A stochastic and dynamical view of pluripotency in mouse embryonic stem cells

Lin, Yen Ting; Hufton, Peter G.; Lee, Esther J.; Potoyan, Davit A.

doi:10.1371/journal.pcbi.1006000

Title: A stochastic and dynamical view of pluripotency in mouse embryonic stem cells

Journal Article · Fri Feb 16 00:00:00 EST 2018 · PLoS Computational Biology (Online)

DOI:https://doi.org/10.1371/journal.pcbi.1006000· OSTI ID:1627254

^[1];

^[2]; Lee, Esther J. ^[3];

^[4]

Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Theoretical Division and Center for Nonlinear Studies; Univ. of Manchester (United Kingdom). School of Physics and Astronomy
Univ. of Manchester (United Kingdom). School of Physics and Astronomy
Rice Univ., Houston, TX (United States). Dept. of Bioengineering
Iowa State Univ., Ames, IA (United States). Dept. of Chemistry

Pluripotent embryonic stem cells are of paramount importance for biomedical sciences because of their innate ability for self-renewal and differentiation into all major cell lines. The fateful decision to exit or remain in the pluripotent state is regulated by complex genetic regulatory networks. The rapid growth of single-cell sequencing data has greatly stimulated applications of statistical and machine learning methods for inferring topologies of pluripotency regulating genetic networks. The inferred network topologies, however, often only encode Boolean information while remaining silent about the roles of dynamics and molecular stochasticity inherent in gene expression. Herein we develop a framework for systematically extending Boolean-level network topologies into higher resolution models of networks which explicitly account for the promoter architectures and gene state switching dynamics. We show the framework to be useful for disentangling the various contributions that gene switching, external signaling, and network topology make to the global heterogeneity and dynamics of transcription factor populations. We find the pluripotent state of the network to be a steady state which is robust to global variations of gene switching rates which we argue are a good proxy for epigenetic states of individual promoters. The temporal dynamics of exiting the pluripotent state, on the other hand, is significantly influenced by the rates of genetic switching which makes cells more responsive to changes in extracellular signals.

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division

Grant/Contract Number:: AC52-06NA25396

OSTI ID:: 1627254

Journal Information:: PLoS Computational Biology (Online), Vol. 14, Issue 2; ISSN 1553-7358

Publisher:: Public Library of ScienceCopyright Statement

Country of Publication:: United States

Language:: English

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