A Targeted RNAi Screen Identifies Endocytic Trafficking Factors That Control GLP-1 Receptor Signaling in Pancreatic β-Cells
Bibliographic record
Abstract
The glucagon-like peptide 1 (GLP-1) receptor (GLP-1R) is a key target for type 2 diabetes (T2D) treatment. Because endocytic trafficking of agonist-bound receptors is one of the most important routes for regulation of receptor signaling, a better understanding of this process may facilitate the development of new T2D therapeutic strategies. Here, we screened 29 proteins with known functions in G protein-coupled receptor trafficking for their role in GLP-1R potentiation of insulin secretion in pancreatic β-cells. We identify five (clathrin, dynamin1, AP2, sorting nexins [SNX] SNX27, and SNX1) that increase and four (huntingtin-interacting protein 1 [HIP1], HIP14, GASP-1, and Nedd4) that decrease insulin secretion from murine insulinoma MIN6B1 cells in response to the GLP-1 analog exendin-4. The roles of HIP1 and the endosomal SNX1 and SNX27 were further characterized in mouse and human β-cell lines and human islets. While HIP1 was required for the coupling of cell surface GLP-1R activation with clathrin-dependent endocytosis, the SNXs were found to control the balance between GLP-1R plasma membrane recycling and lysosomal degradation and, in doing so, determine the overall β-cell incretin responses. We thus identify key modulators of GLP-1R trafficking and signaling that might provide novel targets to enhance insulin secretion in T2D.
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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 | 0.001 |
| 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".