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Association of dietary fibre intake and gut microbiota in adults

  • Daniel Lin (a1), Brandilyn A. Peters (a2), Charles Friedlander (a3) (a4), Hal J. Freiman (a4), James J. Goedert (a5), Rashmi Sinha (a5), George Miller (a1) (a6), Mitchell A. Bernstein (a6), Richard B. Hayes (a1) (a2) and Jiyoung Ahn (a1) (a2)...


Increasing evidence indicates that gut microbiota may influence colorectal cancer risk. Diet, particularly fibre intake, may modify gut microbiota composition, which may affect cancer risk. We investigated the relationship between dietary fibre intake and gut microbiota in adults. Using 16S rRNA gene sequencing, we assessed gut microbiota in faecal samples from 151 adults in two independent study populations: National Cancer Institute (NCI), n 75, and New York University (NYU), n 76. We calculated energy-adjusted fibre intake based on FFQ. For each study population with adjustment for age, sex, race, BMI and smoking, we evaluated the relationship between fibre intake and gut microbiota community composition and taxon abundance. Total fibre intake was significantly associated with overall microbial community composition in NYU (P=0·008) but not in NCI (P=0·81). In a meta-analysis of both study populations, higher fibre intake tended to be associated with genera of class Clostridia, including higher abundance of SMB53 (fold change (FC)=1·04, P=0·04), Lachnospira (FC=1·03, P=0·05) and Faecalibacterium (FC=1·03, P=0·06), and lower abundance of Actinomyces (FC=0·95, P=0·002), Odoribacter (FC=0·95, P=0·03) and Oscillospira (FC=0·96, P=0·06). A species-level meta-analysis showed that higher fibre intake was marginally associated with greater abundance of Faecalibacterium prausnitzii (FC=1·03, P=0·07) and lower abundance of Eubacterium dolichum (FC=0·96, P=0·04) and Bacteroides uniformis (FC=0·97, P=0·05). Thus, dietary fibre intake may impact gut microbiota composition, particularly class Clostridia, and may favour putatively beneficial bacteria such as F. prausnitzii. These findings warrant further understanding of diet–microbiota relationships for future development of colorectal cancer prevention strategies.


Corresponding author

*Corresponding author: J. Ahn, email


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1. Human Microbiome Project Consortium (2012) Structure, function and diversity of the healthy human microbiome. Nature 486, 207214.
2. Hold, GL, Smith, M, Grange, C, et al. (2014) Role of the gut microbiota in inflammatory bowel disease pathogenesis: what have we learnt in the past 10 years? World J Gastroenterol 20, 11921210.
3. Marchesi, JR, Dutilh, BE, Hall, N, et al. (2011) Towards the human colorectal cancer microbiome. PLoS ONE 6, e20447.
4. Han, M, Wang, C, Liu, P, et al. (2017) Dietary fiber gap and host gut microbiota. Protein Pept Lett 24, 388396.
5. Sobhani, I, Tap, J, Roudot-Thoraval, F, et al. (2011) Microbial dysbiosis in colorectal cancer (CRC) patients. PLoS ONE 6, e16393.
6. Ahn, J, Sinha, R, Pei, Z, et al. (2013) Human gut microbiome and risk for colorectal cancer. J Natl Cancer Inst 105, 19071911.
7. Chen, W, Liu, F, Ling, Z, et al. (2012) Human intestinal lumen and mucosa-associated microbiota in patients with colorectal cancer. PLOS ONE 7, e39743.
8. Weir, TL, Manter, DK, Sheflin, AM, et al. (2013) Stool microbiome and metabolome differences between colorectal cancer patients and healthy adults. PLOS ONE 8, e70803.
9. Bouvard, V, Loomis, D, Guyton, KZ, et al. (2015) Carcinogenicity of consumption of red and processed meat. Lancet Oncol 16, 15991600.
10. Aune, D, Chan, DS, Lau, R, et al. (2011) Dietary fibre, whole grains, and risk of colorectal cancer: systematic review and dose-response meta-analysis of prospective studies. BMJ 343, d6617.
11. Donohoe, DR, Holley, D, Collins, LB, et al. (2014) A gnotobiotic mouse model demonstrates that dietary fiber protects against colorectal tumorigenesis in a microbiota- and butyrate-dependent manner. Cancer Discov 4, 13871397.
12. O’Keefe, SJ, Li, JV, Lahti, L, et al. (2015) Fat, fibre and cancer risk in African Americans and rural Africans. Nat Commun 6, 6342.
13. Tap, J, Furet, JP, Bensaada, M, et al. (2015) Gut microbiota richness promotes its stability upon increased dietary fibre intake in healthy adults. Environ Microbiol 17, 49544964.
14. Liu, P, Zhao, J, Guo, P, et al. (2017) Dietary corn bran fermented by Bacillus subtilis MA139 decreased gut cellulolytic bacteria and microbiota diversity in finishing pigs. Front Cell Infect Microbiol 7, 526.
15. Wu, GD, Chen, J, Hoffmann, C, et al. (2011) Linking long-term dietary patterns with gut microbial enterotypes. Science 334, 105108.
16. Peters, BA, Dominianni, C, Shapiro, JA, et al. (2016) The gut microbiota in conventional and serrated precursors of colorectal cancer. Microbiome 4, 69.
17. Schiffman, MH, Van Tassell, RL, Robinson, A, et al. (1989) Case–control study of colorectal cancer and fecapentaene excretion. Cancer Res 49, 13221326.
18. Schiffman, MH, Andrews, AW, Van Tassell, RL, et al. (1989) Case–control study of colorectal cancer and fecal mutagenicity. Cancer Res 49, 34203424.
19. World Health Organization (2006) BMI Classification. Global Database on Body Mass Index. Geneva: WHO.
20. Willett, WC, Howe, GR & Kushi, LH (1997) Adjustment for total energy intake in epidemiologic studies. Am J Clin Nutr 65, Suppl. 4, 1220S1228S (discussion 9S–31S).
21. Nossa, CW, Oberdorf, WE, Yang, L, et al. (2010) Design of 16S rRNA gene primers for 454 pyrosequencing of the human foregut microbiome. World J Gastroenterol 16, 41354144.
22. Caporaso, JG, Lauber, CL, Walters, WA, et al. (2011) Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci U S A 108, Suppl. 1, 45164522.
23. Caporaso, JG, Kuczynski, J, Stombaugh, J, et al. (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7, 335336.
24. Haas, BJ, Gevers, D, Earl, AM, et al. (2011) Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome Res 21, 494504.
25. Love, MI, Huber, W & Anders, S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15, 550.
26. Shannon, CE (1997) The mathematical theory of communication. 1963. MD Comput 14, 306317.
27. Lozupone, CA, Hamady, M, Kelley, ST, et al. (2007) Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities. Appl Environ Microbiol 73, 15761585.
28. McArdle, BH & Anderson, MJ (2001) Fitting multivariate models to community data: a comment on distance‐based redundancy analysis. Ecology 82, 290297.
29. Benjamini, Y & Hochberg, Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B Methodol 57, 289300.
30. Benjamini, Y, Drai, D, Elmer, G, et al. (2001) Controlling the false discovery rate in behavior genetics research. Behav Brain Res 125, 279284.
31. Evangelou, E & Ioannidis, JP (2013) Meta-analysis methods for genome-wide association studies and beyond. Nat Rev Genet 14, 379389.
32. Sonnenburg, ED, Smits, SA, Tikhonov, M, et al. (2016) Diet-induced extinctions in the gut microbiota compound over generations. Nature 529, 212215.
33. Liu, H, Wang, J, He, T, et al. (2018) Butyrate: a double-edged sword for health? Adv Nutr 9, 2129.
34. Pryde, SE, Duncan, SH, Hold, GL, et al. (2002) The microbiology of butyrate formation in the human colon. FEMS Microbiol Lett 217, 133139.
35. Donohoe, DR, Garge, N, Zhang, X, et al. (2011) The microbiome and butyrate regulate energy metabolism and autophagy in the mammalian colon. Cell Metab 13, 517526.
36. Chen, J, Li, Y, Tian, Y, et al. (2015) Interaction between microbes and host intestinal health: modulation by dietary nutrients and gut-brain-endocrine-immune axis. Curr Protein Pept Sci 16, 592603.
37. Meijer, K, de Vos, P & Priebe, MG (2010) Butyrate and other short-chain fatty acids as modulators of immunity: what relevance for health? Curr Opin Clin Nutr Metab Care 13, 715721.
38. Aguilar, EC, Leonel, AJ, Teixeira, LG, et al. (2014) Butyrate impairs atherogenesis by reducing plaque inflammation and vulnerability and decreasing NFkappaB activation. Nutr Metab Cardiovasc Dis 24, 606613.
39. Donohoe, DR, Collins, LB, Wali, A, et al. (2012) The Warburg effect dictates the mechanism of butyrate-mediated histone acetylation and cell proliferation. Mol Cell 48, 612626.
40. Gutierrez-Diaz, I, Fernandez-Navarro, T, Salazar, N, et al. (2017) Adherence to a Mediterranean diet influences the fecal metabolic profile of microbial-derived phenolics in a Spanish cohort of middle-age and older people. J Agric Food Chem 65, 586595.
41. Arumugam, M, Raes, J, Pelletier, E, et al. (2011) Enterotypes of the human gut microbiome. Nature 473, 174180.
42. Louis, P & Flint, HJ (2009) Diversity, metabolism and microbial ecology of butyrate-producing bacteria from the human large intestine. FEMS Microbiol Lett 294, 18.
43. Sokol, H, Pigneur, B, Watterlot, L, et al. (2008) Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients. Proc Natl Acad Sci U S A 105, 1673116736.
44. Lopez-Siles, M, Martinez-Medina, M, Suris-Valls, R, et al. (2016) Changes in the abundance of Faecalibacterium prausnitzii phylogroups I and II in the intestinal mucosa of inflammatory bowel disease and patients with colorectal cancer. Inflamm Bowel Dis 22, 2841.
45. Zackular, JP, Baxter, NT, Iverson, KD, et al. (2013) The gut microbiome modulates colon tumorigenesis. mBio 4, e00692e00713.
46. Thomas, AM, Jesus, EC, Lopes, A, et al. (2016) Tissue-associated bacterial alterations in rectal carcinoma patients revealed by 16S rRNA community profiling. Front Cell Infect Microbiol 6, 179.
47. Kasai, C, Sugimoto, K, Moritani, I, et al. (2016) Comparison of human gut microbiota in control subjects and patients with colorectal carcinoma in adenoma: terminal restriction fragment length polymorphism and next-generation sequencing analyses. Oncol Rep 35, 325333.
48. Dominianni, C, Sinha, R, Goedert, JJ, et al. (2015) Sex, body mass index, and dietary fiber intake influence the human gut microbiome. PLOS ONE 10, e0124599.
49. Liu, L, Li, Y, Li, S, et al. (2012) Comparison of next-generation sequencing systems. J Biomed Biotechnol 2012, 251364.
50. Allali, I, Arnold, JW, Roach, J, et al. (2017) A comparison of sequencing platforms and bioinformatics pipelines for compositional analysis of the gut microbiome. BMC Microbiol 17, 194.
51. Fungwe, TV, Bente, L & Hiza, H (2007) The Food Supply and Dietary Fiber: Its Availability and Effect on Health: Nutrition Insight 36. Alexandria, VA: USDA Center for Nutrition Policy and Promotion.


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