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A feed-forward loop (FFL) is a common gene-regulatory motif in which usuallythe upstream regulator is a protein, a transcription factor, that regulates theexpression of the target protein in two parallel pathways. Here, we study adistinct sRNA-driven FFL (sFFL) discovered recently in Salmonella enterica.Unlike previously studied transcriptional FFLs (tFFL) and sRNA-mediated FFLs(smFFL), here the upstream regulator is an sRNA that activates the targetprotein and its transcriptional activator. Such sFFL has not been subjected torigorous analysis. We, therefore, set out to understand two aspects. First is aquantitative comparison of the regulatory response of sFFL with tFFL and smFFLusing a differential equation framework. Since the process of gene expressionis inherently stochastic, the second objective is to find how the noise affectsthe functionality of sFFL. We find the response of sFFLto be stronger, faster,and more sensitive to the initial concentration of the upstream regulator thantFFL and smFFL. Further, a generating function based analysis and stochasticsimulations lead to a non-trivial prediction that an optimal noise filtrationcan be attained depending on the synthesis rate of the sRNA and the degradationrate of the transcriptional activator. We conclude that in sFFL, sRNA plays acritical role not only in driving a rapid and strong response, but also areliable response that depends critically on its concentration. Given theadvantages of sFFL brought out in this work, it should not be surprising iffuture work reveals their employment in different biological contexts.

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