Coupling of Human Rhodopsin to a Yeast Signaling Pathway Enables Characterization of Mutations Associated with Retinal Disease
Bibliographic record
Abstract
G protein-coupled receptors (GPCRs) are crucial sensors of extracellular signals in eukaryotes, with multiple GPCR mutations linked to human diseases. With the growing number of sequenced human genomes, determining the pathogenicity of a mutation is challenging, but can be aided by a direct measurement of GPCR-mediated signaling. This is particularly difficult for the visual pigment rhodopsin-a GPCR activated by light-for which hundreds of mutations have been linked to inherited degenerative retinal diseases such as retinitis pigmentosa. In this study, we successfully engineered, for the first time, activation by human rhodopsin of the yeast mating pathway, resulting in signaling via a fluorescent reporter. We combine this novel assay for rhodopsin light-dependent activation with studies of subcellular localization, and the upregulation of the unfolded protein response in response to misfolded rhodopsin protein. We use these assays to characterize a panel of rhodopsin mutations with known molecular phenotypes, finding that rhodopsin maintains a similar molecular phenotype in yeast, with some interesting differences. Furthermore, we compare our assays in yeast with clinical phenotypes from patients with novel disease-linked mutations. We demonstrate that our engineered yeast strain can be useful in rhodopsin mutant classification, and in helping to determine the molecular mechanisms underlying their pathogenicity. This approach may also be applied to better understand the clinical relevance of other human GPCR mutations, furthering the use of yeast as a tool for investigating molecular mechanisms relevant to human disease.
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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) | 0.001 | 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".