A genome map of<i>Salmonella enterica</i>serovar Agona: numerous insertions and deletions reflecting the evolutionary history of a human pathogen
Bibliographic record
Abstract
Salmonella enterica serovar Agona is an important zoonotic pathogen, causing serious human illness worldwide, but knowledge about its genetics and evolution, especially regarding the genomic events that might have contributed to the formation of S. Agona as an important pathogen, is lacking. As a first step toward understanding this pathogen and characterizing its genomic differences with other salmonellae, we constructed a physical map of S. Agona in strain SARB1 using I-CeuI, XbaI, AvrII and Tn10 insertions with pulsed-field gel electrophoresis techniques. On the 4815-kb genomic map, we located 82 genes, revealed one inversion of about 1000 kb and resolved seven deletions and seven insertions ranging from 10 to 67 kb relative to the genome of Salmonella typhimurium LT2. These genomic features clearly distinguish S. Agona from other previously analyzed salmonellae and provide clues to the molecular basis for its genomic divergence. Additionally, these kinds of physical maps, combined with emerging high-speed sequencing technologies, such as the Solexa or SOLiD techniques, which require a pre-existing high-resolution physical map such as the S. Agona map reported here, will play important roles in genomic comparative studies of bacteria involving large numbers of strains.
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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 | 0.001 | 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) | 0.001 | 0.001 |
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".