Journal of Gastroenterology

, Volume 47, Issue 12, pp 1298–1307 | Cite as

Multicenter analysis of fecal microbiota profiles in Japanese patients with Crohn’s disease

  • Akira Andoh
  • Hiroyuki Kuzuoka
  • Tomoyuki Tsujikawa
  • Shiro Nakamura
  • Fumihito Hirai
  • Yasuo Suzuki
  • Toshiyuki Matsui
  • Yoshihide Fujiyama
  • Takayuki Matsumoto
Original Article—Alimentary Tract

Abstract

Background

We analyzed the fecal microbiota profiles of patients with Crohn’s disease (CD) at 4 inflammatory bowel disease (IBD) centers located in different districts in Japan.

Methods

Terminal restriction fragment length polymorphism (T-RFLP) analysis was performed in 161 fecal samples from CD patients and 121 samples from healthy individuals. The bacterial diversity was evaluated by the Shannon diversity index (SDI).

Results

There were no regional differences in the fecal microbiota profiles of the healthy individuals in Japan. A setting of similarity generated three major clusters of T-RFs: one included almost all the healthy individuals (118/121), and the other two clusters were mainly formed by CD patients at different stages of disease activity. The changes in simulated bacterial composition indicated that the class Clostridia, including the genus Faecalibacterium, was significantly decreased in CD patients with active disease and those in remission as compared with findings in the healthy individuals. In contrast, the genus Bacteroides was significantly increased in CD patients during the active phase as compared with findings in the healthy individuals. The genus Bifidobacterium was significantly decreased during the active phase of CD and increased to healthy levels during the remission phase. The bacterial diversity measured by the SDI was significantly reduced in CD patients during the active and remission phases as compared with findings in the healthy individuals. From the clinical data and T-RFLP analysis, we developed a logistic model to predict disease activity based on the fecal microbiota composition.

Conclusion

Dysbiosis in CD patients was shown by a multi-IBD center study. The feasibility of using the fecal microbiota profile as a predictive marker for disease activity is proposed.

Keywords

Inflammatory bowel disease Faecalibacterium Firmicutes Shannon diversity index T-RFLP 

Supplementary material

535_2012_605_MOESM1_ESM.pptx (238 kb)
Supplementary material 1 (PPTX 237 kb)

References

  1. 1.
    Sands BE. Inflammatory bowel disease: past, present, and future. J Gastroenterol. 2007;42:16–25.PubMedCrossRefGoogle Scholar
  2. 2.
    Mayer L. Evolving paradigms in the pathogenesis of IBD. J Gastroenterol. 2010;45:9–16.PubMedCrossRefGoogle Scholar
  3. 3.
    Hibi T, Ogata H. Novel pathophysiological concepts of inflammatory bowel disease. J Gastroenterol. 2006;41:10–6.PubMedCrossRefGoogle Scholar
  4. 4.
    Podolsky DK. Inflammatory bowel disease. N Engl J Med. 2002;347:417–29.PubMedCrossRefGoogle Scholar
  5. 5.
    Hamilton MJ, Snapper SB, Blumberg RS. Update on biologic pathways in inflammatory bowel disease and their therapeutic relevance. J Gastroenterol. 2012;47:1–8.PubMedCrossRefGoogle Scholar
  6. 6.
    Sartor RB. Microbial influences in inflammatory bowel diseases. Gastroenterology. 2008;134:577–94.PubMedCrossRefGoogle Scholar
  7. 7.
    Mizoguchi A, Mizoguchi E. Inflammatory bowel disease, past, present and future: lessons from animal models. J Gastroenterol. 2008;43:1–17.PubMedCrossRefGoogle Scholar
  8. 8.
    Sartor RB. Mechanisms of disease: pathogenesis of Crohn’s disease and ulcerative colitis. Nat Clin Pract Gastroenterol Hepatol. 2006;3:390–407.PubMedCrossRefGoogle Scholar
  9. 9.
    Wirtz S, Neurath MF. Mouse models of inflammatory bowel disease. Adv Drug Deliv Rev. 2007;59:1073–83.PubMedCrossRefGoogle Scholar
  10. 10.
    Braun J, Wei B. Body traffic: ecology, genetics, and immunity in inflammatory bowel disease. Annu Rev Pathol. 2007;2:401–29.PubMedCrossRefGoogle Scholar
  11. 11.
    Seksik P, Sokol H, Lepage P, Vasquez N, Manichanh C, Mangin I, et al. Review article: the role of bacteria in onset and perpetuation of inflammatory bowel disease. Aliment Pharmacol Ther. 2006;24(Suppl 3):11–8.PubMedCrossRefGoogle Scholar
  12. 12.
    Elson CO, Cong Y, McCracken VJ, Dimmitt RA, Lorenz RG, Weaver CT. Experimental models of inflammatory bowel disease reveal innate, adaptive, and regulatory mechanisms of host dialogue with the microbiota. Immunol Rev. 2005;206:260–76.PubMedCrossRefGoogle Scholar
  13. 13.
    Ogura Y, Bonen DK, Inohara N, Nicolae DL, Chen FF, Ramos R, et al. A frameshift mutation in NOD2 associated with susceptibility to Crohn’s disease. Nature. 2001;411:603–6.PubMedCrossRefGoogle Scholar
  14. 14.
    Cadwell K, Liu JY, Brown SL, Miyoshi H, Loh J, Lennerz JK, et al. A key role for autophagy and the autophagy gene Atg16l1 in mouse and human intestinal Paneth cells. Nature. 2008;456:259–63.PubMedCrossRefGoogle Scholar
  15. 15.
    Kabi A, Nickerson KP, Homer CR, McDonald C. Digesting the genetics of inflammatory bowel disease: Insights from studies of autophagy risk genes. Inflamm Bowel Dis. 2012;18:782–92.PubMedCrossRefGoogle Scholar
  16. 16.
    Frank DN, St Amand AL, Feldman RA, Boedeker EC, Harpaz N, Pace NR. Molecular-phylogenetic characterization of microbial community imbalances in human inflammatory bowel diseases. Proc Natl Acad Sci USA. 2007;104:13780–5.PubMedCrossRefGoogle Scholar
  17. 17.
    Matsuda H, Fujiyama Y, Andoh A, Ushijima T, Kajinami T, Bamba T. Characterization of antibody responses against rectal mucosa-associated bacterial flora in patients with ulcerative colitis. J Gastroenterol Hepatol. 2000;15:61–8.PubMedCrossRefGoogle Scholar
  18. 18.
    Lucke K, Miehlke S, Jacobs E, Schuppler M. Prevalence of Bacteroides and Prevotella spp. in ulcerative colitis. J Med Microbiol. 2006;55:617–24.PubMedCrossRefGoogle Scholar
  19. 19.
    Swidsinski A, Ladhoff A, Pernthaler A, Swidsinski S, Loening-Baucke V, Ortner M, et al. Mucosal flora in inflammatory bowel disease. Gastroenterology. 2002;122:44–54.PubMedCrossRefGoogle Scholar
  20. 20.
    Hayashi H, Sakamoto M, Benno Y. Phylogenetic analysis of the human gut microbiota using 16S rDNA clone libraries and strictly anaerobic culture-based methods. Microbiol Immunol. 2002;46:535–48.PubMedGoogle Scholar
  21. 21.
    Langendijk PS, Schut F, Jansen GJ, Raangs GC, Kamphuis GR, Wilkinson MH, et al. Quantitative fluorescence in situ hybridization of Bifidobacterium spp. with genus-specific 16S rRNA-targeted probes and its application in fecal samples. Appl Environ Microbiol. 1995;61:3069–75.PubMedGoogle Scholar
  22. 22.
    Andoh A, Benno Y, Kanauchi O, Fujiyama Y. Recent advances in molecular approaches to gut microbiota in inflammatory bowel disease. Curr Pharm Des. 2009;15:2066–73.PubMedCrossRefGoogle Scholar
  23. 23.
    Nagalingam NA, Lynch SV. Role of the microbiota in inflammatory bowel diseases. Inflamm Bowel Dis. 2012;18:968–84.PubMedCrossRefGoogle Scholar
  24. 24.
    Andoh A, Imaeda H, Aomatsu T, Inatomi O, Bamba S, Sasaki M, et al. Comparison of the fecal microbiota profiles between ulcerative colitis and Crohn’s disease using terminal restriction fragment length polymorphism analysis. J Gastroenterol. 2011;46:479–86.PubMedCrossRefGoogle Scholar
  25. 25.
    Andoh A, Tsujikawa T, Sasaki M, Mitsuyama K, Suzuki Y, Matsui T, et al. Fecal microbiota profile of Crohn’s disease determined by terminal restriction fragment length polymorphism (t-rflp) analysis. Aliment Pharmacol Ther. 2009;29:75–82.PubMedCrossRefGoogle Scholar
  26. 26.
    De Filippo C, Cavalieri D, Di Paola M, Ramazzotti M, Poullet JB, Massart S, 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. 2010;107:14691–6.PubMedCrossRefGoogle Scholar
  27. 27.
    Best WR, Becktel JM, Singleton JW, Kern F Jr. Development of a Crohn’s disease activity index National Cooperative Crohn’s Disease Study. Gastroenterology. 1976;70:439–44.PubMedGoogle Scholar
  28. 28.
    Matsumoto M, Sakamoto M, Hayashi H, Benno Y. Novel phylogenetic assignment database for terminal-restriction fragment length polymorphism analysis of human colonic microbiota. J Microbiol Methods. 2005;61:305–19.PubMedCrossRefGoogle Scholar
  29. 29.
    Sakamoto M, Takeuchi Y, Umeda M, Ishikawa I, Benno Y. Application of terminal RFLP analysis to characterize oral bacterial flora in saliva of healthy subjects and patients with periodontitis. J Med Microbiol. 2003;52:79–89.PubMedCrossRefGoogle Scholar
  30. 30.
    Marsh TL, Saxman P, Cole J, Tiedje J. Terminal restriction fragment length polymorphism analysis program, a web-based research tool for microbial community analysis. Appl Environ Microbiol. 2000;66:3616–20.PubMedCrossRefGoogle Scholar
  31. 31.
    Hill TC, Walsh KA, Harris JA, Moffett BF. Using ecological diversity measures with bacterial communities. FEMS Microbiol Ecol. 2003;43:1–11.PubMedCrossRefGoogle Scholar
  32. 32.
    Chiang JK, Cheng YH, Koo M, Kao YH, Chen CY. A computer-assisted model for predicting probability of dying within 7 days of hospice admission in patients with terminal cancer. Jpn J Clin Oncol. 2010;40:449–55.PubMedCrossRefGoogle Scholar
  33. 33.
    Andoh A, Sakata S, Koizumi Y, Mitsuyama K, Fujiyama Y, Benno Y. Terminal restriction fragment length polymorphism analysis of the diversity of fecal microbiota in patients with ulcerative colitis. Inflamm Bowel Dis. 2007;13:955–62.PubMedCrossRefGoogle Scholar
  34. 34.
    Nishikawa J, Kudo T, Sakata S, Benno Y, Sugiyama T. Diversity of mucosa-associated microbiota in active and inactive ulcerative colitis. Scand J Gastroenterol. 2009;44:180–6.PubMedCrossRefGoogle Scholar
  35. 35.
    Nomura T, Ohkusa T, Okayasu I, Yoshida T, Sakamoto M, Hayashi H, et al. Mucosa-associated bacteria in ulcerative colitis before and after antibiotic combination therapy. Aliment Pharmacol Ther. 2005;21:1017–27.PubMedCrossRefGoogle Scholar
  36. 36.
    Walker AW, Sanderson JD, Churcher C, Parkes GC, Hudspith BN, Rayment N, et al. High-throughput clone library analysis of the mucosa-associated microbiota reveals dysbiosis and differences between inflamed and non-inflamed regions of the intestine in inflammatory bowel disease. BMC Microbiol. 2011;11:7.PubMedCrossRefGoogle Scholar
  37. 37.
    Schutte UM, Abdo Z, Bent SJ, Shyu C, Williams CJ, Pierson JD, et al. Advances in the use of terminal restriction fragment length polymorphism (T-RFLP) analysis of 16S rRNA genes to characterize microbial communities. Appl Microbiol Biotechnol. 2008;80:365–80.PubMedCrossRefGoogle Scholar
  38. 38.
    Kurokawa K, Itoh T, Kuwahara T, Oshima K, Toh H, Toyoda A, et al. Comparative metagenomics revealed commonly enriched gene sets in human gut microbiomes. DNA Res. 2007;14:169–81.PubMedCrossRefGoogle Scholar
  39. 39.
    Feller M, Huwiler K, Stephan R, Altpeter E, Shang A, Furrer H, et al. Mycobacterium avium subspecies paratuberculosis and Crohn’s disease: a systematic review and meta-analysis. Lancet Infect Dis. 2007;7:607–13.PubMedCrossRefGoogle Scholar
  40. 40.
    Barnich N, Darfeuille-Michaud A. Adherent-invasive Escherichia coli and Crohn’s disease. Curr Opin Gastroenterol. 2007;23:16–20.PubMedCrossRefGoogle Scholar
  41. 41.
    Atarashi K, Tanoue T, Shima T, Imaoka A, Kuwahara T, Momose Y, et al. Induction of colonic regulatory T cells by indigenous Clostridium species. Science. 2011;331:337–41.PubMedCrossRefGoogle Scholar
  42. 42.
    Hall JA, Bouladoux N, Sun CM, Wohlfert EA, Blank RB, Zhu Q, et al. Commensal DNA limits regulatory T cell conversion and is a natural adjuvant of intestinal immune responses. Immunity. 2008;29:637–49.PubMedCrossRefGoogle Scholar
  43. 43.
    Sokol H, Pigneur B, Watterlot L, Lakhdari O, Bermudez-Humaran LG, Gratadoux JJ, et al. Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients. Proc Natl Acad Sci USA. 2008;105:16731–6.PubMedCrossRefGoogle Scholar
  44. 44.
    Sokol H, Seksik P, Furet JP, Firmesse O, Nion-Larmurier I, Beaugerie L, et al. Low counts of Faecalibacterium prausnitzii in colitis microbiota. Inflamm Bowel Dis. 2009;15:1183–9.PubMedCrossRefGoogle Scholar
  45. 45.
    Duncan SH, Hold GL, Harmsen HJ, Stewart CS, Flint HJ. Growth requirements and fermentation products of Fusobacterium prausnitzii, and a proposal to reclassify it as Faecalibacterium prausnitzii gen. nov., comb. nov. Int J Syst Evol Microbiol. 2002;52:2141–6.PubMedCrossRefGoogle Scholar
  46. 46.
    Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature. 2006;444:1022–3.PubMedCrossRefGoogle Scholar
  47. 47.
    Aomatsu T, Imaeda H, Matsumoto K, Kimura E, Yoden A, Tamai H, et al. Faecal chitinase 3-like-1: a novel biomarker of disease activity in paediatric inflammatory bowel disease. Aliment Pharmacol Ther. 2011;34:941–8.PubMedCrossRefGoogle Scholar
  48. 48.
    Aomatsu T, Yoden A, Matsumoto K, Kimura E, Inoue K, Andoh A, et al. Fecal calprotectin is a useful marker for disease activity in pediatric patients with inflammatory bowel disease. Dig Dis Sci. 2011;56:2372–7.PubMedCrossRefGoogle Scholar

Copyright information

© Springer 2012

Authors and Affiliations

  • Akira Andoh
    • 1
  • Hiroyuki Kuzuoka
    • 2
    • 3
  • Tomoyuki Tsujikawa
    • 6
  • Shiro Nakamura
    • 2
  • Fumihito Hirai
    • 4
  • Yasuo Suzuki
    • 5
  • Toshiyuki Matsui
    • 4
  • Yoshihide Fujiyama
    • 6
  • Takayuki Matsumoto
    • 2
  1. 1.Division of Mucosal ImmunologyGraduate School, Shiga University of Medical ScienceOtsuJapan
  2. 2.Department of Lower GastroenterologyHyogo College of MedicineNishinomiyaJapan
  3. 3.Research and Development LaboratoriesEN Otsuka Pharmaceutical Co., Ltd.HanamakiJapan
  4. 4.Department of GastroenterologyFukuoka University Chikushi HospitalChikushinoJapan
  5. 5.Department of Internal MedicineToho University Sakura Medical CenterSakuraJapan
  6. 6.Department of MedicineShiga University of Medical ScienceOtsuJapan

Personalised recommendations