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      Defining and Evaluating a Core Genome Multilocus Sequence Typing Scheme for Whole-Genome Sequence-Based Typing of Listeria monocytogenes

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          Abstract

          Whole-genome sequencing (WGS) has emerged today as an ultimate typing tool to characterize Listeria monocytogenes outbreaks. However, data analysis and interlaboratory comparability of WGS data are still challenging for most public health laboratories. Therefore, we have developed and evaluated a new L. monocytogenes typing scheme based on genome-wide gene-by-gene comparisons (core genome multilocus the sequence typing [cgMLST]) to allow for a unique typing nomenclature. Initially, we determined the breadth of the L. monocytogenes population based on MLST data with a Bayesian approach. Based on the genome sequence data of representative isolates for the whole population, cgMLST target genes were defined and reappraised with 67 L. monocytogenes isolates from two outbreaks and serotype reference strains. The Bayesian population analysis generated five L. monocytogenes groups. Using all available NCBI RefSeq genomes ( n = 36) and six additionally sequenced strains, all genetic groups were covered. Pairwise comparisons of these 42 genome sequences resulted in 1,701 cgMLST targets present in all 42 genomes with 100% overlap and ≥90% sequence similarity. Overall, ≥99.1% of the cgMLST targets were present in 67 outbreak and serotype reference strains, underlining the representativeness of the cgMLST scheme. Moreover, cgMLST enabled clustering of outbreak isolates with ≤10 alleles difference and unambiguous separation from unrelated outgroup isolates. In conclusion, the novel cgMLST scheme not only improves outbreak investigations but also enables, due to the availability of the automatically curated cgMLST nomenclature, interlaboratory exchange of data that are crucial, especially for rapid responses during transsectorial outbreaks.

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          Most cited references29

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

          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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            Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations

            Background During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have appeared in the scientific literature. Most of these methods utilize molecular markers for the inferences, while some are also capable of handling DNA sequence data. In a number of earlier works, we have introduced an array of statistical methods for population genetic inference that are implemented in the software BAPS. However, the complexity of biological problems related to genetic structure analysis keeps increasing such that in many cases the current methods may provide either inappropriate or insufficient solutions. Results We discuss the necessity of enhancing the statistical approaches to face the challenges posed by the ever-increasing amounts of molecular data generated by scientists over a wide range of research areas and introduce an array of new statistical tools implemented in the most recent version of BAPS. With these methods it is possible, e.g., to fit genetic mixture models using user-specified numbers of clusters and to estimate levels of admixture under a genetic linkage model. Also, alleles representing a different ancestry compared to the average observed genomic positions can be tracked for the sampled individuals, and a priori specified hypotheses about genetic population structure can be directly compared using Bayes' theorem. In general, we have improved further the computational characteristics of the algorithms behind the methods implemented in BAPS facilitating the analyses of large and complex datasets. In particular, analysis of a single dataset can now be spread over multiple computers using a script interface to the software. Conclusion The Bayesian modelling methods introduced in this article represent an array of enhanced tools for learning the genetic structure of populations. Their implementations in the BAPS software are designed to meet the increasing need for analyzing large-scale population genetics data. The software is freely downloadable for Windows, Linux and Mac OS X systems at .
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              MLST revisited: the gene-by-gene approach to bacterial genomics.

              Multilocus sequence typing (MLST) was proposed in 1998 as a portable sequence-based method for identifying clonal relationships among bacteria. Today, in the whole-genome era of microbiology, the need for systematic, standardized descriptions of bacterial genotypic variation remains a priority. Here, to meet this need, we draw on the successes of MLST and 16S rRNA gene sequencing to propose a hierarchical gene-by-gene approach that reflects functional and evolutionary relationships and catalogues bacteria 'from domain to strain'. Our gene-based typing approach using online platforms such as the Bacterial Isolate Genome Sequence Database (BIGSdb) allows the scalable organization and analysis of whole-genome sequence data.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                J Clin Microbiol
                J. Clin. Microbiol
                jcm
                jcm
                JCM
                Journal of Clinical Microbiology
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                0095-1137
                1098-660X
                1 July 2015
                September 2015
                1 July 2015
                : 53
                : 9
                : 2869-2876
                Affiliations
                [a ]German-Austrian Binational Consiliary Laboratory for Listeria, Austrian Agency for Health and Food Safety (AGES), Vienna, Austria
                [b ]Department for Periodontology, University Hospital Muenster, Muenster, Germany
                [c ]Institute of Hygiene, University Hospital Muenster, Muenster, Germany
                Author notes
                Address correspondence to Werner Ruppitsch, werner.ruppitsch@ 123456ages.at .

                Citation Ruppitsch W, Pietzka A, Prior K, Bletz S, Fernandez HL, Allerberger F, Harmsen D, Mellmann A. 2015. Defining and evaluating a core genome multilocus sequence typing scheme for whole-genome sequence-based typing of Listeria monocytogenes. J Clin Microbiol 53:2869–2876. doi: 10.1128/JCM.01193-15.

                Article
                01193-15
                10.1128/JCM.01193-15
                4540939
                26135865
                a2904df9-14da-4c86-bf22-5a810c5f61bb
                Copyright © 2015 Ruppitsch et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 4 May 2015
                : 5 June 2015
                : 13 June 2015
                Page count
                Figures: 2, Tables: 2, Equations: 0, References: 36, Pages: 8, Words: 7038
                Categories
                Bacteriology

                Microbiology & Virology
                Microbiology & Virology

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