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      PointFinder: a novel web tool for WGS-based detection of antimicrobial resistance associated with chromosomal point mutations in bacterial pathogens

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          Abstract

          Background

          Antibiotic resistance is a major health problem, as drugs that were once highly effective no longer cure bacterial infections. WGS has previously been shown to be an alternative method for detecting horizontally acquired antimicrobial resistance genes. However, suitable bioinformatics methods that can provide easily interpretable, accurate and fast results for antimicrobial resistance associated with chromosomal point mutations are still lacking.

          Methods

          Phenotypic antimicrobial susceptibility tests were performed on 150 isolates covering three different bacterial species: Salmonella enterica, Escherichia coli and Campylobacter jejuni. The web-server ResFinder-2.1 was used to identify acquired antimicrobial resistance genes and two methods, the novel PointFinder (using BLAST) and an in-house method (mapping of raw WGS reads), were used to identify chromosomal point mutations. Results were compared with phenotypic antimicrobial susceptibility testing results.

          Results

          A total of 685 different phenotypic tests associated with chromosomal resistance to quinolones, polymyxin, rifampicin, macrolides and tetracyclines resulted in 98.4% concordance. Eleven cases of disagreement between tested and predicted susceptibility were observed: two C. jejuni isolates with phenotypic fluoroquinolone resistance and two with phenotypic erythromycin resistance and five colistin-susceptible E. coli isolates with a detected pmrB V161G mutation when assembled with Velvet, but not when using SPAdes or when mapping the reads.

          Conclusions

          PointFinder proved, with high concordance between phenotypic and predicted antimicrobial susceptibility, to be a user-friendly web tool for detection of chromosomal point mutations associated with antimicrobial resistance.

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          Most cited references33

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          The comprehensive antibiotic resistance database.

          The field of antibiotic drug discovery and the monitoring of new antibiotic resistance elements have yet to fully exploit the power of the genome revolution. Despite the fact that the first genomes sequenced of free living organisms were those of bacteria, there have been few specialized bioinformatic tools developed to mine the growing amount of genomic data associated with pathogens. In particular, there are few tools to study the genetics and genomics of antibiotic resistance and how it impacts bacterial populations, ecology, and the clinic. We have initiated development of such tools in the form of the Comprehensive Antibiotic Research Database (CARD; http://arpcard.mcmaster.ca). The CARD integrates disparate molecular and sequence data, provides a unique organizing principle in the form of the Antibiotic Resistance Ontology (ARO), and can quickly identify putative antibiotic resistance genes in new unannotated genome sequences. This unique platform provides an informatic tool that bridges antibiotic resistance concerns in health care, agriculture, and the environment.
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            Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis

            The rise of antibiotic-resistant bacteria has led to an urgent need for rapid detection of drug resistance in clinical samples, and improvements in global surveillance. Here we show how de Bruijn graph representation of bacterial diversity can be used to identify species and resistance profiles of clinical isolates. We implement this method for Staphylococcus aureus and Mycobacterium tuberculosis in a software package (‘Mykrobe predictor') that takes raw sequence data as input, and generates a clinician-friendly report within 3 minutes on a laptop. For S. aureus, the error rates of our method are comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.1%/99.6% across 12 antibiotics (using an independent validation set, n=470). For M. tuberculosis, our method predicts resistance with sensitivity/specificity of 82.6%/98.5% (independent validation set, n=1,609); sensitivity is lower here, probably because of limited understanding of the underlying genetic mechanisms. We give evidence that minor alleles improve detection of extremely drug-resistant strains, and demonstrate feasibility of the use of emerging single-molecule nanopore sequencing techniques for these purposes.
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              Mechanisms of quinolone resistance in Escherichia coli and Salmonella: recent developments.

              Fluoroquinolones are broad-spectrum antimicrobials highly effective for treatment of a variety of clinical and veterinary infections. Their antibacterial activity is due to inhibition of DNA replication. Usually resistance arises spontaneously due to point mutations that result in amino acid substitutions within the topoisomerase subunits GyrA, GyrB, ParC or ParE, decreased expression of outer membrane porins, or overexpression of multidrug efflux pumps. In addition, the recent discovery of plasmid-mediated quinolone resistance could result in horizontal transfer of fluoroquinolone resistance between strains. Acquisition of high-level resistance appears to be a multifactorial process. Care needs to taken to avoid overuse of this important class of antimicrobial in both human and veterinary medicine to prevent an increase in the occurrence of resistant zoonotic and non-zoonotic bacterial pathogens that could subsequently cause human or animal infections.
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                Author and article information

                Journal
                J Antimicrob Chemother
                J. Antimicrob. Chemother
                jac
                Journal of Antimicrobial Chemotherapy
                Oxford University Press
                0305-7453
                1460-2091
                October 2017
                19 July 2017
                19 July 2017
                : 72
                : 10
                : 2764-2768
                Affiliations
                [1 ]National Food Institute, Technical University of Denmark, 2800 Kgs Lyngby, Denmark
                [2 ]Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, 2800 Kgs Lyngby, Denmark
                [3 ]Department of Microbiology and Infection Control, Statens Serum Institut, Copenhagen, Denmark
                Author notes
                [* ]Corresponding author. Tel: +45-35886281; E-mail: fmaa@ 123456food.dtu.dk
                Article
                dkx217
                10.1093/jac/dkx217
                5890747
                29091202
                0b556f43-cd05-45ed-a1ae-ba02bf9c8b59
                © The Author 2017. 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/4.0/), 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
                : 20 March 2017
                : 19 April 2017
                : 2 June 2017
                : 7 June 2017
                Page count
                Pages: 5
                Funding
                Funded by: Center for Genomic Epidemiology 10.13039/501100005191
                Award ID: 09–067103/DSF
                Funded by: Danish Council for Strategic Research 10.13039/100007398
                Categories
                Original Research

                Oncology & Radiotherapy
                Oncology & Radiotherapy

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