UIM domain-dependent recruitment of the endocytic adaptor protein Eps15 to ubiquitin-enriched endosomes
Bibliographic record
Abstract
BACKGROUND: Eps15 is an endocytic adaptor protein that stimulates clathrin-mediated endocytosis. Among other interactions, Eps15 binds ubiquitin via UIM domains, recruiting ubiquitinated cargo into clathrin-coated vesicles. In EGF-treated cells, Eps15 also localizes to endosomes. The basis of this localization is not known. RESULTS: We show that accumulation of ubiquitinated cargo can recruit Eps15 to endosomes via UIM domain interactions. First, treatment of SK-Br-3 breast cancer cells, which overexpress the EGFR family member ErbB2, with geldanamycin to promote receptor ubiquitination and endosomal transport, recruited FLAG-Eps15 to endosomes. Two in-frame ubiquitin constructs, PM-GFP-Ub (retained in endosomes after endocytosis), and GFP-FYVE-UbΔGG (targeted directly to endosomes) also recruited Eps15 to endosomes, as did slowing endosome maturation with constitutively-active Rab5-Q79L. Endosomal recruitment required the UIM domains, but not the N-terminal EH domains or central coiled-coil domains, of Eps15. Silencing of the endosomal Eps15 binding partner Hrs did not affect recruitment of Eps15 to ubiquitin-enriched endosomes. In fact, Hrs silencing itself modestly recruited Eps15 to endosomes, probably by accumulating endogenous ubiquitinated cargo. Eps15 silencing did not affect lysosomal degradation of ubiquitinated ErbB2; however, GFP-FYVE-UbΔGG overexpression inhibited internalization of EGFR and transferrin receptor. CONCLUSIONS: We show for the first time that ubiquitin is sufficient for Eps15 recruitment to endosomes. We speculate that Eps15 recruitment to ubiquitin-rich endosomes may reduce the level of Eps15 at the plasma membrane, slowing endocytosis to allow time for processing of ubiquitinated cargo in endosomes.
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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 | 0.001 |
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".