Effect of promoter architecture on the cell-to-cell variability in gene expression

TL;DR

This study systematically investigates how promoter architecture influences cell-to-cell variability in gene expression using a stochastic microscopic model, highlighting effects of operator strength, multiplicity, and binding modes.

Contribution

It introduces a comprehensive modeling approach to quantify how promoter features affect gene expression noise, aiding interpretation of single-cell experimental data.

Findings

Operator strength and multiplicity significantly impact variability.

Different transcription factor binding modes alter noise levels.

Model predictions can distinguish between kinetic gene regulation models.

Abstract

According to recent experimental evidence, the architecture of a promoter, defined as the number, strength and regulatory role of the operators that control the promoter, plays a major role in determining the level of cell-to-cell variability in gene expression. These quantitative experiments call for a corresponding modeling effort that addresses the question of how changes in promoter architecture affect noise in gene expression in a systematic rather than case-by-case fashion. In this article, we make such a systematic investigation, based on a simple microscopic model of gene regulation that incorporates stochastic effects. In particular, we show how operator strength and operator multiplicity affect this variability. We examine different modes of transcription factor binding to complex promoters (cooperative, independent, simultaneous) and how each of these affects the level of variability in transcription product from cell-to-cell. We propose that direct comparison between in vivo single-cell experiments and theoretical predictions for the moments of the probability distribution of mRNA number per cell can discriminate between different kinetic models of gene regulation.