The Clavesin Family, Neuron-specific Lipid- and Clathrin-binding Sec14 Proteins Regulating Lysosomal Morphology
Bibliographic record
Abstract
Clathrin-coated vesicles (CCVs) originating from the trans-Golgi network (TGN) provide a major transport pathway from the secretory system to endosomes/lysosomes. Herein we describe paralogous Sec14 domain-bearing proteins, clavesin 1/CRALBPL and clavesin 2, identified through a proteomic analysis of CCVs. Clavesins are enriched on CCVs and form a complex with clathrin heavy chain (CHC) and adaptor protein-1, major coat components of TGN-derived CCVs. The proteins co-localize with markers of endosomes and the TGN as well as with CHC and adaptor protein-1. A membrane mimic assay using the Sec14 domain of clavesin 1 reveals phosphatidylinositol 3,5-bisphosphate as a specific lipid partner. Phosphatidylinositol 3,5-bisphosphate is localized to late endosomes/lysosomes, and interestingly, isoform-specific knockdown of clavesins in neurons using lentiviral delivery of interfering RNA leads to enlargement of a lysosome-associated membrane protein 1-positive membrane compartment with no obvious influence on the CCV machinery at the TGN. Since clavesins are expressed exclusively in neurons, this new protein family appears to provide a unique neuron-specific regulation of late endosome/lysosome morphology.
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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".