Maximal information transmission is compatible with ultrasensitive biological pathways

TL;DR

This paper develops a new analytical framework to identify optimal input distributions and input-output relationships in biological signaling pathways, demonstrating that maximal information transmission can coexist with ultrasensitive responses, exemplified by E. coli chemotaxis.

Contribution

It introduces a formalism that finds globally optimal input distributions and input-output curves considering noise and dynamic range, expanding beyond traditional fixed-channel capacity analysis.

Findings

Universal optimal input distribution depends only on input noise.

E. coli chemotaxis pathway is compatible with optimal information transmission.

The formalism generalizes to multiple inputs and outputs.

Abstract

Cells are often considered input-output devices that maximize the transmission of information by converting extracellular stimuli (input) via signaling pathways (communication channel) to cell behavior (output). However, in biological systems outputs might feed back into inputs due to cell motility, and the biological channel can change by mutations during evolution. Here, we show that the conventional channel capacity obtained by optimizing the input distribution for a fixed channel may not reflect the global optimum. In a new approach we analytically identify both input distributions and input-output curves that optimally transmit information, given constraints from noise and the dynamic range of the channel. We find a universal optimal input distribution only depending on the input noise, and we generalize our formalism to multiple outputs (or inputs). Applying our formalism to Escherichia coli chemotaxis, we find that its pathway is compatible with optimal information transmission despite the ultrasensitive rotary motors.