期刊
JOURNAL OF ANTIMICROBIAL CHEMOTHERAPY
卷 68, 期 10, 页码 2234-2244出版社
OXFORD UNIV PRESS
DOI: 10.1093/jac/dkt180
关键词
antibiotic; phenotype; Gram-negative
资金
- Wellcome Trust
- National Institute for Health Research (NIHR) under its Oxford Biomedical Research Centre Infection Theme
- UKCRC Modernising Medical Microbiology Consortium
- Medical Research Council
- Biotechnology and Biological Sciences Research Council
- National Institute for Health Research on behalf of the Department of Health [G0800778]
- Wellcome Trust [087646/Z/08/Z]
- Office of Research and Development, Medical Research Service, Department of Veterans Affairs [1 I01 CX000192 01]
- MRC [G0800778] Funding Source: UKRI
- Medical Research Council [G0800778] Funding Source: researchfish
- National Institute for Health Research [NF-SI-0512-10047, DRF-2010-03-40, NF-SI-0508-10279] Funding Source: researchfish
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 bla(CTX-M), bla(LEN), bla(OKP), bla(OXA), bla(SHV), bla(TEM), 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.
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