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South China Sea (SCS) sediments MiSeq 16S rRNA gene sequencing (archaeal 16S rRNA gene)

ABSTRACT: MiSeq 16S rRNA gene (archaeal 16S rRNA gene) sequences of 12 SCS sediments

PROVIDER: PRJEB11900 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	ERR1146990.fastq.gz	Fastqsanger.gz
	ERR1146991.fastq.gz	Fastqsanger.gz
	ERR1146992.fastq.gz	Fastqsanger.gz
	ERR1146993.fastq.gz	Fastqsanger.gz
	ERR1146994.fastq.gz	Fastqsanger.gz

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South China Sea (SCS) sediments MiSeq 16S rRNA gene sequencing (archaeal 16S rRNA gene)

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WBSCR16 Deficiency Drives Adaptive Metabolic Flexibility Via Impaired Mitochondrial 16S rRNA Maturation

Project description:Mitochondrial rRNAs play important roles in regulating mtDNA-encoded gene expression and energy metabolism subsequently. However, the proteins that regulate mitochondrial 16S rRNA processing remain poorly understood. Herein, we generated adipose-specific Wbscr16-/- mice and cells, both of which exhibited dramatic mitochondrial changes. Subsequently, WBSCR16 was identified as a 16S rRNA-binding protein essential for the cleavage of 16S rRNA-mt-tRNALeu, facilitating 16S rRNA processing and mitochondrial ribosome assembly. Additionally, WBSCR16 recruited RNase P subunit MRPP3 to nascent 16S rRNA and assisted in this specific cleavage. Furthermore, evidence showed that adipose-specific Wbscr16 ablation promotes energy wasting via lipid preference in brown adipose tissue, leading to excess energy expenditure and resistance to obesity. In contrast, overexpression of WBSCR16 upregulated 16S rRNA processing and induced a preference for glucose utilization in both transgenic mouse models and cultured cells. These findings suggest that WBSCR16 plays essential roles in mitochondrial 16S rRNA processing in mammals, and is the key mitochondrial protein to balance glucose and lipid metabolism.

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16s rRNA-young and old mouse gut microbiota-stroke

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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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