Inferring rules of lineage commitment in haematopoiesis
Open accessAbstract
How the molecular programs of differentiated cells develop as cells transit from multipotency through lineage commitment remains unexplored. This reflects the inability to access cells undergoing commitment or located in the immediate vicinity of commitment boundaries. It remains unclear whether commitment constitutes a gradual process, or else represents a discrete transition. Analyses of in vitro self-renewing multipotent systems have revealed cellular heterogeneity with individual cells transiently exhibiting distinct biases for lineage commitment. Such systems can be used to molecularly interrogate early stages of lineage affiliation and infer rules of lineage commitment. In haematopoiesis, population-based studies have indicated that lineage choice is governed by global transcriptional noise, with self-renewing multipotent cells reversibly activating transcriptome-wide lineage-affiliated programs. We examine this hypothesis through functional and molecular analysis of individual blood cells captured from self-renewal cultures, during cytokine-driven differentiation and from primary stem and progenitor bone marrow compartments. We show dissociation between self-renewal potential and transcriptome-wide activation of lineage programs, and instead suggest that multipotent cells experience independent activation of individual regulators resulting in a low probability of transition to the committed state.
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In the absence of fate tracking, all inferred biases in native hematopoiesis are speculative.
“Finally, while single-cell genomic approaches have produced compelling evidence that observed cellular heterogeneity reflects downstream lineage decisions (Herring et al., 2018; La Manno et al., 2018; Rodriguez-Fraticelli et al., 2018), in the absence of fate tracking, all inferred biases in native hematopoiesis are speculative (Pina et al., 2012; Velten et al., 2017).”
From Unraveling Hematopoiesis through the Lens of Genomics (2020) · cites this paper as Pina et al., 2012
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“Yet, both of these populations (Sca1-high and Sca1-low) can reconstitute self-renewing cultures with multipotency, suggesting a robust mechanism for the maintenance of stem cell pools, although transcriptome fluctuation is still under debate (Chang et al., 2008; Pina et al., 2012).”
BackgroundMay, G. E., Soneji, S., Tipping, A. J., Teles, J., McGowan, S. J., Wu, M., Guo, Y., Fugazza, C., Brown, J., Karlsson, G., et al. (2013) · Cell stem cell · doi:10.1016/j.stem.2013.09.003 · Cited by 88 · see citing works
“Primary Cell Harvest and Isolation Primary murine bone marrow cells were harvested and FACsorted as previously reported (Pina et al., 2012).”
Tan, D. W., Jensen, K. B., Trotter, M. W. B., Connelly, J. T., Broad, S., & Watt, F. M. (2013) · Development · doi:10.1242/dev.087551 · Cited by 87 · see citing works
“Complex regulatory networks define stable, interconvertible ‘attractor’ states and stochastic fluctuations in gene expression (transcriptional noise) drive transitions between states (MacArthur et al., 2008; Enver et al., 2009; Pina et al., 2012).”
Wu, W.-S., Morrissey, C. S., Keller, C. A., Mishra, T., Pimkin, M., Blobel, G. A., Weiss, M. J., & Hardison, R. C. (2014) · Genome Research · doi:10.1101/gr.164830.113 · Cited by 82 · see citing works
“Binding of TAL1 in HPC-7 cells and other less differentiated cells could participate in lineage priming, i.e., the expression of lineage-specific genes in multilineage progenitors (Mansson et al. 2007; Pina et al. 2012).”
BackgroundAn autonomous CEBPA enhancer specific for myeloid-lineage priming and neutrophilic differentiation
Avellino, R., Havermans, M., Erpelinck-Verschueren, C. A. J., Sanders, M. A., Hoogenboezem, R. M., van de Werken, H. J. G., Rombouts, E. J. C., van Lom, K., van Strien, P. M. H., Gebhard, C., et al. (2016) · Blood · doi:10.1182/blood-2016-01-695759 · Cited by 82 · see citing works
Regulatory network control of blood stem cells
Göttgens, B. (2015) · Blood · doi:10.1182/blood-2014-08-570226 · Cited by 82 · see citing works
Primed and ready: understanding lineage commitment through single cell analysis
Nimmo, R. A., May, G. E., & Enver, T. (2015) · Trends in Cell Biology · doi:10.1016/j.tcb.2015.04.004 · Cited by 82 · see citing works
Pluripotent stem cells reveal erythroid-specific activities of the GATA1 N-terminus
Byrska‐Bishop, M. S., VanDorn, D., Campbell, A. E., Betensky, M., Arca, P. R., Yao, Y., Gadue, P. J., Costa, F. F., Nemiroff, R. L., Blobel, G. A., et al. (2015) · Journal of Clinical Investigation · doi:10.1172/jci75714 · Cited by 81 · see citing works
Transcriptional control of vertebrate neurogenesis by the proneural factor Ascl1
Vasconcelos, F. F., & Castro, D. S. (2014) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2014.00412 · Cited by 79 · see citing works
“, period, amplitude) and, hence, trigger different functional outcomes (Mengel et al., 2010; Pina et al., 2012; Sequerra et al., 2013).”
Single-cell network analysis identifies DDIT3 as a nodal lineage regulator in hematopoiesis
Pina, C., Teles, J., Fugazza, C., May, G., Wang, D., Guo, Y., Soneji, S., Brown, J., Edén, P., Ohlsson, M., et al. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.05.016 · Cited by 72 · see citing works
Normal Hematopoiesis Is a Balancing Act of Self-Renewal and RegenerationPreprint
Olson, O. C., Kang, Y.-A., & Passegue, E. A. (2020) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a035519 · Cited by 78 · see citing works
Executable cancer models: successes and challenges
Clarke, M. A., & Fisher, J. (2020) · Nature reviews. Cancer · doi:10.1038/s41568-020-0258-x · Cited by 76 · see citing works
“Executable models allow the exploration of the sequence of molecular events in a cell: many events must occur in a precise sequence for a cell to function, from the short-scale ordering of events in the cell cycle 44,45 to more long-term orderings that occur during development 46 .”
BackgroundLineage Tracing of Pf4-Cre Marks Hematopoietic Stem Cells and Their Progeny
Calaminus, S. D. J., Guitart, A. V., Sinclair, A., Schachtner, H., Watson, S. P., Holyoake, T. L., Kranc, K. R., & Machesky, L. M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0051361 · Cited by 75 · see citing works
O’Shaughnessy-Kirwan, A., Signolet, J., Costello, I., Gharbi, S., & Hendrich, B. (2015) · Development · doi:10.1242/dev.125450 · Cited by 70 · see citing works
“Analogous situations have been described during haematopoiesis and neurogenesis, when stochastic or cyclic activation of key regulatory factors underlies the probability that a cell will enter a differentiation pathway (Imayoshi et al., 2013; Pina et al., 2012).”
The chromatin landscape and transcription factors in T cell programming
Rothenberg, E. V. (2014) · Trends in Immunology · doi:10.1016/j.it.2014.03.001 · Cited by 70 · see citing works
Towards a statistical mechanics of cell fate decisions
García‐Ojalvo, J., & Arias, A. M. (2012) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2012.10.004 · Cited by 67 · see citing works
Keap1‐Nrf2 system regulates cell fate determination of hematopoietic stem cells
Murakami, S., Shimizu, R., Roméo, P., Yamamoto, M. P., & Motohashi, H. (2014) · Genes to Cells · doi:10.1111/gtc.12126 · Cited by 63 · see citing works
How much can the tubule regenerate and who does it? An open question
Lombardi, D., Becherucci, F., & Romagnani, P. (2015) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfv262 · Cited by 58 · see citing works
The use of lineage tracing to study kidney injury and regeneration
Romagnani, P., Rinkevich, Y., & Dekel, B. (2015) · Nature Reviews Nephrology · doi:10.1038/nrneph.2015.67 · Cited by 56 · see citing works
Moussy, A., Cosette, J., Parmentier, R., da Silva, C., Corre, G., Richard, A., Gandrillon, O., Stockholm, D., & Páldi, A. (2017) · PLoS Biology · doi:10.1371/journal.pbio.2001867 · Cited by 52 · see citing works
Loss of Kat2a enhances transcriptional noise and depletes acute myeloid leukemia stem-like cells
Domingues, A. F., Kulkarni, R., Giotopoulos, G., Gupta, S., Vinnenberg, L., Arede, L., Foerner, E., Khalili, M., Adao, R. R., Johns, A., et al. (2020) · eLife · doi:10.7554/elife.51754 · Cited by 52 · see citing works
“We had previously shown that normal transitions into hematopoietic lineage specification associate with cell-tocell transcriptional heterogeneity (Pina et al., 2012; Teles et al., 2013).”
BackgroundEVI1 overexpression reprograms hematopoiesis via upregulation of Spi1 transcription
Ayoub, E., Wilson, M. P., McGrath, K. E., Li, A. J., Frisch, B. J., Palis, J., Calvi, L. M., Zhang, Y., & Perkins, A. S. (2018) · Nature Communications · doi:10.1038/s41467-018-06208-y · Cited by 52 · see citing works
Edri, S., Hayward, P. C., Jawaid, W., & Arias, A. M. (2019) · Development · doi:10.1242/dev.180190 · Cited by 51 · see citing works
“This situation is reminiscent of many stem and progenitor cell populations and suggests that, as in some of those cases (Huang, 2009; Moris et al., 2016; Pina et al., 2012), these different cell populations are in dynamic equilibrium.”
BackgroundSingle cell analysis of normal and leukemic hematopoiesis
Povinelli, B. J., Rodríguez-Meira, A., & Mead, A. J. (2017) · Molecular Aspects of Medicine · doi:10.1016/j.mam.2017.08.006 · Cited by 47 · see citing works
“By multiplexing assays for several genes encoding transcription factors, single cell analysis of HSPCs has also been employed to reveal novel transcription factor regulatory networks [29–31] and to explore transcriptional states associated with lineage commitment and loss of self-renewal [32].”
MethodTranscriptional Regulation of Lineage Commitment - A Stochastic Model of Cell Fate Decisions
Teles, J., Pina, C., Edén, P., Ohlsson, M., Enver, T., & Peterson, C. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003197 · Cited by 49 · see citing works
“The computational framework was designed and implemented using single cell expression data observations from different populations of the EML hematopoietic cell line [21].”
BackgroundMethodResultInfluentialRoch, A., Giger, S., Girotra, M., Campos, V., Vannini, N., Naveiras, O., Gobaa, S., & Lütolf, M. P. (2017) · Nature Communications · doi:10.1038/s41467-017-00291-3 · Cited by 48 · see citing works
Noise and the molecular processes underlying cell fate decision-making
Guillemin, A., & Stumpf, M. P. H. (2020) · Physical Biology · doi:10.1088/1478-3975/abc9d1 · Cited by 45 · see citing works
Critical transition and reversion of tumorigenesis
Shin, D., & Cho, K. (2023) · Experimental & Molecular Medicine · doi:10.1038/s12276-023-00969-3 · Cited by 44 · see citing works
Moris, N., Edri, S., Seyres, D., Kulkarni, R., Domingues, A. F., Balayo, T., Frontini, M., & Pina, C. (2018) · Stem Cells · doi:10.1002/stem.2919 · Cited by 44 · see citing works
Using variability in gene expression as a tool for studying gene regulation
Padovan-Merhar, O. M., & Raj, A. (2013) · WIREs Systems Biology and Medicine · doi:10.1002/wsbm.1243 · Cited by 42 · see citing works
Concise Review: Erythroid Versus Myeloid Lineage Commitment: Regulating the Master Regulators
Wolff, L., & Humeniuk, R. (2013) · Stem Cells · doi:10.1002/stem.1379 · Cited by 42 · see citing works
The Tetraspanin CD9 Affords High-Purity Capture of All Murine Hematopoietic Stem Cells
Karlsson, G., Rörby, E., Pina, C., Soneji, S., Reckzeh, K., Miharada, K., Karlsson, C., Guo, Y., Fugazza, C., Gupta, R., et al. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.07.020 · Cited by 41 · see citing works
“This is in line with our recent findings on individual cells from self-renewing cell lines where large-scale expression of lineage programs and self-renewal capacity were separated (Pina et al., 2012).”
MethodResultInfluentialDraper, J. E., Sroczyńska, P., Tsoulaki, O., Leong, H. S., Fadlullah, M. Z. H., Miller, C. J., Kouskoff, V., & Lacaud, G. (2016) · PLoS Genetics · doi:10.1371/journal.pgen.1005814 · Cited by 39 · see citing works
Wang, J., Jenjaroenpun, P., Bhinge, A., Angarica, V. E., del Sol, A., Nookaew, I., Kuznetsov, V. A., & Stanton, L. W. (2017) · Genome Research · doi:10.1101/gr.223313.117 · Cited by 35 · see citing works
Single cell lineage analysis of mouse embryonic stem cells at the exit from pluripotency
Trott, J., & Arias, A. M. (2013) · Biology Open · doi:10.1242/bio.20135934 · Cited by 37 · see citing works
“…(Guo et al., 2010), pluripotent mES cells (Hayashi et al., 2008; Tang et al., 2010; MacArthur et al., 2012; Trott et al., 2012) and haematopoietic stem cells (Pina et al., 2012; Moignard et al., 2013), but our study represents the first analysis of the early stages of differentiation of mES cells.”
BackgroundResultStudying Lineage Decision-Making In Vitro: Emerging Concepts and Novel Tools
Semrau, S., & van Oudenaarden, A. (2015) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev-cellbio-100814-125300 · Cited by 35 · see citing works
“NOVEL TOOLS A typical differentiation experiment with ESCs consists of these basic components: ( a ) culture of ESCs , ( b ) induction of differentiation, ( c ) measurement of differentiation dynamics, and ( d ) data”
Nonmodular oscillator and switch based on RNA decay drive regeneration of multimodal gene expression
Nordick, B., Yu, P. Y., Liao, G., & Hong, T. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac217 · Cited by 33 · see citing works
“…exhibit multimodal expression patterns, a small subpopulation with a relatively homogenous expression profile recovers the parental population’s heterogeneity of individual gene products after several days (Chakraborty et al., 2020; Chang et al., 2008; Kalmar et al., 2009; Pina et al., 2012) (Fig.”
BackgroundResultAdult neural stem cells: plastic or restricted neuronal fates?
Sequerra, E. B., Costa, M. R., Menezes, J. R. L., & Hedin‐Pereira, C. (2013) · Development · doi:10.1242/dev.093096 · Cited by 32 · see citing works
“However, this generation of new neurons in the postnatal/adult cortex seems to be dependent on unknown signals: those not usually elicited by most types of lesions (Saha et al., 2012; Diaz et al., 2013).”
BackgroundRobust control of the adaptive immune system
Wong, H. S., & Germain, R. N. (2017) · Seminars in Immunology · doi:10.1016/j.smim.2017.12.009 · Cited by 31 · see citing works
Entropy, Ergodicity, and Stem Cell Multipotency
Ridden, S. J., Chang, H. H., Zygalakis, K. C., & MacArthur, B. D. (2015) · Physical Review Letters · doi:10.1103/physrevlett.115.208103 · Cited by 32 · see citing works
Nanog induced intermediate state in regulating stem cell differentiation and reprogramming
Yu, P., Nie, Q. H., Tang, C., & Zhang, L. (2018) · BMC Systems Biology · doi:10.1186/s12918-018-0552-3 · Cited by 32 · see citing works
Dissection of progenitor compartments resolves developmental trajectories in B-lymphopoiesis
Jensen, C. T., Åhsberg, J., Sommarin, M. N. E., Strid, T., Somasundaram, R., Okuyama, K., Ungerbäck, J., Kupari, J., Airaksinen, M. S., Lang, S., et al. (2018) · The Journal of Experimental Medicine · doi:10.1084/jem.20171384 · Cited by 30 · see citing works
“Preamplification cycling was preformed according to previously described protocols (Pina et al., 2012) with minor alterations; the first cycle, 50°C at 15 min, was extended to 60 min.”
MethodRole of YAP as a Mechanosensing Molecule in Stem Cells and Stem Cell-Derived Hematopoietic Cells
Damkham, N., Issaragrisil, S., & Lorthongpanich, C. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms232314634 · Cited by 28 · see citing works
Allison, T. F., Smith, A. J. H., Anastassiadis, K., Sloane‐Stanley, J., Biga, V., Stavish, D., Hackland, J. O. S., Sabri, S., Langerman, J., Jones, M., et al. (2018) · Stem Cell Reports · doi:10.1016/j.stemcr.2018.04.015 · Cited by 28 · see citing works
“However, in another study based on single-cell analyses (Pina et al., 2012), that conclusion was questioned since the apparent lineage-biased subsets could themselves be further subdivided into self-renewing and lineage-committed cells, emphasizing the need for clonal analyses to confirm the co-existenceof self-renewa…”
ResultTranscriptional mechanisms of cell fate decisions revealed by single cell expression profiling
Moignard, V., & Göttgens, B. (2014) · BioEssays · doi:10.1002/bies.201300102 · Cited by 27 · see citing works
“Significant cell-to-cell variation in the expression of a set of erythroid-associated genes was observed around commitment, which resolved to a more homogeneous expression state upon commitment, similar to expression patterns for the same gene set in differentiated erythroid cells [46].”
BackgroundMethodResultInfluentialWilkinson, A. C., Kawata-Matsuura, V. K. S., Schütte, J., Gao, X., Antoniou, S., Baumann, C., Woodhouse, S., Hannah, R., Tanaka, Y., Swiers, G., et al. (2014) · Development · doi:10.1242/dev.115709 · Cited by 27 · see citing works
“Such lowlevel expression might be analogous to the transcriptional noise of lineage regulators previously seen in adult haematopoietic progenitor cells (Pina et al., 2012).”
Arede, L., & Pina, C. (2020) · Experimental Hematology · doi:10.1016/j.exphem.2020.10.003 · Cited by 27 · see citing works
Buettner, F., Moignard, V., Göttgens, B., & Theis, F. J. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu134 · Cited by 21 · see citing works
Gene regulatory networks and epigenetic modifications in cell differentiation
Roy, S., & Kundu, T. K. (2014) · IUBMB Life · doi:10.1002/iub.1249 · Cited by 25 · see citing works
“Enver and coworkers have further separated these cell populations into two types: one possessing self-renewal ability and the other possessing gene expression programs characteristic of lineage commitment (21).”
BackgroundNair, G. P., Abranches, E., Guedes, A. M. V., Henrique, D., & Raj, A. (2015) · Scientific Reports · doi:10.1038/srep13339 · Cited by 22 · see citing works
Kinetic models of hematopoietic differentiation
Olariu, V., & Peterson, C. (2018) · WIREs Systems Biology and Medicine · doi:10.1002/wsbm.1424 · Cited by 24 · see citing works
Applications for single cell trajectory analysis in inner ear development and regeneration
Durruthy-Durruthy, R., & Heller, S. (2014) · Cell and Tissue Research · doi:10.1007/s00441-014-2079-2 · Cited by 21 · see citing works
“2013), and regeneration (Pina et al. 2012) in various biological systems.”
Haematopoietic stem cells: entropic landscapes of differentiation
Wiesner, K., Teles, J., Hartnor, M., & Peterson, C. (2018) · Interface Focus · doi:10.1098/rsfs.2018.0040 · Cited by 21 · see citing works
“For more information on culture conditions, cell sorting and gene filtering/normalization we refer to [4].”
BackgroundMethodInfluentialSingle-cell entropy for accurate estimation of differentiation potency from a cell’s transcriptomePreprint
Teschendorff, A. E. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/084202 · Cited by 23 · see citing works
“Although some of the 42 observed heterogeneity represents stochastic noise, a substantial component of intercellular 43 variation has been shown to be of functional importance [1, 5-8].”
Background
- Authors
- Pina, C., Fugazza, C., Tipping, A. J., Brown, J., Soneji, S., Teles, J., Peterson, C., & Enver, T.
- Affiliations
- University College London (GB)
- University of Oxford (GB)
- Lund University (SE)
- Corresponding author
- Enver, Tariq
- Venue
- Nature Cell Biology
- Published
- 2012-02-19
- Volume
- 14
- Issue
- 3
- Pages
- 287-294
- ISSN
- 1465-7392 (ISSN-L)
- 1476-4679
- OpenAlex
- W2073586815
- Cited by
- 162
- References
- 31
- Citations by year
- 2026: 2 · 2024: 5 · 2023: 3 · 2022: 7 · 2021: 8 · 2020: 17 · 2019: 5 · 2018: 18 · 2017: 10 · 2016: 13 · 2015: 19 · 2014: 20 · 2013: 26 · 2012: 9
- FWCI
- 15.76
- Type
- journal article
- Language
- en
- Open access
- green
- zenodo.org
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- Nature Cell Biology (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, other-oa)
- Funders
- Cancer Research UK (12796)
- Topics
- Health Sciences › Medicine › Hematology › Hematopoietic Stem Cell Transplantation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Health Sciences › Medicine › Hematology › Acute Myeloid Leukemia Research
- Keywords
- hematopoiesis, lineage commitment, self-renewal, transcriptional noise, lineage choice, single-cell transcriptomics, bone marrow-derived stem cells, progenitor cells, cell fate transitions
- MeSH terms
- Animals, Antigens, Ly, Bone Marrow Cells, Cell Differentiation, Cell Line, Transformed, Cells, Cultured, Hematopoiesis, Hematopoietic Stem Cells, Membrane Proteins, Mice, Inbred C57BL, Microscopy, Fluorescence, Time Factors, Immunoblotting, Cluster Analysis, Cytokines, Antigens, CD34, Cell Lineage, Reverse Transcriptase Polymerase Chain Reaction, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Multipotent Stem Cells, Erythroid Cells, Mice, Transcriptome
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