Novel Insights Into Megakaryopoiesis, Thrombopoiesis and Acute Coronary
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Novel insights into megakaryopoiesis, thrombopoiesis and acute coronary thrombosis: transcriptome profiling of the haematopoietic stem cell, megakaryocyte and platelet Fizzah Aziz Choudry This dissertation is submitted to the University of Cambridge for the degree of Doctor of Philosophy September 2018 Hughes Hall, Cambridge SUMMARY Novel insights into megakaryopoiesis, thrombopoiesis and acute coronary thrombosis: transcriptome profiling of the haematopoietic stem cell, megakaryocyte and platelet Fizzah Aziz Choudry The aim of this project was to investigate the transcriptome of human haematopoietic stem cells (HSCs), megakaryocytes and platelets to gain insights into steady state and accelerated thrombopoiesis that occurs in states of haemostatic demand and in thrombosis by applying these findings to the pathological setting of acute coronary thrombosis. To investigate transcriptional heterogeneity within the human HSC population, single cell RNA sequencing was performed in human bone marrow HSCs. Transcriptionally distinct subpopulations were identified including two megakaryocyte biased subsets with potentially differing functional relevance. Both populations expressed megakaryocyte specific transcripts, one of which also co-expressed common myeloid and megakaryocyte-erythroid progenitor transcripts while the other did not. This study represents the first interrogation of the human bone marrow megakaryocyte transcriptome. Cells were collected from healthy human bone marrow and analysed by low input and single cell RNA sequencing. To identify novel drivers of megakaryocyte maturation, the human bone marrow megakaryocyte transcriptome was compared to that of megakaryocytes cultured from human CD34+ cells, a process known to generate immature megakaryocytes. Transcriptional signatures associated with increasing megakaryocyte ploidy were then investigated. Increasing megakaryocyte ploidy level was found to be associated with an upregulation of transcripts involved in translation and protein processing as well as expression of a number of transmembrane receptors which might have functional relevance. Finally, the pathological setting of acute coronary thrombosis was used as a model for accelerated thrombopoiesis. Megakaryocyte and platelet transcriptomes were compared between patients with acute myocardial infarction (AMI) as well as severe coronary disease and a control group. The transcriptional signature relating to disease compared to control in megakaryocytes included upregulation of platelet activation related transcripts in megakaryocytes isolated from patients with AMI and severe coronary artery disease. I DECLARATION This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except as declared below and specified in the text. It is not substantially the same as any that I have submitted, or, is being concurrently submitted for a degree or diploma or other qualification at the University of Cambridge or any other University or similar institution except as declared in the Preface and specified in the text. I further state that no substantial part of my dissertation has already been submitted, or, is being concurrently submitted for any such degree, diploma or other qualification at the University of Cambridge or any other University or similar institution except as declared below and specified in the text It does not exceed the prescribed word limit for the relevant Degree Committee. The following collaborations have contributed to this work: 1. Nbeal2+/- mice used for megakaryocyte viability experiments were generated by the Wellcome Trust Sanger Institute and provided by Dr C Ghevaert’s group, Department of Haematology, University of Cambridge, UK. 2. NOD/LtSz-scidIL2Rgnull mice (Jackson Laboratory) used for xenotransplant experiments were provided by Dr E Laurenti’s group, Department of Haematology, University of Cambridge, UK. All xenotransplantation work was performed in collaboration with Dr E Laurenti’s group. 3. Platelet activation and function work was performed in collaboration with Dr K Downes’ group, Department of Haematology, University of Cambridge, UK. 4. Statistical analysis of RNA sequencing data was performed by Dr F Bagger, European Bioinformatics Institute, Hinxton, UK, and Dr R Petersen and Dr L Grassi, Department of Haematology, University of Cambridge, UK. Supervisors: Willem Ouwehand (University of Cambridge) Anthony Mathur (Queen Mary, University of London) II ACKNOWLEDGEMENTS I would like to thank my supervisors Willem Ouwehand, Anthony Mathur and John Martin who not only inspired me to take on this exciting project in the first place but who have provided ongoing guidance and support throughout. Particular thanks must go to Mattia Frontini for the motivation, intellectual stimulation, continued encouragement and technical advice without which this work would not have been possible. I would also like to thank Iain Macaulay for taking me under his wing at the Sanger Institute, teaching me about the sequencing world and helping me take on the challenge of megakaryocyte single cell RNA-seq. Thanks also goes to Frederik Bagger for his tireless help with RNA-seq analysis. I must also thank all the members of Willem’s group and collaborators who have contributed time, materials and ideas to help with this work, in particular, Samantha Farrow, Kate Downes and Elisa Laurenti. I would like to thank Rakesh Uppal and the rest of the Cardiothoracic team at Barts for welcoming me to theatres so often for samples and to the Barts Research team for their support in my endeavours. And of course thanks goes to the patients and volunteers who consented to be in this study. A special thanks goes to my family who have lived every bit of this long journey with me. The long hours, the uncertainty of experiments, the endless writing and the time away from the world. They have looked after me and supported me in every way from the very beginning and this is as much their thesis as it is mine. Thank you for understanding, being patient and doing this with me. Finally, I would like to thank the Medical Research Council for their financial support. III ABBREVIATONS AND CONVENTIONS Abbreviations ACS Acute coronary syndrome ADP Adenosine diphosphate AMI Acute myocardial infarction APC Allophycocyanin B2M B2 microglobulin Bp Base pairs BV Brilliant violet CAD Coronary artery disease CD Cluster of differentiation cDNA Copy deoxyribonucleic acid CFU Colony-forming unit CLP Common lymphoid progenitor CMP Common myeloid progenitor CRP-XL Crosslinked collagen related peptide Cy Cyanine DAPI 4',6-Diamidino-2-Phenylindole DNA Deoxyribonucleic acid ECG Electrocardiogram ERCC External RNA Controls Consortium FACS Fluorescence activated cell sorting FITC Fluorescein isothyocyanate GAPDH Glyceraldehyde-3-phosphate dehydrogenase GFP Green fluorescent protein GMP Granulocyte-macrophage progenitor GO Gene ontology GP Glycoprotein G&T-seq Genome and transcriptome sequencing GWAS Genome-wide association study Hb Haemoglobin HGNC HUGO gene nomenclature committee HSA Human serum albumin HSC Haematopoietic stem cell IPF Immature platelet fraction iPSC Induced pluripotent stem cells LMPP Lymphoid primed multipotent progenitor LV Left ventricle IV MegE Megakaryocyte-Erythroid lineage MEP Megakaryocyte-erythroid progenitor MK Megakaryocyte MPL Myeloproliferative leukaemia protein MPP Multipotent progenitor MPV Mean platelet volume mRNA Messenger ribonucleic acid NSG NOD scid gamma NSTEMI Non ST-elevation myocardial infarction PBS Phosphate buffered saline PCA Principal component analysis PCT Plateletcrit PDW Platelet distribution width PE Phycoerythrin PerCP Peridinin-Chlorophyll-protein P-LCR Platelet large cell ratio Poly(A) Poly-adenylated Plt Platelet PLT Platelet count RNA Ribonucleic acid RNA-seq RNA sequencing rRNA Ribosomal ribonucleic acid RT-qPCR Real time quantitative polymerase chain reaction STEMI ST-elevation myocardial infarction SVM Support vector machine TPO Thrombopoietin TRAP-6 Thrombin receptor activating peptide - 6 WC White cell count Gene, transcript and protein nomenclature Where possible the HUGO Gene Nomenclature Committee (HGNC) gene symbols and guidelines have been used to describe genes and gene products. Human gene and transcript symbols are capitalised and italicised (e.g., ITGA2B) and proteins are represented in standard fonts (e.g., TPO). V TABLE OF CONTENTS SUMMARY…………………………………………………………………………………………I DECLARATION………………………………………………………………………………….. II ACKNOWLEDGEMENTS………………………………………………………………………. III ABBREVIATIONS AND CONVENTIONS…………………………………………………….. IV Abbreviations...................................................................................................................... IV Gene, transcript and protein nomenclature.........................................................................V TABLE OF CONTENTS………………………………………………………………………… VI CHAPTER 1………………………………………………………………………………………. 1 INTRODUCTION 1.1 Megakaryopoiesis………………………………………………………………………. 1 1.1.1 Haematopoietic stem cells…………………………………………………… 1 1.1.2 Early megakaryocyte lineage commitment from the HSC………………... 3 1.1.3 Megakaryocyte-biased HSC population……………………………………. 4 1.1.4 Similarities between HSCs and megakaryocytes and interaction within the stem cell niche…………………………………………………………….. 6 1.1.5 Terminal megakaryopoiesis………………………………………………….. 9 1.1.6 Polyploidisation by endomitosis……………………………………………... 9 1.1.7 Cytoplasmic maturation………………………………………………………. 11 1.1.8 Platelet formation………………………………………………………………