Progesterone Receptor Membrane Component 1 Is a Functional Part of the Glucagon-like Peptide-1 (GLP-1) Receptor Complex in Pancreatic β Cells
Bibliographic record
Abstract
Glucagon-like peptide-1 (GLP-1) is an incretin hormone that regulates glucose homeostasis. Because of their direct stimulation of insulin secretion from pancreatic β cells, GLP-1 receptor (GLP-1R) agonists are now important therapeutic options for the treatment of type 2 diabetes. To better understand the mechanisms that control the insulinotropic actions of GLP-1, affinity purification and mass spectrometry (AP-MS) were employed to uncover potential proteins that functionally interact with the GLP-1R. AP-MS performed on Chinese hamster ovary cells or MIN6 β cells, both expressing the human GLP-1R, revealed 99 proteins potentially associated with the GLP-1R. Three novel GLP-1R interactors (PGRMC1, Rab5b, and Rab5c) were further validated through co-immunoprecipitation/immunoblotting, fluorescence resonance energy transfer, and immunofluorescence. Functional studies revealed that overexpression of PGRMC1, a novel cell surface receptor that associated with liganded GLP-1R, enhanced GLP-1-induced insulin secretion (GIIS) with the most robust effect. Knockdown of PGRMC1 in β cells decreased GIIS, indicative of positive interaction with GLP-1R. To gain insight mechanistically, we demonstrated that the cell surface PGRMC1 ligand P4-BSA increased GIIS, whereas its antagonist AG-205 decreased GIIS. It was then found that PGRMC1 increased GLP-1-induced cAMP accumulation. PGRMC1 activation and GIIS induced by P4-BSA could be blocked by inhibition of adenylyl cyclase/EPAC signaling or the EGF receptor-PI3K signal transduction pathway. These data reveal a dual mechanism for PGRMC1-increased GIIS mediated through cAMP and EGF receptor signaling. In conclusion, we identified several novel GLP-1R interacting proteins. PGRMC1 expressed on the cell surface of β cells was shown to interact with the activated GLP-1R to enhance the insulinotropic actions of GLP-1.
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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) | 0.001 | 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) | 0.001 | 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 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".