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

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 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.

Keywords: Gram-negative; antibiotic; phenotype.

Figure 1.

Sampling frame and processing of isolates. ^aThe study time period for K. pneumoniae was extended to find similar numbers of organisms across both species groups. ^bLosses in retrieval rates were mostly due to the fact that repeat isolates from individuals were not routinely stored; other missing isolates could not be found in the routine laboratory freezer.

Figure 2.

Comparisons of genotypic susceptibility prediction, BD Phoenix phenotype and results of gradient diffusion analyses for discrepancies in either (i) duplicate BD Phoenix testing or (ii) genotypic prediction and concordant BD Phoenix phenotype, for both species across all seven antimicrobials.