Integrating extrinsic and intrinsic cues into a minimal model of lineage commitment for hematopoietic progenitors

PLoS Comput Biol. 2009 Sep;5(9):e1000518. doi: 10.1371/journal.pcbi.1000518. Epub 2009 Sep 25.


Autoregulation of transcription factors and cross-antagonism between lineage-specific transcription factors are a recurrent theme in cell differentiation. An equally prevalent event that is frequently overlooked in lineage commitment models is the upregulation of lineage-specific receptors, often through lineage-specific transcription factors. Here, we use a minimal model that combines cell-extrinsic and cell-intrinsic elements of regulation in order to understand how both instructive and stochastic events can inform cell commitment decisions in hematopoiesis. Our results suggest that cytokine-mediated positive receptor feedback can induce a "switch-like" response to external stimuli during multilineage differentiation by providing robustness to both bipotent and committed states while protecting progenitors from noise-induced differentiation or decommitment. Our model provides support to both the instructive and stochastic theories of commitment: cell fates are ultimately driven by lineage-specific transcription factors, but cytokine signaling can strongly bias lineage commitment by regulating these inherently noisy cell-fate decisions with complex, pertinent behaviors such as ligand-mediated ultrasensitivity and robust multistability. The simulations further suggest that the kinetics of differentiation to a mature cell state can depend on the starting progenitor state as well as on the route of commitment that is chosen. Lastly, our model shows good agreement with lineage-specific receptor expression kinetics from microarray experiments and provides a computational framework that can integrate both classical and alternative commitment paths in hematopoiesis that have been observed experimentally.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Cell Differentiation / physiology*
  • Cell Lineage
  • Computational Biology / methods*
  • Computer Simulation
  • Feedback, Physiological
  • Hematopoiesis / physiology*
  • Hematopoietic Stem Cells / physiology*
  • Models, Biological*
  • Oligonucleotide Array Sequence Analysis
  • Receptors, Cell Surface / genetics
  • Receptors, Cell Surface / metabolism
  • Signal Transduction
  • Stochastic Processes
  • Transcription Factors / genetics
  • Transcription Factors / metabolism


  • Receptors, Cell Surface
  • Transcription Factors