iNVERTOX: Rapid intelligent in silico prediction of sub-lethal ecotoxicological effects in invertebrates following pharmaceutical exposure

iNVERTOX：快速智能计算机预测药物暴露后无脊椎动物的亚致死生态毒理学效应

• 批准号: BB/P005187/1
• 负责人: Leon Barron
• 金额: $ 68.93万
• 依托单位: King's College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FP005187%2F1
• 关键词: iNVERTOX; Rapid; intelligent; silico; prediction

The iNVERTOX project will be the first of its kind to discover and predict both phenotypic and molecular level effects of trace pharmaceutical residues on small, but ecologically critical invertebrate organisms living in UK and international freshwaters which are now impacted by human activity. Pharmaceuticals are widely recognised as bioactive contaminants in our environment having been measured globally at very low concentrations. They enter the environment predominantly following excretion of consumed human and animal medicines and have been shown to be resistant to wastewater treatment. This leads to their consistent and prolonged infusion into receiving water catchments. Recently, three pharmaceuticals were placed on a "watch-list" of emerging priority pollutants following extensive studies of their toxicity to biota. However, the occurrence and diversity of pharmaceuticals contamination in the environment extends much further, with significantly more compounds detected in river water, sediments, soils and recently even in environmental species at any one time. Therefore given the scale of this problem, measurement of their effects on our environment is far too slow and laborious. More innovative and rapid approaches are required to understand and mitigate any effects these may have on our environment. Realistically, this must now involve some form of advanced computational modelling to use the limited information we have to predict the effects of additional pharmaceuticals. Moreover, traditional ecotoxicity testing for micro-pollutants use lethal doses and in the case of pharmaceuticals, these are often much higher than measured environmental concentrations. This suggests that more subtle effects need to be researched instead as a more accurate assessment of risk. In some cases, such small changes have resulted in a significant ecosystem imbalance which has indirect effects on wildlife, our environment and potentially also on human health. These so called, "sub-lethal phenotypic effects" are often more difficult to determine and establishing defined links to a pharmaceutical exposure is extremely challenging. The aim of this project is to study and model four sub-lethal phenotypic effects on a model freshwater benthic invertebrate species (Gammarus pulex) including growth rate, feeding rate, ventilation and locomotion following controlled exposure to low doses of over 60 pharmaceuticals typically found in the aquatic environment. In addition to this, changes in the organism at a molecular level will form a novel, central focus and enable knowledge discovery of how biota respond to such exposures at a fundamental level. This will be achieved via metabolomics, which is the measurement of thousands of small molecules present in a biological system following exposure to environmental contaminants. Lastly, and most importantly, this information will be used to build an set of advanced computational models using new machine learning tools to rapidly allow a user to screen potential phenotypic and molecular level effects of a pharmaceutical on biota in silico and minimise or remove the need for extended use of animals in ecotoxicity testing for this purpose. This project will therefore be pioneering in its approach and draw together the best academic and industry expertise from King's College London, The Francis Crick Institute, London and a global leader in pharmaceuticals, AstraZeneca, to rapidly and responsibly understand the effects of pharmaceuticals on environmental organisms.

iNVERTOX项目将是第一个发现和预测痕量药物残留对生活在英国和国际淡水中的小型但生态关键的无脊椎生物的表型和分子水平影响的项目，这些生物现在受到人类活动的影响。药物被广泛认为是我们环境中的生物活性污染物，在全球范围内以非常低的浓度进行测量。它们主要在人类和动物消耗的药物排泄后进入环境，并已被证明对废水处理具有抗性。这导致它们持续和长期地注入接受水的集水区。最近，在广泛研究了三种药物对生物群的毒性后，将其列入了新出现的优先污染物“观察名单”。然而，环境中药物污染的发生和多样性进一步扩大，在河水，沉积物，土壤中检测到的化合物明显更多，最近甚至在任何一个时间的环境物种中。因此，考虑到这个问题的规模，衡量它们对我们环境的影响太慢太费力了。需要采取更创新和更迅速的方法来了解和减轻这些可能对我们的环境产生的任何影响。现实地说，这现在必须涉及某种形式的先进计算建模，以使用我们所拥有的有限信息来预测其他药物的影响。此外，传统的微污染物生态毒性测试使用致命剂量，而在药品方面，这些剂量往往远远高于测量的环境浓度。这表明需要研究更微妙的影响，而不是更准确的风险评估。在某些情况下，这种微小的变化导致了严重的生态系统失衡，对野生动物、我们的环境以及潜在的人类健康产生了间接影响。这些所谓的“亚致死表型效应”通常更难以确定，并且建立与药物暴露的明确联系极具挑战性。该项目的目的是研究和模拟对淡水底栖无脊椎动物物种（钩虾）的四种亚致死表型效应，包括生长率、摄食率、通风和运动，这些表型效应是在受控暴露于低剂量的60多种通常在水生环境中发现的药物后产生的。除此之外，生物体在分子水平上的变化将形成一个新的中心焦点，并使生物群如何在基本水平上对这种暴露作出反应的知识发现成为可能。这将通过代谢组学来实现，代谢组学是在暴露于环境污染物后测量生物系统中存在的数千个小分子。最后，也是最重要的是，这些信息将用于使用新的机器学习工具建立一套先进的计算模型，以快速允许用户通过计算机筛选药物对生物群的潜在表型和分子水平影响，并最大限度地减少或消除为此目的在生态毒性测试中延长动物使用的需要。因此，该项目将在其方法上具有开创性，并汇集了伦敦国王学院、伦敦弗朗西斯克里克研究所和全球制药业领导者阿斯利康的最佳学术和行业专业知识，以快速、负责任地了解药物对环境生物的影响。

项目成果

Machine Learning for Environmental Toxicology: A Call for Integration and Innovation.

• DOI: 10.1021/acs.est.8b05382
• 发表时间: 2018-10
• 期刊: Environmental science & technology
• 影响因子: 11.4
• 作者: T. Miller;M. Gallidabino;J. MacRae;C. Hogstrand;N. Bury;L. Barron;J. Snape;S. Owen

A review of the pharmaceutical exposome in aquatic fauna.

• DOI: 10.1016/j.envpol.2018.04.012
• 发表时间: 2018-08
• 期刊: Environmental pollution (Barking, Essex : 1987)
• 作者: Miller TH;Bury NR;Owen SF;MacRae JI;Barron LP
• 通讯作者: Barron LP