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氟匹配 2.0-使自动化和全面的非靶向 PFAS 注释成为现实。

FluoroMatch 2.0-making automated and comprehensive non-targeted PFAS annotation a reality.

机构信息

School of Public Health, Yale University, New Haven, CT, USA.

Department of Civil Engineering, Stony Brook University, Stony Brook, NY, USA.

出版信息

Anal Bioanal Chem. 2022 Jan;414(3):1201-1215. doi: 10.1007/s00216-021-03392-7. Epub 2021 May 20.

Abstract

Because of the pervasiveness, persistence, and toxicity of per- and polyfluoroalkyl substances (PFAS), there is growing concern over PFAS contamination, exposures, and health effects. The diversity of potential PFAS is astounding, with nearly 10,000 PFAS catalogued in databases to date (and growing). The ability to detect the thousands of known PFAS, and discover previously uncatalogued PFAS, is necessary to understand the scope of PFAS contamination and to identify appropriate remediation and regulatory solutions. Current non-targeted methods for PFAS analysis require manual curation and are time-consuming, prone to error, and not comprehensive. FluoroMatch Flow 2.0 is the first software to cover all steps of data processing for PFAS discovery in liquid chromatography-high-resolution tandem mass spectrometry samples. These steps include feature detection, feature blank filtering, exact mass matching to catalogued PFAS, mass defect filtering, homologous series detection, retention time pattern analysis, class-based MS/MS screening, fragment screening, and predicted MS/MS from SMILES structures. In addition, a comprehensive confidence level criterion is implemented to help users understand annotation certainty and integrate various layers of evidence to reduce overreporting. Applying the software to aqueous film forming foam analysis, we discovered over one thousand likely PFAS including previously unreported species. Furthermore, we were able to filter out 96% of features which were likely not PFAS. FluoroMatch Flow 2 increased coverage of likely PFAS by over tenfold compared to the previous release. This software will enable researchers to better characterize PFAS in the environment and in biological systems.

摘要

由于全氟和多氟烷基物质(PFAS)的普遍性、持久性和毒性,人们越来越关注 PFAS 污染、暴露和健康影响。潜在的 PFAS 种类繁多,迄今为止已有近 10000 种 PFAS 被编入数据库(且还在不断增加)。为了了解 PFAS 污染的范围并确定适当的修复和监管解决方案,有必要能够检测到数千种已知的 PFAS,并发现以前未被编目的 PFAS。目前用于 PFAS 分析的非靶向方法需要人工策管,既费时、易错,又不全面。FluoroMatch Flow 2.0 是第一款涵盖液相色谱-高分辨串联质谱样品中 PFAS 发现数据处理所有步骤的软件。这些步骤包括特征检测、特征空白过滤、与编目 PFAS 的精确质量匹配、质量缺陷过滤、同系物检测、保留时间模式分析、基于类别的 MS/MS 筛选、碎片筛选以及基于 SMILES 结构的预测 MS/MS。此外,还实施了全面的置信度标准,以帮助用户了解注释的确定性,并整合各个层次的证据,以减少过度报告。将该软件应用于水成膜泡沫分析,我们发现了一千多种可能的 PFAS,包括以前未报告的物种。此外,我们还能够过滤掉 96%的可能不是 PFAS 的特征。与前一版本相比,FluoroMatch Flow 2 增加了 10 倍以上可能的 PFAS 覆盖率。该软件将使研究人员能够更好地描述环境和生物系统中的 PFAS。

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