Dynamical Crossover in a Stochastic Model of Cell Fate Decision

TL;DR

This paper introduces a stochastic model for cell fate decisions that captures the transition between proliferation and differentiation, providing insights into tissue homeostasis and unifying existing theoretical models.

Contribution

It presents a self-replicating Langevin system model that explains how cell populations maintain density through local interactions and unifies different theoretical frameworks.

Findings

Distribution of descendant cells changes over time.

Model unifies critical birth-death process and voter model.

Provides a statistical mechanics framework for cell fate decisions.

Abstract

We study the asymptotic behaviors of stochastic cell fate decision between proliferation and differentiation. We propose a model of a self-replicating Langevin system, where cells choose their fate (i.e. proliferation or differentiation) depending on local cell density. Based on this model, we propose a scenario for multi-cellular organisms to maintain the density of cells (i.e., homeostasis) through finite-ranged cell-cell interactions. Furthermore, we numerically show that the distribution of the number of descendant cells changes over time, thus unifying the previously proposed two models regarding homeostasis: the critical birth death process and the voter model. Our results provide a general platform for the study of stochastic cell fate decision in terms of nonequilibrium statistical mechanics.