Environment Department, University of York, Heslington, York YO10 5NG, UK.
Environ Sci Process Impacts. 2018 Jan 24;20(1):48-57. doi: 10.1039/c7em00328e.
As ecotoxicologists we strive for a better understanding of how chemicals affect our environment. Humanity needs tools to identify those combinations of man-made chemicals and organisms most likely to cause problems. In other words: which of the millions of species are at risk from pollution? And which of the tens of thousands of chemicals contribute most to the risk? We identified our poor knowledge on physiological modes of action (how a chemical affects the energy allocation in an organism), and how they vary across species and toxicants, as a major knowledge gap. We also find that the key to predictive ecotoxicology is the systematic, rigorous characterization of physiological modes of action because that will enable more powerful in vitro to in vivo toxicity extrapolation and in silico ecotoxicology. In the near future, we expect a step change in our ability to study physiological modes of action by improved, and partially automated, experimental methods. Once we have populated the matrix of species and toxicants with sufficient physiological mode of action data we can look for patterns, and from those patterns infer general rules, theory and models.
作为生态毒理学家,我们努力深入了解化学物质对环境的影响。人类需要工具来识别那些最有可能引起问题的人造化学物质和生物的组合。换句话说:数百万个物种中有哪些受到污染的威胁?成千上万的化学物质中有哪些对风险的贡献最大?我们认识到,我们对生理作用模式(化学物质如何影响生物体的能量分配)以及它们在物种和毒物之间的差异了解甚少,这是一个主要的知识空白。我们还发现,预测生态毒理学的关键是对生理作用模式进行系统、严格的特征描述,因为这将使体外到体内毒性推断和计算生态毒理学更加强大。在不久的将来,我们期望通过改进和部分自动化的实验方法,在研究生理作用模式方面取得重大进展。一旦我们用足够的生理作用模式数据填充了物种和毒物矩阵,我们就可以寻找模式,并从这些模式中推断出一般规则、理论和模型。