Force inference predicts local and tissue-scale stress patterns in epithelia

Abstract

Morphogenesis relies on the active generation of forces, and the transmission of these forces to surrounding cells and tissues. Hence measuring forces directly in developing embryos is an essential task to study the mechanics of development. Among the experimental techniques that have emerged to measure forces in epithelial tissues, force inference is particularly appealing. Indeed it only requires a snapshot of the tissue, as it relies on the topology and geometry of cell contacts, assuming that forces are balanced at each vertex. However, establishing force inference as a reliable technique requires thorough validation in multiple conditions. Here we performed systematic comparisons of force inference with laser ablation experiments in three distinct Drosophila epithelia. We show that force inference accurately predicts single junction tensions, tension patterns in stereotyped groups of cells, and tissue-scale stress patterns, in wild type and mutant conditions. We emphasize its ability to capture the distribution of forces at different scales from a single image, which gives it a critical advantage over perturbative techniques such as laser ablation. Our results demonstrate that force inference is a reliable and efficient method to quantify the mechanics of epithelial tissues during morphogenesis.

Variational Method for Image-Based Inference of Internal Stress in Epithelial Tissues

“…In the simplest versions of the method [29,31], 2D geometry was parametrized by a polygonal tiling generally used in vertex models [1,16]. The validity of this approach, of course, rests upon the accuracy of the assumptions and approximations, which varies between tissues and conditions and has to be evaluated in each case; recent studies on force inference techniques show agreement [34]. The major challenge to the approach stems from the sensitivity to noise both in the measurement of cellular geometry as well as on the chosen prior distribution on the boundary conditions at the edge of the observed tissue domain.…”