ForSys: Non-invasive stress inference from time-lapse microscopy.

ABSTRACT: During tissue development and regeneration, cells interpret and exert mechanical forces that are challenging to measure in vivo. Stress inference algorithms have thus emerged as powerful tools to estimate tissue stresses. Yet, effectively incorporating tissue dynamics into these algorithms remains elusive. Here, we introduce ForSys, a Python-based software that infers intercellular stresses and intracellular pressures from time-lapse microscopy. After validation, we applied ForSys to the migrating zebrafish lateral-line primordium, revealing increased stress during the cell rounding that precedes mitosis and accurately predicting the onset of epithelial rosettogenesis. We further used ForSys to study neuromast development and uncovered mechanical asymmetries linked to cell type-spec

SUBMITTER: Borges A 

PROVIDER: S-EPMC12556342 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature