Abstract
BackgroundCells must face the ubiquitous presence of noise at the level of signaling molecules. The latter constitutes a major challenge for the regulation of cellular functions including communication processes. In the context of prokaryotic communication, the so-called quorum sensing (QS) mechanism relies on small diffusive molecules that are produced and detected by cells. This poses the intriguing question of how bacteria cope with the fluctuations for setting up a reliable information exchange.ResultsWe present a stochastic model of gene expression that accounts for the main biochemical processes that describe the QS mechanism close to its activation threshold. Within that framework we study, both numerically and analytically, the role that diffusion plays in the regulation of the dynamics and the fluctuations of signaling molecules. In addition, we unveil the contribution of different sources of noise, intrinsic and transcriptional, in the QS mechanism.ConclusionsThe interplay between noisy sources and the communication process produces a repertoire of dynamics that depends on the diffusion rate. Importantly, the total noise shows a non-monotonic behavior as a function of the diffusion rate. QS systems seems to avoid values of the diffusion that maximize the total noise. These results point towards the direction that bacteria have adapted their communication mechanisms in order to improve the signal-to-noise ratio.
Highlights
Cells must face the ubiquitous presence of noise at the level of signaling molecules
We have shown that the dynamics of the signaling molecule exhibits different behaviors depending on the diffusion coefficient
We have shown that the mRNA dynamics plays a crucial role for regulating the total amount of molecular noise of the signaling molecules
Summary
Cells must face the ubiquitous presence of noise at the level of signaling molecules. Prokaryotic gene regulation mainly relies on the binding of regulatory proteins that attach to DNA for either stimulating or repressing transcription These binding/unbinding events are intrinsically probabilistic because of the significance of thermal fluctuations at that scale and the low number of molecules involved in the process. Over the past years a growing number of experiments have characterized the levels of randomness in cellular biochemical processes and their functionality [3,4,5,6,7,8] Technical advances such as the use of fluorescent tags in single-cell experiments have allowed for quantitative measurements of the noise in protein concentration and have shed light on the mechanisms of gene expression that lead to cell-to-cell variability [9,10,11]. It is accepted that stochastic and non-linear approaches are required for understanding the randomness in the dynamics of biochemical reactions and the effects of fluctuations in gene regulatory networks [7,8]
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