Interferon Regulatory Factor 7 Regulates Expression of Epstein-Barr Virus Latent Membrane Protein 1: a Regulatory Circuit
Bibliographic record
Abstract
We have shown previously that interferon regulatory factor 7 (IRF7), a multifunctional protein intimately involved in latent Epstein-Barr virus (EBV) infection, is induced as well as activated by EBV latent membrane protein 1 (LMP1), the principal EBV oncoprotein. Since the LMP1 promoter (LMP1p) contains an interferon-stimulated response element (ISRE), we hypothesized that IRF7 might be able to regulate LMP1 expression and thus participate in a regulatory circuit between these two genes. In this study, IRF7 was shown first to activate LMP1p in transient transfection assays. Compared with EBV nuclear antigen 2 (EBNA2), the most potent viral transactivator of LMP1p, IRF7 has a lesser effect (approximately 10% that of EBNA2) on induction of LMP1p. Study with IRF7 deletion mutants showed that IRF7 functional domains have similar effects on both the beta interferon (IFN-beta) and LMP1 promoters in BJAB and 293 cells, and study with IRF7 phosphomimetic mutants showed that IRF7 phosphorylation may be involved in the activation of these two promoters. Further, the ISRE in LMP1p responds to IRF7 induction and IRF7 binds to this element. In the EBV-positive cell line P3HR1, which lacks the complete EBNA2 and EBV-encoded leader protein genes and hence expresses low-level LMP1, IRF7 alone can notably increase the endogenous LMP1 mRNA and protein levels. These results indicate that LMP1 is regulated by this host cell gene in addition to the viral factor, EBNA2, and may help to explain how LMP1 is expressed in type II latency in the absence of EBNA2. Moreover, IRF7 can regulate a viral gene in addition to a host cellular gene such as the IFN-beta gene. Together with the previous data that LMP1 can induce IRF7 expression and facilitate IRF7 phosphorylation and nuclear translocation, these results suggest a positive regulatory circuit between IRF7 and LMP1.
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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".