Transition Path, Quasi-potential Energy Landscape and Stability of Genetic Switches

TL;DR

This paper develops a framework using quasi-potential energy landscapes to analyze the stability and transition paths in genetic switches influenced by noise, providing insights into cellular state changes.

Contribution

It introduces a novel approach to quantify metastability in gene expression using energy landscapes derived from a two-state genetic switching model.

Findings

Successfully characterizes transition paths and energy landscapes.

Analyzes stability regimes in gene expression models.

Provides a quantitative tool for biological metastability.

Abstract

One of the fundamental cellular processes governed by genetic regulatory networks in cells is the transition among different states under the intrinsic and extrinsic noise. Based on a two-state genetic switching model with positive feedback, we develop a framework to understand the metastability in gene expressions. This framework is comprised of identifying the transition path, reconstructing the global quasi-potential energy landscape, analyzing the uphill and downhill transition paths, etc. It is successfully utilized to investigate the stability of genetic switching models and fluctuation properties in different regimes of gene expression with positive feedback. The quasi-potential energy landscape, which is the rationalized version of Waddington potential, provides a quantitative tool to understand the metastability in more general biological processes with intrinsic noise.