Abstract
Small non-coding RNAs can exert significant regulatory activity on gene expression in bacteria. In recent years, substantial progress has been made in understanding bacterial gene expression by sRNAs. However, recent findings that demonstrate that families of mRNAs show non-trivial sub-cellular distributions raise the question of how localization may affect the regulatory activity of sRNAs. Here we address this question within a simple mathematical model. We show that the non-uniform spatial distributions of mRNA can alter the threshold-linear response that characterizes sRNAs that act stoichiometrically, and modulate the hierarchy among targets co-regulated by the same sRNA. We also identify conditions where the sub-cellular organization of cofactors in the sRNA pathway can induce spatial heterogeneity on sRNA targets. Our results suggest that under certain conditions, interpretation and modeling of natural and synthetic gene regulatory circuits need to take into account the spatial organization of the transcripts of participating genes.
Highlights
A class of non-coding RNAs, known as small RNAs, play a crucial role in the regulation of gene expression in bacteria [1,2,3]
PACS numbers: Sub-cellular mRNA localization modulates the regulation of gene expression by small RNAs in bacteria2
Sub-cellular mRNA localization modulates the regulation of gene expression by small RNAs in bacteria3 proteins
Summary
Rod-shaped bacteria such as Escherichia and Pseudomonas, regardless of their detailed morphologies, can be idealized as circular cylinders. Sub-cellular mRNA localization modulates the regulation of gene expression by small RNAs in bacteria proteins In this mechanism, nascent membrane proteins may be targeted to the membrane once a signal recognition peptide or a membrane-binding domain has been synthesized, even before completion of translation of the entire protein. Since some of small RNAs have high affinity to Hfq, it is possible that the interaction with Hfq increases the affinity of some sRNAs to the membrane region We investigate both the case where the small RNA diffuses freely between regions, d(s12) = d(s21), as well as the case where the rate d(s21) is associated with unbinding from Hfq. Our model accounts for a single sRNA and its n targets. In all calculations we use a set of parameters that has been experimentally verified in E. coli (Table 1)
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