Recruitment of Histone Deacetylase 3 to the Interferon-A Gene Promoters Attenuates Interferon Expression
Bibliographic record
Abstract
BACKGROUND: Induction of Type I Interferon (IFN) genes constitutes an essential step leading to innate immune responses during virus infection. Sendai virus (SeV) infection of B lymphoid Namalwa cells transiently induces the transcriptional expression of multiple IFN-A genes. Although transcriptional activation of IFN-A genes has been extensively studied, the mechanism responsible for the attenuation of their expression remains to be determined. PRINCIPAL FINDINGS: In this study, we demonstrate that virus infection of Namalwa cells induces transient recruitment of HDAC3 (histone deacetylase 3) to IFN-A promoters. Analysis of chromatin-protein association by Chip-QPCR demonstrated that recruitment of interferon regulatory factor (IRF)3 and IRF7, as well as TBP correlated with enhanced histone H3K9 and H3K14 acetylation, whereas recruitment of HDAC3 correlated with inhibition of histone H3K9/K14 acetylation, removal of IRF7 and TATA-binding protein (TBP) from IFN-A promoters and inhibition of virus-induced IFN-A gene transcription. Additionally, HDAC3 overexpression reduced, and HDAC3 depletion by siRNA enhanced IFN-A gene expression. Furthermore, activation of IRF7 enhanced histone H3K9/K14 acetylation and IFN-A gene expression, whereas activation of both IRF7 and IRF3 led to recruitment of HDAC3 to the IFN-A gene promoters, resulting in impaired histone H3K9 acetylation and attenuation of IFN-A gene transcription. CONCLUSION: Altogether these data indicate that reversal of histone H3K9/K14 acetylation by HDAC3 is required for attenuation of IFN-A gene transcription during viral infection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".