Interferon dependent immune memory during HSV-1 neuronal latency via increased H3K9me3 and restriction by ATRX
Bibliographic record
Abstract
Herpes simplex virus-1 (HSV-1) establishes a latent infection in neurons, periodically reactivating to cause disease. Neuronal conditions, including immune signaling, during initial HSV-1 infection, impact later reactivation. Type I interferon (IFNα) exposure during initial infection results in promyelocytic leukemia nuclear-body (PML-NB) formation and subsequent restriction of reactivation, via mechanisms that were unknown. Here we find that PML-NB formation results in the recruitment of histone chaperones to the viral genome and increased enrichment of the repressive heterochromatin mark, histone H3 lysine 9 tri-methylation (H3K9me3), and its reader, ATRX (alpha-thalassemia/mental retardation, X-linked). ATRX is highly abundant in neurons and prevents reactivation from H3K9me3-bound latent genomes by remaining associated with viral chromatin. Therefore, we demonstrate how immune signaling during initial infection results in an epigenetic memory on HSV-1 genomes and identify ATRX as a neuronal restriction factor against HSV-1 reactivation, elucidating a new potential target for inhibiting HSV-1 reactivation and subsequent human disease. This study uncovers a mechanism for innate immune memory in neurons, demonstrated by a more silent epigenetic structure of the Herpes Simplex Virus genome, resulting in a deep form of latent infection that is restricted for reactivation of the virus.
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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) | 0.002 | 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".