Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1005046 | ENA |
REPOSITORIES: ENA
Similar Datasets
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.
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Project description:Gut microbiota were assessed in 540 colonoscopy-screened adults by 16S rRNA gene sequencing of stool samples. Investigators compared gut microbiota diversity, overall composition, and normalized taxon abundance among these groups.
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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.
2017-05-12 | PXD006118 | Pride
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.
2021-05-17 | PXD023186 | Pride
Project description:The impact of mono-chronic S. stercoralis infection on the gut microbiome and microbial activities in infected participants was explored. The 16S rRNA gene sequencing of a longitudinal study with 2 sets of human fecal was investigated. Set A, 42 samples were matched, and divided equally into positive (Pos) and negative (Neg) for S. stercoralis diagnoses. Set B, 20 samples of the same participant in before (Ss+PreT) and after (Ss+PostT) treatment was subjected for 16S rRNA sequences and LC-MS/MS to explore the effect of anti-helminthic treatment on microbiome proteomes.
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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.
2021-05-17 | PXD023710 | Pride
Project description:We report the use of high-throughput sequencing technology to detect the microbial composition and abundance of mice grastic contents before and after Helicobacter pylori infection or Lactobacillus paracasei ZFM54 pretreatment/treatment. The genomic DNA was obtained by the QIAamp PowerFecal DNA Kit. Then, the DNA samples were sent to BGI Genomics Co., Ltd. (Shenzhen, China) for V3-V4 region of the 16S rRNA gene high-throughput sequencing with an Illumina MiSeq platform. DNA samples were sequenced using primers 338F (forward primer sequence ACTCCTACGGGAGGCAGCAG)-806R (reverse primer sequence GGACTACHVGGGTWTCTAAT). The sequencing analyses were carried out using silva138/16s database as a reference for the assignation of Amplicon Sequence Variant (ASV) at 100% similarity.
2022-07-27 | GSE208665 | GEO
Project description:16S rRNA gene sequencing of colonic feces from mice fed regular chow, regular chow+nobiletin, high-fat diet or high-fat diet+nobiletin.
2022-05-06 | E-MTAB-11551 | biostudies-arrayexpress