Syntaxin-3 Binds and Regulates Both R- and L-Type Calcium Channels in Insulin-Secreting INS-1 832/13 Cells
Bibliographic record
Abstract
Syntaxin (Syn)-1A mediates exocytosis of predocked insulin-containing secretory granules (SGs) during first-phase glucose-stimulated insulin secretion (GSIS) in part via its interaction with plasma membrane (PM)-bound L-type voltage-gated calcium channels (Cav). In contrast, Syn-3 mediates exocytosis of newcomer SGs that accounts for second-phase GSIS. We now hypothesize that the newcomer SG Syn-3 preferentially binds and modulates R-type Cav opening, which was postulated to mediate second-phase GSIS. Indeed, glucose-stimulation of pancreatic islet β-cell line INS-1 induced a predominant increase in interaction between Syn-3 and Cavα1 pore-forming subunits of R-type Cav2.3 and to lesser extent L-type Cavs, while confirming the preferential interactions between Syn-1A with L-type (Cav1.2, Cav1.3) Cavs. Consistently, direct binding studies employing heterologous HEK cells confirmed that Syn-3 preferentially binds Cav2.3, whereas Syn-1A prefers L-type Cavs. We then used siRNA knockdown (KD) of Syn-3 in INS-1 to study the endogenous modulatory actions of Syn-3 on Cav channels. Syn-3 KD enhanced Ca2+ currents by 46% attributed mostly to R- and L-type Cavs. Interestingly, while the transmembrane domain of Syn-1A is the putative functional domain modulating Cav activity, it is the cytoplasmic domain of Syn-3 that appears to modulate Cav activity. We conclude that Syn-3 may mimic Syn-1A in the ability to bind and modulate Cavs, but preferring Cav2.3 to perhaps participate in triggering fusion of newcomer insulin SGs during second-phase GSIS.
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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 | 0.001 |
| 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".