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      Analysis of the Outer Membrane Proteome and Secretome of Bacteroides fragilis Reveals a Multiplicity of Secretion Mechanisms

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      PLoS ONE
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          Abstract

          Bacteroides fragilis is a widely distributed member of the human gut microbiome and an opportunistic pathogen. Cell surface molecules produced by this organism likely play important roles in colonization, communication with other microbes, and pathogenicity, but the protein composition of the outer membrane (OM) and the mechanisms used to transport polypeptides into the extracellular space are poorly characterized. Here we used LC-MS/MS to analyze the OM proteome and secretome of B. fragilis NCTC 9343 grown under laboratory conditions. Of the 229 OM proteins that we identified, 108 are predicted to be lipoproteins, and 61 are predicted to be TonB-dependent transporters. Based on their proximity to genes encoding TonB-dependent transporters, many of the lipoprotein genes likely encode proteins involved in nutrient or small molecule uptake. Interestingly, protease accessibility and biotinylation experiments indicated that an unusually large fraction of the lipoproteins are cell-surface exposed. We also identified three proteins that are members of a novel family of autotransporters, multiple potential type I protein secretion systems, and proteins that appear to be components of a type VI secretion apparatus. The secretome consisted of lipoproteins and other proteins that might be substrates of the putative type I or type VI secretion systems. Our proteomic studies show that B. fragilis differs considerably from well-studied Gram-negative bacteria such as Escherichia coli in both the spectrum of OM proteins that it produces and the range of secretion strategies that it utilizes.

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          Most cited references63

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          A microbial symbiosis factor prevents intestinal inflammatory disease.

          Humans are colonized by multitudes of commensal organisms representing members of five of the six kingdoms of life; however, our gastrointestinal tract provides residence to both beneficial and potentially pathogenic microorganisms. Imbalances in the composition of the bacterial microbiota, known as dysbiosis, are postulated to be a major factor in human disorders such as inflammatory bowel disease. We report here that the prominent human symbiont Bacteroides fragilis protects animals from experimental colitis induced by Helicobacter hepaticus, a commensal bacterium with pathogenic potential. This beneficial activity requires a single microbial molecule (polysaccharide A, PSA). In animals harbouring B. fragilis not expressing PSA, H. hepaticus colonization leads to disease and pro-inflammatory cytokine production in colonic tissues. Purified PSA administered to animals is required to suppress pro-inflammatory interleukin-17 production by intestinal immune cells and also inhibits in vitro reactions in cell cultures. Furthermore, PSA protects from inflammatory disease through a functional requirement for interleukin-10-producing CD4+ T cells. These results show that molecules of the bacterial microbiota can mediate the critical balance between health and disease. Harnessing the immunomodulatory capacity of symbiosis factors such as PSA might potentially provide therapeutics for human inflammatory disorders on the basis of entirely novel biological principles.
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            The PSIPRED protein structure prediction server.

            The PSIPRED protein structure prediction server allows users to submit a protein sequence, perform a prediction of their choice and receive the results of the prediction both textually via e-mail and graphically via the web. The user may select one of three prediction methods to apply to their sequence: PSIPRED, a highly accurate secondary structure prediction method; MEMSAT 2, a new version of a widely used transmembrane topology prediction method; or GenTHREADER, a sequence profile based fold recognition method. Freely available to non-commercial users at http://globin.bio.warwick.ac.uk/psipred/
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              Prediction of lipoprotein signal peptides in Gram-negative bacteria.

              A method to predict lipoprotein signal peptides in Gram-negative Eubacteria, LipoP, has been developed. The hidden Markov model (HMM) was able to distinguish between lipoproteins (SPaseII-cleaved proteins), SPaseI-cleaved proteins, cytoplasmic proteins, and transmembrane proteins. This predictor was able to predict 96.8% of the lipoproteins correctly with only 0.3% false positives in a set of SPaseI-cleaved, cytoplasmic, and transmembrane proteins. The results obtained were significantly better than those of previously developed methods. Even though Gram-positive lipoprotein signal peptides differ from Gram-negatives, the HMM was able to identify 92.9% of the lipoproteins included in a Gram-positive test set. A genome search was carried out for 12 Gram-negative genomes and one Gram-positive genome. The results for Escherichia coli K12 were compared with new experimental data, and the predictions by the HMM agree well with the experimentally verified lipoproteins. A neural network-based predictor was developed for comparison, and it gave very similar results. LipoP is available as a Web server at www.cbs.dtu.dk/services/LipoP/.
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                Author and article information

                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                6 February 2015
                2015
                : 10
                : 2
                : e0117732
                Affiliations
                [1 ]Genetics and Biochemistry Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States of America
                [2 ]Advanced Mass Spectrometry Facility, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States of America
                Author notes

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

                Conceived and designed the experiments: MMW HDB. Performed the experiments: MMW DEA. Analyzed the data: MMW DEA HDB. Contributed reagents/materials/analysis tools: MMW DEA. Wrote the paper: MMW DEA HDB.

                Article
                PONE-D-14-44386
                10.1371/journal.pone.0117732
                4319957
                25658944
                d09b8230-607d-4f42-a185-0d1acf1fba99

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0public domain dedication

                History
                : 2 October 2014
                : 31 December 2014
                Page count
                Figures: 10, Tables: 1, Pages: 24
                Funding
                This study was supported by the Intramural Research Program of the National Institute of Diabetes and Digestive and Kidney Diseases. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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