Important role of N108 residue in binding of bovine foamy virus transactivator Tas to viral promoters
Bibliographic record
Abstract
BACKGROUND: Bovine foamy virus (BFV) encodes the transactivator BTas, which enhances viral gene transcription by binding to the long terminal repeat promoter and the internal promoter. In this study, we investigated the different replication capacities of two similar BFV full-length DNA clones, pBS-BFV-Y and pBS-BFV-B. RESULTS: Here, functional analysis of several chimeric clones revealed a major role for the C-terminal region of the viral genome in causing this difference. Furthermore, BTas-B, which is located in this C-terminal region, exhibited a 20-fold higher transactivation activity than BTas-Y. Sequence alignment showed that these two sequences differ only at amino acid 108, with BTas-B containing N108 and BTas-Y containing D108 at this position. Results of mutagenesis studies demonstrated that residue N108 is important for BTas binding to viral promoters. In addition, the N108D mutation in pBS-BFV-B reduced the viral replication capacity by about 1.5-fold. CONCLUSIONS: Our results suggest that residue N108 is important for BTas binding to BFV promoters and has a major role in BFV replication. These findings not only advances our understanding of the transactivation mechanism of BTas, but they also highlight the importance of certain sequence polymorphisms in modulating the replication capacity of isolated BFV clones.
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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 | 0.001 |
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".