Predictability and persistence of prebiotic dietary supplementation in a healthy human cohort

Scientific Reports

Volumn 8, Issue 1, 2018, Pages

  Gurry, Thomas ^a,b   Dannenberg, Paul H ^a,e   Finlayson, Samuel G ^a,e   Hughes, Travis K ^a,e   Macias Trevino, Claudio ^a,e   Owusu Boaitey, Kwadwo ^a,e   Shomorony, Andre ^a,e   Tuang, Suan Lian ^a,e   Valenstein, Max L ^a,e   Wang, Kathy K ^a,e   Wu, Michael Pei hong ^a,e   Zack, Travis I ^a,e   Gibbons, Sean M ^a,b   Nguyen, Le Thanh Tu ^a   Kearney, Sean M ^a   Ananthakrishnan, Ashwin ^c   Jiang, Xiaofang ^a,b   Duvallet, Claire ^a   Kassam, Zain ^a,d   Alm, Eric J ^a,b  

^a Massachusetts Institute of Technology   (United States)

^b BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^c MASSACHUSETTS GENERAL HOSPITAL   (United States)

^d Open Biome   (United States)

^e HARVARD MIT DIVISION OF HEALTH SCIENCES AND TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PREBIOTIC AGENT;

ADULT; DIETARY SUPPLEMENT; GENETICS; HUMAN; INTESTINE FLORA; PHYSIOLOGY; SINGLE NUCLEOTIDE POLYMORPHISM; YOUNG ADULT;

ADULT; DIETARY SUPPLEMENTS; GASTROINTESTINAL MICROBIOME; HUMANS; POLYMORPHISM, SINGLE NUCLEOTIDE; PREBIOTICS; YOUNG ADULT;

EID: 85052211052     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/s41598-018-30783-1     Document Type: Article

References (58)

1. 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)
2. O’Keefe, S. J. D. et al. Fat, fibre and cancer risk in African Americans and rural Africans. Nat. Commun. 6, 6342 (2015)
3. David, L. A. et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505, 559–563 (2014)
4. Boyle, P. & Leon, M. E. Epidemiology of colorectal cancer. Br. Med. Bull. 64, 1–25 (2002)
5. Baxter, N. T., Ruffin, M. T., Rogers, M. A. M. & Schloss, P. D. Microbiota-based model improves the sensitivity of fecal immunochemical test for detecting colonic lesions. Genome Med. 8, 37 (2016)
6. Minot, S. et al. The human gut virome: Inter-individual variation and dynamic response to diet. Genome Res. 21, 1616–1625 (2011)
7. Vandeputte, D. et al. Prebiotic inulin-type fructans induce specific changes in the human gut microbiota. Gut 66, 1968–1974 (2017)
8. Dewulf, E. M. et al. Insight into the prebiotic concept: lessons from an exploratory, double blind intervention study with inulin-type fructans in obese women. Gut gutjnl-2012-303304, 10.1136/gutjnl-2012-303304 (2012)
9. Hoentjen, F. et al. Reduction of colitis by prebiotics in HLA-B27 transgenic rats is associated with microflora changes and immunomodulation. Inflamm. Bowel Dis. 11, 977–985 (2005)
10. Gibson, G. R., Beatty, E. R., Wang, X. & Cummings, J. H. Selective stimulation of bifidobacteria in the human colon by oligofructose and inulin. Gastroenterology 108, 975–982 (1995)
11. Kruse, H.-P., Kleessen, B. & Blaut, M. Effects of inulin on faecal bifidobacteria in human subjects. Br. J. Nutr. 82, 375–382 (1999)
12. Hunt, D. E. et al. Resource Partitioning and Sympatric Differentiation Among Closely Related Bacterioplankton. Science 320, 1081–1085 (2008)
13. Gibbons, S. M., Kearney, S. M., Smillie, C. S. & Alm, E. J. Two dynamic regimes in the human gut microbiome. PLOS Comput. Biol. 13, e1005364 (2017)
14. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq. 2. Genome Biol. 15, 550 (2014)
15. Weiss, S. et al. Normalization and microbial differential abundance strategies depend upon data characteristics. Microbiome 5, 27 (2017)
16. Cole, J. R. et al. The Ribosomal Database Project (RDP-II): sequences and tools for high-throughput rRNA analysis. Nucleic Acids Res. 33, D294–D296 (2005)
17. Ramirez-Farias, C. et al. Effect of inulin on the human gut microbiota: stimulation of Bifidobacterium adolescentis and Faecalibacterium prausnitzii. Br. J. Nutr. 101, 541–550 (2009)
18. Lopez-Siles, M. et al. Cultured Representatives of Two Major Phylogroups of Human Colonic Faecalibacterium prausnitzii Can Utilize Pectin, Uronic Acids, and Host-Derived Substrates for Growth. Appl. Environ. Microbiol. 78, 420–428 (2012)
19. Wu, M. et al. Genetic determinants of in vivo fitness and diet responsiveness in multiple human gut Bacteroides. Science 350, aac5992 (2015)
20. Bäckhed, F., Ley, R. E., Sonnenburg, J. L., Peterson, D. A. & Gordon, J. I. Host-Bacterial Mutualism in the Human Intestine. Science 307, 1915–1920 (2005)
21. Chassard, C., Delmas, E., Robert, C. & Bernalier-Donadille, A. Cellulose-degrading microbial community of the human gut varies according to the presence or absence of methanogens. FEMS Microbiol. Ecol. 74, 205–213 (2010)
22. Gibson, P. R. & Shepherd, S. J. Evidence-based dietary management of functional gastrointestinal symptoms: The FODMAP approach. J. Gastroenterol. Hepatol. 25, 252–258 (2010)
23. Chung, W. S. F. et al. Modulation of the human gut microbiota by dietary fibres occurs at the species level. BMC Biol. 14, 3 (2016)
24. Sonnenburg, E. D. et al. Specificity of Polysaccharide Use in Intestinal Bacteroides Species Determines Diet-Induced Microbiota Alterations. Cell 141, 1241–1252 (2010)
25. Xu, J. et al. Evolution of Symbiotic Bacteria in the Distal Human Intestine. PLOS Biol. 5, e156 (2007)
26. Yin, Y. et al. dbCAN: a web resource for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 40, W445–W451 (2012)
27. Sokol, H. et al. Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients. Proc. Natl. Acad. Sci. 105, 16731–16736 (2008)
28. Kishony, R. & Leibler, S. Environmental stresses can alleviate the average deleterious effect of mutations. J. Biol. 2, 14 (2003)
29. Maslowski, K. M. & Mackay, C. R. Diet, gut microbiota and immune responses. Nat. Immunol. 12, 5–9 (2011)
30. Willing, B. P. et al. A Pyrosequencing Study in Twins Shows That Gastrointestinal Microbial Profiles Vary With Inflammatory Bowel Disease Phenotypes. Gastroenterology 139, 1844–1854.e1 (2010)
31. Duvallet, C., Gibbons, S. M., Gurry, T., Irizarry, R. A. & Alm, E. J. Meta-analysis of gut microbiome studies identifies disease-specific and shared responses. Nat. Commun. 8, 1784, 10.1038/s41467-017-01973-8 (2017)
32. Devkota, S. et al. Dietary-fat-induced taurocholic acid promotes pathobiont expansion and colitis in Il10-/- mice. Nature 487, 104–108 (2012)
33. Ijssennagger, N., van der Meer, R. & van Mil, S. W. C. Sulfide as a Mucus Barrier-Breaker in Inflammatory Bowel Disease? Trends Mol. Med. 22, 190–199 (2016)
34. Moreno-Indias, I. et al. Insulin resistance is associated with specific gut microbiota in appendix samples from morbidly obese patients. Am. J. Transl. Res. 8, 5672–5684 (2016)
35. Williams, B. L., Hornig, M., Parekh, T. & Lipkin, W. I. Application of Novel PCR-Based Methods for Detection, Quantitation, and Phylogenetic Characterization of Sutterella Species in Intestinal Biopsy Samples from Children with Autism and Gastrointestinal Disturbances. mBio 3, e00261–11 (2012)
36. Desai, M. S. et al. A Dietary Fiber-Deprived Gut Microbiota Degrades the Colonic Mucus Barrier and Enhances Pathogen Susceptibility. Cell 167, 1339–1353.e21 (2016)
37. David, L. A. et al. Host lifestyle affects human microbiota on daily timescales. Genome Biol. 15, R89 (2014)
38. Rossi, M. et al. Fermentation of Fructooligosaccharides and Inulin by Bifidobacteria: a Comparative Study of Pure and Fecal Cultures. Appl. Environ. Microbiol. 71, 6150–6158 (2005)
39. Brockhausen, I., Schutzbach, J. & Kuhns, W. Glycoproteins and Their Relationship to Human Disease. Cells Tissues Organs 161, 36–78 (1998)
40. Corfield, A. P. et al. Glycosylation patterns of mucins in colonic disease. Biochem. Soc. Trans. 23, 840–845 (1995)
41. Shirazi, T., Longman, R. J., Corfield, A. P. & Probert, C. S. J. Mucins and inflammatory bowel disease. Postgrad. Med. J. 76, 473–478 (2000)
42. Zhang, J., Kobert, K., Flouri, T. & Stamatakis, A. PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinforma. Oxf. Engl. 30, 614–620 (2014)
43. Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010)
44. Edgar, R. C. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998 (2013)
45. NCBI Resource Coordinators. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 44, D7–D19 (2016)
46. Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree: Computing Large Minimum Evolution Trees with Profiles instead of a Distance Matrix. Mol. Biol. Evol. 26, 1641–1650 (2009)
47. Letunic, I. & Bork, P. Interactive tree of life (iTOL)v3: an online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res. 44, W242–245 (2016)
48. Lozupone, C. & Knight, R. UniFrac: a New Phylogenetic Method for Comparing Microbial Communities. Appl. Environ. Microbiol. 71, 8228–8235 (2005)
49. Kent, W. J. et al. The Human Genome Browser at UCSC. Genome Res. 12, 996–1006 (2002)
50. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinforma. Oxf. Engl. 25, 1754–1760 (2009)
51. Schmieder, R. & Edwards, R. Quality control and preprocessing of metagenomic datasets. Bioinformatics 27, 863–864 (2011)
52. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014)
53. Goujon, M. et al. A new bioinformatics analysis tools framework at EMBL–EBI. Nucleic Acids Res. 38, W695–W699 (2010)
54. Finn, R. D., Clements, J. & Eddy, S. R. HMMER web server: interactive sequence similarity searching. Nucleic Acids Res. 39, W29–W37 (2011)
55. Wu, M. & Eisen, J. A. A simple, fast, and accurate method of phylogenomic inference. Genome Biol. 9, R151 (2008)
56. Consortium, T. H. M. P. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012)
57. Smillie, C. S. et al. Strain Tracking Reveals the Determinants of Bacterial Engraftment in the Human Gut Following Fecal Microbiota Transplantation. Cell Host Microbe 23, 229–240.e5 (2018)
58. Wood, D. E. & Salzberg, S. L. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol. 15, R46 (2014)