Water hose 16S
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB49015 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:16s metagenomics of dam water from 3 sources.
| PRJEB14048 | ENA
Project description:Hypervariable regions V3-V5 of bacterial 16S rRNA genes. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
2014-03-14 | E-ERAD-254 | biostudies-arrayexpress
Project description:We characterized the bacterial diversity of chlorinated drinking water from three surface water treatment plants supplying the city of Paris, France. For this purpose, we used serial analysis of V6 ribosomal sequence tag (SARST-V6) to produce concatemers of PCR-amplified ribosomal sequence tags (RSTs) from the V6 hypervariable region of the 16S rRNA gene for sequence analysis. Using SARST-V6, we obtained bacterial profiles for each drinking water sample, demonstrating a strikingly high degree of biodiversity dominated by a large collection of low-abundance phylotypes. In all water samples, between 57.2-77.4% of the sequences obtained indicated bacteria belonging to the Proteobacteria phylum. Full-length 16S rDNA sequences were also generated for each sample, and comparison of the RSTs with these sequences confirmed the accurate assignment for several abundant bacterial phyla identified by SARST-V6 analysis, including members of unclassified bacteria, which account for 6.3-36.5% of all V6 sequences. These results suggest that these bacteria may correspond to a common group adapted to drinking water systems. The V6 primers used were subsequently evaluated with a computer algorithm to assess their hybridization efficiency. Potential errors associated with primer-template mismatches and their impacts on taxonomic group detection were investigated. The biodiversity present in all three drinking water samples suggests that the bacterial load of the drinking water leaving treatment plants may play an important role in determining the downstream community dynamics of water distribution networks.
2009-01-08 | GSE14318 | GEO
Project description:We performed a 16S sequencing analysis on Cervical Swab of women undergoing Assisted Reproductive Technologies
2023-11-17 | E-MTAB-11151 | biostudies-arrayexpress
Project description:Irrigation Water and Fecal 16S rRNA Raw sequence reads
| PRJNA545292 | ENA
Project description:Surface water 16S rRNA gene amplicons
| PRJNA507089 | ENA
Project description:We characterized the bacterial diversity of chlorinated drinking water from three surface water treatment plants supplying the city of Paris, France. For this purpose, we used serial analysis of V6 ribosomal sequence tag (SARST-V6) to produce concatemers of PCR-amplified ribosomal sequence tags (RSTs) from the V6 hypervariable region of the 16S rRNA gene for sequence analysis. Using SARST-V6, we obtained bacterial profiles for each drinking water sample, demonstrating a strikingly high degree of biodiversity dominated by a large collection of low-abundance phylotypes. In all water samples, between 57.2-77.4% of the sequences obtained indicated bacteria belonging to the Proteobacteria phylum. Full-length 16S rDNA sequences were also generated for each sample, and comparison of the RSTs with these sequences confirmed the accurate assignment for several abundant bacterial phyla identified by SARST-V6 analysis, including members of unclassified bacteria, which account for 6.3-36.5% of all V6 sequences. These results suggest that these bacteria may correspond to a common group adapted to drinking water systems. The V6 primers used were subsequently evaluated with a computer algorithm to assess their hybridization efficiency. Potential errors associated with primer-template mismatches and their impacts on taxonomic group detection were investigated. The biodiversity present in all three drinking water samples suggests that the bacterial load of the drinking water leaving treatment plants may play an important role in determining the downstream community dynamics of water distribution networks. 3 different drinking water samples (Orly, Ivry, Joinville drinking water sample)
2009-01-07 | E-GEOD-14318 | biostudies-arrayexpress
Project description:16S rRNA gene sequencing of colonic feces from mice fed regular chow, regular chow+nobiletin, high-fat diet or high-fat diet+nobiletin.
2022-05-06 | E-MTAB-11551 | biostudies-arrayexpress
Project description:We aim to determine if mice in our mouse colony had similar of different microbiomes. To do this, we perfromed 16S sequencing of stool from unifected mice of the gentotypes listed below. We also looked at how infection causes dysbiosis of the mircobiome, measuring 16S sequencing over a C.rodentium infection timecourse.
2018-07-03 | GSE116491 | GEO
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