Acinetobacter baumannii Genomic Sequence-Based Core Genome Multilocus Sequence Typing Using Ridom SeqSphere+ and Antimicrobial Susceptibility Prediction in ARESdb

Madiha Fida, Scott A. Cunningham, Stephan Beisken, Andreas E. Posch, Nicholas Chia, Patricio R. Jeraldo, Matthew P. Murphy, Nicole M. Zinsmaster, Robin Patel

Research output: Contribution to journalArticlepeer-review

Abstract

Whole-genome sequencing (WGS) is rapidly replacing traditional typing methods for the investigation of infectious disease outbreaks. Additionally, WGS data are being used to predict phenotypic antimicrobial susceptibility. Acinetobacter baumannii, which is often multidrug-resistant, is a significant culprit in outbreaks in health care settings. A well-characterized collection of A. baumannii was studied using core genome multilocus sequence typing (cgMLST). Seventy-two isolates previously typed by PCR-electrospray ionization mass spectrometry (PCR/ESI-MS) provided by the Antimicrobial Resistance Leadership Group (ARLG) were analyzed using a clinical microbiology laboratory developed workflow for cgMLST with genomic susceptibility prediction performed using the ARESdb platform. Previously performed PCR/ESI-MS correlated with cgMLST using relatedness thresholds of allelic differences of #9 and #200 allelic differences in 78 and 94% of isolates, respectively. Categorical agreement between genotypic and phenotypic antimicrobial susceptibility across a panel of 11 commonly used drugs was 89%, with minor, major, and very major error rates of 8%, 11%, and 1%, respectively.

Original languageEnglish (US)
JournalJournal of clinical microbiology
Volume60
Issue number8
DOIs
StatePublished - Aug 2022

Keywords

  • antimicrobial resistance
  • cgMLST
  • genotypic resistance
  • whole-genome sequencing

ASJC Scopus subject areas

  • Microbiology (medical)

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