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      ResFinder 4.0 for predictions of phenotypes from genotypes

      research-article
      d1 , d1 , d2 , d3 , d4 , d5 , d6 , d7 , d8 , d1 , d9 , d1 , d1 , d10 , d11 , d12 , d10 , d11 , d13 , d13 , d13 , d14 , d15 , d15 , d15 , d15 , d16 , d17 , d16 , d18 , d18 , d19 , d20 , d20 , d21 , d22 , d22 , d23 , d24 , d23 , d1 , d1
      Journal of Antimicrobial Chemotherapy
      Oxford University Press

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          Abstract

          Objectives

          WGS-based antimicrobial susceptibility testing (AST) is as reliable as phenotypic AST for several antimicrobial/bacterial species combinations. However, routine use of WGS-based AST is hindered by the need for bioinformatics skills and knowledge of antimicrobial resistance (AMR) determinants to operate the vast majority of tools developed to date. By leveraging on ResFinder and PointFinder, two freely accessible tools that can also assist users without bioinformatics skills, we aimed at increasing their speed and providing an easily interpretable antibiogram as output.

          Methods

          The ResFinder code was re-written to process raw reads and use Kmer-based alignment. The existing ResFinder and PointFinder databases were revised and expanded. Additional databases were developed including a genotype-to-phenotype key associating each AMR determinant with a phenotype at the antimicrobial compound level, and species-specific panels for in silico antibiograms. ResFinder 4.0 was validated using Escherichia coli ( n = 584), Salmonella spp. ( n = 1081), Campylobacter jejuni ( n = 239), Enterococcus faecium ( n = 106), Enterococcus faecalis ( n = 50) and Staphylococcus aureus ( n = 163) exhibiting different AST profiles, and from different human and animal sources and geographical origins.

          Results

          Genotype–phenotype concordance was ≥95% for 46/51 and 25/32 of the antimicrobial/species combinations evaluated for Gram-negative and Gram-positive bacteria, respectively. When genotype–phenotype concordance was <95%, discrepancies were mainly linked to criteria for interpretation of phenotypic tests and suboptimal sequence quality, and not to ResFinder 4.0 performance.

          Conclusions

          WGS-based AST using ResFinder 4.0 provides in silico antibiograms as reliable as those obtained by phenotypic AST at least for the bacterial species/antimicrobial agents of major public health relevance considered.

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          Most cited references45

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          SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing.

          The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.
            • Record: found
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            Identification of acquired antimicrobial resistance genes

            Objectives Identification of antimicrobial resistance genes is important for understanding the underlying mechanisms and the epidemiology of antimicrobial resistance. As the costs of whole-genome sequencing (WGS) continue to decline, it becomes increasingly available in routine diagnostic laboratories and is anticipated to substitute traditional methods for resistance gene identification. Thus, the current challenge is to extract the relevant information from the large amount of generated data. Methods We developed a web-based method, ResFinder that uses BLAST for identification of acquired antimicrobial resistance genes in whole-genome data. As input, the method can use both pre-assembled, complete or partial genomes, and short sequence reads from four different sequencing platforms. The method was evaluated on 1862 GenBank files containing 1411 different resistance genes, as well as on 23 de- novo-sequenced isolates. Results When testing the 1862 GenBank files, the method identified the resistance genes with an ID = 100% (100% identity) to the genes in ResFinder. Agreement between in silico predictions and phenotypic testing was found when the method was further tested on 23 isolates of five different bacterial species, with available phenotypes. Furthermore, ResFinder was evaluated on WGS chromosomes and plasmids of 30 isolates. Seven of these isolates were annotated to have antimicrobial resistance, and in all cases, annotations were compatible with the ResFinder results. Conclusions A web server providing a convenient way of identifying acquired antimicrobial resistance genes in completely sequenced isolates was created. ResFinder can be accessed at www.genomicepidemiology.org. ResFinder will continuously be updated as new resistance genes are identified.
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              PointFinder: a novel web tool for WGS-based detection of antimicrobial resistance associated with chromosomal point mutations in bacterial pathogens

              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.

                Author and article information

                Journal
                J Antimicrob Chemother
                J Antimicrob Chemother
                jac
                Journal of Antimicrobial Chemotherapy
                Oxford University Press
                0305-7453
                1460-2091
                December 2020
                11 August 2020
                11 August 2020
                : 75
                : 12
                : 3491-3500
                Affiliations
                [d1 ] Technical University of Denmark, National Food Institute, European Union Reference Laboratory for Antimicrobial Resistance, WHO Collaborating Centre for Antimicrobial Resistance in Foodborne Pathogens and Genomics, FAO Reference Laboratory for Antimicrobial Resistance , Kgs. Lyngby, Denmark
                [d2 ] Université de Paris, IAME, INSERM , Paris, France
                [d3 ] Department of Environmental and Occupational Health Sciences, University of Washington , Seattle, WA, USA
                [d4 ] Institute of Microbiology and Epizootics, Centre for Infection Medicine, Department of Veterinary Medicine, Freie Universität Berlin , Berlin, Germany
                [d5 ] Rennes University Hospital, Department of Clinical Microbiology , Rennes, France
                [d6 ] National Reference Center for Antimicrobial Resistance (lab Enterococci) , Rennes, France
                [d7 ] University of Rennes 1, INSERM U1230 , Rennes, France
                [d8 ] Faculty of Medicine Paris Descartes, Bacteriology , Paris, France
                [d9 ] Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen , Copenhagen N, Denmark
                [d10 ] Institute of Medical Microbiolgy, Justus Liebig University Giessen , Giessen, Germany
                [d11 ] German Center for Infection Research, site Giessen-Marburg-Langen, Justus Liebig University Giessen , Giessen, Germany
                [d12 ] Institute of Hygiene and Environmental Medicine, Justus Liebig University Giessen , Giessen, Germany
                [d13 ] Robert Koch Institute, Wernigerode Branch, Department of Infectious Diseases, Division of Nosocomial Pathogens and Antibiotic Resistances , Wernigerode, Germany
                [d14 ] German Federal Institute for Risk Assessment, Department of Biological Safety, National Reference Laboratory for Campylobacter , Berlin, Germany
                [d15 ] Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute, University of Antwerp , Belgium
                [d16 ] Department of Clinical Microbiology, Hvidovre University Hospital , Hvidovre, Denmark
                [d17 ] Department of Clinical Medicine, University of Copenhagen , Copenhagen, Denmark
                [d18 ] Animal and Plant Health Agency , Addlestone, Surrey, UK
                [d19 ] ANSES, Ploufragan-Plouzané-Niort Laboratory , Ploufragan, France
                [d20 ] Finnish Food Authority , Helsinki, Finland
                [d21 ] National Veterinary Research Institute , Pulawy, Poland
                [d22 ] National Institute of Agrarian and Veterinary Research (INIAV), National Reference Laboratory for Animal Health , Oeiras, Portugal
                [d23 ] Laboratoire National de Santé, Epidemiology and Microbial Genomics , Dudelange, Luxembourg
                [d24 ] Laboratoire de Médecine Vétérinaire de l'Etat, Veterinary Services Administration , Dudelange, Luxembourg
                Author notes
                Corresponding author. E-mail: fmaa@ 123456food.dtu.dk

                Valeria Bortolaia and Rolf S. Kaas contributed equally.

                Author information
                http://orcid.org/0000-0002-5050-8668
                http://orcid.org/0000-0002-6303-8212
                http://orcid.org/0000-0003-4026-9912
                http://orcid.org/0000-0001-7652-1898
                http://orcid.org/0000-0002-7116-2723
                Article
                dkaa345
                10.1093/jac/dkaa345
                7662176
                32780112
                b01c65fb-d64f-4996-9657-069647d719fa
                © The Author(s) 2020. 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
                : 17 April 2020
                : 30 June 2020
                Page count
                Pages: 10
                Funding
                Funded by: European Union Horizon 2020;
                Award ID: 643476
                Funded by: Novo Nordisk Foundation, DOI 10.13039/501100009708;
                Award ID: NNF16OC0021856
                Funded by: Global Surveillance of Antimicrobial Resistance;
                Funded by: German Center of Infection Research;
                Funded by: Zoonoses Network ‘ESBL;
                Funded by: German Federal Ministry of Education and Research;
                Award ID: 8000 701-3
                Award ID: 01KI1313G
                Award ID: TI06.001
                Award ID: 8032808811
                Award ID: 8032808818
                Award ID: 8032808820
                Funded by: BMBF, DOI 10.13039/501100002347;
                Award ID: 03ZZ0815A
                Categories
                Original Research
                AcademicSubjects/MED00740
                AcademicSubjects/MED00290
                AcademicSubjects/MED00230

                Oncology & Radiotherapy
                Oncology & Radiotherapy

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