The University of Queensland, Queensland Alliance for Environmental Health Sciences (QAEHS), 20 Cornwall Street, Woolloongabba, QLD, 4102, Australia.
The University of Queensland, Queensland Alliance for Environmental Health Sciences (QAEHS), 20 Cornwall Street, Woolloongabba, QLD, 4102, Australia.
Chemosphere. 2024 Feb;349:140697. doi: 10.1016/j.chemosphere.2023.140697. Epub 2023 Nov 15.
Non-target analysis (NTA) using high-resolution mass spectrometry is becoming a useful approach to screen for suspect and unknown chemicals. For comprehensive analyses, data-independent acquisition (DIA), like Sequential Windowed Acquisition of all THeoretical Mass Spectra (SWATH-MS) on Sciex instruments, is necessary, usually followed by library matching for feature annotation. The choice of parameters, such as acquisition window number and size, may influence the comprehensiveness of the suspect features detected. The goal of this study was to assess how mass spectrometric DIA settings may influence the ability to obtain confident annotations and identifications of features in environmental (river water, passive sample extract (PSE)), wastewater (unpreserved and acidified) and biological (urine) sample matrices. Each matrix was analysed using 11 different MS methods, with 5-15 variable size acquisition windows. True positive (TP) annotation (i.e., matching experimental and library spectra) rates were constant for PSE (40%) and highest for urine (18%), wastewater (34% and 36%, unpreserved and acidified, respectively) and river water (8%) when using higher numbers of windows (15). The number of annotated features was highest for PSE (12%) and urine (8.5%) when using more acquisition windows (9 and 14, respectively). Less complex matrices (based on average total ion chromatogram intensities) like river water, unpreserved and acidified wastewater have higher annotation rates (7.5%, 8% and 13.2%, respectively) when using less acquisition windows (5-6), indicating matrix dependency of optimum settings. Library scores varied widely for correct (scores between 6 and 100) as well as incorrect annotations (scores between 2 and 100), making it hard to define specific ideal cut-off values. Results highlight the need for properly curated libraries and careful optimization of SWATH-MS and other DIA methods for each individual matrix, finding the best ratio of total annotations to true positive, (i.e., correct) annotations to achieve best NTA results.
非靶向分析（NTA）使用高分辨率质谱正在成为筛选可疑和未知化学物质的有用方法。对于全面分析，需要数据独立采集（DIA），例如 Sciex 仪器上的连续窗口采集所有理论质量谱（SWATH-MS），通常随后进行特征注释的库匹配。采集窗口数量和大小等参数的选择可能会影响检测到的可疑特征的全面性。本研究的目的是评估质谱 DIA 设置如何影响获得置信度注释和鉴定环境（河水、被动采样提取物（PSE））、废水（未保存和酸化）和生物（尿液）样品基质中特征的能力。每个基质都使用 11 种不同的 MS 方法进行分析，采集窗口大小为 5-15 个变量。使用更多的窗口（15 个）时，PSE（40%）和尿液（18%）的真阳性（TP）注释（即匹配实验和库谱）率保持不变，废水（未保存和酸化，分别为 34%和 36%）和河水（8%）最高。使用更多采集窗口（分别为 9 和 14）时，PSE（12%）和尿液（8.5%）的注释特征数量最高。基于平均总离子色谱强度，更复杂的基质（如河水、未保存和酸化废水）使用更少的采集窗口（5-6 个）时具有更高的注释率（分别为 7.5%、8%和 13.2%），表明最佳设置依赖于基质。正确（分数在 6 到 100 之间）和不正确（分数在 2 到 100 之间）的注释的库分数差异很大，因此很难定义特定的理想截止值。结果强调了需要为每个单独的基质正确整理库，并仔细优化 SWATH-MS 和其他 DIA 方法，以找到最佳的总注释与真阳性（即正确）注释的比例，从而获得最佳的 NTA 结果。
