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Universality of human microbial dynamics

Author

Listed:
  • Amir Bashan

    (Brigham and Women’s Hospital and Harvard Medical School)

  • Travis E. Gibson

    (Brigham and Women’s Hospital and Harvard Medical School)

  • Jonathan Friedman

    (Physics of Living Systems, Massachusetts Institute of Technology)

  • Vincent J. Carey

    (Brigham and Women’s Hospital and Harvard Medical School)

  • Scott T. Weiss

    (Brigham and Women’s Hospital and Harvard Medical School)

  • Elizabeth L. Hohmann

    (Massachusetts General Hospital and Harvard Medical School)

  • Yang-Yu Liu

    (Brigham and Women’s Hospital and Harvard Medical School
    Center for Cancer Systems Biology, Dana-Farber Cancer Institute)

Abstract

A new computational method to characterize the dynamics of human-associated microbial communities is applied to data from two large-scale metagenomic studies, and suggests that gut and mouth microbiomes of healthy individuals are subjected to universal (that is, host-independent) dynamics, whereas skin microbiomes are shaped by the host environment; the method paves the way to designing general microbiome-based therapies.

Suggested Citation

  • Amir Bashan & Travis E. Gibson & Jonathan Friedman & Vincent J. Carey & Scott T. Weiss & Elizabeth L. Hohmann & Yang-Yu Liu, 2016. "Universality of human microbial dynamics," Nature, Nature, vol. 534(7606), pages 259-262, June.
    • Handle: RePEc:nat:nature:v:534:y:2016:i:7606:d:10.1038_nature18301
    DOI: 10.1038/nature18301
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    Citations

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    Cited by:

    1. Lena Takayasu & Wataru Suda & Eiichiro Watanabe & Shinji Fukuda & Kageyasu Takanashi & Hiroshi Ohno & Misako Takayasu & Hideki Takayasu & Masahira Hattori, 2017. "A 3-dimensional mathematical model of microbial proliferation that generates the characteristic cumulative relative abundance distributions in gut microbiomes," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-20, August.
    2. Sean M Gibbons & Sean M Kearney & Chris S Smillie & Eric J Alm, 2017. "Two dynamic regimes in the human gut microbiome," PLOS Computational Biology, Public Library of Science, vol. 13(2), pages 1-20, February.
    3. Joe J. Lim & Christian Diener & James Wilson & Jacob J. Valenzuela & Nitin S. Baliga & Sean M. Gibbons, 2023. "Growth phase estimation for abundant bacterial populations sampled longitudinally from human stool metagenomes," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    4. Hunter R Johnson & Donovan D Trinidad & Stephania Guzman & Zenab Khan & James V Parziale & Jennifer M DeBruyn & Nathan H Lents, 2016. "A Machine Learning Approach for Using the Postmortem Skin Microbiome to Estimate the Postmortem Interval," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-23, December.
    5. Lu Wu & Xu-Wen Wang & Zining Tao & Tong Wang & Wenlong Zuo & Yu Zeng & Yang-Yu Liu & Lei Dai, 2024. "Data-driven prediction of colonization outcomes for complex microbial communities," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    6. Pengfa Li & Leho Tedersoo & Thomas W. Crowther & Baozhan Wang & Yu Shi & Lu Kuang & Ting Li & Meng Wu & Ming Liu & Lu Luan & Jia Liu & Dongzhen Li & Yongxia Li & Songhan Wang & Muhammad Saleem & Alex , 2023. "Global diversity and biogeography of potential phytopathogenic fungi in a changing world," Nature Communications, Nature, vol. 14(1), pages 1-13, December.

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