Abstract

Genomic technologies show great potential for classifying disease states and toxicological impacts from exposure to chemicals into functional categories. In environmental monitoring, the ability to classify field samples and predict the pollutants present in these samples could contribute to monitoring efforts and the diagnosis of contaminated sites. Using gene expression analysis, we challenged our custom Daphnia magna cDNA microarray to determine the presence of a specific metal toxicant in blinded field samples collected from two copper mines in California. We compared the gene expression profiles from our field samples to previously established expression profiles for Cu, Cd, and Zn. The expression profiles from the Cu-containing field samples clustered with the laboratory-exposed Cu-specific gene expression profiles and included genes previously identified as copper biomarkers, verifying that gene expression analysis can predict environmental exposure to a specific pollutant. In addition, our study revealed that upstream field samples containing undetectable levels of Cu caused the differential expression of only a few genes, lending support for the concept of a no observed transcriptional effect level (NOTEL). If confirmed by further studies, the NOTEL may play an important role in discriminating polluted and nonpolluted sites in future monitoring efforts.