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Cell Fate Decision as High-Dimensional Critical State Transition

Cell fate choice and commitment of multipotent progenitor cells to a differentiated lineage requires broad changes of their gene expression profile. But how progenitor cells overcome the stability of their gene expression configuration (attractor) to exit the attractor in one direction remains elusi...

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Autores principales: Mojtahedi, Mitra, Skupin, Alexander, Zhou, Joseph, Castaño, Ivan G., Leong-Quong, Rebecca Y. Y., Chang, Hannah, Trachana, Kalliopi, Giuliani, Alessandro, Huang, Sui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5189937/
https://www.ncbi.nlm.nih.gov/pubmed/28027308
http://dx.doi.org/10.1371/journal.pbio.2000640
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author Mojtahedi, Mitra
Skupin, Alexander
Zhou, Joseph
Castaño, Ivan G.
Leong-Quong, Rebecca Y. Y.
Chang, Hannah
Trachana, Kalliopi
Giuliani, Alessandro
Huang, Sui
author_facet Mojtahedi, Mitra
Skupin, Alexander
Zhou, Joseph
Castaño, Ivan G.
Leong-Quong, Rebecca Y. Y.
Chang, Hannah
Trachana, Kalliopi
Giuliani, Alessandro
Huang, Sui
author_sort Mojtahedi, Mitra
collection PubMed
description Cell fate choice and commitment of multipotent progenitor cells to a differentiated lineage requires broad changes of their gene expression profile. But how progenitor cells overcome the stability of their gene expression configuration (attractor) to exit the attractor in one direction remains elusive. Here we show that commitment of blood progenitor cells to the erythroid or myeloid lineage is preceded by the destabilization of their high-dimensional attractor state, such that differentiating cells undergo a critical state transition. Single-cell resolution analysis of gene expression in populations of differentiating cells affords a new quantitative index for predicting critical transitions in a high-dimensional state space based on decrease of correlation between cells and concomitant increase of correlation between genes as cells approach a tipping point. The detection of “rebellious cells” that enter the fate opposite to the one intended corroborates the model of preceding destabilization of a progenitor attractor. Thus, early warning signals associated with critical transitions can be detected in statistical ensembles of high-dimensional systems, offering a formal theory-based approach for analyzing single-cell molecular profiles that goes beyond current computational pattern recognition, does not require knowledge of specific pathways, and could be used to predict impending major shifts in development and disease.
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spelling pubmed-51899372017-01-19 Cell Fate Decision as High-Dimensional Critical State Transition Mojtahedi, Mitra Skupin, Alexander Zhou, Joseph Castaño, Ivan G. Leong-Quong, Rebecca Y. Y. Chang, Hannah Trachana, Kalliopi Giuliani, Alessandro Huang, Sui PLoS Biol Research Article Cell fate choice and commitment of multipotent progenitor cells to a differentiated lineage requires broad changes of their gene expression profile. But how progenitor cells overcome the stability of their gene expression configuration (attractor) to exit the attractor in one direction remains elusive. Here we show that commitment of blood progenitor cells to the erythroid or myeloid lineage is preceded by the destabilization of their high-dimensional attractor state, such that differentiating cells undergo a critical state transition. Single-cell resolution analysis of gene expression in populations of differentiating cells affords a new quantitative index for predicting critical transitions in a high-dimensional state space based on decrease of correlation between cells and concomitant increase of correlation between genes as cells approach a tipping point. The detection of “rebellious cells” that enter the fate opposite to the one intended corroborates the model of preceding destabilization of a progenitor attractor. Thus, early warning signals associated with critical transitions can be detected in statistical ensembles of high-dimensional systems, offering a formal theory-based approach for analyzing single-cell molecular profiles that goes beyond current computational pattern recognition, does not require knowledge of specific pathways, and could be used to predict impending major shifts in development and disease. Public Library of Science 2016-12-27 /pmc/articles/PMC5189937/ /pubmed/28027308 http://dx.doi.org/10.1371/journal.pbio.2000640 Text en © 2016 Mojtahedi 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
Mojtahedi, Mitra
Skupin, Alexander
Zhou, Joseph
Castaño, Ivan G.
Leong-Quong, Rebecca Y. Y.
Chang, Hannah
Trachana, Kalliopi
Giuliani, Alessandro
Huang, Sui
Cell Fate Decision as High-Dimensional Critical State Transition
title Cell Fate Decision as High-Dimensional Critical State Transition
title_full Cell Fate Decision as High-Dimensional Critical State Transition
title_fullStr Cell Fate Decision as High-Dimensional Critical State Transition
title_full_unstemmed Cell Fate Decision as High-Dimensional Critical State Transition
title_short Cell Fate Decision as High-Dimensional Critical State Transition
title_sort cell fate decision as high-dimensional critical state transition
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5189937/
https://www.ncbi.nlm.nih.gov/pubmed/28027308
http://dx.doi.org/10.1371/journal.pbio.2000640
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