Quantification of noise in the bifunctionality-induced post-translational modification

TL;DR

This paper introduces an analytical framework to quantify noise in bacterial two-component systems caused by bifunctionality and post-translational modifications, providing insights into signal transduction variability.

Contribution

It presents a novel analytical model using Langevin equations to quantify fluctuations in phosphorylation states within bacterial signaling pathways.

Findings

Noise can be enhanced or reduced by phosphate flux adjustments.

Fluctuations influence promoter activation/deactivation dynamics.

Analytical expressions for noise profiles in branched pathways are derived.

Abstract

We present a generic analytical scheme for the quantification of fluctuations due to bifunctionality-induced signal transduction within the members of bacterial two-component system. The proposed model takes into account post-translational modifications in terms of elementary phosphotransfer kinetics. Sources of fluctuations due to autophosphorylation, kinase and phosphatase activity of the sensor kinase have been considered in the model via Langevin equations, which are then solved within the framework of linear noise approximation. The resultant analytical expression of phosphorylated response regulators are then used to quantify the noise profile of biologically motivated single and branched pathways. Enhancement and reduction of noise in terms of extra phosphate outflux and influx, respectively, have been analyzed for the branched system. Furthermore, role of fluctuations of the network output in the regulation of a promoter with random activation/deactivation dynamics has been analyzed.