A role for PKD1 in insulin secretion downstream of P2Y <sub>1</sub> receptor activation in mouse and human islets
Bibliographic record
Abstract
Along with insulin, β-cells co-secrete the neurotransmitter ATP which acts as a positive autocrine signal via P2Y1 receptors to activate phospholipase C and increase the production of diacylglycerol (DAG). However, the downstream signaling that couples P2Y1 activation to insulin secretion remains to be fully elucidated. Since DAG activates protein kinase D1 (PKD1) to potentiate glucose-stimulated insulin release, we hypothesized that autocrine ATP signaling activates downstream PKD1 to regulate insulin secretion. Indeed, we find that the P2Y1 receptor agonists, MRS2365 and ATP induce, PKD1 phosphorylation at serine 916 in mouse islets. Similarly, direct depolarization of islets by KCl caused PKD1 activation, which is reduced upon P2Y1 antagonism. Potentiation of insulin secretion by P2Y1 activation was lost from PKD1−/− mouse islets, and knockdown of PKD1 reduced the ability of P2Y1 activation to facilitate exocytosis in single mouse β-cells. Finally, qPCR analysis confirmed PKD1 transcript (PRKD1) expression in human islets, and insulin secretion assays showed that inhibition of either P2Y1 or PKD1 signaling impaired glucose-stimulated insulin secretion. Human islets showed donor-to-donor variation in their responses to both P2Y1 and PKD1 inhibition, however, and we find that the P2Y1-PKD1 pathway contributes a substantially greater proportion of insulin secretion from islets of overweight and obese donors. Thus, PKD1 promotes increased insulin secretion, likely mediating an autocrine ATP effect via P2Y1 receptor activation which may be more important in islets of donors who are overweight or obese.
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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".