ceRNA crosstalk stabilizes protein expression and affects the correlation pattern of interacting proteins

Abstract

Gene expression is a noisy process and several mechanisms, both transcriptional and post-transcriptional, can stabilize protein levels in cells. Much work has focused on the role of miRNAs, showing in particular that miRNA-mediated regulation can buffer expression noise for lowly expressed genes. Here, using in silico simulations and mathematical modeling, we demonstrate that miRNAs can exert a much broader influence on protein levels by orchestrating competition-induced crosstalk between mRNAs. Most notably, we find that miRNA-mediated cross-talk (i) can stabilize protein levels across the full range of gene expression rates, and (ii) modifies the correlation pattern of co-regulated interacting proteins, changing the sign of correlations from negative to positive. The latter feature may constitute a potentially robust signature of the existence of RNA crosstalk induced by endogenous competition for miRNAs in standard cellular conditions.

Single cell transcriptomes reveal characteristics of miRNA in gene expression noise reduction

“…Previous studies were mainly focused on the role of miRNAs but neglected the miRNA-mediated cross-talk among competing targets. Recent works have found that the cross-talk among competing targets could enhance the stability of gene expression [13,14,45]. Here, we observed a positive correlation between the abundance of targets pool and noise reduction ( Fig.…”

“…Without loss of generality, we assumed that the extrinsic noise has the same effect on all parameters, that is, all reaction kinetic rates share an equivalent Fano factor. 13 Model simulation suggested that, miRNA could reduce mRNA expression noise in the low expression zone but introduce extra miRNA pool noise in high level of mRNA expression compared to an unregulated gene at equal mRNA expression levels (yellow line in Fig. 6C) similar to previous experimental results in protein level [9].…”

“…One proposed assumption is that miRNAs can modulate variations of gene expression and confer robustness of cell population phenotypes [7,[9][10][11]. Several recent works have studied the effect of miRNA regulation on gene expression noise in protein levels using synthetic gene circuits [9,10,12,13]. Siciliano et al [10] demonstrated that miRNAs provide phenotypic robustness to transcriptional regulatory networks by buffering fluctuations in protein levels.…”

“…Schmiedel et al [9] showed that miRNAs can reduces target gene intrinsic noise but with the cost of introducing extra noise of miRNA itself (miRNA pool noise, the fluctuation leaded by the changing of miRNA expression level [9]). Martirosyan et al [13,14] showed that the co-regulated targets of one miRNA species (competing RNAs) could enhance target stability across the full range of protein expression by buffering miRNA pool noise.…”

Competing endogenous RNA crosstalk at system level

“…In silico studies of small motifs, summarized e.g. in [16,17], have characterized how the strength, selectivity and directionality of miRNA-mediated RNA crosstalk are modulated by kinetic and topologic ingredients, leading to highly adjustable output profiles [18][19][20], differential processing of intrinsic and extrinsic heterogeneities [21][22][23][24], stabilization of protein levels [25,26] and long-range effects [27], both at steady state and during transients [28]. Experimental evidence, however, suggests that, in order to fully develop its potential, RNA crosstalk presupposes rather specific conditions, either in terms of the size of the perturbation required to generate a significant response [29][30][31] or in terms of molecular abundances and kinetic parameters [32][33][34] (see e.g.…”