Dataset Information

Adaptation of a microbial community to demand-oriented biological methanation

ABSTRACT: Background: Biological conversion of the surplus of renewable electricity to CH4 could support energy storage and strengthen the power grid. Biological methanation (BM) is closely linked to the activity of biogas-producing bacterial community and methanogenic Archaea in particular. During reactor operations, the microbiome is often subject to various changes whereby the microorganisms are challenged to adapt to the new conditions. In this study, a hydrogenotrophic-adapted microbial community in a laboratory-scale BM fermenter was monitored for its pH, gas production, conversion yields and composition. To investigate the robustness of BM regarding power oscillations, the biogas microbiome was exposed to five H2 starvations patterns for several hours.

INSTRUMENT(S): maXis

ORGANISM(S): Escherichia Coli

SUBMITTER: Robert Heyer

LAB HEAD: Dirk Benndorf

PROVIDER: PXD034618 | Pride | 2023-03-11

REPOSITORIES: Pride

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Adaptation of a microbial community to demand-oriented biological methanation.

Khesali Aghtaei Hoda H Püttker Sebastian S Maus Irena I Heyer Robert R Huang Liren L Sczyrba Alexander A Reichl Udo U Benndorf Dirk D

Biotechnology for biofuels and bioproducts 20221116 1

<h4>Background</h4>Biological conversion of the surplus of renewable electricity and carbon dioxide (CO<sub>2</sub>) from biogas plants to biomethane (CH<sub>4</sub>) could support energy storage and strengthen the power grid. Biological methanation (BM) is linked closely to the activity of biogas-producing Bacteria and methanogenic Archaea. During reactor operations, the microbiome is often subject to various changes, e.g., substrate limitation or pH-shifts, whereby the microorganisms are chall ...[more]

PMID: 36384582

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Project description:Biogas plants (BGPs) produce methane and carbon dioxide through the anaerobic digestion of agricultural waste. Identification of strategies for more stable biogas plant operation and increased biogas yields require better knowledge about the individual degradation steps and the interactions within the microbial communities. The metaprotein profiles of ten agricultural BGPs and one laboratory reactor were investigated using a metaproteomics pipeline. Fractionation of samples using SDS-PAGE was combined with a high resolution Orbitrap mass spectrometer, metagenome sequences specific for BGPs, and the MetaProteomeAnalyzer software. This enabled us to achieve a high coverage of the metaproteome of the BGP microbial communities. The investigation revealed approx. 17,000 protein groups (metaproteins), covering the majority of the expected metabolic networks of the biogas process such as hydrolysis, transport, fermentation processes, amino acid metabolism, methanogenesis and bacterial C1-metabolism. Biological functions could be linked with the taxonomic composition. Two different types of BGPs were classified by the abundance of the acetoclastic methanogenesis and by abundance of enzymes implicating syntrophic acetate oxidation. Linking of the identified metaproteins with the process steps of the Anaerobic Digestion Model 1 proved the main model assumptions but indicated also some improvements such as considering syntrophic acetate oxidation. Beside the syntrophic interactions, the microbial communities in BGPs are also shaped by competition for substrates and host-phage interactions causing cell lysis. In particular, larger amounts of Bacteriophages for the bacterial families Bacillaceae, Enterobacteriaceae and Clostridiaceae, exceeding the cell number of the Bacteria by approximately four-fold. In contrast, less Bacteriophages were found for Archaea, but more CRISPR proteins were detected. On the one hand, the virus induced turnover of biomass might cause slow degradation of complex biomass in BGP. On the other hand, the lysis of bacterial cells allows cycling of essential nutrients.

Project description:Background: Methane yield and biogas productivity of biogas plants depend on microbial community structure and functionality, substrate supply, and general process parameters. Little is known, however, about the correlations between microbial community function and the process parameters. To close this knowledge gap the microbial community of 40 industrial biogas plants was evaluated by a metaproteomics approach in this study. Results: Liquid chromatography coupled to tandem mass spectrometry (Elite Hybrid Ion Trap Orbitrap) enabled the identification of 3138 metaproteins belonging to 162 biological processes and 75 different taxonomic orders. Therefore, database searches were performed against UniProtKB/Swiss-Prot and several metagenome databases. Subsequent clustering and principal component analysis of these data allowed to identify four main clusters associated to mesophilic and thermophilic process conditions, upflow anaerobic sludge blanket reactors and sewage sludge as substrate. Observations confirm a previous phylogenetic study of the same biogas plant samples that was based on 16S-rRNA gene by De Vrieze et al. (2015) (De Vrieze, Saunders et al. 2015). Both studies described similar microbial key players of the biogas process, namely Bacillales, Enterobacteriales, Bacteriodales, Clostridiales, Rhizobiales and Thermoanaerobacteriales as well as Methanobacteriales, Methanosarcinales and Methanococcales. In addition, a correlation study and a Gephi graph network based on the correlations between the taxonomic orders and process parameters suggested the presence of various trophic interactions, e.g. syntrophic hydrogen transfer between Thermoanaerobacteriales and Methanomicrobiales. For the elucidation of the main biomass degradation pathways the most abundant 1% of metaproteins were assigned to the KEGG map 1200 representing the central carbon metabolism. Additionally, the effect of the process parameters (i) temperature, (ii) organic loading rate (OLR), (iii) total ammonia nitrogen (TAN) and (iv) sludge retention time (SRT) on these pathways was investigated. For example high TAN correlated with hydrogenotrophic methanogens and bacterial one-carbon metabolism, indicating syntrophic acetate oxidation. Conclusion: This study shows the benefit of large-scale proteotyping of biogas plants, enabling the identification of general correlations between the process parameters and the microbial community structure and function. Changes in the level of microbial key functions or even in the microbial community type represent a valuable hint for process problems and disturbances.

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Dataset Information

Adaptation of a microbial community to demand-oriented biological methanation

Publications

Adaptation of a microbial community to demand-oriented biological methanation.

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