  A feed-forward loop (FFL) is a common gene-regulatory motif in which usually
the upstream regulator is a protein, a transcription factor, that regulates the
expression of the target protein in two parallel pathways. Here, we study a
distinct 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 target
protein and its transcriptional activator. Such 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 the noise affects
the functionality of sFFL. We find the response of sFFLto be stronger, faster,
and more sensitive to the initial concentration of the upstream regulator than
tFFL and smFFL. Further, a generating function based analysis and stochastic
simulations lead to a non-trivial prediction that an optimal noise filtration
can be attained depending on the synthesis rate of the sRNA and the degradation
rate of the transcriptional activator. We conclude that in sFFL, 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. Given the
advantages of sFFL brought out in this work, it should not be surprising if
future work reveals their employment in different biological contexts.
