Diet rapidly and reproducibly alters the human gut microbiome

Diet rapidly and reproducibly alters the human gut microbiome

  • 1

    Wu, G. D. et al. Linking long-term dietary patterns with gut microbial enterotypes. Science 334, 105–108 (2011)

  • 2

    Muegge, B. D. et al. Diet drives convergence in gut microbiome functions across mammalian phylogeny and within humans. Science 332, 970–974 (2011)

  • 3

    Duncan, S. H. et al. Reduced dietary intake of carbohydrates by obese subjects results in decreased concentrations of butyrate and butyrate-producing bacteria in feces. Appl. Environ. Microbiol. 73, 1073–1078 (2007)

  • 4

    Ley, R. E., Turnbaugh, P. J., Klein, S. & Gordon, J. I. Microbial ecology: human gut microbes associated with obesity. Nature 444, 1022–1023 (2006)

  • 5

    Walker, A. W. et al. Dominant and diet-responsive groups of bacteria within the human colonic microbiota. ISME J. 5, 220–230 (2011)

  • 6

    Devkota, S. et al. Dietary-fat-induced taurocholic acid promotes pathobiont expansion and colitis in Il10−/− mice. Nature 487, 104–108 (2012)

  • 7

    Turnbaugh, P. J. et al. The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice. Sci. Transl. Med. 1, 6ra14 (2009)

  • 8

    Turnbaugh, P. J. et al. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444, 1027–1031 (2006)

  • 9

    Faith, J. J., McNulty, N. P., Rey, F. E. & Gordon, J. I. Predicting a human gut microbiota’s response to diet in gnotobiotic mice. Science 333, 101–104 (2011)

  • 10

    Russell, W. R. et al. High-protein, reduced-carbohydrate weight-loss diets promote metabolite profiles likely to be detrimental to colonic health. Am. J. Clin. Nutr. 93, 1062–1072 (2011)

  • 11

    Cordain, L. et al. Plant-animal subsistence ratios and macronutrient energy estimations in worldwide hunter-gatherer diets. Am. J. Clin. Nutr. 71, 682–692 (2000)

  • 12

    Arumugam, M. et al. Enterotypes of the human gut microbiome. Nature 473, 174–180 (2011)

  • 13

    De Filippo, C. et al. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc. Natl Acad. Sci. USA 107, 14691–14696 (2010)

  • 14

    Reddy, B. S. Diet and excretion of bile acids. Cancer Res. 41, 3766–3768 (1981)

  • 15

    Smith, E. A. & Macfarlane, G. T. Enumeration of amino acid fermenting bacteria in the human large intestine: effects of pH and starch on peptide metabolism and dissimilation of amino acids. FEMS Microbiol. Ecol. 25, 355–368 (1998)

  • 16

    Smith, E. A. & Macfarlane, G. T. Enumeration of human colonic bacteria producing phenolic and indolic compounds: effects of pH, carbohydrate availability and retention time on dissimilatory aromatic amino acid metabolism. J. Appl. Bacteriol. 81, 288–302 (1996)

  • 17

    Sinha, R. et al. High concentrations of the carcinogen 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) occur in chicken but are dependent on the cooking method. Cancer Res. 55, 4516–4519 (1995)

  • 18

    Langille, M. G. I. et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature Biotechnol. 31, 814–821 (2013)

  • 19

    Kanehisa, M. & Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27–30 (2000)

  • 20

    Pittard, J. & Wallace, B. J. Distribution and function of genes concerned with aromatic biosynthesis in Escherichia coli. J. Bacteriol. 91, 1494–1508 (1966)

  • 21

    Hawkes, K., O’Connell, J. F. & Jones, N. G. Hunting income patterns among the Hadza: big game, common goods, foraging goals and the evolution of the human diet. Philos. Trans. R. Soc. Lond. B Biol. Sci. 334, 243–250 (1991)

  • 22

    Bourdichon, F., Berger, B. & Casaregola, S. Safety demonstration of microbial food cultures (MFC) in fermented food products. Bull. Int. Dairy Fed. 455, 1–66 (2012)

  • 23

    Nychas, G. J. & Arkoudelos, J. S. Staphylococci: their role in fermented sausages. Soc. Appl. Bacteriol. Symp. Ser. 19, 167S–188S (1990)

  • 24

    McGavin, W. J. & Macfarlane, S. A. Rubus chlorotic mottle virus, a new sobemovirus infecting raspberry and bramble. Virus Res. 139, 10–13 (2009)

  • 25

    Zhang, T. et al. RNA viral community in human feces: prevalence of plant pathogenic viruses. PLoS Biol. 4, e3 (2006)

  • 26

    Yoshimoto, S. et al. Obesity-induced gut microbial metabolite promotes liver cancer through senescence secretome. Nature 499, 97–101 (2013)

  • 27

    Ridlon, J. M., Kang, D. J. & Hylemon, P. B. Bile salt biotransformations by human intestinal bacteria. J. Lipid Res. 47, 241–259 (2006)

  • 28

    Islam, K. B. et al. Bile acid is a host factor that regulates the composition of the cecal microbiota in rats. Gastroenterology 141, 1773–1781 (2011)

  • 29

    Maurice, C. F., Haiser, H. J. & Turnbaugh, P. J. Xenobiotics shape the physiology and gene expression of the active human gut microbiome. Cell 152, 39–50 (2013)

  • 30

    Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7, 335–336 (2010)

  • 31

    Lewis, S. J. & Heaton, K. W. Stool form scale as a useful guide to intestinal transit time. Scand. J. Gastroenterol. 32, 920–924 (1997)

  • 32

    National Institutes of Health Diet History Questionnaire Version 2.0 (National Institutes of Health, Applied Research Program, National Cancer Institute, 2010)

  • 33

    Caporaso, J. G. et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl Acad. Sci. USA 108 (suppl. 1). 4516–4522 (2011)

  • 34

    Caporaso, J. G. et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 6, 1621–1624 (2012)

  • 35

    DeSantis, T. Z. et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microbiol. 72, 5069–5072 (2006)

  • 36

    Jones, E. et al. SciPy: open source scientific tools for Python. (2001)

  • 37

    McKinney, W. Data structures for statistical computing in Python. Proc. 9th Python Sci. Conf. 51–56. (2010)

  • 38

    Strimmer, K. fdrtool: a versatile R package for estimating local and tail areabased false discovery rates. Bioinformatics 24, 1461–1462 (2008)

  • 39

    Friedman, J. & Alm, E. J. Inferring correlation networks from genomic survey data. PLoS Comput. Biol. 8, e1002687 (2012)

  • 40

    Turnbaugh, P. J. et al. Organismal, genetic, and transcriptional variation in the deeply sequenced gut microbiomes of identical twins. Proc. Natl Acad. Sci. USA 107, 7503–7508 (2010)

  • 41

    Rey, F. E. et al. Dissecting the in vivo metabolic potential of two human gut acetogens. J. Biol. Chem. 285, 22082–22090 (2010)

  • 42

    Nelson, K. E. et al. A catalog of reference genomes from the human microbiome. Science 328, 994–999 (2010)

  • 43

    Ning, Z., Cox, A. J. & Mullikin, J. C. SSAHA: a fast search method for large DNA databases. Genome Res. 11, 1725–1729 (2001)

  • 44

    Abubucker, S. et al. Metabolic reconstruction for metagenomic data and its application to the human microbiome. PLOS Comput. Biol. 8, e1002358 (2012)

  • 45

    Segata, N. et al. Metagenomic biomarker discovery and explanation. Genome Biol. 12, R60 (2011)

  • 46

    Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nature Methods 9, 357–359 (2012)

  • 47

    Markowitz, V. M. et al. IMG: the Integrated Microbial Genomes database and comparative analysis system. Nucleic Acids Res. 40, D115–D122 (2012)

  • 48

    Martin, J. et al. Optimizing read mapping to reference genomes to determine composition and species prevalence in microbial communities. PLoS ONE 7, e36427 (2012)

  • 49

    Deplancke, B. et al. Molecular ecological analysis of the succession and diversity of sulfate-reducing bacteria in the mouse gastrointestinal tract. Appl. Environ. Microbiol. 66, 2166–2174 (2000)

  • 50

    Stewart, J. A., Chadwick, V. S. & Murray, A. Carriage, quantification, and predominance of methanogens and sulfate-reducing bacteria in faecal samples. Lett. Appl. Microbiol. 43, 58–63 (2006)

  • 51

    Porter, J. L. et al. Accurate enzymatic measurement of fecal bile acids in patients with malabsorption. J. Lab. Clin. Med. 141, 411–418 (2003)

  • 52

    Setchell, K. D., Lawson, A. M., Tanida, N. & Sjovall, J. General methods for the analysis of metabolic profiles of bile acids and related compounds in feces. J. Lipid Res. 24, 1085–1100 (1983)

  • 53

    Schoch, C. L. et al. Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi. Proc. Natl Acad. Sci. USA 109, 6241–6246 (2012)

  • 54

    Gardes, M. & Bruns, T. D. ITS primers with enhanced specificity for basidiomycetes application to the identification of mycorrhizae and rusts. Mol. Ecol. 2, 113–118 (1993)

  • 55

    White, T. J., Bruns, T., Lee, S. & Taylor, J. in PCR Protocols: A Guide to Methods and Applications (eds Gelfand, D. H., Innis, M. A., Shinsky, J. J. & White, T. J. ) 315–322. (1990)

  • 56

    Walker, H. K., Hall, W. D., Hurst, J. W., Comstock, J. P. & Garber, A. J. Ketonuria 3rd edn (Butterworths, 1990)

  • Source Article