Novel interactors and a role for supervillin in early cytokinesis
Bibliographic record
Abstract
Supervillin, the largest member of the villin/gelsolin/flightless family, is a peripheral membrane protein that regulates each step of cell motility, including cell spreading. Most known interactors bind within its amino (N)-terminus. We show here that the supervillin carboxy (C)-terminus can be modeled as supervillin-specific loops extending from gelsolin-like repeats plus a villin-like headpiece. We have identified 27 new candidate interactors from yeast two-hybrid screens. The interacting sequences from 12 of these proteins (BUB1, EPLIN/LIMA1, FLNA, HAX1, KIF14, KIFC3, MIF4GD/SLIP1, ODF2/Cenexin, RHAMM, STARD9/KIF16A, Tks5/SH3PXD2A, TNFAIP1) co-localize with and mis-localize EGFP-supervillin in mammalian cells, suggesting associations in vivo. Supervillin-interacting sequences within BUB1, FLNA, HAX1, and MIF4GD also mimic supervillin over-expression by inhibiting cell spreading. Most new interactors have known roles in supervillin-associated processes, e.g. cell motility, membrane trafficking, ERK signaling, and matrix invasion; three (KIF14, KIFC3, STARD9/KIF16A) have kinesin motor domains; and five (EPLIN, KIF14, BUB1, ODF2/cenexin, RHAMM) are important for cell division. GST fusions of the supervillin G2-G3 or G4-G6 repeats co-sediment KIF14 and EPLIN, respectively, consistent with a direct association. Supervillin depletion leads to increased numbers of bi- and multi-nucleated cells. Cytokinesis failure occurs predominately during early cytokinesis. Supervillin localizes with endogenous myosin II and EPLIN in the cleavage furrow, and overlaps with the oncogenic kinesin, KIF14, at the midbody. We conclude that supervillin, like its interactors, is important for efficient cytokinesis. Our results also suggest that supervillin and its interaction partners coordinate actin and microtubule motor functions throughout the cell cycle.
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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".