Proteomic and biochemical comparison of the cellular interaction partners of human VPS33A and VPS33B
Bibliographic record
Abstract
ABSTRACT Multi-subunit tethering complexes control membrane fusion events in eukaryotic cells. CORVET and HOPS are two such multi-subunit tethering complexes, both containing the Sec1/Munc18 protein subunit VPS33A. Metazoans additionally possess VPS33B, which has considerable sequence similarity to VPS33A but does not integrate into CORVET or HOPS complexes and instead stably interacts with VIPAR. It has been recently suggested that VPS33B and VIPAR comprise two subunits of a novel multi-subunit tethering complex (named ‘CHEVI’), analogous in configuration to CORVET and HOPS. We utilised the BioID proximity biotinylation assay to compare and contrast the interactomes of VPS33A and VPS33B. Overall, few proteins were identified as associating with both VPS33A and VPS33B, suggesting these proteins have distinct sub-cellular localisations. Consistent with previous reports, we observed that VPS33A was co-localised with many components of class III phosphatidylinositol 3-kinase (PI3KC3) complexes: PIK3C3, PIK3R4, NRBF2, UVRAG and RUBICON. Although in this assay VPS33A clearly co-localised with several subunits of CORVET and HOPS, no proteins with the canonical CORVET/HOPS domain architecture were found to co-localise with VPS33B. Instead, we identified two novel VPS33B-interacting proteins, VPS53 and CCDC22. CCDC22 co-immunoprecipitated with VPS33B and VIPAR in over-expression conditions and interacts directly with the VPS33B-VIPAR complex in vitro. However, CCDC22 does not appear to co-fractionate with VPS33B and VIPAR in gel filtration of human cell lysates. We also observed that the protein complex in HEK293T cells which contained VPS33B and VIPAR was considerably smaller than CORVET/HOPS, suggesting that, unlike VPS33A, VPS33B does not assemble into a large stable multi-subunit tethering complex.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".