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.
Highlights
Gene-expression data displays bimodal distributions in several systems ranging from cancer to immune cells [1, 2]
Phenotypic differentiation often relies on bimodal distributions of gene expression levels, which can normally be achieved by different molecular mechanisms
We theoretically address the question on how microRNA-mediated regulation can induce the appearance of bimodal phenotypes
Summary
Gene-expression data displays bimodal distributions in several systems ranging from cancer to immune cells [1, 2]. The two peaks of the distribution are usually associated with different physiological states of the system, be that different stem-cell fates or different disease states or cancer subtypes [3,4,5,6]. As shown in [7] and reviewed in [8], bimodality in some biological systems is solely due to stochastic effects. Environmental fluctuations, usually referred to as extrinsic noise [9, 10], can be a source of noise in molecular networks. Together with intrinsic fluctuations due to the probabilistic nature of chemical reactions, extrinsic noise shapes gene expression and may in principle drive cell differentiation
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