Project description:Polyphosphate accumulating organisms are responsible for enhanced biological phosphate removal from wastewater, where they grow embedded in a matrix of extracellular polymeric substances. Little is known about the composition and dynamics of those proteins and their production by the different microorganisms. Tomás-Martínez et al., (2022) studied the turnover of proteins and polysaccharides in extracellular polymeric fractions of an enrichment culture of polyphosphate accumulating organisms using an anaerobic-aerobic sequencing batch reactor simulating EBPR conditions. Finally, the carbon source was switched to 13C-labelled acetate to study the protein turnover. Samples were collected at the end of each aerobic phase.
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: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.
Project description:Polyhydroxyalkanoates (PHAs) are bio-based, biodegradable polyesters that can be produced from organic-rich waste streams using mixed microbial cultures. To maximize PHA production, mixed microbial cultures may be enriched for PHA-producing bacteria with a high storage capacity through the imposition of cyclic, aerobic feast-famine conditions in a sequencing batch reactor (SBR). Though enrichment SBRs have been extensively investigated a bulk solutions-level, little evidence at the proteome level is available to describe the observed SBR behavior to guide future SBR optimization strategies. As such, the purpose of this investigation was to characterize proteome dynamics of a mixed microbial culture in an SBR operated under aerobic feast-famine conditions using fermented dairy manure as the feedstock for PHA production. At the beginning of the SBR cycle, excess PHA precursors were provided to the mixed microbial culture (i.e., feast), after which followed a long duration devoid of exogenous substrate (i.e., famine). Two-dimensional electrophoresis was used to separate protein mixtures during a complete SBR cycle, and proteins of interest were identified.
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.