The clathrin adaptor AP-1 complex and Arf1 regulate planar cell polarity in vivo
Bibliographic record
Abstract
A key step in generating planar cell polarity (PCP) is the formation of restricted junctional domains containing Frizzled/Dishevelled/Diego (Fz/Dsh/Dgo) or Van Gogh/Prickle (Vang/Pk) complexes within the same cell, stabilized via Flamingo (Fmi) across cell membranes. Although models have been proposed for how these complexes acquire and maintain their polarized localization, the machinery involved in moving core PCP proteins around cells remains unknown. We describe the AP-1 adaptor complex and Arf1 as major regulators of PCP protein trafficking in vivo. AP-1 and Arf1 disruption affects the accumulation of Fz/Fmi and Vang/Fmi complexes in the proximo–distal axis, producing severe PCP phenotypes. Using novel tools, we demonstrate a direct and specific Arf1 involvement in Fz trafficking in vivo. Moreover, we uncover a conserved Arf1 PCP function in vertebrates. Our data support a model whereby the trafficking machinery plays an important part during PCP establishment, promoting formation of polarized PCP-core complexes in vivo. Planar cell polarity (PCP) is generated by the restricted localization of membrane-bound multiprotein complexes, but how they are trafficked to the correct location is unknown. Here, the authors show that the GTPase ARF1 and the AP-1 adaptor complex are major regulators of PCP protein trafficking 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 | 0.001 | 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".