Regulation of Insulin Exocytosis by Munc13-1
Bibliographic record
Abstract
The slower kinetics of insulin release from pancreatic islet beta cells, as compared with other regulated secretory processes such as chromaffin granule secretion, can in part be explained by the small number of the insulin granules that are docked to the plasma membrane and readily releasable. In type-2 diabetes, the kinetics of insulin secretion become grossly distorted, and, to therapeutically correct this, it is imperative to elucidate the mechanisms that regulate priming and secretion of insulin secretory granules. Munc13-1, a synaptic protein that regulates SNARE complex assembly, is the major protein determining the priming of synaptic vesicles. Here, we demonstrate the presence of Munc13-1 in human, rat, and mouse pancreatic islet beta cells. Expression of Munc13-1, along with its cognate partners, syntaxin 1a and Munc18a, is reduced in the pancreatic islets of type-2 diabetes non-obese Goto-Kakizaki and obese Zucker fa/fa rats. In insulinoma cells, overexpressed Munc13-1-enhanced green fluorescent protein is translocated to the plasma membrane in a temperature-dependent manner. This, in turn, greatly amplifies insulin exocytosis as determined by patch clamp capacitance measurements and radioimmunoassay of the insulin released. The potentiation of exocytosis by Munc13-1 is dependent on endogenously produced diacylglycerol acting on the overexpressed Munc13-1 because it is blocked by a phospholipase C inhibitor (U73122) and abrogated when the diacylglycerol binding-deficient Munc13-1H567K mutant is expressed instead of the wild type protein. Our data demonstrate that Munc13-mediated vesicle priming is not restricted to neurotransmitter release but is also functional in insulin secretion, where it is subject to regulation by the diacylglycerol second messenger pathway. In view of our findings, Munc13-1 is a potential drug target for therapeutic optimization of insulin secretion in diabetes.
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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".