β‐arrestin‐biased ACKR3 Promotes Gαi:β‐arrestin Complex Formation
Bibliographic record
Abstract
Atypical chemokine receptor 3 (ACKR3)—previously known as CXC‐chemokine receptor 7 (CXCR7)—is involved in a wide range of physiological processes including angiogenesis, neuronal development, and tumorigenesis. As a β‐arrestin biased G protein‐coupled receptor (GPCR), ACKR3 recruits β‐arrestin, but lacks G protein activity. Work from our lab has demonstrated that Gαi and β‐arrestin can form complexes together downstream of receptor stimulation, even upon activation by β‐arrestin‐biased agonists. Therefore, we hypothesized that stimulation of β‐arrestin biased receptors such as ACKR3 also promote Gαi:β‐arrestin complex formation. Our early results indicated that Gαi and β‐arrestin 2 associate at ACKR3 when treated with the synthetic agonists WW36 and WW38. Here, we expanded our panel of ligands to include proenkephalin‐derived BAM22 and endogenous chemokine CXCL11 in addition to WW36 and WW38, and we sought to characterize the canonical behavior of ACKR3 and assess its capacity to similarly promote Gαi:β‐arrestin complex formation with endogenous ligands. Using TRUPATH as well as other bioluminescence resonance energy transfer (BRET)‐based assays, we show that all ligands did not activate Gαi, while they stimulated dose‐dependent β‐arrestin 2 recruitment to ACKR3 and internalization. This aligned with the expected behavior of a β‐arrestin‐biased GPCR. Furthermore, using split‐luciferase assays, we found that a Gαi:β‐arrestin 2 complex consistently formed in a dose‐dependent manner across all four distinct ligands. Further studies will be necessary to elucidate the mechanism of formation and functional significance of this Gαi:β‐arrestin 2 complex in ACKR3 signaling.
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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) | 0.002 | 0.001 |
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".