Mobile colistin resistance gene mcr-1 detected on an IncI1 plasmid in Escherichia coli from meat
Bibliographic record
Abstract
OBJECTIVES: Mobile colistin resistance (mcr) genes encoded on conjugative plasmids, although described only relatively recently, have been reported globally both in humans and livestock. The genes are often associated with the insertion sequence ISApl1 that can transpose the genes to novel genetic locations. Since its first report, multiple variants of mcr have been discovered in a variety of genetic locations in Escherichia coli, in plasmids and integrated into the chromosome. METHODS: Using hybrid assembly of short-read and long-read whole-genome sequencing data, the presence ofmcr-1 was confirmed on an IncI1 plasmid in E. coli. In vitro conjugation assays were performed to determine the potential to transfer between strains. Genetic comparison with previously reported IncI1 plasmids was performed. RESULTS: The genomic sequence identified thatmcr-1 is present on a complete IncI1 plasmid. Comparison with previously reported extended-spectrum β-lactamase (ESBL)-encoding plasmids from E. coli in the Netherlands from the same time period indicated a distinct lineage for this plasmid. CONCLUSIONS: The observation ofmcr-1 on an IncI1 plasmid confirms that the genetic region of this gene is actively transposed between genetic locations. This active transposition has consequences for the study of the epidemiology of mcr in populations.
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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 | 0.000 |
| 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".