SUMOylation regulates Kv2.1 and modulates pancreatic β-cell excitability
Bibliographic record
Abstract
The covalent attachment of small ubiquitin-like modifier (SUMO) proteins regulates protein localization and function. SUMOylation has recently been shown to modulate ion-channel function; however, the extent to which this affects native currents and cellular excitability remains to be determined. The voltage-dependent K(+) (Kv) channel Kv2.1 regulates pancreatic beta-cell excitability and insulin secretion. We found that YFP-tagged SUMO1 (SUMO1-YFP) can be immunoprecipitated with Kv2.1 when these two proteins are coexpressed in HEK 293 cells. Furthermore, direct infusion of recombinant SUMO1 peptide or coexpression of SUMO1-YFP inhibited current through cloned Kv2.1 by 80% and 48%, respectively. Insulin-secreting cells express SUMO variants 1 and 3, and expression of the SUMO1-YFP in human beta-cells or insulinoma cells inhibited native Kv currents (by 49% and 33%, respectively). Inhibition of the channel resulted from an acceleration of channel inactivation and an inhibition of recovery from inactivation, resulting in the widening of beta-cell action potentials and a decreased firing frequency. Finally, these effects on channel function and excitability were augmented by the conjugating enzyme Ubc9 and rescued by the SUMO protease SENP1. Thus, protein SUMOylation can exert a strong inhibitory action on the voltage-dependent K(+) channel Kv2.1 and can regulate cellular excitability in native beta-cells.
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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".