Genomic insights into the diversity, virulence and resistance of Klebsiella pneumoniae extensively drug resistant clinical isolates
Bibliographic record
Abstract
Klebsiella pneumoniae has been implicated in wide-ranging nosocomial outbreaks, causing severe infections without effective treatments due to antibiotic resistance. Here, we performed genome sequencing of 70 extensively drug resistant clinical isolates, collected from Brasília’s hospitals (Brazil) between 2010 and 2014. The majority of strains (60 out of 70) belonged to a single clonal complex (CC), CC258, which has become distributed worldwide in the last two decades. Of these CC258 strains, 44 strains were classified as sequence type 11 (ST11) and fell into two distinct clades, but no ST258 strains were found. These 70 strains had a pan-genome size of 10 366 genes, with a core-genome size of ~4476 genes found in 95 % of isolates. Analysis of sequences revealed diverse mechanisms of resistance, including production of multidrug efflux pumps, enzymes with the same target function but with reduced or no affinity to the drug, and proteins that protected the drug target or inactivated the drug. β-Lactamase production provided the most notable mechanism associated with K. pneumoniae . Each strain presented two or three different β-lactamase enzymes, including class A (SHV, CTX-M and KPC), class B and class C AmpC enzymes, although no class D β-lactamase was identified. Strains carrying the NDM enzyme involved three different ST types, suggesting that there was no common genetic origin.
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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 | 0.001 | 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".