ToxSci Advance Access published online on July 11, 2006
Toxicological Sciences, doi:10.1093/toxsci/kfl057
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1 Department of Biology, Laboratory for Ecophysiology, Biochemistry and Toxicology, University of Antwerp, B-2020 Antwerp, Belgium
* To whom correspondence should be addressed. Exposure to a variety of anthropogenic compounds has been shown to interfere with normal development, physiology and reproduction in a wide range of organisms, both in laboratory studies and wildlife. We have developed a Cyprinus carpio cDNA microarray consisting of endocrine-related genes. In the current study, we investigated the applicability of this microarray (i) to study the molecular effects induced by exposure to a variety of endocrine disruptive compounds (EDCs) in fish, and (ii) to discriminate the specific transcriptional profiles associated with these compounds. To that purpose, gene expression profiles were generated in livers of juvenile carp exposed to 14 OECD-recommended reference EDCs (17beta-estradiol, 17alpha-ethinylestradiol, 4-nonylphenol, bisphenol-A, tamoxifen, 17alpha-methyltestosterone, 11keto-testosterone, dibutyl phthalate, flutamide, vinclozolin, hydrocortisone, CuCl2, propylthiouracil, and a mixture of L-triiodothyronine & L-Thyroxine). Our results show that, in addition to some expression similarities between analogous acting substances, each individual compound produced its own unique expression pattern on the array, distinct from the profiles generated by the other compounds. In addition, we were able to identify a minimal subset of genes, which also allowed to discriminate between the different compounds. Overall, our findings suggest that the developed cDNA array has great promise to screen new and existing chemicals on their endocrine disruptive potential, and to identify distinct classes of endocrine disruptive compounds.
Received April 25, 2006
Accepted June 29, 2006
Environmental Toxicology
Expression Profiling of Endocrine Disrupting Compounds using a Customized Cyprinus carpio cDNA Microarray
Lotte N. Moens 1 *,
Karlijn van der Ven 1,
Piet Van Remortel 2,
Jurgen Del-Favero 3,
and
Wim M. De Coen 1
2 Department of Mathematics and Computer Science, Intelligent Systems Laboratory, University of Antwerp, B-2020 Antwerp, Belgium
3 Department of Biomedical Sciences, Laboratory for Molecular Genetics, University of Antwerp, B-2610 Antwerp (Wilrijk), Belgium
Lotte N. Moens, E-mail: lotte.moens{at}ua.ac.be
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