SUMOylation Regulates Insulin Exocytosis Downstream of Secretory Granule Docking in Rodents and Humans
Bibliographic record
Abstract
OBJECTIVE: The reversible attachment of small ubiquitin-like modifier (SUMO) proteins controls target localization and function. We examined an acute role for the SUMOylation pathway in downstream events mediating insulin secretion. RESEARCH DESIGN AND METHODS: We studied islets and β-cells from mice and human donors, as well as INS-1 832/13 cells. Insulin secretion, intracellular Ca(2+), and β-cell exocytosis were monitored after manipulation of the SUMOylation machinery. Granule localization was imaged by total internal reflection fluorescence and electron microscopy; immunoprecipitation and Western blotting were used to examine the soluble NSF attachment receptor (SNARE) complex formation and SUMO1 interaction with synaptotagmin VII. RESULTS: SUMO1 impairs glucose-stimulated insulin secretion by blunting the β-cell exocytotic response to Ca(2+). The effect of SUMO1 to impair insulin secretion and β-cell exocytosis is rapid and does not require altered gene expression or insulin content, is downstream of granule docking at the plasma membrane, and is dependent on SUMO-conjugation because the deSUMOylating enzyme, sentrin/SUMO-specific protease (SENP)-1, rescues exocytosis. SUMO1 coimmunoprecipitates with the Ca(2+) sensor synaptotagmin VII, and this is transiently lost upon glucose stimulation. SENP1 overexpression also disrupts the association of SUMO1 with synaptotagmin VII and mimics the effect of glucose to enhance exocytosis. Conversely, SENP1 knockdown impairs exocytosis at stimulatory glucose levels and blunts glucose-dependent insulin secretion from mouse and human islets. CONCLUSIONS: SUMOylation acutely regulates insulin secretion by the direct and reversible inhibition of β-cell exocytosis in response to intracellular Ca(2+) elevation. The SUMO protease, SENP1, is required for glucose-dependent insulin secretion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".