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Development of a Python Script to Aid in Identification of Biotransformation Products of Emerging PFAS
Citation:
Renyer, A., B. Payne, W. Willis, A. Brennan, AND D. Macmillan. Development of a Python Script to Aid in Identification of Biotransformation Products of Emerging PFAS. Presented at SERMACS, Durham, NC, October 25 - 28, 2023. https://doi.org/10.23645/epacomptox.24790626
Impact/Purpose:
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Description:
Per- and polyfluoroalkyl substances (PFAS) are a class of chemicals that are widespread throughout soils and waters around the world, leading to high potential for exposure. One concern of PFAS exposure is the biotransformation of the native species to unknown and potentially harmful products. The tools that currently exist to expedite identification of unknown PFAS tend not to be well suited for our workflow which includes data independent acquisition on Sciex instrumentation (SWATH) and involve biotransformation products that do not appear in homologous series and that also lack corresponding authentic standards. There are currently tools to predict biotransformation products, including the EPA CTS: Chemical Transformation Simulator and commercial software, though the predictions for PFAS biotransformations are only recently beginning to be characterized. Our initial workflow for non-targeted analysis after data collection involved evaluating retention time and mass error variability; calculating the average abundances of features across replicates; filtering data by Kendrick mass defect (KMD), t-test significance, and fold change magnitude; screening for predicted biotransformation products, known tracers, and characteristic fragments; and searching for potential candidate PFAS by using the EPA’s CompTox Chemicals Dashboard. Manually performing these tasks for large data sets requires substantial time investment and may introduce errors. We developed a user-friendly Python script to automate the data processing workflow, thereby significantly reducing processing time (from multiple days to a few hours) and generating reproducible, transparent, well documented data sets. This script may be easily modified to adjust the desired KMD range, select different tracers, and customize characteristic fragments. We tested the script using LC/MS/MS results from in vivo exposure to PFAS 6:1 fluorotelomer alcohol (6:1 FTOH) and perfluoro-(2,5,8-trimethyl-3,6,9-trioxadodecanoic) acid (HFPO-TeA). A biotransformation product with the tentative Schymanski confidence level 1 was identified for both compounds. The views expressed in this abstract are those of the author(s) and do not necessarily represent the views or the policies of the U.S. Environmental Protection Agency.
URLs/Downloads:
DOI: Development of a Python Script to Aid in Identification of Biotransformation Products of Emerging PFAS
PRESENTATION.PDF (PDF, NA pp, 1635.867 KB, about PDF)