Ontology highlight
ABSTRACT:
PROVIDER: PRJNA338862 | ENA |
REPOSITORIES: ENA
Similar Datasets
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: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:<p><strong>BACKGROUND:</strong> The human intestinal microbiome plays a central role in overall health status, especially in early life stages. 16S rRNA amplicon sequencing is used to profile its taxonomic composition; however, multiomic approaches have been proposed as the most accurate methods for study of the complexity of the gut microbiota. In this study, we propose an optimized method for bacterial diversity analysis that we validated and complemented with metabolomics by analyzing fecal samples.</p><p><strong>METHODS:</strong> Forty-eight different analytical combinations regarding (1) 16S rRNA variable region sequencing, (2) a feature selection approach, and (3) taxonomy assignment methods were tested. A total of 18 infant fecal samples grouped depending on the type of feeding were analyzed by the proposed 16S rRNA workflow and by metabolomic analysis.</p><p><strong>RESULTS:</strong> The results showed that the sole use of V4 region sequencing with ASV identification and VSEARCH for taxonomy assignment produced the most accurate results. The application of this workflow showed clear differences between fecal samples according to the type of feeding, which correlated with changes in the fecal metabolic profile.</p><p><strong>CONCLUSION:</strong> A multiomic approach using real fecal samples from 18 infants with different types of feeding demonstrated the effectiveness of the proposed 16S rRNA-amplicon sequencing workflow.</p>
2021-08-18 | MTBLS2942 | MetaboLights
Project description:We used 16S V3/V4 region amplification to evaluate the composition of bacteria species in mouse fecal pellets. Fecel pellets were collected from young-adult (12 weeks old) wild type C57Bl/6 mice and aged (72 weeks old) wild type C57Bl/6 mice after 21 days of vehicle or antibiotics treatment (to induce gut microbiota depletion). In one sequencing round, we sequenced a total of 12 different fecal samples (3 young control, 3 aged control, 3 young depleted gut microbiota (ABX) and 3 aged depleted gut microbiota (ABX)). Amplicons were indexed using the Nextera XT Index Kit and pooled into a library for Illumina sequencing.
2020-11-03 | GSE160628 | GEO
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:Fecal samples collected on day 5 from randomly selected colitic SD rats were analyzed for gut microbiota by sequencing the V4 region of the 16S rRNA gene. The orally administered Dex-P-laden NPA2 coacervate (Dex-P/NPA2) significantly restores the diversity of gut microbiota compared with colitic SD rats in the Dex-P/PBS group and the untreated colitic rats (Control).
2021-11-06 | GSE167138 | GEO
Project description:This study aimed to analyze changes in gut microbiota composition in mice after transplantation of fecal microbiota (FMT, N = 6) from the feces of NSCLC patients by analyzing fecal content using 16S rRNA sequencing, 10 days after transplantation. Specific-pathogen-free (SPF) mice were used for each experiments (N=4) as controls.
2023-07-01 | E-MTAB-12812 | biostudies-arrayexpress
Project description:Analysis of breast cancer survivors' gut microbiota after lifestyle intervention, during the COVID-19 lockdown, by 16S sequencing of fecal samples.
2023-01-13 | E-MTAB-12486 | biostudies-arrayexpress
Project description:The gut microbiome is known to be sensitive to changes in the immune system, especially during autoimmune diseases such as Multiple Sclerosis (MS). Our study examines the changes to the gut microbiome that occur during Experimental Autoimmune Encephalomyelitis (EAE), an animal model for MS. We collected fecal samples at key stages of EAE progression and quantified microbial abundances with 16S V4 amplicon sequencing. Our analysis of the data suggests that commensal Lactobacillaceae fall in abundance during EAE while other commensal populations belonging to the Clostridiaceae, Ruminococcaceae, and Peptostreptococcaceae families expand. Community analysis with microbial co-occurrence networks points to these three taxa as mediators of gut microbiome dysbiosis. We also employed PICRUSt2 to impute MetaCyc Enzyme Consortium (EC) pathway abundances from the original microbial abundance data. From this analysis, we found that a number of imputed EC pathways responsible for the production of compounds with indole groups are enriched in mice undergoing EAE. Our analysis and interpretation of results provides a detailed picture of the changes to the gut microbiome that are occurring throughout the course of EAE disease progression.
2020-09-15 | GSE153118 | GEO
Project description:Fecal samples Illumina MiSeq 16S rRNA sequencing, V4 hypervariable region
| EGAD00001004106 | EGA