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      The effect of environmental conditions on expression of Bacteroides fragilis and Bacteroides thetaiotaomicron C10 protease genes

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          Abstract

          Background

          Bacteroides fragilis and Bacteroides thetaiotaomicron are members of the normal human intestinal microbiota. However, both organisms are capable of causing opportunistic infections, during which the environmental conditions to which the bacteria are exposed change dramatically. To further explore their potential for contributing to infection, we have characterized the expression in B. thetaiotaomicron of four homologues of the gene encoding the C10 cysteine protease SpeB, a potent extracellular virulence factor produced by Streptococcus pyogenes.

          Results

          We identified a paralogous set of genes ( btp genes) in the B. thetaiotaomicron genome, that were related to C10 protease genes we recently identified in B. fragilis. Similar to C10 proteases found in B. fragilis, three of the B. thetaiotaomicron homologues were transcriptionally coupled to genes encoding small proteins that are similar in structural architecture to Staphostatins, protease inhibitors associated with Staphopains in Staphylococcus aureus. The expression of genes for these C10 proteases in both B. fragilis and B. thetaiotaomicron was found to be regulated by environmental stimuli, in particular by exposure to oxygen, which may be important for their contribution to the development of opportunistic infections.

          Conclusions

          Genes encoding C10 proteases are increasingly identified in operons which also contain genes encoding proteins homologous to protease inhibitors. The Bacteroides C10 protease gene expression levels are responsive to different environmental stimuli suggesting they may have distinct roles in the bacterial-host interaction.

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          Most cited references46

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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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            Spatial organization and composition of the mucosal flora in patients with inflammatory bowel disease.

            The composition and spatial organization of the mucosal flora in biopsy specimens from patients with inflammatory bowel disease (IBD; either Crohn's disease or ulcerative colitis), self-limiting colitis, irritable-bowel syndrome (IBS), and healthy controls were investigated by using a broad range of fluorescent bacterial group-specific rRNA-targeted oligonucleotide probes. Each group included 20 subjects. Ten patients who had IBD and who were being treated with antibiotics were also studied. Use of nonaqueous Carnoy fixative to preserve the mucus layer was crucial for detection of bacteria adherent to the mucosal surface (mucosal bacteria). No biofilm was detectable in formalin-fixed biopsy specimens. Mucosal bacteria were found at concentrations greater than 10(9)/ml in 90 to 95% of IBD patients, 95% of patients with self-limiting colitis, 65% of IBS patients, and 35% of healthy controls. The mean density of the mucosal biofilm was 2 powers higher in IBD patients than in patients with IBS or controls, and bacteria were mostly adherent. Bacteroides fragilis was responsible for >60% of the biofilm mass in patients with IBD but for only 30% of the biofilm mass in patients with self-limiting colitis and 40% of the biofilm in IBS patients but for <15% of the biofilm in IBD patients. In patients treated with (5-ASA) or antibiotics, the biofilm could be detected with 4,6-diamidino-2-phenylindole but did not hybridize with fluorescence in situ hybridization probes. A Bacteroides fragilis biofilm is the main feature of IBD. This was not previously recognized due to a lack of appropriate tissue fixation. Both 5-ASA and antibiotics suppress but do not eliminate the adherent biofilm.
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              MatGAT: An application that generates similarity/identity matrices using protein or DNA sequences

              Background The rapid increase in the amount of protein and DNA sequence information available has become almost overwhelming to researchers. So much information is now accessible that high-quality, functional gene analysis and categorization has become a major goal for many laboratories. To aid in this categorization, there is a need for non-commercial software that is able to both align sequences and also calculate pairwise levels of similarity/identity. Results We have developed MatGAT (Matrix Global Alignment Tool), a simple, easy to use computer application that generates similarity/identity matrices for DNA or protein sequences without needing pre-alignment of the data. Conclusions The advantages of this program over other software are that it is open-source freeware, can analyze a large number of sequences simultaneously, can visualize both sequence alignment and similarity/identity values concurrently, employs global alignment in calculations, and has been formatted to run under both the Unix and the Microsoft Windows Operating Systems. We are presently completing the Macintosh-based version of the program.
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                Author and article information

                Journal
                BMC Microbiol
                BMC Microbiol
                BMC Microbiology
                BioMed Central
                1471-2180
                2012
                3 September 2012
                : 12
                : 190
                Affiliations
                [1 ]Department of Life Sciences, University of Limerick, Limerick, Ireland
                [2 ]Materials and Surface Science Institute, University of Limerick, Limerick, Ireland
                [3 ]Department of Microbiology, & Alimentary Pharmabiotic Centre, University College Cork, Cork, Ireland
                [4 ]Present address: Department of Clinical Sciences, Lund University, Lund, Sweden
                Article
                1471-2180-12-190
                10.1186/1471-2180-12-190
                3462683
                22943521
                f380f76b-d218-4af3-94b5-e31ff7be2073
                Copyright ©2012 Thornton et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 13 December 2011
                : 23 August 2012
                Categories
                Research Article

                Microbiology & Virology
                Microbiology & Virology

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