ArticleBiotechnology for biofuels2016
Proteotyping of biogas plant microbiomes separates biogas plants according to process temperature and reactor type.
Article in Biotechnology for biofuels, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- Taxonomic-Level Protein Quantification in Metaproteomics Using a Biomass-Constrained Expectation-Maximization Approach.Journal of the American Society for Mass Spectrometry · 2026Article
- Biological Function Assignment across Taxonomic Levels in Mass-Spectrometry-Based Metaproteomics via a Modified Expectation Maximization Algorithm.Journal of proteome research · 2025Article
- Article
- Microbiome modeling: a beginner's guide.Frontiers in microbiology · 2024Review
- Cover crop monocultures and mixtures enhance bacterial abundance and functionality in the maize root zone.ISME communications · 2024Article
- A metagenomic approach to demystify the anaerobic digestion black box and achieve higher biogas yield: a review.Frontiers in microbiology · 2024Review
- GroEL-Proteotyping of Bacterial Communities Using Tandem Mass Spectrometry.International journal of molecular sciences · 2023Article
- Inter-kingdom interactions and stability of methanogens revealed by machine-learning guided multi-omics analysis of industrial-scale biogas plants.The ISME journal · 2023Article
- In silico evaluation of a targeted metaproteomics strategy for broad screening of cellulolytic enzyme capacities in anaerobic microbiome bioreactors.Biotechnology for biofuels and bioproducts · 2022Article
- Bioconversion of Lignocellulosic Biomass into Value Added Products under Anaerobic Conditions: Insight into Proteomic Studies.International journal of molecular sciences · 2021Review
- Increasing the power of interpretation for soil metaproteomics data.Microbiome · 2021Article
- Indicative Marker Microbiome Structures Deduced from the Taxonomic Inventory of 67 Full-Scale Anaerobic Digesters of 49 Agricultural Biogas Plants.Microorganisms · 2021Article
- Molecular Microbial Community Analysis as an Analysis Tool for Optimal Biogas Production.Microorganisms · 2021Review
- Combined whole cell wall analysis and streamlined in silico carbohydrate-active enzyme discovery to improve biocatalytic conversion of agricultural crop residues.Biotechnology for biofuels · 2021Review
- Microbial invasions in sludge anaerobic digesters.Applied microbiology and biotechnology · 2021Review
- Microbiological Surveillance of Biogas Plants: Targeting Acetogenic Community.Frontiers in microbiology · 2021Article
- A complete and flexible workflow for metaproteomics data analysis based on MetaProteomeAnalyzer and Prophane.Nature protocols · 2020Article
- Robust Accurate Identification and Biomass Estimates of Microorganisms via Tandem Mass Spectrometry.Journal of the American Society for Mass Spectrometry · 2020Article
- Genome Analyses and Genome-Centered Metatranscriptomics ofMicroorganisms · 2019Article
- Different response of bacteria, archaea and fungi to process parameters in nine full-scale anaerobic digesters.Microbial biotechnology · 2019Article
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10 authors.
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Abstract
backgroundMethane yield and biogas productivity of biogas plants (BGPs) depend on microbial community structure and function, substrate supply, and general biogas process parameters. So far, however, relatively little is known about correlations between microbial community function and process parameters. To close this knowledge gap, microbial communities of 40 samples from 35 different industrial biogas plants were evaluated by a metaproteomics approach in this study.
resultsLiquid chromatography coupled to tandem mass spectrometry (Orbitrap Elite™ Hybrid Ion Trap-Orbitrap Mass Spectrometer) of all 40 samples as triplicate enabled the identification of 3138 different metaproteins belonging to 162 biological processes and 75 different taxonomic orders. The respective database searches were performed against UniProtKB/Swiss-Prot and seven metagenome databases. Subsequent clustering and principal component analysis of these data allowed for the identification of four main clusters associated with mesophile and thermophile process conditions, the use of upflow anaerobic sludge blanket reactors and BGP feeding with sewage sludge. Observations confirm a previous phylogenetic study of the same BGP samples that was based on 16S rRNA gene sequencing by De Vrieze et al. (Water Res 75:312-323, 2015). In particular, we identified similar microbial key players of biogas processes, namely Bacillales, Enterobacteriales, Bacteriodales, Clostridiales, Rhizobiales and Thermoanaerobacteriales as well as Methanobacteriales, Methanosarcinales and Methanococcales. For the elucidation of the main biomass degradation pathways, the most abundant 1 % of metaproteins was 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.
conclusionsThis is the first large-scale metaproteome study of BGPs. Proteotyping of BGPs reveals general correlations between the microbial community structure and its function with process parameters. The monitoring of changes on the level of microbial key functions or even of the microbial community represents a well-directed tool for the identification of process problems and disturbances.Graphical abstractCorrelation between the different orders and process parameter, as well as principle component analysis of all investigated biogas plants based on the identified metaproteins.
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