Determining the accuracy of spatial gradient sensing using statistical mechanics

TL;DR

This paper models eukaryotic cell gradient sensing using statistical mechanics, deriving physical limits of accuracy and showing how cell size and receptor cooperativity influence measurement precision.

Contribution

It introduces a novel Ising spin chain model to analyze the physical limits of spatial gradient sensing in cells, incorporating receptor interactions.

Findings

Accuracy improves with cell size

Receptor cooperativity enhances sensing precision

Small bacteria can perform spatial gradient measurements

Abstract

Many eukaryotic cells are able to sense chemical gradients by directly measuring spatial concentration differences. The precision of such gradient sensing is limited by fluctuations in the binding of diffusing particles to specific receptors on the cell surface. Here, we explore the physical limits of the spatial sensing mechanism by modeling the chemotactic cell as an Ising spin chain subject to a spatially varying field. This allows us to derive the maximum likelihood estimators of the gradient parameters as well as explicit expressions for their asymptotic uncertainties. The accuracy increases with the cell's size and our results demonstrate that this accuracy be further increased by introducing a non-zero cooperativity between neighboring receptors. Thus, consistent with recent experimental data, it is possible for small bacteria to perform spatial measurements of gradients.