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      Genomics of Sponge-Associated Streptomyces spp. Closely Related to Streptomyces albus J1074: Insights into Marine Adaptation and Secondary Metabolite Biosynthesis Potential

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          Abstract

          A total of 74 actinomycete isolates were cultivated from two marine sponges, Geodia barretti and Phakellia ventilabrum collected at the same spot at the bottom of the Trondheim fjord (Norway). Phylogenetic analyses of sponge-associated actinomycetes based on the 16S rRNA gene sequences demonstrated the presence of species belonging to the genera Streptomyces, Nocardiopsis, Rhodococcus, Pseudonocardia and Micromonospora. Most isolates required sea water for growth, suggesting them being adapted to the marine environment. Phylogenetic analysis of Streptomyces spp. revealed two isolates that originated from different sponges and had 99.7% identity in their 16S rRNA gene sequences, indicating that they represent very closely related strains. Sequencing, annotation, and analyses of the genomes of these Streptomyces isolates demonstrated that they are sister organisms closely related to terrestrial Streptomyces albus J1074. Unlike S. albus J1074, the two sponge streptomycetes grew and differentiated faster on the medium containing sea water. Comparative genomics revealed several genes presumably responsible for partial marine adaptation of these isolates. Genome mining targeted to secondary metabolite biosynthesis gene clusters identified several of those, which were not present in S. albus J1074, and likely to have been retained from a common ancestor, or acquired from other actinomycetes. Certain genes and gene clusters were shown to be differentially acquired or lost, supporting the hypothesis of divergent evolution of the two Streptomyces species in different sponge hosts.

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          Most cited references31

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          Consed: a graphical tool for sequence finishing.

          Sequencing of large clones or small genomes is generally done by the shotgun approach (Anderson et al. 1982). This has two phases: (1) a shotgun phase in which a number of reads are generated from random subclones and assembled into contigs, followed by (2) a directed, or finishing phase in which the assembly is inspected for correctness and for various kinds of data anomalies (such as contaminant reads, unremoved vector sequence, and chimeric or deleted reads), additional data are collected to close gaps and resolve low quality regions, and editing is performed to correct assembly or base-calling errors. Finishing is currently a bottleneck in large-scale sequencing efforts, and throughput gains will depend both on reducing the need for human intervention and making it as efficient as possible. We have developed a finishing tool, consed, which attempts to implement these principles. A distinguishing feature relative to other programs is the use of error probabilities from our programs phred and phrap as an objective criterion to guide the entire finishing process. More information is available at http:// www.genome.washington.edu/consed/consed. html.
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            Toward an online repository of Standard Operating Procedures (SOPs) for (meta)genomic annotation.

            The methodologies used to generate genome and metagenome annotations are diverse and vary between groups and laboratories. Descriptions of the annotation process are helpful in interpreting genome annotation data. Some groups have produced Standard Operating Procedures (SOPs) that describe the annotation process, but standards are lacking for structure and content of these descriptions. In addition, there is no central repository to store and disseminate procedures and protocols for genome annotation. We highlight the importance of SOPs for genome annotation and endorse an online repository of SOPs.
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              antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers

              Microbial secondary metabolites are a potent source of antibiotics and other pharmaceuticals. Genome mining of their biosynthetic gene clusters has become a key method to accelerate their identification and characterization. In 2011, we developed antiSMASH, a web-based analysis platform that automates this process. Here, we present the highly improved antiSMASH 2.0 release, available at http://antismash.secondarymetabolites.org/. For the new version, antiSMASH was entirely re-designed using a plug-and-play concept that allows easy integration of novel predictor or output modules. antiSMASH 2.0 now supports input of multiple related sequences simultaneously (multi-FASTA/GenBank/EMBL), which allows the analysis of draft genomes comprising multiple contigs. Moreover, direct analysis of protein sequences is now possible. antiSMASH 2.0 has also been equipped with the capacity to detect additional classes of secondary metabolites, including oligosaccharide antibiotics, phenazines, thiopeptides, homo-serine lactones, phosphonates and furans. The algorithm for predicting the core structure of the cluster end product is now also covering lantipeptides, in addition to polyketides and non-ribosomal peptides. The antiSMASH ClusterBlast functionality has been extended to identify sub-clusters involved in the biosynthesis of specific chemical building blocks. The new features currently make antiSMASH 2.0 the most comprehensive resource for identifying and analyzing novel secondary metabolite biosynthetic pathways in microorganisms.
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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
                12 May 2014
                : 9
                : 5
                : e96719
                Affiliations
                [1 ]Department of Biotechnology, Norwegian University of Science and Technology, Trondheim, Norway
                [2 ]N.I. Vavilov Institute of General Genetics, Department of Computational Biology, Russian Academy of Sciences, Moscow, Russia
                [3 ]Institut fuer Genomforschung und Systembiologie, Centrum für Biotechnologie (CeBiTec), Universitaet Bielefeld, Bielefeld, Germany
                [4 ]A.A. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia
                [5 ]Faculty of Bioengineering and Bioinformatics, M.V.Lomonosov Moscow State University, Moscow, Russia
                University of Strathclyde, United Kingdom
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: DBM CR JK MSG SBZ. Performed the experiments: EI HB DBM ONS CR AA MEB MSG. Analyzed the data: EI DBM ONS CR MEB AA MSG SBZ. Contributed reagents/materials/analysis tools: DBM CR. Wrote the paper: DBM CR MSG SBZ. Read and approved of the final manuscript: EI DBM ONS HB CR MEB AA JK MSG SBZ.

                Article
                PONE-D-14-07661
                10.1371/journal.pone.0096719
                4018334
                24819608
                288e80ba-7ceb-4bf3-9050-cd04a64066c6
                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
                : 19 February 2014
                : 10 April 2014
                Page count
                Pages: 11
                Funding
                This work was supported by the Research Council of Norway. DBM, MEB and MSG were partially supported by Russian state contract 8049, RFBR grant 12-04-01105 and RAS program “Molecular and Cellular Biology”. CR acknowledges a grant by the German Federal Ministry for Education and Research (0316017A). 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
                Genetics
                Genomics
                Microbiology
                Ecology and Environmental Sciences

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