Determining the stability of genetic switches: explicitly accounting for mRNA noise

TL;DR

This paper investigates the stability of genetic switches by explicitly modeling mRNA noise, using advanced mathematical techniques to provide accurate predictions of switch dynamics and stability.

Contribution

It introduces a novel analytical approach that explicitly accounts for mRNA fluctuations in genetic switch models, improving understanding of switch stability.

Findings

Analytical results match Monte Carlo simulations.

mRNA noise significantly impacts switch dynamics.

Parameter variations affect switch stability.

Abstract

Cells use genetic switches to shift between alternate gene expression states, e.g., to adapt to new environments or to follow a developmental pathway. Here, we study the dynamics of switching in a generic-feedback on/off switch. Unlike protein-only models, we explicitly account for stochastic fluctuations of mRNA, which have a dramatic impact on switch dynamics. Employing the WKB theory to treat the underlying chemical master equations, we obtain accurate results for the quasi-stationary distributions of mRNA and protein copy numbers and for the mean switching time, starting from either state. Our analytical results agree well with Monte Carlo simulations. Importantly, one can use the approach to study the effect of varying biological parameters on switch stability.