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

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          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 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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          Most cited references29

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          Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads.

          High-volume sequencing of DNA and RNA is now within reach of any research laboratory and is quickly becoming established as a key research tool. In many workflows, each of the short sequences ("reads") resulting from a sequencing run are first "mapped" (aligned) to a reference sequence to infer the read from which the genomic location derived, a challenging task because of the high data volumes and often large genomes. Existing read mapping software excel in either speed (e.g., BWA, Bowtie, ELAND) or sensitivity (e.g., Novoalign), but not in both. In addition, performance often deteriorates in the presence of sequence variation, particularly so for short insertions and deletions (indels). Here, we present a read mapper, Stampy, which uses a hybrid mapping algorithm and a detailed statistical model to achieve both speed and sensitivity, particularly when reads include sequence variation. This results in a higher useable sequence yield and improved accuracy compared to that of existing software.
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            Antimicrobial susceptibility testing: a review of general principles and contemporary practices.

            An important task of the clinical microbiology laboratory is the performance of antimicrobial susceptibility testing of significant bacterial isolates. The goals of testing are to detect possible drug resistance in common pathogens and to assure susceptibility to drugs of choice for particular infections. The most widely used testing methods include broth microdilution or rapid automated instrument methods that use commercially marketed materials and devices. Manual methods that provide flexibility and possible cost savings include the disk diffusion and gradient diffusion methods. Each method has strengths and weaknesses, including organisms that may be accurately tested by the method. Some methods provide quantitative results (eg, minimum inhibitory concentration), and all provide qualitative assessments using the categories susceptible, intermediate, or resistant. In general, current testing methods provide accurate detection of common antimicrobial resistance mechanisms. However, newer or emerging mechanisms of resistance require constant vigilance regarding the ability of each test method to accurately detect resistance.
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              Transforming clinical microbiology with bacterial genome sequencing.

              Whole-genome sequencing of bacteria has recently emerged as a cost-effective and convenient approach for addressing many microbiological questions. Here, we review the current status of clinical microbiology and how it has already begun to be transformed by using next-generation sequencing. We focus on three essential tasks: identifying the species of an isolate, testing its properties, such as resistance to antibiotics and virulence, and monitoring the emergence and spread of bacterial pathogens. We predict that the application of next-generation sequencing will soon be sufficiently fast, accurate and cheap to be used in routine clinical microbiology practice, where it could replace many complex current techniques with a single, more efficient workflow.
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                Author and article information

                Journal
                J Antimicrob Chemother
                J. Antimicrob. Chemother
                jac
                jac
                Journal of Antimicrobial Chemotherapy
                Oxford University Press
                0305-7453
                1460-2091
                October 2013
                30 May 2013
                30 May 2013
                : 68
                : 10
                : 2234-2244
                Affiliations
                [1 ]Nuffield Department of Clinical Medicine, University of Oxford , John Radcliffe Hospital (Level 5), Headley Way, Headington OX3 9DU, UK
                [2 ]John Radcliffe Hospital Microbiology Laboratory, John Radcliffe Hospital (Level 7) , Headley Way, Headington OX3 9DU, UK
                [3 ]The Wellcome Trust Centre for Human Genetics, Roosevelt Drive , Oxford OX3 7BN, UK
                [4 ]Health Protection Agency Collaborating Centre (Oxford), John Radcliffe Hospital (Level 5) , Headley Way, Headington OX3 9DU, UK
                [5 ]Infectious Diseases (111F), Veterans Affairs Medical Center, One Veterans Drive , Minneapolis, MN 55417, USA
                Author notes
                [* ]Corresponding author. Tel: +44-1865-220883; Fax: +44-1865-222195; E-mail: nicole.stoesser@ 123456ndm.ox.ac.uk
                Article
                dkt180
                10.1093/jac/dkt180
                3772739
                23722448
                4f575808-9373-47c5-a6f0-89400b57ec16
                © The Author 2013. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 17 February 2013
                : 18 March 2013
                : 22 March 2013
                : 7 April 2013
                Categories
                Original Research

                Oncology & Radiotherapy
                antibiotic,phenotype,gram-negative
                Oncology & Radiotherapy
                antibiotic, phenotype, gram-negative

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