<scp>RalA GTPase</scp> Tethers Insulin Granules to L‐ and R‐Type Calcium Channels Through Binding α<sub>2</sub>δ‐1 Subunit
Bibliographic record
Abstract
RalA GTPase has been implicated in the regulated delivery of exocytotic vesicles to the plasma membrane (PM) in mammalian cells. We had reported that RalA regulates biphasic insulin secretion, which we have now determined to be contributed by RalA direct interaction with voltage-gated calcium (Cav ) channels. RalA knockdown (KD) in INS-1 cells and primary rat β-cells resulted in a reduction in Ca(2+) currents arising specifically from L-(Cav 1.2 and Cav 1.3) and R-type (Cav 2.3) Ca(2+) channels. Restoration of RalA expression in RalA KD cells rescued these defects in Ca(2+) currents. RalA co-immunoprecipitated with the Cav α2 δ-1 auxiliary subunit known to bind the three Cav s. Moreover, the functional molecular interactions between Cav α2 δ-1 and RalA on the PM shown by total internal reflection fluorescent microscopy/FRET analysis could be induced by glucose stimulation. KD of RalA inhibited trafficking of α2 δ-1 to insulin granules without affecting the localization of the other Cav subunits. Furthermore, we confirmed that RalA and α2 δ-1 functionally interact since RalA KD-induced inhibition of Cav currents could not be recovered by RalA when α2 δ-1 was simultaneously knocked down. These data provide a mechanism for RalA function in insulin secretion, whereby RalA binds α2 δ-1 on insulin granules to tether these granules to PM Ca(2+) channels. This acts as a chaperoning step prior to and in preparation for sequential assembly of exocyst and excitosome complexes that mediate biphasic 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 | 0.001 |
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".