Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1207756 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:In this study, microbial communities from triplicate leach-bed anaerobic bioreactors digesting grass were analysed. Each reactor comprised two microbial fractions, one immobilized on grass (biofilm) and the other in a planktonic state present in the leachate. Microbial communities from the two fractions were systematically investigated for community composition and function. This was carried out using DNA, RNA and protein co-extraction. The microbial structure of each fraction was examined using 16S rRNA deep sequencing, while the active members of the consortia were identified using the same approach on cDNA generated from co-extracted RNA samples. Microbial function was investigated using a metaproteomic workflow combining SDS-PAGE and LC-MS/MS analysis.
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Project description: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.
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Project description:Microbial communities that degrade lignocellulosic biomass are typified by high levels of species- and strain-level complexity, as well as synergistic interactions between both cellulolytic and non-cellulolytic microorganisms. Here we deconvoluted a highly efficient cellulose-degrading and methanogenic consortium (SEM1b) that is co-dominated by Clostridium (Ruminiclostridium) thermocellum and multiple heterogenic strains affiliated to C. proteolyticus. A time-series analysis was performed over the entire lifetime span of the microbial community and comprised of metagenomic, metatranscriptomic, metabolomics, metaproteomic and 16S rRNA gene analysis for 8 time points, in triplicate. Metagenomic analysis of SEM1b recovered metagenome-assembled genomes (MAGs) for each constituent population, whereas in parallel two novel strains of C. proteolyticus were isolated and sequenced. Both the recovered MAGs and the isolated strains were used as a database for further functional meta-omics. Absolute quantitative metatranscriptomics was performed thanks the spike-in of an in vitro transcribed RNA as an internal standard and label-free quantification was used for the metaproteomic analysis. The present dataset has been used for several publications. The first aim of the project was to characterize the interactions between uncultured populations in a lignocellulose-degrading community. Furthermore, because of the in-depth multi-omics characterization of the community, the dataset was used to develop new approaches for meta-omics integration as well as to assess the protein-to-RNA ratio of multiple microbial populations simultaneously. Modifications of multi-omics toolkits allowed us to assess the linearity between transcriptome and proteome for each population over time and reveal deeper functional-related trends and integrative co-dependent metabolisms that drive the overall phenotype of microbial communities.
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Project description:Soil transplant serves as a proxy to simulate climate change in realistic climate regimes. Here, we assessed the effects of climate warming and cooling on soil microbial communities, which are key drivers in Earth’s biogeochemical cycles, four years after soil transplant over large transects from northern (N site) to central (NC site) and southern China (NS site) and vice versa. Four years after soil transplant, soil nitrogen components, microbial biomass, community phylogenetic and functional structures were altered. Microbial functional diversity, measured by a metagenomic tool named GeoChip, and phylogenetic diversity are increased with temperature, while microbial biomass were similar or decreased. Nevertheless, the effects of climate change was overridden by maize cropping, underscoring the need to disentangle them in research. Mantel tests and canonical correspondence analysis (CCA) demonstrated that vegetation, climatic factors (e.g., temperature and precipitation), soil nitrogen components and CO2 efflux were significantly correlated to the microbial community composition. Further investigation unveiled strong correlations between carbon cycling genes and CO2 efflux in bare soil but not cropped soil, and between nitrogen cycling genes and nitrification, which provides mechanistic understanding of these microbe-mediated processes and empowers an interesting possibility of incorporating bacterial gene abundance in greenhouse gas emission modeling.
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