HTLV-3 and HTLV-4 antisense proteins activate JunB-, c-Jun- and JunD-dependent transcription
Bibliographic record
Abstract
The antisense transcript-encoded HBZ protein acts upon viral and cellular gene expression through its modulation of the activation of transcription factors such as Jun family members. A possible link between HBZ and ATL development has also been highlighted. HTLV-3 and HTLV-4 are two newly discovered human retroviruses closely related to HTLV-1; no known diseases have yet been associated to these viruses. Based on previous in silico analyses, our aim was to test for the presence of antisense transcripts in these new viruses and to functionally assess these viral proteins. By RT-PCR analyses, HTLV-3 and HTLV-4 were shown to produce spliced antisense transcripts termed APH (Antisense Protein of HTLV)-3 and APH-4. Confocal microscopy analyses of cells expressing Myc- or GFP-tagged APH-3 and APH-4 showed distinct localization but partial colocalization with HBZ to the nucleus and the nucleoli. Using LTR-luciferase constructs, we demonstrated that APH-3 and APH-4 inhibited Tax1 and Tax3 transactivation of respective LTRs. In transfection experiments with a collagenase promoter-driven luciferase reporter construct, we showed that APH-3 and APH-4 modulated JunB- and c-Jun-dependent transcription differently from HBZ. Deletion mutants indicated that this upregulation of the transactivation potential of Jun factors was mediated through the atypical bZIP domain of APH-3 and APH-4. We show that HTLV-3 and HTLV-4 express new viral proteins, APH-3 and APH-4, which modulate Jun-dependent transcription differently from HBZ. These data underscore the importance of our study on APH-3 and APH-4 to help in better understanding the role of HBZ in the development of ATL.
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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) | 0.002 | 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".