The Tat Protein of Human Immunodeficiency Virus Type 1 (HIV-1) Can Promote Placement of tRNA Primer onto Viral RNA and Suppress Later DNA Polymerization in HIV-1 Reverse Transcription
Bibliographic record
Abstract
Human immunodeficiency virus type-1 Tat has been proposed to play a role in the regulation of reverse transcription. We previously demonstrated that wild-type Tat can augment viral infectivity by suppressing the reverse transcriptase (RT) reaction at late stages of the viral life cycle in order to prevent the premature synthesis of potentially deleterious viral DNA products. Here we have performed a detailed analysis of the cell-free reverse transcription reaction to elucidate the mechanism(s) whereby Tat can affect this process. Our results show that Tat can suppress nonspecific DNA elongation while moderately affecting the specific initiation stage of reverse transcription. In addition, Tat has an RNA-annealing activity and can promote the placement of tRNA onto viral RNA. This points to a functional homology between Tat and the viral nucleocapsid (NC) protein that is known to be directly involved in this process. Experiments using a series of mutant Tat proteins revealed that the cysteine-rich and core domains of Tat are responsible for suppression of DNA elongation, while each of the cysteine-rich, core, and basic domains, as well as a glutamine-rich region in the C-terminal domain, are important for the placement of tRNA onto the viral RNA genome. These results suggest that Tat can play at least two different roles in the RT reaction, i.e., suppression of DNA polymerization and placement of tRNA onto viral RNA. We believe that the first of these activities of Tat may contribute to the overall efficiency of reverse transcription of the viral genome during a new round of infection as well as to enhanced production of infectious viral particles. We hypothesize that the second activity, illustrating functional homology between Tat and NC, suggests a potential role for NC in the displacement of Tat during viral maturation.
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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".