Optimizing information flow in small genetic networks. IV. Spatial coupling

TL;DR

This paper extends an information-theoretic framework to spatially coupled gene networks, showing that diffusion enhances signal transmission and leads to new regulatory strategies in noisy gene expression systems.

Contribution

It introduces a model for spatially extended gene regulation, demonstrating how diffusion improves information flow and alters gene activation responses.

Findings

Diffusion significantly enhances information transmission at low input concentrations.

Optimal gene activation functions shift towards step-like responses with diffusion.

A new regulatory strategy involves cells responding sharply to inputs, averaged by diffusion.

Abstract

We typically think of cells as responding to external signals independently by regulating their gene expression levels, yet they often locally exchange information and coordinate. Can such spatial coupling be of benefit for conveying signals subject to gene regulatory noise? Here we extend our information-theoretic framework for gene regulation to spatially extended systems. As an example, we consider a lattice of nuclei responding to a concentration field of a transcriptional regulator (the "input") by expressing a single diffusible target gene. When input concentrations are low, diffusive coupling markedly improves information transmission; optimal gene activation functions also systematically change. A qualitatively new regulatory strategy emerges where individual cells respond to the input in a nearly step-like fashion that is subsequently averaged out by strong diffusion. While motivated by early patterning events in the Drosophila embryo, our framework is generically applicable to spatially coupled stochastic gene expression models.