Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Organismal sensitivity to environmental agents induced toxicity: A comparative ecotoxicogenomics approach

ABSTRACT: Organismal sensitivity to environmental agents induced toxicity: A comparative ecotoxicogenomics approach

PROVIDER: PRJNA384181 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Organismal sensitivity to environmental agents induced toxicity: A comparative ecotoxicogenomics approach [Drosophila]

Project description:To understand the role of genetic makeup in organismal tolerance/susceptibility we compared the Caenorhabditis elegans transcriptome profiles with those of Drosophila melanogaster. In this study, we exposed both organisms, to a synthetic chemical and evaluated their response at the transcriptome level, to gain insights to molecular players/pathways underlying organismal tolerance/susceptibility to xenobiotics

2018-12-01 | GSE98164 | GEO

Organismal sensitivity to environmental agents induced toxicity: A comparative ecotoxicogenomics approach [Caenorhabditis elegans]

2018-12-01 | GSE98165 | GEO

Organismal sensitivity to environmental agents induced toxicity: A comparative ecotoxicogenomics approach

Project description:This SuperSeries is composed of the SubSeries listed below.

2018-12-01 | GSE98166 | GEO

Drosophila melanogaster

Project description:Organismal sensitivity to environmental agents induced toxicity: A comparative ecotoxicogenomics approach [Drosophila]

| PRJNA384195 | ENA

Caenorhabditis elegans

Project description:Organismal sensitivity to environmental agents induced toxicity: A comparative ecotoxicogenomics approach [Caenorhabditis elegans]

| PRJNA384194 | ENA

organismal metagenomes

Project description:organismal metagenomes Raw sequence reads

| PRJNA473282 | ENA

Transcription profiling of rat intestinal epithelial IEC-6 cells treated with non-steroidal anti-inflammatory agents to investigate gastrointestinal toxicity of NSAIDs

Project description:Non-steroidal anti-inflammatory drugs (NSAIDs) are used extensively as therapeutic agents, despite their well-documented gastrointestinal (GI) toxicity. Presently, the mechanisms responsible for NSAID-associated GI damage are incompletely understood. In this study, we used Microarray analysis to generate a novel hypothesis about cellular mechanisms that underlie the GI toxicity of NSAIDs. Monolayers of intestinal epithelial; cells (IEC-6) were treated with NSAIDs that either exhibit indomethacin, NS-398) or lack (SC-560) inhibitory effects on intestinal epithelial cell migration. Bioinformatic analysis of array data suggested that NSAIDs with adverse GI effects either decrease the gene expression of the calpains or increase the gene expression of the calpain engodenous; inhibitor, calpastatin. Calpains have been shown previously to modulate the migration of a variety of cells in different physiological contexts. Our experimental results suggest that the altered expression of calpain genes may contribute to the adverse effects of NSAIDs on intestinal; epithelial restitution. Microarray analysis has generated the novel hypothesis that the GI toxicity of NSAIDs may be attributed in part to drug-induced changes in the expression and activity of calpains. Experiment Overall Design: Monolayers of intestinal epithelial cells (IEC-6) were treated with NSAIDs that either exhibit (indomethacin, NS-398) or lack (SC-560) inhibitory effects on intestinal epithelial cell migration. Samples were then pooled to obtain sufficient material for gene array analysis. The pooled samples were used to hybridize 4 gene array chips for each biological sample.

2009-03-27 | E-GEOD-7584 | biostudies-arrayexpress

Thrombopoietic Agents: Novel Osteoinductive Agents for Bone Healing

Project description:Thrombopoietic Agents: Novel Osteoinductive Agents for Bone Healing

| PRJNA627964 | ENA

Daphnia magna DNA microarray for the evaluation of toxicity of environmental chemicals

Project description:Toxic chemical contaminants have variety of detrimental effects on various species and the impact of pollutants on ecosystems has become an urgent issue. However, very limited species have been examined to date and those studies are mainly limited to vertebrates. In this study, we aimed to establish an ecotoxicogenomic bases for Daphnia magna. Based on a daphnia EST database, we made oligonucleotide-based DNA microarray that has high reproducibility. The DNA microarray was applied to evaluate gene expression profiles of daphnid exposed to chemicals. Characteristic gene expression patterns depending on chemicals indicate that the Daphnia microarray can be used for mechanistic understanding of chemical toxicity. Although acute toxicity test or reproductive toxicity test can provide hazardous concentrations of chemicals, they give no information about mode of action. Our study can be a breakthrough for the evaluation of chemical toxicity on environmental organisms. Keywords: Chemical response

2005-12-31 | GSE3445 | GEO

The Molecular Toxicity Identification Evaluation (mTIE) Approach Predicts Chemical Exposure in Daphnia magna

Project description:Daphnia magna is a bio-indicator organism accepted by several international water quality regulatory agencies. Current approaches for assessment of water quality rely on acute and chronic toxicity that provide no insight into the cause of toxicity. Recently, molecular approaches, such as genome wide gene expression responses, are enabling an alternative mechanism based approach to toxicity assessment. While these genomic methods are providing important mechanistic insight into toxicity, statistically robust prediction systems that allow the identification of chemical contaminants from the molecular response to exposure are needed. Here we apply advanced machine learning approaches to develop predictive models of contaminant exposure using a D. magna gene expression dataset for 36 chemical exposures. We demonstrate here that we can discriminate between chemicals belonging to different chemical classes including endocrine disruptors, metals and industrial chemicals based on gene expression. We also show that predictive models based on indices of whole pathway transcriptional activity can achieve comparable results while facilitating biological interpretability. D. magna were exposed to 36 Chemicals and 5 control series in quadruplicate.

2013-01-17 | E-GEOD-43564 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data