Genomic Comparisons of <i>Salmonella enterica</i> Serovar Dublin, Agona, and Typhimurium Strains Recently Isolated from Milk Filters and Bovine Samples from Ireland, Using a <i>Salmonella</i> Microarray
Bibliographic record
Abstract
Salmonella-induced enterocolitis is the leading food-borne illness with a lethal outcome and causes millions of cases of gastroenteritis each year. We examined genomic variation among 12 environmental, veterinary, and clinical Salmonella enterica serovar Dublin, Agona, and Typhimurium strains isolated in Ireland between 2000 and 2003, as well as two clinical isolates from Canada and four archival isolates, which belonged to serovars Dublin and Agona. Using DNA-DNA hybridization to a microarray consisting of most of the predicted protein-encoding sequences of the S. enterica serovar Typhimurium LT2 genome, we identified a number of genomic regions that were absent in one or more serovars. The 34 genomic regions encoded proteins involved in sugar metabolism, transport, fimbrial and phage biogenesis, and transcriptional regulation, as well as inner and outer membrane-associated proteins. Two of the four prophages identified in strain LT2, prophages Gifsy-1 and Gifsy-2, were present in all six serovar Typhimurium strains examined. Prophage Fels-1 was absent from all 18 isolates examined, and Fels-2 was completely absent from the serovar Typhimurium isolates and the Salmonella Reference Collection B serovar Dublin strain Du2. All five Salmonella pathogenicity islands were present in all isolates. Plasmid pSLT was absent from all serovar Agona isolates, and only homologues of the spv genes were present in eight of the nine serovar Dublin strains. Only limited intraserovar diversity was found among the nine serovar Dublin, three serovar Agona, and six serovar Typhimurium isolates examined even though these isolates had extensive geographic, temporal, and source differences.
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 | 0.000 | 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".