Dataset Information

Biogas Plant Survey Magdeburg 2014-2016

ABSTRACT: 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.

INSTRUMENT(S): LTQ Orbitrap Elite

ORGANISM(S): Environmental Samples <methanosarcinales>

SUBMITTER: Kay Schallert

LAB HEAD: Dirk Benndorf

PROVIDER: PXD009349 | Pride | 2019-05-03

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	BGP02_T17_Ext1_Bande01.mgf	Mgf
	BGP02_T17_Ext1_Bande01.raw	Raw
	BGP02_T17_Ext1_Bande01_F035275.dat	Other
	BGP02_T17_Ext1_Bande02.mgf	Mgf
	BGP02_T17_Ext1_Bande02.raw	Raw

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Publications

Metaproteome analysis reveals that syntrophy, competition, and phage-host interaction shape microbial communities in biogas plants.

Heyer R R Schallert K K Siewert C C Kohrs F F Greve J J Maus I I Klang J J Klocke M M Heiermann M M Hoffmann M M Püttker S S Calusinska M M Zoun R R Saake G G Benndorf D D Reichl U U

Microbiome 20190427 1

<h4>Background</h4>In biogas plants, complex microbial communities produce methane and carbon dioxide by anaerobic digestion of biomass. For the characterization of the microbial functional networks, samples of 11 reactors were analyzed using a high-resolution metaproteomics pipeline.<h4>Results</h4>Examined methanogenesis archaeal communities were either mixotrophic or strictly hydrogenotrophic in syntrophy with bacterial acetate oxidizers. Mapping of identified metaproteins with process steps ...[more]

PMID: 31029164

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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.

Project description:Current developments have led to a reconsidering of energy policy in many countries with the aim of increasing the share of renewable energies in the energy supply, where the anaerobic digestion (AD) of biomass to produce methane also plays an important role. To improve biomass digestion while ensuring overall process stability, microbiome-based management strategies became more important. By applying combined metagenome and metaproteome, as well as metagenomically assembled genome (MAG)-centric analyses, it is possible to determine not only the functional potential but also the expressed functions of the entire microbial community and also individual MAGs. This approach was used in this study for the production-scale biogas plant 35 (BP35) consisting of three digesters which were operated differently regarding process temperatures, feedstocks and other process parameters. Different process conditions were hypothesized to result in specific microbiome adaptations and differentially abundant metabolic functions in the digesters. Based on metagenomic single-read analyses, several taxa residing in the three digesters of BP35 were shown to correlate with the corresponding substrates and temperatures. In particular, the genus Defluviitoga showed the strongest correlation to the process temperature and the genus Acetomicrobium featured a direct correlation to the concentartions of different acids including acetic acid. Analysis of the functional potential and expressed functions of the entire microbial community of the three digesters revealed that the genes and key enzymes relevant for the biogas process were present and also expressed. Differences between the abundances of certain genes and expressed enzymes could be related to the specific parameters of the corresponding digesters. Regarding the biogas related metabolic pathways, MAG-centric metagenomics and metaproteomics indicated the functional potential and the actual expressed metabolic functions of certain MAGs that are differentially abundant in the three digesters. These MAGs, belonging to the phylum Firmicutes, the class Bacilli and the orders Caldicoprobacterales and Bacteroidales showed a specific metabolic activity within the three digesters and have important roles in the hydrolysis, acidogenesis or acetogenesis of the anaerobic digestion process. An archaeal MAG assigned to the species Methanothermobacter wolfeii was the most abundant and highly active hydrogenotrophic methanogen in digester 3 featuring an operation temperature of 54 °C. Beside the MAGs that were differentially abundant in the three digesters, also MAGs which were more evenly distributed were analyzed. The most abundant and highly active MAG in all digesters belongs to the class Limnochordia and was shown to be ubiquitous in all three digesters and exhibit activity in a variety of pathways representing hydrolysis as well as the acido- and acetogenesis steps of the biogas process. Other MAGs assigned to the phylum Firmicutes, genus Acetomicrobium and the hydrogenotrophic species Methanoculleus thermohydrogenotrophicum were also shown to be more evenly distributed and active in the three digesters. Corresponding taxa appeared to be more resilient to the different process parameters of the three digesters, and therefore, may support a stable biogas process. Overall, the combined metagenome and metaproteome analysis of biogas digesters helps to gain deeper insights into the composition of the whole microbial community, biogas related pathways and their expression, which could contribute to an improved microbiome-based process management in the future.