Plasticity in the glucagon interactome reveals novel proteins that regulate glucagon secretion in αTC1-6 cells
Bibliographic record
Abstract
Abstract Glucagon is stored within secretory granules of pancreatic alpha cells until a stimulus, such as a change in microenvironmental conditions, triggers its release. We hypothesized that the secretory response of the alpha cell to various stimuli could be determined by plasticity in the network of proteins that interact with glucagon within alpha cell secretory granules. To answer this question, we isolated secretory granules from alpha TC1-6 cells and identified glucagon-interacting proteins by affinity purification coupled with liquid chromatography/tandem mass spectrometry. Proteomic analyses revealed a network of cytoplasmic and histone proteins. Specifically, the interaction between glucagon and histone H4 and the ER stress protein GRP78 was confirmed through co-immunoprecipitation of secretory granule lysates, and co-localization within secretory granules using high-resolution confocal microscopy. The composition of these networks was altered at different glucose levels (25 mM vs 5.5 mM) and in response to the paracrine inhibitors of glucagon secretion, GABA and insulin. Finally, siRNA-mediated silencing of a subset of nonhistone proteins revealed novel proteins that may regulate glucagon secretion. We have therefore described a novel and dynamic glucagon interactome within alpha cell secretory granules, and suggest that plasticity in the interactome governs the alpha cell secretory response to paracrine and nutritional stimuli.
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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".