Inhibition of Epstein-Barr Virus (EBV) Reactivation by Short Interfering RNAs Targeting p38 Mitogen-Activated Protein Kinase or c-<i>myc</i>in EBV-Positive Epithelial Cells
Bibliographic record
Abstract
Latent Epstein-Barr virus (EBV) is reactivated by 12-O-tetradecanoylphorbol-13-acetate (TPA) in EBV-infected cells. In this study, we found that TPA up-regulated phosphorylation of p38, a mitogen-activated protein kinase, and activated c-myc mRNA in EBV-positive epithelial GT38 cells. The EBV immediate-early gene BZLF1 mRNA and its product ZEBRA protein were induced following TPA treatment. Protein kinase C inhibitors, 1-(5-isoquinolinesulphonyl)-2, 5-dimethylpiperazine (H7) and staurosporine, inhibited the induction of p38 phosphorylation and the activation of c-Myc by TPA. The p38 inhibitor SB203580 blocked both p38 phosphorylation and ZEBRA expression by TPA. Pretreatment of GT38 cells with the nitric oxide (NO) donor S-nitroso-N-acetylpenicillamine inhibited p38 phosphorylation and c-Myc activation by TPA, suggesting that NO may inhibit EBV reactivation via both p38 and c-Myc. By using short interfering RNA (siRNA) targeting either p38 or c-myc, we found that p38 or c-myc siRNA specifically inhibited expression of the respective gene and also suppressed the induction of ZEBRA and EBV early antigen. The interferon (IFN)-responsive gene expression tests ruled out the possibility that the antiviral effect of siRNA is dependent on IFN. Our present study demonstrates for the first time that either p38 or c-myc siRNA can efficiently inhibit TPA-induced EBV reactivation in GT38 cells, indicating that p38- and/or c-myc-associated signaling pathways may play critical roles in the disruption of EBV latency by TPA.
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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 | 0.001 |
| 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".