Assessing species biomass contributions in microbial communities via metaproteomics
Open accessPublished version of a preprint
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.
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Chen, T., Yu, W.-H., Izard, J., Baranova, O. V., Lakshmanan, A., & Dewhirst, F. E. (2010) · Database · doi:10.1093/database/baq013 · Cited by 1,162 · see citing works
MetaQUAST: evaluation of metagenome assemblies
Mikheenko, A., Saveliev, V., & Gurevich, A. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btv697 · Cited by 711 · see citing works
Milo, R. (2013) · BioEssays · doi:10.1002/bies.201300066 · Cited by 643 · see citing works
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Li, L., Ning, Z., Zhang, X., Mayne, J., Cheng, K., Stintzi, A., & Figeys, D. (2020) · Microbiome · doi:10.1186/s40168-020-00806-z · Cited by 328 · see citing works
- Authors
- Kleiner, M., Thorson, E., Sharp, C. E., Dong, X., Liu, D., Li, C., & Strous, M.
- Affiliations
- North Carolina State University (US)
- University of Calgary (CA)
- Corresponding author
- Kleiner, Manuel
- Venue
- Nature Communications
- Published
- 2017-11-16
- Volume
- 8
- Issue
- 1
- Pages
- 1558-1558
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC5691128
- OpenAlex
- W2950438666
- Cited by
- 291
- References
- 3
- Citations by year
- 2026: 25 · 2025: 36 · 2024: 45 · 2023: 48 · 2022: 30 · 2021: 33 · 2020: 37 · 2019: 29 · 2018: 7 · 2017: 1
- FWCI
- 15.67
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- University of Calgary
- Canada First Research Excellence Fund
- Natural Sciences and Engineering Research Council of Canada
- Topics
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Keywords
- microbial community structure, species biomass, protein abundance, metaproteomics, microbial mats, saliva microbiota, sequencing bias, population abundance estimation
- MeSH terms
- Archaea, Bacteria, Bacteriophages, Humans, RNA, Ribosomal, 16S, Saliva, Biomass, Proteome, Genomics, Proteomics, Lakes, Microbiota
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