Widespread occurrence of botulinum and tetanus neurotoxin genes in ancient DNA
Bibliographic record
Abstract
Abstract Background Ancient DNA collected from archaeological specimens not only provides a window into ancient human genetic diversity but also contains a rich mixture of associated microbial DNA including potential pathogens. In recent work, we identified C. tetani and tetanus neurotoxin (TeNT) genes in ancient DNA datasets collected from human archaeological specimens. However, the reasons underlying the occurrence of these toxin genes and the extent to which other toxin genes are present in ancient DNA is unclear. Methods Here, we performed a large-scale analysis of 6,435 ancient DNA (aDNA) sequencing datasets including human and non-human sources, searching for 49 clostridial neurotoxin types and subtypes, as well as 3 additional unrelated toxins. Results Our search identified a total of 105 ancient DNA datasets (1.6%) containing significant matches to one or more neurotoxin genes. Consistent with our earlier work, TeNT genes were most common, found in 50 ancient DNA datasets. In addition, we identified sequences encoding diverse botulinum neurotoxins including BoNT/C (40 samples), BoNT/D (6 samples), BoNT/B (4 samples), BoNT/E (1 sample), and the Enterococcus -associated BoNT/En (10 samples). TeNT genes were detected in a broad range of ancient samples including human and animal (horse, wild bear, chimpanzee) remains, whereas the largest diversity of toxins was detected in aDNA from Egyptian mummies. Phylogenetic and sequence analysis of the identified matches revealed close identity to modern forms of these toxins. Damage analysis revealed several toxin genes with hallmarks of ancient DNA associated damage, indicative of an ancient origin. Conclusions Our work reveals that clostridial neurotoxin genes occur frequently in aDNA samples, including human and animal-associated toxin variants. We conclude that the frequent association of these genes with aDNA likely reflects a strong ecological association of pathogenic clostridia with decaying human and animal remains and possible post-mortem colonization of these samples.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".