A Systems Biology Platform for Predictive Ecotoxicology in Daphnia magna

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The monitoring of the environment for adverse effects of chemical pollution is of paramount importance in maintaining biodiversity and environmental health. This is particularly important for the aquatic environment into which a wide range of pollutants find their way, for example from pesticide run-off, industrial spills and excess nutrients from the release of untreated sewage. Pollution remains a major problem in the UK, with the Environment Agency estimating that up to 82% of rivers are 'at risk' from chemicals such as nitrate and phosphorus. Often adverse impacts to these pollutants can only be identified when they are sufficiently severe so as to affect survival of organisms and thus are identifiable at a late stage, after the damage is done. Attempts have been made to use more sensitive molecular indicators of early change ("biomarkers") but these generally inform only on the levels of chemical exposure and have limited diagnostic or predictive power in relation to toxicity. Therefore the application of molecular biomarkers to environmental monitoring has been very limited to date.Inspired by the tremendous success of recent technologies in biomedicine, we propose to develop an equivalent system for biomarker discovery in an environmental context, i.e., to develop biomarkers for application to environmental monitoring and diagnostics. These technologies can measure many thousands of biochemicals (including gene products and metabolites) in exposed organisms and by using mathematical and computational tools we can identify the underlying pathways to toxicity. These computational models will enable us to discover a set of genes and metabolites that can be highly predictive of an adverse impact on living organisms and at the same time provide a characteristic fingerprint of the type of pollutant class(es) responsible for such impact. We will study these effects in the water flea (Daphnia magna) which is already commonly used in the testing of contaminated water samples for toxicity. A wide range of chemicals representing major pollutant classes will be assessed and the molecular signatures will be compared to physiological responses in the water fleas. This will allow us to discover molecular signatures that have high diagnostic value in an ecological context, specifically telling us about the health and reproductive fitness of the water fleas. Also, the computational methods will allow us to discover molecular signatures that causally relate to the water fleas' health. This represents a major advance over current molecular biomarkers.Once these characteristic fingerprints of molecules that are predictive of different toxicities are established, we will test such fingerprints to be predictive of the chemical makeup of water samples taken from polluted environments and with proven environmental impact. Such sampling will be in collaboration with our project partner, the Environment Agency. We will be "blinded" to the nature of these samples, enabling a robust evaluation of our ability to (1) determine the "ecological status" of the water and (2) diagnose the underlying pollutant class, thus enhancing the regulators' ability to target remedial measures. Following this validation of the new predictive biomarkers we will convert them into simple, rapid and economic assays, resulting in the provision of a new generation of environmental monitoring tools. After the project, and through our collaborations with end-users in the UK, Europe and North America, we will seek to pilot our molecular biomarkers alongside conventional biological and chemical monitoring, e.g. as part of the Water Framework Directive. In summary, this exciting project is interdisciplinary, involving fundamental biochemistry and physiology, toxicology, molecular biology and bioinformatics, and promises a significant advance in the tools available to monitor the health of our environment.