TY - JOUR
T1 - Correlating the cellular microenvironment with cell fate decisions
T2 - Asymmetric behavior under symmetric control
AU - Miao, Yuchen
AU - Du, Lin
AU - Deng, Zichen
AU - Grebogi, Celso
N1 - Publisher Copyright:
Copyright © 2026. Published by Elsevier B.V.
PY - 2026/11
Y1 - 2026/11
N2 - Directed cell differentiation is a stochastic process governed by gene regulatory motifs and modulated by the microenvironment. However, a rigorous physical framework to quantify how microenvironmental fluctuations interact with intrinsic transcriptional noise remains elusive. In this work, we investigate the regulatory role of the microenvironment in phenotypic transitions by bridging microscopic biological processes with macroscopic landscape modeling. We first establish a self-activating promoter switching (PS) model subject to microenvironmental influences, coupling intrinsic Poisson noise with extrinsic colored noise. By employing large deviation theory and asymptotic analysis, we characterize the limiting behavior of the quasipotential to quantify the potential landscape. Our results reveal a non-monotonic regulation of phenotypic switching by the microenvironment, which can either inhibit or enhance transitions, with a distinct optimal enhancement point identified. This analysis is further extended to an asymmetric toggle switch (TS) model to depict lineage-directed differentiation. We find that early stages of differentiation are particularly sensitive to microenvironmental factors, aligning with in vivo observations. By integrating these frameworks via model reduction, we uncover a key regulatory principle: a symmetrical microenvironment can effectively modulate differentiation trends induced by asymmetrical internal gene expression. This study provides a quantitative physical perspective on how intrinsic and extrinsic fluctuations synergistically shape cellular decision-making.
AB - Directed cell differentiation is a stochastic process governed by gene regulatory motifs and modulated by the microenvironment. However, a rigorous physical framework to quantify how microenvironmental fluctuations interact with intrinsic transcriptional noise remains elusive. In this work, we investigate the regulatory role of the microenvironment in phenotypic transitions by bridging microscopic biological processes with macroscopic landscape modeling. We first establish a self-activating promoter switching (PS) model subject to microenvironmental influences, coupling intrinsic Poisson noise with extrinsic colored noise. By employing large deviation theory and asymptotic analysis, we characterize the limiting behavior of the quasipotential to quantify the potential landscape. Our results reveal a non-monotonic regulation of phenotypic switching by the microenvironment, which can either inhibit or enhance transitions, with a distinct optimal enhancement point identified. This analysis is further extended to an asymmetric toggle switch (TS) model to depict lineage-directed differentiation. We find that early stages of differentiation are particularly sensitive to microenvironmental factors, aligning with in vivo observations. By integrating these frameworks via model reduction, we uncover a key regulatory principle: a symmetrical microenvironment can effectively modulate differentiation trends induced by asymmetrical internal gene expression. This study provides a quantitative physical perspective on how intrinsic and extrinsic fluctuations synergistically shape cellular decision-making.
KW - Heterogeneous noise coupling
KW - Large deviation theory
KW - Microenvironmental regulation
KW - Phenotypic switching
KW - Quasipotential landscape
UR - https://www.scopus.com/pages/publications/105042530069
U2 - 10.1016/j.cnsns.2026.110358
DO - 10.1016/j.cnsns.2026.110358
M3 - 文章
AN - SCOPUS:105042530069
SN - 1007-5704
VL - 162
JO - Communications in Nonlinear Science and Numerical Simulation
JF - Communications in Nonlinear Science and Numerical Simulation
M1 - 110358
ER -