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      Whole genome sequencing reveals within-host genetic changes in paired meningococcal carriage isolates from Ethiopia

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          Abstract

          Background

          Meningococcal colonization is a prerequisite for transmission and disease, but the bacterium only very infrequently causes disease while asymptomatic carriage is common. Carriage is highly dynamic, showing a great variety across time and space within and across populations, but also within individuals. The understanding of genetic changes in the meningococcus during carriage, when the bacteria resides in its natural niche, is important for understanding not only the carriage state, but the dynamics of the entire meningococcal population.

          Results

          Paired meningococcal isolates, obtained from 50 asymptomatic carriers about 2 months apart were analyzed with whole genome sequencing (WGS). Phylogenetic analysis revealed that most paired isolates from the same individual were closely related, and the average and median number of allelic differences between paired isolates defined as the same strain was 35. About twice as many differences were seen between isolates from different individuals within the same sequence type (ST). In 8%, different strains were detected at different time points. A difference in ST was observed in 6%, including an individual who was found to carry three different STs over the course of 9 weeks. One individual carried different strains from the same ST.

          In total, 566 of 1605 cgMLST genes had undergone within-host genetic changes in one or more pairs. The most frequently changed cgMLST gene was relA that was changed in 47% of pairs. Across the whole genome, pilE, differed mostly, in 85% of the pairs. The most frequent mechanisms of genetic difference between paired isolates were phase variation and recombination, including gene conversion. Different STs showed variation with regard to which genes that were most frequently changed, mostly due to absence/presence of phase variation.

          Conclusions

          This study revealed within-host genetic differences in meningococcal isolates during short-term asymptomatic carriage. The most frequently changed genes were genes belonging to the pilin family, the restriction/modification system, opacity proteins and genes involved in glycosylation. Higher resolution genome-wide sequence typing is necessary to resolve the diversity of isolates and reveals genetic differences not discovered by traditional typing schemes, and would be the preferred choice of technology.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12864-017-3806-3) contains supplementary material, which is available to authorized users.

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          Most cited references60

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          Neighbor-net: an agglomerative method for the construction of phylogenetic networks.

          We present Neighbor-Net, a distance based method for constructing phylogenetic networks that is based on the Neighbor-Joining (NJ) algorithm of Saitou and Nei. Neighbor-Net provides a snapshot of the data that can guide more detailed analysis. Unlike split decomposition, Neighbor-Net scales well and can quickly produce detailed and informative networks for several hundred taxa. We illustrate the method by reanalyzing three published data sets: a collection of 110 highly recombinant Salmonella multi-locus sequence typing sequences, the 135 "African Eve" human mitochondrial sequences published by Vigilant et al., and a collection of 12 Archeal chaperonin sequences demonstrating strong evidence for gene conversion. Neighbor-Net is available as part of the SplitsTree4 software package.
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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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              Hierarchical and Spatially Explicit Clustering of DNA Sequences with BAPS Software

              Phylogeographical analyses have become commonplace for a myriad of organisms with the advent of cheap DNA sequencing technologies. Bayesian model-based clustering is a powerful tool for detecting important patterns in such data and can be used to decipher even quite subtle signals of systematic differences in molecular variation. Here, we introduce two upgrades to the Bayesian Analysis of Population Structure (BAPS) software, which enable 1) spatially explicit modeling of variation in DNA sequences and 2) hierarchical clustering of DNA sequence data to reveal nested genetic population structures. We provide a direct interface to map the results from spatial clustering with Google Maps using the portal http://www.spatialepidemiology.net/ and illustrate this approach using sequence data from Borrelia burgdorferi. The usefulness of hierarchical clustering is demonstrated through an analysis of the metapopulation structure within a bacterial population experiencing a high level of local horizontal gene transfer. The tools that are introduced are freely available at http://www.helsinki.fi/bsg/software/BAPS/.
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                Author and article information

                Contributors
                gurokristine.barnes@fhi.no
                ola.brynildsrud@fhi.no
                bente.borud@fhi.no
                bekicho@gmail.com
                paul.kristiansen@fhi.no
                beyene88@gmail.com
                aseffaa@gmail.com
                dominique.caugant@fhi.no
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                25 May 2017
                25 May 2017
                2017
                : 18
                : 407
                Affiliations
                [1 ]ISNI 0000 0001 1541 4204, GRID grid.418193.6, Division for Infection Control and Environmental Health, , Norwegian Institute of Public Health, ; Oslo, Norway
                [2 ]ISNI 0000 0001 1541 4204, GRID grid.418193.6, WHO Collaborating Center for Reference and Research on Meningococci, , Norwegian Institute of Public Health, ; Oslo, Norway
                [3 ]Faculty of Medicine, University of Oslo, Oslo, Norway
                [4 ]Arba Minch College of Health Sciences, Arba Minch, Ethiopia
                [5 ]ISNI 0000 0000 4319 4715, GRID grid.418720.8, , Armauer Hansen Research Institute, ; Addis Ababa, Ethiopia
                [6 ]Hamlin Fistula Ethiopia, Addis Ababa, Ethiopia
                Article
                3806
                10.1186/s12864-017-3806-3
                5445459
                28545446
                2527be82-ac3d-4bc8-84f1-82561c7c4153
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 13 March 2017
                : 17 May 2017
                Funding
                Funded by: FundRef http://dx.doi.org/http://dx.doi.org/10.13039/501100005416, Norges Forskningsråd;
                Award ID: 220829
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Genetics
                neisseria meningitidis,carriage,ethiopia,meningitis belt,whole genome sequencing,core genome,genetics

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