Upstream Stimulatory Factors Regulate HIV-1 Latency and Are Required for Robust T Cell Activation
Bibliographic record
Abstract
HIV-1 provirus expression is controlled by signaling pathways that are responsive to T cell receptor engagement, including those involving Ras and downstream protein kinases. The induction of transcription from the HIV-1 LTR in response to Ras signaling requires binding of the Ras-responsive element binding factor (RBF-2) to conserved cis elements flanking the enhancer region, designated RBE3 and RBE1. RBF-2 is composed minimally of the USF1, USF2, and TFII-I transcription factors. We recently determined that TFII-I regulates transcriptional elongation from the LTR through recruitment of the co-activator TRIM24. However, the function of USF1 and USF2 for this effect are uncharacterized. Here, we find that genetic deletion of USF2 but not USF1 in T cells inhibits HIV-1 expression. The loss of USF2 caused a reduction in expression of the USF1 protein, an effect that was not associated with decreased USF1 mRNA abundance. USF1 and USF2 were previously shown to exist predominately as heterodimers and to cooperatively regulate target genes. To examine cooperativity between these factors, we performed RNA-seq analysis of T cell lines bearing knockouts of the genes encoding these factors. In untreated cells, we found limited evidence of coordinated global gene regulation between USF1 and USF2. In contrast, we observed a high degree of genome-wide cooperative regulation of RNA expression between these factors in cells stimulated with the combination of PMA and ionomycin. In particular, we found that the deletion of USF1 or USF2 restricted T cell activation response. These observations indicate that USF2, but not USF1, is crucial for HIV-1 expression, while the combined function of these factors is required for a robust T cell inflammatory response.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".