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Pàgina inicial > Articles > Articles publicats > A multiscale model of epigenetic heterogeneity-driven cell fate decision-making |
Data: | 2019 |
Resum: | 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 entryexit 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. |
Ajuts: | 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 MDM2014-0445 Ministerio de Economía y Competitividad SAF2016-80639-P Agència de Gestió d'Ajuts Universitaris i de Recerca 2014/SGR-229 Instituto de Salud Carlos III CD15/00033 |
Nota: | Altres ajuts: Obra Social La Caixa Foundation on Collaborative Mathematics awarded to the Centre de Recerca Matemàtica |
Nota: | Altres ajuts: CERCA Programme/Generalitat de Catalunya |
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 |
Matèria: | Aging ; Cellular reprogramming ; Computational biology ; Epigenesis ; Genetic ; Gene regulatory networks ; Humans ; Models biological ; Neoplasms ; Phenotype |
Publicat a: | PLoS computational biology, Vol. 15, Issue 4 (April 2019) , art. e1006592, ISSN 1553-7358 |
27 p, 3.0 MB |