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      Ruminant and chicken: important sources of campylobacteriosis in France despite a variation of source attribution in 2009 and 2015

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          Abstract

          Pathogen source attribution studies are a useful tool for identifying reservoirs of human infection. Based on Multilocus Sequence Typing (MLST) data, such studies have identified chicken as a major source of C. jejuni human infection. The use of whole genome sequence-based typing methods offers potential to improve the precision of attribution beyond that which is possible from 7 MLST loci. Using published data and 156 novel C. jejuni genomes sequenced in this study, we performed probabilistic host source attribution of clinical C. jejuni isolates from France using three types of genotype data: comparative genomic fingerprints; MLST genes; 15 host segregating genes previously identified by whole genome sequencing. Consistent with previous studies, chicken was an important source of campylobacteriosis in France (31–63% of clinical isolates assigned). There was also evidence that ruminants are a source (22–55% of clinical isolates assigned), suggesting that further investigation of potential transmission routes from ruminants to human would be useful. Additionally, we found evidence of environmental and pet sources. However, the relative importance as sources varied according to the year of isolation and the genotyping technique used. Annual variations in attribution emphasize the dynamic nature of zoonotic transmission and the need to perform source attribution regularly.

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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.
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            BIGSdb: Scalable analysis of bacterial genome variation at the population level

            Background The opportunities for bacterial population genomics that are being realised by the application of parallel nucleotide sequencing require novel bioinformatics platforms. These must be capable of the storage, retrieval, and analysis of linked phenotypic and genotypic information in an accessible, scalable and computationally efficient manner. Results The Bacterial Isolate Genome Sequence Database (BIGSDB) is a scalable, open source, web-accessible database system that meets these needs, enabling phenotype and sequence data, which can range from a single sequence read to whole genome data, to be efficiently linked for a limitless number of bacterial specimens. The system builds on the widely used mlstdbNet software, developed for the storage and distribution of multilocus sequence typing (MLST) data, and incorporates the capacity to define and identify any number of loci and genetic variants at those loci within the stored nucleotide sequences. These loci can be further organised into 'schemes' for isolate characterisation or for evolutionary or functional analyses. Isolates and loci can be indexed by multiple names and any number of alternative schemes can be accommodated, enabling cross-referencing of different studies and approaches. LIMS functionality of the software enables linkage to and organisation of laboratory samples. The data are easily linked to external databases and fine-grained authentication of access permits multiple users to participate in community annotation by setting up or contributing to different schemes within the database. Some of the applications of BIGSDB are illustrated with the genera Neisseria and Streptococcus. The BIGSDB source code and documentation are available at http://pubmlst.org/software/database/bigsdb/. Conclusions Genomic data can be used to characterise bacterial isolates in many different ways but it can also be efficiently exploited for evolutionary or functional studies. BIGSDB represents a freely available resource that will assist the broader community in the elucidation of the structure and function of bacteria by means of a population genomics approach.
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              Multilocus sequence typing system for Campylobacter jejuni.

              The gram-negative bacterium Campylobacter jejuni has extensive reservoirs in livestock and the environment and is a frequent cause of gastroenteritis in humans. To date, the lack of (i) methods suitable for population genetic analysis and (ii) a universally accepted nomenclature has hindered studies of the epidemiology and population biology of this organism. Here, a multilocus sequence typing (MLST) system for this organism is described, which exploits the genetic variation present in seven housekeeping loci to determine the genetic relationships among isolates. The MLST system was established using 194 C. jejuni isolates of diverse origins, from humans, animals, and the environment. The allelic profiles, or sequence types (STs), of these isolates were deposited on the Internet (http://mlst.zoo.ox.ac.uk), forming a virtual isolate collection which could be continually expanded. These data indicated that C. jejuni is genetically diverse, with a weakly clonal population structure, and that intra- and interspecies horizontal genetic exchange was common. Of the 155 STs observed, 51 (26% of the isolate collection) were unique, with the remainder of the collection being categorized into 11 lineages or clonal complexes of related STs with between 2 and 56 members. In some cases membership in a given lineage or ST correlated with the possession of a particular Penner HS serotype. Application of this approach to further isolate collections will enable an integrated global picture of C. jejuni epidemiology to be established and will permit more detailed studies of the population genetics of this organism.
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                Author and article information

                Contributors
                Katell.RIVOAL@anses.fr
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                18 June 2018
                18 June 2018
                2018
                : 8
                : 9305
                Affiliations
                [1 ]ISNI 0000 0001 0584 7022, GRID grid.15540.35, Hygiene and Quality of Poultry & Pork Products Unit, Laboratory of Ploufragan-Plouzané, , French Agency for Food Environmental and Occupational Health & Safety (Anses), ; Ploufragan, France
                [2 ]ISNI 0000 0001 2191 9284, GRID grid.410368.8, University of Rennes 1, ; Rennes, France
                [3 ]Viral Genetics & Biosafety Unit, Laboratory of Ploufragan-Plouzané, French Agency for Food Environmental and Occupational Health & Safety (Anses), Ploufragan, France
                [4 ]ISNI 0000 0001 2162 1699, GRID grid.7340.0, The Milner Centre for Evolution, Department of Biology and Biochemistry, , University of Bath, Claverton Down, ; Bath, United Kingdom
                [5 ]ISNI 0000 0001 0658 8800, GRID grid.4827.9, Swansea University, Medical School, Institute of Life Science, Singleton Campus, ; Swansea, United Kingdom
                [6 ]Department of Zoology, University of Oxford, South Parks Road, Oxford, OX1 3PS United Kingdom
                Author information
                http://orcid.org/0000-0002-1103-2425
                Article
                27558
                10.1038/s41598-018-27558-z
                6006168
                29915208
                7025385f-ef9d-4c15-926a-d3d2d7d34ed9
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 9 January 2018
                : 30 May 2018
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