The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.
The gut mycobiome of the Human Microbiome Project healthy cohort
Open accessAbstract
BACKGROUND: Most studies describing the human gut microbiome in healthy and diseased states have emphasized the bacterial component, but the fungal microbiome (i.e., the mycobiome) is beginning to gain recognition as a fundamental part of our microbiome. To date, human gut mycobiome studies have primarily been disease centric or in small cohorts of healthy individuals. To contribute to existing knowledge of the human mycobiome, we investigated the gut mycobiome of the Human Microbiome Project (HMP) cohort by sequencing the Internal Transcribed Spacer 2 (ITS2) region as well as the 18S rRNA gene. RESULTS: Three hundred seventeen HMP stool samples were analyzed by ITS2 sequencing. Fecal fungal diversity was significantly lower in comparison to bacterial diversity. Yeast dominated the samples, comprising eight of the top 15 most abundant genera. Specifically, fungal communities were characterized by a high prevalence of Saccharomyces, Malassezia, and Candida, with S. cerevisiae, M. restricta, and C. albicans operational taxonomic units (OTUs) present in 96.8, 88.3, and 80.8% of samples, respectively. There was a high degree of inter- and intra-volunteer variability in fungal communities. However, S. cerevisiae, M. restricta, and C. albicans OTUs were found in 92.2, 78.3, and 63.6% of volunteers, respectively, in all samples donated over an approximately 1-year period. Metagenomic and 18S rRNA gene sequencing data agreed with ITS2 results; however, ITS2 sequencing provided greater resolution of the relatively low abundance mycobiome constituents. CONCLUSIONS: Compared to bacterial communities, the human gut mycobiome is low in diversity and dominated by yeast including Saccharomyces, Malassezia, and Candida. Both inter- and intra-volunteer variability in the HMP cohort were high, revealing that unlike bacterial communities, an individual's mycobiome is no more similar to itself over time than to another person's. Nonetheless, several fungal species persisted across a majority of samples, evidence that a core gut mycobiome may exist. ITS2 sequencing data provided greater resolution of the mycobiome membership compared to metagenomic and 18S rRNA gene sequencing data, suggesting that it is a more sensitive method for studying the mycobiome of stool samples.
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2 retracted
Gouba, N., Raoult, D., & Drancourt, M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0059474 · Cited by 96
RetractedRETRACTED: Eukaryote Culturomics of the Gut Reveals New Species
Gouba, N., Raoult, D., & Drancourt, M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0106994 · Cited by 90
RetractedR: A Language and Environment for Statistical Computing
R Core Team (2025) · doi:10.32614/r.manuals · Cited by 352,181
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Basic local alignment search tool
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics
White, T. J., Bruns, T., Lee, S., & Taylor, J. (1990) · PCR Protocols · doi:10.1016/b978-0-12-372180-8.50042-1 · Cited by 36,648
The SILVA ribosomal RNA gene database project: improved data processing and web-based tools
Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Peplies, J., & Glöckner, F. O. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1219 · Cited by 33,055
vegan: Community Ecology Package
Oksanen, J., Simpson, G. L., Blanchet, F. G., Kindt, R., Legendre, P., Minchin, P. R., O'Hara, R. B., Solymos, P., Stevens, M. H. H., Szoecs, E., et al. (2001) · CRAN: Contributed Packages · doi:10.32614/cran.package.vegan · Cited by 22,615
BLAST+: architecture and applications
Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., & Madden, T. L. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-421 · Cited by 22,074
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Pan-cancer analyses reveal cancer-type-specific fungal ecologies and bacteriome interactions
Narunsky-Haziza, L., Sepich-Poore, G. D., Livyatan, I., Asraf, O., Martino, C., Nejman, D., Gavert, N., Stajich, J. E., Amit, G., González, A., et al. (2022) · Cell · doi:10.1016/j.cell.2022.09.005 · Cited by 538
“Different cancer types exhibit cancer-type-specific mycobiomes Tumor bacterial richness was significantly higher than fungal richness (Figure 3A), similar to the gut microbiome (Nash et al., 2017).”
BackgroundHuman Anti-fungal Th17 Immunity and Pathology Rely on Cross-Reactivity against Candida albicans
Bacher, P., Hohnstein, T., Beerbaum, E., Röcker, M., Blango, M. G., Kaufmann, S., Röhmel, J., Eschenhagen, P., Grehn, C., Seidel, K., et al. (2019) · Cell · doi:10.1016/j.cell.2019.01.041 · Cited by 473
Gut microbiome, liver immunology, and liver diseases
Wang, R., Tang, R., Li, B., Ma, X., Schnabl, B., & Tilg, H. (2021) · Cellular & Molecular Immunology · doi:10.1038/s41423-020-00592-6 · Cited by 466
Metadata
- Authors
- Nash, A. K., Auchtung, T. A., Wong, M. C., Smith, D. P., Gesell, J. R., Ross, M. C., Stewart, C. J., Metcalf, G. A., Muzny, D. M., Gibbs, R. A., Ajami, N. J., & Petrosino, J. F.
- Venue
- Microbiome
- Published
- 2017-11-25
- Volume
- 5
- Issue
- 1
- Pages
- 153-153
- ISSN
- 2049-2618 (ISSN-L)
- OpenAlex
- W2769232178
- Cited by
- 980
- References
- 75
- FWCI
- 21.06
- Type
- journal article
- Language
- en
- Open access
- gold
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- Nash, A. K., Auchtung, T. A., Wong, M. C., Smith, D. P., Gesell, J. R., Ross, M. C., Stewart, C. J., Metcalf, G. A., Muzny, D. M., Gibbs, R. A., Ajami, N. J., & Petrosino, J. F. (2017). The gut mycobiome of the Human Microbiome Project healthy cohort. Microbiome. https://doi.org/10.1186/s40168-017-0373-4
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