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Assessing species biomass contributions in microbial communities via metaproteomics.

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, 16-S 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.

SUBMITTER: Kleiner M

PROVIDER: S-EPMC5691128 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Assessing species biomass contributions in microbial communities via metaproteomics.

Kleiner Manuel M Thorson Erin E Sharp Christine E CE Dong Xiaoli X Liu Dan D Li Carmen C Strous Marc M

Nature communications 20171116 1

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, 16-S 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 ...[more]

PMID: 29146960

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Project description:Hitherto, the main goal of metaproteomic analyses has been to characterize the functional role of particular microorganisms in the microbial ecology of various microbial communities. Recently, it has been suggested that metaproteomics could be used for bioprospecting microbial communities to query for the most active enzymes to improve the selection process of industrially relevant enzymes. In the present study, to reduce the complexity of metaproteomic samples for targeted bioprospecting of novel enzymes, a microbial community capable of producing cellulases was maintained on a chemically defined medium in an enzyme suppressed metabolic steady state. From this state, it was possible to specifically and distinctively induce the desired cellulolytic activity. The extracellular fraction of the protein complement of the induced sample could thereby be purified and compared to a non-induced sample of the same community by differential gel electrophoresis to discriminate between constitutively expressed proteins and proteins upregulated in response to the inducing substance.Using the applied approach, downstream analysis by mass spectrometry could be limited to only proteins recognized as upregulated in the cellulase-induced sample. Of 39 selected proteins, the majority were found to be linked to the need to degrade, take up, and metabolize cellulose. In addition, 28 (72%) of the proteins were non-cytosolic and 17 (44%) were annotated as carbohydrate-active enzymes. The results demonstrated both the applicability of the proposed approach for identifying extracellular proteins and guiding the selection of proteins toward those specifically upregulated and targeted by the enzyme inducing substance. Further, because identification of interesting proteins was based on the regulation of enzyme expression in response to a need to hydrolyze and utilize a specific substance, other unexpected enzyme activities were able to be identified.The described approach created the conditions necessary to be able to select relevant extracellular enzymes that were extracted from the enzyme-induced microbial community. However, for the purpose of bioprospecting for enzymes to clone, produce, and characterize for practical applications, it was concluded that identification against public databases was not sufficient to identify the correct gene or protein sequence for cloning of the identified novel enzymes.

Dataset Information

Assessing species biomass contributions in microbial communities via metaproteomics.

Publications

Assessing species biomass contributions in microbial communities via metaproteomics.

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