Genomic Sequence and Virulence of Clonal Isolates of Vaccinia Virus Tiantan, the Chinese Smallpox Vaccine Strain
Bibliographic record
Abstract
Despite the worldwide eradication of smallpox in 1979, the potential bioterrorism threat from variola virus and the ongoing use of vaccinia virus (VACV) as a vector for vaccine development argue for continued research on VACV. In China, the VACV Tiantan strain (TT) was used in the smallpox eradication campaign. Its progeny strain is currently being used to develop a human immunodeficiency virus (HIV) vaccine. Here we sequenced the full genomes of five TT clones isolated by plaque purification from the TT (752-1) viral stock. Phylogenetic analysis with other commonly used VACV strains showed that TT (752-1) and its clones clustered and exhibited higher sequence diversity than that found in Dryvax clones. The ∼190 kbp genomes of TT appeared to encode 273 open reading frames (ORFs). ORFs located in the middle of the genome were more conserved than those located at the two termini, where many virulence and immunomodulation associated genes reside. Several patterns of nucleotide changes including point mutations, insertions and deletions were identified. The polymorphisms in seven virulence-associated proteins and six immunomodulation-related proteins were analyzed. We also investigated the neuro- and skin- virulence of TT clones in mice and rabbits, respectively. The TT clones exhibited significantly less virulence than the New York City Board of Health (NYCBH) strain, as evidenced by less extensive weight loss and morbidity in mice as well as produced smaller skin lesions and lower incidence of putrescence in rabbits. The complete genome sequences, ORF annotations, and phenotypic diversity yielded from this study aid our understanding of the Chinese historic TT strain and are useful for HIV vaccine projects employing TT as a vector.
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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) | 0.000 | 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".