Biogass plant
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA926915 | ENA |
REPOSITORIES: ENA
Similar Datasets
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
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:Anna Karenina as a promoter of microbial diversity in the cosmopolitan agricultural pest Zeugodacus cucurbitae (Diptera, Tephritidae)
| PRJEB70707 | ENA
Project description:Loss of mature β cell function and identity, or β cell dedifferentiation, is seen in all types of diabetes mellitus. Two competing models explain β cell dedifferentiation in diabetes. In the first model, β cells dedifferentiate in the reverse order of their developmental ontogeny. This model predicts that dedifferentiated β cells resemble β cell progenitors. In the second model, β cell dedifferentiation depends on the type of diabetogenic stress. This model, which we call the “Anna Karenina” model, predicts that in each type of diabetes, β cells dedifferentiate in their own way, depending on how their mature identity is disrupted by any particular diabetogenic stress. We directly tested the two models using a β cell-specific lineage-tracing system coupled with RNA-sequencing in mice. We constructed a multidimensional map of β cell transcriptional trajectories during the normal course of β cell postnatal development, and during their dedifferentiation in models of both type 1 diabetes (NOD) and type 2 diabetes (BTBR-Lepob/ob). Using this unbiased approach, we show here that despite some similarities between immature and dedifferentiated β cells, β cells dedifferentiation in the two mouse models is not a reversal of developmental ontogeny and is different between different types of diabetes.
2021-03-12 | GSE168743 | GEO
Project description:Biogas plant reactors microbiome metagenome
| PRJNA1101514 | ENA
Project description:16S amplicon biogas plant Metagenome
| PRJNA477920 | ENA
Project description:The functional diversity of soil microbial communities was explored for a poplar plantation, which was treated solely with biogas slurry, or combined with biochar at different fertilization intensities over several years.
2020-03-30 | GSE133800 | GEO
Project description:The Anna Karenina model of β cell maturation in development and their dedifferentiation in type 1 and type 2 diabetes
| PRJNA713802 | ENA