Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1095876 | 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.
2022-03-01 | PXD009773 | Pride
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.
| 2255499 | ecrin-mdr-crc
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: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.
2023-11-07 | PXD037975 | JPOST Repository
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:Freshwater ecosystems can be largely affected by neighboring agriculture fields where potential fertilizer nitrate run-off may leach into surrounding water bodies. To counteract this eutrophic driver, farmers often utilize denitrifying woodchip bioreactors (WBRs) in which a consortium of microorganisms convert the nitrate into nitrogen-gases in anoxia, fueled by the degradation of lignocellulose. Polysaccharide-degrading strategies have been well-described for various aerobic and anaerobic systems, including the use of carbohydrate-active enzymes, utilization of lytic polysaccharide monooxygenases (LPMOs) and other redox enzymes, as well as the use of cellulosomes and polysaccharide utilization loci. However, for denitrifying microorganisms, the lignocellulose-degrading strategies remain largely unknown. Here, we have applied a combination of enrichment techniques, gas measurements, multi-omics approaches, and amplicon sequencing of fungal ITS and procaryotic 16S rRNA genes to highlight microbial drivers for lignocellulose transformation in woodchip bioreactors with the aim to provide an in-depth characterization of the indigenous microorganisms and their active enzymes. Our findings highlight a microbial community enriched for lignocellulose-degrading denitrifiers with key players from Giesbergeria, Cellulomonas, Azonexus, and UBA5070, including polysaccharide utilization loci from Bacteroidetes. A wide substrate specificity is observed among the many expressed carbohydrate active enzymes (CAZymes), evidencing a swift degradation of lignocellulose, including even enzymes with auxiliary activities whose functionality is still puzzling under strict anaerobic conditions.
2024-10-21 | PXD050137 | Pride
Project description:Amplicon sequencing analysis of 16S rRNA gene of SCN-degrading consortium
| PRJDB7172 | ENA