Department of Civil and Environmental Engineering and Nicholas School of the Environment, Duke University, 121 Hudson Hall, Box 90287, Durham, North Carolina 27708-0287, United States.
Department of Civil and Environmental Engineering, Colorado School of Mines, 1500 Illinois St., Golden, Colorado 80401, United States.
Anal Chem. 2021 Feb 9;93(5):2820-2827. doi: 10.1021/acs.analchem.0c04109. Epub 2021 Jan 26.
Per and polyfluoroalkyl substances (PFASs) are an important class of organic pollutants. Many diverse PFASs are used in commerce and most are not amenable to conventional targeted chemical analysis due to lack of reference standards. Therefore, methods for elucidating the chemical structure of previously unreported or unexpected PFASs in the environment rely extensively on high-resolution mass spectrometry (HRMS). High-throughput structure identification by HRMS is hindered by a lack of PFAS molecular databases and tandem mass spectral libraries. Here, we report a new approach for generating an environmentally relevant PFAS molecular database constructed from curated structure lists and biotic/abiotic predicted transformation products. Further, we have generated a predicted tandem mass spectral library using computational mass spectrometry tools. Results demonstrate the utility of the generated database and approach for identifying PFASs in HRMS-enabled suspect- and nontarget screening studies.
全氟和多氟烷基物质（PFASs）是一类重要的有机污染物。许多不同的 PFASs 被用于商业用途，由于缺乏参考标准，大多数 PFASs 无法进行传统的靶向化学分析。因此，阐明环境中以前未报道或意外的 PFASs 的化学结构的方法广泛依赖于高分辨率质谱（HRMS）。由于缺乏 PFAS 分子数据库和串联质谱谱库，HRMS 高通量结构鉴定受到阻碍。在这里，我们报告了一种从经过精心整理的结构清单和生物/非生物预测转化产物中构建与环境相关的 PFAS 分子数据库的新方法。此外，我们还使用计算质谱工具生成了一个预测的串联质谱谱库。结果表明，所生成的数据库和方法可用于在基于 HRMS 的可疑和非目标筛选研究中鉴定 PFASs。
