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Session I: Stress Biology and Genotoxicity

Toxic chemicals in the environment evoke multiple defensive stress responses in all living organisms. These include protein/DNA repair, xenobiotic metabolism, and coping with heavy metals and reactive oxygen species (ROS). The pathways involved, though not the individual gene-family members, are all highly conserved. The effects of single toxicants on these processes are well understood, but pollution usually involves toxicant mixtures, which may have additive, antagonistic or synergistic effects. Stress-response pathways are regulated co-ordinately, as well as individually, so, in principle, mixture toxicity could be predicted by using dynamic mathematical models informed by knowledge of the underlying gene circuitry and how key pathways respond to single toxicants. Our UK–India Education and Research Initiative (UK–IERI) project starts down this road, by combining the efforts of molecular toxicologists, mathematical modellers and bioinformaticians, and working with two invertebrate models: Caenor habditis elegans and Drosophila melanogaster. Our experimental work involves the use of green-fluorescent protein (GFP) reporter genes in C. elegans to provide a rapid read-out of expression levels for key output genes involved in major stress-response pathways. A more-complete picture is obtainable by using gene arrays, but, as shown for dichlorvos, such data are expensive and unwieldy. By focusing on a few known toxicant-inducible stress genes, we can generate a simplified, but sketchy, overview of a toxicant’s acute effects. We present data on how single and mixed metals affect stress-reporter gene expression in transgenic worms. For two-component mixtures, modelling predicts additive effects on metallothionein gene expression for similar divalent metal ions, but interference for dissimilar ions (trivalent plus divalent); this is fully confirmed by subsequent experimental work. For more-complex metal mixtures, both additive and interference effects are seen, or the predominant toxic species may overwhelm other contributions. Our modelling approach can usefully predict important aspects of mixture toxicity, at least for metals.