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Comparative Analysis of Carbohydrate Active Enzymes in Clostridium termitidis CT1112 Reveals Complex Carbohydrate Degradation Ability

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      Abstract

      Clostridium termitidis strain CT1112 is an anaerobic, gram positive, mesophilic, cellulolytic bacillus isolated from the gut of the wood-feeding termite, Nasutitermes lujae. It produces biofuels such as hydrogen and ethanol from cellulose, cellobiose, xylan, xylose, glucose, and other sugars, and therefore could be used for biofuel production from biomass through consolidated bioprocessing. The first step in the production of biofuel from biomass by microorganisms is the hydrolysis of complex carbohydrates present in biomass. This is achieved through the presence of a repertoire of secreted or complexed carbohydrate active enzymes (CAZymes), sometimes organized in an extracellular organelle called cellulosome. To assess the ability and understand the mechanism of polysaccharide hydrolysis in C. termitidis, the recently sequenced strain CT1112 of C. termitidis was analyzed for both CAZymes and cellulosomal components, and compared to other cellulolytic bacteria. A total of 355 CAZyme sequences were identified in C. termitidis, significantly higher than other Clostridial species. Of these, high numbers of glycoside hydrolases (199) and carbohydrate binding modules (95) were identified. The presence of a variety of CAZymes involved with polysaccharide utilization/degradation ability suggests hydrolysis potential for a wide range of polysaccharides. In addition, dockerin-bearing enzymes, cohesion domains and a cellulosomal gene cluster were identified, indicating the presence of potential cellulosome assembly.

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      Most cited references 52

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      A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding

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        We announce the release of the fourth version of MEGA software, which expands on the existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses. Version 4 includes a unique facility to generate captions, written in figure legend format, in order to provide natural language descriptions of the models and methods used in the analyses. This facility aims to promote a better understanding of the underlying assumptions used in analyses, and of the results generated. Another new feature is the Maximum Composite Likelihood (MCL) method for estimating evolutionary distances between all pairs of sequences simultaneously, with and without incorporating rate variation among sites and substitution pattern heterogeneities among lineages. This MCL method also can be used to estimate transition/transversion bias and nucleotide substitution pattern without knowledge of the phylogenetic tree. This new version is a native 32-bit Windows application with multi-threading and multi-user supports, and it is also available to run in a Linux desktop environment (via the Wine compatibility layer) and on Intel-based Macintosh computers under the Parallels program. The current version of MEGA is available free of charge at (http://www.megasoftware.net).
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          The neighbor-joining method: a new method for reconstructing phylogenetic trees.

           N Saitou,  M Nei (1987)
          A new method called the neighbor-joining method is proposed for reconstructing phylogenetic trees from evolutionary distance data. The principle of this method is to find pairs of operational taxonomic units (OTUs [= neighbors]) that minimize the total branch length at each stage of clustering of OTUs starting with a starlike tree. The branch lengths as well as the topology of a parsimonious tree can quickly be obtained by using this method. Using computer simulation, we studied the efficiency of this method in obtaining the correct unrooted tree in comparison with that of five other tree-making methods: the unweighted pair group method of analysis, Farris's method, Sattath and Tversky's method, Li's method, and Tateno et al.'s modified Farris method. The new, neighbor-joining method and Sattath and Tversky's method are shown to be generally better than the other methods.
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            Author and article information

            Affiliations
            [1 ]Department of Biosystems Engineering, University of Manitoba, Winnipeg, Manitoba, Canada
            [2 ]Department of Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada
            [3 ]CNRS and Universities of Aix-Marseille, Marseille, France
            University of Massachusetts, United States of America
            Author notes

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

            Conceived and designed the experiments: RM JS BH TJV RS DBL. Performed the experiments: RM JS TJV. Analyzed the data: RM RS DBL. Contributed reagents/materials/analysis tools: DBL RS. Wrote the paper: DBL RM.

            Contributors
            Role: Editor
            Journal
            PLoS One
            PLoS ONE
            plos
            plosone
            PLoS ONE
            Public Library of Science (San Francisco, USA )
            1932-6203
            2014
            7 August 2014
            : 9
            : 8
            25101643
            4125193
            PONE-D-13-50443
            10.1371/journal.pone.0104260
            (Editor)

            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.

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            Pages: 13
            Funding
            This work was supported by funds provided by Genome Canada, through the Applied Genomics Research in Bioproducts or Crops (ABC) program, for the grant titled, “Microbial Genomics for Biofuels and CoProducts from Biorefining Processes”, and by the Province of Manitoba, Agricultural and Rural Development Initiative (ARDI). 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
            Agriculture
            Biochemistry
            Biocatalysis
            Biotechnology
            Applied Microbiology
            Computational Biology
            Comparative Genomics
            Evolutionary Biology
            Genetics
            Genomics
            Microbiology
            Earth Sciences
            Engineering and Technology
            Energy and Power
            Fuels
            Biofuels
            Physical Sciences
            Chemistry
            Catalysis
            Chemical Reactions

            Uncategorized

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