Rap1 coordinates cell-cell adhesion and cytoskeletal reorganization to drive collective cell migration <i>in vivo</i>
Bibliographic record
Abstract
Abstract Collective cell movements contribute to tissue development and repair, and spread metastatic disease. In epithelia, cohesive cell movements require reorganization of adherens junctions and the actomyosin cytoskeleton. However, the mechanisms that coordinate cell-cell adhesion and cytoskeletal remodelling during collective cell migration in vivo are unclear. We investigated the mechanisms of collective cell migration during wound healing in the Drosophila embryonic epidermis. Upon wounding, the cells adjacent to the wound internalize cell-cell adhesion molecules and polarize actin and the motor protein myosin II to form a supracellular cable around the wound that coordinates cell movements. The cable anchors at former tricellular junctions (TCJs) along the wound edge, and TCJs are reinforced during wound closure. We found that the small GTPase Rap1 was both necessary and sufficient for rapid wound repair. Rap1 promoted actomyosin polarization to the wound edge and E-cadherin accumulation at TCJs. Using embryos expressing a mutant form of the Rap1 effector Canoe/Afadin that cannot bind Rap1, we found that Rap1 signals through Canoe for adherens junction remodelling, but not for actomyosin cable assembly. Rap1 was necessary and sufficient for RhoA/Rho1 activation at the wound edge. Consistent with this, the RhoGEF Ephexin localized to the wound edge in a Rap1-dependent manner, and Ephexin was necessary for myosin polarization and rapid wound repair, but not for E-cadherin redistribution. Together, our data show that Rap1 coordinates the molecular rearrangements that drive embryonic wound healing and independently drives actomyosin cable assembly through Ephexin-Rho1, and E-cadherin redistribution through Canoe, thus enabling rapid collective cell migration in vivo .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".