Acetylated Tat Regulates Human Immunodeficiency Virus Type 1 Splicing through Its Interaction with the Splicing Regulator p32
Bibliographic record
Abstract
The human immunodeficiency virus type 1 (HIV-1) potent transactivator Tat protein mediates pleiotropic effects on various cell functions. Posttranslational modification of Tat affects its activity during viral transcription. Tat binds to TAR and subsequently becomes acetylated on lysine residues by histone acetyltransferases. Novel protein-protein interaction domains on acetylated Tat are then established, which are necessary for both sustained transcriptional activation of the HIV-1 promoter and viral transcription elongation. In this study, we investigated the identity of proteins that preferentially bound acetylated Tat. Using a proteomic approach, we identified a number of proteins that preferentially bound AcTat, among which p32, a cofactor of splicing factor ASF/SF-2, was identified. We found that p32 was recruited to the HIV-1 genome, suggesting a mechanism by which acetylation of Tat may inhibit HIV-1 splicing needed for the production of full-length transcripts. Using Tat from different clades, harboring a different number of acetylation sites, as well as Tat mutated at lysine residues, we demonstrated that Tat acetylation affected splicing in vivo. Finally, using confocal microscopy, we found that p32 and Tat colocalize in vivo in HIV-1-infected cells.
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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".