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      Comparison of classical multi-locus sequence typing software for next-generation sequencing data

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          Abstract

          Multi-locus sequence typing (MLST) is a widely used method for categorizing bacteria. Increasingly, MLST is being performed using next-generation sequencing (NGS) data by reference laboratories and for clinical diagnostics. Many software applications have been developed to calculate sequence types from NGS data; however, there has been no comprehensive review to date on these methods. We have compared eight of these applications against real and simulated data, and present results on: (1) the accuracy of each method against traditional typing methods, (2) the performance on real outbreak datasets, (3) the impact of contamination and varying depth of coverage, and (4) the computational resource requirements.

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          Multilocus sequence typing: a portable approach to the identification of clones within populations of pathogenic microorganisms.

          M. C. J. Maiden, J. Bygraves, E Feil … (1998)
          Traditional and molecular typing schemes for the characterization of pathogenic microorganisms are poorly portable because they index variation that is difficult to compare among laboratories. To overcome these problems, we propose multilocus sequence typing (MLST), which exploits the unambiguous nature and electronic portability of nucleotide sequence data for the characterization of microorganisms. To evaluate MLST, we determined the sequences of approximately 470-bp fragments from 11 housekeeping genes in a reference set of 107 isolates of Neisseria meningitidis from invasive disease and healthy carriers. For each locus, alleles were assigned arbitrary numbers and dendrograms were constructed from the pairwise differences in multilocus allelic profiles by cluster analysis. The strain associations obtained were consistent with clonal groupings previously determined by multilocus enzyme electrophoresis. A subset of six gene fragments was chosen that retained the resolution and congruence achieved by using all 11 loci. Most isolates from hyper-virulent lineages of serogroups A, B, and C meningococci were identical for all loci or differed from the majority type at only a single locus. MLST using six loci therefore reliably identified the major meningococcal lineages associated with invasive disease. MLST can be applied to almost all bacterial species and other haploid organisms, including those that are difficult to cultivate. The overwhelming advantage of MLST over other molecular typing methods is that sequence data are truly portable between laboratories, permitting one expanding global database per species to be placed on a World-Wide Web site, thus enabling exchange of molecular typing data for global epidemiology via the Internet.
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            Comparison of Next-Generation Sequencing Systems

            Lin Liu, Yinhu Li, Siliang Li … (2012)
            With fast development and wide applications of next-generation sequencing (NGS) technologies, genomic sequence information is within reach to aid the achievement of goals to decode life mysteries, make better crops, detect pathogens, and improve life qualities. NGS systems are typically represented by SOLiD/Ion Torrent PGM from Life Sciences, Genome Analyzer/HiSeq 2000/MiSeq from Illumina, and GS FLX Titanium/GS Junior from Roche. Beijing Genomics Institute (BGI), which possesses the world's biggest sequencing capacity, has multiple NGS systems including 137 HiSeq 2000, 27 SOLiD, one Ion Torrent PGM, one MiSeq, and one 454 sequencer. We have accumulated extensive experience in sample handling, sequencing, and bioinformatics analysis. In this paper, technologies of these systems are reviewed, and first-hand data from extensive experience is summarized and analyzed to discuss the advantages and specifics associated with each sequencing system. At last, applications of NGS are summarized.
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              Complete genome sequence of a multiple drug resistant Salmonella enterica serovar Typhi CT18.

              J. Parkhill, G. Dougan, K. D. James … (2001)
              Salmonella enterica serovar Typhi (S. typhi) is the aetiological agent of typhoid fever, a serious invasive bacterial disease of humans with an annual global burden of approximately 16 million cases, leading to 600,000 fatalities. Many S. enterica serovars actively invade the mucosal surface of the intestine but are normally contained in healthy individuals by the local immune defence mechanisms. However, S. typhi has evolved the ability to spread to the deeper tissues of humans, including liver, spleen and bone marrow. Here we have sequenced the 4,809,037-base pair (bp) genome of a S. typhi (CT18) that is resistant to multiple drugs, revealing the presence of hundreds of insertions and deletions compared with the Escherichia coli genome, ranging in size from single genes to large islands. Notably, the genome sequence identifies over two hundred pseudogenes, several corresponding to genes that are known to contribute to virulence in Salmonella typhimurium. This genetic degradation may contribute to the human-restricted host range for S. typhi. CT18 harbours a 218,150-bp multiple-drug-resistance incH1 plasmid (pHCM1), and a 106,516-bp cryptic plasmid (pHCM2), which shows recent common ancestry with a virulence plasmid of Yersinia pestis.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Microb Genom
                Journal ID (iso-abbrev): Microb Genom
                Journal ID (publisher-id): MGen
                Title: Microbial Genomics
                Publisher: Microbiology Society
                ISSN (Electronic): 2057-5858
                Publication date Collection: August 2017
                Publication date (Electronic): 4 July 2017
                Volume: 3
                Issue: 8
                Electronic Location Identifier: e000124
                Affiliations
                [ 1​ ]Pathogen Genomics, Wellcome Trust Sanger Institute, Wellcome Genome Campus , Hinxton, Cambridgeshire CB10 1SA, UK
                [ 2​ ]Microbiology and Infection, University of Warwick , Coventry, UK
                [ 3​ ]Enteric Diseases Laboratory Branch, Centers for Disease Control and Prevention , Atlanta, GA, USA
                [ 4​ ]Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, University of Melbourne, Peter Doherty Institute for Infection and Immunity , Melbourne, Australia
                [ 5​ ]Pathogen Informatics, Wellcome Trust Sanger Institute, Wellcome Genome Campus , Hinxton, Cambridgeshire, UK
                [ 6​ ]Center for Food Safety, College of Agricultural and Environmental Sciences, University of Georgia , Griffin, GA, USA
                Author notes
                *Correspondence: Andrew J. Page, ap13@ 123456sanger.ac.uk

                All supporting data, code and protocols have been provided within the article or through supplementary data files. Two supplementary tables are available with the online Supplementary Material.

                Article
                Publisher ID: mgen000124
                DOI: 10.1099/mgen.0.000124
                PMC ID: 5610716
                SO-VID: c08f6412-bd11-4896-b2bf-5de42eee8072
                Copyright © © 2017 The Authors
                License:

                This is an open access article under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 15 March 2017
                Date accepted : 07 June 2017
                Funding
                Funded by: Wellcome Trust
                Award ID: 098051
                Funded by: Wellcome Trust
                Award ID: 098051
                Categories
                Subject: Review
                Subject: Microbial Evolution and Epidemiology
                Subject: Population Genomics
                Custom metadata
                OpenAccessEmbargo 0

                Keywords: mlst,multi-locus sequence typing,software comparison,next-generation sequencing
                Data availability:
                Keywords: mlst, multi-locus sequence typing, software comparison, next-generation sequencing

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