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A multiscale model of epigenetic heterogeneity-driven cell fate decision-making

The inherent capacity of somatic cells to switch their phenotypic status in response to damage stimuli in vivo might have a pivotal role in ageing and cancer. However, how the entry-exit mechanisms of phenotype reprogramming are established remains poorly understood. In an attempt to elucidate such...

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Autores principales: Folguera-Blasco, Núria, Pérez-Carrasco, Rubén, Cuyàs, Elisabet, Menendez, Javier A., Alarcón, Tomás
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510448/
https://www.ncbi.nlm.nih.gov/pubmed/31039148
http://dx.doi.org/10.1371/journal.pcbi.1006592
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author Folguera-Blasco, Núria
Pérez-Carrasco, Rubén
Cuyàs, Elisabet
Menendez, Javier A.
Alarcón, Tomás
author_facet Folguera-Blasco, Núria
Pérez-Carrasco, Rubén
Cuyàs, Elisabet
Menendez, Javier A.
Alarcón, Tomás
author_sort Folguera-Blasco, Núria
collection PubMed
description The inherent capacity of somatic cells to switch their phenotypic status in response to damage stimuli in vivo might have a pivotal role in ageing and cancer. However, how the entry-exit mechanisms of phenotype reprogramming are established remains poorly understood. In an attempt to elucidate such mechanisms, we herein introduce a stochastic model of combined epigenetic regulation (ER)-gene regulatory network (GRN) to study the plastic phenotypic behaviours driven by ER heterogeneity. To deal with such complex system, we additionally formulate a multiscale asymptotic method for stochastic model reduction, from which we derive an efficient hybrid simulation scheme. Our analysis of the coupled system reveals a regime of tristability in which pluripotent stem-like and differentiated steady-states coexist with a third indecisive state, with ER driving transitions between these states. Crucially, ER heterogeneity of differentiation genes is for the most part responsible for conferring abnormal robustness to pluripotent stem-like states. We formulate epigenetic heterogeneity-based strategies capable of unlocking and facilitating the transit from differentiation-refractory (stem-like) to differentiation-primed epistates. The application of the hybrid numerical method validates the likelihood of such switching involving solely kinetic changes in epigenetic factors. Our results suggest that epigenetic heterogeneity regulates the mechanisms and kinetics of phenotypic robustness of cell fate reprogramming. The occurrence of tunable switches capable of modifying the nature of cell fate reprogramming might pave the way for new therapeutic strategies to regulate reparative reprogramming in ageing and cancer.
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spelling pubmed-65104482019-05-23 A multiscale model of epigenetic heterogeneity-driven cell fate decision-making Folguera-Blasco, Núria Pérez-Carrasco, Rubén Cuyàs, Elisabet Menendez, Javier A. Alarcón, Tomás PLoS Comput Biol Research Article The inherent capacity of somatic cells to switch their phenotypic status in response to damage stimuli in vivo might have a pivotal role in ageing and cancer. However, how the entry-exit mechanisms of phenotype reprogramming are established remains poorly understood. In an attempt to elucidate such mechanisms, we herein introduce a stochastic model of combined epigenetic regulation (ER)-gene regulatory network (GRN) to study the plastic phenotypic behaviours driven by ER heterogeneity. To deal with such complex system, we additionally formulate a multiscale asymptotic method for stochastic model reduction, from which we derive an efficient hybrid simulation scheme. Our analysis of the coupled system reveals a regime of tristability in which pluripotent stem-like and differentiated steady-states coexist with a third indecisive state, with ER driving transitions between these states. Crucially, ER heterogeneity of differentiation genes is for the most part responsible for conferring abnormal robustness to pluripotent stem-like states. We formulate epigenetic heterogeneity-based strategies capable of unlocking and facilitating the transit from differentiation-refractory (stem-like) to differentiation-primed epistates. The application of the hybrid numerical method validates the likelihood of such switching involving solely kinetic changes in epigenetic factors. Our results suggest that epigenetic heterogeneity regulates the mechanisms and kinetics of phenotypic robustness of cell fate reprogramming. The occurrence of tunable switches capable of modifying the nature of cell fate reprogramming might pave the way for new therapeutic strategies to regulate reparative reprogramming in ageing and cancer. Public Library of Science 2019-04-30 /pmc/articles/PMC6510448/ /pubmed/31039148 http://dx.doi.org/10.1371/journal.pcbi.1006592 Text en © 2019 Folguera-Blasco et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Folguera-Blasco, Núria
Pérez-Carrasco, Rubén
Cuyàs, Elisabet
Menendez, Javier A.
Alarcón, Tomás
A multiscale model of epigenetic heterogeneity-driven cell fate decision-making
title A multiscale model of epigenetic heterogeneity-driven cell fate decision-making
title_full A multiscale model of epigenetic heterogeneity-driven cell fate decision-making
title_fullStr A multiscale model of epigenetic heterogeneity-driven cell fate decision-making
title_full_unstemmed A multiscale model of epigenetic heterogeneity-driven cell fate decision-making
title_short A multiscale model of epigenetic heterogeneity-driven cell fate decision-making
title_sort multiscale model of epigenetic heterogeneity-driven cell fate decision-making
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510448/
https://www.ncbi.nlm.nih.gov/pubmed/31039148
http://dx.doi.org/10.1371/journal.pcbi.1006592
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