Kedma 16s rRNA gene
Ontology highlight
ABSTRACT:
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR526982.fastq.gz | Fastqsanger.gz | |||
| ERR526983.fastq.gz | Fastqsanger.gz | |||
| ERR526984.fastq.gz | Fastqsanger.gz | |||
| ERR526985.fastq.gz | Fastqsanger.gz | |||
| ERR526986.fastq.gz | Fastqsanger.gz |
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Project description:We aimed to investigate the microbial community composition in patients with intracerebral hemorrhage (ICH) and its effect on prognosis. The relationship between changes in bacterial flora and the prognosis of spontaneous cerebral hemorrhage was studied in two cohort studies. Fecal samples from healthy volunteers and patients with intracerebral hemorrhage were subjected to 16S rRNA sequencing at three time points: T1 (within 24 hours of admission), T2 (3 days post-surgery), and T3 (7 days post-surgery) using Illumina high-throughput sequencing technology.
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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.
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Project description:Irrigation Water and Fecal 16S rRNA Raw sequence reads
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Project description:Iron metabolism is pivotal for cell fitness in the mammalian host. However, its role in group 3 innate lymphoid cells (ILC3s) is unknown. Here we show that transferrin receptor CD71-mediated iron metabolism cell-intrinsically controls ILC3 maintenance, cytokine production and host protection against Citrobacter rodentium infection, and metabolically affects mitochondrial respiration by switching of oxidative phosphorylation toward glycolysis. Iron deprivation or Tfrc deficiency reduces the expression and/or activity of the aryl hydrocarbon receptor (Ahr), a ligand-dependent transcription factor and a key ILC3 regulator. Furthermore, consistent with its role in generation of Ahr ligand, microbiome exerts a negative impact on CD71 expression in an Ahr-dependent manner. Genetic ablation or activation of Ahr in ILC3s leads to CD71 upregulation or downregulation, respectively, suggesting an active suppression of CD71 by Ahr. Iron overload partially restores defective ILC3 compartment in the small intestine of Ahr-deficient mice, representing compensatory action of CD71 upregulation during Ahr deficiency. Mechanistically, Ahr directly binds to the promoter region of the Tfrc locus to inhibit Tfrc transcription. These data collectively demonstrate an under-appreciated role of the Ahr-CD71-iron axis in regulation of ILC3 maintenance and function.
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