Antimicrobial Agents and ChemotherapyGenomicsPeer-reviewed journal article
Next-generation sequencing based hospital outbreak investigation yields insight into Klebsiella aerogenes population structure and determinants of carbapenem resistance and virulence
Adel MalekiD, Kelly A. McGlynniD, Samantha M. Taffner, Lynn Fine, Brenda L. TesiniiD, Jun Wang, Heba H. MostafaiD, Sharon Petry, Archibald S. PerkinsiD, PAUL S. GRAMANiD, Dwight J. Hardy, Nicole PecoraiD
Abstract
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 clonal cluster (<7 SNPs apart), suggestive of a protracted intra-ward 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. Genes encoding carbapenemases or 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 (ICEKp10), which has been associated with pathogenicity in hypervirulent Klebsiella pneumoniae lineages. Comparative genomics with global K. aerogenes genomes showed our outbreak strains to group closely with global ST4 strains, which along with ST93 likely represent dominant K. aerogenes lineages associated with human infections. WGS is a powerful tool that goes beyond high-resolution tracking of transmission events into identifying the genetic basis of drug-resistance and virulence, which are not part of conventional diagnostic workflows. With an increasing availability of sequenced genomes from across the globe, population structure analysis offers opportunities to identify emerging trends and dominant clones associated with specific syndromes and geographical locations for poorly characterized pathogens.
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- top 13%
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