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      Microbiome of prebiotic-treated mice reveals novel targets involved in host response during obesity

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          Abstract

          The gut microbiota is involved in metabolic and immune disorders associated with obesity and type 2 diabetes. We previously demonstrated that prebiotic treatment may significantly improve host health by modulating bacterial species related to the improvement of gut endocrine, barrier and immune functions. An analysis of the gut metagenome is needed to determine which bacterial functions and taxa are responsible for beneficial microbiota–host interactions upon nutritional intervention. We subjected mice to prebiotic (Pre) treatment under physiological (control diet: CT) and pathological conditions (high-fat diet: HFD) for 8 weeks and investigated the production of intestinal antimicrobial peptides and the gut microbiome. HFD feeding significantly decreased the expression of regenerating islet-derived 3-gamma (Reg3g) and phospholipase A2 group-II (PLA2g2) in the jejunum. Prebiotic treatment increased Reg3g expression (by ∼50-fold) and improved intestinal homeostasis as suggested by the increase in the expression of intectin, a key protein involved in intestinal epithelial cell turnover. Deep metagenomic sequencing analysis revealed that HFD and prebiotic treatment significantly affected the gut microbiome at different taxonomic levels. Functional analyses based on the occurrence of clusters of orthologous groups (COGs) of proteins also revealed distinct profiles for the HFD, Pre, HFD-Pre and CT groups. Finally, the gut microbiota modulations induced by prebiotics counteracted HFD-induced inflammation and related metabolic disorders. Thus, we identified novel putative taxa and metabolic functions that may contribute to the development of or protection against the metabolic alterations observed during HFD feeding and HFD-Pre feeding.

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          Most cited references 20

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          Paneth cells, antimicrobial peptides and maintenance of intestinal homeostasis.

          Building and maintaining a homeostatic relationship between a host and its colonizing microbiota entails ongoing complex interactions between the host and the microorganisms. The mucosal immune system, including epithelial cells, plays an essential part in negotiating this equilibrium. Paneth cells (specialized cells in the epithelium of the small intestine) are an important source of antimicrobial peptides in the intestine. These cells have become the focus of investigations that explore the mechanisms of host-microorganism homeostasis in the small intestine and its collapse in the processes of infection and chronic inflammation. In this Review, we provide an overview of the intestinal microbiota and describe the cell biology of Paneth cells, emphasizing the composition of their secretions and the roles of these cells in intestinal host defence and homeostasis. We also highlight the implications of Paneth cell dysfunction in susceptibility to chronic inflammatory bowel disease.
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            Fast Identification and Removal of Sequence Contamination from Genomic and Metagenomic Datasets

            High-throughput sequencing technologies have strongly impacted microbiology, providing a rapid and cost-effective way of generating draft genomes and exploring microbial diversity. However, sequences obtained from impure nucleic acid preparations may contain DNA from sources other than the sample. Those sequence contaminations are a serious concern to the quality of the data used for downstream analysis, causing misassembly of sequence contigs and erroneous conclusions. Therefore, the removal of sequence contaminants is a necessary and required step for all sequencing projects. We developed DeconSeq, a robust framework for the rapid, automated identification and removal of sequence contamination in longer-read datasets ( 150 bp mean read length). DeconSeq is publicly available as standalone and web-based versions. The results can be exported for subsequent analysis, and the databases used for the web-based version are automatically updated on a regular basis. DeconSeq categorizes possible contamination sequences, eliminates redundant hits with higher similarity to non-contaminant genomes, and provides graphical visualizations of the alignment results and classifications. Using DeconSeq, we conducted an analysis of possible human DNA contamination in 202 previously published microbial and viral metagenomes and found possible contamination in 145 (72%) metagenomes with as high as 64% contaminating sequences. This new framework allows scientists to automatically detect and efficiently remove unwanted sequence contamination from their datasets while eliminating critical limitations of current methods. DeconSeq's web interface is simple and user-friendly. The standalone version allows offline analysis and integration into existing data processing pipelines. DeconSeq's results reveal whether the sequencing experiment has succeeded, whether the correct sample was sequenced, and whether the sample contains any sequence contamination from DNA preparation or host. In addition, the analysis of 202 metagenomes demonstrated significant contamination of the non-human associated metagenomes, suggesting that this method is appropriate for screening all metagenomes. DeconSeq is available at http://deconseq.sourceforge.net/.
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              Responses of Gut Microbiota and Glucose and Lipid Metabolism to Prebiotics in Genetic Obese and Diet-Induced Leptin-Resistant Mice

              OBJECTIVE To investigate deep and comprehensive analysis of gut microbial communities and biological parameters after prebiotic administration in obese and diabetic mice. RESEARCH DESIGN AND METHODS Genetic (ob/ob) or diet-induced obese and diabetic mice were chronically fed with prebiotic-enriched diet or with a control diet. Extensive gut microbiota analyses, including quantitative PCR, pyrosequencing of the 16S rRNA, and phylogenetic microarrays, were performed in ob/ob mice. The impact of gut microbiota modulation on leptin sensitivity was investigated in diet-induced leptin-resistant mice. Metabolic parameters, gene expression, glucose homeostasis, and enteroendocrine-related L-cell function were documented in both models. RESULTS In ob/ob mice, prebiotic feeding decreased Firmicutes and increased Bacteroidetes phyla, but also changed 102 distinct taxa, 16 of which displayed a >10-fold change in abundance. In addition, prebiotics improved glucose tolerance, increased L-cell number and associated parameters (intestinal proglucagon mRNA expression and plasma glucagon-like peptide-1 levels), and reduced fat-mass development, oxidative stress, and low-grade inflammation. In high fat–fed mice, prebiotic treatment improved leptin sensitivity as well as metabolic parameters. CONCLUSIONS We conclude that specific gut microbiota modulation improves glucose homeostasis, leptin sensitivity, and target enteroendocrine cell activity in obese and diabetic mice. By profiling the gut microbiota, we identified a catalog of putative bacterial targets that may affect host metabolism in obesity and diabetes.
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                Author and article information

                Journal
                ISME J
                ISME J
                The ISME Journal
                Nature Publishing Group
                1751-7362
                1751-7370
                October 2014
                03 April 2014
                1 October 2014
                : 8
                : 10
                : 2116-2130
                Affiliations
                [1 ]Université catholique de Louvain, Louvain Drug Research Institute, WELBIO (Walloon Excellence in Life sciences and BIOtechnology), Metabolism and Nutrition Research Group , Brussels, Belgium
                [2 ]Geneva University Hospitals, Division of Infectious Diseases, Genomic Research Lab , Geneva, Switzerland
                [3 ]Wallenberg Laboratory/Sahlgrenska Center for Cardiovascular and Metabolic Research, Sahlgrenska University Hospital , Gothenburg, Sweden
                [4 ]Department of Molecular and Clinical Medicine, University of Gothenburg , Gothenburg, Sweden
                [5 ]Geneva University Hospitals, Laboratory of Bacteriology , Geneva, Switzerland
                Author notes
                [* ]Université catholique de Louvain, LDRI, Metabolism and Nutrition Research Group , Av. E. Mounier, 73 Box B1.73.11, 1200 Brussels, Belgium. E-mail: patrice.cani@ 123456uclouvain.be
                [6]

                These authors contributed equally to this work.

                Article
                ismej201445
                10.1038/ismej.2014.45
                4163056
                24694712
                Copyright © 2014 International Society for Microbial Ecology

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/

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