Hepatitis C virus NS2 and NS3/4A proteins are potent inhibitors of host cell cytokine/chemokine gene expression.
Bibliographic record
Abstract
BACKGROUND: Hepatitis C virus (HCV) encodes several proteins that interfere with the host cell antiviral response. Previously, the serine protease NS3/4A was shown to inhibit IFN-beta gene expression by blocking dsRNA-activated retinoic acid-inducible gene I (RIG-I) and Toll-like receptor 3 (TLR3)-mediated signaling pathways. RESULTS: In the present work, we systematically studied the effect of all HCV proteins on IFN gene expression. NS2 and NS3/4A inhibited IFN gene activation. NS3/4A inhibited the Sendai virus-induced expression of multiple IFN (IFN-alpha, IFN-beta and IFN-lambda1/IL-29) and chemokine (CCL5, CXCL8 and CXCL10) gene promoters. NS2 and NS3/4A, but not its proteolytically inactive form NS3/4A-S139A, were found to inhibit promoter activity induced by RIG-I or its adaptor protein Cardif (or IPS-1/MAVS/VISA). Both endogenous and transfected Cardif were proteolytically cleaved by NS3/4A but not by NS2 indicating different mechanisms of inhibition of host cell cytokine production by these HCV encoded proteases. Cardif also strongly colocalized with NS3/4A at the mitochondrial membrane, implicating the mitochondrial membrane as the site for proteolytic cleavage. In many experimental systems, IFN priming dramatically enhances RNA virus-induced IFN gene expression; pretreatment of HEK293 cells with IFN-alpha strongly enhanced RIG-I expression, but failed to protect Cardif from NS3/4A-mediated cleavage and failed to restore Sendai virus-induced IFN-beta gene expression. CONCLUSION: HCV NS2 and NS3/4A proteins were identified as potent inhibitors of cytokine gene expression suggesting an important role for HCV proteases in counteracting host cell antiviral response.
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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) | 0.002 | 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".