Combining resonance energy transfer methods reveals a complex between the α <sub>2A</sub> ‐adrenergic receptor, Gα <sub>i1</sub> β <sub>1</sub> γ <sub>2</sub> , and GRK2
Bibliographic record
Abstract
ABSTRACT Traditionally, G‐protein‐coupled receptor (GPCR) interactions with their G proteins and regulatory proteins, GPCR kinases (GRKs) and ar‐restins, are described as sequential events involving rapid assemblies/disassemblies. To directly monitor the dynamics of these interactions in living cells, we combined two spectrally resolved bioluminescence and one fluorescence resonance energy transfer (RET) methods. The RET combination analysis revealed that stimulation of the α 2A ‐adrenergic receptor (α 2A AR) leads to the recruitment of GRK2 at a receptor still associated with the Gα i1 β 1 γ 2 complex. The interaction kinetics of GRKs with Gγ 2 (2.8±0.4 s) and α 2A AR (5.2±0.5 s) were similar to that of the receptor‐promoted change in RET between Gα i1 and Gγ 2 (5.2±1.2 s), and persisted until the translocation of βarrestin2 to the receptor, indicating that GRK2 remains associated to the receptor/G‐protein complex for longer periods than anticipated. Moreover, GRK2 or a kinase‐deficient GRK2 mutant, but not GRK5, potentiated the receptor‐promoted changes in RET between Gα i1 and Gγ 2 and abrogated the α 2A AR‐stimulated calcium response, suggesting that the recruitment of GRK2 to the complex contributes to the structural rearrangement and functional regulation of the signaling unit, independently of the kinase activity. RET combination analysis revealed unanticipated dynamics in GPCR signaling and will be applicable to many biological systems.—Breton, B., Lagace, M., Bouvier, M. Combining resonance energy transfer methods reveals a complex between the α 2A ‐adrenergic receptor, Gα i1 β 1 γ 2 , and GRK2. FASEBJ. 24, 4733–4743 (2010). www.fasebj.org
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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".