Yoshiki Vázquez-Baeza, University of California, San Diego
Alison Vrbanac, University of California, San Diego
Paul Wischmeyer, Duke University School of Medicine
Elaine Wolfe, University of California, San Diego
Qiyun Zhu, University of California, San DiegoFollow
Rob Knight, University of California, San DiegoFollow
Daniel McDonald, University of California, San DiegoFollow
Embriette Hyde, University of California, San Diego
Justine W. Debelius, University of California, San Diego
James T. Morton, University of California, San DiegoFollow
Antonio Gonzalez, University of California, San DiegoFollow
Gail Ackermann, University of California, San DiegoFollow
Alexander A. Aksenov, University of California, San Diego
Bahar Behsaz, Department of Computer Science and Engineering
Caitriona Brennan, University of California, San Diego
Yingfeng Chen, San Diego State University
Lindsay De Right Goldasich, University of California, San Diego
Pieter C. Dorrestein, University of California, San DiegoFollow
Robert R. Dunn, NC State University
Ashkaan K. Fahimipour, University of Oregon
James Gaffney, University of California, San Diego
Jack A. Gilbert, The University of ChicagoFollow
Grant Gogul, University of California, San Diego
Jessica L. Green, University of Oregon
Philip Hugenholtz, The University of Queensland
Greg Humphrey, University of California, San DiegoFollow
Curtis Huttenhower, Harvard T.H. Chan School of Public Health
Matthew A. Jackson, King's College London
Stefan Janssen, University of California, San DiegoFollow
Dilip V. Jeste, Department of Psychiatry
Lingjing Jiang, University of California, San DiegoFollow
Scott T. Kelley, San Diego State University
Dan Knights, University of Minnesota Twin Cities

Document Type

Article

Publication Date

6-1-2018

Department

Coastal Sciences, Gulf Coast Research Laboratory

School

Ocean Science and Engineering

Abstract

Copyright © 2018 McDonald et al. Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. IMPORTANCE We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n = 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples.

Publication Title

mSystems

Volume

3

Issue

3

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