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Record W2338813672 · doi:10.1093/ofid/ofv133.134

Whole Genome Sequencing in Tracking Intergenus Klebsiella Pneumoniae Carbapenemase (KPC) Gene Transmission in a Tertiary Care Center

2015· article· en· W2338813672 on OpenAlexaboutno aff
Kristin Y. Popiel, Yves Longtin, Laura Mataseje, Michael R. Mulvey, Chand S. Mangat, Mark A. Miller, Brigitte Lefebvre, Louis‐Patrick Haraoui

Bibliographic record

VenueOpen Forum Infectious Diseases · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsnot available
Fundersnot available
KeywordsKlebsiella pneumoniaeTertiary careMedicineWhole genome sequencingGeneTransmission (telecommunications)Center (category theory)GenomeMicrobiologyGeneticsBiologyEscherichia coliFamily medicine

Abstract

fetched live from OpenAlex

Background. An outbreak is traditionally suspected when a cluster of cases associated with a common organism is observed. Outbreaks due to carbapenemase-producing organisms challenge traditional infection control approaches as the focus shifts to resistance genes transmitted between different genera and species. Whole genome sequencing (WGS) is a new tool that allows for the genetic typing of isolates and for tracking of mobile resistance elements. Methods. In a 637-bed university teaching hospital in Montréal, Canada, detection of a new case of a nosocomially acquired KPC-producing Enterobacter cloacae (Ec1) prompted the application of WGS analysis to epidemiologically-linked clinical and surveillance samples harbouring the KPC gene (n = 9). blaKPC gene presence was confirmed by PCR. Pulsed-field gel electrophoresis using XbaI, plasmid fingerprinting (pRFLP) using Bgl II and PCR to detect plasmid incompatibility groups (Inc) was conducted. Whole genome sequencing (WGS) was conducted using Illumina technology on a Miseq with assembly using Spades. Analysis of the genomes was conducted by single variant polymorphisms (SVP), MLST and mapping of Tn4401 to a referencing using Bowtie. Results. In all, 9 isolates from 5 subjects were sequenced: 5 K. pneumoniae, 1 E.coli, 1 K. oxytoca and 2 E. cloacae (Ec1 and the only other known KPC-producing E. cloacae detected at the hospital in the previous year). SNP analysis of Tn4401 and pRFLP revealed 3 transposon types (Tn4401-type1-3), incorporated into 6 distinct plasmids (A1, A2, B1, C1, D1, E1), belonging to IncN, IncP,L/M, IncFllk or IncFIA(H1). Tn4401-type1 was identified in 3 plasmids (A2, D1, E1), found in 3 species, K. pneumoniae, E. cloacae and K. oxytoca. A2, an IncN plasmid, associated with Tn4401-type1 was identified in Ec1 and in a K. pneumoniae suggesting that the isolates are linked. Conclusion. WGS is a promising tool to aid in investigating and tracking transmission of both organisms and their highly mobile genetic determinants of resistance. As demonstrated here, its application in the setting of nosocomial transmission supports re-thinking of when and how to implement infection control practices and endorses WGS on a larger scale to optimize the management of nosocomial outbreaks. Disclosures. All authors: No reported disclosures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.264
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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