A Systems Biology Platform for Predictive Ecotoxicology in Daphnia magna

监测环境中化学污染的不利影响对维持生物多样性和环境健康至关重要。这对水生环境尤其重要，因为水生环境中有各种各样的污染物，例如农药径流、工业泄漏和未经处理的污水排放产生的过量营养物质。污染仍然是英国的一个主要问题，据环境署估计，高达82%的河流受到硝酸盐和磷等化学物质的“威胁”。对这些污染物的不利影响往往只有在它们严重到足以影响生物体的生存时才能查明，从而在造成损害后的后期阶段才能查明。人们曾尝试使用更敏感的早期变化分子指标（“生物标志物”），但这些指标通常只能提供化学物质暴露水平的信息，在毒性方面的诊断或预测能力有限。因此，目前分子生物标志物在环境监测中的应用非常有限。受最近生物医学技术取得巨大成功的启发，我们建议在环境背景下开发一个等效的生物标志物发现系统，即开发用于环境监测和诊断的生物标志物。这些技术可以测量暴露生物体中的数千种生化物质（包括基因产物和代谢物），并通过使用数学和计算工具，我们可以确定潜在的毒性途径。这些计算模型将使我们能够发现一组基因和代谢物，这些基因和代谢物可以高度预测对生物体的不利影响，同时提供造成这种影响的污染物类型的特征指纹。我们将在水蚤（大水蚤）中研究这些影响，水蚤已被广泛用于污染水样的毒性测试。将对代表主要污染物类别的各种化学物质进行评估，并将分子特征与水蚤的生理反应进行比较。这将使我们能够发现在生态环境中具有高诊断价值的分子特征，特别是告诉我们水蚤的健康和生殖适应性。此外，计算方法将使我们能够发现与水蚤健康有因果关系的分子特征。这代表了目前分子生物标志物的重大进步。一旦这些预测不同毒性的分子特征指纹被建立起来，我们将测试这些指纹，以预测从污染环境中提取的水样的化学组成，并证明对环境有影响。这种抽样将与我们的项目合作伙伴环境局合作。我们将对这些样本的性质“视而不见”，从而能够对我们的能力(1)确定水的“生态状况”和(2)诊断潜在的污染物类别进行强有力的评估，从而提高监管机构制定针对性补救措施的能力。随着新的预测性生物标志物的验证，我们将把它们转化为简单、快速和经济的分析，从而提供新一代的环境监测工具。项目结束后，通过我们与英国、欧洲和北美最终用户的合作，我们将寻求将我们的分子生物标志物与传统的生物和化学监测一起进行试点，例如作为水框架指令的一部分。总之，这个令人兴奋的项目是跨学科的，涉及基础生物化学和生理学，毒理学，分子生物学和生物信息学，并承诺在监测我们环境健康的可用工具方面取得重大进展。

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.