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      Comparative analysis of the fecal bacterial community of five harbor seals ( Phoca vitulina)

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          The gut microbiota has many beneficial effects on host metabolism and health, and its composition is determined by numerous factors. It is also assumed that there was a co‐evolution of mammals and the bacteria inhabiting their gut. Current knowledge of the mammalian gut microbiota mainly derives from studies on humans and terrestrial animals, whereas those on marine mammals are sparse. However, they could provide additional information on influencing factors, such as the role of diet and co‐evolution with the host. In this study, we investigated and compared the bacterial diversity in the feces of five male harbor seals ( Phoca vitulina). Because this small population included two half‐brother pairs, each sharing a common father, it allowed an evaluation of the impact of host relatedness or genetic similarity on the gut microbial community. Fresh feces obtained from the seals by an enema were analyzed by fluorescence in situ hybridization and amplicon sequencing of 16S rRNA genes. The results showed that the bacterial communities in the seals' feces mainly consisted of the phyla Firmicutes (19–43%), Bacteroidetes (22–36%), Fusobacteria (18–32%), and Proteobacteria (5–17%) . Twenty‐one bacterial members present in the fecal samples of the five seals contributed an average relative abundance of 93.7  + 8.7% of the total fecal microbial community. Contrary to all expectations based on previous studies a comparison of the fecal community between individual seals showed a higher similarity between unrelated than related individuals.

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          Most cited references 47

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          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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            An obesity-associated gut microbiome with increased capacity for energy harvest.

            The worldwide obesity epidemic is stimulating efforts to identify host and environmental factors that affect energy balance. Comparisons of the distal gut microbiota of genetically obese mice and their lean littermates, as well as those of obese and lean human volunteers have revealed that obesity is associated with changes in the relative abundance of the two dominant bacterial divisions, the Bacteroidetes and the Firmicutes. Here we demonstrate through metagenomic and biochemical analyses that these changes affect the metabolic potential of the mouse gut microbiota. Our results indicate that the obese microbiome has an increased capacity to harvest energy from the diet. Furthermore, this trait is transmissible: colonization of germ-free mice with an 'obese microbiota' results in a significantly greater increase in total body fat than colonization with a 'lean microbiota'. These results identify the gut microbiota as an additional contributing factor to the pathophysiology of obesity.
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              Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences.

              In 2001 and 2002, we published two papers (Bioinformatics, 17, 282-283, Bioinformatics, 18, 77-82) describing an ultrafast protein sequence clustering program called cd-hit. This program can efficiently cluster a huge protein database with millions of sequences. However, the applications of the underlying algorithm are not limited to only protein sequences clustering, here we present several new programs using the same algorithm including cd-hit-2d, cd-hit-est and cd-hit-est-2d. Cd-hit-2d compares two protein datasets and reports similar matches between them; cd-hit-est clusters a DNA/RNA sequence database and cd-hit-est-2d compares two nucleotide datasets. All these programs can handle huge datasets with millions of sequences and can be hundreds of times faster than methods based on the popular sequence comparison and database search tools, such as BLAST.

                Author and article information

                John Wiley and Sons Inc. (Hoboken )
                14 May 2016
                October 2016
                : 5
                : 5 ( doiID: 10.1002/mbo3.2016.5.issue-5 )
                : 782-792
                [ 1 ]Leibniz Institute for Baltic Sea Research Seestrasse 15 Rostock D‐18119Germany
                [ 2 ]University of Rostock Albert‐Einstein‐Strasse 3 Rostock D‐18059Germany
                [ 3 ]Marine Science Center Am Yachthafen 3a Rostock D‐18119Germany
                [ 4 ]Present address: Leibniz Institute for Zoo and Wildlife Research Alfred‐Kowalke‐Strasse 17 D‐10315Berlin
                Author notes
                [* ] Correspondence

                Daniela Numberger, Leibniz Institute for Baltic Sea Research, University of Rostock Seestrasse 15, Albert‐Einstein‐Strasse 3, Rostock D‐18119, Germany. Tel: +49 30 5168 226; Fax: +49 30 5168 104; E‐Mail: numberger@

                © 2016 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                Page count
                Figures: 3, Tables: 3, Pages: 11, Words: 7714
                Funded by: Leibniz Association
                Original Research
                Original Research
                Custom metadata
                October 2016
                Converter:WILEY_ML3GV2_TO_NLMPMC version:4.9.4 mode:remove_FC converted:12.10.2016

                Microbiology & Virology

                microbiome., gut bacteria, microbial ecology


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