Ontology highlight
ABSTRACT:
PROVIDER: PRJNA507289 | ENA |
REPOSITORIES: ENA
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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:Anaerobic degradation (AD) of heterogeneous agricultural substrates is a complex process involving a diverse microbial community. While microbial community composition of a variety of biogas plants (BPs) is well described, little is known about metabolic processes and microbial interaction patterns. Here, we analyzed 16 large-scale BPs using metaproteomics. All metabolic steps of AD were observed in the metaproteome, and multivariate analyses indicated that they were shaped by temperature, pH, volatile fatty acid content and substrate types. Biogas plants can be subdivided into hydrogenotrophic, acetoclastic or a mixture of both methanogenic pathways based on their process parameters, taxonomic and functional metaproteome. Network analyses showed large differences in metabolic and microbial interaction patterns. Both, number of interactions and interaction partners were highly dependent on the prevalent methanogenic pathway for most species. Nevertheless, we observed a highly conserved metabolism of different abundant Pseudomonas spp. for all BPs indicating a key role during AD in carbohydrate hydrolysis irrespectively of variabilities in substrate input and process parameters. Thus, Pseudomonas spp. are of high importance for robust and versatile AD food webs, which highlight a large variety of downstream metabolic processes for their respective methanogenic pathways.
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