The antisense protein of HTLV-2 positively modulates HIV-1 replication
Bibliographic record
Abstract
Unlike HTLV-1, HTLV-2 does not induce leukemia and has been tentatively associated with an HTLV-1-associated myelopathy-like disorder. It has been reported that HTLV-2/HIV-1 co-infected patients progress less rapidly to AIDS than HIV-1-infected individuals. Tax2 has been suggested to mediate this protective state by inducing MIP-1 expression and blocking HIV-1 infection. As cells from HTLV-2-infected individuals mainly express Antisense Protein 2 (APH-2), our objective was to determine if this protein might also intervene in controlling HIV-1 replication in dually infected individuals. Using Jurkat cells, we first demonstrated that both APH-2 and HBZ, the HTLV-1 analogue, equally induced MIP-1 in unstimulated and stimulated Jurkat T cells. To assess if APH-2 might directly affect HIV-1 replication, a full length luciferase-expressing proviral DNA was tested in Jurkat cells. Surprisingly, upon co-transfection with an APH-2 expression vector, an increase in luciferase activity was observed, while HBZ expression rather led to reduced reporter gene expression. Western blot analyses and ELISA assay further indicated that HIV-1 p24 levels were more important in APH-2-expressing cells. To determine if APH-2 was directly modulating HIV-1 LTR activity, both NF-B and NFAT were tested in stimulated Jurkat cells. Unexpectedly, HBZ and APH-2 inhibited NF-B and NFAT activation, albeit at different extent. In addition, LTR activation was also inhibited by both antisense proteins although APH-2 had a more modest effect. Our results thus highlight the complex interplay between HTLV antisense transcript-encoded proteins and HIV-1 expression and further studies will be required to determine the potential impact of APH-2 in HTLV-2/HIV-1-infected individuals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".