Small RNA driven feed-forward loop: critical role of sRNA in noise filtering

Gene regulatory networks are often partitioned into different types of recurring network motifs. A feed-forward loop (FFL) is a common motif in which an upstream regulator is a protein, typically a transcription factor, that regulates the expression of the target protein in two ways-first, directly by regulating the mRNA levels of the target protein and second, indirectly via an intermediate molecule that in turn regulates the target protein level. Investigations on two variants of FFL-purely transcriptional FFL (tFFL) and sRNA-mediated FFL (smFFL) reveal several advantages of using such motifs. Here, we study a distinct sRNA-driven FFL (sFFL) that was discovered recently in Salmonella enterica: the distinction being the upstream regulator here is not a protein but an sRNA that translationally activates the target protein expression directly; and also indirectly via regulation of the transcriptional activator of the target protein. This variant, i.e. sFFL has not been subjected to rigorous analysis. We, therefore, set out to understand two aspects. First is a quantitative comparison of the regulatory response of sFFL with tFFL and smFFL using a differential equation framework. Since the process of gene expression is inherently stochastic, the second objective is to find how noise in gene expression affects the functionality of the sFFL. We find that unlike for tFFL and smFFL, the response of sFFL is stronger and faster: the change in target protein concentration is rapid and depends critically on the initial concentration of sRNA. Further, our analysis based on generating function approach and stochastic simulations leads to a non-trivial prediction that an optimal noise filtration can be attained depending on the synthesis rate of the upstream sRNA and the degradation rate of the intermediate transcriptional activator. A comparison with a simpler process involving only translational activation by sRNA indicates that the design of sFFL is crucial for optimal noise filtration. These observations prompt us to conclude that sFFL has distinct advantages where the master regulator, sRNA, plays a critical role not only in driving a rapid and strong response, but also a reliable response that depends critically on its concentration.