Multidimensional Library for the Improved Identification of Per- and Polyfluoroalkyl Substances (PFAS)#
Authors#
Kara M. Joseph, Anna K. Boatman, James N. Dodds, Kaylie I. Kirkwood-Donelson, Jack P. Ryan, Jian Zhang, Paul A. Thiessen, Evan E. Bolton, Alan Valdiviezo, Yelena Sapozhnikova, Ivan Rusyn, Emma Schymanski, Erin S. Baker
Abstract#
As the occurrence of human diseases and conditions increase, questions continue to arise about their linkages to chemical exposure, especially for per-and polyfluoroalkyl substances (PFAS). Currently, many chemicals of concern have limited experimentalinformation available for their use in analytical assessments. Here, we aim to increase this knowledge by providing the scientific community with multidimensional characteristics for 174 PFAS and their resulting 280 ion types. Using a platform coupling reversed-phase liquid chromatography (RPLC), electrospray ionization (ESI) or atmospheric pressure chemical onization (APCI), drift tube ion mobility spectrometry (IMS), and mass spectrometry (MS), the retention times, collision cross section (CCS) values, and m/z ratios were determined for all analytes and assembled into an openly available multidimensional database. This information will provide the scientific community with essential characteristics to expand analytical assessments of PFAS and improve machine learning capabilities for discovering new PFAS. Additionally, all CCS values have been added to PubChem and the multidimensional database webpage (https://tarheels.live/bakerlab/databases) and Zenodo (10.5281/zenodo.13387493) and populated regularly as new PFAS standards become available.
Code Availability#
In this study, RStudio was used for data visualization and figure creation. Microsoft Excel was used for calculating CCS values from drift times, as well as statistical analyses of relative standard deviation and mass error. An example fillable Excel workbook of the “Single Field Template” used to calculate the CCS values from extracted drift times is available as a part of Supplemental Materials (S2). Code and data related to the CCS integration in PubChem is available on GitLab (https://gitlab.com/uniluxembourg/lcsb/eci/pubchem), which also includes example scripts to retrieve the CCS data from PubChem in R.
