ABSTRACT: The recent development of a custom cDNA microarray platform for one of thé standard organisms in aquatic toxicology, Daphnia magna, opened up new ways to mechanistic insights of toxicological responses. In this study, gene expression and (sub)organismal responses (Cellular Energy Allocation, growth) were assayed after short-term waterborne metal exposure. Microarray analysis of Ni-exposed daphnids revealed several affected functional gene classes, of which the largest ones were involved in different metabolic processes (mainly protein and chitin related processes), cuticula turnover, transport and signal transduction. Furthermore, genes involved in oxygen transport and heme metabolism (hemoglobin, δ-aminolevilunate synthase) were down-regulated. Applying a Partial Least Squares regression on nickel fingerprints and biochemical (sub)organismal parameters revealed a set of co-varying genes (hemoglobin, RNA terminal phosphate cyclase, a ribosomal protein and an âunknownâ gene fragment). An inverse relationship was seen between the mRNA expression levels of different cuticula proteins and available energy reserves. In addition to the nickel exposure, daphnids were exposed to binary mixtures of nickel and cadmium or nickel and lead. Using multivariate analysis techniques, the mixture gene expression fingerprints (Ni2++Cd2+, Ni2++Pb2+) were compared to those of the single metal treatments (Ni2+, Cd2+, Pb2+). It was hypothesized that the molecular fingerprints of the mixtures would be additive combinations of the gene expression profiles of the individual compounds present in the mixture. However, our results clearly showed additionally affected pathways after mixture treatment (e.g. additional affected genes involved in carbohydrate catabolic processes and proteolysis), indicating interactive molecular responses which are not merely the additive sum of the individual metals. These findings, although indicative of the complex nature of mixture toxicity evaluation, underline the potential of a toxicogenomics approach in gaining more mechanistic information on the effects of single compounds and mixtures. In general, a universal reference design was used. The following analysis (normalization and statistical analysis) was performed. Spots were identified and ratioâs quantified by means of the Genepix software 5.0 (Axon Instruments). Subsequently, a MIAME compliant platform, the BioArray Software Environment Database (BASE 1.2.12, http://www.islab.ua.ac.be/base/) was used for storage, further evaluation and succeeding statistical analysis of the microarray datasets. After a local background correction, spots with a foreground larger than the mean local background +2 standard deviations for one or both colours were selected for further analysis. The Log2 transformed Cy3/Cy5 ratio data were normalized by implementation of a Locally Weighed Scatterplot Smoothing (Lowess) (Yang et al., 2002) step, which is an intensity-based method. Significant vertical cut-off values of log -0.85 and 0.85 were determined through multiple self-self hybridizations. These were performed by labelling the same biological material with both Cy3 and Cy5 dyes and hybridizing them simultaneously on a microarray slide. To statistically evaluate the microarray results, Significance Analysis of Microarrays (SAM) described by Tusher et al. (2001) was applied on the Lowess normalized datasets. With this SAM approach a false discovery rate (FDR) below 5% was applied. As a result genes with log2 ratios outside the confidence interval of -0.85 and 0.85 were considered as differentially expressed gene fragments when FDR was below 5%.
