Ontology highlight
ABSTRACT:
PROVIDER: PRJNA627640 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:To determine what can the transcriptome tell us about populations of free-ranging bottlenose dolphins, Tursiops truncatus. Keywords: health assessment A total of 151 individuals were sampled from 4 different geographic location in U.S. waters between June of 2003 and June of 2006. Of the 151 dolphins, 59 were from Charleston, 35 from Indian River Lagoon, FL, 32 from Sarasota Bay, FL and 25 from St. Josephs Bay FL. Total RNA extracted from blood leukocytes of wild dolphins was analyzed and different sets of genes were used as classifiers in a machine learning approach, Artificial Neural Networks (ANN).
2010-05-05 | E-GEOD-10617 | biostudies-arrayexpress
Project description:Goal: To determine the effects of capture-release events in wild dolphins (Tursiops truncatus). Methods: An analysis of the Peripheral Blood Leukocyte (PBL) transcriptome was conducted on a group of 20 animals. The samples were collected in 2 different locations along the US east coast (Charleston, SC; Indian River Lagoon, FL) and 2 blood samples were collected for each dolphin 1) immediately after the capture event (*pre*) and 2) just before the animal was released (*post*). In between *pre* and *post* blood collections (30-40 minutes) additional samples were collected from the animals for physiological, chemical and biochemical analysis. RNA extracted from *pre* and *post* blood samples was used for micorarray hybridizations and transcriptome analysis using a species-specific PBL cDNA microarray (Mancia *et al*., 2007). Keywords: blood cells (PBL)
2007-05-03 | GSE7691 | GEO
Project description:Gas hydrates, also known as clathrates, are cages of ice-like water crystals encasing gas molecules such as methane (CH4). Despite the global importance of gas hydrates, their microbiomes remain mysterious. Microbial cells are physically associated with hydrates, and the taxonomy of these hydrate-associated microbiomes is distinct from non-hydrate-bearing sites. Global 16S rRNA gene surveys show that members of sub-clade JS-1 of the uncultivated bacterial candidate phylum Atribacteria are the dominant taxa in gas hydrates. The Atribacteria phylogeny is highly diverse, suggesting the potential for wide functional variation and niche specialization. Here, we examined the distribution, phylogeny, and metabolic potential of uncultivated Atribacteria in cold, salty, and high-pressure sediments beneath Hydrate Ridge, off the coast of Oregon, USA, using a combination of 16S rRNA gene amplicon, metagenomic, and metaproteomic analysis. Methods were developed to extract bacterial cellular protein from these sediments, as outlined below. Sample Description Three sediments samples were collected from beneath Hydrate Ridge, off the coast of Oregon, USA. Sediments were cored at ODP site 1244 (44°35.1784´N; 125°7.1902´W; 895 m water depth) on the eastern flank of Hydrate Ridge ~3 km northeast of the southern summit on ODP Leg 204 in 2002 and stored at -80°C at the IODP Gulf Coast Repository. E10H5 sediment is from 68.5 meters below sediment surface interface C1H2 sediment is from 2 meters below sediment surface interface. C3H4 sediment is from 21 meters below sediment surface interface.
2020-01-22 | PXD012479 | Pride
Project description:Freshwater environments such as rivers receive effluent discharges from wastewater treatment plants, representing a potential hotspot for antibiotic resistance genes (ARGs). These effluents also contain low levels of different antimicrobials including biocides and antibiotics such as sulfonamides that can be frequently detected in rivers. The impact of such exposure on ARG prevalence and microbial diversity of riverine environment is unknown, so the aim of this study was to investigate the release of a sub-lethal concentration (<4 g L-1) of the sulfonamide compound sulfamethoxazole (SMX) on the river bacterial microbiome using a microflume system. This system was a semi-natural in-vitro microflume using river water (30 L) and sediment, with circulation to mimic river flow. A combination of ‘omics’ approaches were conducted to study the impact of SMX exposure on the microbiomes within the microflumes. Metaproteomics did not show differences in ARGs expression with SMX exposure in water.
2021-07-06 | PXD023822 | Pride
Project description:To explore how gene expression translates to developmental phenotype in both sensitive and resistant Fundulus embryos upon POP exposure, we exposed Fundulus embryos from the Elizabeth River Superfund population and the Magotha Bay, VA clean population to Elizabeth River polluted sediment extracts and measured chemical uptake, gene expression, and altered embryo anatomy, morphology and cardiac physiology during four critical developmental stages: somitogenesis, heart beat initiation, late organogenesis, and pre-hatching.
2019-05-07 | GSE130754 | GEO
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