Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: High throughput sequencing of 16S rRNA gene amplicon from enriched activated sludge

PROVIDER: PRJNA598535 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR10812383.fastq.gz	Fastqsanger.gz
	SRR10812384.fastq.gz	Fastqsanger.gz
	SRR10812385.fastq.gz	Fastqsanger.gz
	SRR10812386.fastq.gz	Fastqsanger.gz
	SRR10812387.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 13

Similar Datasets

Hhigh-throughput sequencing of in vitro fecal fermentation samples

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:High throughput 16S rRNA amplicon sequencing

| PRJNA751915 | ENA

Soil Metaproteomics LC-MS

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:16S rRNA amplicon sequencing - Low-DO activated sludge

| PRJNA482250 | ENA

Project description:16S rRNA amplicon data from activated sludge

| PRJNA1062133 | ENA

Study of Gut Microbiome and Colorectal Tumors

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

activated sludge metagenome

Project description:Activated sludge 16S rRNA gene

| PRJNA182716 | ENA

Quantification of mock microbial communities with metagenomes, 16S rRNA gene amplicons and metaproteomics

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:16S rRNA gene high-throughput sequencing

| PRJNA1153362 | ENA

Project description:16S rRNA gene high-throughput sequencing

| PRJNA874856 | ENA