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PFΔ Screen — an open-source tool for automated PFAS feature prioritization in non-target HRMS data
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Abstract
Per- and polyfluoroalkyl substances (PFAS) are a huge group of anthropogenic chemicals with unique properties that are used in countless products and applications. Due to the high stability of their C-F bonds, PFAS or their transformation products (TPs) are persistent in the environment, leading to ubiquitous detection in various samples worldwide. Since PFAS are industrial chemicals, the availability of authentic PFAS reference standards is limited, making non-target screening (NTS) approaches based on high-resolution mass spectrometry (HRMS) necessary for a more comprehensive characterization. NTS usually is a time-consuming process, since only a small fraction of the detected chemicals can be identified. Therefore, efficient prioritization of relevant HRMS signals is one of the most crucial steps. We developed PFΔ Screen, a Python-based open-source tool with a simple graphical user interface (GUI) to perform efficient feature prioritization using several PFAS-specific techniques such as the highly promising MD/C-m/C approach, Kendrick mass defect analysis, diagnostic fragments (MS 2), fragment mass differences (MS 2), and suspect screening. Feature detection from vendor-independent MS raw data (mzML, data-dependent acquisition) is performed via pyOpenMS (or custom feature lists) with subsequent calculations for prioritization and identification of PFAS in both HPLC- and GC-HRMS data. The PFΔ Screen workflow is presented on four PFAS-contaminated agricultural soil samples from south-western Germany. Over 15 classes of PFAS (more than 80 single compounds with several isomers) could be identified, including four novel classes, potentially TPs of the precursors fluorotelomer mercapto alkyl phosphates (FTMAPs). PFΔ Screen can be used within the Python environment and is easily automatically installable and executable on Windows. Its source code is freely available on GitHub ( https://github.com/JonZwe/PFAScreen).
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An overview of the uses of per- and polyfluoroalkyl substances (PFAS)
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is a PhD candidate (German Federal Environmental Foundation scholar) in the lab of Christian Zwiener. His current research includes analysis of per- and polyfluoroalkyl substances (PFAS) and their transformation products by GC- and LC-HRMS and PFAS precursor characterization by oxidative conversion. His main focus is on the development of non-target screening data analysis approaches for PFAS identification in HRMS data.
is a postdoctoral researcher in the lab of Christian Zwiener at the University of Tübingen. His research covers the analysis, occurrence, and environmental fate of per- and polyfluoroalkyl substances (PFAS) and their transformation products. His interests particularly lie in the development of novel screening techniques by liquid and gas chromatography coupled to high-resolution mass spectrometry and an enhanced understanding of the complex and wide-ranging impacts of PFAS on the environment.
holds a PhD in analytical chemistry and the environment, and is currently a postdoctoral researcher in the lab of Prof. Peter Grathwohl at the University of Tübingen. His research covers the environmental fate of organic pollutants in the soil environment. In particular, his main interests are the analysis, sorption, and biodegradation processes of per- and polyfluoroalkyl substances, as well as the application of remediation strategies to contaminated sites.
is Head of the Environmental Analytical Chemistry Group in the Department of Geosciences at the Eberhard Karls Universität Tübingen. His research focuses on the analysis, occurrence, and fate of organic micropollutants in the environment and in water treatment (e.g., disinfection byproducts, pharmaceuticals, personal care products, pesticides, poly- and perfluorinated compounds). This includes the development of analytical approaches for non-target and suspect screening by LC-high-resolution mass spectrometry, field investigations and lab-scale experiments for photochemistry, biodegradation, and electrochemical oxidation to identify transformation products.
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