A rapid screening method for the detection of nontargeted compounds in surface water samples was developed using MS-MS high-resolution mass spectrometry and data-dependent acquisition. The key parameters for the acquisition method were optimized using five model compounds with diverse chemical characteristics. The parameter selection required optimization between the total number of precursor ions that could be selected in an LC-MS run, the quality of each MS (full range) spectrum, and the quality of each MS-MS fragmentation spectrum. After the acquisition method was optimized, 18 surface water samples from rivers, reservoirs, and effluents from wastewater treatment plants were analyzed, generating 41625 MS-MS spectra in about 14 h. The raw data were then converted into two generic formats using the open-access program MSConvert. A combinatorial approach, similar partition searching (SPS), was then used to putatively identify analytes from the accurate mass of each analyte (adjusted for the adduct mass) and the corresponding MS-MS spectra were obtained. In this approach, the structures of about 250000 common compounds, stored in a large database as mathematical partitions of their exact mass, were compared directly to each MS-MS spectrum. Compounds with a similar mass and retention time were grouped together and labeled as "Analytes", using an Excel Add-In. The isotope ratio data from the MS spectrum, the corresponding MS-MS spectra, and the putative identifications were then imported into an Access relational database to facilitate sorting, searching, filtering, and querying the results. This allowed final inspection to assess confidence of the identifications made through the nontargeted screening.

中文翻译：

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使用类似分区搜索的数据相关采集，对水样品进行非目标筛选。

建立了一种使用MS-MS高分辨率质谱和数据依赖采集的快速筛选方法，用于检测地表水样品中的非目标化合物。使用五个具有不同化学特性的模型化合物优化了采集方法的关键参数。参数选择需要在LC-MS运行中可以选择的前驱体离子总数，每个MS（全范围）质谱图的质量以及每个MS-MS碎片质谱图的质量之间进行优化。优化采集方法后，分析了来自河流，水库和废水处理厂的废水的18个地表水样品，在约14小时内产生了41625 MS-MS光谱。然后，使用开放访问程序MSConvert将原始数据转换为两种通用格式。然后，采用组合方法，类似的分区搜索（SPS），从每种分析物的准确质量（针对加合物质量进行调整）中推断出分析物，并获得了相应的MS-MS光谱。通过这种方法，将大约25万种常见化合物的结构作为其确切质量的数学分区存储在大型数据库中，直接与每个MS-MS光谱进行比较。使用Excel加载项将质量和保留时间相似的化合物分组在一起，并标记为“分析物”。然后将来自MS质谱图，相应的MS-MS质谱图和推定标识的同位素比率数据导入Access关系数据库中，以利于对结果进行排序，搜索，过滤和查询。