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Variable habitat conditions drive species covariation in the human microbiota

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  • Charles K Fisher
  • Thierry Mora
  • Aleksandra M Walczak

Abstract

Two species with similar resource requirements respond in a characteristic way to variations in their habitat—their abundances rise and fall in concert. We use this idea to learn how bacterial populations in the microbiota respond to habitat conditions that vary from person-to-person across the human population. Our mathematical framework shows that habitat fluctuations are sufficient for explaining intra-bodysite correlations in relative species abundances from the Human Microbiome Project. We explicitly show that the relative abundances of closely related species are positively correlated and can be predicted from taxonomic relationships. We identify a small set of functional pathways related to metabolism and maintenance of the cell wall that form the basis of a common resource sharing niche space of the human microbiota.Author summary: The human body is inhabited by a vast number of microorganisms comprising the human microbiota. The species composition of the microbiota varies considerably from person-to-person and the relative abundances of some species rise and fall in concert. We introduce a mathematical model where differences in habitat conditions cause most of the variability of the microbiota. A statistical analysis shows that variable habitat conditions are sufficient for explaining the patterns of variation observed across a healthy human population and, as a result, the correlation between the relative abundances of two species reflects how closely related they are rather than how they directly interact with each other.

Suggested Citation

  • Charles K Fisher & Thierry Mora & Aleksandra M Walczak, 2017. "Variable habitat conditions drive species covariation in the human microbiota," PLOS Computational Biology, Public Library of Science, vol. 13(4), pages 1-18, April.
  • Handle: RePEc:plo:pcbi00:1005435
    DOI: 10.1371/journal.pcbi.1005435
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    1. Trendafilov, Nickolay T., 2010. "Stepwise estimation of common principal components," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3446-3457, December.
    2. Tanya Yatsunenko & Federico E. Rey & Mark J. Manary & Indi Trehan & Maria Gloria Dominguez-Bello & Monica Contreras & Magda Magris & Glida Hidalgo & Robert N. Baldassano & Andrey P. Anokhin & Andrew C, 2012. "Human gut microbiome viewed across age and geography," Nature, Nature, vol. 486(7402), pages 222-227, June.
    3. Chris S. Smillie & Mark B. Smith & Jonathan Friedman & Otto X. Cordero & Lawrence A. David & Eric J. Alm, 2011. "Ecology drives a global network of gene exchange connecting the human microbiome," Nature, Nature, vol. 480(7376), pages 241-244, December.
    4. Peter J. Turnbaugh & Ruth E. Ley & Micah Hamady & Claire M. Fraser-Liggett & Rob Knight & Jeffrey I. Gordon, 2007. "The Human Microbiome Project," Nature, Nature, vol. 449(7164), pages 804-810, October.
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    Cited by:

    1. Rajita Menon & Vivek Ramanan & Kirill S Korolev, 2018. "Interactions between species introduce spurious associations in microbiome studies," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-20, January.

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