Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

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

ABSTRACT: 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.

ORGANISM(S): Daphnia magna

SUBMITTER: Philipp Antczak

PROVIDER: E-GEOD-43564 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:Nanowires (NWs), high-aspect-ratio nanomaterials, are increasingly used in technological materials and consumer products and may have toxicological characteristics distinct from nanoparticles. We carried out a comprehensive evaluation of the physicochemical stability of four silver nanowires (AgNWs) of two sizes and coatings and their toxicity to Daphnia magna. Inorganic aluminum-doped silica coatings were less effective than organic poly(vinyl pyrrolidone) coatings at preventing silver oxidation or Ag+ release and underwent a significant morphological transformation within 1 h following addition to low ionic strength Daphnia growth media. All AgNWs were highly toxic to D. magna but less toxic than ionic silver. Toxicity varied as a function of AgNW dimension, coating, and solution chemistry. Ag+ release in the media could not account for observed AgNW toxicity. Single-particle inductively coupled plasma mass spectrometry distinguished and quantified dissolved and nanoparticulate silver in microliter-scale volumes of Daphnia magna hemolymph with a limit of detection of approximately 10 ppb. The silver levels within the hemolymph of Daphnia exposed to both Ag+ and AgNW met or exceeded the initial concentration in the growth medium, indicating effective accumulation during filter feeding. Silver-rich particles were the predominant form of silver in hemolymph following exposure to both AgNWs and Ag+. Scanning electron microscopy imaging of dried hemolymph found both AgNWs and silver precipitates that were not present in the AgNW stock or the growth medium. Both organic and inorganic coatings on the AgNW were transformed during ingestion or absorption. Pathway, gene ontology, and clustering analyses of gene expression response indicated effects of AgNWs distinct from ionic silver on Daphnia magna. Four replicates each of five toxicant exposure groups of ~20 animals and four replicates of control, unexposed animals. Each control was compared to each exposed data set for a total of 16 comparisons per chemical condition.

Dataset Information

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets