The Dynamic regulation of ßarrestin trafficking in endosomes
Bibliographic record
Abstract
ßarrestins bind agonist‐activated G protein‐coupled receptors (GPCRs) to mediate their desensitization and internalization, and to regulate the rate at which receptors resensitize. GPCRs exhibit different patterns of agonist‐induced ßarrestin interaction. Some receptors dissociate from ßarrestin, at or near the plasma membrane and recycle faster than those which are trafficking in endosomes with ßarrestin. It is unknown however what controls the dissociation of ßarrestin from receptors. We have previously reported that the bradykinin type 2 receptor (B2R) forms a stable complex with ßarrestin in endosomes and recycles rapidly to the plasma membrane despite its high avidity to ßarrestin. Here we show using FRET and FRAP approaches that although ßarrestin2 interacts with B2R in endosomes, it dissociated rapidly from the receptors. Although both B2R and the Angiotensin II type 1 receptor (AT1R) internalize with ßarrestin in endosomes, the rate of ßarrestin2 dissociation was faster for B2R than for AT1R. We also tested the effect of a ßarrestin2 mutant, which has an increased avidity for B2R, and showed that it dissociated slower from the receptor than wild‐type. Finally we demonstrate that ERK2 signaling in endosomes is important in regulating the ßarrestin2/B2R complex. These experiments give new insight about the mechanisms regulating receptor trafficking, which impact receptor recycling and resensitization.
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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 | 0.001 | 0.001 |
| 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".