Deciphering the Mechanisms of Heterogeneity within Haematopoiesis in Health, Development & Disease

Haematopoiesis represents one of the most intricate stem cell processes; in terms of the range of diverse cellular output and the extent of turnover through the system. It also stands as one of the most well characterised cellular systems given the accessibility of the tissue. As our understanding of this system has evolved, a key characteristic which has become increasingly clear is the degree of heterogeneity that exists within the system. This heterogeneity occurs at various levels: within discrete cell types or the global hierarchy, temporally across human development, and conditionally driven by altered cell-intrinsic factors (e.g. mutations) and cell-extrinsic factors (e.g. inflammation) as is seen in disease. The best way to understand heterogeneity is to look at cells at the smallest possible unit scale: the single cell level. Therefore, the resolution provided by single cell transcriptomic sequencing (scRNA-seq), combined with its interpretability, has been a pivotal driver to our understanding of haematopoietic heterogeneity and the mechanisms driving it. scRNA-seq focusses exclusively on measuring spliced mRNA transcript abundance within cells. My work is centred on leveraging adjunct modalities in combination with scRNA-seq to improve our ability to uncover further heterogeneity across scales and explore the contributing mechanisms. Starting at the scale of an individual cellular compartment, I incorporate unspliced pre-mRNA abundance to enable the discrimination of quiescent and active Haematopoietic Stem Cells (HSCs) from transcriptomes alone. Having separated these HSC subtypes, my single-cell analysis reveals previously unrecognised features of HSC heterogeneity, such as how HSCs interconvert in murine and adult bone marrow during homeostasis, as well as how HSC dormancy and activity signatures show dynamic changes during fetal/post-natal development and are dysregulated by the pre-leukaemic mutation Jak2 V617F. Moreover, this work reveals that leukaemia arrested at different stages of differentiation express distinct HSC dormancy genes and differ in their prognosis, pointing towards an underexplored, yet therapeutically relevant, complexity of the stem cell state. I then integrate clonal barcoding with scRNA-seq to interrogate why human developmental haematopoiesis exhibits temporal heterogeneity in the balance of myeloid and erythroid production between the foetal and peri-natal period. With this ground-truth clonal information, I identify a unique stem cell state during the foetal stage characterised by a MYC-enriched signature that promotes high rates of erythroid expansion over myeloid. Finally, I focus on how heterogeneity in haematopoiesis can be conferred through differing cell-intrinsic or cell-extrinsic conditions. By again harnessing unspliced with spliced mRNA abundance, I develop a bioinformatic technique, diffGEK, that compares differences in transcription, splicing and degradation rates between conditions. This approach provides an additional angle to further disentangle heterogeneity and provide a new source of mechanistic gene candidates. Applying this novel gene expression kinetics analysis in combination with traditional alternative splicing analysis, unveils key mechanisms and gene pathways driving ineffective erythropoiesis and luspatercept efficacy in SF3B1-mutant erythroid cells – a common myelodysplastic syndrome (MDS) mutation in a component of the spliceosome. Understanding the intricacies of haematopoietic heterogeneity is crucial, given its implications for various diseases and its relevance to advancements in stem cell technologies. Together, by utilising these additional modalities, in combination with single-cell transcriptomics, this research further disentangles and highlights mechanisms for haematopoietic heterogeneity across different scales. I nominate pathways regulating the dormancy-activity axis in HSCs as therapeutic targets, uncover foetal stem cell fates that holds significant potential for ex vivo engineering approaches aimed at enhancing red blood cell output for cell therapies, and provide an additional framework to better understand treatment for splicing factor-mutant MDS.

Name dc:type.qualificationname

Doctor of Philosophy (PhD)

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2024

Author dc:creator

• Chabra, Shirom

Advisor dc:contributor.advisor

• Gottgens, Berthold

• Computational Biology
• Bioinformatics
• Machine Learning
• Artificial Intelligence
• Haematology
• Haematopoietic Stem Cells
• Myelodysplastic Syndrome
• Stem Cell Engineering
• Leukaemia
• Single Cell RNA-sequencing
• Transcriptomics
• RNA Velocity
• Cellular Differentiation
• Differentiation Dynamics

Licence

• https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/c6fe7986-93be-4c11-932f-22de323d7a7b/download
• http://purl.org/NET/rdflicense/allrightsreserved

Language dc:language

eng

DOI dc:identifier.doi

https://doi.org/10.17863/CAM.115921

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/379951