A Role for the Nucleosome Assembly Proteins TAF-Iβ and NAP1 in the Activation of BZLF1 Expression and Epstein-Barr Virus Reactivation
Bibliographic record
Abstract
The reactivation of Epstein-Barr virus (EBV) from latent to lytic infection begins with the expression of the viral BZLF1 gene, leading to a subsequent cascade of viral gene expression and amplification of the EBV genome. Using RNA interference, we show that nucleosome assembly proteins NAP1 and TAF-I positively contribute to EBV reactivation in epithelial cells through the induction of BZLF1 expression. In addition, overexpression of NAP1 or the β isoform of TAF-I (TAF-Iβ) in AGS cells latently infected with EBV was sufficient to induce BZLF1 expression. Chromatin immunoprecipitation experiments performed in AGS-EBV cells showed that TAF-I associated with the BZLF1 promoter upon lytic induction and affected local histone modifications by increasing H3K4 dimethylation and H4K8 acetylation. MLL1, the host protein known to dimethylate H3K4, was found to associate with the BZLF1 promoter upon lytic induction in a TAF-I-dependent manner, and MLL1 depletion decreased BZLF1 expression, confirming its contribution to lytic reactivation. The results indicate that TAF-Iβ promotes BZLF1 expression and subsequent lytic infection by affecting chromatin at the BZLF1 promoter.
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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".