Project description:Freshwater ecosystems can be largely affected by neighboring agriculture fields where potential fertilizer nitrate run-off may leach into surrounding water bodies. To counteract this eutrophic driver, farmers often utilize denitrifying woodchip bioreactors (WBRs) in which a consortium of microorganisms convert the nitrate into nitrogen-gases in anoxia, fueled by the degradation of lignocellulose. Polysaccharide-degrading strategies have been well-described for various aerobic and anaerobic systems, including the use of carbohydrate-active enzymes, utilization of lytic polysaccharide monooxygenases (LPMOs) and other redox enzymes, as well as the use of cellulosomes and polysaccharide utilization loci. However, for denitrifying microorganisms, the lignocellulose-degrading strategies remain largely unknown. Here, we have applied a combination of enrichment techniques, gas measurements, multi-omics approaches, and amplicon sequencing of fungal ITS and procaryotic 16S rRNA genes to highlight microbial drivers for lignocellulose transformation in woodchip bioreactors with the aim to provide an in-depth characterization of the indigenous microorganisms and their active enzymes. Our findings highlight a microbial community enriched for lignocellulose-degrading denitrifiers with key players from Giesbergeria, Cellulomonas, Azonexus, and UBA5070, including polysaccharide utilization loci from Bacteroidetes. A wide substrate specificity is observed among the many expressed carbohydrate active enzymes (CAZymes), evidencing a swift degradation of lignocellulose, including even enzymes with auxiliary activities whose functionality is still puzzling under strict anaerobic conditions.

2024-10-21 | PXD050137 | Pride

Integrated meta-omic analysis of a lignocellulose-degrading microbial community

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.

2020-08-21 | PXD016242 | Pride

GC-MS files for modeling bacterial interactions in coastal lignin degrading consortium

Project description:GC-MS files for modeling bacterial interactions in coastal lignin degrading consortium

| MSV000095829 | MassIVE