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RNA expression in the early characterization of hepatotoxicants in Wistar rats by high‐density DNA microarrays
Author(s) -
Bulera Steven J.,
Eddy Susan M.,
Ferguson Erika,
Jatkoe Timothy A.,
Reindel James F.,
Bleavins Michael R.,
De La Iglesia Felix A.
Publication year - 2001
Publication title -
hepatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.488
H-Index - 361
eISSN - 1527-3350
pISSN - 0270-9139
DOI - 10.1053/jhep.2001.23560
Subject(s) - dna microarray , gene expression , biology , gene expression profiling , microbiology and biotechnology , gene , in situ hybridization , microarray , microarray analysis techniques , biochemistry
High‐density microarrays are useful tools to study gene expression for the purpose of characterizing functional tissue changes in response to the action of drugs and chemicals. To test whether high‐density expression data can identify mechanisms of toxicity and to identify an unknown sample through its RNA expression pattern, groups of male Wistar rats were administered 6 hepatotoxicants. The compounds chosen for this study were microcystin‐LR (MLR), phenobarbital (PB), lipopolysaccharide (LPS), carbon tetrachloride (CT), thioacetamide (THA), and cyproterone acetate (CPA). These hepatotoxicants are known to induce adverse liver effects through different mechanisms. Liver mRNA was isolated and used to generate biotinylated cRNA for hybridization to a custom 1,600–rat gene DNA microarray. Treatment correlation matrices analyzed hybridization data from a hepatotoxicant‐blinded sample, with gene expression coefficients (GEC) evaluated by means of hierarchical cluster analysis and visual representation as dendrograms. The experimental liver toxicity from the different treatments was confirmed by means of concurrent histopathology, liver enzymes, and bilirubin assays. This toxico genomic analysis identified multiple genes and groups of genes that were affected by the hepatotoxicants on study, indicating that high‐density microarray expression data are useful to identify groups of genes involved in toxicity. In addition, the mRNA expression profile of an unidentified sample can be accurately identified when compared with the expression profiles resident in the data set. This study supports the use of gene expression–profiling technology to determine or to predict toxic liver effects. (H EPATOLOGY 2001;33:1239‐1258.)