133 research outputs found
Optimal first-passage time in gene regulatory networks
The inherent probabilistic nature of the biochemical reactions, and low copy
number of species can lead to stochasticity in gene expression across identical
cells. As a result, after induction of gene expression, the time at which a
specific protein count is reached is stochastic as well. Therefore events
taking place at a critical protein level will see stochasticity in their
timing. First-passage time (FPT), the time at which a stochastic process hits a
critical threshold, provides a framework to model such events. Here, we
investigate stochasticity in FPT. Particularly, we consider events for which
controlling stochasticity is advantageous. As a possible regulatory mechanism,
we also investigate effect of auto-regulation, where the transcription rate of
gene depends on protein count, on stochasticity of FPT. Specifically, we
investigate for an optimal auto-regulation which minimizes stochasticity in
FPT, given fixed mean FPT and threshold.
For this purpose, we model the gene expression at a single cell level. We
find analytic formulas for statistical moments of the FPT in terms of model
parameters. Moreover, we examine the gene expression model with
auto-regulation. Interestingly, our results show that the stochasticity in FPT,
for a fixed mean, is minimized when the transcription rate is independent of
protein count. Further, we discuss the results in context of lysis time of an
\textit{E. coli} cell infected by a phage virus. An optimal lysis
time provides evolutionary advantage to the phage, suggesting a
possible regulation to minimize its stochasticity. Our results indicate that
there is no auto-regulation of the protein responsible for lysis. Moreover,
congruent to experimental evidences, our analysis predicts that the expression
of the lysis protein should have a small burst size.Comment: 8 pages, 3 figures, Submitted to Conference on Decision and Control
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