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      Diet rapidly and reproducibly alters the human gut microbiome

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          Abstract

          Long-term diet influences the structure and activity of the trillions of microorganisms residing in the human gut 15 , but it remains unclear how rapidly and reproducibly the human gut microbiome responds to short-term macronutrient change. Here, we show that the short-term consumption of diets composed entirely of animal or plant products alters microbial community structure and overwhelms inter-individual differences in microbial gene expression. The animal-based diet increased the abundance of bile-tolerant microorganisms ( Alistipes, Bilophila, and Bacteroides) and decreased the levels of Firmicutes that metabolize dietary plant polysaccharides ( Roseburia, Eubacterium rectale , and Ruminococcus bromii). Microbial activity mirrored differences between herbivorous and carnivorous mammals 2 , reflecting trade-offs between carbohydrate and protein fermentation. Foodborne microbes from both diets transiently colonized the gut, including bacteria, fungi, and even viruses. Finally, increases in the abundance and activity of Bilophila wadsworthia on the animal-based diet support a link between dietary fat, bile acids, and the outgrowth of microorganisms capable of triggering inflammatory bowel disease 6 . In concert, these results demonstrate that the gut microbiome can rapidly respond to altered diet, potentially facilitating the diversity of human dietary lifestyles.

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          Most cited references 57

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          Fast gapped-read alignment with Bowtie 2.

          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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            QIIME allows analysis of high-throughput community sequencing data.

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              KEGG: kyoto encyclopedia of genes and genomes.

               M Kanehisa (2000)
              KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                16 December 2013
                11 December 2013
                23 January 2014
                23 July 2014
                : 505
                : 7484
                : 559-563
                Affiliations
                [1 ]FAS Center for Systems Biology, Harvard University, Cambridge, MA, 02138, USA.
                [2 ]Society of Fellows, Harvard University, Cambridge, MA, 02138, USA.
                [3 ]Division of Endocrinology, Children’s Hospital Boston, Harvard Medical School, Boston, MA, 02115, USA.
                [4 ]Department of Bioengineering & Therapeutic Sciences and the California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, CA, 94158, USA.
                Author notes
                [* ]To whom correspondence should be addressed. pturnbaugh@ 123456fas.harvard.edu
                [#]

                Present address: Mocular Genetics & Microbiology and Institute for Genome Sciences & Policy, Duke University, Durham, NC, 27708.

                Article
                NIHMS536070
                10.1038/nature12820
                3957428
                24336217

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