Genomic Epidemiology of NDM-1-Encoding Plasmids in Latin American Clinical Isolates Reveals Insights into the Evolution of Multidrug Resistance
Bibliographic record
Abstract
Bacteria that produce the broad-spectrum Carbapenem antibiotic New Delhi Metallo-β-lactamase (NDM) place a burden on health care systems worldwide, due to the limited treatment options for infections caused by them and the rapid global spread of this antibiotic resistance mechanism. Although it is believed that the associated resistance gene blaNDM-1 originated in Acinetobacter spp., the role of Enterobacteriaceae in its dissemination remains unclear. In this study, we used whole genome sequencing to investigate the dissemination dynamics of blaNDM-1-positive plasmids in a set of 21 clinical NDM-1-positive isolates from Colombia and Mexico (Providencia rettgeri, Klebsiella pneumoniae, and Acinetobacter baumannii) as well as six representative NDM-1-positive Escherichia coli transconjugants. Additionally, the plasmids from three representative P. rettgeri isolates were sequenced by PacBio sequencing and finished. Our results demonstrate the presence of previously reported plasmids from K. pneumoniae and A. baumannii in different genetic backgrounds and geographically distant locations in Colombia. Three new previously unclassified plasmids were also identified in P. rettgeri from Colombia and Mexico, plus an interesting genetic link between NDM-1-positive P. rettgeri from distant geographic locations (Canada, Mexico, Colombia, and Israel) without any reported epidemiological links was discovered. Finally, we detected a relationship between plasmids present in P. rettgeri and plasmids from A. baumannii and K. pneumoniae. Overall, our findings suggest a Russian doll model for the dissemination of blaNDM-1 in Latin America, with P. rettgeri playing a central role in this process, and reveal new insights into the evolution and dissemination of plasmids carrying such 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 | 0.001 |
| 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".