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

Meritxell Sáez,Eric D Siggia,David A Rand,James Briscoe,Elena Camacho-Aguilar,Robert Blassberg

doi:10.1016/j.cels.2021.08.013

Abstract

SummaryFate 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.

Highlights

Cell fate decisions in developing tissues involve gene regulatory networks comprising multiple genes, many molecular components, and elaborate signaling dynamics
Quantitative methods based on experimental data that represent and permit analysis of developmental processes at the scale of cell fate decisions would provide insight into the underlying principles and allow quantitative and testable predictions
embryonic stem cells (ESCs) removed from pluripotency conditions and grown in basal media containing FGF2 (FGF) and an inhibitor of endogenous WNT secretion (LGK974) adopt a post-implantation epiblast-like (EPI) identity by day (D)2 of culture (Figure 1Ba) (Blassberg et al, 2020) and, subsequently, following removal of exogenous FGF, adopt an OTX2+/ SOX1+ molecular identity characteristic of anterior neural progenitors (AN) (Figure 1Bb)

Summary

Introduction

Cell fate decisions in developing tissues involve gene regulatory networks comprising multiple genes, many molecular components, and elaborate signaling dynamics. A popular and intuitive metaphor for the process of developmental decision making is the Waddington landscape, in which the differentiation trajectory of a cell is conceived as a ball rolling down a landscape of branching valleys, representing specific cell fates (Waddington, 1957) This can be mathematically formalized, with only minor changes, using dynamical systems theory (Camacho-Aguilar et al, 2021; Corson and Siggia, 2012, 2017, Corson et al, 2017; Huang, 2012; Mojtahedi et al, 2016). The transition to a new fate is signified by a cell entering a new basin of attraction, caused either by a signal-induced bifurcation or by a stochastic fluctuation resulting in a cell jumping from one attractor’s pull to another In both cases, the route from the old to the new cell state is defined by a saddle point in the landscape. This approach enables a rigorous link between the dynamical systems underlying gene regulatory networks and Waddington’s landscapes

Methods

Results

Discussion

Conclusion