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      Adaptation of Surface-Associated Bacteria to the Open Ocean: A Genomically Distinct Subpopulation of Phaeobacter gallaeciensis Colonizes Pacific Mesozooplankton

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          Abstract

          The marine Roseobacter group encompasses numerous species which occupy a large variety of ecological niches. However, members of the genus Phaeobacter are specifically adapted to a surface-associated lifestyle and have so far been found nearly exclusively in disjunct, man-made environments including shellfish and fish aquacultures, as well as harbors. Therefore, the possible natural habitats, dispersal and evolution of Phaeobacter spp. have largely remained obscure. Applying a high-throughput cultivation strategy along a longitudinal Pacific transect, the present study revealed for the first time a widespread natural occurrence of Phaeobacter in the marine pelagial. These bacteria were found to be specifically associated to mesoplankton where they constitute a small but detectable proportion of the bacterial community. The 16S rRNA gene sequences of 18 isolated strains were identical to that of Phaeobacter gallaeciensis DSM26640 T but sequences of internal transcribed spacer and selected genomes revealed that the strains form a distinct clade within P. gallaeciensis. The genomes of the Pacific and the aquaculture strains were highly conserved and had a fraction of the core genome of 89.6%, 80 synteny breakpoints, and differed 2.2% in their nucleotide sequences. Diversification likely occurred through neutral mutations. However, the Pacific strains exclusively contained two active Type I restriction modification systems which is commensurate with a reduced acquisition of mobile elements in the Pacific clade. The Pacific clade of P. gallaeciensis also acquired a second, homolog phosphonate transport system compared to all other P. gallaeciensis. Our data indicate that a previously unknown, distinct clade of P. gallaeciensis acquired a limited number of clade-specific genes that were relevant for its association with mesozooplankton and for colonization of the marine pelagial. The divergence of the Pacific clade most likely was driven by the adaptation to this novel ecological niche rather than by geographic isolation.

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          BIONJ: an improved version of the NJ algorithm based on a simple model of sequence data.

          O. Gascuel (1997)
          We propose an improved version of the neighbor-joining (NJ) algorithm of Saitou and Nei. This new algorithm, BIONJ, follows the same agglomerative scheme as NJ, which consists of iteratively picking a pair of taxa, creating a new mode which represents the cluster of these taxa, and reducing the distance matrix by replacing both taxa by this node. Moreover, BIONJ uses a simple first-order model of the variances and covariances of evolutionary distance estimates. This model is well adapted when these estimates are obtained from aligned sequences. At each step it permits the selection, from the class of admissible reductions, of the reduction which minimizes the variance of the new distance matrix. In this way, we obtain better estimates to choose the pair of taxa to be agglomerated during the next steps. Moreover, in comparison with NJ's estimates, these estimates become better and better as the algorithm proceeds. BIONJ retains the good properties of NJ--especially its low run time. Computer simulations have been performed with 12-taxon model trees to determine BIONJ's efficiency. When the substitution rates are low (maximum pairwise divergence approximately 0.1 substitutions per site) or when they are constant among lineages, BIONJ is only slightly better than NJ. When the substitution rates are higher and vary among lineages,BIONJ clearly has better topological accuracy. In the latter case, for the model trees and the conditions of evolution tested, the topological error reduction is on the average around 20%. With highly-varying-rate trees and with high substitution rates (maximum pairwise divergence approximately 1.0 substitutions per site), the error reduction may even rise above 50%, while the probability of finding the correct tree may be augmented by as much as 15%.
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            PopGenome: An Efficient Swiss Army Knife for Population Genomic Analyses in R

            Although many computer programs can perform population genetics calculations, they are typically limited in the analyses and data input formats they offer; few applications can process the large data sets produced by whole-genome resequencing projects. Furthermore, there is no coherent framework for the easy integration of new statistics into existing pipelines, hindering the development and application of new population genetics and genomics approaches. Here, we present PopGenome, a population genomics package for the R software environment (a de facto standard for statistical analyses). PopGenome can efficiently process genome-scale data as well as large sets of individual loci. It reads DNA alignments and single-nucleotide polymorphism (SNP) data sets in most common formats, including those used by the HapMap, 1000 human genomes, and 1001 Arabidopsis genomes projects. PopGenome also reads associated annotation files in GFF format, enabling users to easily define regions or classify SNPs based on their annotation; all analyses can also be applied to sliding windows. PopGenome offers a wide range of diverse population genetics analyses, including neutrality tests as well as statistics for population differentiation, linkage disequilibrium, and recombination. PopGenome is linked to Hudson’s MS and Ewing’s MSMS programs to assess statistical significance based on coalescent simulations. PopGenome’s integration in R facilitates effortless and reproducible downstream analyses as well as the production of publication-quality graphics. Developers can easily incorporate new analyses methods into the PopGenome framework. PopGenome and R are freely available from CRAN (http://cran.r-project.org/) for all major operating systems under the GNU General Public License.
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              genoPlotR: comparative gene and genome visualization in R

              Summary: The amount of gene and genome data obtained by next-generation sequencing technologies generates a need for comparative visualization tools. Complementing existing software for comparison and exploration of genomics data, genoPlotR automatically creates publication-grade linear maps of gene and genomes, in a highly automatic, flexible and reproducible way. Availability: genoPlotR is a platform-independent R package, available with full source code under a GPL2 license at R-Forge: http://genoplotr.r-forge.r-project.org/ Contact: lionel.guy@ebc.uu.se
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                31 August 2017
                2017
                : 8
                : 1659
                Affiliations
                Leibniz-Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen Braunschweig, Germany
                Author notes

                Edited by: Bernd Wemheuer, University of New South Wales, Australia

                Reviewed by: James T. Hollibaugh, University of Georgia, United States; Julia Grosse, GEOMAR Helmholtz Centre for Ocean Research Kiel (HZ), Germany

                *Correspondence: Heike M. Freese, heike.freese@ 123456dsmz.de

                This article was submitted to Aquatic Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2017.01659
                5583230
                28912769
                f81e195f-047f-44e9-8911-ebcd58e2bddd
                Copyright © 2017 Freese, Methner and Overmann.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 28 April 2017
                : 16 August 2017
                Page count
                Figures: 5, Tables: 5, Equations: 0, References: 86, Pages: 12, Words: 0
                Funding
                Funded by: Deutsche Forschungsgemeinschaft 10.13039/501100001659
                Award ID: TRR 51/2 TA07
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                phaeobacter gallaeciensis,zooplankton,attached bacteria,bacterial adaptation,genome evolution,high-throughput cultivation

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