HMGA1 directly interacts with TAR to modulate basal and Tat-dependent HIV transcription
Bibliographic record
Abstract
The transactivating response element (TAR) of human immunodeficiency virus 1 (HIV-1) is essential for promoter transactivation by the viral transactivator of transcription (Tat). The Tat-TAR interaction thereby recruits active positive transcription elongation factor b (P-TEFb) from its inactive, 7SK/HEXIM1-bound form, leading to efficient viral transcription. Here, we show that the 7SK RNA-associating chromatin regulator HMGA1 can specifically bind to the HIV-1 TAR element and that 7SK RNA can thereby compete with TAR. The HMGA1-binding interface of TAR is located within the binding site for Tat and other cellular activators, and we further provide evidence for competition between HMGA1 and Tat for TAR-binding. HMGA1 negatively influences the expression of a HIV-1 promoter-driven reporter in a TAR-dependent manner, both in the presence and in the absence of Tat. The overexpression of the HMGA1-binding substructure of 7SK RNA results in a TAR-dependent gain of HIV-1 promoter activity similar to the effect of the shRNA-mediated knockdown of HMGA1. Our results support a model in which the HMGA1/TAR interaction prevents the binding of transcription-activating cellular co-factors and Tat, subsequently leading to reduced HIV-1 transcription.
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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".