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Fishing for contaminants: identification of three mechanism specific transcriptome signatures using Danio rerio embryos
Institute for Environmental Research, RWTH Aachen University, Aachen, Germany.
Institute of Toxicology and Genetics, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany.
Environment and Health, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
Institute of Toxicology and Genetics, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany .
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2018 (English)In: Environmental Science and Pollution Research, ISSN 0944-1344, E-ISSN 1614-7499, Vol. 25, no 5, p. 4023-4036Article in journal (Refereed) Published
Abstract [en]

In ecotoxicology, transcriptomics is an effective way to detect gene expression changes in response to environmental pollutants. Such changes can be used to identify contaminants or contaminant classes and can be applied as early warning signals for pollution. To do so, it is important to distinguish contaminant-specific transcriptomic changes from genetic alterations due to general stress. Here we present a first step in the identification of contaminant class-specific transcriptome signatures. Embryos of zebrafish (Danio rerio) were exposed to three substances (methylmercury, chlorpyrifos and Aroclor 1254, each from 24 to 48 hpf exposed) representing sediment typical contaminant classes. We analyzed the altered transcriptome to detect discriminative genes significantly regulated in reaction to the three applied contaminants. By comparison of the results of the three contaminants, we identified transcriptome signatures and biologically important pathways (using Cytoscape/ClueGO software) that react significantly to the contaminant classes. This approach increases the chance of finding genes that play an important role in contaminant class-specific pathways rather than more general processes.

Place, publisher, year, edition, pages
Springer, 2018. Vol. 25, no 5, p. 4023-4036
Keywords [en]
Transcriptomics; Methylmercury; Aroclor 1254; Chlorpyrifos; Ecotoxicogenomics; Pathway network analysis
National Category
Environmental Sciences
Identifiers
URN: urn:nbn:se:oru:diva-57329DOI: 10.1007/s11356-017-8977-6ISI: 000425770300009PubMedID: 28391457Scopus ID: 2-s2.0-85017145945OAI: oai:DiVA.org:oru-57329DiVA, id: diva2:1103625
Note

Funding Agencies:

DanTox  

German Federal Ministry of Education and Research (BMBF)  02WU1053 

GENDarT2 project (BMBF)  AZ:0315190 B 

Available from: 2017-05-30 Created: 2017-05-30 Last updated: 2020-06-05Bibliographically approved

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Keiter, Steffen

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