The key problem faced by environmental scientists is to predictand recognize the damaging effects of chemical pollutants on natural biota. The aim of this thesis was to evaluate the potential for proteomics in ecotoxicology and environmental risk assessment (ERA), with the hypothesis that proteomic technologies (i.e. ProteinChip technology in combination with SELDI TOF MS) could be a useftil supplement to existing methods of environmental assessment, by providing a sensitive, non-invasive, rapid multi-endpoint assessment of effects of anthropogenic chemicals on organism in vivo. Three invertebrate species, Mytilus edulis, Hyas araneus and Strongylocentrotus droebachiensis was exposed to natural and anthropogenic chemicals in laboratory and field studies. Results revealed that proteomics was a sensitive endpoint, as all exposure regimes significantly affected protein expression. It was shown that plasma protein expression profiles contained information that was compound, dose, site, species and gender-specific. Regarding the latter; male and female organisms responded differently to all exposures both quantitatively (e.g. in terms of number of affected protein species) and qualitatively (e.g. in terms of tj^e of affected protein species). Furthermore, genders have shown opposite responses following the same exposure regime. Equally, species-specific responses were observed. Moreover, exposing organisms to graded levels of contamination under controlled laboratory conditions and in the field revealed that different subsets of proteomes were affected at different levels of exposure. This finding represents an opportunity for appljdng proteomics for both prognostic (e.g. early warning of potential adverse effects or assessment of recovery) and diagnostic purposes. Moreover, those protein features that were changed by all exposure concentrations showed complex dose-response relationships, including both linear and various types of biphasic response-curves. In summary, results from the present study indicate that proteomics have the potential to be a useftil tool in ERA. For example, identification of key molecules could elucidate mechanism of action related to mixture effects, gender and species-specific susceptibility to environmental pollutants as well as dose-response relationships at low doses. Furthermore, key proteins (i.e. putative biomarkers) could, be purified and coupled to e.g. a biosensor for automated monitoring.

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