1
|
Oedekoven CA, Belmonte M, Bode D, Hamey FK, Shepherd MS, Che JLC, Boyd G, McDonald C, Belluschi S, Diamanti E, Bastos HP, Bridge KS, Göttgens B, Laurenti E, Kent DG. Hematopoietic stem cells retain functional potential and molecular identity in hibernation cultures. Stem Cell Reports 2021; 16:1614-1628. [PMID: 33961793 PMCID: PMC8190576 DOI: 10.1016/j.stemcr.2021.04.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 04/07/2021] [Accepted: 04/07/2021] [Indexed: 02/02/2023] Open
Abstract
Advances in the isolation and gene expression profiling of single hematopoietic stem cells (HSCs) have permitted in-depth resolution of their molecular program. However, long-term HSCs can only be isolated to near purity from adult mouse bone marrow, thereby precluding studies of their molecular program in different physiological states. Here, we describe a powerful 7-day HSC hibernation culture system that maintains HSCs as single cells in the absence of a physical niche. Single hibernating HSCs retain full functional potential compared with freshly isolated HSCs with respect to colony-forming capacity and transplantation into primary and secondary recipients. Comparison of hibernating HSC molecular profiles to their freshly isolated counterparts showed a striking degree of molecular similarity, further resolving the core molecular machinery of HSC self-renewal while also identifying key factors that are potentially dispensable for HSC function, including members of the AP1 complex (Jun, Fos, and Ncor2), Sult1a1 and Cish. Finally, we provide evidence that hibernating mouse HSCs can be transduced without compromising their self-renewal activity and demonstrate the applicability of hibernation cultures to human HSCs.
Collapse
Affiliation(s)
- Caroline A Oedekoven
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Hills Road, Cambridge CB2 0XY, UK; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK
| | - Miriam Belmonte
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Hills Road, Cambridge CB2 0XY, UK; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK
| | - Daniel Bode
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Hills Road, Cambridge CB2 0XY, UK; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK
| | - Fiona K Hamey
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Hills Road, Cambridge CB2 0XY, UK; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK
| | - Mairi S Shepherd
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Hills Road, Cambridge CB2 0XY, UK; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK
| | - James Lok Chi Che
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Hills Road, Cambridge CB2 0XY, UK; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK
| | - Grace Boyd
- York Biomedical Research Institute, Department of Biology, University of York, York YO10 5DD, UK
| | - Craig McDonald
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Hills Road, Cambridge CB2 0XY, UK; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK
| | - Serena Belluschi
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Hills Road, Cambridge CB2 0XY, UK; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK
| | - Evangelia Diamanti
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Hills Road, Cambridge CB2 0XY, UK; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK
| | - Hugo P Bastos
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Hills Road, Cambridge CB2 0XY, UK; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK
| | - Katherine S Bridge
- York Biomedical Research Institute, Department of Biology, University of York, York YO10 5DD, UK
| | - Berthold Göttgens
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Hills Road, Cambridge CB2 0XY, UK; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK
| | - Elisa Laurenti
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Hills Road, Cambridge CB2 0XY, UK; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK
| | - David G Kent
- Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Hills Road, Cambridge CB2 0XY, UK; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK; York Biomedical Research Institute, Department of Biology, University of York, York YO10 5DD, UK.
| |
Collapse
|
2
|
Hamey FK, Lau WW, Kucinski I, Wang X, Diamanti E, Wilson NK, Göttgens B, Dahlin JS. Single-cell molecular profiling provides a high-resolution map of basophil and mast cell development. Allergy 2021; 76:1731-1742. [PMID: 33078414 PMCID: PMC8246912 DOI: 10.1111/all.14633] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 09/11/2020] [Accepted: 09/30/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND Basophils and mast cells contribute to the development of allergic reactions. Whereas these mature effector cells are extensively studied, the differentiation trajectories from hematopoietic progenitors to basophils and mast cells are largely uncharted at the single-cell level. METHODS We performed multicolor flow cytometry, high-coverage single-cell RNA sequencing analyses, and cell fate assays to chart basophil and mast cell differentiation at single-cell resolution in mouse. RESULTS Analysis of flow cytometry data reconstructed a detailed map of basophil and mast cell differentiation, including a bifurcation of progenitors into two specific trajectories. Molecular profiling and pseudotime ordering of the single cells revealed gene expression changes during differentiation. Cell fate assays showed that multicolor flow cytometry and transcriptional profiling successfully predict the bipotent phenotype of a previously uncharacterized population of peritoneal basophil-mast cell progenitors. CONCLUSIONS A combination of molecular and functional profiling of bone marrow and peritoneal cells provided a detailed road map of basophil and mast cell development. An interactive web resource was created to enable the wider research community to explore the expression dynamics for any gene of interest.
Collapse
Affiliation(s)
- Fiona K. Hamey
- Department of HaematologyWellcome–Medical Research Council Cambridge Stem Cell InstituteUniversity of CambridgeCambridgeUK
- Present address: JDRF/Wellcome Diabetes and Inflammation LaboratoryWellcome Centre for Human GeneticsUniversity of OxfordOxfordUK
| | - Winnie W.Y. Lau
- Department of HaematologyWellcome–Medical Research Council Cambridge Stem Cell InstituteUniversity of CambridgeCambridgeUK
| | - Iwo Kucinski
- Department of HaematologyWellcome–Medical Research Council Cambridge Stem Cell InstituteUniversity of CambridgeCambridgeUK
| | - Xiaonan Wang
- Department of HaematologyWellcome–Medical Research Council Cambridge Stem Cell InstituteUniversity of CambridgeCambridgeUK
| | - Evangelia Diamanti
- Department of HaematologyWellcome–Medical Research Council Cambridge Stem Cell InstituteUniversity of CambridgeCambridgeUK
| | - Nicola K. Wilson
- Department of HaematologyWellcome–Medical Research Council Cambridge Stem Cell InstituteUniversity of CambridgeCambridgeUK
| | - Berthold Göttgens
- Department of HaematologyWellcome–Medical Research Council Cambridge Stem Cell InstituteUniversity of CambridgeCambridgeUK
| | - Joakim S. Dahlin
- Department of HaematologyWellcome–Medical Research Council Cambridge Stem Cell InstituteUniversity of CambridgeCambridgeUK
- Department of MedicineKarolinska Institutet and Karolinska University HospitalStockholmSweden
| |
Collapse
|
3
|
Hamey FK, Göttgens B. Machine learning predicts putative hematopoietic stem cells within large single-cell transcriptomics data sets. Exp Hematol 2019; 78:11-20. [PMID: 31513832 PMCID: PMC6900257 DOI: 10.1016/j.exphem.2019.08.009] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 08/29/2019] [Accepted: 08/31/2019] [Indexed: 12/25/2022]
Abstract
Hematopoietic stem cells (HSCs) are an essential source and reservoir for normal hematopoiesis, and their function is compromised in many blood disorders. HSC research has benefitted from the recent development of single-cell molecular profiling technologies, where single-cell RNA sequencing (scRNA-seq) in particular has rapidly become an established method to profile HSCs and related hematopoietic populations. The classic definition of HSCs relies on transplantation assays, which have been used to validate HSC function for cell populations defined by flow cytometry. Flow cytometry information for single cells, however, is not available for many new high-throughput scRNA-seq methods, thus highlighting an urgent need for the establishment of alternative ways to pinpoint the likely HSCs within large scRNA-seq data sets. To address this, we tested a range of machine learning approaches and developed a tool, hscScore, to score single-cell transcriptomes from murine bone marrow based on their similarity to gene expression profiles of validated HSCs. We evaluated hscScore across scRNA-seq data from different laboratories, which allowed us to establish a robust method that functions across different technologies. To facilitate broad adoption of hscScore by the wider hematopoiesis community, we have made the trained model and example code freely available online. In summary, our method hscScore provides fast identification of mouse bone marrow HSCs from scRNA-seq measurements and represents a broadly useful tool for analysis of single-cell gene expression data.
Collapse
Affiliation(s)
- Fiona K Hamey
- Wellcome-MRC Cambridge Stem Cell Institute and Department of Haematology, University of Cambridge, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, United Kingdom.
| | - Berthold Göttgens
- Wellcome-MRC Cambridge Stem Cell Institute and Department of Haematology, University of Cambridge, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, United Kingdom
| |
Collapse
|
4
|
Wolf FA, Hamey FK, Plass M, Solana J, Dahlin JS, Göttgens B, Rajewsky N, Simon L, Theis FJ. PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells. Genome Biol 2019; 20:59. [PMID: 30890159 PMCID: PMC6425583 DOI: 10.1186/s13059-019-1663-x] [Citation(s) in RCA: 654] [Impact Index Per Article: 130.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Accepted: 02/26/2019] [Indexed: 02/02/2023] Open
Abstract
Single-cell RNA-seq quantifies biological heterogeneity across both discrete cell types and continuous cell transitions. Partition-based graph abstraction (PAGA) provides an interpretable graph-like map of the arising data manifold, based on estimating connectivity of manifold partitions ( https://github.com/theislab/paga ). PAGA maps preserve the global topology of data, allow analyzing data at different resolutions, and result in much higher computational efficiency of the typical exploratory data analysis workflow. We demonstrate the method by inferring structure-rich cell maps with consistent topology across four hematopoietic datasets, adult planaria and the zebrafish embryo and benchmark computational performance on one million neurons.
Collapse
Affiliation(s)
- F. Alexander Wolf
- Helmholtz Center Munich – German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Munich, Germany
| | - Fiona K. Hamey
- Department of Haematology and Wellcome and Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - Mireya Plass
- Berlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Jordi Solana
- Berlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Joakim S. Dahlin
- Department of Haematology and Wellcome and Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
- Department of Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Berthold Göttgens
- Department of Haematology and Wellcome and Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - Nikolaus Rajewsky
- Berlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Lukas Simon
- Helmholtz Center Munich – German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Munich, Germany
| | - Fabian J. Theis
- Helmholtz Center Munich – German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Munich, Germany
- Department of Mathematics, Technische Universität München, Munich, Germany
| |
Collapse
|
5
|
Abstract
Hematopoietic stem cells (HSCs) reside at the apex of the hematopoietic hierarchy, possessing the ability to self-renew and differentiate toward all mature blood lineages. Along with more specialized progenitor cells, HSCs have an essential role in maintaining a healthy blood system. Incorrect regulation of cell fate decisions in stem/progenitor cells can lead to an imbalance of mature blood cell populations-a situation seen in diseases such as leukemia. Transcription factors, acting as part of complex regulatory networks, are known to play an important role in regulating hematopoietic cell fate decisions. Yet, discovering the interactions present in these networks remains a big challenge. Here, we discuss a computational method that uses single-cell gene expression data to reconstruct Boolean gene regulatory network models and show how this technique can be applied to enhance our understanding of transcriptional regulation in hematopoiesis.
Collapse
Affiliation(s)
- Fiona K Hamey
- Department of Haematology, Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - Berthold Göttgens
- Department of Haematology, Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.
| |
Collapse
|
6
|
Dahlin JS, Hamey FK, Pijuan-Sala B, Shepherd M, Lau WWY, Nestorowa S, Weinreb C, Wolock S, Hannah R, Diamanti E, Kent DG, Göttgens B, Wilson NK. A single-cell hematopoietic landscape resolves 8 lineage trajectories and defects in Kit mutant mice. Blood 2018; 131:e1-e11. [PMID: 29588278 PMCID: PMC5969381 DOI: 10.1182/blood-2017-12-821413] [Citation(s) in RCA: 122] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 03/16/2018] [Indexed: 12/19/2022] Open
Abstract
Hematopoietic stem and progenitor cells (HSPCs) maintain the adult blood system, and their dysregulation causes a multitude of diseases. However, the differentiation journeys toward specific hematopoietic lineages remain ill defined, and system-wide disease interpretation remains challenging. Here, we have profiled 44 802 mouse bone marrow HSPCs using single-cell RNA sequencing to provide a comprehensive transcriptional landscape with entry points to 8 different blood lineages (lymphoid, megakaryocyte, erythroid, neutrophil, monocyte, eosinophil, mast cell, and basophil progenitors). We identified a common basophil/mast cell bone marrow progenitor and characterized its molecular profile at the single-cell level. Transcriptional profiling of 13 815 HSPCs from the c-Kit mutant (W41/W41) mouse model revealed the absence of a distinct mast cell lineage entry point, together with global shifts in cell type abundance. Proliferative defects were accompanied by reduced Myc expression. Potential compensatory processes included upregulation of the integrated stress response pathway and downregulation of proapoptotic gene expression in erythroid progenitors, thus providing a template of how large-scale single-cell transcriptomic studies can bridge between molecular phenotypes and quantitative population changes.
Collapse
Affiliation(s)
- Joakim S Dahlin
- Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research and Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge, United Kingdom
- Department of Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Fiona K Hamey
- Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research and Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge, United Kingdom
| | - Blanca Pijuan-Sala
- Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research and Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge, United Kingdom
| | - Mairi Shepherd
- Department of Haematology, University of Cambridge, Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge, United Kingdom; and
| | - Winnie W Y Lau
- Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research and Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge, United Kingdom
| | - Sonia Nestorowa
- Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research and Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge, United Kingdom
| | - Caleb Weinreb
- Department of Systems Biology, Harvard Medical School, Boston, MA
| | - Samuel Wolock
- Department of Systems Biology, Harvard Medical School, Boston, MA
| | - Rebecca Hannah
- Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research and Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge, United Kingdom
| | - Evangelia Diamanti
- Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research and Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge, United Kingdom
| | - David G Kent
- Department of Haematology, University of Cambridge, Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge, United Kingdom; and
| | - Berthold Göttgens
- Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research and Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge, United Kingdom
| | - Nicola K Wilson
- Department of Haematology, University of Cambridge, Cambridge Institute for Medical Research and Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge, United Kingdom
| |
Collapse
|
7
|
Hamey FK, Göttgens B. Sorting apples from oranges in single-cell expression comparisons. Nat Methods 2018; 15:321-322. [PMID: 29702635 DOI: 10.1038/nmeth.4675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Fiona K Hamey
- Department of Haematology, Cambridge Institute for Medical Research, and Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - Berthold Göttgens
- Department of Haematology, Cambridge Institute for Medical Research, and Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| |
Collapse
|
8
|
Loughran SJ, Comoglio F, Hamey FK, Giustacchini A, Errami Y, Earp E, Göttgens B, Jacobsen SEW, Mead AJ, Hendrich B, Green AR. Mbd3/NuRD controls lymphoid cell fate and inhibits tumorigenesis by repressing a B cell transcriptional program. J Exp Med 2017; 214:3085-3104. [PMID: 28899870 PMCID: PMC5626393 DOI: 10.1084/jem.20161827] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2016] [Revised: 07/04/2017] [Accepted: 07/25/2017] [Indexed: 02/02/2023] Open
Abstract
Differentiation of lineage-committed cells from multipotent progenitors requires the establishment of accessible chromatin at lineage-specific transcriptional enhancers and promoters, which is mediated by pioneer transcription factors that recruit activating chromatin remodeling complexes. Here we show that the Mbd3/nucleosome remodeling and deacetylation (NuRD) chromatin remodeling complex opposes this transcriptional pioneering during B cell programming of multipotent lymphoid progenitors by restricting chromatin accessibility at B cell enhancers and promoters. Mbd3/NuRD-deficient lymphoid progenitors therefore prematurely activate a B cell transcriptional program and are biased toward overproduction of pro-B cells at the expense of T cell progenitors. The striking reduction in early thymic T cell progenitors results in compensatory hyperproliferation of immature thymocytes and development of T cell lymphoma. Our results reveal that Mbd3/NuRD can regulate multilineage differentiation by constraining the activation of dormant lineage-specific enhancers and promoters. In this way, Mbd3/NuRD protects the multipotency of lymphoid progenitors, preventing B cell-programming transcription factors from prematurely enacting lineage commitment. Mbd3/NuRD therefore controls the fate of lymphoid progenitors, ensuring appropriate production of lineage-committed progeny and suppressing tumor formation.
Collapse
Affiliation(s)
- Stephen J Loughran
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, England, UK
- Wellcome Trust/MRC Stem Cell Institute, University of Cambridge, Cambridge, England, UK
| | - Federico Comoglio
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, England, UK
- Wellcome Trust/MRC Stem Cell Institute, University of Cambridge, Cambridge, England, UK
| | - Fiona K Hamey
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, England, UK
- Wellcome Trust/MRC Stem Cell Institute, University of Cambridge, Cambridge, England, UK
| | - Alice Giustacchini
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, England, UK
| | - Youssef Errami
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, England, UK
- Wellcome Trust/MRC Stem Cell Institute, University of Cambridge, Cambridge, England, UK
| | - Eleanor Earp
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, England, UK
- Wellcome Trust/MRC Stem Cell Institute, University of Cambridge, Cambridge, England, UK
| | - Berthold Göttgens
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, England, UK
- Wellcome Trust/MRC Stem Cell Institute, University of Cambridge, Cambridge, England, UK
| | - Sten Eirik W Jacobsen
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, England, UK
- Wallenberg Institute for Regenerative Medicine, Department of Cell and Molecular Biology and Department of Medicine Huddinge, Karolinska Institutet and Center for Hematology and Regenerative Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Adam J Mead
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, England, UK
| | - Brian Hendrich
- Wellcome Trust/MRC Stem Cell Institute, University of Cambridge, Cambridge, England, UK
- Department of Biochemistry, University of Cambridge, Cambridge, England, UK
| | - Anthony R Green
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, England, UK
- Wellcome Trust/MRC Stem Cell Institute, University of Cambridge, Cambridge, England, UK
| |
Collapse
|
9
|
Hamey FK, Nestorowa S, Kinston SJ, Kent DG, Wilson NK, Göttgens B. Reconstructing blood stem cell regulatory network models from single-cell molecular profiles. Proc Natl Acad Sci U S A 2017; 114:5822-5829. [PMID: 28584094 PMCID: PMC5468644 DOI: 10.1073/pnas.1610609114] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Adult blood contains a mixture of mature cell types, each with specialized functions. Single hematopoietic stem cells (HSCs) have been functionally shown to generate all mature cell types for the lifetime of the organism. Differentiation of HSCs toward alternative lineages must be balanced at the population level by the fate decisions made by individual cells. Transcription factors play a key role in regulating these decisions and operate within organized regulatory programs that can be modeled as transcriptional regulatory networks. As dysregulation of single HSC fate decisions is linked to fatal malignancies such as leukemia, it is important to understand how these decisions are controlled on a cell-by-cell basis. Here we developed and applied a network inference method, exploiting the ability to infer dynamic information from single-cell snapshot expression data based on expression profiles of 48 genes in 2,167 blood stem and progenitor cells. This approach allowed us to infer transcriptional regulatory network models that recapitulated differentiation of HSCs into progenitor cell types, focusing on trajectories toward megakaryocyte-erythrocyte progenitors and lymphoid-primed multipotent progenitors. By comparing these two models, we identified and subsequently experimentally validated a difference in the regulation of nuclear factor, erythroid 2 (Nfe2) and core-binding factor, runt domain, alpha subunit 2, translocated to, 3 homolog (Cbfa2t3h) by the transcription factor Gata2. Our approach confirms known aspects of hematopoiesis, provides hypotheses about regulation of HSC differentiation, and is widely applicable to other hierarchical biological systems to uncover regulatory relationships.
Collapse
Affiliation(s)
- Fiona K Hamey
- Department of Haematology, Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 0XY, United Kingdom
| | - Sonia Nestorowa
- Department of Haematology, Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 0XY, United Kingdom
| | - Sarah J Kinston
- Department of Haematology, Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 0XY, United Kingdom
| | - David G Kent
- Department of Haematology, Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 0XY, United Kingdom
| | - Nicola K Wilson
- Department of Haematology, Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 0XY, United Kingdom
| | - Berthold Göttgens
- Department of Haematology, Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 0XY, United Kingdom
| |
Collapse
|
10
|
Abstract
Determining the differentiation potential of stem and progenitor cells is essential for understanding their function, yet our ability to do so is limited by the restrictions of experimental assays. Based on single-cell functional and molecular profiling experiments, a new computational approach shows how lineage commitment may occur in human haematopoiesis.
Collapse
Affiliation(s)
- Fiona K Hamey
- Department of Haematology, Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, United Kingdom
| | - Berthold Göttgens
- Department of Haematology, Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, United Kingdom
| |
Collapse
|
11
|
Hamey FK, Nestorowa S, Wilson NK, Göttgens B. Advancing haematopoietic stem and progenitor cell biology through single-cell profiling. FEBS Lett 2016; 590:4052-4067. [PMID: 27259698 DOI: 10.1002/1873-3468.12231] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2016] [Revised: 05/27/2016] [Accepted: 05/31/2016] [Indexed: 12/25/2022]
Abstract
Haematopoietic stem and progenitor cells (HSPCs) sit at the top of the haematopoietic hierarchy, and their fate choices need to be carefully controlled to ensure balanced production of all mature blood cell types. As cell fate decisions are made at the level of the individual cells, recent technological advances in measuring gene and protein expression in increasingly large numbers of single cells have been rapidly adopted to study both normal and pathological HSPC function. In this review we emphasise the importance of combining the correct computational models with single-cell experimental techniques, and illustrate how such integrated approaches have been used to resolve heterogeneities in populations, reconstruct lineage differentiation, identify regulatory relationships and link molecular profiling to cellular function.
Collapse
Affiliation(s)
- Fiona K Hamey
- Department of Haematology and Wellcome Trust - MRC Cambridge Stem Cell Institute, University of Cambridge, UK
| | - Sonia Nestorowa
- Department of Haematology and Wellcome Trust - MRC Cambridge Stem Cell Institute, University of Cambridge, UK
| | - Nicola K Wilson
- Department of Haematology and Wellcome Trust - MRC Cambridge Stem Cell Institute, University of Cambridge, UK
| | - Berthold Göttgens
- Department of Haematology and Wellcome Trust - MRC Cambridge Stem Cell Institute, University of Cambridge, UK
| |
Collapse
|