IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-39149-2.html
   My bibliography  Save this article

Revealing proteome-level functional redundancy in the human gut microbiome using ultra-deep metaproteomics

Author

Listed:
  • Leyuan Li

    (Beijing Institute of Lifeomics
    University of Ottawa)

  • Tong Wang

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

  • Zhibin Ning

    (University of Ottawa)

  • Xu Zhang

    (University of Ottawa)

  • James Butcher

    (University of Ottawa)

  • Joeselle M. Serrana

    (University of Ottawa)

  • Caitlin M. A. Simopoulos

    (University of Ottawa)

  • Janice Mayne

    (University of Ottawa)

  • Alain Stintzi

    (University of Ottawa)

  • David R. Mack

    (University of Ottawa and Children’s Hospital of Eastern Ontario Inflammatory Bowel Disease Centre and Research Institute)

  • Yang-Yu Liu

    (Brigham and Women’s Hospital and Harvard Medical School
    The Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign)

  • Daniel Figeys

    (University of Ottawa)

Abstract

Functional redundancy is a key ecosystem property representing the fact that different taxa contribute to an ecosystem in similar ways through the expression of redundant functions. The redundancy of potential functions (or genome-level functional redundancy $${{{{{{\rm{FR}}}}}}}_{g}$$ FR g ) of human microbiomes has been recently quantified using metagenomics data. Yet, the redundancy of expressed functions in the human microbiome has never been quantitatively explored. Here, we present an approach to quantify the proteome-level functional redundancy $${{{{{{\rm{FR}}}}}}}_{p}$$ FR p in the human gut microbiome using metaproteomics. Ultra-deep metaproteomics reveals high proteome-level functional redundancy and high nestedness in the human gut proteomic content networks (i.e., the bipartite graphs connecting taxa to functions). We find that the nested topology of proteomic content networks and relatively small functional distances between proteomes of certain pairs of taxa together contribute to high $${{{{{{\rm{FR}}}}}}}_{p}$$ FR p in the human gut microbiome. As a metric comprehensively incorporating the factors of presence/absence of each function, protein abundances of each function and biomass of each taxon, $${{{{{{\rm{FR}}}}}}}_{p}$$ FR p outcompetes diversity indices in detecting significant microbiome responses to environmental factors, including individuality, biogeography, xenobiotics, and disease. We show that gut inflammation and exposure to specific xenobiotics can significantly diminish the $${{{{{{\rm{FR}}}}}}}_{p}$$ FR p with no significant change in taxonomic diversity.

Suggested Citation

  • Leyuan Li & Tong Wang & Zhibin Ning & Xu Zhang & James Butcher & Joeselle M. Serrana & Caitlin M. A. Simopoulos & Janice Mayne & Alain Stintzi & David R. Mack & Yang-Yu Liu & Daniel Figeys, 2023. "Revealing proteome-level functional redundancy in the human gut microbiome using ultra-deep metaproteomics," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39149-2
    DOI: 10.1038/s41467-023-39149-2
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-39149-2
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-023-39149-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Manuel Kleiner & Erin Thorson & Christine E. Sharp & Xiaoli Dong & Dan Liu & Carmen Li & Marc Strous, 2017. "Assessing species biomass contributions in microbial communities via metaproteomics," Nature Communications, Nature, vol. 8(1), pages 1-14, December.
    2. Marco Tulio Angulo & Claude H. Moog & Yang-Yu Liu, 2019. "A theoretical framework for controlling complex microbial communities," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    3. Liang Tian & Xu-Wen Wang & Ang-Kun Wu & Yuhang Fan & Jonathan Friedman & Amber Dahlin & Matthew K. Waldor & George M. Weinstock & Scott T. Weiss & Yang-Yu Liu, 2020. "Deciphering functional redundancy in the human microbiome," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    4. Xu Zhang & Shelley A. Deeke & Zhibin Ning & Amanda E. Starr & James Butcher & Jennifer Li & Janice Mayne & Kai Cheng & Bo Liao & Leyuan Li & Ruth Singleton & David Mack & Alain Stintzi & Daniel Figeys, 2018. "Metaproteomics reveals associations between microbiome and intestinal extracellular vesicle proteins in pediatric inflammatory bowel disease," Nature Communications, Nature, vol. 9(1), pages 1-14, December.
    5. Fernanda Salvato & Robert L Hettich & Manuel Kleiner, 2021. "Five key aspects of metaproteomics as a tool to understand functional interactions in host-associated microbiomes," PLOS Pathogens, Public Library of Science, vol. 17(2), pages 1-10, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xu, Libai & Kong, Dehan & Wang, Lidan & Gu, Hong & Kenney, Toby & Xu, Ximing, 2023. "Proportional stochastic generalized Lotka–Volterra model with an application to learning microbial community structures," Applied Mathematics and Computation, Elsevier, vol. 448(C).
    2. Carolyne Luciane de Almeida Godoy & Lucas Marques Costa & Carlos Alberto Guerra & Vanessa Sales de Oliveira & Breno Pereira de Paula & Wilson José Fernandes Lemos Junior & Vinícius da Silva Duarte & R, 2022. "Potentially Postbiotic-Containing Preservative to Extend the Use-By Date of Raw Chicken Sausages and Semifinished Chicken Products," Sustainability, MDPI, vol. 14(5), pages 1-17, February.
    3. Joaquín Gutiérrez Mena & Sant Kumar & Mustafa Khammash, 2022. "Dynamic cybergenetic control of bacterial co-culture composition via optogenetic feedback," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    4. Yasa Baig & Helena R. Ma & Helen Xu & Lingchong You, 2023. "Autoencoder neural networks enable low dimensional structure analyses of microbial growth dynamics," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    5. Leah A. Owens & Sagan Friant & Bruno Martorelli Di Genova & Laura J. Knoll & Monica Contreras & Oscar Noya-Alarcon & Maria G. Dominguez-Bello & Tony L. Goldberg, 2024. "VESPA: an optimized protocol for accurate metabarcoding-based characterization of vertebrate eukaryotic endosymbiont and parasite assemblages," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    6. Vanessa R. Marcelino & Caitlin Welsh & Christian Diener & Emily L. Gulliver & Emily L. Rutten & Remy B. Young & Edward M. Giles & Sean M. Gibbons & Chris Greening & Samuel C. Forster, 2023. "Disease-specific loss of microbial cross-feeding interactions in the human gut," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    7. Ray Sajulga & Caleb Easterly & Michael Riffle & Bart Mesuere & Thilo Muth & Subina Mehta & Praveen Kumar & James Johnson & Bjoern Andreas Gruening & Henning Schiebenhoefer & Carolin A Kolmeder & Steph, 2020. "Survey of metaproteomics software tools for functional microbiome analysis," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-20, November.
    8. Benjamin H. Good & Layton B. Rosenfeld, 2023. "Eco-evolutionary feedbacks in the human gut microbiome," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    9. Xu-Wen Wang & Yang Hu & Giulia Menichetti & Francine Grodstein & Shilpa N. Bhupathiraju & Qi Sun & Xuehong Zhang & Frank B. Hu & Scott T. Weiss & Yang-Yu Liu, 2023. "Nutritional redundancy in the human diet and its application in phenotype association studies," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    10. Yu, Xiaoyao & Liang, Yongqing & Wang, Xiaomeng & Jia, Tao, 2021. "The network asymmetry caused by the degree correlation and its effect on the bimodality in control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39149-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.