Transient noise amplification and gene expression synchronization in a bistable mammalian cell-fate switch

Cell Rep. 2012 Mar 29;1(3):215-24. doi: 10.1016/j.celrep.2012.01.007. Epub 2012 Mar 15.

Abstract

Progenitor cells within a clonal population show variable proclivity toward lineage commitment and differentiation. This cell-to-cell variability has been attributed to transcriptome-wide gene expression noise generated by fluctuations in the amount of cellular machinery and stochasticity in the biochemical reactions involved in protein synthesis. It therefore remains unclear how a signaling network, in the presence of such noise, can execute unequivocal cell-fate decisions from external cues. Here, we use mathematical modeling and model-guided experiments to reveal functional interplay between instructive signaling and noise in erythropoiesis. We present evidence that positive transcriptional feedback loops in a lineage-specific receptor signaling pathway can generate ligand-induced memory to engender robust, switch-like responses. These same feedback loops can also transiently amplify gene expression noise in the signaling network, suggesting that external cues can actually bias seemingly stochastic decisions during cell-fate specification. Gene expression levels among key effectors in the signaling pathway are uncorrelated in the initial population of progenitor cells but become synchronized after addition of ligand, which activates the transcriptional feedback loops. Finally, we show that this transient noise amplification and gene expression synchronization induced by ligand can directly influence cell survival and differentiation kinetics within the population.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cell Differentiation / genetics
  • Cell Line
  • Cell Lineage / genetics*
  • Cell Survival / genetics
  • Computer Simulation
  • Feedback, Physiological
  • Gene Expression Regulation*
  • Genes, Switch / genetics*
  • Humans
  • Kinetics
  • Ligands
  • Mammals / genetics*
  • Models, Biological
  • Receptors, Cell Surface / metabolism
  • Signal Transduction / genetics*
  • Transcription Factors / metabolism

Substances

  • Ligands
  • Receptors, Cell Surface
  • Transcription Factors