Variation in plasmid conjugation among nontyphoidal <i>Salmonella enterica</i> serovars
Bibliographic record
Abstract
Conjugation is a complex phenomenon involving multiple plasmid, bacterial, and environmental factors. Here we describe an IncI1 plasmid encoding multidrug antibiotic resistance to aminoglycosides, sulfonamides, and third-generation cephalosporins. This plasmid is widespread geographically among animal, human, and environmental sectors. We present data on the transmissibility of this plasmid from Salmonella enterica ser. Kentucky into 40 strains of S. enterica (10 strains each from serovars Enteritidis, Heidelberg, Infantis, and Typhimurium). Thirty seven out of 40 strains were able to take up the plasmid. Rates of conjugation were variable between strains ranging from 10−8 to 10−4. Overall, serovars Enteritidis and Typhimurium demonstrated the highest rates of conjugation, followed by Heidelberg, and then Infantis. No relationships were observed between the recipient cell surface and rate of conjugation. Recipient cell numbers correlated positively with conjugation rate and strains with high conjugation rates had marginally but significantly higher growth parameters compared to strains that took up the plasmid at lower frequencies. Environmental conditions known to impact cell growth, such as temperature, nutrient availability, and the presence of antibiotics, had a modulating effect on conjugation. Collectively, these results will further understanding of plasmid transmission dynamics in Salmonella, which is a critical first step towards the development of mitigation strategies.
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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 | 0.001 |
| 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 | 0.000 |
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".