4.7 Article

Next-Generation-Sequencing-Based Hospital Outbreak Investigation Yields Insight into Klebsiella aerogenes Population Structure and Determinants of Carbapenem Resistance and Pathogenicity

Journal

ANTIMICROBIAL AGENTS AND CHEMOTHERAPY
Volume 63, Issue 6, Pages -

Publisher

AMER SOC MICROBIOLOGY
DOI: 10.1128/AAC.02577-18

Keywords

AmpD; carbapenem-resistant Klebsiella aerogenes; MLST; ST4; cardiothoracic intensive care unit; genomic epidemiology; integrative conjugative element; outbreak; porins; yersiniabactin

Funding

  1. URMC Genomics Research Center
  2. University of Rochester Department of Pathology and Laboratory Medicine

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Klebsiella aerogenes is a nosocomial pathogen associated with drug resistance and outbreaks in intensive care units. In a 5-month period in 2017, we experienced an increased incidence of cultures for carbapenem-resistant K. aerogenes (CR-KA) from an adult cardiothoracic intensive care unit (CICU) involving 15 patients. Phylogenomic analysis following whole-genome sequencing (WGS) identified the outbreak CR-KA isolates to group together as a tight monoclonal cluster (with no more than six single nucleotide polymorphisms [SNPs]), suggestive of a protracted intraward transmission event. No clonal relationships were identified between the CICU CR-KA strains and additional hospital CR-KA patient isolates from different wards and/or previous years. Carbapenemase-encoding genes and drug-resistant plasmids were absent in the outbreak strains, and carbapenem resistance was attributed to mutations impacting AmpD activity and membrane permeability. The CICU outbreak strains harbored an integrative conjugative element (ICE) which has been associated with pathogenic Klebsiella pneumoniae lineages (ICEKp10). Comparative genomics with global K. aerogenes genomes showed our outbreak strains to group closely with global sequence type 4 (ST4) strains, which, along with ST93, likely represent dominant K. aerogenes lineages associated with human infections. For poorly characterized pathogens, scaling analyses to include sequenced genomes from public databases offer the opportunity to identify emerging trends and dominant clones associated with specific attributes, syndromes, and geographical locations.

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