Abstract
MicroRNAs (miRNAs) have been shown to modulate gene expression noise, but less is known about how miRNAs with different properties may regulate noise differently. Here, we investigate the role of competing RNAs and the composition of miRNA response elements (MREs) in modulating noise. We find that weak competing RNAs could introduce lower noise than strong competing RNAs. In comparison with a single MRE, both repetitive and composite MREs can reduce the noise at low expression, but repetitive MREs can elevate the noise remarkably at high expression. We further observed the behavior of a synthetic cell-type classifier with miRNAs as inputs and find that miRNAs and MREs that could introduce higher noise tend to enhance cell state transition. These results provide a systematic and quantitative understanding of the function of miRNAs in controlling gene expression noise and the utilization of miRNAs to modulate the behavior of synthetic gene circuits.
Highlights
Stochastic fluctuations lead to variation, or noise, in gene expression levels, which is inevitable even among genetically identical cells exposed to the same environmental conditions (Elowitz et al, 2002)
miRNA response elements (MREs) are fused to the 30 untranslated region (30 UTR) of EYFP, whereas the expression of mKate2 is not regulated by miRNAs (Figure 1A)
Though imperfect MREs can only repress the target gene slightly (Figure S6A), we found that weak competing RNAs can buffer gene expression noise via imperfect MREs at intermediate and high expression especially when calculating modulation capacity (MC) by the miRmap score, and the trend is insensitive to the value of threshold (Figures S4D–S4F)
Summary
Stochastic fluctuations lead to variation, or noise, in gene expression levels, which is inevitable even among genetically identical cells exposed to the same environmental conditions (Elowitz et al, 2002). In clonal populations of microbes, gene expression noise enables cells to generate diverse phenotypes, which may improve the fitness of the population in certain environments (Blake et al, 2006; Cagatay et al, 2009; Maamar et al, 2007; Su€el et al, 2007). Noise is necessary in excitable circuits for the initiation of transient state transition (Eldar and Elowitz, 2010; Maamar et al, 2007; Su€el et al, 2007). It is valuable to understand the mechanism of noise modulation in nature and manipulate gene expression noise to control phenotypes according to expectations
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