Photoactivation-Induced Instability of Rhodopsin Mutants T4K and T17M in Rod Outer Segments Underlies Retinal Degeneration in<i>X. laevis</i>Transgenic Models of Retinitis Pigmentosa
Bibliographic record
Abstract
Retinitis pigmentosa (RP) is an inherited neurodegenerative disease involving progressive vision loss, and is often linked to mutations in the rhodopsin gene. Mutations that abolish N-terminal glycosylation of rhodopsin (T4K and T17M) cause sector RP in which the inferior retina preferentially degenerates, possibly due to greater light exposure of this region. Transgenic animal models expressing rhodopsin glycosylation mutants also exhibit light exacerbated retinal degeneration (RD). In this study, we used transgenic Xenopus laevis to investigate the pathogenic mechanism connecting light exposure and RD in photoreceptors expressing T4K or T17M rhodopsin. We demonstrate that increasing the thermal stability of these rhodopsins via a novel disulfide bond resulted in significantly less RD. Furthermore, T4K or T17M rhodopsins that were constitutively inactive (due to lack of the chromophore-binding site or dietary deprivation of the chromophore precursor vitamin A) induced less toxicity. In contrast, variants in the active conformation accumulated in the ER and caused RD even in the absence of light. In vitro, T4K and T17M rhodopsins showed reduced ability to regenerate pigment after light exposure. Finally, although multiple amino acid substitutions of T4 abolished glycosylation at N2 but were not toxic, similar substitutions of T17 were not tolerated, suggesting that the carbohydrate moiety at N15 is critical for cell viability. Our results identify a novel pathogenic mechanism in which the glycosylation-deficient rhodopsins are destabilized by light activation. These results have important implications for proposed RP therapies, such as vitamin A supplementation, which may be ineffective or even detrimental for certain RP genotypes.
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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 | 0.001 |
| 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".