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      A Comparative Metagenome Survey of the Fecal Microbiota of a Breast- and a Plant-Fed Asian Elephant Reveals an Unexpectedly High Diversity of Glycoside Hydrolase Family Enzymes

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          Abstract

          A phylogenetic and metagenomic study of elephant feces samples (derived from a three-weeks-old and a six-years-old Asian elephant) was conducted in order to describe the microbiota inhabiting this large land-living animal. The microbial diversity was examined via 16S rRNA gene analysis. We generated more than 44,000 GS-FLX+454 reads for each animal. For the baby elephant, 380 operational taxonomic units (OTUs) were identified at 97% sequence identity level; in the six-years-old animal, close to 3,000 OTUs were identified, suggesting high microbial diversity in the older animal. In both animals most OTUs belonged to Bacteroidetes and Firmicutes. Additionally, for the baby elephant a high number of Proteobacteria was detected. A metagenomic sequencing approach using Illumina technology resulted in the generation of 1.1 Gbp assembled DNA in contigs with a maximum size of 0.6 Mbp. A KEGG pathway analysis suggested high metabolic diversity regarding the use of polymers and aromatic and non-aromatic compounds. In line with the high phylogenetic diversity, a surprising and not previously described biodiversity of glycoside hydrolase (GH) genes was found. Enzymes of 84 GH families were detected. Polysaccharide utilization loci (PULs), which are found in Bacteroidetes, were highly abundant in the dataset; some of these comprised cellulase genes. Furthermore the highest coverage for GH5 and GH9 family enzymes was detected for Bacteroidetes, suggesting that bacteria of this phylum are mainly responsible for the degradation of cellulose in the Asian elephant. Altogether, this study delivers insight into the biomass conversion by one of the largest plant-fed and land-living animals.

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          GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions.

          J Besemer (2001)
          Improving the accuracy of prediction of gene starts is one of a few remaining open problems in computer prediction of prokaryotic genes. Its difficulty is caused by the absence of relatively strong sequence patterns identifying true translation initiation sites. In the current paper we show that the accuracy of gene start prediction can be improved by combining models of protein-coding and non-coding regions and models of regulatory sites near gene start within an iterative Hidden Markov model based algorithm. The new gene prediction method, called GeneMarkS, utilizes a non-supervised training procedure and can be used for a newly sequenced prokaryotic genome with no prior knowledge of any protein or rRNA genes. The GeneMarkS implementation uses an improved version of the gene finding program GeneMark.hmm, heuristic Markov models of coding and non-coding regions and the Gibbs sampling multiple alignment program. GeneMarkS predicted precisely 83.2% of the translation starts of GenBank annotated Bacillus subtilis genes and 94.4% of translation starts in an experimentally validated set of Escherichia coli genes. We have also observed that GeneMarkS detects prokaryotic genes, in terms of identifying open reading frames containing real genes, with an accuracy matching the level of the best currently used gene detection methods. Accurate translation start prediction, in addition to the refinement of protein sequence N-terminal data, provides the benefit of precise positioning of the sequence region situated upstream to a gene start. Therefore, sequence motifs related to transcription and translation regulatory sites can be revealed and analyzed with higher precision. These motifs were shown to possess a significant variability, the functional and evolutionary connections of which are discussed.
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            Ray Meta: scalable de novo metagenome assembly and profiling

            Voluminous parallel sequencing datasets, especially metagenomic experiments, require distributed computing for de novo assembly and taxonomic profiling. Ray Meta is a massively distributed metagenome assembler that is coupled with Ray Communities, which profiles microbiomes based on uniquely-colored k-mers. It can accurately assemble and profile a three billion read metagenomic experiment representing 1,000 bacterial genomes of uneven proportions in 15 hours with 1,024 processor cores, using only 1.5 GB per core. The software will facilitate the processing of large and complex datasets, and will help in generating biological insights for specific environments. Ray Meta is open source and available at http://denovoassembler.sf.net.
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              Assessing the complex sponge microbiota: core, variable and species-specific bacterial communities in marine sponges.

              Marine sponges are well known for their associations with highly diverse, yet very specific and often highly similar microbiota. The aim of this study was to identify potential bacterial sub-populations in relation to sponge phylogeny and sampling sites and to define the core bacterial community. 16S ribosomal RNA gene amplicon pyrosequencing was applied to 32 sponge species from eight locations around the world's oceans, thereby generating 2567 operational taxonomic units (OTUs at the 97% sequence similarity level) in total and up to 364 different OTUs per sponge species. The taxonomic richness detected in this study comprised 25 bacterial phyla with Proteobacteria, Chloroflexi and Poribacteria being most diverse in sponges. Among these phyla were nine candidate phyla, six of them found for the first time in sponges. Similarity comparison of bacterial communities revealed no correlation with host phylogeny but a tropical sub-population in that tropical sponges have more similar bacterial communities to each other than to subtropical sponges. A minimal core bacterial community consisting of very few OTUs (97%, 95% and 90%) was found. These microbes have a global distribution and are probably acquired via environmental transmission. In contrast, a large species-specific bacterial community was detected, which is represented by OTUs present in only a single sponge species. The species-specific bacterial community is probably mainly vertically transmitted. It is proposed that different sponges contain different bacterial species, however, these bacteria are still closely related to each other explaining the observed similarity of bacterial communities in sponges in this and previous studies. This global analysis represents the most comprehensive study of bacterial symbionts in sponges to date and provides novel insights into the complex structure of these unique associations.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                10 September 2014
                : 9
                : 9
                : e106707
                Affiliations
                [1 ]Universität Hamburg, Biozentrum Klein Flottbek, Abteilung für Mikrobiologie & Biotechnologie, Hamburg, Germany
                [2 ]Georg-August-University Göttingen, Institute of Microbiology and Genetics, Göttingen, Germany
                [3 ]University Medical Center Hamburg-Eppendorf, Bioinformatics Service Facility, Hamburg, Germany
                [4 ]University of Vienna, CUBE - Division for Computational Systems Biology, Department of Microbiology and Ecosystem Science, Vienna, Austria
                [5 ]Novozymes A/S, Microbial Discovery, Bagsværd, Denmark
                [6 ]Heinrich Pette Institute, Leibniz Institute for Experimental Virology, Hamburg, Germany
                Charité-University Medicine Berlin, Germany
                Author notes

                Competing Interests: Some of the authors are affiliated with Novozymes A/S. This does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: NI MSB WRS. Performed the experiments: NI SG JD BW. Analyzed the data: MA AP CS JS PBO TR DT. Contributed reagents/materials/analysis tools: RD AG MSB. Contributed to the writing of the manuscript: NI SG UR JT JC RD AG WRS.

                Article
                PONE-D-14-16767
                10.1371/journal.pone.0106707
                4160196
                25208077
                dc2244ec-e293-4227-b687-16811d888a06
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 17 April 2014
                : 29 July 2014
                Page count
                Pages: 12
                Funding
                This work was in part funded by the ministry of education and research “Bundesministerium für Bildung und Forschung” (BMBF; http://www.bmbf.de/) within the network program ExpresSys and the grant FKZ 0315586F to WRS. JT was funded by the German Academic Exchange program (DAAD; https://www.daad.de/de/index.html). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and life sciences
                Biotechnology
                Environmental Biotechnology
                Ecology
                Biodiversity
                Microbiology
                Molecular biology
                Molecular biology techniques
                Sequencing techniques
                Sequence analysis
                DNA sequence analysis
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. The data will be available upon publication. This project has been deposited at GenBank ( www.ncbi.nlm.nih.gov/genbank) using the BioProject number PRJNA240141. The sequences derived from Illumina and 454 sequencing were deposited in the NCBI Short Read Archive ( www.ncbi.nlm.nih.gov/sra) under the study accession number SRP040073. Genome assembly together with predicted gene models and annotation is available from www.jgi.doe.gov. (DOE Joint Genome Institute) under the IMG Project Id 50566.

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