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Metaproteomics of complex microbial communities in biogas plants
Author(s) -
Heyer Robert,
Kohrs Fabian,
Reichl Udo,
Benndorf Dirk
Publication year - 2015
Publication title -
microbial biotechnology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.287
H-Index - 74
ISSN - 1751-7915
DOI - 10.1111/1751-7915.12276
Subject(s) - metaproteomics , biogas , metagenomics , biomass (ecology) , biochemical engineering , bioenergy , microbiology and biotechnology , environmental science , biology , computer science , biofuel , ecology , engineering , biochemistry , gene
Summary Production of biogas from agricultural biomass or organic wastes is an important source of renewable energy. Although thousands of biogas plants ( BGP s) are operating in G ermany, there is still a significant potential to improve yields, e.g. from fibrous substrates. In addition, process stability should be optimized. Besides evaluating technical measures, improving our understanding of microbial communities involved into the biogas process is considered as key issue to achieve both goals. Microscopic and genetic approaches to analyse community composition provide valuable experimental data, but fail to detect presence of enzymes and overall metabolic activity of microbial communities. Therefore, metaproteomics can significantly contribute to elucidate critical steps in the conversion of biomass to methane as it delivers combined functional and phylogenetic data. Although metaproteomics analyses are challenged by sample impurities, sample complexity and redundant protein identification, and are still limited by the availability of genome sequences, recent studies have shown promising results. In the following, the workflow and potential pitfalls for metaproteomics of samples from full‐scale BGP are discussed. In addition, the value of metaproteomics to contribute to the further advancement of microbial ecology is evaluated. Finally, synergistic effects expected when metaproteomics is combined with advanced imaging techniques, metagenomics, metatranscriptomics and metabolomics are addressed.

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