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      Tissue-Associated Bacterial Alterations in Rectal Carcinoma Patients Revealed by 16S rRNA Community Profiling

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          Abstract

          Sporadic and inflammatory forms of colorectal cancer (CRC) account for more than 80% of cases. Recent publications have shown mechanistic evidence for the involvement of gut bacteria in the development of both CRC-forms. Whereas, colon and rectal cancer have been routinely studied together as CRC, increasing evidence show these to be distinct diseases. Also, the common use of fecal samples to study microbial communities may reflect disease state but possibly not the tumor microenvironment. We performed this study to evaluate differences in bacterial communities found in tissue samples of 18 rectal-cancer subjects when compared to 18 non-cancer controls. Samples were collected during exploratory colonoscopy (non-cancer group) or during surgery for tumor excision (rectal-cancer group). High throughput 16S rRNA amplicon sequencing of the V4–V5 region was conducted on the Ion PGM platform, reads were filtered using Qiime and clustered using UPARSE. We observed significant increases in species richness and diversity in rectal cancer samples, evidenced by the total number of OTUs and the Shannon and Simpson indexes. Enterotyping analysis divided our cohort into two groups, with the majority of rectal cancer samples clustering into one enterotype, characterized by a greater abundance of Bacteroides and Dorea. At the phylum level, rectal-cancer samples had increased abundance of candidate phylum OD1 (also known as Parcubacteria) whilst non-cancer samples had increased abundance of Planctomycetes. At the genera level, rectal-cancer samples had higher abundances of Bacteroides, Phascolarctobacterium, Parabacteroides, Desulfovibrio, and Odoribacter whereas non-cancer samples had higher abundances of Pseudomonas, Escherichia, Acinetobacter, Lactobacillus, and Bacillus. Two Bacteroides fragilis OTUs were more abundant among rectal-cancer patients seen through 16S rRNA amplicon sequencing, whose presence was confirmed by immunohistochemistry and enrichment verified by digital droplet PCR. Our findings point to increased bacterial richness and diversity in rectal cancer, along with several differences in microbial community composition. Our work is the first to present evidence for a possible role of bacteria such as B. fragilis and the phylum Parcubacteria in rectal cancer, emphasizing the need to study tissue-associated bacteria and specific regions of the gastrointestinal tract in order to better understand the possible links between the microbiota and rectal cancer.

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          Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics

          We introduce Dirichlet multinomial mixtures (DMM) for the probabilistic modelling of microbial metagenomics data. This data can be represented as a frequency matrix giving the number of times each taxa is observed in each sample. The samples have different size, and the matrix is sparse, as communities are diverse and skewed to rare taxa. Most methods used previously to classify or cluster samples have ignored these features. We describe each community by a vector of taxa probabilities. These vectors are generated from one of a finite number of Dirichlet mixture components each with different hyperparameters. Observed samples are generated through multinomial sampling. The mixture components cluster communities into distinct ‘metacommunities’, and, hence, determine envirotypes or enterotypes, groups of communities with a similar composition. The model can also deduce the impact of a treatment and be used for classification. We wrote software for the fitting of DMM models using the ‘evidence framework’ (http://code.google.com/p/microbedmm/). This includes the Laplace approximation of the model evidence. We applied the DMM model to human gut microbe genera frequencies from Obese and Lean twins. From the model evidence four clusters fit this data best. Two clusters were dominated by Bacteroides and were homogenous; two had a more variable community composition. We could not find a significant impact of body mass on community structure. However, Obese twins were more likely to derive from the high variance clusters. We propose that obesity is not associated with a distinct microbiota but increases the chance that an individual derives from a disturbed enterotype. This is an example of the ‘Anna Karenina principle (AKP)’ applied to microbial communities: disturbed states having many more configurations than undisturbed. We verify this by showing that in a study of inflammatory bowel disease (IBD) phenotypes, ileal Crohn's disease (ICD) is associated with a more variable community.
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            Connecting dysbiosis, bile-acid dysmetabolism and gut inflammation in inflammatory bowel diseases.

            Gut microbiota metabolises bile acids (BA). As dysbiosis has been reported in inflammatory bowel diseases (IBD), we aim to investigate the impact of IBD-associated dysbiosis on BA metabolism and its influence on the epithelial cell inflammation response. Faecal and serum BA rates, expressed as a proportion of total BA, were assessed by high-performance liquid chromatography tandem mass spectrometry in colonic IBD patients (42) and healthy subjects (29). The faecal microbiota composition was assessed by quantitative real-time PCR. Using BA profiles and microbiota composition, cluster formation between groups was generated by ranking models. The faecal BA profiles in germ-free and conventional mice were compared. Direct enzymatic activities of BA biotransformation were measured in faeces. The impact of BA on the inflammatory response was investigated in vitro using Caco-2 cells stimulated by IL-1β. IBD-associated dysbiosis was characterised by a decrease in the ratio between Faecalibacterium prausntizii and Escherichia coli. Faecal-conjugated BA rates were significantly higher in active IBD, whereas, secondary BA rates were significantly lower. Interestingly, active IBD patients exhibited higher levels of faecal 3-OH-sulphated BA. The deconjugation, transformation and desulphation activities of the microbiota were impaired in IBD patients. In vitro, secondary BA exerted anti-inflammatory effects, but sulphation of secondary BAs abolished their anti-inflammatory properties. Impaired microbiota enzymatic activity observed in IBD-associated dysbiosis leads to modifications in the luminal BA pool composition. Altered BA transformation in the gut lumen can erase the anti-inflammatory effects of some BA species on gut epithelial cells and could participate in the chronic inflammation loop of IBD.
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              Gut mucosal microbiome across stages of colorectal carcinogenesis

              Gut microbial dysbiosis contributes to the development of colorectal cancer (CRC). Here we catalogue the microbial communities in human gut mucosae at different stages of colorectal tumorigenesis. We analyse the gut mucosal microbiome of 47 paired samples of adenoma and adenoma-adjacent mucosae, 52 paired samples of carcinoma and carcinoma-adjacent mucosae and 61 healthy controls. Probabilistic partitioning of relative abundance profiles reveals that a metacommunity predominated by members of the oral microbiome is primarily associated with CRC. Analysis of paired samples shows differences in community configurations between lesions and the adjacent mucosae. Correlations of bacterial taxa indicate early signs of dysbiosis in adenoma, and co-exclusive relationships are subsequently more common in cancer. We validate these alterations in CRC-associated microbiome by comparison with two previously published data sets. Our results suggest that a taxonomically defined microbial consortium is implicated in the development of CRC.
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                Author and article information

                Contributors
                Journal
                Front Cell Infect Microbiol
                Front Cell Infect Microbiol
                Front. Cell. Infect. Microbiol.
                Frontiers in Cellular and Infection Microbiology
                Frontiers Media S.A.
                2235-2988
                09 December 2016
                2016
                : 6
                : 179
                Affiliations
                [1] 1Medical Genomics Laboratory, CIPE/A.C. Camargo Cancer Center São Paulo, Brazil
                [2] 2Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo São Paulo, Brazil
                [3] 3Curso de Pós-Graduação em Bioinformática, Universidade de São Paulo São Paulo, Brazil
                [4] 4Department of Pelvic Surgery, A.C. Camargo Cancer Center São Paulo, Brazil
                [5] 5Department of Pathology, A.C. Camargo Cancer Center São Paulo, Brazil
                [6] 6Laboratory of Molecular Gynecology, Department of Gynecology, Medicine College, Federal University of São Paulo São Paulo, Brazil
                [7] 7Centro de Oncologia Molecular, Hospital Sirio-Libanês São Paulo, Brazil
                [8] 8Departamento de Alimentos e Nutrição Experimental, Faculdade de Ciências Farmacêuticas, Food Research Center (FoRC), Universidade de São Paulo São Paulo, Brazil
                [9] 9Department of Clinical Oncology, A.C. Camargo Cancer Center São Paulo, Brazil
                [10] 10Laboratory of Computational Biology and Bioinformatics, A.C. Camargo Cancer Center São Paulo, Brazil
                [11] 11Biocomplexity Institute, Virginia Tech Blacksburg, VA, USA
                [12] 12Laboratory of Neurosciences (LIM-27) Alzira Denise Hertzog Silva, Institute of Psychiatry, Faculdade de Medicina, Universidade de São Paulo São Paulo, Brazil
                Author notes

                Edited by: Venkatakrishna Rao Jala, University of Louisville, USA

                Reviewed by: David Albert Scott, University of Louisville, USA; Daniel Raimunda, CONICET–UNC, Argentina

                *Correspondence: Emmanuel Dias-Neto emmanuel@ 123456cipe.accamargo.org.br
                Article
                10.3389/fcimb.2016.00179
                5145865
                28018861
                44dc2950-1b37-413c-a5df-58ef81f663b9
                Copyright © 2016 Thomas, Jesus, Lopes, Aguiar, Begnami, Rocha, Carpinetti, Camargo, Hoffmann, Freitas, Silva, Nunes, Setubal and Dias-Neto.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 26 September 2016
                : 24 November 2016
                Page count
                Figures: 4, Tables: 1, Equations: 3, References: 81, Pages: 13, Words: 9032
                Funding
                Funded by: Fundação de Amparo à Pesquisa do Estado de São Paulo 10.13039/501100001807
                Award ID: 2015/01507-7
                Categories
                Microbiology
                Original Research

                Infectious disease & Microbiology
                mucosa-associated microbiota,rectal cancer,16s rrna gene sequencing,bacteroides fragilis,bacterial diversity and community composition

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