Epigenetic regulation of cell fate reprogramming in aging and disease : A predictive computational model
Folguera Blasco, Núria (Universitat Autònoma de Barcelona. Departament de Matemàtiques)
Cuyàs, Elisabet (Institut de Recerca Biomèdica de Girona)
Menéndez, Javier A. (Institut Català d'Oncologia)
Alarcón Cor, Tomás (Escola Superior de Matemàtiques de Barcelona)

Data:	2018
Resum:	Understanding the control of epigenetic regulation is key to explain and modify the aging process. Because histone-modifying enzymes are sensitive to shifts in availability of cofactors (e. g. metabolites), cellular epigenetic states may be tied to changing conditions associated with cofactor variability. The aim of this study is to analyse the relationships between cofactor fluctuations, epigenetic landscapes, and cell state transitions. Using Approximate Bayesian Computation, we generate an ensemble of epigenetic regulation (ER) systems whose heterogeneity reflects variability in cofactor pools used by histone modifiers. The heterogeneity of epigenetic metabolites, which operates as regulator of the kinetic parameters promoting/preventing histone modifications, stochastically drives phenotypic variability. The ensemble of ER configurations reveals the occurrence of distinct epi-states within the ensemble. Whereas resilient states maintain large epigenetic barriers refractory to reprogramming cellular identity, plastic states lower these barriers, and increase the sensitivity to reprogramming. Moreover, fine-tuning of cofactor levels redirects plastic epigenetic states to re-enter epigenetic resilience, and vice versa. Our ensemble model agrees with a model of metabolism-responsive loss of epigenetic resilience as a cellular aging mechanism. Our findings support the notion that cellular aging, and its reversal, might result from stochastic translation of metabolic inputs into resilient/plastic cell states via ER systems.
Ajuts:	Ministerio de Economía y Competitividad CD15/00033 Ministerio de Economía y Competitividad MTM2015-71509-C2-1-R Agència de Gestió d'Ajuts Universitaris i de Recerca 2014/SGR-1307 Ministerio de Economía y Competitividad SAF2016-80639-P Agència de Gestió d'Ajuts Universitaris i de Recerca 2014/SGR-229
Nota:	Altres ajuts: Barcelona Graduate School of Mahematics, MDM-2014-0445
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Publicat a:	PLoS computational biology, Vol. 14, Issue 3 (March 2018) , art. e1006052, ISSN 1553-7358

DOI: 10.1371/journal.pcbi.1006052
PMID: 29543808

24 p, 13.5 MB

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