title: Predicting antimicrobial susceptibilities for Escherichia coli and Klebsiella pneumoniae isolates using whole genomic sequence data.
abstract: OBJECTIVE
  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 from genomic 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, as well as resistance-associated mutations in chromosomal gyrA and parC genes. The sensitivity of genome-based resistance prediction across all antibiotics for both species was 0.96 (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.
authors.affiliation: Nuffield Department of Clinical Medicine, University of Oxford, John Radcliffe Hospital (Level 5), Headley Way, Headington OX3 9DU, UK.
authors.forename: N
authors.initials: N
authors.lastname: Stoesser
authors.forename: E M
authors.initials: EM
authors.lastname: Batty
authors.forename: D W
authors.initials: DW
authors.lastname: Eyre
authors.forename: M
authors.initials: M
authors.lastname: Morgan
authors.forename: D H
authors.initials: DH
authors.lastname: Wyllie
authors.forename: C
authors.initials: C
authors.lastname: Del Ojo Elias
authors.forename: J R
authors.initials: JR
authors.lastname: Johnson
authors.forename: A S
authors.initials: AS
authors.lastname: Walker
authors.forename: T E A
authors.initials: TE
authors.lastname: Peto
authors.forename: D W
authors.initials: DW
authors.lastname: Crook
mesh_terms: D000900:Anti-Bacterial Agents / Q000494:pharmacology; D016470:Bacteremia / Q000382:microbiology; D004269:DNA, Bacterial / Q000235:genetics*; D024881:Drug Resistance, Bacterial; D004926:Escherichia coli / Q000187:drug effects* / Q000235:genetics* / Q000302:isolation & purification; D016680:Genome, Bacterial; D006801:Humans; D007711:Klebsiella pneumoniae / Q000187:drug effects* / Q000235:genetics* / Q000302:isolation & purification; D008826:Microbial Sensitivity Tests / Q000379:methods; D012680:Sensitivity and Specificity; D017422:Sequence Analysis, DNA; D006113:United Kingdom
chemical_list: D000900:Anti-Bacterial Agents; D004269:DNA, Bacterial
keywords: Gram-negative; antibiotic; phenotype