Ontology highlight
ABSTRACT:
PROVIDER: PRJNA890919 | ENA |
REPOSITORIES: ENA
Similar Datasets
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:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River.
2016-08-02 | GSE85064 | GEO
Project description:Lysinibacillus varians GY32 was isolated from river sediment of electronic waste recycling site. Its invariably filament-to-rod cell cycle represents a novel bacteria morphogenesis that is crucial in understanding cell division coordination with lifecycle and environmental bacteria adaptation. A description of genes and biological processes involved in the special filament-to-rod cell cycle of L. varians GY32 is within reach.
2017-08-15 | GSE99804 | GEO
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: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:Aquatic organisms are exposed to many toxic chemicals and interpreting the cause and effect relationships between occurrence and impairment is difficult. Toxicity Identification Evaluation (TIE) provides a systematic approach for identifying responsible toxicants. TIE relies on relatively uninformative and potentially insensitive toxicological endpoints. Gene expression analysis may provide needed sensitivity and specificity aiding in the identification of primary toxicants. The current work aims to determine the added benefit of integrating gene expression endpoints into the TIE process. A cDNA library and a custom microarray were constructed for the marine amphipod Ampelisca abdita. Phase 1 TIEs were conducted using 10% and 40% dilutions of acutely toxic sediment. Gene expression was monitored in survivors and controls. An expression-based classifier was developed and evaluated against control organisms, organisms exposed to low or medium toxicity diluted sediment, and chemically selective manipulations of highly toxic sediment. The expression-based classifier correctly identified organisms exposed to toxic sediment even when little mortality was observed, suggesting enhanced sensitivity of the TIE process. The ability of the expression-based endpoint to correctly identify toxic sediment was lost concomitantly with acute toxicity when organic contaminants were removed. Taken together, this suggests that gene expression enhances the performance of the TIE process. Wild-collected Ampelisca abdita were exposed to either control (from sites in Long Island Sound, labeled LIS) sediment, toxic (from site on Elizabeth River, labeled ER) sediment, a series of mixtures of LIS and ER sediment, sediments manipulated to alter toxin bioavailability, or toxicant amended sediments. Lethality was scored, and survivors were subjected to mRNA expression analysis via oligo microarray.
2012-12-21 | E-GEOD-41463 | biostudies-arrayexpress