Phenotypic switching in gene regulatory networks

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Abstract
Significance: Phenotypes of an isogenic cell population are determined by states of low and high gene expression. These are often associated with multiple steady states predicted by deterministic models of gene regulatory networks. Gene expression is, however, regulated via stochastic molecular interactions at transcriptional and translational levels. Here, we show that intrinsic noise can induce multimodality in a wide class of regulatory networks whose corresponding deterministic description lacks multistability, thus offering a plausible alternative mechanism for phenotypic switching without the need for ultrasensitivity or highly cooperative interactions. We derive a general analytical framework for quantifying this phenomenon, thereby elucidating how cells encode decisions, and how they retain memory of transient environmental signals, using common gene regulatory motifs.

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