The Ubiquitin-Specific Protease 18 Promotes Hepatitis C Virus Production by Increasing Viral Infectivity
Bibliographic record
Abstract
Background and Aims. Ubiquitin-specific protease 18 (USP18) is involved in immunoregulation and response to interferon- (IFN-) based treatment in patients chronically infected with hepatitis C virus (HCV). We investigated whether and how its upregulation alters HCV infection. Methods. Overexpression of wild-type (USP18 WT) or catalytically inactive mutant (USP18 C64S) USP18 was examined for effects on HCV replication in the absence and presence of IFNα or IFNλ using both the HCV-infective model and replicon cells. The IFN signaling pathway was assessed via STAT1 phosphorylation (western blot) and downstream ISG expression (real-time PCR). Mechanistic roles were sought by quantifying microRNA-122 levels and J6/JFH1 infectivity of Huh7.5 cells. Results. We found that overexpression of either USP18 WT or USP18 C64S stimulated HCV production and blunted the anti-HCV effect of IFNα and IFNλ in the infective model but not in the replicon system. Overexpressed USP18 showed no effect on Jak/STAT signaling nor on microRNA-122 expression. However, USP18 upregulation markedly increased J6/JFH1 infectivity and promoted the expression of the key HCV entry factor CD81 on Huh7.5 cells. Conclusions. USP18 stimulates HCV production and blunts the effect of both type I and III IFNs by fostering a cellular environment characterized by upregulation of CD81, promoting virus entry and infectivity.
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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) | 0.001 | 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".