Assessing species biomass contributions in microbial communities via metaproteomics. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Kleiner, Manuel; Thorson, Erin; Sharp, Christine; Dong, Xiaoli; Liu, Dan; Li, Carmen; Strous, Marc
• Is Part Of: Nature communications. Volume 8:Issue 1(2017)
• Page Start: 1
• Page End: 14
• Publication Date: 2017-12
• Subjects: Biology -- Periodicals; Physical sciences -- Periodicals; 505
• DOI: 10.1038/s41467-017-01544-x
• Languages: English
• ISSNs: 2041-1723

Abstract

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. Convenient methods for assessing microbial community structure in terms of biomass are lacking. Here, the authors present a metaproteomics-based approach for assessing microbial community structure using protein abundance as a measure for biomass contributions of individual populations.