Back

Asymmetric Contraction of Adherens Junctions arises through RhoA and E-cadherin feedback

Cavanaugh, K.; Staddon, M.; Chmiel, T. A.; Harmon, R. M.; Budnar, S.; Yap, A. S.; Banerjee, S.; Gardel, M.

2021-02-26 cell biology
10.1101/2021.02.26.433093 bioRxiv
Show abstract

Tissue morphogenesis often arises from the culmination of discrete changes in cell-cell junction behaviors, namely ratcheted junction contractions that lead to collective cellular rearrangements. Mechanochemical signaling in the form of RhoA underlies these ratcheted contractions, which occur asymmetrically as one highly motile vertex contracts toward a relatively less motile tricellular vertex. The underlying mechanisms driving asymmetric vertex movement remains unknown. Here, we use optogenetically controlled RhoA in model epithelia together with biophysical modeling to uncover the mechanism lending to asymmetric vertex motion. We find that both local and global RhoA activation leads to increases in junctional tension, thereby facilitating vertex motion. RhoA activation occurs in discrete regions along the junction and is skewed towards the less-motile vertex. At these less-motile vertices, E-cadherin acts as an opposing factor to limit vertex motion through increased frictional drag. Surprisingly, we uncover a feedback loop between RhoA and E-cadherin, as regional optogenetic activation of specified junctional zones pools E-cadherin to the location of RhoA activation. Incorporating this circuit into a mathematical model, we find that a positive feedback between RhoA-mediated tension and E-cadherin-induced frictional drag on tricellular vertices recapitulates experimental data. As such, the location of RhoA determines which vertex is under high tension, pooling E-cadherin and increasing the frictional load at the tricellular vertex to limit its motion. This feedback drives a tension-dependent intercellular "clutch" at tricellular vertices which stabilizes vertex motion upon tensional load.

Matching journals

The top 3 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.