Multiscale Modeling of Information Conveyed by Gene-Regulatory Signaling

Cells leverage signaling molecules to carry information about the cellular state to receptors that regulate protein synthesis in order to suit the cell's dynamically evolving needs. This regulation remains efficient and robust, despite that substantial stochasticity pervades the sub-cellular environment. In electronic and wireless signaling systems, the mutual information quantifies the extent to which information in a signal can be received across a communications channel. Applying this same metric to gene-regulatory interactions can better clarify how these biological signaling systems mitigate environmental noise. In this paper we study the information-transmission characteristics of a single gene-regulatory interaction by employing an exactly solvable master equation model for the production and degradation of individual proteins. This molecular-scale description is then coupled to a mass-action kinetics model of dynamic protein concentrations in a macroscopic sample of cells, enabling parameter values to be obtained by experiments performed using cell-based assays. We find that the mutual information depends monotonically on two parameters: one which characterizes stochastic variations in the concentration of signaling molecules, and the other the ratio of kinetic production to degradation rates of the regulated protein.