A Systems Biology Platform for Predictive Ecotoxicology in Daphnia magna

大型溞预测生态毒理学的系统生物学平台

• 批准号: NE/I028246/2
• 负责人: Francesco Falciani
• 金额: $ 68.04万
• 依托单位: University of Liverpool
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2012
• 资助国家: 英国
• 起止时间: 2012 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FI028246%2F2
• 关键词: Systems; Biology; Platform; Predictive; Ecotoxicology

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.

监测环境中是否存在化学污染的不利影响，对于维护生物多样性和环境健康至关重要。这对于各种污染物进入的水环境尤其重要，例如农药流失、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，据环境局估计，多达82%的河流受到硝酸盐和磷等化学物质的威胁。通常，对这些污染物的不利影响只有在其严重到足以影响生物体的生存时才能确定，因此在损害发生后的后期阶段才能确定。已经尝试使用更敏感的早期变化的分子指标(“生物标志物”)，但这些指标通常只提供有关化学物质暴露水平的信息，对毒性的诊断或预测能力有限。因此，分子生物标记物在环境监测中的应用一直非常有限。受生物医学领域最新技术的巨大成功的启发，我们建议开发一种在环境背景下发现生物标记物的等效系统，即开发应用于环境监测和诊断的生物标记物。这些技术可以测量暴露生物中数以千计的生物化学物质(包括基因产品和代谢物)，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产物，这些基因和代谢物可以高度预测对生物的不利影响，同时提供造成这种影响的污染物类别的特征指纹。我们将在水蚤(大型水蚤)中研究这些影响，这种水蚤已经被广泛用于测试受污染的水样的毒性。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很高诊断价值的分子特征，特别是告诉我们关于水蚤的健康和生殖适合性。此外，计算方法将使我们能够发现与水蚤健康有关的分子特征。这是对当前分子生物标记的重大进步。一旦建立了这些可预测不同毒性的分子的特征指纹，我们将测试这些指纹，以预测从受污染的环境中采集的水样的化学成分，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署合作进行。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进行强有力的评估，以(1)确定水的“生态状况”和(2)诊断潜在的污染物类别，从而增强监管机构针对补救措施的能力。在对新的预测生物标志物进行验证后，我们将把它们转换成简单、快速和经济的分析方法，从而提供新一代环境监测工具。项目结束后，通过我们与英国、欧洲和北美的最终用户的合作，我们将寻求在进行常规生物和化学监测的同时试验我们的分子生物标志物，例如，作为水框架指令的一部分。总而言之，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，并有望在可用于监测我们环境健康的工具方面取得重大进展。

项目成果

Modeling the Metabolic Profile of Mytilus Edulis Reveals Molecular Signatures Linked to Gonadal Development, Sex and Environmental Site

贻贝的代谢特征建模揭示了与性腺发育、性别和环境位点相关的分子特征

• DOI: 10.21203/rs.3.rs-150213/v1
• 发表时间: 2021
• 作者: Kronberg J

Chemical hazard prediction and hypothesis testing using quantitative adverse outcome pathways.

使用定量不良结果途径进行化学危害预测和假设检验。

• DOI: 10.14573/altex.1808241
• 发表时间: 2019
• 期刊: ALTEX
• 作者: Perkins EJ

The Role of Omics in the Application of Adverse Outcome Pathways for Chemical Risk Assessment.

• DOI: 10.1093/toxsci/kfx097
• 发表时间: 2017-08-01
• 期刊: Toxicological sciences : an official journal of the Society of Toxicology
• 作者: Brockmeier EK;Hodges G;Hutchinson TH;Butler E;Hecker M;Tollefsen KE;Garcia-Reyero N;Kille P;Becker D;Chipman K;Colbourne J;Collette TW;Cossins A;Cronin M;Graystock P;Gutsell S;Knapen D;Katsiadaki I;Lange A;Marshall S;Owen SF;Perkins EJ;Plaistow S;Schroeder A;Taylor D;Viant M;Ankley G;Falciani F
• 通讯作者: Falciani F

Modeling the metabolic profile of Mytilus edulis reveals molecular signatures linked to gonadal development, sex and environmental site.

• DOI: 10.1038/s41598-021-90494-y
• 发表时间: 2021-06-18
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Kronberg J;Byrne JJ;Jansen J;Antczak P;Hines A;Bignell J;Katsiadaki I;Viant MR;Falciani F
• 通讯作者: Falciani F