Dynein-mediated trafficking negatively regulates LET-23 EGFR signaling
Bibliographic record
Abstract
Epidermal Growth Factor Receptor (EGFR) signaling is essential for animal development and increased signaling underlies many human cancers. Identifying the genes and cellular processes that regulate EGFR signaling in vivo will help elucidate how this pathway can become inappropriately activated. Caenorhabditis elegans vulva development provides an in vivo model to genetically dissect EGFR signaling. Here we identified a mutation in dhc-1, the heavy chain of the cytoplasmic dynein minus-end directed microtubule motor, in a genetic screen for regulators of EGFR signaling. Despite the many cellular functions of dynein, DHC-1 is a strong negative regulator of EGFR signaling during vulva induction. DHC-1 is required in the signal-receiving cell, genetically functions upstream or in parallel to LET-23 EGFR. LET-23 EGFR accumulates in cytoplasmic foci in dhc-1 mutants consistent with mammalian cell studies whereby dynein has been shown to regulate late endosome trafficking of EGFR with the Rab7 GTPase. However, we found different distributions of LET-23 EGFR foci in rab-7 versus dhc-1 mutants, suggesting that dynein functions at an earlier step of LET-23 EGFR trafficking to the lysosome than RAB-7. Our results demonstrate an in vivo role for dynein in limiting LET-23 EGFR signaling via endosomal trafficking.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".