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      Discovery of Two β-1,2-Mannoside Phosphorylases Showing Different Chain-Length Specificities from Thermoanaerobacter sp. X-514

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          Abstract

          We characterized Teth514_1788 and Teth514_1789, belonging to glycoside hydrolase family 130, from Thermoanaerobacter sp. X-514. These two enzymes catalyzed the synthesis of 1,2-β-oligomannan using β-1,2-mannobiose and d-mannose as the optimal acceptors, respectively, in the presence of the donor α- d-mannose 1-phosphate. Kinetic analysis of the phosphorolytic reaction toward 1,2-β-oligomannan revealed that these enzymes followed a typical sequential Bi Bi mechanism. The kinetic parameters of the phosphorolysis of 1,2-β-oligomannan indicate that Teth514_1788 and Teth514_1789 prefer 1,2-β-oligomannans containing a DP ≥3 and β-1,2-Man 2, respectively. These results indicate that the two enzymes are novel inverting phosphorylases that exhibit distinct chain-length specificities toward 1,2-β-oligomannan. Here, we propose 1,2-β-oligomannan:phosphate α- d-mannosyltransferase as the systematic name and 1,2-β-oligomannan phosphorylase as the short name for Teth514_1788 and β-1,2-mannobiose:phosphate α- d-mannosyltransferase as the systematic name and β-1,2-mannobiose phosphorylase as the short name for Teth514_1789.

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          Most cited references38

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          Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites.

          We have developed a new method for the identification of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequence. The method performs significantly better than previous prediction schemes and can easily be applied on genome-wide data sets. Discrimination between cleaved signal peptides and uncleaved N-terminal signal-anchor sequences is also possible, though with lower precision. Predictions can be made on a publicly available WWW server.
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            PSORT-B: Improving protein subcellular localization prediction for Gram-negative bacteria.

            Automated prediction of bacterial protein subcellular localization is an important tool for genome annotation and drug discovery. PSORT has been one of the most widely used computational methods for such bacterial protein analysis; however, it has not been updated since it was introduced in 1991. In addition, neither PSORT nor any of the other computational methods available make predictions for all five of the localization sites characteristic of Gram-negative bacteria. Here we present PSORT-B, an updated version of PSORT for Gram-negative bacteria, which is available as a web-based application at http://www.psort.org. PSORT-B examines a given protein sequence for amino acid composition, similarity to proteins of known localization, presence of a signal peptide, transmembrane alpha-helices and motifs corresponding to specific localizations. A probabilistic method integrates these analyses, returning a list of five possible localization sites with associated probability scores. PSORT-B, designed to favor high precision (specificity) over high recall (sensitivity), attained an overall precision of 97% and recall of 75% in 5-fold cross-validation tests, using a dataset we developed of 1443 proteins of experimentally known localization. This dataset, the largest of its kind, is freely available, along with the PSORT-B source code (under GNU General Public License).
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              The structures of Escherichia coli O-polysaccharide antigens.

              Escherichia coli is usually a non-pathogenic member of the human colonic flora. However, certain strains have acquired virulence factors and may cause a variety of infections in humans and in animals. There are three clinical syndromes caused by E. coli: (i) sepsis/meningitis; (ii) urinary tract infection and (iii) diarrhoea. Furthermore the E. coli causing diarrhoea is divided into different 'pathotypes' depending on the type of disease, i.e. (i) enterotoxigenic; (ii) enteropathogenic; (iii) enteroinvasive; (iv) enterohaemorrhagic; (v) enteroaggregative and (vi) diffusely adherent. The serotyping of E. coli based on the somatic (O), flagellar (H) and capsular polysaccharide antigens (K) is used in epidemiology. The different antigens may be unique for a particular serogroup or antigenic determinants may be shared, resulting in cross-reactions with other serogroups of E. coli or even with other members of the family Enterobacteriacea. To establish the uniqueness of a particular serogroup or to identify the presence of common epitopes, a database of the structures of O-antigenic polysaccharides has been created. The E. coli database (ECODAB) contains structures, nuclear magnetic resonance chemical shifts and to some extent cross-reactivity relationships. All fields are searchable. A ranking is produced based on similarity, which facilitates rapid identification of strains that are difficult to serotype (if known) based on classical agglutinating methods. In addition, results pertinent to the biosynthesis of the repeating units of O-antigens are discussed. The ECODAB is accessible to the scientific community at http://www.casper.organ.su.se/ECODAB/.
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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 December 2014
                : 9
                : 12
                : e114882
                Affiliations
                [1 ]Faculty of Agriculture, Niigata University, Niigata, Japan
                [2 ]National Food Research Institute, National Agriculture and Food Research Organization, Tsukuba, Ibaraki, Japan
                INRA, France
                Author notes

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

                Conceived and designed the experiments: MK HN. Performed the experiments: KC TN ES. Analyzed the data: KC TN ES MK HN. Contributed reagents/materials/analysis tools: MN KO MK. Wrote the paper: KC MK HN.

                Article
                PONE-D-14-38876
                10.1371/journal.pone.0114882
                4264767
                25500577
                986be46f-fa0a-4e2e-bcbc-2f8db72d4b26
                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
                : 10 September 2014
                : 14 November 2014
                Page count
                Pages: 21
                Funding
                This work was supported in part by JSPS's program “Grant-in-Aid for Research Activity Start-up”, MEXT's program “Promotion of Environmental Improvement for Independence of Young Researchers” under the Special Coordination Funds for Promoting Science and Technology, Science and Technology Research Promotion Program for Agriculture, Forestry, Fisheries and Food Industry, and Grant for Promotion of Niigata University Research Projects. 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
                Biochemistry
                Enzymology
                Enzymes
                Transferases
                Phosphorylases
                Proteins
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information files.

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