Insulin Granule Recruitment and Exocytosis Is Dependent on p110γ in Insulinoma and Human β-Cells
Bibliographic record
Abstract
OBJECTIVE: Phosphatidylinositol 3-OH kinase (PI3K) has a long-recognized role in beta-cell mass regulation and gene transcription and is implicated in the modulation of insulin secretion. The role of nontyrosine kinase receptor-activated PI3K isoforms is largely unexplored. We therefore investigated the role of the G-protein-coupled PI3Kgamma and its catalytic subunit p110gamma in the regulation of insulin granule recruitment and exocytosis. RESEARCH DESIGN AND METHODS: The expression of p110gamma was knocked down by small-interfering RNA, and p110gamma activity was selectively inhibited with AS605240 (40 nmol/l). Exocytosis and granule recruitment was monitored by islet perifusion, whole-cell capacitance, total internal reflection fluorescence microscopy, and electron microscopy in INS-1 and human beta-cells. Cortical F-actin was examined in INS-1 cells and human islets and in mouse beta-cells lacking the phosphatase and tensin homolog (PTEN). RESULTS: Knockdown or inhibition of p110gamma markedly blunted depolarization-induced insulin secretion and exocytosis and ablated the exocytotic response to direct Ca(2+) infusion. This resulted from reduced granule localization to the plasma membrane and was associated with increased cortical F-actin. Inhibition of p110gamma had no effect on F-actin in beta-cells lacking PTEN. Finally, the effect of p110gamma inhibition on granule localization and exocytosis could be rapidly reversed by agents that promote actin depolymerization. CONCLUSIONS: The G-protein-coupled PI3Kgamma is an important determinant of secretory granule trafficking to the plasma membrane, at least in part through the negative regulation of cortical F-actin. Thus, p110gamma activity plays an important role in maintaining a membrane-docked, readily releasable pool of secretory granules in insulinoma and human beta-cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".