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Related Concept Videos

Cellular Differentiation00:57

Cellular Differentiation

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How does a complex organism such as a human develop from a single cell? It all starts from a single fertilized egg which gives rise to a vast array of cell types, such as nerve cells, muscle cells, and epithelial cells that characterize the adult? Throughout development and adulthood, cellular differentiation leads cells to assume their final morphology and physiology. Differentiation is the process by which unspecialized cells become specialized to carry out distinct functions.
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Several external and internal factors influence the initiation and inhibition of cell division. For instance, the death of nearby cells or the release of human growth hormone (hGH) promotes cell division. In contrast, lack of hGH or crowding of cells can inhibit cell division.
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The ability of induced pluripotent stem cells or iPSCs to differentiate into most body cell types has stimulated repair and regenerative medicine research over the past few decades. iPSC-derived blood cells, hepatocytes, beta islet cells, cardiomyocytes, neurons, and other cell types can repair injuries or regenerate damaged tissue in diseases such as diabetes and neurodegenerative disorders.
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Common myeloid progenitors (CMPs) are oligopotent cells that can differentiate into granulocytes and macrophages. Granulocytes and macrophages are essential for protecting the body against bacterial, viral, or fungal infections. They migrate from the bone marrow into the circulating blood to reach specific tissue sites where they differentiate and help in immune surveillance. However, they survive only for a few days and must be continuously made available to the organism to maintain a robust...
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Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment

Angélique Richard1, Loïs Boullu2,3,4, Ulysse Herbach1,2,3

  • 1Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, Laboratory of Biology and Modelling of the Cell, 46 allée d'Italie Site Jacques Monod, F-69007, Lyon, France.

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Cell differentiation involves dynamic gene expression changes, with single-cell analysis revealing peak variability at fate commitment. This study uses Shannon entropy to track heterogeneity during erythroid progenitor differentiation, identifying key drivers and network dynamics.

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Area of Science:

  • Cellular and Molecular Biology
  • Developmental Biology
  • Systems Biology

Background:

  • Stochastic dynamics in cell differentiation suggest gene expression variability peaks at fate commitment.
  • Population-based studies mask crucial cell-to-cell variations in gene expression during differentiation.
  • Understanding single-cell dynamics is key to deciphering complex biological processes like cell fate decisions.

Purpose of the Study:

  • To test the hypothesis that gene expression variability peaks at cell fate commitment during differentiation.
  • To analyze single-cell gene expression dynamics in primary chicken erythroid progenitors.
  • To identify potential molecular drivers and network behaviors governing cell differentiation.

Main Methods:

  • Single-cell gene expression analysis of chicken erythroid progenitors at six sequential time-points.
  • Quantification of cell-to-cell variability using Shannon entropy.
  • Analysis of gene correlation networks and identification of dynamical network biomarkers (DNB).

Main Results:

  • Single-cell analysis revealed high cell-to-cell variability masked by population averaging.
  • Shannon entropy peaked between 8 and 24 hours, preceding irreversible differentiation commitment (24-48h) and cell size variability increase (48h).
  • A subgroup of genes related to sterol synthesis was identified as potential initial drivers of differentiation.

Conclusions:

  • Cell differentiation is a dynamic process driven by molecular network behavior, not a simple, identical program for all cells.
  • Single-cell analysis provides new insights and observables, like entropy, crucial for understanding differentiation heterogeneity.
  • Dynamical network biomarker theory and single-cell entropy measurements offer powerful tools for studying cell fate transitions.