miRome’s from distinct regions of developing human cartilage (progenitor, differentiated and hypertrophic chondrocytes); these include miR-214, miR-675 and miR-335 (McAlinden et al. 2013). Mixed roles of these miRNAs have been reported in mesoderm lineage regulation. For example, miR-335 promotes osteogenesis (Zhang et al. 2011a) while miR-214 inhibits osteogenesis (Wang et al. 2013a), furthermore miR-214 has been shown to promote skeletal muscle differentiation (Juan et al. 2009; Liu et al. 2010). The only miRNA found to promote chondrogenesis in the ’ECM’ cluster and enriched in progenitor chondrocytes was miR-675 which promotes COL2A1 expression by an unknown mechanism (Dudek et al. 2010). One hypothesis for the large variation in the previously reported function of these chondroprogenitor enriched miRNAs is that they are acting as ’mesoderm-brakes’, preventing uncontrolled differentiation of progenitors until a sufficiently strong or specific pro-differentiation signal is received to direct the cells towards a transition to a defined state. Alternatively these miRNAs may be expressed within distinct subpopulations of the culture or the function of the miRNAs in this model may well be different from those previously reported, due to different target genes being expressed. Single cell RNA-seq and validation of miRNA targets specific to this model will help explain the apparent opposing roles of these miRNAs. Further understanding of miRNA regulation of chondrogenesis will provide a more comprehensive knowledge of the molecular mechanism driving chondrogenesis and the correct signals required for the production of mature chondrocytes. This understanding could improve current cell therapies for osteoarthritis.

Chapter 6 168 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

6.1.3 Role of exosomes

As mentioned in Section 1.7.7, several potential functions for exosomes have already been investigated, such as: antigen presentation (Thery´ et al. 2009) and angiogenesis (Janowska-Wieczorek et al. 2005). However, these previous in vitro investigations of exosome function have largely been inconclusive due to; i) poor characterisation of extracellular vesicle populations, ii) substantially more exosomes being added to cells than would be expected endogenously, and/or iii) the molecular mechanism of exosome function had not been characterised. This thesis aimed to investigate the role of exosomes during hESC-directed differentiation.

Waste disposal

The first reported function of exosomes was disposal of the trasnsferrin receptor during reticulocyte maturation (Pan et al. 1985). However, as exosomes are highly conserved across eukaryotes and prokaryotes (Deatherage and Cookson 2012) this suggests they may have a more vital function than a secondary lysosome. It was recently discovered that miRNAs with a guanine-rich motif were selectively packaged into exosomes via hnRNPA2B1 (Villarroya-Beltri et al. 2013; Momose et al. 2016). I found a similar guanine-rich motif in the exosome-enriched miRNAs, suggesting that the selective packaging of miRNAs may be a feature of diverse cell types and play a role in cell-cell communication in many contexts. Another potential role of this selective enrichment could be for the disposal of guanine-rich sequences which may be detrimental to cell function, such as miRNAs which were once required to help maintain a specific cell state but during differentiation are no longer required and may impede development. Interestingly, the most well characterised pluripotency miRNAs, the miR-302 cluster (Card et al. 2008; Subramanyam et al. 2011) and cartilage specific miRNA, miR-140 (Tuddenham et al. 2006), were both found to be cell enriched in hESCs and hESC-chondroprogenitors respectively. This suggests that more functional miRNAs are retained within the cell while miRNAs which do not have a specific function relating to their cell of origin are disposed off via exosomes.

Development

Exosomes have previously been implicated in development as transporters of proteins regulating growth and developmental patterning. Key morphogens in early development (Perrimon et al. 2012) have been found in exosomes including, Wnt proteins (Gross et al. 2012), hedgehog signalling protein Hh in Drosophila development (Gradilla et al. 2014), Hedgehog-related proteins in exosomes from C. elegans from the apical plasma membrane (Liegeois´ et al. 2006), FGF-triggered release of vesicles containing sonic hedgehog and retinoic acid have been implicated in the patterning of internal organs

Chapter 6 169 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

(Tanaka et al. 2005). While FGF signalling has been shown to signal the release of morphogen-containing vesicles, another mechanism by which exosomes could be triggered for release is by calcium signalling. The involvement of calcium signalling during embryo development has been well-studied. Calcium signalling has for instance been implicated in axis-specification and gastrulation (Webb and Miller 2003) and was recently shown to regulate exosome release (Savina et al. 2003). These experiments suggest exosomes may have a role during early development; an initial signal (FGF or calcium) could stimulate the release of exosomes in an apical manner producing a long-range morphogen gradient, potentially leading to tissue patterning. However, a clear and mechanistically well understood role of exosomal-miRNAs in development has yet to be determined. The importance of miRNAs during development however has been clear since their discovery, with the first cloned miRNA being identified while investigating developmental timing in C.elegens (Lee et al. 1993). Furthermore global loss of miRNAs in Dicer1 null mouse models were embryonic lethal (Bernstein et al. 2003; reviewed in Alvarez-Garcia and Miska 2005). Exosome-profiling identified miR-7704 as highly exosome-enriched miRNA. It is predicted to target LEF1, which is a downstream mediator of Wnt signalling, a key signalling pathway regulating development patterning (Perrimon et al. 2012). However, the role of exosomal miRNAs in development has yet to be investigated.

Differentiation

Recent experiments have shown that exosomes could be targeted to cells via interactions with integrins (Nazarenko et al. 2010; (Hwang et al. 2003; (Morelli et al. 2004). Our initial exosome uptake experiment suggested that more pluripotent stem cell-derived exosomes were taken up by hESCs lacking expression of the pluripotency marker, Tra-1-60, than cells expressing Tra-1-60 (Figure 5.11A). This suggests that there may be a selective mechanism directing pluripotent-exosome uptake by differentiating cells compared with pluripotent cells, however further validation is required. If this is the case, it opens a number of new and unanswered questions: i) is the reverse also true i.e. are differentiating cell-derived exosomes selectively taken up by pluripotent stem cells, ii) do differentiating cells have an increased ability for non-specific exosome uptake, iii) what regulates the selective uptake of differentiated cells and iv) do exosome contents have different functions after uptake in differentiated cells compared with pluripotent cells i.e do contents enter the lysosome pathway for destruction or do they have a biological function. Many of these questions could be investigated using the high-throughput exosome assay developed in Section 5.2.12. In Chapter 3, principal component analysis of RNA-seq libraries showed biological

Chapter 6 170 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells replicates at the intermediate stages of hESC-directed chondrogenesis were clustered less well than the hESC and hESC-chondroprogenitor stage replicates. Although it is possible that this is due to experimental conditions it suggests an interesting possibility that expression profiles at intermediate stages of differentiation are much more variable or may contain different subpopulations of cells that undergo differentiation at different rates relative to the starting and end points of the differentiation protocol. Whether exosomes may play a role in regulating this heterogeneity during differentiation is unclear; one hypothesis is that exosomes released during differentiation contain specifically packaged miRNAs and proteins to signal neighbouring cells to undergo similar differentiation. Gene ontology analysis of predicted targets of exosome-enriched miRNAs during hESC directed chondrogenesis revealed they were enriched with genes associated with ’Embryonic skeletal system development’ suggesting these exosomal miRNAs may have common functions, however GO analysis of predicted targets is a poor predictor of function due to high false positives in target prediction algorithms and bias of certain GO terms for miRNA targets (Bleazard et al. 2015). One exosomal miRNA identified in Chapter 5, miR-1323, is predicted to target several genes involved in skeletal development, including HOXD3, GLI3 and BMP4, suggesting it may be involved in regulating differentiation. Notably, miR-1323 had considerably more predicted targets compared with other miRNAs. Whether this is a common trend of other exosomal miRNAs compared with cell enriched miRNAs is yet to be investigated. If so it may suggest exosomal-miRNAs have different targeting properties to cell-enriched miRNAs, acting to target a broad rage of transcripts rather than a specific subset.

6.1.4 Candidate miRNAs identified

In this thesis several miRNAs have been identified as potential novel regulators of hESC-directed chondrogenesis or pluripotency (summarised in Table 6.1). MicroRNAs were identified based on two or more the following criteria; co-expression with known regulators (i.e. cluster miRNA), validated target of interest, significant enrichment of targets associated with GO term of interest and/or exosome-enriched.

Chapter 6 171 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

miRNA Potential Role Evidence Known role miR-22-3p ECM organisation Cluster 4 Promotes osteogenesis by targeting HDAC6 (Huang et al. 2012) miR-143-3p ECM organisation Cluster 4 Targets MMP13 (Wu et al. 2013a) miR-7704 Pluripotency by Fig. 5.14; none targeting Wnt signalling Cluster 1 (LEF1) miR-1323 Skeletal development Fig. 4.5; Placenta-specific (Higashijima et al. 2013; Fig. 5.10; Kurashina et al. 2014) Cluster 1 miR-331-3p Chondrocyte maturation Fig. 5.8 Targets ERBB2 (Epis et al. 2009; Epis and/or proliferation et al. 2011) which regulates chondrocyte proliferation and maturation (Fisher et al. 2007) miR-542 ECM organisation Fig. 4.6 Inhibits osteogenesis by targeting BMP7 (Kureel et al. 2014) miR-1246 Pluripotency Cluster 1, Wnt signalling (CHAI et al. 2016) exosome miR-7641 Pluripotency Cluster 1 Targets pluripotency promoting ligand CXCL1 (Yoo et al. 2013; Jung et al. 2014)

Table 6.1: Candidate miRNAs. Several candidate miRNAs identified in this thesis which may regulate hESC- directed chondrogenesis of pluripotency. For each candidate miRNA the following information is given: i) potential novel role of each miRNA suggested from analysis, ii) Evidence presented in this thesis to suggest the novel role suggested, iii) currently known role of miRNA from literature. Expression of cluster miRNAs is shown in Figure 4.3

6.2 Future Work

6.2.1 Novel regulators of hESC-directed chondrogenesis

We have identified several potential novel regulators of hESC-directed chondrogenesis in the course of this study. To validate their function during chondrogenesis the use of siRNA knock-down approach (for gene candidates) or by use of anti-miR inhibitor (for miRNA candidate) coupled with RT-PCR validation and examination of change in cartilage markers (SOX9, ACAN and COL2A1) will be the next step. In preliminary miRNA inhibition experiments, where miRNA inhibition by lipofectamine transfection of anti-miR oligos exhibited cytotoxic effects in hESCs during differentiation. This may be overcome by using a lentiviral overexpression system, work by Dr Ioannis Bantounas in the Kimber lab showed a functional effect of miR-199a and miR-214 during hESC-directed kidney differentiation using a lentiviral overexpression approach. Lentiviral transfection of hESCs showed high transfection efficiency with low toxicity. Also using a CRISPR/cas9 strategy miRNA expression can be modulated using several different methods, however the most

Chapter 6 172 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells appropriate method will depend on the specific miRNA in question and the hypothesis being investigated. The CRISPR/cas9 system had been proven to be highly efficient (up to 96%) and long- term miRNA knock-down can be readily achieved (Chang et al. 2016). CRISPR can also be utilised to modulate miRNA promoter activity, leading to upregulated miRNA expression (CRISPRa) (Cheng et al. 2013; Gilbert et al. 2014) or inhibition of expression (CRISPRi) (Thakore et al. 2015; Gilbert et al. 2013; Gilbert et al. 2014; Zhao et al. 2014), allowing for a more tune-able system to modulation of the expression of specific miRNAs. This provides a more biologically relevant control of miRNA levels than complete knock-down or an unphysiologically high level of miRNA over-expression. However, developing a CRISPR/cas9 system for miRNA knockdown or modulation of its promoter activity is inappropriate if the candidate mature miRNA is produced from several different primary transcripts at several genomic loci. For example, mature miR-199a is produced from two separate loci therefore both miRNAs will have to be modulated requiring two separate CRISRP systems to be developed which is time-consuming and both will have different efficiencies and off-target effects. Also this method is not appropriate for modulating expression of miRNAs expressed from protein coding genes, as the off-target effect of protein-coding gene modulation will also have to be assessed. MicroRNA sponges can be used to inhibit miRNAs transcribed from multiple loci and/or from protein coding genes (Ebert and Sharp 2010). MicroRNA sponges contain multiple binding sites for the miRNA of interest to efficiently ’soak’ up its expression. Also multiple binding sites for different miRNAs can be incorporated into the sponge to allow inhibition of multiple miRNAs simultaneously. Once the levels of a miRNA of interest have been modulated the effect on hESC-directed differentiation must be evaluated. Firstly, expression of cartilage markers (SOX9, ACAN and COL2A1) can be assessed by RT-PCR and cartilage deposition can be assessed by safranin ’O’ staining for glycosaminoglycans. If a miRNA of interest affects hESC-directed chondrogenesis, it is most likely to mediate this effect by miRNA-mRNA targeting interactions. Several targets of the candidate miRNA can be predicted using TargetScan (Agarwal et al. 2015) and then validated using a 3’UTR luciferase reporter assay, in which the 3’UTR of the predicted target is cloned downstream of luciferase, expression of luciferase can then be assessed after candidate miRNA modulation (O’Donnell et al. 2005).

6.2.2 Heterogeneity during hESC-directed chondrogenesis

One aspect of hESC-directed chondrogenesis which has not be addressed in the analysis presented is the heterogeneity during hESC-directed differentiation, this can be investigated by using single-cell RNA-seq. Single-cell RNA-seq has allowed identification

Chapter 6 173 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells of new subpopulations of cells (Buettner et al. 2015) also identification of co-expressed gene clusters and bimodally expressed genes (Shalek et al. 2013), which may not of been possible with whole population analysis. There is currently no method for single-cell small RNA-seq analysis, however a multiplex method has been developed which allows the profiling of 220 miRNAs in single-cells (Tang et al. 2006), it has recently been used recently to profile 330 miRNAs in 10-cell populations of mESCs and inner cell mass cells of mouse blastocysts (Tang et al. 2010).

6.2.3 Investigating the role of exosomes during pluripotency and differentiation

Not much is know about the function of exosomes during hESC pluripotency or differentiation. However many studies have shown the potential for exosomes to regulate differentiation by transfer of exosomal proteins or RNA (Section 1.7.7). In the previous chapter it was discovered that several miRNAs were selectively enriched in exosomes derived from hESCs and hESC-derived chondroprogenitors. However, the specific role of these exosome-enriched miRNAs in hESC maintenance or differentiation is unknown, preliminary experiments in Section 5.2.14 suggest hESC-exosomes may promote hESC proliferation. One hypothesis is that exosomes released from pluripotent stem cells may act in a paracrine manner to maintain pluripotency of neighbouring cells. Similarly, differentiating hESCs may signal neighbouring cells to follow the same differentiation path. If this hypothesis is true it produces several unanswered questions including, i) what is the molecular mechanism by which exosomes promote differentiation/pluripotency, ii) are pluripotent/differentiated hESC-derived exosomes selectively taken up by hESCs or differentiated-hESCs, and if so iii) what is the mechanism behind selective exosome uptake in pluripotent stem cells and/or differentiated cells.

Exosome functional properties

To investigate the function of exosomes during hESC pluripotency and differentiation the high-throughput exosome-uptake assay developed in Section 5.2.12 can be utilised. Firstly, the function of exosomes during pluripotency and differentiation can be examined by incubating exosomes derived from eGFP-CD63-hESCs and differentiated-eGFP-CD63-hESCs (diff-hESCs) with hESCs in either pro-differentiation or pro-pluripotency conditions. The effect of exosomes on hESC pluripotency can be evaluated by performing immunocytochemistry for pluripotency markers (Oct4, Sox2 and Nanog) and negative-pluripotency marker SSEA-1, and quantified using high content analysis (Cell Insight, Life Technologies). Preliminary functional exosome experiments in Chapter 5 revealed a PBS negative control alone was insufficient and use of ’mock’ exosome sample from non-cell conditioned media is also required to examine the

Chapter 6 174 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells background effect of possible pelleted proteins in the medium, also including a UV-treated exosome control would help to determine if the functional effect is RNA dependent.

Selective uptake of exosomes

Using high content analysis the number of eGFP-CD63-exosomes taken up in pluripotent and differentiated cells can be compared. If there are significant difference in exosome uptake between the two cell populations this may due to i) exosomes being selectively taken up into one population of cells, ii) exosomes may promote pluripotency/differentiation leading to exosome containing cells having the same phenotype, iii) cells with lower proliferation may accumulate more exosomes over time, and/or iv) exosomes may have different fates after uptake i.e. enter lysosome pathway (loss of eGFP signal) or release contents in cell (eGFP signal remains in cell). To further elucidate what is the cause of observed differences in exosome uptake, the following experiments could be performed; i) a short-term uptake experiment evaluating cell populations before exosome mediated effects occur, ii) a lysosome marker co-localisation experiment to determine if exosomes in one cell type are more likely to enter the lysosome pathway. These experiments should validate if hESC-exosomes show selective uptake and/or processing. A detailed understanding of the mechanisms through which exosomes are selectively taken by cells is of great interest as it could aid therapeutic targeting of drugs to specific cells. Papers which have reported a selective uptake of exosomes suggest exosome membranes present integrins that may be involved. To date no proteomic profiling of pluripotent-derived exosomes has been performed, however potential integrins involved could be identified by finding integrins expressed in both pluripotent stem cells and commonly found to be incorporated into exosomes from the literature and then validated in hESC-exosomes by Western blot. Once a potential candidate is identified, its role in exosome uptake can be validated by blocking its function using mono-clonal blocking antibodies against it and assessing exosome uptake using the exosome-uptake assay. It is not yet known if cells overexpressing CD63 tagged with eGFP exhibit normal exosome function, therefore exosome uptake experiments performed using eGFP-CD63 cells may have to validated using a different method such as the PKH26 dye used in preliminary uptake experiments in Chapter 5.

Exosome miRNAs during hESC pluripotency and differentiation

In the previous chapter, preliminary experiments suggested hESC-exosomes can promote hESC proliferation. However the molecular mechanism behind this effect was not investigated. If functional experiments show a loss of function after exosomes were treated with UV irradiated this would suggest the function is mediated via exosomal

Chapter 6 175 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells nucleic acids such as miRNAs. A good candidate which may be mediating the effect is miR-7704, as it was discovered from RNA-seq to be the highest expressed miRNA in hESC-exosomes and is predicted to target Wnt signalling, a key pathway for pluripotency and differentiation of hECS. The role of miR-7704 in hESC could be examined by creating a miR-7704 knockout hESC line. Exosomes are a compelling candidate for regulating the behaviour of hESCs and may play an important role in hESC pluripotency and differentiation. Further understanding of mechanisms maintaining hESC pluripotency and signals driving stem cell differentiation are of huge interest as this information can lead to improved methods of pluripotent stem cell maintenance and differentiation for regenerative medicine.

6.2.4 Cartilage Exosomes

As well as examining exosomes during hESC-directed chondrogenesis, exosomes in cartilage were also examined although only preliminary data is presented here. As shown in Section 5.2.10, microvesicles can be isolated from different stages of cartilage digestion, suggesting the possibility that cartilage may release exosomes. However this experiment was only performed once and the microvesicles isolated were not fully characterised to validate their identity as exosomes. The identification of these microvesicles from articular cartilage opens the question as to what their function in cartilage biology is. It is known mature chondrocytes lose cell-cell contact as they become encapsulated in their own extracellular matrix, therefore it is hypothesised that exosomes may provide a novel method of cell-cell communication between chondrocytes. In future experiments the following questions need to be answered to conclusively demonstrate that chondrocyte-derived exosomes have a role in cell-cell communication in articular cartilage; i) do mature chondrocytes release exosomes, ii) can chondrocyte-exosomes pass through the dense ECM of cartilage to subsequently be taken up by nearby cells, iii) once exosomes are taken up do they have a functional effect in their acceptor cell. Firstly, it is important to validate if mature chondrocytes in articular cartilage release exosomes. Exosomes could be isolated using the same method as used in earlier experiments and validated for expression of exosomal markers. As suggested by low Ct values of the exosomal RNA isolated in preliminary experiments (Figure 5.11) only very small quantities of microvesicles were possible to isolate in these experiments. Therefore it may not be possible to perform Western blot analysis on microvesicles samples similarly isolated due to limited sample amount. To overcome this limitation, samples could be characterised by nanoparticle tracking analysis (NTA) with use of exosomal markers such as CD63 or TSG-101 conjugated to quantum dots. This would provide strong confirmation the microvesicles isolated are exosomes.

Chapter 6 176 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

For chondrocyte-derived exosomes to have a role in cell-cell communication in articular cartilage they will have to pass through the dense extracellular matrix which encapsulates chondrocytes. One way to investigate the ability of chondrocyte-derived exosomes to pass through ECM is by using a 3D in vitro model of cartilage. One such model could be eGFP- CD63-hESC-derived chondroprogenitors encapsulated in a fibrin gel or a similar matrix molecule which would most closely resemble the properties of cartilage ECM. Exosomes released from these cells could then be tracked by fluorescence imaging of eGFP-CD63 exosomes. Using a transwell system exosome uptake in acceptor cells, separated from the eGFP-CD63 expressing donor cells by a microporous membrane could be examined. In addition the transwell insert could also be coated with collagen to ensure any eGFP- exosomes which have been taken up by acceptor cells in the separate compartment have first passed through a ECM-like matrix. If significantly more eGFP-CD63-exosomes are detected in the acceptor cells compared to control then this would constitute a strong indication that exosomes are able to pass through ECM and be taken up by nearby cells and suggests exosomes could provide a novel method of cell-cell communication for chondrocytes. There are two potential functions of exosomes that could be next examined: i) the role of exosomes in chondrocyte maturation, and ii) the role of exosomes in cell-cell communication. Firstly, to investigate the role of exosomes in chondrocyte maturation hESC-derived chondroprogenitors could be cultured with exosomes-derived from mature human articular chondrocytes (hACs), to assess if hACs-derived exosomes provide a pro-maturation signal to the chondroprogenitors. Secondly, to investigate the role of exosomes in cell-cell communication hACs could be cultured with exosomes isolated from hACs under different conditions. In this experiment exosomes can be investigated to asses if they can provide signals related to their treatment i.e. do exosomes isolated from hACs culture in inflammatory conditions produce an anti-inflammatory signal. To support this hypothesis a recent study showed exosomes from mast cells exposed to oxidative stress could provide a protective effect against oxidative stress in mast cells (Eldh et al. 2010). After treatment with exosomes, functionality of exosomes can be assessed by RT-PCR of acceptor cell transcripts for change in gene expression of cartilage markers (SOX9, ACAN and COL2A1) and other genes of interest (i.e. inflammatory response genes). During these experiments the following negative controls could be included; incubation of exosome samples with Annexin-V to prevent exosome uptake and UV treatment of exosome samples to degrade exosomal RNAs (this control also validates effect is RNA dependant) and ’mock’ exosome sample (as mentioned earlier). During these experiments if exosomes display a functional effect on chondrocytes and

Chapter 6 177 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells this effect is lost after short UV-irradiation of exosomes this is strong evidence exosomal RNAs are mediating this effect, if not it suggests exosome proteins may be the mediators. Profiling of exosome miRome or proteome can help identify molecules involved in mediating this effect however this may be difficult due to low amount of exosome sample. In Chapter 5 the miRome of hESC-exosomes and chondroprogenitors-exosomes were profiled from only a few nanograms of total RNA, suggesting it may be possible to profile cartilage-derived exosomes. Proteome profiling may be more difficult. A proteomic analysis of exosomes used 100µg protein of purified exosomes from 108 rat mast cells (RBL-2H3 cell line) (Subra et al. 2010). In another proteomic analysis of exosomes they were profiled with less starting exosome protein 2-40µg of rat hepatocytes-derived exosomes (Conde-Vancells et al. 2008). Depending on the amount of exosome protein that can be isolated from healthy human cartilage, proteome profiling of exosomes may or may not be possible with current technology available. One limitation for the above described experiments is the availability of health articular cartilage for hACs isolation. Also differences in age and genetic backgrounds of patients will lead to large variation. One possibility that would overcome this problem would be the use of mature chondrocytes derived from pluripotent stem cells. Dr Steven Woods from the lab has developed a protocol for the differentiation of pluripotent stem cells into mature chondrocytes via an intermediate MSC-like population which then undergo chondrogenesis using a pellet culture method. These experiments could identify a novel role of exosomes in cartilage and be further evidence to support the hypothesis exosomes act as cell-cell communicators. This role of exosomes could potential lead to new therapeutics for arthritis and cartilage regeneration by exploiting the known chondrocyte exosome uptake mechanism to delivery proliferative and anti-immunogenic signals to chondrocytes using artificial exosomes.

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Chapter 215 Appendix A

Appendix

A.1 List of primers for RT-PCR, cloning and DNA sequencing

216 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Name Use Sequence CMV CD63 Fwd Cloning GGGGGCTAGCGGCGCAGCTAGAGAGCC CMV CD63 Rev Cloning GGGGACCGGTAGCATCACCTCGTAGCCACTTC EF1a CD63 Rev Cloning TTAAGGATCCCCCATCACCTCGTAGCCAC EF1a CD63 Fwd Cloning TTGGTCTAGAGGCGCAGCTAGAGAGCC CMV 3’ end Seq AAATGTCGTAACAACTCCGC CD63 middle Seq TCTGTCTCTTATCATGTTGGTGG eGFP 3’ end Seq GACAACCACTACCTGAGCAC NR2F2 Fwd qPCR CGGAGGAACCTGAGCTACAC NR2F2 Rev qPCR CCTCTGCACCGCTTCCC TGFBR2 Fwd qPCR TGTTGAGCTCTTCAAGCAGACCGA TGFBR2 Rev qPCR ACTTCTCCCACTGCATTACAGCGA RHOC Fwd qPCR ACAGCAGGGCAGGAAGACTATGAT RHOC Rev qPCR TGTCGATGGAGAAGCACATGAGGA CDKN1A Fwd qPCR AAGACCATGTGGACCTGTCACTGT CDKN1A Rev qPCR AGAAATCTGTCATGCTGGTCTGCC RBL2 Fwd qPCR AACGCTGGTTCAGGAACAGAGACT RBL2 Rev qPCR AGAAACTGGAGTCACACAAGGGCT COL2A1 Fwd qPCR GGCAATAGCAGGTTCACGTACA COL2A1 Rev qPCR CGATAACAGTCTTGCCCCACTT SOX9 Fwd qPCR GACTTCCGCGACGTGGAC SOX9 Rev qPCR GTTGGGCGGCAGGTACTG OCT4 Fwd qPCR AGACCATCTGCCGCTTTGAG OCT4 Rev qPCR GCAAGGGCCGCAGCTT ACAN Fwd qPCR TCGAGGACAGCGAGGCC ACAN Rev qPCR TCGAGGGTGTAGCGTGTAGAGA NANOG Fwd qPCR GGCTCTGTTTTGCTATATCCCCTAA NANOG Rev qPCR CATTACGATGCAGCAAATACAAGA SOX2 Fwd qPCR TGGTCCTGCATCATGCTGTAG SOX2 Rev qPCR AACCAGCGCATGGACAGTTAC GAPDH Fwd qPCR ATGGGGAAGGTGAAGGTCG GAPDH Rev qPCR TAAAAGCAGCCCTGGTGACC ACTB Fwd qPCR CGAGAAGATGACCCAGATCA ACTB Rev qPCR CGTACAGGGATAGCACAGC

Table A.1: Table of primers. All primers used during the course of this project. Seq, DNA Sequencing; Fwd, Forward Primer; Rev, Reverse Primer.

Chapter A 217 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

A.2 Co-expressed miRNAs and protein-coding genes

The following tables contain highly co-expressed miRNAs and protein-coding genes identified from co-expression analysis in Chapter 4.

Table A.2: Co-expressed clusters (1-3) of miRNAs and protein-coding genes All protein-coding genes and miRNAs found to be highly co-expressed in clusters 1-3 identified in Chapter 4.

Cluster 1 Cluster 2 Cluster 3 A2ML1 IDO1 ABHD12B ABCB1 HES7 PAX1 AADACL3 IL23A ADGRF2 ABCC8 HIRIP3 PAX6 AASS IL34 ANKS1B ABHD1 HLA-B PAX7 ACAP1 IQSEC2 ATP12A ABHD14B HLA-DMB PAX9 ACOXL ITM2A BHLHE22 ABHD15 HLA-DOA PCK1 ADAMTS8 KANK3 CA12 ACSL1 HLA-DOB PCSK6 ADGRG2 KDF1 CCDC141 ACSS1 HLA-DPA1 PDIA2 ADGRG5 KIAA0319 CCKBR ACTN2 HLA-DQB1 PDIK1L AGMAT KLHDC7A CD177 ACYP1 HLA-DRA PEX11A ANKRD24 KLK5 CDH12 ADAM11 HLA-DRB1 PHF8 AP1M2 L1TD1 CER1 ADAP2 HLA-DRB5 PI15 ARFGEF3 LAD1 CHST9 ADCK3 HLA-F PI4KB ATP2A3 LCK CR1L AGAP2 HMG20A PIN4 ATP2C2 LECT1 CST1 AKAP10 HMX2 PLD6 AURKC LEFTY1 CST2 ALDH8A1 HMX3 PLEKHH2 B3GAT2 LEFTY2 CYP26A1 ALG1L HNF4G PLIN4 BCAN LHFPL4 DEC1 ALKBH5 HOXA4 PLP2 BSPRY LRRC16B DLL3 ALOX12B HOXC11 POLE4 C12orf45 LY75 DUSP26 ALPK1 HOXC12 POLG C12orf56 M1AP EOMES AMBN HOXC13 POM121L2 C1orf210 MACC1 EPSTI1 ANKRD34B HOXD1 POU3F3 C4orf51 MAL2 ERBB4 APOA1BP HOXD10 POU4F1 CA4 MAP10 FOXA2 APOD HOXD11 PPP1R13B CABYR MAP4K1 FOXQ1 AQP6 HOXD13 PPP1R14C CALB1 MARVELD3 GATM ARAP2 HOXD9 PPP1R3E CALN1 MATK GDF3 ARHGDIG HPCAL4 PPP4C CBLC MB21D1 GPR83 ARL17A HPSE PRAME CBR1 MB21D2 HPDL ARL17B HS6ST3 PRC1 CCDC152 MMP24 HPGD ATP6V1B1 let-7a-5p PRDM13 CCDC169 MNS1 HRASLS5 BARHL2 let-7e-5p PRDM16 CCDC172 MPP1 miR-141-5p BARX2 miR-1224-3p PROX1 Continued on next page

Chapter A 218 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Table A.2 – continued from previous page Cluster 1 Cluster 2 Cluster 3 CCDC64B MT1E miR-200a-3p BMI1 miR-1469 PRR14 CHGA MT1F miR-200a-5p BMP8B miR-146b-5p PRRG4 CHGB MT1G miR-200b-3p BOLA1 miR-192-5p PYGL CHRNB2 MT1X miR-200c-3p BRD2 miR-195-5p RAD51C CHST4 MYBPC2 miR-200c-5p BRINP3 miR-20a-5p RAET1G CKMT1A MYH2 miR-205-3p BTBD6 miR-2277-5p RAET1L CLDN7 NANOG miR-367-5p BTNL9 miR-3127-5p RASEF CNTN2 NECAB1 miR-371a-3p C11orf70 miR-3200-3p RBM15 CR2 NLRP2 miR-371a-5p C15orf40 miR-338-3p RBP5 CRB3 NLRP7 miR-372-3p C17orf51 miR-338-5p RCCD1 CRYBB1 NMRAL1 miR-373-3p C19orf45 miR-424-3p REEP1 CRYGD NODAL miR-373-5p C1GALT1C1L miR-424-5p RHOT1 CSH1 NRROS miR-429 C1orf115 miR-449a RHOV CSH2 NSG1 miR-519b-3p C1QL4 miR-449b-5p RIMS4 CXCR2 OTUD6B IQCA1 C2orf88 miR-449c-5p RNASEH2C DCAF12L1 OVOL2 ITLN2 C5orf63 miR-503-5p RNF150 DDX25 OXCT2 JAKMIP1 C8orf33 miR-542-5p RNF40 DNAJA4 PAK1 KCNK10 C8orf34 miR-5683 RP5-862P8.2 DNMT3B PCNXL2 KCNV1 CACNB4 miR-5699-5p RPL3L DOCK2 PDPR KCTD6 CAMK2B miR-629-5p RPRD1A DPEP1 PDZD4 LOXHD1 CARD6 miR-6500-3p RPS4X DPPA2 PHC1 MESP1 CAT miR-7975 RTN1 DPPA4 PIM2 MESP2 CCDC116 miR-99a-5p RUNDC3B DSG3 PIPOX MIXL1 CCDC117 HSPA1A RWDD2B EAF2 PLPPR4 MYL4 CCDC189 HSPA1B SAXO2 ECHDC3 PNPLA5 OTX2 CCNO HSPA1L SCARA5 EFCAB13 POLR3G PIK3R5 CCSER1 HSPA4L SDHA EMB POU5F1 PRR9 CD19 HYKK SFTA3 EPCAM PRKCQ RASSF6 CD207 IAH1 SHISA2 EPHX3 PROK2 RYR3 CD302 ICAM2 SIDT1 ESRP1 PTPRN2 S100A14 CDADC1 IDI1 SIM1 FA2H PYCARD SHISA6 CDH17 IFIH1 SIM2 FAAH2 RAB17 STK32A CDH20 IGIP SIX1 FAM101B RAB25 T CDKN2C IL15RA SIX2 FAM124A RBM47 TTN CGA IL2RG SLAIN1 FAM19A4 RCL1 ZAP70 CKLF INHBB SLC17A7 FAM46B RIT2 ZNF578 CLEC4F IRF8 SLC25A27 FAM78B RPL39L CLK2 ISL2 SLC27A2 Continued on next page

Chapter A 219 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Table A.2 – continued from previous page Cluster 1 Cluster 2 Cluster 3 FAM83E SCG3 CNNM1 ITGAL SLC30A3 FAM83F SCGB3A2 CNNM4 ITPKA SLC38A3 FGF8 SEC14L5 CNPY1 KAZALD1 SLC6A11 FHDC1 SELV CORO6 KCNC1 SLFN11 FLVCR2 SEMG1 CRACR2A KCNIP3 SLITRK5 FOXH1 SEPHS1 CRHR1 KCNJ11 SMDT1 FOXI2 SETSIP CSNK1E KCTD19 SMOC1 FZD5 SH2D3A CSPG5 KDM5C SNAP47 GALNT3 SLC15A1 CTB-55O6.8 KIAA0100 SNAP91 GLB1L3 SLC15A3 CXCL16 KIAA0907 SNX22 GLDC SLC18A2 CXorf57 KLC3 SOWAHA GLS2 SLFN12 DCDC2 KLF12 SP9 GNA14 SLFN13 DCT KLF4 SPATA6L GOLGA6A SMPDL3B DIS3 KLHL11 SPDYC GPR160 SNAI3 DLL1 KLHL15 SPEN GRID2 ST14 DLX4 KLHL41 SPOCK3 GRPR STAG3 DMBX1 KLK1 SPTB GSTO2 SUCLA2 DMRT3 KPNA5 SRPK3 HBA2 TCEAL5 DMRTA2 KRTAP19-1 STAC2 HENMT1 TDGF1 DMTN LAMA3 STARD5 HERC6 TDRP DNAJC12 LAMA4 SUV39H1 HESX1 TERF1 DNAJC22 LBX1 SUZ12 miR-1246 TFR2 DNPH1 LDHC SYCP2 miR-1248 TMEM125 DOC2A LHX2 SYK miR-1251-3p TMEM30B DUSP19 LHX4 SYP miR-1323 TMPRSS2 DUSP9 LHX9 SYT11 miR-141-3p TRABD2A E2F2 LINS1 SYTL4 miR-150-5p TRPM6 ECEL1 LMBRD2 TBC1D2B miR-155-3p TTC39C EDC3 LMX1B TCF24 miR-2113 UNC5D EEF1A2 LONRF2 TCHH miR-302a-5p UPK3B ELOVL3 LONRF3 TDRD6 miR-3171 USP44 EML5 LRRC75A TEX14 miR-3675-5p VASH2 EML6 LRRK2 TIGD3 miR-3687 VAV1 EMX2 LTK TIPIN miR-372-5p VSNL1 EN2 LYSMD1 TKTL1 miR-3937 VWDE ENPP4 MACROD2 TLE4 miR-4449 ZFP42 EPHA10 MAK TLL1 miR-4492 ZFP57 EPHA5 MAN2A2 TLX3 Continued on next page

Chapter A 220 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Table A.2 – continued from previous page Cluster 1 Cluster 2 Cluster 3 miR-4497 ZNF208 EPHA6 MANSC1 TM2D3 miR-4508 ZNF253 ERAP2 MAP3K13 TMEM106C miR-4699-3p ZNF311 EXOC6 MCIDAS TMEM132E miR-4792 ZNF350 EXOC8 MCOLN2 TMEM173 miR-498 ZNF454 EYA4 MED9 TMEM178B miR-512-3p ZNF492 F12 MEGF11 TMEM38A miR-512-5p ZNF501 FAM132B MEI1 TMEM80 miR-516a-5p ZNF502 FAM199X MFSD6 TP73 miR-516b-5p ZNF506 FAM50B MGARP TPPP miR-517-5p ZNF528 FAM81A MGAT4A TRAPPC13 miR-517a/b- ZNF544 FBXL3 MKX TRAPPC8 3p miR-518a-3p ZNF552 FBXL8 MNX1 TRIM43 miR-518b ZNF572 FEM1B MOCOS TRIM52 miR-518c-3p ZNF613 FER1L5 MPI TRIM7 miR-518d-3p ZNF649 FGF5 MR1 TRMT2B miR-518e-3p ZNF667 FGF9 MST1R TRPC3 miR-518f-3p ZNF677 FHL1 MYOM2 TSKS miR-518f-5p ZNF829 FLT3LG MYOM3 TTC32 miR-519c-3p ZNF844 FLT4 MYT1 TTC6 miR-519d-3p ZNF860 FOXA1 NALCN UBB miR-520a-3p ZNF880 FOXC1 NCOR1 UBE2Q2L miR-520a-5p ZNF98 FOXD2 NCR3LG1 ULBP1 miR-520c-3p FOXE1 NDFIP2 ULBP2 miR-520d-3p FOXG1 NEIL1 ULK3 miR-520d-5p FOXP2 NEUROG2 UQCR10 miR-523-3p FRK NKD2 USH1C miR-524-3p GALNTL6 NKX2-1 VAX2 miR-524-5p GBX1 NKX2-2 VGLL2 miR-526b-3p GFI1 NKX2-4 VWA5B2 miR-526b-5p GGPS1 NKX2-8 VWA9 miR-7641 GJA3 NMUR1 WDR76 miR-7704 GLRB NOD2 YPEL3 GNGT1 NOXA1 YPEL4 GNL1 NPTX1 YY1AP1 GOLGA8K NR2E1 ZBTB33 GPM6A NR2F2 ZCCHC12 GPR180 NR3C2 ZIC1 Continued on next page

Chapter A 221 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Table A.2 – continued from previous page Cluster 1 Cluster 2 Cluster 3 GPRASP2 NRN1 ZMYND15 GPRIN3 NTN1 ZNF24 GRID1 OAS3 ZNF248 GRIN2C OLIG1 ZNF280A H1F0 OLIG2 ZNF536 HAP1 ONECUT2 ZNF736 HCAR1 OPHN1 ZNF768 HDAC8 OSR2 ZSCAN30 HES5 OTUD1 ZXDA OTX1 ZYG11A

Table A.3: Co-expressed clusters (4-6) of miRNAs and protein-coding genes All protein-coding genes and miRNAs found to be highly co-expressed in clusters 4-6 identified in Chapter 4.

Cluster 4 Cluster 5 Cluster 6 ABCA10 CXCL14 HSPG2 PROK1 ALX3 C1orf105 ABCA8 CXCL8 HTR2B PRR16 APC2 CD300E ABCA9 DCN HTRA1 PRSS35 ASIC2 CYB5D1 ACVRL1 DLL4 HTRA3 PSG4 CHODL GABRP ADAM12 DPP10 ICAM1 PTGS2 CNGA1 IGSF10 ADAM9 DPP4 IFIT3 PTX3 CNR1 LIX1 ADAMTSL5 DRAM1 IFNGR1 PVR CNTN5 PRPH ADCY4 DYNLT3 IGF1 RAB27B CORIN PRR15 ADGRA2 ECE1 IGFBP3 RASGRP3 CRISPLD2 RAB37 ADGRG6 EGFL6 IGFBP7 RCN1 DCX RGS4 AFAP1L2 EGFLAM IL18R1 RCN3 EN1 SLC9A3R1 AKAP6 EHD3 IL1R1 RELN EPHA3 SPNS2 ALDH1L2 EMCN IL1RL1 RGS1 GOLIM4 TECRL ANO1 ENDOD1 IL33 ROBO4 HAND2 TRIM55 ARHGDIB ENTPD3 IL4I1 RRAD HOXB2 ARHGEF3 ERG IL6 RSPO2 miR-181a-2- 3p ARSI ERLEC1 IL6ST S1PR1 miR-6800-3p ART4 ERP27 IL7R S1PR3 miR-99b-3p ASAH1 ERVV-1 ITGA1 SARM1 ISM1 ATP7B ERVV-2 ITGA11 SBSPON KIF26B Continued on next page

Chapter A 222 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Table A.3 – continued from previous page Cluster 4 Cluster 5 Cluster 6 BCO2 EVI5 KCNA3 SCN3A MAB21L2 BDKRB1 F5 KCND3 SDF4 MCHR1 BDKRB2 FAM114A1 KCNE4 SDPR MECOM BDNF FAM163B KCNQ5 SELE MEIS1 BIK FAM46A KCTD16 SGIP1 MEIS2 BMP1 FAP LAMB2 SHE NEFM BMP10 FBLN2 LAYN SIL1 NELL1 BMP6 FBLN5 LINGO2 SLA NTRK2 C10orf54 FBN1 LMCD1 SLC14A1 PBX1 C15orf41 FIBIN LOX SLC22A2 PCDH17 C1QTNF1 FILIP1L LOXL4 SLC22A3 PCSK1N C1S FKBP10 LRP10 SLC2A10 PLPPR5 C3 FKBP14 LRRC15 SLC46A3 PRRX1 C7 FKBP7 LRRC32 SLC4A4 RARB CALCRL FLT1 LRRN4 SLC6A17 SAMD11 CCDC183 FMOD LTBP1 SLC7A4 SLC5A7 CCDC184 FN1 LTBP3 SLIT3 SORCS1 CCDC68 FNDC3B LTBR SMCO3 ST6GAL2 CCDC80 FOSL2 LUM SNCAIP TBX2 CCL2 FOXF1 MALL SOD3 TLX2 CCL7 FSTL3 MAML2 SPARC TSHZ2 CD55 GALNT1 Mar-03 SRPX2 TXK CD69 GALNT5 MASP1 SST UNC5C CD82 GBP1 MATN2 ST3GAL1 CD93 GBP2 MEST STOM CDC42EP5 GBP3 MFAP5 STXBP6 CDH11 GBP4 MFI2 SULF2 CDH13 GBP5 MGP SUSD2 CDH5 GFRA3 MMRN2 SVEP1 CDKN2B GGT5 MORC4 SYNPO CEBPD GGTLC2 MSRB3 SYNPO2L CFI GJA4 MYDGF SYT10 CHPF GLIS3 MYH15 TBC1D8B CHPF2 GPBAR1 NCOA7 TBX20 CHRM2 GREM2 NFATC2 TBX4 CHSY3 GRIA3 NFKBIZ TDO2 CKAP4 H2AFJ NID2 TFPI CLEC1B HEATR5A NIPAL3 TFPI2 Continued on next page

Chapter A 223 MicroRNA Regulation of Chondrogenesis in Human Embryonic Stem Cells

Table A.3 – continued from previous page Cluster 4 Cluster 5 Cluster 6 CLEC2B HEG1 NNMT TGFBI CLIC3 HGF NOX5 TGFBR2 CLUL1 HOPX NUCB1 TGFBR3 COL15A1 HRH1 NXPE2 TGM2 COL16A1 miR-1245a ODF3B THBD COL1A1 miR-126-3p OLR1 TIMP1 COL1A2 miR-126-5p OSMR TIMP3 COL21A1 miR-143-3p P4HA2 TMED10 COL3A1 miR-143-5p P4HA3 TMEM263 COL4A1 miR-145-5p P4HB TMEM87B COL4A2 miR-188-5p PABPC4L TNFAIP3 COL4A5 miR-193a-3p PAPPA TNFRSF9 COL4A6 miR-199a/b- PARM1 TPST1 3p COL5A1 miR-214-5p PCDH12 TRIM8 COLEC10 miR-22-3p PCOLCE2 TSLP COPZ2 miR-22-5p PDIA5 TSPAN5 CPA1 miR-29a-5p PDLIM5 TTR CPA4 miR-3064-5p PITX2 TXNDC15 CPQ miR-3117-3p PLA2R1 TXNDC5 CPZ miR-3194-5p PLD1 TYMP CREB3L1 miR-335-5p PLN TYRP1 CRHBP miR-4636 PLOD1 UACA CSGALNACT1 miR-490-3p PLOD2 VCAM1 CSRNP1 miR-574-3p PLVAP VTN CTBS miR-574-5p PLXNB3 WIPI1 CTHRC1 miR-592 POFUT2 WISP1 CTSA miR-675-3p POSTN WNT2 CTSB miR-675-5p PPIC YIPF5 CXCL1 HSPB6 PRCP ZNF469 PRELP ZNF804A

Chapter A 224