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      Impact of violacein from Chromobacterium violaceum on the mammalian gut microbiome

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          Abstract

          Violacein is a violet pigment produced by Chromobacterium violaceum that possesses several functions such as antibacterial, antiviral, antifungal, and antioxidant activities. The search for potential compounds and therapies that may interfere with and modulate the gut microbial consortia without causing severe damage and increased resistance is important for the treatment of inflammatory, allergic, and metabolic diseases. The aim of the present work was to evaluate the ability of violacein to change microbial patterns in the mammalian gut by favoring certain groups over the others in order to be used as a therapy for diseases associated with changes in the intestinal microflora. To do this, we used male Wistar rats, and administered violacein orally, in low (50 μg/ml) and high (500 μg/ml) doses for a month. Initially, the changes in the microbial diversity were observed by DGGE analyses that showed that the violacein significantly affects the gut microbiota of the rats. Pyrosequencing of 16S rDNA was then employed using a 454 GS Titanium platform, and the results demonstrated that higher taxonomic richness was observed with the low violacein treatment group, followed by the control group and high violacein treatment group. Modulation of the microbiota at the class level was observed in the low violacein dose, where Bacilli and Clostridia (Firmicutes) were found as dominant. For the high violacein dose, Bacilli followed by Clostridia and Actinobacteria were present as the major components. Further analyses are crucial for a better understanding of how violacein affects the gut microbiome and whether this change would be beneficial to the host, providing a framework for the development of alternative treatment strategies for intestinal diseases using this compound.

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          Fecal microbiome and volatile organic compound metabolome in obese humans with nonalcoholic fatty liver disease.

          The histopathology of nonalcoholic fatty liver disease (NAFLD) is similar to that of alcoholic liver disease. Colonic bacteria are a source of many metabolic products, including ethanol and other volatile organic compounds (VOC) that may have toxic effects on the human host after intestinal absorption and delivery to the liver via the portal vein. Recent data suggest that the composition of the gut microbiota in obese human beings is different from that of healthy-weight individuals. The aim of this study was to compare the colonic microbiome and VOC metabolome of obese NAFLD patients (n = 30) with healthy controls (n = 30). Multitag pyrosequencing was used to characterize the fecal microbiota. Fecal VOC profiles were measured by gas chromatography-mass spectrometry. There were statistically significant differences in liver biochemistry and metabolic parameters in NAFLD. Deep sequencing of the fecal microbiome revealed over-representation of Lactobacillus species and selected members of phylum Firmicutes (Lachnospiraceae; genera, Dorea, Robinsoniella, and Roseburia) in NAFLD patients, which was statistically significant. One member of phylum Firmicutes was under-represented significantly in the fecal microbiome of NAFLD patients (Ruminococcaceae; genus, Oscillibacter). Fecal VOC profiles of the 2 patient groups were different, with a significant increase in fecal ester compounds observed in NAFLD patients. A significant increase in fecal ester VOC is associated with compositional shifts in the microbiome of obese NAFLD patients. These novel bacterial metabolomic and metagenomic factors are implicated in the etiology and complications of obesity. Copyright © 2013 AGA Institute. Published by Elsevier Inc. All rights reserved.
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            Diabetes, obesity and gut microbiota.

            The gut microbiota composition has been associated with several hallmarks of metabolic syndrome (e.g., obesity, type 2 diabetes, cardiovascular diseases, and non-alcoholic steatohepatitis). Growing evidence suggests that gut microbes contribute to the onset of the low-grade inflammation characterising these metabolic disorders via mechanisms associated with gut barrier dysfunctions. Recently, enteroendocrine cells and the endocannabinoid system have been shown to control gut permeability and metabolic endotoxaemia. Moreover, targeted nutritional interventions using non-digestible carbohydrates with prebiotic properties have shown promising results in pre-clinical studies in this context, although human intervention studies warrant further investigations. Thus, in this review, we discuss putative mechanisms linking gut microbiota and type 2 diabetes. These data underline the advantage of investigating and changing the gut microbiota as a therapeutic target in the context of obesity and type 2 diabetes. Copyright © 2013 Elsevier Ltd. All rights reserved.
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              Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA.

              The variation in community composition between microbiome samples, termed beta diversity, can be measured by pairwise distance based on either presence-absence or quantitative species abundance data. PERMANOVA, a permutation-based extension of multivariate analysis of variance to a matrix of pairwise distances, partitions within-group and between-group distances to permit assessment of the effect of an exposure or intervention (grouping factor) upon the sampled microbiome. Within-group distance and exposure/intervention effect size must be accurately modeled to estimate statistical power for a microbiome study that will be analyzed with pairwise distances and PERMANOVA.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: VisualizationRole: Writing – review & editing
                Role: Project administrationRole: VisualizationRole: Writing – review & editing
                Role: Resources
                Role: Resources
                Role: Formal analysisRole: ResourcesRole: Writing – review & editing
                Role: ResourcesRole: Writing – review & editing
                Role: Funding acquisitionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: VisualizationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                13 September 2018
                2018
                : 13
                : 9
                : e0203748
                Affiliations
                [1 ] Laboratório de Biologia de Anaeróbios, Departamento de Microbiologia Médica, Instituto de Microbiologia Paulo de Góes, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
                [2 ] Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz, Rio de Janeiro, RJ, Brazil
                [3 ] Laboratório de Interação Hospedeiro-Microbiota, Instituto de Biociências, Universidade Estadual Paulista, Campus do Litoral Paulista, São Vicente, SP, Brazil
                [4 ] Faculdade de Farmácia, Universidade Federal do Rio de Janeiro, Campus Macaé, Macaé, RJ, Brazil
                [5 ] Faculdades Integradas Aparício Carvalho, Porto Velho, RO, Brazil
                [6 ] Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro–Rio de Janeiro, Brazil
                [7 ] Instituto Nacional de Ciência e Tecnologia em Inovação em Doenças de Populações Negligenciadas, Centro de Desenvolvimento Tecnológico em Saúde, Fundação Oswaldo Cruz, Rio de Janeiro, RJ, Brazil
                East Carolina University Brody School of Medicine, UNITED STATES
                Author notes

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

                Article
                PONE-D-17-44082
                10.1371/journal.pone.0203748
                6136722
                30212521
                ac434b1e-ffcf-466a-8073-5d4bbfcdf4c5
                © 2018 Pauer et al

                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
                : 25 January 2018
                : 20 August 2018
                Page count
                Figures: 7, Tables: 2, Pages: 21
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100003593, Conselho Nacional de Desenvolvimento Científico e Tecnológico;
                Award ID: 160621/2012-7
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100004586, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro;
                Award ID: E-26/201.398/2014
                Award Recipient :
                This study was supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) - 160621/2012-7 - http://cnpq.br/; and Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro - E-26/201.398/2014 - http://www.faperj.br/. 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
                Biosynthesis
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Metabolic Pathways
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Protein Metabolism
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbiome
                Biology and Life Sciences
                Genetics
                Genomics
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Microbiology
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Organisms
                Bacteria
                Gut Bacteria
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Sequence Analysis
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbial Pathogens
                Bacterial Pathogens
                Clostridium
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Microbial Pathogens
                Bacterial Pathogens
                Clostridium
                Biology and Life Sciences
                Organisms
                Bacteria
                Gut Bacteria
                Clostridium
                Biology and life sciences
                Genetics
                DNA
                DNA metabolism
                Biology and life sciences
                Biochemistry
                Nucleic acids
                DNA
                DNA metabolism
                Custom metadata
                The raw data and sequencing sample information have been submitted to the NCBI’s Sequence Read Archive (SRA) database under the accession number SRP116689.

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