Journal of Gastroenterology

, Volume 54, Issue 2, pp 149–159 | Cite as

Characterization of fungal dysbiosis in Japanese patients with inflammatory bowel disease

  • Takayuki Imai
  • Ryo Inoue
  • Yuki Kawada
  • Yasuhiro Morita
  • Osamu Inatomi
  • Atsushi Nishida
  • Shigeki Bamba
  • Masahiro Kawahara
  • Akira AndohEmail author
Original Article—Alimentary Tract


Background and aims

There are no previous reports describing the fecal fungal microbiome of a Japanese population using advanced molecular techniques. In this study, we performed a molecular analysis on the fungal microbial community of a healthy Japanese population and patients with inflammatory bowel diseases (IBDs).

Patients and methods

Fecal samples were obtained from 18 patients with inactive ulcerative colitis (UC, n = 18), Crohn’s disease (CD, n = 20) and healthy volunteers (n = 20). Bacterial and fungal microbiome was analyzed by sequencing of 16S rRNA and the internal transcribed spacer (ITS) region, respectively.


16S rRNA sequencing of the bacterial microbiome revealed that the α-diversity indicated by the Chao-1 and Shannon indices was significantly lower in CD patients compared to healthy controls and/or UC patients. Principal coordinate (PCo) analysis of the bacterial community revealed significant structural differences in microbiome among healthy controls, UC and CD patients (PERMANOVA P = 0.0001). ITS sequencing of the fungal microbiome indicated no significant differences in α-diversity between healthy controls and IBD patients. However, the overall structure of the fungal microbial community of CD patients was significantly different from those of healthy controls and UC patients (PERMANOVA = 0.03). At the genus level, the genus Saccharomyces was dominant and this was followed by the genus Sarocladium in healthy controls. The abundance of the genus Candida was significantly higher in CD patients than healthy controls and/or UC patients.


The fecal fungal microbiome of a Japanese population differed considerably from that of a Western population. We identified fungal dysbiosis in Japanese patients with IBD.


Fungi Candida IBD 



This study was supported in part by a Grant-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology of Japan (18K08002), a grant for the Intractable Diseases from the Ministry of Health, Labor and Welfare of Japan, and a grant from the Smoking Research Foundation.

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflict of interest in this study.

Supplementary material

535_2018_1530_MOESM1_ESM.pptx (1.3 mb)
Supplementary material 1 (PPTX 1308 kb)


  1. 1.
    Kaplan GG, Ng SC. Understanding and preventing the global increase of inflammatory bowel disease. Gastroenterology. 2017;152(2):313–21 (e2).CrossRefGoogle Scholar
  2. 2.
    Chan HC, Ng SC. Emerging biologics in inflammatory bowel disease. J Gastroenterol. 2017;52(2):141–50.CrossRefGoogle Scholar
  3. 3.
    Sartor RB, Wu GD. Roles for intestinal bacteria, viruses, and fungi in pathogenesis of inflammatory bowel diseases and therapeutic approaches. Gastroenterology. 2017;152(2):327–39 (e4).CrossRefGoogle Scholar
  4. 4.
    Nishino K, Nishida A, Inoue R, Kawada Y, Ohno M, Sakai S, et al. Analysis of endoscopic brush samples identified mucosa-associated dysbiosis in inflammatory bowel disease. J Gastroenterol. 2018;53(1):95–106.CrossRefGoogle Scholar
  5. 5.
    Frank DN, Robertson CE, Hamm CM, Kpadeh Z, Zhang T, Chen H, et al. Disease phenotype and genotype are associated with shifts in intestinal-associated microbiota in inflammatory bowel diseases. Inflamm Bowel Dis. 2011;17(1):179–84.CrossRefGoogle Scholar
  6. 6.
    Nagalingam NA, Lynch SV. Role of the microbiota in inflammatory bowel diseases. Inflamm Bowel Dis. 2012;18(5):968–84.CrossRefGoogle Scholar
  7. 7.
    Sartor RB. The intestinal microbiota in inflammatory bowel diseases. Nestle Nutr Inst Workshop Ser. 2014;79:29–39.CrossRefGoogle Scholar
  8. 8.
    Li J, Chen D, Yu B, He J, Zheng P, Mao X, et al. Fungi in gastrointestinal tracts of human and mice: from community to functions. Microb Ecol. 2018;75(4):821–9.CrossRefGoogle Scholar
  9. 9.
    Cui L, Morris A, Ghedin E. The human mycobiome in health and disease. Genome Med. 2013;5(7):63.CrossRefGoogle Scholar
  10. 10.
    Iliev ID, Funari VA, Taylor KD, Nguyen Q, Reyes CN, Strom SP, et al. Interactions between commensal fungi and the C-type lectin receptor Dectin-1 influence colitis. Science. 2012;336(6086):1314–7.CrossRefGoogle Scholar
  11. 11.
    Sokol H, Conway KL, Zhang M, Choi M, Morin B, Cao Z, et al. Card9 mediates intestinal epithelial cell restitution, T-helper 17 responses, and control of bacterial infection in mice. Gastroenterology. 2013;145(3):591–601 (e3).CrossRefGoogle Scholar
  12. 12.
    Jawhara S, Thuru X, Standaert-Vitse A, Jouault T, Mordon S, Sendid B, et al. Colonization of mice by Candida albicans is promoted by chemically induced colitis and augments inflammatory responses through galectin-3. J Infect Dis. 2008;197(7):972–80.CrossRefGoogle Scholar
  13. 13.
    Jawhara S, Poulain D. Saccharomyces boulardii decreases inflammation and intestinal colonization by Candida albicans in a mouse model of chemically-induced colitis. Med Mycol. 2007;45(8):691–700.CrossRefGoogle Scholar
  14. 14.
    Sokol H, Leducq V, Aschard H, Pham HP, Jegou S, Landman C, et al. Fungal microbiota dysbiosis in IBD. Gut. 2017;66(6):1039–48.CrossRefGoogle Scholar
  15. 15.
    Liguori G, Lamas B, Richard ML, Brandi G, da Costa G, Hoffmann TW, et al. Fungal dysbiosis in mucosa-associated microbiota of Crohn’s disease patients. J Crohns Colitis. 2016;10(3):296–305.CrossRefGoogle Scholar
  16. 16.
    Nishijima S, Suda W, Oshima K, Kim SW, Hirose Y, Morita H, et al. The gut microbiome of healthy Japanese and its microbial and functional uniqueness. DNA Res. 2016;23(2):125–33.CrossRefGoogle Scholar
  17. 17.
    Rutgeerts P, Sandborn WJ, Feagan BG, Reinisch W, Olson A, Johanns J, et al. Infliximab for induction and maintenance therapy for ulcerative colitis. N Engl J Med. 2005;353(23):2462–76.CrossRefGoogle Scholar
  18. 18.
    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(3):439–44.Google Scholar
  19. 19.
    Matsumoto M, Inoue R, Tsuruta T, Hara H, Yajima T. Long-term oral administration of cows’ milk improves insulin sensitivity in rats fed a high-sucrose diet. Br J Nutr. 2009;102(9):1324–33.CrossRefGoogle Scholar
  20. 20.
    Inoue R, Sakaue Y, Sawai C, Sawai T, Ozeki M, Romero-Perez GA, et al. A preliminary investigation on the relationship between gut microbiota and gene expressions in peripheral mononuclear cells of infants with autism spectrum disorders. Biosci Biotechnol Biochem. 2016;80(12):2450–8.CrossRefGoogle Scholar
  21. 21.
    Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7(5):335–6.CrossRefGoogle Scholar
  22. 22.
    Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics. 2010;26(19):2460–1.CrossRefGoogle Scholar
  23. 23.
    Rognes T, Flouri T, Nichols B, Quince C, Mahe F. VSEARCH: a versatile open source tool for metagenomics. PeerJ. 2016;4:e2584.CrossRefGoogle Scholar
  24. 24.
    DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol. 2006;72(7):5069–72.CrossRefGoogle Scholar
  25. 25.
    Gardes M, Bruns TD. ITS primers with enhanced specificity for basidiomycetes—application to the identification of mycorrhizae and rusts. Mol Ecol. 1993;2(2):113–8.CrossRefGoogle Scholar
  26. 26.
    Abarenkov K, Henrik Nilsson R, Larsson KH, Alexander IJ, Eberhardt U, Erland S, et al. The UNITE database for molecular identification of fungi—recent updates and future perspectives. New Phytol. 2010;186(2):281–5.CrossRefGoogle Scholar
  27. 27.
    McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One. 2013;8(4):e61217.CrossRefGoogle Scholar
  28. 28.
    Parks DH, Tyson GW, Hugenholtz P, Beiko RG. STAMP: statistical analysis of taxonomic and functional profiles. Bioinformatics. 2014;30(21):3123–4.CrossRefGoogle Scholar
  29. 29.
    Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, et al. Metagenomic biomarker discovery and explanation. Genome Biol. 2011;12(6):R60.CrossRefGoogle Scholar
  30. 30.
    Zuo T, Ng SC. The gut microbiota in the pathogenesis and therapeutics of inflammatory bowel disease. Front Microbiol. 2018;9:2247.CrossRefGoogle Scholar
  31. 31.
    Willing BP, Dicksved J, Halfvarson J, Andersson AF, Lucio M, Zheng Z, et al. A pyrosequencing study in twins shows that gastrointestinal microbial profiles vary with inflammatory bowel disease phenotypes. Gastroenterology. 2010;139(6):1844–54 (e1).CrossRefGoogle Scholar
  32. 32.
    Levitz SM. Innate recognition of fungal cell walls. PLoS Pathog. 2010;6(4):e1000758.CrossRefGoogle Scholar

Copyright information

© Japanese Society of Gastroenterology 2018

Authors and Affiliations

  • Takayuki Imai
    • 1
  • Ryo Inoue
    • 2
  • Yuki Kawada
    • 2
  • Yasuhiro Morita
    • 1
  • Osamu Inatomi
    • 1
  • Atsushi Nishida
    • 1
  • Shigeki Bamba
    • 1
  • Masahiro Kawahara
    • 1
  • Akira Andoh
    • 1
    Email author
  1. 1.Department of MedicineShiga University of Medical ScienceOtsuJapan
  2. 2.Laboratory of Animal Science, Department of Agriculture and Life ScienceKyoto Prefectural UniversityKyotoJapan

Personalised recommendations