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      The Genome Sequences of Cellulomonas fimi and “ Cellvibrio gilvus” Reveal the Cellulolytic Strategies of Two Facultative Anaerobes, Transfer of “ Cellvibrio gilvus” to the Genus Cellulomonas, and Proposal of Cellulomonas gilvus sp. nov

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          Abstract

          Actinobacteria in the genus Cellulomonas are the only known and reported cellulolytic facultative anaerobes. To better understand the cellulolytic strategy employed by these bacteria, we sequenced the genome of the Cellulomonas fimi ATCC 484 T. For comparative purposes, we also sequenced the genome of the aerobic cellulolytic “ Cellvibrio gilvus” ATCC 13127 T. An initial analysis of these genomes using phylogenetic and whole-genome comparison revealed that “ Cellvibrio gilvus” belongs to the genus Cellulomonas. We thus propose to assign “ Cellvibrio gilvus” to the genus Cellulomonas. A comparative genomics analysis between these two Cellulomonas genome sequences and the recently completed genome for Cellulomonas flavigena ATCC 482 T showed that these cellulomonads do not encode cellulosomes but appear to degrade cellulose by secreting multi-domain glycoside hydrolases. Despite the minimal number of carbohydrate-active enzymes encoded by these genomes, as compared to other known cellulolytic organisms, these bacteria were found to be proficient at degrading and utilizing a diverse set of carbohydrates, including crystalline cellulose. Moreover, they also encode for proteins required for the fermentation of hexose and xylose sugars into products such as ethanol. Finally, we found relatively few significant differences between the predicted carbohydrate-active enzymes encoded by these Cellulomonas genomes, in contrast to previous studies reporting differences in physiological approaches for carbohydrate degradation. Our sequencing and analysis of these genomes sheds light onto the mechanism through which these facultative anaerobes degrade cellulose, suggesting that the sequenced cellulomonads use secreted, multidomain enzymes to degrade cellulose in a way that is distinct from known anaerobic cellulolytic strategies.

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          MRBAYES: Bayesian inference of phylogenetic trees.

          The program MRBAYES performs Bayesian inference of phylogeny using a variant of Markov chain Monte Carlo. MRBAYES, including the source code, documentation, sample data files, and an executable, is available at http://brahms.biology.rochester.edu/software.html.
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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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              The Universal Protein Resource (UniProt) in 2010

              The primary mission of UniProt is to support biological research by maintaining a stable, comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and querying interfaces freely accessible to the scientific community. UniProt is produced by the UniProt Consortium which consists of groups from the European Bioinformatics Institute (EBI), the Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is comprised of four major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. UniProt is updated and distributed every 3 weeks and can be accessed online for searches or download at http://www.uniprot.org.
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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
                2013
                14 January 2013
                : 8
                : 1
                : e53954
                Affiliations
                [1 ]Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
                [2 ]Department of Energy, Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
                [3 ]Lucigen, Middleton, Wisconsin, United States of America
                [4 ]C5-6 Technologies, Middleton, Wisconsin, United States of America
                University of Florida, United States of America
                Author notes

                Competing Interests: The authors have read the journal’s policy and have the following conflicts: David Mead is employed by Lucigen Corp., a manufacturer of research reagents. Phillip Brumm is employed by C5–6 Technologies Corp., an enzyme discovery company. All work reported here was performed under and supported by subcontract to the GLBRC. No funds from either corporation was used for this research or to support the researchers during performance of this work. The commercial affiliations which the authors have declared do not alter their adherence to all the PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: MRC GS SB KJ FOA DM PB. Performed the experiments: MRC GS SB KJ DM PB. Analyzed the data: MRC GS SB KJ DM PB. Contributed reagents/materials/analysis tools: GS SB KJ FOA DM PB. Wrote the paper: MRC GS PB.

                Article
                PONE-D-12-26237
                10.1371/journal.pone.0053954
                3544764
                23342046
                c239fe3e-d879-475e-9005-78d5c4fc7fb2
                Copyright @ 2013

                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
                : 29 August 2012
                : 4 December 2012
                Page count
                Pages: 10
                Funding
                This work was funded in part by the DOE Great Lakes Bioenergy Research Center (GLBRC) (DOE BER Office of Science DE-FC02–07ER64494) supporting FOA, DM, and PJB. This work was also supported by a DOE BER Early Career Research Program Award DE–SC0008104 and funding from the Wisconsin Bioenergy Initiative to GS. MRC was supported by a DOE GLBRC/BACTER Post-doctoral Research Fellowship. The work conducted by the US Department of Energy Joint Genome Institute is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231. All work performed by employees of Lucigen or C5–6 Technologies was performed under and supported by subcontract to the GLBRC. Neither corporation was a funder of the work; no funds of either corporation was used for this research or to support the researchers during performance of this work. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Biochemistry
                Metabolism
                Carbohydrate Metabolism
                Enzymes
                Computational Biology
                Genomics
                Comparative Genomics
                Genome Sequencing
                Microbiology
                Bacteriology
                Bacterial Taxonomy
                Bacterial Physiology

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                Uncategorized

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