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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Bibliographic Details
Published in:PLoS biology 2016-12, Vol.14 (12), p.e2000640-e2000640
Main Authors: Mojtahedi, Mitra, Skupin, Alexander, Zhou, Joseph, Castaño, Ivan G, Leong-Quong, Rebecca Y Y, Chang, Hannah, Trachana, Kalliopi, Giuliani, Alessandro, Huang, Sui
Format: Article
Language:English
Subjects:
Animals
Biology
Biology and Life Sciences
Blood
Cell Differentiation
Cell Lineage
Colleges & universities
Computer and Information Sciences
Cytokines
Data collection
Editing
Efficiency
Flow cytometry
Funding
Gene expression
Gene Expression Profiling
Genetic aspects
Hematopoietic stem cells
Medicine and Health Sciences
Observations
Physical Sciences
Research and Analysis Methods
Roles
Single-Cell Analysis
Writing
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Summary: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.
ISSN:1545-7885
1544-9173
1545-7885
DOI:10.1371/journal.pbio.2000640