Dynamical information synergy in biochemical signaling networks

TL;DR

This paper analytically and numerically investigates how biochemical signaling networks encode information through dynamical patterns, revealing synergy effects in measurements and extending understanding beyond linear regimes.

Contribution

It introduces an analytical framework for information in signaling dynamics and uncovers synergy effects in oscillatory and modulated signals, advancing knowledge of biochemical information processing.

Findings

Synergy between successive measurements exceeds sum of individual information.

Oscillatory dynamics can enhance information encoding.

Frequency and damping modulation induce synergistic effects.

Abstract

Biological cells encode information about their environment through biochemical signaling networks that control their internal state and response. This information is often encoded in the dynamical patterns of the signaling molecules, rather than just their instantaneous concentrations. Here, we analytically calculate the information contained in these dynamics for a number of paradigmatic cases in the linear regime, for both static and time-dependent input signals. When considering oscillatory output dynamics, we report the emergence of synergy between successive measurements, meaning that the joint information in two measurements exceeds the sum of the individual information. We extend our analysis numerically beyond the scope of linear input encoding to reveal synergetic effects in the cases of frequency or damping modulation, both of which are relevant to classical biochemical signaling systems.