Genome-wide gene expression noise in Escherichia coli is condition-dependent and determined by propagation of noise through the regulatory network

Abstract

Although it is well appreciated that gene expression is inherently noisy and that transcriptional noise is encoded in a promoter’s sequence, little is known about the extent to which noise levels of individual promoters vary across growth conditions. Using flow cytometry, we here quantify transcriptional noise in Escherichia coli genome-wide across 8 growth conditions and find that noise levels systematically decrease with growth rate, with a condition-dependent lower bound on noise. Whereas constitutive promoters consistently exhibit low noise in all conditions, regulated promoters are both more noisy on average and more variable in noise across conditions. Moreover, individual promoters show highly distinct variation in noise across conditions. We show that a simple model of noise propagation from regulators to their targets can explain a significant fraction of the variation in relative noise levels and identifies TFs that most contribute to both condition-specific and condition-independent noise propagation. In addition, analysis of the genome-wide correlation structure of various gene properties shows that gene regulation, expression noise, and noise plasticity are all positively correlated genome-wide and vary independently of variations in absolute expression, codon bias, and evolutionary rate. Together, our results show that while absolute expression noise tends to decrease with growth rate, relative noise levels of genes are highly condition-dependent and determined by the propagation of noise through the gene regulatory network.

Growth rate controls the sensitivity of gene regulatory circuits

“…That is, GCS causes fast growing cells to stabilize their current state by effectively muting their response to fluctuations in external signals and causes slowly growing cells to become highly sensitive to external signals. This view is consistent with recent work from our lab that shows that gene expression noise in E. coli results to a large extent from the propagation of noise through the gene regulatory network, and that noise levels systematically decrease with growth rate [23]. This suggests a general strategy in which GCS causes slowly growing cells to more actively explore alternative gene expression states and we show elsewhere that such behavior is highly adaptive for bet-hedging strategies [24].…”

Coupling phenotype stability to growth rate overcomes limitations of bet-hedging strategies

“…There is in fact significant evidence supporting that phenotype switching rates tend to decrease with growth rate. In a number of studies it has been observed that gene expression noise levels decrease with growth rate [22][23][24]30] and metabolic heterogeneity has also been observed to increase with nutrient limitation [41][42][43][44][45][46]. Since phenotype switches are often ultimately driven by fluctuations in gene expression or metabolic state [12,[25][26][27][28][29]47], phenotype switching rates will generally increase with gene expression noise levels.…”

“…It is currently not clear what mechanisms underlie the decrease of gene expression noise with growth rate. Analysis of genome-wide noise in E. coli across different growth conditions has shown that while relative noise levels of different genes are highly condition-dependent and are driven by noise propagation through the regulatory network, absolute noise levels decrease systematically with growth rate in a way that appears to affect all genes [24]. This suggests that the overall decrease in gene expression noise with growth rate results from mechanisms that affect all genes.…”

Transcriptional control of the lacZ promoter is under directional and diversifying selection

“…We did find a single random mutant that shared one of these segregating polymorphisms, and the noise phenotype of this random mutant changed considerably from the progenitor MG1655 in the direction expected if this polymorphism is causal. It has previously been shown that only a small number of genetic changes can affect noise phenotypes (Hornung et al 2012; Metzger et al 2015; Wolf et al 2015; Schmiedel et al 2019; Urchueguía et al 2021; Vlková and Silander 2021).…”