Identifying Multidimensional Characteristics of PFAS Using LC-DTIMS-HRMS

A team of researchers from multiple institutions have identified the multidimensional characteristics for 175 per-and polyfluoroalkyl substances (PFAS) using a platform coupling reversed-phase liquid chromatography (RPLC), electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI), drift tube ion mobility spectrometry (IMS), and mass spectrometry (MS). The team was able to determine and assemble into an openly available multidimensional dataset the retention times, collision cross section (CCS) values, and m/z ratios. This work provides the scientific community with essential characteristics to expand analytical assessments of PFAS and augment machine learning (ML) training sets for discovering new PFAS. An article based on this work was published in Scientific Data (1).

A class of synthetic, fluorinated chemicals used in a variety of consumer products and industrial processes over the last 70 years(2), PFAS, due to special chemical and physical properties because of their characteristic carbon-fluorine bonds, are both water and oil repellent, resistant to thermal or chemical degradation, and highly useful surfactants (3). Regardless of suspected adverse health implications and prevalence of PFAS in the environment, the United States regulates the concentration of only six PFAS, exclusively in drinking water (4). Common targeted analytical methods for PFAS utilize liquid chromatography-mass spectrometry (LC-MS) platforms with a triple quadrupole mass spectrometer, usually covering less than 50 of these analytes, to evaluate their presence and concentration (5). However, as the list of PFAS continues to grow in number and chemical complexity, the authors state that more comprehensive and robust analytical techniques are becoming essential to evaluate a problem of such scale (1).

The team, composed of staff from the University of North Carolina at Chapel Hill (Chapel Hill, North Carolina), the National Institute of Environmental Health Sciences (Durham, North Carolina), the National Institutes of Health (Bethesda, Maryland), Texas A&M University (College Station, Texas), the U.S Department of Agriculture (Wyndmoor, Pennsylvania), and the University of Luxembourg (Belvaux, Luxembourg) reports that for the 175 PFAS noted in the multidimensional dataset, 281 ion types were detected, including collision cross section (CCS) values for 30 analytes reported for the first time. The information presented, the authors wrote, offers an argument for analysis of PFAS in positive mode whereas many PFAS are studied only in negative mode; however, for their dataset, 169 PFAS in negative mode, 14 in positive mode, and 8 ions in both modes were observed. The authors believe that these 281 PFAS precursor CCS values will advance analytical analyses and machine learning studies (1).

To use the multidimensional PFAS dataset for targeted analyses of environmental and clinical samples in the software Skyline (6), the authors suggest copying and pasting columns B-G of the “Skyline Formatted Library” directly into the transition list. A more detailed description of how to create a Skyline document and use this software for targeted analyses can be found on the Computer Science and Engineering, University of California, San Diego website (7). The authors also recommend that users select the appropriate sheet within the workbook to reflect their data collection method(s) (1).

Perfluoroalkyl and polyfluoroalkyl substances; hazardous materials for water resistance. © Emin - stock.adobe.com

References

1. Joseph, K. M.; Boatman, A. K.; Dodds, J. N.; Kirkwood-Donelson, K. I.; Ryan, J. P.; Zhang, J.; Thiessen, P. A.; Bolton, E. E.; Valdiviezo, A.; Sapozhnikova, Y.; Rusyn, I.; Schymanski, E. L.; Baker, E. S. Multidimensional library for the improved identification of per- and polyfluoroalkyl substances (PFAS). Sci Data 2025, 12 (1), 150. DOI: DOI: 10.1038/s41597-024-04363-0

2. Gaines, L. G. T. Historical and Current Usage of Per- and Polyfluoroalkyl Substances (PFAS): A Literature Review. Am. J. Ind. Med. 2023, 66 (5), 353-378. DOI: 10.1002/ajim.23362

3. Brase, R. A.; Mullin, E. J.; Spink, DC. Legacy and Emerging Per- and Polyfluoroalkyl Substances: Analytical Techniques, Environmental Fate, and Health Effects. Int. J. Mol. Sci. 2021, 22 (3), 995. DOI: 10.3390/ijms22030995

4. Phillis, M. Biden Administration Sets First-Ever Limits on ‘Forever Chemicals’ in Drinking Water. Associated Press (2024).

5. PFAS Team. PFAS Technical and Regulatory Guidance Document and Fact Sheets, 2023).

6. MacLean, B.; Tomazela, D. M.; Shulman, N.; Chambers, M.; Finney, G.L.; Frewen, B.; Kern,R.; Tabb, D. L.; Liebler, D. C.; MacCoss, M. J. Skyline: An Open Source Document Editor for Creating and Analyzing Targeted Proteomics Experiments. Bioinformatics 2010, 26 (7), 966-968. DOI: 10.1093/bioinformatics/btq054

7. Joseph, K. et al. Data for Multidimensional Library for the Improved Identification of Per- and Polyfluoroalkyl Substances (PFAS). MassIVE/Computer Science and Engineering University of California, San Diego website. DOI: 10.25345/C5XW4876Q (2024).