Gene expression noise is affected differentially by feedback in burst frequency and burst size

TL;DR

This paper compares how negative feedback in gene expression, through either burst frequency or burst size regulation, differentially affects noise suppression in stochastic gene expression models, revealing context-dependent advantages.

Contribution

It introduces a mathematical model to compare feedback effects on gene expression noise, highlighting the conditions where burst size feedback outperforms burst frequency feedback.

Findings

Both feedback types similarly buffer noise at low levels.

Burst size feedback is more effective in high noise regimes.

The study provides insights into cellular strategies for noise control.

Abstract

Inside individual cells, expression of genes is stochastic across organisms ranging from bacterial to human cells. A ubiquitous feature of stochastic expression is burst-like synthesis of gene products, which drives considerable intercellular variability in protein levels across an isogenic cell population. One common mechanism by which cells control such stochasticity is negative feedback regulation, where a protein inhibits its own synthesis. For a single gene that is expressed in bursts, negative feedback can affect the burst frequency or the burst size. In order to compare these feedback types, we study a piecewise deterministic model for gene expression of a self-regulating gene. Mathematically tractable steady-state protein distributions are derived and used to compare the noise suppression abilities of the two feedbacks. Results show that in the low noise regime, both feedbacks are similar in term of their noise buffering abilities. Intriguingly, feedback in burst size outperforms the feedback in burst frequency in the high noise regime. Finally, we discuss various regulatory strategies by which cells implement feedback to control burst sizes of expressed proteins at the level of single cells.