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J Clin Microbiol. 2016 Mar;54(3):593-612. doi: 10.1128/JCM.01818-15. Epub 2015 Dec 23.

Utility of Whole-Genome Sequencing in Characterizing Acinetobacter Epidemiology and Analyzing Hospital Outbreaks.

Author information

1
Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
2
Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA e-ozer@northwestern.edu.
3
Department of Microbiology and Immunology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.

Abstract

Acinetobacter baumannii frequently causes nosocomial infections and outbreaks. Whole-genome sequencing (WGS) is a promising technique for strain typing and outbreak investigations. We compared the performance of conventional methods with WGS for strain typing clinical Acinetobacter isolates and analyzing a carbapenem-resistant A. baumannii (CRAB) outbreak. We performed two band-based typing techniques (pulsed-field gel electrophoresis and repetitive extragenic palindromic-PCR), multilocus sequence type (MLST) analysis, and WGS on 148 Acinetobacter calcoaceticus-A. baumannii complex bloodstream isolates collected from a single hospital from 2005 to 2012. Phylogenetic trees inferred from core-genome single nucleotide polymorphisms (SNPs) confirmed three Acinetobacter species within this collection. Four major A. baumannii clonal lineages (as defined by MLST) circulated during the study, three of which are globally distributed and one of which is novel. WGS indicated that a threshold of 2,500 core SNPs accurately distinguished A. baumannii isolates from different clonal lineages. The band-based techniques performed poorly in assigning isolates to clonal lineages and exhibited little agreement with sequence-based techniques. After applying WGS to a CRAB outbreak that occurred during the study, we identified a threshold of 2.5 core SNPs that distinguished nonoutbreak from outbreak strains. WGS was more discriminatory than the band-based techniques and was used to construct a more accurate transmission map that resolved many of the plausible transmission routes suggested by epidemiologic links. Our study demonstrates that WGS is superior to conventional techniques for A. baumannii strain typing and outbreak analysis. These findings support the incorporation of WGS into health care infection prevention efforts.

PMID:
26699703
PMCID:
PMC4767972
DOI:
10.1128/JCM.01818-15
[Indexed for MEDLINE]
Free PMC Article

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