Hensen Birte, Olsson Oliver, Kümmerer Klaus
Institute of Sustainable and Environmental Chemistry, Leuphana University of Lüneburg, Universitätsallee 1, 21335 Lüneburg, Germany.
Institute of Sustainable and Environmental Chemistry, Leuphana University of Lüneburg, Universitätsallee 1, 21335 Lüneburg, Germany.
Environ Int. 2020 Apr;137:105533. doi: 10.1016/j.envint.2020.105533. Epub 2020 Feb 26.
In order to conduct a fast and comprehensive toxicity screening of pesticide transformation products (TPs), this study used a tiered approach by a combination of in silico and experimental methods to determine the probability to be of relevance for risk assessment. The six pesticides Boscalid, Penconazole, Diuron, Terbutryn, Octhilinone (OIT), and Mecoprop were used as model compounds. Identification of corresponding environmental known and unknown TPs were done by literature analysis and photolysis experiments in combination. Aquatic solutions of the pesticides were photolysed to generate TPs which can be expected in the aquatic environment. The resulting mixtures were screened for TPs by high resolution LC-MS/MS. The herein developed approach was conducted at three different tiers: Literature review and in silico methods were used to predict exemplary the environmental bacterial toxicity and the genotoxicity of every single TP at tier I. In case of indications to be toxic, experiments at tier II were applied. Hereby, the photolytic mixtures containing parent compound and TPs were used for the consecutive toxicity test. Microtox assay for the parent compounds and the photolytic mixture was conducted to determine the acute and chronic toxicity and the growth inhibition of V. fischeri. Umu-tests were conducted to determine primary DNA damage. At tier III, single substance standards were used to conduct toxicity tests in case of toxic indication by previous tiers and availability of analytical standard. Identification of TPs revealed 45 known environmental TPs that originated from the six pesticides. The number of substances that need to be assessed was therefore more than sevenfold. By the tiered approach, it was possible to assess toxicological effects on environmental bacteria of 94% of the selected TPs. For 20% we found strong evidence to be toxic to environmental bacteria, as they were assessed at least at two tiers. For further 44% of the TPs we found slight evidence, as they could be assessed at one tier. Contrary, this approach turned out to be unsuitable to assess genotoxic effects of TPs neither by in silico tools nor by experiments. The number of substances that could probably pose a risk onto environment was quadrupled in comparison to the consideration of solely the parent compounds. Thus, this study demonstrates that the conducted screening approach allows for easy and fast identification of environmental relevant TPs. However, the study presented was a very first screening. Its applicability domain needs to be assessed further. For this purpose as a very next step the approach suggested here should be verified by applying additional endpoints and including additional parent compounds.
为了对农药转化产物(TPs)进行快速且全面的毒性筛选,本研究采用了一种分层方法,结合计算机模拟和实验方法来确定其与风险评估相关的可能性。选用了六种农药:啶酰菌胺、戊唑醇、敌草隆、特丁津、氯苯醚菊酯(OIT)和2-甲-4-氯丙酸作为模型化合物。通过文献分析和光解实验相结合的方式,对相应的环境已知和未知TPs进行鉴定。将农药的水溶液进行光解,以生成在水环境中可能出现的TPs。通过高分辨率液相色谱-串联质谱(LC-MS/MS)对所得混合物中的TPs进行筛选。本文所开发的方法分三个不同层次进行:在第一层,使用文献综述和计算机模拟方法示例性地预测每个单一TP的环境细菌毒性和遗传毒性。如果有迹象表明有毒,则在第二层进行实验。在此,将含有母体化合物和TPs的光解混合物用于后续的毒性测试。对母体化合物和光解混合物进行微毒试验,以确定对费氏弧菌的急性和慢性毒性以及生长抑制情况。进行Umu试验以确定初级DNA损伤。在第三层,如果前几层有有毒迹象且有分析标准品,则使用单一物质标准品进行毒性测试。TPs的鉴定揭示了源自这六种农药的45种已知环境TPs。因此,需要评估的物质数量增加了七倍多。通过分层方法,可以评估所选TPs中94%对环境细菌的毒理学效应。对于20%的TPs,我们发现有强有力的证据表明它们对环境细菌有毒,因为它们至少在两个层次上进行了评估。对于另外44%的TPs,我们发现有轻微证据,因为它们只在一个层次上进行了评估。相反,事实证明这种方法无论是通过计算机模拟工具还是实验,都不适用于评估TPs的遗传毒性。与仅考虑母体化合物相比,可能对环境构成风险的物质数量增加了两倍。因此,本研究表明所进行的筛选方法能够轻松快速地鉴定与环境相关的TPs。然而,所呈现的研究只是初步筛选。其适用范围需要进一步评估。为此,作为下一步,应通过应用额外的终点指标并纳入更多母体化合物来验证此处建议的方法。