Title
An integrated transcriptomic and proteomic approach characterizing estrogenic and metabolic effects of 17 <tex>$\alpha$</tex>-ethinylestradiol in zebrafish (**Danio rerio**) An integrated transcriptomic and proteomic approach characterizing estrogenic and metabolic effects of 17 <tex>$\alpha$</tex>-ethinylestradiol in zebrafish (**Danio rerio**)
Author
Faculty/Department
Faculty of Sciences. Biology
Publication type
article
Publication
New York ,
Subject
Biology
Source (journal)
General and comparative endocrinology. - New York
Volume/pages
167(2010) :2 , p. 190-201
ISSN
0016-6480
ISI
000278172500002
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Nowadays there is much concern about the presence of endocrine disrupting compounds (EDCs) in the environment due to their ability to interfere with the endocrine system. In the presented study, adult zebrafish (Danio rerio) were exposed to 30 ng L−1 17α-ethinylestradiol (EE2) for 4 and 28 days. The underlying molecular mechanisms of EE2 were studied in the zebrafish liver by applying a combined transcriptomics and proteomics approach. In addition, we assessed the added value of such an integratedomics approach. Oligo microarrays, spotted with 3479 zebrafish-specific oligos, were employed to generate differential gene expression levels. The proteomic responses were evaluated by means of differential in-gel electrophoresis (DiGE), combined with MALDI-tandem mass spectrometry. Assessment of the major biological functions of the differentially expressed transcripts and proteins illustrated that both individual platforms could profile a clear estrogenic interference, next to numerous metabolism-related effects and stress responses. Cross-comparison of both transcriptomics and proteomics datasets displayed limited concordance, though, thorough revision of the results illustrated that transcriptional effects were projected on protein level as downstream effects of affected signalling pathways. Overall, this study demonstrated that a proteomics approach can lift the biological interpretation of microarrays to a higher level, and moreover, opens a window for identification of possible new biomarkers.
E-info
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000278172500002&DestLinkType=RelatedRecords&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000278172500002&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000278172500002&DestLinkType=CitingArticles&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848
Handle