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N Biotechnol. 2013 Sep 25;30(6):614-22. doi: 10.1016/j.nbt.2013.01.002. Epub 2013 Jan 29.

Metaproteome analysis of the microbial communities in agricultural biogas plants.

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1
Otto von Guericke University, Bioprocess Engineering, Universitätsplatz 2, 39106 Magdeburg, Germany.

Abstract

In biogas plants agricultural waste and energy crops are converted by complex microbial communities to methane for the production of renewable energy. In Germany, this process is widely applied namely in context of agricultural production systems. However, process disturbances, are one of the major causes for economic losses. In addition, the conversion of biomass, in particular of cellulose, is in most cases incomplete and, hence, insufficient. Besides technical aspects, a more profound characterization concerning the functionality of the microbial communities involved would strongly support the improvement of yield and stability in biogas production. To monitor these communities on the functional level, metaproteome analysis was applied in this study to full-scale agricultural biogas plants. Proteins were extracted directly from sludge for separation by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and subsequent identification with mass spectrometry. Protein profiles obtained with SDS-PAGE were specific for different biogas plants and often stable for several months. Differences of protein profiles were visualized by clustering, which allowed not only the discrimination between mesophilic and thermophilic operated biogas plants but also the detection of process disturbances such as acidification. In particular, acidification of a biogas plant was detected in advance by disappearance of major bands in SDS-PAGE. Identification of proteins from SDS-PAGE gels revealed that methyl CoM reductase, which is responsible for the release of methane during methanogenesis, from the order Methanosarcinales was significantly decreased. Hence, it is assumed that this enzyme might be a promising candidate to serve as a predictive biomarker for acidification.

PMID:
23369865
DOI:
10.1016/j.nbt.2013.01.002
[Indexed for MEDLINE]
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