Department of Chemistry, University at Buffalo, The State University of New York (SUNY) Buffalo, New York, 14260, USA.
Department of Epidemiology and Environmental Health, University at Buffalo, The State University of New York (SUNY) Buffalo, New York, 14214, USA.
Rapid Commun Mass Spectrom. 2021 Apr 30;35(8):e9048. doi: 10.1002/rcm.9048.
Silicone wristbands have emerged as valuable passive samplers for monitoring of personal exposure to environmental contaminants in the rapidly developing field of exposomics. Once deployed, silicone wristbands collect and hold a wealth of chemical information that can be interrogated using high-resolution mass spectrometry (HRMS) to provide a broad coverage of chemical mixtures.
Gas chromatography coupled to Orbitrap™ mass spectrometry (GC/Orbitrap™ MS) was used to simultaneously perform suspect screening (using in-house database) and unknown screening (using vendor databases) of extracts from wristbands worn by volunteers. The goal of this study was to optimize a workflow that allows detection of low levels of priority pollutants, with high reliability. In this regard, a data processing workflow for GC/Orbitrap™ MS was developed using a mixture of 123 environmentally relevant standards consisting of pesticides, flame retardants, organophosphate esters, and polycyclic aromatic hydrocarbons as test compounds.
The optimized unknown screening workflow using a search index threshold of 750 resulted in positive identification of 70 analytes in validation samples, and a reduction in the number of false positives by over 50%. An average of 26 compounds with high confidence identification, 7 level 1 compounds and 19 level 2 compounds, were observed in worn wristbands. The data were further analyzed via suspect screening and retrospective suspect screening to identify an additional 36 compounds.
This study provides three important findings: (1) a clear evidence of the importance of sample cleanup in addressing complex sample matrices for unknown analysis, (2) a valuable workflow for the identification of unknown contaminants in silicone wristband samplers using electron ionization HRMS data, and (3) a novel application of GC/Orbitrap™ MS for the unknown analysis of organic contaminants that can be used in exposomics studies.
在快速发展的暴露组学领域,硅树脂腕带已成为监测环境污染物个体暴露情况的有价值的被动采样器。硅树脂腕带一旦部署,就会收集和保留大量的化学信息,这些信息可以使用高分辨率质谱(HRMS)进行询问,以提供广泛的化学混合物覆盖范围。
气相色谱法与轨道阱质谱(GC/Orbitrap™ MS)联用,对志愿者佩戴的腕带提取物进行可疑物筛查(使用内部数据库)和未知物筛查(使用供应商数据库)。本研究的目的是优化一种工作流程,该流程允许以高可靠性检测低水平的优先污染物。在这方面,使用由 123 种环境相关标准组成的混合物(包括农药、阻燃剂、有机磷酸酯和多环芳烃)作为测试化合物,开发了用于 GC/Orbitrap™ MS 的数据处理工作流程。
使用搜索索引阈值为 750 的优化未知物筛查工作流程,在验证样品中阳性鉴定了 70 种分析物,并将假阳性数量减少了 50%以上。在佩戴的腕带中观察到 26 种具有高置信度鉴定的化合物、7 种 1 级化合物和 19 种 2 级化合物。通过可疑物筛查和回溯可疑物筛查,进一步分析数据,确定了另外 36 种化合物。
本研究提供了三个重要发现:(1)清楚地证明了在解决复杂的未知物分析样品基质时,样品净化的重要性;(2)使用电子电离 HRMS 数据鉴定硅树脂腕带采样器中未知污染物的有价值的工作流程;(3)GC/Orbitrap™ MS 用于未知分析有机污染物的新应用,可用于暴露组学研究。