Noise and information transmission in promoters with multiple internal states

TL;DR

This paper investigates how multi-state promoter architectures influence gene expression noise and information transmission, extending the two-state model to more complex promoter states and analyzing their functional implications.

Contribution

It introduces a generalized framework for modeling multi-state promoters, computes their noise characteristics, and evaluates their information transmission capacity compared to the traditional two-state model.

Findings

Adding internal states generally decreases channel capacity.

Certain promoter features like cooperativity can mitigate capacity loss.

Complex promoter architectures can have diverse effects on gene regulation efficiency.

Abstract

Based on the measurements of noise in gene expression performed during the last decade, it has become customary to think of gene regulation in terms of a two-state model, where the promoter of a gene can stochastically switch between an ON and an OFF state. As experiments are becoming increasingly precise and the deviations from the two-state model start to be observable, we ask about the experimental signatures of complex multi-state promoters, as well as the functional consequences of this additional complexity. In detail, we (i) extend the calculations for noise in gene expression to promoters described by state transition diagrams with multiple states, (ii) systematically compute the experimentally accessible noise characteristics for these complex promoters, and (iii) use information theory to evaluate the channel capacities of complex promoter architectures and compare them to the baseline provided by the two-state model. We find that adding internal states to the promoter generically decreases channel capacity, except in certain cases, three of which (cooperativity, dual-role regulation, promoter cycling) we analyze in detail.