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      dbCAN2: a meta server for automated carbohydrate-active enzyme annotation

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          Abstract

          Complex carbohydrates of plants are the main food sources of animals and microbes, and serve as promising renewable feedstock for biofuel and biomaterial production. Carbohydrate active enzymes (CAZymes) are the most important enzymes for complex carbohydrate metabolism. With an increasing number of plant and plant-associated microbial genomes and metagenomes being sequenced, there is an urgent need of automatic tools for genomic data mining of CAZymes. We developed the dbCAN web server in 2012 to provide a public service for automated CAZyme annotation for newly sequenced genomes. Here, dbCAN2 ( http://cys.bios.niu.edu/dbCAN2) is presented as an updated meta server, which integrates three state-of-the-art tools for CAZome (all CAZymes of a genome) annotation: (i) HMMER search against the dbCAN HMM (hidden Markov model) database; (ii) DIAMOND search against the CAZy pre-annotated CAZyme sequence database and (iii) Hotpep search against the conserved CAZyme short peptide database. Combining the three outputs and removing CAZymes found by only one tool can significantly improve the CAZome annotation accuracy. In addition, dbCAN2 now also accepts nucleotide sequence submission, and offers the service to predict physically linked CAZyme gene clusters (CGCs), which will be a very useful online tool for identifying putative polysaccharide utilization loci (PULs) in microbial genomes or metagenomes.

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          Glycan complexity dictates microbial resource allocation in the large intestine

          The structure of the human gut microbiota is controlled primarily through the degradation of complex dietary carbohydrates, but the extent to which carbohydrate breakdown products are shared between members of the microbiota is unclear. We show here, using xylan as a model, that sharing the breakdown products of complex carbohydrates by key members of the microbiota, such as Bacteroides ovatus, is dependent on the complexity of the target glycan. Characterization of the extensive xylan degrading apparatus expressed by B. ovatus reveals that the breakdown of the polysaccharide by the human gut microbiota is significantly more complex than previous models suggested, which were based on the deconstruction of xylans containing limited monosaccharide side chains. Our report presents a highly complex and dynamic xylan degrading apparatus that is fine-tuned to recognize the different forms of the polysaccharide presented to the human gut microbiota.
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            CAZymes Analysis Toolkit (CAT): web service for searching and analyzing carbohydrate-active enzymes in a newly sequenced organism using CAZy database.

            The Carbohydrate-Active Enzyme (CAZy) database provides a rich set of manually annotated enzymes that degrade, modify, or create glycosidic bonds. Despite rich and invaluable information stored in the database, software tools utilizing this information for annotation of newly sequenced genomes by CAZy families are limited. We have employed two annotation approaches to fill the gap between manually curated high-quality protein sequences collected in the CAZy database and the growing number of other protein sequences produced by genome or metagenome sequencing projects. The first approach is based on a similarity search against the entire nonredundant sequences of the CAZy database. The second approach performs annotation using links or correspondences between the CAZy families and protein family domains. The links were discovered using the association rule learning algorithm applied to sequences from the CAZy database. The approaches complement each other and in combination achieved high specificity and sensitivity when cross-evaluated with the manually curated genomes of Clostridium thermocellum ATCC 27405 and Saccharophagus degradans 2-40. The capability of the proposed framework to predict the function of unknown protein domains and of hypothetical proteins in the genome of Neurospora crassa is demonstrated. The framework is implemented as a Web service, the CAZymes Analysis Toolkit, and is available at http://cricket.ornl.gov/cgi-bin/cat.cgi.
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              Functional genomic and metabolic studies of the adaptations of a prominent adult human gut symbiont, Bacteroides thetaiotaomicron, to the suckling period.

              The adult human gut microbiota is dominated by two divisions of Bacteria, the Bacteroidetes and the Firmicutes. Assembly of this community begins at birth through processes that remain largely undefined. In this report, we examine the adaptations of Bacteroides thetaiotaomicron, a prominent member of the adult distal intestinal microbiota, during the suckling and weaning periods. Germ-free NMRI mice were colonized at birth from their gnotobiotic mothers, who harbored this anaerobic Gram-negative saccharolytic bacterium. B. thetaiotaomicron was then harvested from the ceca of these hosts during the suckling period (postnatal day 17) and after weaning (postnatal day 30). Whole genome transcriptional profiles were obtained at these two time points using custom B. thetaiotaomicron GeneChips. Transcriptome-based in silico reconstructions of bacterial metabolism and gas chromatography-mass spectrometry and biochemical assays of carbohydrate utilization in vivo indicated that in the suckling gut B. thetaiotaomicron prefers host-derived polysaccharides, as well as mono- and oligosaccharides present in mother's milk. After weaning, B. thetaiotaomicron expands its metabolism to exploit abundant, plant-derived dietary polysaccharides. The bacterium's responses to postnatal alterations in its nutrient landscape involve expression of gene clusters encoding environmental sensors, outer membrane proteins involved in binding and import of glycans, and glycoside hydrolases. These expression changes are interpreted in light of a phylogenetic analysis that revealed unique expansions of related polysaccharide utilization loci in three human alimentary tract-associated Bacteroidetes, expansions that likely reflect the evolutionary adaptations of these species to different nutrient niches.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                02 July 2018
                16 May 2018
                16 May 2018
                : 46
                : Web Server issue
                : W95-W101
                Affiliations
                [1 ]College of Computer and Control Engineering, Nankai University, Tianjin, China
                [2 ]Department of Biological Sciences, Northern Illinois University, DeKalb, IL, USA
                [3 ]Department of Science and Environment, Roskilde University, Roskilde, Denmark
                [4 ]Department of Biochemistry and Molecular Biology, University of Georgia. Athens, GA, USA
                Author notes
                To whom correspondence should be addressed. Tel: +1 815 753 8963; Fax: +1 815 753 0461; Email: yyin@ 123456niu.edu

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.

                Article
                gky418
                10.1093/nar/gky418
                6031026
                29771380
                2747e887-6f46-4fc0-88e9-8a70a1054cdf
                © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 04 May 2018
                : 20 April 2018
                : 09 February 2018
                Page count
                Pages: 7
                Funding
                Funded by: National Science Foundation 10.13039/100000001
                Award ID: DBI-1652164
                Funded by: National Institutes of Health 10.13039/100000002
                Award ID: 1R15GM114706
                Funded by: Research & Artistry Award of the NIU
                Award ID: 2017-YIN
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 31728013
                Categories
                Web Server Issue

                Genetics
                Genetics

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