PFΔScreen – An open-source tool for automated PFAS feature prioritization in non-target HRMS data DOI Creative Commons
Jonathan Zweigle, Boris Bugsel, Joel Fabregat‐Palau

et al.

Published: Sept. 26, 2023

Per- and polyfluoroalkyl substances (PFAS) are a huge group of anthropogenic chemicals with unique properties that used in countless products applications. Due to the high stability their C–F bonds, PFAS or transformation (TPs) persistent environment, leading ubiquitous detection various samples worldwide. Since industrial chemicals, availability authentic reference standards is limited, making non-target screening (NTS) approaches based on high-resolution mass spectrometry (HRMS) necessary for more comprehensive characterization. NTS usually time-consuming process, since only small fraction detected can be identified. Therefore, efficient prioritization relevant HRMS signals one most crucial steps. We developed PFΔScreen, Python-based open-source tool simple graphical user interface (GUI) perform feature by several specific techniques such as highly promising MD/C-m/C approach, Kendrick defect analysis, diagnostic fragments (MS2), fragment differences (MS2) suspect screening. Feature from vendor-independent MS raw data (mzML, data-dependent acquisition) performed via pyOpenMS (or custom lists) subsequent calculations identification both HPLC- GC-HRMS data. The PFΔScreen workflow presented four PFAS-contaminated agricultural soil south-western Germany. Over 15 classes (more than 80 single compounds isomers) could identified, including novel classes, potentially TPs precursors fluorotelomer mercapto alkyl phosphates (FTMAPs). within Python environment easily automatically installable executable Windows. Its source code freely available GitHub (https://github.com/JonZwe/PFAScreen).

Language: Английский

Nontarget screening strategies for PFAS prioritization and identification by high resolution mass spectrometry: A review DOI
Boris Bugsel, Jonathan Zweigle, Christian Zwiener

et al.

Trends in Environmental Analytical Chemistry, Journal Year: 2023, Volume and Issue: 40, P. e00216 - e00216

Published: Oct. 14, 2023

Language: Английский

Citations

23
Online and Offline Prioritization of Chemicals of Interest in Suspect Screening and Non-targeted Screening with High-Resolution Mass Spectrometry DOI Creative Commons
Drew Szabo, Travis M. Falconer, Christine M. Fisher

et al.

Analytical Chemistry, Journal Year: 2024, Volume and Issue: 96(9), P. 3707 - 3716

Published: Feb. 21, 2024

Recent advances in high-resolution mass spectrometry (HRMS) have enabled the detection of thousands chemicals from a single sample, while computational methods improved identification and quantification these absence reference standards typically required targeted analysis. However, to determine presence interest that may pose an overall impact on ecological human health, prioritization strategies must be used effectively efficiently highlight for further investigation. Prioritization can based chemical's physicochemical properties, structure, exposure, toxicity, addition its regulatory status. This Perspective aims provide framework chemical implemented facilitate high-quality research communication results. These are categorized as either "online" or "offline" techniques. Online techniques trigger isolation fragmentation ions low-energy spectra real time, with user-defined parameters. Offline techniques, contrast, after data has been acquired; detected features filtered ranked relative abundance predicted concentration imputed tandem spectrum (MS

Language: Английский

Citations

11
PFΔScreen – An open-source tool for automated PFAS feature prioritization in non-target HRMS data DOI Creative Commons
Jonathan Zweigle, Boris Bugsel, Joel Fabregat‐Palau

et al.

Published: Sept. 26, 2023

Per- and polyfluoroalkyl substances (PFAS) are a huge group of anthropogenic chemicals with unique properties that used in countless products applications. Due to the high stability their C–F bonds, PFAS or transformation (TPs) persistent environment, leading ubiquitous detection various samples worldwide. Since industrial chemicals, availability authentic reference standards is limited, making non-target screening (NTS) approaches based on high-resolution mass spectrometry (HRMS) necessary for more comprehensive characterization. NTS usually time-consuming process, since only small fraction detected can be identified. Therefore, efficient prioritization relevant HRMS signals one most crucial steps. We developed PFΔScreen, Python-based open-source tool simple graphical user interface (GUI) perform feature by several specific techniques such as highly promising MD/C-m/C approach, Kendrick defect analysis, diagnostic fragments (MS2), fragment differences (MS2) suspect screening. Feature from vendor-independent MS raw data (mzML, data-dependent acquisition) performed via pyOpenMS (or custom lists) subsequent calculations identification both HPLC- GC-HRMS data. The PFΔScreen workflow presented four PFAS-contaminated agricultural soil south-western Germany. Over 15 classes (more than 80 single compounds isomers) could identified, including novel classes, potentially TPs precursors fluorotelomer mercapto alkyl phosphates (FTMAPs). within Python environment easily automatically installable executable Windows. Its source code freely available GitHub (https://github.com/JonZwe/PFAScreen).

Language: Английский

Citations

3