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:<p>Microbial life in soil is fueled by dissolved organic matter (DOM) that leaches from the litter layer. It is well known that decomposer communities adapt to the available litter source, but it remains unclear if they functionally compete or synergistically address different litter types. Therefore, we decomposed beech, oak, pine and grass litter from two geologically distinct sites in a lab-scale decomposition experiment. We performed a correlative network analysis on the results of direct infusion HR-MS DOM analysis and cross-validated functional predictions from 16S rRNA gene amplicon sequencing and with DOM and metaproteomic analyses. Here we show that many functions are redundantly distributed within decomposer communities and that their relative expression is rapidly optimized to address litter-specific properties. However, community changes are likely forced by antagonistic mechanisms as we identified several natural antibiotics in DOM. As a consequence, the decomposer community is specializing towards the litter source and the state of decomposition (community divergence) but showing similar litter metabolomes (metabolome convergence). Our multi-omics-based results highlight that DOM not only fuels microbial life, but it additionally holds meta-metabolomic information on the functioning of ecosystems.</p>
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.
