Improved molecular characterization of the Klebsiella oxytoca complex reveals the prevalence of the kleboxymycin biosynthetic gene cluster
Bibliographic record
Abstract
As part of the ongoing studies with clinically relevant Klebsiella spp., we characterized the genomes of three clinical GES-5-positive ST138 strains originally identified as Klebsiella oxytoca. bla OXY gene, average nucleotide identity and phylogenetic analyses showed the strains to be Klebsiella michiganensis . Affiliation of the strains to ST138 led us to demonstrate that the current multi-locus sequence typing scheme for K. oxytoca can be used to distinguish members of this genetically diverse complex of bacteria. The strains encoded the kleboxymycin biosynthetic gene cluster (BGC), previously only found in K. oxytoca strains and one strain of Klebsiella grimontii . The finding of this BGC, associated with antibiotic-associated haemorrhagic colitis, in K. michiganensis led us to carry out a wide-ranging study to determine the prevalence of this BGC in Klebsiella spp. Of 7170 publicly available Klebsiella genome sequences screened, 88 encoded the kleboxymycin BGC. All BGC-positive strains belonged to the K. oxytoca complex, with strains of four ( K. oxytoca , K. pasteurii , K. grimontii , K. michiganensis ) of the six species of complex found to encode the complete BGC. In addition to being found in K. grimontii strains isolated from preterm infants, the BGC was found in K. oxytoca and K. michiganensis metagenome-assembled genomes recovered from neonates. Detection of the kleboxymycin BGC across the K. oxytoca complex may be of clinical relevance and this cluster should be included in databases characterizing virulence factors, in addition to those characterizing BGCs.
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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".