On the role of extrinsic noise in microRNA-mediated bimodal gene expression

Abstract

Several studies highlighted the relevance of extrinsic noise in shaping cell decision making and differentiation in molecular networks. Bimodal distributions of gene expression levels provide experimental evidence of phenotypic differentiation, where the modes of the distribution often correspond to different physiological states of the system. We theoretically address the presence of bimodal phenotypes in the context of microRNA (miRNA)-mediated regulation. MiRNAs are small noncoding RNA molecules that downregulate the expression of their target mRNAs. The nature of this interaction is titrative and induces a threshold effect: below a given target transcription rate almost no mRNAs are free and available for translation. We investigate the effect of extrinsic noise on the system by introducing a fluctuating miRNA-transcription rate. We find that the presence of extrinsic noise favours the presence of bimodal target distributions which can be observed for a wider range of parameters compared to the case with intrinsic noise only and for lower miRNA-target interaction strength. Our results suggest that combining threshold-inducing interactions with extrinsic noise provides a simple and robust mechanism for obtaining bimodal populations without requiring fine tuning. Furthermore, we characterise the protein distribution’s dependence on protein half-life.

Long Range Order and Short Range Disorder in Saccharomyces cerevisiae Biofilm

“…Single cell microorganisms are free-living system often yielding uncorrelated (disordered) responses [31][32][33]. However, when they are exposed to environmental or pathogenic threats, a large number of species are able to aggregate, often within a self-secreted extracellular polymeric substances matrix or through quorum sensing, resulting in a highly ordered structure called biofilm [14].…”

“…This result suggests that the two tails of the gene expression distributions might be due to two different regulations [32]. The upper tail corresponds to higher gene expressions, from transcripts produced through more constitutive gene expression mechanisms, less prone to biological variations or to technical noise.…”

Networks of enhancers and microRNAs drive variation in cell states

“…This implies that when miRNA transcription rates for different cells are sampled around this threshold due to cell-to-cell heterogeneity, one will typically find the target to be expressed in some cells (at different levels) and repressed in others. Such a setup has been shown to robustly generate bimodal expression profiles even in presence of weak miRNA-RNA interactions (Del Giudice et al, 2018).…”

microRNA-mediated noise processing in cells: A fight or a game?

“…the broader the miRNA distribution, the easier to have values of miRNA such that the target is for one cell in the repressed regime and for another cell in the unrepressed one. Bimodal distributions may then appear even if the interaction strength is mild [25,26]. Such a scenario is valid not only for a one-miRNA/one-target system but also when multiple miRNAs and targets are interacting.…”