Munc18c mediates exocytosis of pre-docked and newcomer insulin granules underlying biphasic glucose stimulated insulin secretion in human pancreatic beta-cells
Bibliographic record
Abstract
OBJECTIVE: Pancreatic beta-cells express three Munc18 isoforms. Much is known about the roles of Munc18a (pre-docked secretory granules-SGs) and Munc18b (newcomer SGs and SG-SG fusion) in insulin exocytosis. Although shown to influence glucose-stimulated insulin secretion (GSIS) in rodents the precise role of Munc18c in insulin SG exocytosis has not been elucidated. We here examined the role of Munc18c in human pancreatic beta-cells. METHODS: Munc18c-shRNA/RFP lenti-virus (versus control virus) was used to knock down the expression level of Munc18c in human islets or single beta-cells. Insulin secretion and granule exocytosis were measured by performing islets perifusion, single-cell patch clamp capacitance measurements and total internal reflection fluorescence microscopy (TIRFM). RESULTS: Munc18c is most abundant in the cytosol of human beta-cells. Endogenous function of Munc18c was assessed by knocking down (KD) its islet expression by 70% employing lenti-shRNA virus. Munc18c-KD caused reduction in cognate syntaxin-4 islet expression but not in other exocytotic proteins, resulting in the reduction in GSIS in first- (by 42%) and second phases (by 35%). Single cell analyses of RFP-tagged Munc18c-KD beta-cells by patch clamp capacitance measurements showed inhibition in both readily-releasable pool (by 52%) and mobilization from the reserve pool (by 57%). TIRFM to assess single SG behavior showed that Munc18c-KD inhibition of first phase GSIS was attributed to reduction in exocytosis of pre-docked and newcomer SGs, and second phase inhibition attributed entirely to reduction in newcomer SG fusion (SGs that undergo minimal residence or docking time at the plasma membrane before fusion). CONCLUSION: Munc18c is involved in the distinct molecular machineries that affect exocytosis of both predocked and newcomer SG pools that underlie Munc18c's role in first and second phases of GSIS, respectively.
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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".