Project description:Nitrate-reducing iron(II)-oxidizing bacteria are widespread in the environment contribute to nitrate removal and influence the fate of the greenhouse gases nitrous oxide and carbon dioxide. The autotrophic growth of nitrate-reducing iron(II)-oxidizing bacteria is rarely investigated and poorly understood. The most prominent model system for this type of studies is enrichment culture KS, which originates from a freshwater sediment in Bremen, Germany. To gain insights in the metabolism of nitrate reduction coupled to iron(II) oxidation under in the absence of organic carbon and oxygen limited conditions, we performed metagenomic, metatranscriptomic and metaproteomic analyses of culture KS. Raw sequencing data of 16S rRNA amplicon sequencing, shotgun metagenomics (short reads: Illumina; long reads: Oxford Nanopore Technologies), metagenome assembly, raw sequencing data of shotgun metatranscriptomes (2 conditions, triplicates) can be found at SRA in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA682552. This dataset contains proteomics data for 2 conditions (heterotrophic and autotrophic growth conditions) in triplicates.
Project description:The study critically evaluate the results of 16S targeted amplicon sequencing performed on the total DNA collected from healthy donors’ blood samples in the light of specific negative controls.
Project description:16S amplicon pool analyses of the four gut sections of the wood-feeding beetle, Odontotaenius disjunctus The beetle is purely wood feeding, and we aim to first characterize the community that exist within the gut sections
Project description:16S amplicon pool analyses of the four gut sections of the wood-feeding beetle, Odontotaenius disjunctus The beetle is purely wood feeding, and we aim to first characterize the community that exist within the gut sections 4 beetles, four gut sections per beetle, one PhyloChip per gut section, total = 16 chips
Project description:Sensitive models of climate change impacts would require a better integration of multi-omics approaches that connect the abundance and activity of microbial populations. Here, we show that climate is a fundamental driver of the protein abundance of microbial populations (metaproteomics), yet not their genomic abundance (16S rRNA gene amplicon sequencing), supporting the hypothesis that metabolic activity may be more closely linked to climate than community composition.
