Generating active T1 transitions through mechanochemical feedback

Rastko Sknepnek*, Ilyas Djafer-Cherif, Manli Chuai, Cornelis Weijer*, Silke Henkes*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

22 Citations (Scopus)

Abstract

Convergence–extension in embryos is controlled by chemical and mechanical signalling. A key cellular process is the exchange of neighbours via T1 transitions. We propose and analyse a model with positive feedback between recruitment of myosin motors and mechanical tension in cell junctions. The model produces active T1 events, which act to elongate the tissue perpendicular to the main direction of tissue stress. Using an idealised tissue patch comprising several active cells embedded in a matrix of passive hexagonal cells, we identified an optimal range of mechanical stresses to trigger an active T1 event. We show that directed stresses also generate tension chains in a realistic patch made entirely of active cells of random shapes and leads to convergence–extension over a range of parameters. Our findings show that active intercalations can generate stress that activates T1 events in neighbouring cells, resulting in tension-dependent tissue reorganisation, in qualitative agreement with experiments on gastrulation in chick embryos.
Original languageEnglish
Article numbere79862
JournaleLife
Volume12
Early online date11 Apr 2023
DOIs
Publication statusPublished - 3 May 2023

Bibliographical note

Funding Information:
RS, MC, and CJW acknowledge support by the UK BBSRC (award BB/N009789/1). SH and IDC acknowledge support by the UK BBSRC (grant number BB/N009150/1-2). IDC acknowledges funding under Dioscuri, a programme initiated by the Max Planck Society, jointly managed with the National Science Centre in Poland, and mutually funded by the Polish Ministry of Science and Higher Education and German Federal Ministry of Education and Research (UMO-2019/02/H/NZ6/00003). We thank Antti Karjalainen for providing the MATLAB code used to analyse experimental data. RS thanks Andrej Košmrlj, Daniel Matoz-Fernandez, and Sijie Tong for many helpful discussions about the vertex model.

Publisher Copyright:
© 2023, eLife Sciences Publications Ltd. All rights reserved.

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