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      Age‐related changes in the gut microbiota influence systemic inflammation and stroke outcome

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          Abstract

          Objective

          Chronic systemic inflammation contributes to the pathogenesis of many age‐related diseases. Although not well understood, alterations in the gut microbiota, or dysbiosis, may be responsible for age‐related inflammation.

          Methods

          Using stroke as a disease model, we tested the hypothesis that a youthful microbiota, when established in aged mice, produces positive outcomes following ischemic stroke. Conversely, an aged microbiota, when established in young mice, produces negative outcomes after stroke. Young and aged male mice had either a young or an aged microbiota established by fecal transplant gavage (FTG). Mice were subjected to ischemic stroke (middle cerebral artery occlusion; MCAO) or sham surgery. During the subsequent weeks, mice underwent behavioral testing and fecal samples were collected for 16S ribosomal RNA analysis of bacterial content.

          Results

          We found that the microbiota is altered after experimental stroke in young mice and resembles the biome of uninjured aged mice. In aged mice, the ratio of Firmicutes to Bacteroidetes (F:B), two main bacterial phyla in gut microbiota, increased ∼9‐fold ( p < 0.001) compared to young. This increased F:B ratio in aged mice is indicative of dysbiosis. Altering the microbiota in young by fecal gavage to resemble that of aged mice (∼6‐fold increase in F:B ratio, p < 0.001) increased mortality following MCAO, decreased performance in behavioral testing, and increased cytokine levels. Conversely, altering the microbiota in aged to resemble that of young (∼9‐fold decrease in F:B ratio, p < 0.001) increased survival and improved recovery following MCAO.

          Interpretation

          Aged biome increased the levels of systemic proinflammatory cytokines. We conclude that the gut microbiota can be modified to positively impact outcomes from age‐related diseases. Ann Neurol 2018;83:23–36

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          Most cited references 65

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          QIIME allows analysis of high-throughput community sequencing data.

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            UCHIME improves sensitivity and speed of chimera detection

            Motivation: Chimeric DNA sequences often form during polymerase chain reaction amplification, especially when sequencing single regions (e.g. 16S rRNA or fungal Internal Transcribed Spacer) to assess diversity or compare populations. Undetected chimeras may be misinterpreted as novel species, causing inflated estimates of diversity and spurious inferences of differences between populations. Detection and removal of chimeras is therefore of critical importance in such experiments. Results: We describe UCHIME, a new program that detects chimeric sequences with two or more segments. UCHIME either uses a database of chimera-free sequences or detects chimeras de novo by exploiting abundance data. UCHIME has better sensitivity than ChimeraSlayer (previously the most sensitive database method), especially with short, noisy sequences. In testing on artificial bacterial communities with known composition, UCHIME de novo sensitivity is shown to be comparable to Perseus. UCHIME is >100× faster than Perseus and >1000× faster than ChimeraSlayer. Contact: robert@drive5.com Availability: Source, binaries and data: http://drive5.com/uchime. Supplementary information: Supplementary data are available at Bioinformatics online.
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              Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB.

              A 16S rRNA gene database (http://greengenes.lbl.gov) addresses limitations of public repositories by providing chimera screening, standard alignment, and taxonomic classification using multiple published taxonomies. It was found that there is incongruent taxonomic nomenclature among curators even at the phylum level. Putative chimeras were identified in 3% of environmental sequences and in 0.2% of records derived from isolates. Environmental sequences were classified into 100 phylum-level lineages in the Archaea and Bacteria.
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                Author and article information

                Contributors
                Louise.D.McCullough@uth.tmc.edu
                Journal
                Ann Neurol
                Ann. Neurol
                10.1002/(ISSN)1531-8249
                ANA
                Annals of Neurology
                John Wiley and Sons Inc. (Hoboken )
                0364-5134
                1531-8249
                18 July 2018
                July 2018
                : 84
                : 1 ( doiID: 10.1002/ana.v84.1 )
                : 23-36
                Affiliations
                [ 1 ] Department of Neurology McGovern Medical School at University of Texas Health Science Center Houston TX
                [ 2 ] Department of Anesthesiology University of Maryland Baltimore MD
                [ 3 ] Department of Anesthesiology Baylor College of Medicine Houston TX
                [ 4 ] Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology & Microbiology, Baylor College of Medicine Houston TX
                [ 5 ] Dan L. Duncan Comprehensive Cancer Center, Advanced Technology Core, Alkek Center for Molecular Discovery, Department of Molecular and Cellular Biology, Baylor College of Medicine Houston TX
                [ 6 ] Department of Molecular and Cell Biology, Institute of Systems Genomics University of Connecticut Storrs CT
                Author notes
                [* ]Address correspondence to Dr Louise D. McCullough, Department of Neurology, University of Texas Health Science Center, 6410 Fannin Street, Suite 1014, Houston, TX 77030. E‐mail: Louise.D.McCullough@ 123456uth.tmc.edu .
                [†]

                Equally contributing authors

                Article
                ANA25250
                10.1002/ana.25250
                6119509
                29733457
                © 2018 The Authors. Annals of Neurology published by Wiley Periodicals, Inc. on behalf of American Neurological Association

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                Page count
                Figures: 7, Tables: 0, Pages: 14, Words: 9957
                Product
                Funding
                Funded by: NINDS
                Award ID: RO1 NSO94543
                Award ID: R01NS080531
                Award ID: R21 NS094806
                Award ID: RF1AG058463
                Award ID: R01NS103592
                Funded by: NIH Public Health Service Grant
                Award ID: DK‐56338
                Funded by: American Heart Association
                Award ID: 16SDG29970000
                Award ID: 15SDG23250025
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                ana25250
                July 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.6.5 mode:remove_FC converted:10.07.2019

                Neurology

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