Abstract
Traditional culture-based methods have incompletely defined the microbial landscape of common recalcitrant human fungal skin diseases, including athlete’s foot and toenail infections. Skin protects humans from invasion by pathogenic microorganisms and provides a home for diverse commensal microbiota1. Bacterial genomic sequence data have generated novel hypotheses about species and community structures underlying human disorders2,3,4. However, microbial diversity is not limited to bacteria; microorganisms such as fungi also have major roles in microbial community stability, human health and disease5. Genomic methodologies to identify fungal species and communities have been limited compared with those that are available for bacteria6. Fungal evolution can be reconstructed with phylogenetic markers, including ribosomal RNA gene regions and other highly conserved genes7. Here we sequenced and analysed fungal communities of 14 skin sites in 10 healthy adults. Eleven core-body and arm sites were dominated by fungi of the genus Malassezia, with only species-level classifications revealing fungal-community composition differences between sites. By contrast, three foot sites—plantar heel, toenail and toe web—showed high fungal diversity. Concurrent analysis of bacterial and fungal communities demonstrated that physiologic attributes and topography of skin differentially shape these two microbial communities. These results provide a framework for future investigation of the contribution of interactions between pathogenic and commensal fungal and bacterial communities to the maintainenace of human health and to disease pathogenesis.
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Accession codes
Accessions
GenBank/EMBL/DDBJ
Sequence Read Archive
Data deposits
Sequence data from this study have been submitted to GenBank/EMBL/DDBJ under accession numbers KC669797–KC675175, and the Sequence Read Archive,and can be accessed through BioProject identification no.46333. Patient and sample metadata have been deposited in the controlled-access Database of Genotypes and Phenotypes (dbGaP) under study accession phs000266.v1.p1.
References
Marples, M., ed. The Ecology of the Human Skin (Bannerstone House, 1965)
Grice, E. A. & Segre, J. A. The human microbiome: our second genome. Annu. Rev. Genomics Hum. Genet. 13, 151–170 (2012)
Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012)
Pflughoeft, K. J. & Versalovic, J. Human microbiome in health and disease. Annu. Rev. Pathol. 7, 99–122 (2012)
Peleg, A. Y., Hogan, D. A. & Mylonakis, E. Medically important bacterial–fungal interactions. Nature Rev. Microbiol. 8, 340–349 (2010)
Dollive, S. et al. A tool kit for quantifying eukaryotic rRNA gene sequences from human microbiome samples. Genome Biol. 13, R60 (2012)
James, T. Y. et al. Reconstructing the early evolution of Fungi using a six-gene phylogeny. Nature 443, 818–822 (2006)
Ghannoum, M. A. et al. Characterization of the oral fungal microbiome (mycobiome) in healthy individuals. PLoS Pathog. 6, e1000713 (2010)
Paulino, L. C., Tseng, C. H., Strober, B. E. & Blaser, M. J. Molecular analysis of fungal microbiota in samples from healthy human skin and psoriatic lesions. J. Clin. Microbiol. 44, 2933–2941 (2006)
Roth, R. R. & James, W. D. Microbial ecology of the skin. Annu. Rev. Microbiol. 42, 441–464 (1988)
Bickers, D. R. et al. The burden of skin diseases: 2004 a joint project of the American Academy of Dermatology Association and the Society for Investigative Dermatology. J. Am. Acad. Dermatol. 55, 490–500 (2006)
Gaitanis, G., Magiatis, P., Hantschke, M., Bassukas, I. D. & Velegraki, A. The Malassezia genus in skin and systemic diseases. Clin. Microbiol. Rev. 25, 106–141 (2012)
Saunders, C. W., Scheynius, A. & Heitman, J. Malassezia fungi are specialized to live on skin and associated with dandruff, eczema, and other skin diseases. PLoS Pathog. 8, e1002701 (2012)
Larone, D. H. Medically Important Fungi: A guide to identification (ASM Press, 2002)
St-Germain, G. & Summerbell, R. Identifying Fungi: A Clinical Laboratory Handbook (Star Publishing Company, 2011)
Gioti, A. et al. Genomic insights into the atopic eczema-associated skin commensal yeast Malassezia sympodialis. mBio 4, e00572–12 (2013)
Bruns, T. D. et al. Evolutionary relationships within the fungi: analyses of nuclear small subunit rRNA sequences. Mol. Phylogenet. Evol. 1, 231–241 (1992)
Schoch, C. L. et al. Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi. Proc. Natl Acad. Sci. USA 109, 6241–6246 (2012)
Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013)
Matsen, F. A., Kodner, R. B. & Armbrust, E. V. pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree. BMC Bioinformatics 11, 538 (2010)
Schloss, P. D. et al. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537–7541 (2009)
Costello, E. K. et al. Bacterial community variation in human body habitats across space and time. Science 326, 1694–1697 (2009)
Grice, E. A. et al. Topographical and temporal diversity of the human skin microbiome. Science 324, 1190–1192 (2009)
Cohen, A. D., Wolak, A., Alkan, M., Shalev, R. & Vardy, D. A. Prevalence and risk factors for tinea pedis in Israeli soldiers. Int. J. Dermatol. 44, 1002–1005 (2005)
Perea, S. et al. Prevalence and risk factors of tinea unguium and tinea pedis in the general population in Spain. J. Clin. Microbiol. 38, 3226–3230 (2000)
Iliev, I. D. et al. Interactions between commensal fungi and the C-type lectin receptor Dectin-1 influence colitis. Science 336, 1314–1317 (2012)
Perfect, J. R., Lindsay, M. H. & Drew, R. H. Adverse drug reactions to systemic antifungals. Prevention and management. Drug Saf. 7, 323–363 (1992)
Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011)
Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267 (2007)
Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990)
Grice, E. A. et al. Topographical and temporal diversity of the human skin microbiome. Science 324, 1190–1192 (2009)
Grice, E. A. et al. A diversity profile of the human skin microbiota. Genome Res. 18, 1043–1050 (2008)
Lennon, N. J. et al. A scalable, fully automated process for construction of sequence-ready barcoded libraries for 454. Genome Biol. 11, R15 (2010)
Li, W. & Godzik, A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658–1659 (2006)
Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011)
Schloss, P. D. et al. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537–7541 (2009)
Conlan, S., Kong, H. H. & Segre, J. A. Species-level analysis of DNA sequence data from the NIH Human Microbiome Project. PLoS ONE 7, e47075 (2012)
Kong, H. H. et al. Temporal shifts in the skin microbiome associated with disease flares and treatment in children with atopic dermatitis. Genome Res. 22, 850–859 (2012)
Yue, J. C. & Clayton, M. K. A similarity measure based on species proportions. Comm. Statist. Theory Methods 34, 2123–2131 (2005)
Ewing, B. & Green, P. Base-calling of automated sequencer traces using phred. II. Error probabilities. Genome Res. 8, 186–194 (1998)
Ewing, B., Hillier, L., Wendl, M. C. & Green, P. Base-calling of automated sequencer traces using phred. I. Accuracy assessment. Genome Res. 8, 175–185 (1998)
Pruesse, E. et al. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res. 35, 7188–7196 (2007)
Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004)
Matsen, F. A., Kodner, R. B. & Armbrust, E. V. pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree. BMC Bioinformatics 11, 538 (2010)
Han, M. V. & Zmasek, C. M. phyloXML: XML for evolutionary biology and comparative genomics. BMC Bioinformatics 10, 356 (2009)
Acknowledgements
We thank J. Heitman, A. Amend, Y. Shea, M. Turner, I. Brownell and M. Udey for helpful discussions. We thank J. Fekecs for assistance with the figures. This work was supported by the US National Institutes of Health (NIH) NHGRI and NCI Intramural Research Programs, and in part by NIH grant no. 1K99AR059222 (to H.H.K.). Sequencing was funded by grants from the NIH (1UH2AR057504-01 and 4UH3AR057504-02).
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K.F., H.H.K. and J.A.S. designed the outline of the study. D.S. and E.N. recruited human subjects and assisted H.H.K. in sample collection for the experiment. K.F. and J.Y. assembled and curated the fungal database. J.A.M. and C.D. prepared the clinical samples for sequencing. The members of the NIH Intramural Sequencing Center Comparative Sequencing program carried out sequencing. K.F., J.O., S.C. and M.P. analysed sequence data. K.F., H.H.K. and J.A.S. drafted the manuscript with specific contributions from J.O., J.Y. and S.C. All authors read and approved the final version of the manuscript.
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This file contains Supplementary Material and Methods, additional references, Supplementary Figures 1-10 and Supplementary Tables 1-8. (PDF 1904 kb)
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Findley, K., Oh, J., Yang, J. et al. Topographic diversity of fungal and bacterial communities in human skin. Nature 498, 367–370 (2013). https://doi.org/10.1038/nature12171
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DOI: https://doi.org/10.1038/nature12171