Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR26415406_1.fastq.gz | Fastqsanger.gz | |||
| SRR26415406_2.fastq.gz | Fastqsanger.gz | |||
| SRR26415407_1.fastq.gz | Fastqsanger.gz | |||
| SRR26415407_2.fastq.gz | Fastqsanger.gz | |||
| SRR26415408_1.fastq.gz | Fastqsanger.gz |
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Similar Datasets
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:Analysis of microbial gene expression in response to physical and chemical gradients forming in the Columbia River, estuary, plume and coastal ocean was done in the context of the environmental data base. Gene expression was analyzed for 2,234 individual genes that were selected from fully sequenced genomes of 246 prokaryotic species (bacteria and archaea) as related to the nitrogen metabolism and carbon fixation. Seasonal molecular portraits of differential gene expression in prokaryotic communities during river-to-ocean transition were created using freshwater baseline samples (268, 270, 347, 002, 006, 207, 212).
2010-09-10 | GSE18303 | GEO
Project description:Analysis of microbial gene expression in response to physical and chemical gradients forming in the Columbia River, estuary, plume and coastal ocean was done in the context of the environmental data base. Gene expression was analyzed for 2,234 individual genes that were selected from fully sequenced genomes of 246 prokaryotic species (bacteria and archaea) as related to the nitrogen metabolism and carbon fixation. Seasonal molecular portraits of differential gene expression in prokaryotic communities during river-to-ocean transition were created using freshwater baseline samples (268, 270, 347, 002, 006, 207, 212). Total RNA was isolated from 64 filtered environmental water samples collected in the Columbia River coastal margin during 4 research cruises (14 from August, 2007; 17 from November, 2007; 18 from April, 2008; and 16 from June, 2008), and analyzed using microarray hybridization with the CombiMatrix 4X2K format. Microarray targets were prepared by reverse transcription of total RNA into fluorescently labeled cDNA. All samples were hybridized in duplicate, except samples 212 and 310 (hybridized in triplicate) and samples 336, 339, 50, 152, 157, and 199 (hybridized once). Sample location codes: number shows distance from the coast in km; CR, Columbia River transect in the plume and coastal ocean; NH, Newport Hydroline transect in the coastal ocean at Newport, Oregon; AST and HAM, Columbia River estuary locations near Astoria (river mile 7-9) and Hammond (river mile 5), respectively; TID, Columbia River estuary locations in the tidal basin (river mile 22-23); BA, river location at Beaver Army Dock (river mile 53) near Quincy, Oregon; UP, river location at mile 74.
2010-09-10 | E-GEOD-18303 | biostudies-arrayexpress
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 copper redhorse (Moxostoma hubbsi) is an endangered fish endemic to Quebec, Canada that is only known to spawn in two locations within the Richelieu River, a waterway draining a significant area of agricultural land. Accordingly, concerns have been raised over the impacts that agricultural pesticide contamination of spawning grounds and nursery habitats within the Richelieu River may have on early life stage copper redhorse. We assessed the effects of contaminants on early life stages of copper redhorse and river redhorse (Moxostoma carinatum), a closely related fish that shares the copper redhorse’s habitat and spawning grounds but is distributed more widely and is not yet listed as endangered. Copper and river redhorse embryos (1000 each) were exposed to either Richelieu River water in an in-situ flow-through system or to laboratory water used as a control. We assessed embryos hatching time, incidence of deformities and survival in copper and river redhorses. We then performed RNA sequencing on copper redhorse larvae to better understand changes due to river water exposure. We identified 341 compounds in the river water that were absent from lab water. Pesticide concentrations in the river peaked following rainfall during the spawning season. Embryos exposed to river water hatched prematurely at 63.0 and 59.2 cumulative degree days (CDD) compared to 65.4 and 69.9 CDD in laboratory water for river and copper redhorse, respectively. Copper redhorse exposed to river water also had a significantly lower survival rate than laboratory water (73% vs. 93%). RNA sequencing of copper redhorse revealed 18 differentially expressed genes (DEGs) following river water exposure. Eight of the upregulated DEGs (cd44, il1b, lamb3, lamc2, tgm5, orm1, saa, acod1) are linked to immune function and injury response and 7 of the downregulated DEGs (cpa2, ctrb, cela2a, ctrl, cpa1, prss1, cel) are involved with digestion and nutrient absorption. This study provided valuable data on the effects of anthropogenic contaminants present in the Richelieu River and increased our knowledge on the individual and mixture effects they have on an endangered fish.
2022-06-01 | GSE185175 | GEO
Project description:We have developed a 60-mer oligonucleotide multibacterial microarray for detection and expression profiling of biodegradative genes and bacterial diversity (16S rRNA gene) in different habitats contaminated with varieties of hazardous chemicals. The genes selected were involved in biodegradation and biotransformation of various groups of compounds viz. nitroaromatic compounds (148 genes), chloroaromatic compounds (75 genes), monoaromatic compounds (373 genes), polyaromatic hydrocarbons (174 genes), pesticides/ herbicides (34 genes), alkanes/aliphatics (185 genes) and heavy metals (68 genes), which covered a total number of 133 chemicals. The efficiency (specificity, detection sensitivity) of the developed array was evaluated using the labeled genomic DNA of pure bacterial strains, Escherichia coli DH5α and Sphingomonas sp. strain NM-05 (involved in the biodegradation of γ-hexachlorohexane isolated from IPL, Lucknow) at different concentrations of 300ng, 500ng, 800ng, 1000ng and 1250ng. The specificity of the developed array was further validated using mixed cultures containing three strains (Sphingomonas sp. strain NM-05, Rhodococcus sp. strain RHA1 and Bordetella sp. strain IITR-02) involved in biodegradation of γ-hexachlorohexane, biphenyl and chlorobenzenes respectively. The mixed culture also contained non-target/non-degrader strains (E. coli DHα, E.coli BL21 and E.coli K12 NCTC50192). The developed array was applied for profiling using the total soil DNA in five contaminated habitats of north India, viz. chloroaromatic chemicals contaminated site (India Pesticide Limited, Chinhat, Lucknow), a river sediments (Gomti river sediment, Lucknow), heavy metal industry dump site (Jajmau industrial area Kanpur), a effluent treatment plant (CETP along Ganges river near Kanpur), and an oil refinery (Mathura oil refinery). Hybridization of 16S rRNA probes revealed the presence of bacteria similar to well characterized genera involved in biodegradation of pollutants. Genes involved in complete degradation pathways for hexachlorocyclohexane (lin), 1,2,4-trichlorobenzene (tcb), naphthalene (nah), phenol (mph), biphenyl (bph), benzene (ben), toluene (tbm), xylene (xyl), phthalate (pht), Salicylate (sal) and resistance to mercury (mer) were detected with highest intensity. The most abundant genes belonged to hydroxylases, monooxygenases and dehydrogenases which were present in all the five samples. Many compound specific genes which initiate the degradation pathway were also detected. Thus, the array developed and validated here may be useful in assessing the biodegradative potential and composition of environmentally useful bacteria in hazardous ecosystems.
2011-04-15 | GSE24353 | GEO