Elucidating the distinct contributions of miR-122 in the HCV life cycle reveals insights into virion assembly
Bibliographic record
Abstract
Efficient hepatitis C virus (HCV) RNA accumulation is dependent upon interactions with the human liver-specific microRNA, miR-122. MiR-122 has at least three roles in the HCV life cycle: it acts as an RNA chaperone, or 'riboswitch', allowing formation of the viral internal ribosomal entry site; it provides genome stability; and promotes viral translation. However, the relative contribution of each role in HCV RNA accumulation remains unclear. Herein, we used point mutations, mutant miRNAs, and HCV luciferase reporter RNAs to isolate each of the roles and evaluate their contribution to the overall impact of miR-122 in the HCV life cycle. Our results suggest that the riboswitch has a minimal contribution in isolation, while genome stability and translational promotion have similar contributions in the establishment phase of infection. However, in the maintenance phase, translational promotion becomes the dominant role. Additionally, we found that an alternative conformation of the 5' untranslated region, termed SLIIalt, is important for efficient virion assembly. Taken together, we have clarified the overall importance of each of the established roles of miR-122 in the HCV life cycle and provided insight into the regulation of the balance between viral RNAs in the translating/replicating pool and those engaged in virion assembly.
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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) | 0.000 | 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".