Global genomic epidemiology of Salmonella Typhimurium DT104
Bibliographic record
Abstract
It has been 30 years since the initial emergence and subsequent rapid global spread of multidrug-resistant S. Typhimurium DT104. Nonetheless, its origin and transmission route have never been revealed. We used whole genome sequence (WGS) and temporally structured sequence analysis within a Bayesian framework to reconstruct temporal and spatial phylogenetic trees and estimate the rate of mutation and divergence time of 315 S. Typhimurium DT104 isolates sampled from 1969 to 2012 from 21 countries on six continents. DT104 was estimated to have emerged initially as antimicrobial-susceptible strains in ~1948 (95% credible interval, 1934 - 1962) and later became multidrug-resistant (MDR) DT104 in ~1972 (95% CI 1972 – 1988) through horizontal transfer of the 13-kb SGI1 MDR region into already SGI1-containing susceptible strains. This was followed by multiple transmission events initially from Central Europe and later between several European countries. An independent transmission occurred to the United States and another to Japan and from here likely to Taiwan and Canada. An independent acquisition of resistance genes took place in Thailand in ~1975 (95% CI 1975-1990). Locally in Denmark, WGS was capable of confirming local epidemiology for transmission between animal herds. Interestingly, the demographic history of Danish MDR DT104 provided evidence for the accomplishment of an eradication program across pig herds in Denmark from 1996 to 2000. The results from this study refute several hypotheses on the evolution of DT104 and would suggest WGS may be useful in monitoring emerging clones and making strategies for prevention.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 | 0.000 |
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".