Quantifying efficient information transduction of biochemical signaling cascades

TL;DR

This paper models biochemical signaling cascades as efficient information transduction systems, linking entropy production to signal transmission efficiency and proposing entropy rate as a quantifiable measure.

Contribution

It introduces a coding framework that minimizes bits per molecule concentration, revealing uniform entropy production rates in cascades for optimal information transfer.

Findings

Entropy production rate is uniform across cascade cycles.

Entropy rate effectively quantifies intracellular signal transduction.

Chemical reaction cascades can be optimized for maximum information efficiency.

Abstract

Cells can be considered as systems that utilize changes in thermodynamic entropy as information. Therefore, they serve as useful models for investigating the relationships between entropy production and information transmission, i.e., signal transduction. Based on the hypothesis that cells apply a chemical reaction cascade for the most efficient transduction of information, we adopted a coding design that minimizes the number of bits per concentration of molecules that are employed for information transduction. As a result, the average rate of entropy production is uniform across all cycles in a cascade reaction. Thus, the entropy production rate can be a valuable measure for the quantification of intracellular signal transduction.