Cargando…
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...
Autores principales: | , , , , , , , , |
---|---|
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 |
_version_ | 1782487317666070528 |
---|---|
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. |
format | Online Article Text |
id | pubmed-5189937 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT mojtahedimitra cellfatedecisionashighdimensionalcriticalstatetransition AT skupinalexander cellfatedecisionashighdimensionalcriticalstatetransition AT zhoujoseph cellfatedecisionashighdimensionalcriticalstatetransition AT castanoivang cellfatedecisionashighdimensionalcriticalstatetransition AT leongquongrebeccayy cellfatedecisionashighdimensionalcriticalstatetransition AT changhannah cellfatedecisionashighdimensionalcriticalstatetransition AT trachanakalliopi cellfatedecisionashighdimensionalcriticalstatetransition AT giulianialessandro cellfatedecisionashighdimensionalcriticalstatetransition AT huangsui cellfatedecisionashighdimensionalcriticalstatetransition |