Expansion of the tetracycline resistome in Aeromonas salmonicida with a tet(D) gene found in plasmids pAsa-2900 and pAsa-2900b
Bibliographic record
Abstract
Plasmids carrying antibiotic resistance genes occur frequently in Aeromonas salmonicida subsp. salmonicida, an aquatic pathogen. In this study, we describe three new plasmids found in strains of A. salmonicida subsp. salmonicida from Québec, Canada: pAsa-2358, pAsa-2900, and pAsa-2900b. The last two plasmids have a tet(D) resistance gene against tetracycline, which has not been previously found in A. salmonicida. The only difference between these two plasmids is the presence of a florfenicol resistance gene (floR) surrounded by two copies of the same insertion sequence, indicating that pAsa-2900 and pAsa-2900b are plasmid variants. All three plasmids represent an issue for aquaculture because they bear resistance genes against antibiotics used to treat infected fish: floR and tet(A) for pAsa-2358; floR, sul2, and tet(D) for pAsa-2900; and sul2 and tet(D) for pAsa-2900b. Conjugation assays confirmed that the three plasmids are capable of conjugation with one A. salmonicida mesophilic strain, one A. hydrophila strain, and Escherichia coli DH5α; except for pAsa-2358 that is not able to conjugate into E. coli DH5α. Based on the results of antibiotic resistance assays, the tet(D) gene provides a greater resistance to tetracycline than the tet(A) gene found in many A. salmonicida subsp. salmonicida plasmids. This is the case whether the plasmids are in their parental A. salmonicida subsp. salmonicida strains or in Aeromonas sp. transconjugates. The presence of these three plasmids in A. salmonicida subsp. salmonicida strengthens the role of this bacterium as a reservoir for antibiotic resistance genes.
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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 | 0.000 | 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 | 0.001 |
| 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".