Statistically derived geometrical landscapes capture principles of decision-making dynamics during cell fate transitions

Cell Syst. 2022 Jan 19;13(1):12-28.e3. doi: 10.1016/j.cels.2021.08.013. Epub 2021 Sep 17.

Abstract

Fate decisions in developing tissues involve cells transitioning between discrete cell states, each defined by distinct gene expression profiles. The Waddington landscape, in which the development of a cell is viewed as a ball rolling through a valley filled terrain, is an appealing way to describe differentiation. To construct and validate accurate landscapes, quantitative methods based on experimental data are necessary. We combined principled statistical methods with a framework based on catastrophe theory and approximate Bayesian computation to formulate a quantitative dynamical landscape that accurately predicts cell fate outcomes of pluripotent stem cells exposed to different combinations of signaling factors. Analysis of the landscape revealed two distinct ways in which cells make a binary choice between one of two fates. We suggest that these represent archetypal designs for developmental decisions. The approach is broadly applicable for the quantitative analysis of differentiation and for determining the logic of developmental decisions.

Keywords: Waddington landscape; catastrophe theory; cell fate decisions; dynamical systems; geometric models; pluripotent stem cell differentiation.

MeSH terms

  • Bayes Theorem*
  • Cell Differentiation