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

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.

Communicating Confidence of Per- and Polyfluoroalkyl Substance Identification via High-Resolution Mass Spectrometry

“…Common prioritizations through filtering data include the following: Features with a mass defect between −0.11 and 0.12. 5 For PFAS studies, it is convenient to filter features by their CF 2 -normalized mass defect, frequently 0.85–1 in negative ionization mode 29 , 30 or 0–0.15 in positive ionization mode. 17 Features with at least three homologues detected.…”

“…Data filtering for homologous series is commonly facilitated by Kendrick mass defect plots. 5 , 30 , 31 …”

Per‐ and Polyfluoroalkyl Substances (PFAS) in Subsurface Environments: Occurrence, Fate, Transport, and Research Prospect

“…Given that a large portion of PFAS remain unidentified (Koelmel et al., 2021; Xiao, 2017), along with the heterogeneity and complexity of geological conditions, simple‐to‐use approaches for non‐targeted or suspected screening of PFAS need to be developed for identifying unknown PFAS as well as to evaluate PFAS degradation and transformation in the environment. To this end, software for PFAS compound analysis (e.g., FluoroMatch Flow) (Koelmel et al., 2021) that includes compound feature detection, mass matching, retention time pattern analysis, and fragment screening could accelerate identifying unknown PFAS in complicated environmental samples. However, transparency, collaboration, and coherence among academia, industry, government, and other stakeholders are the keys to share the hidden information on the environmental release of thousands of PFAS in the environment.…”

Current progress in the environmental analysis of poly- and perfluoroalkyl substances (PFAS)

“…In an application of this revolutionary tool to aqueous film forming foam analysis, Koelmel et al discovered over one thousand likely PFAS including previously unreported species. Furthermore, the authors were able to filter out 96% of features which were likely not PFAS, yet contained some fluorinated carbon atoms in their molecule 99 .…”