Regulation of GPR54 Signaling by GRK2 and β-Arrestin
Bibliographic record
Abstract
Kisspeptin and its receptor, GPR54, are major regulators of the hypothalamic-pituitary-gonadal axis as well as regulators of human placentation and tumor metastases. GPR54 is a G(q/11)-coupled G protein-coupled receptor (GPCR), and activation by kisspeptin stimulates phosphatidy linositol 4, 5-biphosphate hydrolysis, Ca(2+) mobilization, arachidonic acid release, and ERK1/2 MAPK phosphorylation. Physiological evidence suggests that GPR54 undergoes agonist-dependent desensitization, but underlying molecular mechanisms are unknown. Furthermore, very little has been reported on the early events that regulate GPR54 signaling. The lack of information in these important areas led to this study. Here we report for the first time on the role of GPCR serine/threonine kinase (GRK)2 and beta-arrestin in regulating GPR54 signaling in human embryonic kidney (HEK) 293 cells, a model cell system for studying the molecular regulation of GPCRs, and genetically modified MDA MB-231 cells, an invasive breast cancer cell line expressing about 75% less beta-arrestin-2 than the control cell line. Our study reveals that in HEK 293 cells, GPR54 is expressed both at the plasma membrane and intracellularly and also that plasma membrane expression is regulated by cytoplasmic tail sequences. We also demonstrate that GPR54 exhibits constitutive activity, internalization, and association with GRK2 and beta- arrestins-1 and 2 through sequences in the second intracellular loop and cytoplasmic tail of the receptor. We also show that GRK2 stimulates the desensitization of GPR54 in HEK 293 cells and that beta-arrestin-2 mediates GPR54 activation of ERK1/2 in MDA-MB-231 cells. The significance of these findings in developing molecular-based therapies for treating certain endocrine-related disorders is discussed.
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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 | 0.000 |
| 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".