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      Whole genome sequencing reveals extended natural transformation in Campylobacter impacting diagnostics and the pathogens adaptive potential

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          Abstract

          Campylobacter is the major bacterial agent of human gastroenteritis worldwide and represents a crucial global public health burden. Species differentiation of C. jejuni and C. coli and phylogenetic analysis is challenged by inter-species horizontal gene transfer. Routine real-time PCR on more than 4000  C. jejuni and C. coli field strains identified isolates with ambiguous PCR results for species differentiation, in particular, from the isolation source eggs. K-mer analysis of whole genome sequencing data indicated the presence of C. coli hybrid strains with huge amounts of C. jejuni introgression. Recombination events were distributed over the whole chromosome. MLST typing was impaired, since C. jejuni sequences were also found in six of the seven housekeeping genes. cgMLST suggested that the strains were phylogenetically unrelated. Intriguingly, the strains shared a stress response set of C. jejuni variant genes, with proposed roles in oxidative, osmotic and general stress defence, chromosome maintenance and repair, membrane transport, cell wall and capsular biosynthesis and chemotaxis. The results have practical impact on routine typing and on the understanding of the functional adaption to harsh environments, enabling successful spreading and persistence of Campylobacter.

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          Most cited references41

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          ClonalFrameML: Efficient Inference of Recombination in Whole Bacterial Genomes

          Recombination is an important evolutionary force in bacteria, but it remains challenging to reconstruct the imports that occurred in the ancestry of a genomic sample. Here we present ClonalFrameML, which uses maximum likelihood inference to simultaneously detect recombination in bacterial genomes and account for it in phylogenetic reconstruction. ClonalFrameML can analyse hundreds of genomes in a matter of hours, and we demonstrate its usefulness on simulated and real datasets. We find evidence for recombination hotspots associated with mobile elements in Clostridium difficile ST6 and a previously undescribed 310kb chromosomal replacement in Staphylococcus aureus ST582. ClonalFrameML is freely available at http://clonalframeml.googlecode.com/.
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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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              Rapid and precise alignment of raw reads against redundant databases with KMA

              Background As the cost of sequencing has declined, clinical diagnostics based on next generation sequencing (NGS) have become reality. Diagnostics based on sequencing will require rapid and precise mapping against redundant databases because some of the most important determinants, such as antimicrobial resistance and core genome multilocus sequence typing (MLST) alleles, are highly similar to one another. In order to facilitate this, a novel mapping method, KMA (k-mer alignment), was designed. KMA is able to map raw reads directly against redundant databases, it also scales well for large redundant databases. KMA uses k-mer seeding to speed up mapping and the Needleman-Wunsch algorithm to accurately align extensions from k-mer seeds. Multi-mapping reads are resolved using a novel sorting scheme (ConClave scheme), ensuring an accurate selection of templates. Results The functionality of KMA was compared with SRST2, MGmapper, BWA-MEM, Bowtie2, Minimap2 and Salmon, using both simulated data and a dataset of Escherichia coli mapped against resistance genes and core genome MLST alleles. KMA outperforms current methods with respect to both accuracy and speed, while using a comparable amount of memory. Conclusion With KMA, it was possible map raw reads directly against redundant databases with high accuracy, speed and memory efficiency. Electronic supplementary material The online version of this article (10.1186/s12859-018-2336-6) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Kerstin.stingl@bfr.bund.de
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                28 February 2020
                28 February 2020
                2020
                : 10
                : 3686
                Affiliations
                [1 ]ISNI 0000 0000 8852 3623, GRID grid.417830.9, German Federal Institute for Risk Assessment, Department of Biological Safety, National Reference Laboratory for Campylobacter, ; Berlin, Germany
                [2 ]ISNI 0000 0000 8852 3623, GRID grid.417830.9, German Federal Institute for Risk Assessment, Department of Biological Safety, Study Centre for Genome Sequencing and Analysis, ; Berlin, Germany
                [3 ]ISNI 0000 0001 0940 3744, GRID grid.13652.33, Robert Koch Institute, Microbial Genomics, ; Berlin, Germany
                Author information
                http://orcid.org/0000-0003-2031-8991
                http://orcid.org/0000-0002-3902-8524
                http://orcid.org/0000-0002-3363-8225
                http://orcid.org/0000-0002-2225-7267
                Article
                60320
                10.1038/s41598-020-60320-y
                7048796
                32111893
                dd1b8ed0-96da-497c-9355-ffc643f6529c
                © The Author(s) 2020

                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
                : 7 October 2019
                : 5 February 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research);
                Award ID: IP10/01KI1725F
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100008751, Federal Ministry of Food and Agriculture | Bundesinstitut für Risikobewertung (Federal Institute for Risk Assessment);
                Award ID: 1322-646 SFB
                Award Recipient :
                Categories
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                © The Author(s) 2020

                Uncategorized
                bacterial genomics,food microbiology,pathogens
                Uncategorized
                bacterial genomics, food microbiology, pathogens

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