miRNAs confer phenotypic robustness to gene networks by suppressing biological noise

Abstract

miRNAs are small non-coding RNAs able to modulate target-gene expression. It has been postulated that miRNAs confer robustness to biological processes, but a clear experimental evidence is still missing. Using a synthetic biology approach, we demonstrate that microRNAs provide phenotypic robustness to transcriptional regulatory networks by buffering fluctuations in protein levels. Here we construct a network motif in mammalian cells exhibiting a “toggle - switch” phenotype in which two alternative protein expression levels define its ON and OFF states. The motif consists of an inducible transcription factor that self-regulates its own transcription and that of a miRNA against the transcription factor itself. We confirm, using mathematical modeling and experimental approaches, that the microRNA confers robustness to the toggle-switch by enabling the cell to maintain and transmit its state. When absent, a dramatic increase in protein noise level occurs, causing the cell to randomly switch between the two states.

Clk post-transcriptional control denoises circadian transcription both temporally and spatially

“…In sum, here we found that post-transcriptional control of a master transcriptional regulator provides an efficient mechanism that assures canalized development and that stabilizes a transcriptional network during development and in adult animals. The role of post-transcriptional control in stabilizing the activities and levels of key activators of systems based on feedback loops has been previously proposed 46,47,51 , but to the best of our knowledge, our work constitutes the first theoretical and experimental example of this control principle.…”

“…It has been previously suggested that post-transcriptional control (for example, by miRNAs) could be used to diminish variability in biological systems [46][47][48][49][50][51] . In this context, we speculate that the high-transcriptional/high-turnover Clk profile stabilizes the circadian system by minimizing the consequences of transcriptional noise and/or by allowing rapid transcriptional feedback control.…”

Model-guided quantitative analysis of microRNA-mediated regulation on competing endogenous RNAs using a synthetic gene circuit

“…On the other hand, our work and several recent publications demonstrated that synthetic gene circuits offer a powerful tool, in a largely controlled manner, to understand the fundamental design principles of complex cellular systems (12,13,15). Although the synthetic circuit used in our study could not be fully isolated from the cellular environment because natural miR-21 targets may compete with the synthetic ceRNAs, our model deviation suggested that taking endogenous miR-21 targets into account rescales only the parameter θ in our computational model but does not change any of our conclusions (SI Materials and Methods).…”

“…Synthetic biology provides a complementary approach to investigate miRNA-mediated regulations in a controlled and largely isolated biological setting by using engineered genetic circuits (11). Synthetic circuits have been constructed to help elucidate the underlying design principles of network motifs that combine transcriptional and miRNA-mediated regulations (12)(13)(14). It has also been demonstrated that miRNAs can generate a threshold in target gene expression by using a bidirectional reporter assay in mammalian cells (15).…”

Mathematical modeling of combinatorial regulation suggests that apparent positive regulation of targets by miRNA could be an artifact resulting from competition for mRNA

“…Multi-miRNA-multi-mRNA models have been formulated for specific modules where the targets regulate miRNA transcription, e.g., 2miRNA-2mRNA networks regulating the cell fate/differentiation decision (Lu et al 2013;Yan et al 2014), feedback loops with one miRNA and one target whose protein product regulates miRNA expression (Siciliano et al 2013), or modules where one of the targets is a TF that regulates expression of the other targets (Riba et al 2013). However, we limit our discussion to models where the target proteins have no effect on miRNA activity or concentration.…”