ArticlebioRxiv : the preprint server for biology2025
Inferring active and passive mechanical drivers of epithelial convergent extension.
Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
What can we learn about the mechanical processes that shape tissues by simply watching? Several schemes suggest that static cell morphology or junctional connectivity can reveal where chains of cells transmit force or where force asymmetries drive cellular rearrangements. We hypothesize that dynamic cell shape changes from time lapse sequences can be used to distinguish specific mechanisms of tissue morphogenesis. Convergent extension (CE) is a crucial developmental motif wherein a planar tissue narrows in one direction and lengthens in the other. It is tempting to assume that forces driving CE reside within cells of the deforming tissue, as CE may reflect a variety of active processes or passive responses to forces generated by adjacent tissues. In this work, we first construct a simple model of epithelial cells capable of passive CE in response to external forces. We adapt this framework to simulate CE from active anisotropic processes in three different modes: crawling, contraction, and capture. We develop an image analysis pipeline for analysis of morphogenetic changes in both live cells and simulated cells using a panel of mechanical and statistical approaches. Our results allow us to identify how each simulated mechanism uniquely contributes to tissue morphology and provide insight into how force transmission is coordinated. We construct a MEchanism Index (MEI) to quantify how similar live cells are to simulated passive and active cells undergoing CE. Applying these analyses to live cell data of
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