Reovirus μ2 Protein Impairs Translation to Reduce U5 snRNP Protein Levels
Bibliographic record
Abstract
family that infects a large range of mammals, including humans. Recently, studies have shown that MRV alters cellular alternative splicing (AS) during viral infection. The structural protein μ2 appears to be the main determinant of these AS modifications by decreasing the levels of U5 core components EFTUD2, PRPF8, and SNRNP200 during infection. In the present study, we investigated the mechanism by which μ2 exerts this effect on the U5 components. Our results revealed that μ2 has no impact on steady-state mRNA levels, RNA export, and protein stability of these U5 snRNP proteins. However, polysome profiling and metabolic labeling of newly synthesized proteins revealed that μ2 exerts an inhibitory effect on global translation. Moreover, we showed that μ2 mutants unable to accumulate in the nucleus retain most of the ability to reduce PRPF8 protein levels, indicating that the effect of μ2 on U5 snRNP components mainly occurs in the cytoplasm. Finally, co-expression experiments demonstrated that μ2 suppresses the expression of U5 snRNP proteins in a dose-dependent manner, and that the expression of specific U5 snRNP core components have different sensitivities to μ2's presence. Altogether, these results suggest a novel mechanism by which the μ2 protein reduces the levels of U5 core components through translation inhibition, allowing this viral protein to alter cellular AS during infection.
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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 | 0.001 |
| 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".