Identifying unknown by-products in drinking water using comprehensive two-dimensional gas chromatography-quadrupole mass spectrometry and in silico toxicity assessment
Identifying unknown by-products in drinking water using comprehensive two-dimensional gas chromatography-quadrupole mass spectrometry and in silico toxicity assessment
复制标题
使用全面的二维气相色谱-四极杆质谱法和计算机毒性评估来识别饮用水中的未知副产物
DOI：
10.1016/j.chemosphere.2016.08.053
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发表时间：
2016
期刊：
影响因子：
8.8
通讯作者：
Wang Zijian
中科院分区：
文献类型：
--
作者：
Li Chunmei;Wang Donghong;Li Na;Luo Qian;Xu Xiong;Wang Zijian
在过去的40年里，提取和检测技术的改进提高了我们识别新消毒副产物（DBPs）的能力。然而，大多数先前的研究将DBP识别和测量工作与毒理学相结合，以解决对少数预期DBP的担忧，因此难以更好地定义单个DBP的健康风险。本研究采用全二维气相色谱-四极杆质谱（GC × GC-qMS）联用技术，结合OECD定量构效关系（QSAR）分析方法，建立了一种非靶向筛选方法。3.2是为了确定和优先考虑饮用水中的挥发性和半挥发性消毒副产物而开发的。该方法已成功地应用于原水氯化、氯胺化和臭氧化过程中消毒副产物的分析。在每个样品中初步鉴定了500多种化合物，显示了这种分析技术的上级性能。然后，根据DBP在重复处理的样品中存在的标准，确定了代表14个化学类别的总共170种挥发性和半挥发性DBP。使用Toolbox评估了DBPs的遗传毒性和致癌性，发现58种DBPs是实际或潜在的遗传毒物。通过将47种已鉴定化合物与市售标准品进行比较，确定化合物鉴定的准确度。使用库自动识别的化合物中约有90%（47种中的41种）是正确的。结果表明，GC×GC-qMS结合定量构效关系模型是一种高效、快速的化合物非靶向筛选技术。该方法和结果为DBPs的识别和排序提供了新的思路。
Improvements in extraction and detection technologies have increased our abilities to identify new disinfection by-products (DBPs) over the last 40 years. However, most previous studies combined DBP identification and measurement efforts with toxicology to address concerns on a few expected DBPs, making it difficult to better define the health risk from the individual DBPs. In this study, a nontargeted screening method involving comprehensive two-dimensional gas chromatography-quadrupole mass spectrometry (GC × GC-qMS) combined with OECD QSAR Toolbox Ver. 3.2 was developed for identifying and prioritizing of volatile and semi-volatile DBPs in drinking water. The method was successfully applied to analyze DBPs formed during chlorination, chloramination or ozonation of the raw water. Over 500 compounds were tentatively identified in each sample, showing the superior performance of this analytical technique. A total of 170 volatile and semi-volatile DBPs representing fourteen chemical classes were then identified, according to the criteria that the DBP was presented in the duplicate treated samples. The genotoxicity and carcinogenicity of the DBPs were evaluated using Toolbox, and 58 DBPs were found to be actual or potential genotoxicants. The accuracy of the compound identification was determined by comparing 47 identified compounds with commercially available standards. About 90% (41 of the 47) of the compounds that were automatically identified using the library were correct. The results show that GC×GC-qMS coupled with a quantitative structure–activity relationship model is a powerful and fast nontargeted screening technique for compounds. The method and results provide us a new idea for identification and prioritization of DBPs.