Expression of mini-G proteins specifically halt cognate GPCR trafficking and intracellular signalling
Bibliographic record
Abstract
Abstract Mini-G proteins are engineered thermostable variants of Gα subunits designed to specifically stabilise G protein-coupled receptors (GPCRs) in their active conformation for structural analyses. Due to their smaller size and ease of use, they have become popular tools in recent years to assess specific GPCR behaviours in cells, both as reporters of receptor coupling to each G protein subtype and for in-cell assays designed to quantify compartmentalised receptor signalling from a range of subcellular locations. Here, we describe a previously unappreciated consequence of the co-expression of mini-G proteins with their cognate GPCRs, namely a profound disruption in GPCR trafficking and intracellular signalling caused by the co-expression of the specific mini-G subtype coupled to the affected receptor. We studied the Gαs-coupled pancreatic beta cell class B GPCR glucagon-like peptide-1 receptor (GLP-1R) as a model to describe in detail the molecular consequences derived from this effect, including a complete halt in β-arrestin-2 recruitment and receptor internalisation, despite near-normal levels of receptor GRK2 recruitment and lipid nanodomain segregation, as well as the disruption of endosomal GLP-1R signalling by mini-G s co-expression. We also extend our analysis to a range of other prototypical GPCRs covering the spectrum of Gα subtype coupling preferences, to unveil a widely conserved phenomenon of GPCR internalisation blockage by specific mini-G proteins coupled to a particular receptor. Our results have important implications for the design of methods to assess intracellular GPCR signalling. We also present an alternative adapted bystander intracellular signalling assay for the GLP-1R in which we substitute the mini-G s by a nanobody, Nb37, with specificity for active Gαs:GPCR complexes and no deleterious effect on the capacity for GLP-1R internalisation.
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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) | 0.000 | 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 | 0.001 |
| 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 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".