Biased Signaling Favoring Gi over β-Arrestin Promoted by an Apelin Fragment Lacking the C-terminal Phenylalanine
Bibliographic record
Abstract
Apelin plays a prominent role in body fluid and cardiovascular homeostasis. We previously showed that the C-terminal Phe of apelin 17 (K17F) is crucial for triggering apelin receptor internalization and decreasing blood pressure (BP) but is not required for apelin binding or Gi protein coupling. Based on these findings, we hypothesized that the important role of the C-terminal Phe in BP decrease may be as a Gi-independent but β-arrestin-dependent signaling pathway that could involve MAPKs. For this purpose, we have used apelin fragments K17F and K16P (K17F with the C-terminal Phe deleted), which exhibit opposite profiles on apelin receptor internalization and BP. Using BRET-based biosensors, we showed that whereas K17F activates Gi and promotes β-arrestin recruitment to the receptor, K16P had a much reduced ability to promote β-arrestin recruitment while maintaining its Gi activating property, revealing the biased agonist character of K16P. We further show that both β-arrestin recruitment and apelin receptor internalization contribute to the K17F-stimulated ERK1/2 activity, whereas the K16P-promoted ERK1/2 activity is entirely Gi-dependent. In addition to providing new insights on the structural basis underlying the functional selectivity of apelin peptides, our study indicates that the β-arrestin-dependent ERK1/2 activation and not the Gi-dependent signaling may participate in K17F-induced BP decrease.
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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".