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      Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases

      research-article
      1 , 2 , 2 , 3 , 1 , 3 , 4 , 1 , 3 , 5 , 1 , 2 , 6 , 7 , 3 , 8 , 9 , 1 , 10 , 11 , 1 , 2 , 1 , 12 , 1 , 2 , 13 , 1 , 14 , 15 , 16 , 6 , IBDMDB Investigators, 7 , 10 , 18 , 6 , 8 , 16 , 19 , 12 , 11 , 5 , 20 , 21 , 22 , 4 , 2 , 1 , 1 , 3 , 23 , 1 , 2 ,
      Nature
      Nature Publishing Group UK
      Ulcerative colitis, Microbiome, Systems analysis, Crohn's disease

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          Abstract

          Inflammatory bowel diseases, which include Crohn’s disease and ulcerative colitis, affect several million individuals worldwide. Crohn’s disease and ulcerative colitis are complex diseases that are heterogeneous at the clinical, immunological, molecular, genetic, and microbial levels. Individual contributing factors have been the focus of extensive research. As part of the Integrative Human Microbiome Project (HMP2 or iHMP), we followed 132 subjects for one year each to generate integrated longitudinal molecular profiles of host and microbial activity during disease (up to 24 time points each; in total 2,965 stool, biopsy, and blood specimens). Here we present the results, which provide a comprehensive view of functional dysbiosis in the gut microbiome during inflammatory bowel disease activity. We demonstrate a characteristic increase in facultative anaerobes at the expense of obligate anaerobes, as well as molecular disruptions in microbial transcription (for example, among clostridia), metabolite pools (acylcarnitines, bile acids, and short-chain fatty acids), and levels of antibodies in host serum. Periods of disease activity were also marked by increases in temporal variability, with characteristic taxonomic, functional, and biochemical shifts. Finally, integrative analysis identified microbial, biochemical, and host factors central to this dysregulation. The study’s infrastructure resources, results, and data, which are available through the Inflammatory Bowel Disease Multi’omics Database ( http://ibdmdb.org), provide the most comprehensive description to date of host and microbial activities in inflammatory bowel diseases.

          Abstract

          The Inflammatory Bowel Disease Multi’omics Database includes longitudinal data encompassing a multitude of analyses of stool, blood and biopsies of more than 100 individuals, and provides a comprehensive description of host and microbial activities in inflammatory bowel diseases.

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          Most cited references49

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          Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn's disease.

          Crohn's disease and ulcerative colitis, the two main types of chronic inflammatory bowel disease, are multifactorial conditions of unknown aetiology. A susceptibility locus for Crohn's disease has been mapped to chromosome 16. Here we have used a positional-cloning strategy, based on linkage analysis followed by linkage disequilibrium mapping, to identify three independent associations for Crohn's disease: a frameshift variant and two missense variants of NOD2, encoding a member of the Apaf-1/Ced-4 superfamily of apoptosis regulators that is expressed in monocytes. These NOD2 variants alter the structure of either the leucine-rich repeat domain of the protein or the adjacent region. NOD2 activates nuclear factor NF-kB; this activating function is regulated by the carboxy-terminal leucine-rich repeat domain, which has an inhibitory role and also acts as an intracellular receptor for components of microbial pathogens. These observations suggest that the NOD2 gene product confers susceptibility to Crohn's disease by altering the recognition of these components and/or by over-activating NF-kB in monocytes, thus documenting a molecular model for the pathogenic mechanism of Crohn's disease that can now be further investigated.
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            The microbiome in inflammatory bowel disease: current status and the future ahead.

            Studies of the roles of microbial communities in the development of inflammatory bowel disease (IBD) have reached an important milestone. A decade of genome-wide association studies and other genetic analyses have linked IBD with loci that implicate an aberrant immune response to the intestinal microbiota. More recently, profiling studies of the intestinal microbiome have associated the pathogenesis of IBD with characteristic shifts in the composition of the intestinal microbiota, reinforcing the view that IBD results from altered interactions between intestinal microbes and the mucosal immune system. Enhanced technologies can increase our understanding of the interactions between the host and its resident microbiota and their respective roles in IBD from both a large-scale pathway view and at the metabolic level. We review important microbiome studies of patients with IBD and describe what we have learned about the mechanisms of intestinal microbiota dysfunction. We describe the recent progress in microbiome research from exploratory 16S-based studies, reporting associations of specific organisms with a disease, to more recent studies that have taken a more nuanced view, addressing the function of the microbiota by metagenomic and metabolomic methods. Finally, we propose study designs and methodologies for future investigations of the microbiome in patients with inflammatory gut and autoimmune diseases in general. Copyright © 2014 AGA Institute. Published by Elsevier Inc. All rights reserved.
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              UniRef: comprehensive and non-redundant UniProt reference clusters.

              Redundant protein sequences in biological databases hinder sequence similarity searches and make interpretation of search results difficult. Clustering of protein sequence space based on sequence similarity helps organize all sequences into manageable datasets and reduces sampling bias and overrepresentation of sequences. The UniRef (UniProt Reference Clusters) provide clustered sets of sequences from the UniProt Knowledgebase (UniProtKB) and selected UniProt Archive records to obtain complete coverage of sequence space at several resolutions while hiding redundant sequences. Currently covering >4 million source sequences, the UniRef100 database combines identical sequences and subfragments from any source organism into a single UniRef entry. UniRef90 and UniRef50 are built by clustering UniRef100 sequences at the 90 or 50% sequence identity levels. UniRef100, UniRef90 and UniRef50 yield a database size reduction of approximately 10, 40 and 70%, respectively, from the source sequence set. The reduced redundancy increases the speed of similarity searches and improves detection of distant relationships. UniRef entries contain summary cluster and membership information, including the sequence of a representative protein, member count and common taxonomy of the cluster, the accession numbers of all the merged entries and links to rich functional annotation in UniProtKB to facilitate biological discovery. UniRef has already been applied to broad research areas ranging from genome annotation to proteomics data analysis. UniRef is updated biweekly and is available for online search and retrieval at http://www.uniprot.org, as well as for download at ftp://ftp.uniprot.org/pub/databases/uniprot/uniref. Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                chuttenh@hsph.harvard.edu
                Journal
                Nature
                Nature
                Nature
                Nature Publishing Group UK (London )
                0028-0836
                1476-4687
                29 May 2019
                29 May 2019
                2019
                : 569
                : 7758
                : 655-662
                Affiliations
                [1 ]GRID grid.66859.34, Infectious Disease and Microbiome Program, , Broad Institute of MIT and Harvard, ; Cambridge, MA USA
                [2 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Biostatistics, , Harvard T. H. Chan School of Public Health, ; Boston, MA USA
                [3 ]ISNI 0000 0004 0386 9924, GRID grid.32224.35, Gastroenterology, Massachusetts General Hospital, ; Boston, MA USA
                [4 ]GRID grid.66859.34, Metabolomics Platform, , Broad Institute of MIT and Harvard, ; Cambridge, MA USA
                [5 ]ISNI 0000 0001 2160 926X, GRID grid.39382.33, Molecular Virology and Microbiology, , Baylor College of Medicine, ; Houston, TX USA
                [6 ]ISNI 0000 0001 2218 3491, GRID grid.451303.0, Earth and Biological Sciences Directorate, , Pacific Northwest National Lab, ; Richland, WA USA
                [7 ]ISNI 0000 0000 9632 6718, GRID grid.19006.3e, Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, , University of California Los Angeles, ; Los Angeles, CA USA
                [8 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Department of Pediatrics, , University of California San Diego, ; La Jolla, CA USA
                [9 ]ISNI 0000 0000 9632 6718, GRID grid.19006.3e, Molecular and Medical Pharmacology, , University of California Los Angeles, ; Los Angeles, CA USA
                [10 ]ISNI 0000 0000 9025 8099, GRID grid.239573.9, Department of Pediatrics, , Cincinnati Children’s Hospital Medical Center, ; Cincinnati, OH USA
                [11 ]ISNI 0000 0001 2152 9905, GRID grid.50956.3f, F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, , Cedars-Sinai Medical Center, ; Los Angeles, CA USA
                [12 ]ISNI 0000 0001 0941 6502, GRID grid.189967.8, Department of Pediatrics, , Emory University, ; Atlanta, GA USA
                [13 ]ISNI 0000 0000 9632 6718, GRID grid.19006.3e, Vatche and Tamar Manoukian Division of Digestive Diseases, , University of California Los Angeles, ; Los Angeles, CA USA
                [14 ]ISNI 0000 0001 1034 3451, GRID grid.12650.30, Department of Odontology, , Umeå University, ; Umeå, Sweden
                [15 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Jacobs School of Engineering, , University of California San Diego, ; La Jolla, CA USA
                [16 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Center for Microbiome Innovation, , University of California San Diego, ; La Jolla, CA USA
                [18 ]ISNI 0000 0001 2179 9593, GRID grid.24827.3b, Department of Pediatrics, , University of Cincinnati College of Medicine, ; Cincinnati, OH USA
                [19 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Department of Computer Science and Engineering, , University of California San Diego, ; La Jolla, CA USA
                [20 ]ISNI 0000 0001 2355 7002, GRID grid.4367.6, Department of Pathology & Immunology, , Washington University, ; St. Louis, MO USA
                [21 ]ISNI 0000 0004 0386 9924, GRID grid.32224.35, Department of Pediatrics, , MassGeneral Hospital for Children, ; Boston, MA USA
                [22 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Pediatrics, , Harvard Medical School, ; Boston, MA USA
                [23 ]ISNI 0000 0001 2341 2786, GRID grid.116068.8, Center for Microbiome Informatics and Therapeutics, , Massachusetts Institute of Technology, ; Cambridge, MA USA
                Article
                1237
                10.1038/s41586-019-1237-9
                6650278
                31142855
                6db42dd8-5be4-4b50-9231-bd0db3a0b01c
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 February 2018
                : 16 April 2019
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                © The Author(s), under exclusive licence to Springer Nature Limited 2019

                Uncategorized
                ulcerative colitis,microbiome,systems analysis,crohn's disease
                Uncategorized
                ulcerative colitis, microbiome, systems analysis, crohn's disease

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