Department of Chemistry, University of Toronto, Toronto, Ontario, M1C 1A4, Canada.
Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, Ontario M1C 1A4, Canada.
Anal Chem. 2021 Jan 26;93(3):1498-1506. doi: 10.1021/acs.analchem.0c03733. Epub 2020 Dec 23.
The identity of an unknown environmental pollutant is reflected by the mass and dissociation chemistry of its (quasi)molecular ion. Gas chromatography-atmospheric pressure chemical ionization-mass spectrometry (GC-APCI-MS) increases the yield of molecular ions (compared to conventional electron ionization) by collisional cooling. Scanning quadrupole data-independent acquisition (SQDIA) permits unbiased, unattended selection of (quasi)molecular ions and acquisition of structure-diagnostic collision-induced dissociation mass spectra, while minimizing interferences, by sequentially cycling a quadrupole isolation window through the / range. This study reports on the development of a suspect screening method based on industrial compounds with bioaccumulation potential. A comparison of false and correct identifications in a mixed standard containing 30 analytes suggests that SQDIA results in a markedly lower false-positive rate than standard DIA: 5 for SQDIA and 82 for DIA. Electronic waste dust was analyzed using GC and quadrupole time-of-flight MS with APCI and SQDIA acquisition. A total of 52 brominated, chlorinated, and organophosphorus compounds were identified by suspect screening; 15 unique elemental compositions were identified using nontargeted screening; 17 compounds were confirmed using standards and others identified to confidence levels 2, 3, or 4. SQDIA reduced false-positive identifications, compared to experiments without quadrupole isolation. False positives also varied by class: 20% for Br, 37% for Cl, 75% for P, and >99% for all other classes. The structure proposal of a previously reported halogenated compound was revisited. The results underline the utility of GC-SQDIA experiments that provide information on both the (quasi)molecular ions and its dissociation products for a more confident structural assignment.
未知环境污染物的特征反映在其(准)分子离子的质量和离解化学性质上。与传统的电子电离相比,气相色谱-大气压化学电离-质谱(GC-APCI-MS)通过碰撞冷却提高了分子离子的产率。扫描四极杆数据非依赖性采集(SQDIA)允许通过顺序循环四极杆隔离窗口通过/范围,对(准)分子离子进行无偏见、无人值守的选择,并采集结构诊断碰撞诱导解离质谱,同时最大限度地减少干扰。本研究报告了一种基于具有生物累积潜力的工业化合物的可疑筛选方法的开发。在含有 30 种分析物的混合标准品中进行错误和正确鉴定的比较表明,SQDIA 导致的假阳性率明显低于标准 DIA:SQDIA 为 5,DIA 为 82。使用 GC 和四极杆飞行时间 MS 以及 APCI 和 SQDIA 采集对电子废物粉尘进行了分析。通过可疑筛选鉴定了 52 种溴化、氯化和有机磷化合物;使用非靶向筛选鉴定了 15 种独特的元素组成;使用标准品确认了 17 种化合物,其他化合物的鉴定置信度为 2、3 或 4。与没有四极杆隔离的实验相比,SQDIA 减少了假阳性鉴定。假阳性也因类别而异:Br 为 20%,Cl 为 37%,P 为 75%,所有其他类别均>99%。对先前报道的卤化化合物的结构提案进行了重新考察。结果强调了 GC-SQDIA 实验的有用性,该实验提供了有关(准)分子离子及其解离产物的信息,有助于更有信心地进行结构分配。