Messenger RNA Fluctuations and Regulatory RNAs Shape the Dynamics of Negative Feedback Loop

TL;DR

This study demonstrates how stochastic fluctuations in messenger RNA and regulatory RNAs influence the dynamics of negative feedback loops, leading to sustained protein pulses and reduced variability in gene expression.

Contribution

It introduces a fully stochastic model of a negative feedback loop that explicitly includes RNA fluctuations and regulatory RNA effects, highlighting their roles in gene expression dynamics.

Findings

RNA fluctuations can produce sustained protein pulses.

Regulatory RNAs reduce gene expression variability.

Stochastic modeling captures single-cell oscillations.

Abstract

Single cell experiments of simple regulatory networks can markedly differ from cell population experiments. Such differences arise from stochastic events in individual cells that are averaged out in cell populations. For instance, while individual cells may show sustained oscillations in the concentrations of some proteins, such oscillations may appear damped in the population average. In this paper we investigate the role of RNA stochastic fluctuations as a leading force to produce a sustained excitatory behavior at the single cell level. Opposed to some previous models, we build a fully stochastic model of a negative feedback loop that explicitly takes into account the RNA stochastic dynamics. We find that messenger RNA random fluctuations can be amplified during translation and produce sustained pulses of protein expression. Motivated by the recent appreciation of the importance of non--coding regulatory RNAs in post--transcription regulation, we also consider the possibility that a regulatory RNA transcript could bind to the messenger RNA and repress translation. Our findings show that the regulatory transcript helps reduce gene expression variability both at the single cell level and at the cell population level.