Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1104755 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR28830154.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 1 of 1 |
Similar Datasets
Project description:Metagenomic analysis of Vibrio cholerae contaminated fresh water
| PRJNA33243 | 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.
2009-01-08 | GSE14318 | GEO
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:Metagenomic and metaproteomic analyses were utilized to determine the composition and function of complex air-water interface biofilms sampled from the hulls of two ships that were deployed in different geographic locations.
2014-10-13 | PXD000961 | Pride
Project description:Today, many contaminants of emerging concern can be measured in waters across the United States, including the tributaries of the Great Lakes. However, just because the chemicals can be measured does not mean that they necessarily result in harm to fish and other aquatic species. Complicating risk assessment in these waters is the fact that aquatic species are encountering the chemicals as mixtures, which may have additive or synergistic risks that cannot be calculated using single chemical hazard and concentration-response information. We developed an in vitro effects-based screening approach to help us predict potential liver toxicity and cancer in aquatic organisms using water from specific Great Lakes tributaries: St. Louis River (MN), Bad River (WI), Fox River (WI), Manitowoc River (WI), Milwaukee River (WI), Indiana Harbor Canal (IN), St. Joseph River (MI), Grand River (MI), Clinton River (MI), River Rouge (MI), Maumee River (OH), Vermilion River (OH), Cuyahoga River (OH), Genesee River (NY), and Oswego River (NY). We exposed HepG2 cells for 48hrs to medium spiked with either field collected water (final concentration of environmental samples in the exposure medium were 75% of the field-collected water samples) or purified water. Using a deep neural network we clustered our collection sites from each tributary based on water chemistry. We also performed high throughput transcriptomics on the RNA obtained from the HepG2 cells. We used the transcriptomics data with our Bayesian Inferene for Sustance and Chemical Toxicity (BISCT) Bayesian Network for Steatosis to predict the probability of the field samples yielding a gene expression pattern consistent with predicting steatosis as an outcome. Surprisingly, we found that the probability of steatosis did not correspond to the surface water chemistry clustering. Our analysis suggests that chemical signatures are not informative in predicting biological effects. Furthermore, recent reports published after we obtained our samples, suggest that chemical levels in the sediment may be more relevant for predicting potential biological effects in the fish species developing tumors in the Great Lakes basin.
2022-12-01 | GSE146903 | GEO
Project description:The increased urban pressures are often associated with specialization of microbial communities. Microbial communities being a critical player in the geochemical processes, makes it important to identify key environmental parameters that influence the community structure and its function.In this proect we study the influence of land use type and environmental parameters on the structure and function of microbial communities. The present study was conducted in an urban catchment, where the metal and pollutants levels are under allowable limits. The overall goal of this study is to understand the role of engineered physicochemical environment on the structure and function of microbial communities in urban storm-water canals. Water and sediment samples were collected after a rain event from Sungei Ulu Pandan watershed of >25km2, which has two major land use types: Residential and industrial. Samples were analyzed for physicochemical variables and microbial community structure and composition. Functional gene abundance was determined using GeoChip.
2014-12-22 | E-GEOD-64286 | biostudies-arrayexpress