Viral Retasking of hBre1/RNF20 to Recruit hPaf1 for Transcriptional Activation
Bibliographic record
Abstract
Upon infection, human adenovirus (HAdV) must activate the expression of its early genes to reprogram the cellular environment to support virus replication. This activation is orchestrated in large part by the first HAdV gene expressed during infection, early region 1A (E1A). E1A binds and appropriates components of the cellular transcriptional machinery to modulate cellular gene transcription and activate viral early genes transcription. Previously, we identified hBre1/RNF20 as a target for E1A. The interaction between E1A and hBre1 antagonizes the innate antiviral response by blocking H2B monoubiquitination, a chromatin modification necessary for the interferon (IFN) response. Here, we describe a second distinct role for the interaction of E1A with hBre1 in transcriptional activation of HAdV early genes. Furthermore, we show that E1A changes the function of hBre1 from a ubiquitin ligase involved in substrate selection to a scaffold which recruits hPaf1 as a means to stimulate transcription and transcription-coupled histone modifications. By using hBre1 to recruit hPaf1, E1A is able to optimally activate viral early transcription and begin the cycle of viral replication. The ability of E1A to target hBre1 to simultaneously repress cellular IFN dependent transcription while activating viral transcription, represents an elegant example of the incredible economy of action accomplished by a viral regulatory protein through a single protein interaction.
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".