Project description:In this study we developed metaproteomics based methods for quantifying taxonomic composition of microbiomes (microbial communities). We also compared metaproteomics based quantification to other quantification methods, namely metagenomics and 16S rRNA gene amplicon sequencing. The metagenomic and 16S rRNA data can be found in the European Nucleotide Archive (Study number: PRJEB19901). For the method development and comparison of the methods we analyzed three types of mock communities with all three methods. The communities contain between 28 to 32 species and strains of bacteria, archaea, eukaryotes and bacteriophage. For each community type 4 biological replicate communities were generated. All four replicates were analyzed by 16S rRNA sequencing and metaproteomics. Three replicates of each community type were analyzed with metagenomics. The "C" type communities have same cell/phage particle number for all community members (C1 to C4). The "P" type communities have the same protein content for all community members (P1 to P4). The "U" (UNEVEN) type communities cover a large range of protein amounts and cell numbers (U1 to U4). We also generated proteomic data for four pure cultures to test the specificity of the protein inference method. This data is also included in this submission.
Project description:Drosophila melanogaster was used to investigate the influence of microbiota-derived intestinal flora and its metabolites on host transcriptional regulation by adding sodium butyrate to a sterile diet for constructing a sterile Drosophila model. In order to further investigate the effects of sodium butyrate on Drosophila melanogaster at the molecular mechanism level, we detected the abundance and composition of midgut microbial colonies based on 16S rRNA gene sequences, and analyzed the overall structure and metabolic activities of host transcriptional networks by combining transcriptome and non-target metabolomics data.
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 consumption of fermented food has been linked to positive health outcomes due to a variety of functional properties. Fermented dairy constitutes a major dietary source and contains lactoseas main carbohydrate and living starter cultures. To investigate whether nutritional and microbial modulation impacted intestinal microbiota composition and activity, we employed fecal microbiota fermentations and a dairy model system consisting of lactose and β-galactosidase positive and negative Streptococcus thermophilus. Based on 16S rRNA gene based microbial community analysis, we observed that lactose addition increased the abundance of Bifidobacteriaceae, and of Veillonellaceae and Enterobacteraceae in selected samples. The supplied lactose was hydrolysed within 24 h of fermentation and led to higher expression of community indigenous β-galactosidases. Targeted protein analysis confirmed that bifidobacteria contributed most β-galactosidases together with other taxa including Escherichia coli and Anaerobutyricum hallii. Lactose addition led to 1.1-1.8 fold higher levels of butyrate compared to controls likely due to (i) lactate-crossfeeding and (ii) direct lactose metabolism by butyrate producing Anaerobutyricum and Faecalibacterium spp. Representatives of both genera used lactose to produce butyrate in single cultures. When supplemented at around 5.5 log cells mL-1, S. thermophilus or its beta-galactosidase negative mutant outnumbered the indigenous Streptococcaceae population at the beginning of fermentation but had no impact on lactose utilisation and final SCFA profiles. This study brings forward new fundamental insight into interactions of major constituents of fermented dairy with the intestinal microbiota. We provide evidence that lactose addition increases fecal microbiota production of butyrate through cross-feeding and direct metabolism without contribution of starter cultures.
Project description:Nitrate-reducing iron(II)-oxidizing (NDFO) 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. A second NDFO culture, culture BP, was obtained with a sample taken in 2015 at the same pond and cultured in a similar way. 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 BP. Raw sequencing data of 16S rRNA amplicon sequencing (V4 region with Illumina and near full-length with PacBio), shotgun metagenomics, metagenome assembly, raw sequencing data of shotgun metatranscriptomes (2 conditions, triplicates) can be found at SRA in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA693457. This dataset contains proteomics data for 2 conditions in triplicates. Samples R23, R24, and R25 are grown in autotrophic conditions, samples R26, R27, and R28 in heterotrophic conditions.
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.