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Toxicol Appl Pharmacol. 2007 Dec 1;225(2):171-88. Epub 2007 Aug 29.

Transcriptomics analysis of interactive effects of benzene, trichloroethylene and methyl mercury within binary and ternary mixtures on the liver and kidney following subchronic exposure in the rat.

Author information

1
TNO Quality of Life, Zeist, The Netherlands. phendriksen@tno.nl

Abstract

The present research aimed to study the interaction of three chemicals, methyl mercury, benzene and trichloroethylene, on mRNA expression alterations in rat liver and kidney measured by microarray analysis. These compounds were selected based on presumed different modes of action. The chemicals were administered daily for 14 days at the Lowest-Observed-Adverse-Effect-Level (LOAEL) or at a two- or threefold lower concentration individually or in binary or ternary mixtures. The compounds had strong antagonistic effects on each other's gene expression changes, which included several genes encoding Phase I and II metabolizing enzymes. On the other hand, the mixtures affected the expression of "novel" genes that were not or little affected by the individual compounds. The three compounds exhibited a synergistic interaction on gene expression changes at the LOAEL in the liver and both at the sub-LOAEL and LOAEL in the kidney. Many of the genes induced by mixtures but not by single compounds, such as Id2, Nr2f6, Tnfrsf1a, Ccng1, Mdm2 and Nfkb1 in the liver, are known to affect cellular proliferation, apoptosis and tissue-specific function. This indicates a shift from compound specific response on exposure to individual compounds to a more generic stress response to mixtures. Most of the effects on cell viability as concluded from transcriptomics were not detected by classical toxicological endpoints illustrating the benefit of increased sensitivity of assessing gene expression profiling. These results emphasize the benefit of applying toxicogenomics in mixture interaction studies, which yields biomarkers for joint toxicity and eventually can result in an interaction model for most known toxicants.

PMID:
17905399
DOI:
10.1016/j.taap.2007.08.017
[Indexed for MEDLINE]

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