Predicting antimicrobial susceptibilities for Escherichia coli and Klebsiella pneumoniae isolates using whole genomic sequence data

N. Stoesser, E. M. Batty, D. W. Eyre, M. Morgan, D. H. Wyllie, C. Del Ojo Elias, J. R. Johnson, A. S. Walker, T. E.A. Peto, D. W. Crook

Research output: Contribution to journalArticlepeer-review

162 Scopus citations

Abstract

Objectives:Whole-genome sequencing potentially represents a single, rapid and cost-effective approach to defining resistance mechanisms and predicting phenotype, and strain type, for both clinical and epidemiological purposes. This retrospective study aimed to determine the efficacy of whole genome-based antimicrobial resistance prediction in clinical isolates of Escherichia coli and Klebsiella pneumoniae.Methods: Seventy-four E. coli and 69 K. pneumoniae bacteraemia isolates from Oxfordshire, UK, were sequenced (Illumina HiSeq 2000). Resistance phenotypes were predicted fromgenomic sequences using BLASTn-based comparisons of de novo-assembled contigs with a study database of>100 known resistance-associated loci, including plasmid-associated and chromosomal genes. Predictions were made for seven commonly used antimicrobials: amoxicillin, co-amoxiclav, ceftriaxone, ceftazidime, ciprofloxacin, gentamicin and meropenem. Comparisons were made with phenotypic results obtained in duplicate by broth dilution (BD Phoenix). Discrepancies, either between duplicate BD Phoenix results or between genotype and phenotype, were resolved with gradient diffusion analyses. Results:A wide variety of antimicrobial resistance genes were identified, including blaCTX-M, blaLEN, blaOKP, blaOXA, blaSHV, blaTEM, aac(3′)-Ia, aac-(3′)-IId, aac-(3′)-IIe, aac(6′)-Ib-cr, aadA1a, aadA4, aadA5, aadA16, aph(6′)-Id, aph(3′)-Ia, qnrB and qnrS, aswell as resistance-associatedmutations in chromosomal gyrA and parCgenes. The sensitivityofgenome- basedresistancepredictionacrossallantibiotics forbothspecieswas0.96(95%CI: 0.94-0.98)and the specificity was 0.97 (95%CI: 0.95-0.98). Very major and major error rates were 1.2%and 2.1%, respectively.Conclusions: Our method was as sensitive and specific as routinely deployed phenotypic methods. Validation against larger datasets and formal assessments of cost and turnaround time in a routine laboratory setting are warranted.

Original languageEnglish (US)
Article numberdkt180
Pages (from-to)2234-2244
Number of pages11
JournalJournal of Antimicrobial Chemotherapy
Volume68
Issue number10
DOIs
StatePublished - Oct 2013

Bibliographical note

Funding Information:
This work was supported by the Wellcome Trust (doctoral fellowship award to N. S.). It was also supported by the National Institute for Health Research (NIHR) under its Oxford Biomedical Research Centre Infection Theme and the UKCRC Modernising Medical Microbiology Consortium, the latter funded under the UKCRC Translational Infection Research Initiative supported by the Medical Research Council, the Biotechnology and Biological Sciences Research Council and the National Institute for Health Research on behalf of the Department of Health [Grant G0800778] and the Wellcome Trust [Grant 087646/Z/08/Z]. D. W. C. and T. E. A. P. are NIHR Senior Investigators. D. W. E. is an NIHR Doctoral Research Fellow. This material is also based partly upon work supported by the Office of Research and Development, Medical Research Service, Department of Veterans Affairs, grant # 1 I01 CX000192 01 (J. R. J.).

Keywords

  • Antibiotic
  • Gram-negative
  • Phenotype

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