Genomic Changes within a Subset of IncI2 Plasmids Associated with Dissemination of mcr-1 Genes and Other Important Antimicrobial Resistance Determinants
Bibliographic record
Abstract
IncI2 plasmids appear to have only recently become associated with resistance genes; however, their tendency to carry resistance to the antibiotics of last resort and their widespread distribution increase their relative importance. In this study, we describe lineages within this plasmid family that have an increased likelihood of acquisition of antimicrobial resistance genes. Globally distributed mcr-1-carrying IncI2 plasmids were found to cluster with other IncI2 plasmids carrying extended-spectrum beta-lactamase genes, and separately from the non-resistant IncI2 plasmids. In addition, insertion sequence (IS) elements with no direct association with the acquired resistance genes also clustered with the resistance plasmids in the phylogenetic tree. In recognition of the biased sequencing of resistant plasmids globally, the analysis was also performed on resistant and non-resistant IncI2 plasmids sequenced in the USA through government surveillance efforts that do not rely on antibiotic selection. This analysis confirmed a distinct clustering associated with both resistance and mobile elements and identified possible genomic changes in core genes that correlate with increased acquisition of foreign DNA. This work highlights a potential genetic mechanism for increased uptake of foreign DNA within this prevalent family of plasmids.
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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 | 0.001 |
| 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".