Plasmid genomic epidemiology of <i>bla</i> <sub>KPC</sub> carbapenemase-producing <i>Enterobacterales</i> in Canada, 2010–2021
Bibliographic record
Abstract
ABSTRACT Carbapenems are considered last-resort antibiotics for the treatment of infections caused by multidrug-resistant Enterobacterales , but carbapenem resistance due to acquisition of carbapenemase genes is a growing threat that has been reported worldwide. Klebsiella pneumoniae carbapenemase ( bla KPC ) is the most common type of carbapenemase in Canada and elsewhere; it can hydrolyze penicillins, cephalosporins, aztreonam, and carbapenems and is frequently found on mobile plasmids in the Tn 4401 transposon. This means that alongside clonal expansion, bla KPC can disseminate through plasmid- and transposon-mediated horizontal gene transfer. We applied whole genome sequencing to characterize the molecular epidemiology of 829 bla KPC carbapenemase-producing isolates collected by the Canadian Nosocomial Infection Surveillance Program from 2010 to 2021. Using a combination of short-read and long-read sequencing, we obtained 202 complete and circular bla KPC -encoding plasmids. Using MOB-suite, 10 major plasmid clusters were identified from this data set which represented 87% (175/202) of the Canadian bla KPC -encoding plasmids. We further estimated the genomic location of incomplete bla KPC -encoding contigs and predicted a plasmid cluster for 95% (603/635) of these. We identified different patterns of carbapenemase mobilization across Canada related to different plasmid clusters, including clonal transmission of IncF-type plasmids (108/829, 13%) in K. pneumoniae clonal complex 258 and novel repE(pEh60-7) plasmids (44/829, 5%) in Enterobacter hormaechei ST316, and horizontal transmission of IncL/M (142/829, 17%) and IncN-type plasmids (149/829, 18%) across multiple genera. Our findings highlight the diversity of bla KPC genomic loci and indicate that multiple, distinct plasmid clusters have contributed to bla KPC spread and persistence in Canada.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".