Ancient <i>Clostridium</i> DNA and variants of tetanus neurotoxins associated with human archaeological remains
Bibliographic record
Abstract
SUMMARY The analysis of microbial genomes from human archaeological samples offers a historic snapshot of ancient pathogens and provides insights into the origins of modern infectious diseases. Here, through a large-scale metagenomic analysis of archeological samples, we discovered bacterial species related to modern-day Clostridium tetani , which produces the tetanus neurotoxin (TeNT) and causes the disease tetanus. We assembled draft genomes from 38 distinct human archeological samples spanning five continents and dating to as early as ~4000 BCE. These genomes had varying levels of completeness and a subset of them displayed hallmarks of ancient DNA damage. While 24 fall into known C. tetani clades, phylogenetic analysis revealed novel C. tetani lineages, as well as two novel Clostridium species (“ Clostridium sp. X and Y”) closely related to C. tetani . Within these genomes, we found 13 TeNT variants with unique substitution profiles, including a subgroup of TeNT variants found exclusively in ancient samples from South America. We experimentally tested a TeNT variant selected from a ~6000-year-old Chilean mummy sample and found that it induced tetanus muscle paralysis in mice with potency comparable to modern TeNT. Our work identifies neurotoxigenic C. tetani in ancient DNA, new Clostridium species unique to ancient human samples, and a novel variant of TeNT that can cause disease in mammals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".