Inference of internal stress in a cell monolayer

TL;DR

This paper introduces Bayesian inversion stress microscopy (BISM), a robust method combining traction force data to accurately infer the internal stress field in cell monolayers, validated through simulations and applied to experimental data.

Contribution

The paper presents BISM, a novel Bayesian approach for stress inference in cell monolayers that is independent of tissue rheology and validated with simulations and experiments.

Findings

BISM accurately infers stress fields from traction data.

The method is robust across various model assumptions.

Experimental application confirms the method's validity.

Abstract

We combine traction force data with Bayesian inversion to obtain an absolute estimate of the internal stress field of a cell monolayer. The method, Bayesian inversion stress microscopy (BISM), is validated using numerical simulations performed in a wide range of conditions. It is robust to changes in each ingredient of the underlying statistical model. Importantly, its accuracy does not depend on the rheology of the tissue. We apply BISM to experimental traction force data measured in a narrow ring of cohesive epithelial cells, and check that the inferred stress field coincides with that obtained by direct spatial integration of the traction force data in this quasi-one-dimensional geometry.