Back

Dynamical forces drive organ morphology changes during embryonic development

Manna, R. K.; Retzlaff, E. M.; Hinman, A. M.; Lan, Y.; Abdel-Razek, O.; Bates, M.; Hehnly, H.; Amack, J. D.; Manning, M. L.

2024-07-17 developmental biology
10.1101/2024.07.13.603371 bioRxiv
Show abstract

Cells, tissues, and organs must change shape in precise ways during embryonic development to execute their functions. Multiple mechanisms including biochemical signaling pathways and biophysical forces help drive these morphology changes, but it has been difficult to tease apart their contributions, especially from tissue-scale dynamic forces that are typically ignored. We use a combination of mathematical models and in vivo experiments to study a simple organ in the zebrafish embryo called Kupffers vesicle. Modeling indicates that dynamic forces generated by tissue movements in the embryo produce shape changes in Kupffers vesicle that are observed during development. Laser ablations in the zebrafish embryo that alter these forces result in altered organ shapes matching model predictions. These results demonstrate that dynamic forces sculpt cell and organ shape during embryo development. Significance StatementWe aim to understand the mechanisms that control precise cell and tissue shape changes required for organ function. Many studies focused on cell shapes have ignored the role of dynamic forces self-generated by slow tissue flows, but recent work showing tissues are near a jamming transition with diverging relaxation timescales suggests slow motion could give rise to large forces. Through a combination of mathematical modeling, imaging, and mechanical perturbations to in vivo experiments, our work demonstrates that tissue-scale dynamic forces are sculpting the shape of an epithelial organ in the zebrafish embryo called Kupffers vesicle (KV). Because there are many processes during development that occur at similarly slow rates, this suggests that self-generated dynamic forces should be investigated more broadly.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.