Threshold response and bistability in gene regulation by small noncoding RNA

TL;DR

This paper uses mathematical modeling to explore how small noncoding RNAs influence gene regulation, revealing a transition from threshold to bistable responses and analyzing noise effects on gene expression in E.coli.

Contribution

It demonstrates how subtle regulatory changes can induce bistability in gene expression and characterizes noise effects on sRNA concentration distributions.

Findings

Threshold response shifts to bistability with regulatory changes.

Steady state distributions are bimodal under noise.

Noise influences the stability and distribution of gene expression states.

Abstract

In this paper, we study through mathematical modelling the combined effect of transcriptional and translational regulation by proteins and small noncoding RNAs (sRNA) in a genetic feedback motif that has an important role in the survival of E.coli under stress associated with oxygen and energy availability. We show that subtle changes in this motif can bring in drastically different effects on the gene expression. In particular, we show that a threshold response in the gene expression changes to a bistable response as the regulation on sRNA synthesis or degradation is altered. These results are obtained under deterministic conditions. Next, we study how the gene expression is altered by additive and multiplicative noise which might arise due to probabilistic occurrences of different biochemical events. Using the Fokker-Planck formulation, we obtain steady state probability distributions for sRNA concentration for the network motifs displaying bistability. The probability distributions are found to be bimodal with two peaks at low and high concentrations of sRNAs. We further study the variations in the probability distributions under different values of noise strength and correlations. The results presented here might be of interest for designing synthetic network for artificial control.