Hepatitis C virus internal ribosome entry site‐mediated translation is stimulated by <i>cis</i>‐acting RNA elements and <i>trans</i>‐acting viral factors
Bibliographic record
Abstract
Translation initiation of hepatitis C virus (HCV) occurs through an internal ribosome entry site (IRES) located at its 5'-end. As a positive-stranded RNA virus, HCV uses its genome as a common template for translation and replication, but the coordination between these two processes remains poorly characterized. Moreover, although genetic evidence of RNA-protein interactions for viral replication is accumulating because of subgenomic replicons and a recent culture system for HCV, such interactions are still contentious in the regulation of translation. To gain insight into such mechanisms, we addressed the involvement of cis and trans viral factors in HCV IRES activity by using a cell-based RNA reporter system. We found that the HCV 3' noncoding region (NCR) strongly stimulates IRES efficiency in cis, depending on the genotype and the cell line. Moreover, we confirmed the role of the core protein in viral gene expression as previously reported in vitro. Surprisingly, we observed a similar effect, i.e. a twofold increase under low amounts of NS5B RNA polymerase, followed by a decrease at higher concentrations. However, no contribution of NS5A to HCV IRES-mediated translation was noted and no cooperative effect could be detected between 3' NCR and viral proteins or between proteins. Collectively, these results suggest that HCV RNA translation is regulated, and that the switch from translation to replication might involve a sequential requirement for both cis and trans viral factors, because of their apparent lack of synergy, probably with the aid of host factors.
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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 | 0.001 |
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".