Genome trimming: A unique strategy for replication control employed by Borna disease virus
Bibliographic record
Abstract
Genome and antigenome synthesis of negative-strand RNA viruses is initiated at promoters located in inverted terminal repeats (ITR). The ITR of Borna disease virus (BDV), a persisting neurotropic virus with a nuclear replication phase, are exceptional in that they appear to be noncomplete. Our analysis showed that the vast majority of genomic and antigenomic RNA molecules of BDV lack four 5'-terminal nucleotides required for perfect complementarity with the 3' ITR. By using a previously undescribed reverse genetics system, we investigated whether the structure of the ITR would affect virus propagation. BDV rescued from cDNA encoding complete ITR (rBDVc) showed wild-type virulence, whereas virus rescued from cDNA encoding a viral genome with noncomplete ITR (rBDVnc) was strongly attenuated. Both recombinant viruses expressed similar RNA and protein levels in persistently infected cells. However, rBDVnc particles were less infectious, indicating that complete ITR are required for high viral replicase but not transcriptase activity. Interestingly, genomic RNA from purified rBDVc particles lacked 5'-terminal nucleotides like authentic BDV, strongly suggesting programmed genome truncation. By specifically trimming its genome at the 5' terminus, BDV seems to limit viral genome amplification, which may favor noncytolytic viral persistence.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".