Reference : Modeling heterogeneity in the pluripotent state: A promising strategy for improving t...
Scientific journals : Article
Life sciences : Biochemistry, biophysics & molecular biology
Systems Biomedicine
Modeling heterogeneity in the pluripotent state: A promising strategy for improving the efficiency and fidelity of stem cell differentiation
Espinosa Angarica, Vladimir mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
del Sol Mesa, Antonio mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Wiley Periodicals
Yes (verified by ORBilu)
New York
[en] pluripotent state ; gene expression heterogeneity ; gene regulatory networks ; signalling pathway ; epigenetics ; stem cells
[en] Pluripotency can be considered a functional characteristic of pluripotent stem cells (PSCs) populations and their niches, rather than a property of individual cells. In this view, individual cells within the population independently adopt a variety of different expression states, maintained by different signaling, transcriptional, and epigenetics regulatory networks. In this review, we propose that generation of integrative network models from single cell data will be essential for getting a better understanding of the regulation of self-renewal and differentiation. In particular, we suggest that the identification of network stability determinants in these integrative models will provide important insights into the mechanisms mediating the transduction of signals from the niche, and how these signals can trigger differentiation. In this regard, the differential use of these stability determinants in subpopulation-specific regulatory networks would mediate differentiation into different cell fates. We suggest that this approach could offer a promising avenue for the development of novel strategies for increasing the efficiency and fidelity of differentiation, which could have a strong impact on regenerative medicine
Luxembourg Centre for Systems Biomedicine (LCSB): Computational Biology (Del Sol Group)
Fonds National de la Recherche - FnR
Researchers ; Professionals ; Students ; General public
FnR ; FNR5810227 > Antonio del Sol Mesa > PlaCellRep > Platform to design new strategies for cellular reprogramming in regenerative medicine > 01/02/2014 > 31/01/2017 > 2013

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