Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1067524 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR27737063_1.fastq.gz | Fastqsanger.gz | |||
| SRR27737063_2.fastq.gz | Fastqsanger.gz | |||
| SRR27737064_1.fastq.gz | Fastqsanger.gz | |||
| SRR27737064_2.fastq.gz | Fastqsanger.gz | |||
| SRR27737065_1.fastq.gz | Fastqsanger.gz |
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Project description:Rural household biogas digesters in Qinghai-Tibet Plateau Metagenome
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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.
2016-04-19 | PXD003526 | Pride
Project description:Metagenome data of the four biogas plants of the "Biogas Marker" project
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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.
2019-05-03 | PXD009349 | Pride
Project description:Inhibition of the anaerobic digestion process through accumulation of volatile fatty acids (VFA) is a recurring problem which is the result of unbalanced growth between acidogenic bacteria and methanogens. A speedy recovery is essential for an establishment of a feasible economical biogas productions. Yet, little is known regarding the organisms participating in the recovery. In this study the organisms involved in the recovery were studied using protein-stable isotope probing (Protein-SIP) and mapping this data onto a binned metagenome. Under acetate-accumulated simulating conditions a formation of 13C-labeled CO2 and CH4 was detected immediately after the addition of [U-13C]acetate, indicative of a high turnover rate of acetate. Several labeled peptides were detected in protein-SIP analysis. These 13C-labeled peptides were mapped onto a binned metagenome for improved taxanomical classification of the organisms involved. The results revealed that Methanosarcina and Methanoculleus were actively involved in acetate turnover, as were five subspecies of Clostridia and one Bacteroidetes. The organisms affiliating with Clostridia and Bacteroidetes all contained the FTFHS gene for formyltetrahydrofolate synthetase, a key enzyme for reductive acetogenesis; indicating that these organisms are possible syntrophic acetate-oxidizing bacteria (SAOB) that can facilitate acetate consumption via syntrophic acetate oxidation coupled with hydrogenotrophic methanogenesis (SAO-HM). This study represents the first study applying protein-SIP for analysis of complex biogas samples, a promising method for identifying key microorganisms involved in specific pathways.
2016-05-11 | PXD002996 | Pride
Project description:Bacteriophage – host dynamics and interactions are important for microbial community composition and ecosystem function. Nonetheless, empirical evidence in engineered environment is scarce. Here, we examined phage and prokaryotic community composition of four anaerobic digestors in full-scale wastewater treatment plants (WWTPs) across China. Despite relatively stable process performance in biogas production, both phage and prokaryotic groups fluctuated monthly over a year of study period. Nonetheless, there were significant correlations in their α- and β-diversities between phage and prokaryotes. Phages explained 40.6% of total prokaryotic community composition, much higher than the explainable power by abiotic factors (14.5%). Consequently, phages were significantly (P<0.010) linked to parameters related to process performance including biogas production and volatile solid concentrations. Association network analyses showed that phage-prokaryote pairs were deeply rooted, and two network modules were exclusively comprised of phages, suggesting a possibility of co-infection. Those results collectively demonstrate phages as a major biotic factor in controlling bacterial composition. Therefore, phages may play a larger role in shaping prokaryotic dynamics and process performance of WWTPs than currently appreciated, enabling reliable prediction of microbial communities across time and space.
2016-12-29 | GSE92978 | GEO