Glycerol-3-phosphate phosphatase operates a glycerol shunt in pancreatic β-cells that controls insulin secretion and metabolic stress
Bibliographic record
Abstract
The recently identified glycerol-3-phosphate (Gro3P) phosphatase (G3PP) in mammalian cells, encoded by the PGP gene, was shown to regulate glucose, lipid and energy metabolism by hydrolyzing Gro3P and to control glucose-stimulated insulin secretion (GSIS) in β-cells, in vitro. However, whether G3PP regulates β-cell function and insulin secretion in vivo is not known. We now examined the role of G3PP in the control of insulin secretion in vivo, β-cell function and glucotoxicity in inducible β-cell specific G3PP-KO (BKO) mice. Inducible BKO mice were generated by crossing floxed-G3PP mice with Mip-Cre-ERT (MCre) mice. All the in vivo studies were done using BKO and control mice fed normal diet and the ex vivo studies were done using pancreatic islets from these mice. BKO mice, compared to MCre controls, showed increased body weight, adiposity, fed insulinemia, enhanced in vivo GSIS, reduced plasma triglycerides and mild glucose intolerance. Isolated BKO mouse islets incubated at high (16.7 mM), but not at low or intermediate glucose (3 and 8 mM), showed elevated GSIS, Gro3P content as well as increased levels of metabolites and signaling coupling factors known to reflect β-cell activation for insulin secretion. BKO islets also showed reduced glycerol release and increased O2 consumption and ATP production at high glucose only. BKO islets chronically exposed to elevated glucose levels showed increased apoptosis, reduced insulin content and decreased mRNA expression of β-cell differentiation markers, Pdx-1, MafA and Ins-2. The results demonstrate that β-cells are endowed with a “glycerol shunt”, operated by G3PP that regulates β-cell metabolism, signaling and insulin secretion in vivo, primarily at elevated glucose concentrations. We propose that the glycerol shunt plays a role in preventing insulin hypersecretion and excess body weight gain and contributes to β-cell mass preservation in the face of hyperglycemia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".