Cell population model to track stochastic cellular decision-making during differentiation

Abstract

Human pluripotent stem cells are defined by their potential to give rise to all of the lineages of an embryo proper. Guiding the differentiation of embryonic stem cells or induced pluripotent stem cells can be achieved by exposing them to a succession of signaling conditions meant to mimic developmental milieus. However, achieving a quantitative understanding of the relationship between proliferation, cell death, and commitment has been difficult due to the inherent heterogeneity of pluripotent stem cells and their differentiation. Here, we describe a computational modeling approach to track the dynamics of germ layer commitment of human embryonic stem cells. We demonstrate that simulations using this model yield specific hypotheses regarding proliferation, cell death, and commitment and that these predictions are consistent with experimental measurements.