Redundancy in the information transmission in a two-step cascade

TL;DR

This paper introduces a stochastic framework to analyze information transmission in a two-step biochemical cascade, revealing how redundancy enhances signaling fidelity through Markovian properties.

Contribution

It develops a mathematical model using Langevin equations to quantify redundancy and synergy in a two-step cascade, linking Markovianity to information transmission.

Findings

Redundancy arises from the Markovian nature of the cascade.

Redundancy increases the fidelity of signal transmission.

The framework accounts for linear and nonlinear production terms.

Abstract

We present a stochastic framework to study signal transmission in a generic two-step cascade $\text{S} \rightarrow \text{X} \rightarrow \text{Y}$. Starting from a set of Langevin equations obeying Gaussian noise processes we calculate the variance and covariance while considering both linear and nonlinear production terms for different biochemical species of the cascade. These quantities are then used to calculate the net synergy within the purview of partial information decomposition. We show that redundancy in information transmission is essentially an important consequence of Markovian property of the two-step cascade motif. We also show that redundancy increases fidelity of the signalling pathway.