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Assessing species biomass contributions in microbial communities via metaproteomics

Author

Listed:
  • Manuel Kleiner

    (University of Calgary
    North Carolina State University)

  • Erin Thorson

    (University of Calgary)

  • Christine E. Sharp

    (University of Calgary)

  • Xiaoli Dong

    (University of Calgary)

  • Dan Liu

    (University of Calgary)

  • Carmen Li

    (University of Calgary)

  • Marc Strous

    (University of Calgary)

Abstract

Microbial community structure can be analyzed by quantifying cell numbers or by quantifying biomass for individual populations. Methods for quantifying cell numbers are already available (e.g., fluorescence in situ hybridization, 16S rRNA gene amplicon sequencing), yet high-throughput methods for assessing community structure in terms of biomass are lacking. Here we present metaproteomics-based methods for assessing microbial community structure using protein abundance as a measure for biomass contributions of individual populations. We optimize the accuracy and sensitivity of the method using artificially assembled microbial communities and show that it is less prone to some of the biases found in sequencing-based methods. We apply the method to communities from two different environments, microbial mats from two alkaline soda lakes, and saliva from multiple individuals. We show that assessment of species biomass contributions adds an important dimension to the analysis of microbial community structure.

Suggested Citation

  • 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.
    • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_s41467-017-01544-x
    DOI: 10.1038/s41467-017-01544-x
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    Cited by:

    1. 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.
    2. Zihao Zhao & Chie Amano & Thomas Reinthaler & Federico Baltar & Mónica V. Orellana & Gerhard J. Herndl, 2024. "Metaproteomic analysis decodes trophic interactions of microorganisms in the dark ocean," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    3. 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.
    4. 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.
    5. Natalie R. Cohen & Arianna I. Krinos & Riss M. Kell & Rebecca J. Chmiel & Dawn M. Moran & Matthew R. McIlvin & Paloma Z. Lopez & Alexander J. Barth & Joshua P. Stone & Brianna A. Alanis & Eric W. Chan, 2024. "Microeukaryote metabolism across the western North Atlantic Ocean revealed through autonomous underwater profiling," Nature Communications, Nature, vol. 15(1), pages 1-19, December.

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