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Stem cell differentiation is a stochastic process with memory

View ORCID ProfilePatrick S. Stumpf, View ORCID ProfileRosanna C. G. Smith, Michael Lenz, Andreas Schuppert, Franz-Josef Müller, Ann Babtie, Thalia E. Chan, Michael P. H. Stumpf, Colin P. Please, Sam D. Howison, Fumio Arai, Ben D. MacArthur
doi: https://doi.org/10.1101/101048
Patrick S. Stumpf
1Centre for Human Development, Stem Cells and Regeneration, Faculty of Medicine, University of Southampton, SO17 1BJ, United Kingdom
2Institute for Life Sciences, University of Southampton, SO17 1BJ, United Kingdom
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  • ORCID record for Patrick S. Stumpf
Rosanna C. G. Smith
1Centre for Human Development, Stem Cells and Regeneration, Faculty of Medicine, University of Southampton, SO17 1BJ, United Kingdom
2Institute for Life Sciences, University of Southampton, SO17 1BJ, United Kingdom
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Michael Lenz
3Joint Research Center for Computational Biomedicine, RWTH Aachen University, 52056, Aachen, Germany
4Aachen Institute for Advanced Study in Computational Engineering Science, RWTH Aachen University, 52062, Aachen, Germany
5Maastricht Centre for Systems Biology, Maastricht University, 6229 ER, Maastricht, Netherlands
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Andreas Schuppert
3Joint Research Center for Computational Biomedicine, RWTH Aachen University, 52056, Aachen, Germany
4Aachen Institute for Advanced Study in Computational Engineering Science, RWTH Aachen University, 52062, Aachen, Germany
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Franz-Josef Müller
6Zentrum für Integrative Psychiatrie, 24105, Kiel, Germany
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Ann Babtie
7Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College, London SW7 2AZ, United Kingdom
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Thalia E. Chan
7Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College, London SW7 2AZ, United Kingdom
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Michael P. H. Stumpf
7Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College, London SW7 2AZ, United Kingdom
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Colin P. Please
8Mathematical Institute, University of Oxford, Oxford, OX2 6GG, United Kingdom
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Sam D. Howison
8Mathematical Institute, University of Oxford, Oxford, OX2 6GG, United Kingdom
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Fumio Arai
9Department of Stem Cell Biology and Medicine, Graduate School of Medical Sciences, Kyushu University, 812-8582, Fukuoka, Japan
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Ben D. MacArthur
1Centre for Human Development, Stem Cells and Regeneration, Faculty of Medicine, University of Southampton, SO17 1BJ, United Kingdom
2Institute for Life Sciences, University of Southampton, SO17 1BJ, United Kingdom
10Mathematical Sciences, University of Southampton, SO17 1BJ, United Kingdom
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  • For correspondence: bdm@soton.ac.uk
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Abstract

Pluripotent stem cells are able to self-renew indefinitely in culture and differentiate into all somatic cell types in vivo. While much is known about the molecular basis of pluripotency, the molecular mechanisms of lineage commitment are complex and only partially understood. Here, using a combination of single cell profiling and mathematical modeling, we examine the differentiation dynamics of individual mouse embryonic stem cells (ESCs) as they progress from the ground state of pluripotency along the neuronal lineage. In accordance with previous reports we find that cells do not transit directly from the pluripotent state to the neuronal state, but rather first stochastically permeate an intermediate primed pluripotent state, similar to that found in the maturing epiblast in development. However, analysis of rate at which individual cells enter and exit this intermediate metastable state using a hidden Markov model reveals that the observed ESC and epiblast-like ‘macrostates’ conceal a chain of unobserved cellular ‘microstates’, which individual cells transit through stochastically in sequence. These hidden microstates ensure that individual cells spend well-defined periods of time in each functional macrostate and encode a simple form of epigenetic ‘memory’ that allows individual cells to record their position on the differentiation trajectory. To examine the generality of this model we also consider the differentiation of mouse hematopoietic stem cells along the myeloid lineage and observe remarkably similar dynamics, suggesting a general underlying process. Based upon these results we suggest a statistical mechanics view of cellular identities that distinguishes between functionally-distinct macrostates and the many functionally-similar molecular microstates associated with each macrostate. Taken together these results indicate that differentiation is a discrete stochastic process amenable to analysis using the tools of statistical mechanics.

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Posted January 17, 2017.
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Stem cell differentiation is a stochastic process with memory
Patrick S. Stumpf, Rosanna C. G. Smith, Michael Lenz, Andreas Schuppert, Franz-Josef Müller, Ann Babtie, Thalia E. Chan, Michael P. H. Stumpf, Colin P. Please, Sam D. Howison, Fumio Arai, Ben D. MacArthur
bioRxiv 101048; doi: https://doi.org/10.1101/101048
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Stem cell differentiation is a stochastic process with memory
Patrick S. Stumpf, Rosanna C. G. Smith, Michael Lenz, Andreas Schuppert, Franz-Josef Müller, Ann Babtie, Thalia E. Chan, Michael P. H. Stumpf, Colin P. Please, Sam D. Howison, Fumio Arai, Ben D. MacArthur
bioRxiv 101048; doi: https://doi.org/10.1101/101048

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