Reference : Retrospective non-target analysis to support regulatory water monitoring: from masses...
Scientific journals : Article
Life sciences : Environmental sciences & ecology
Sustainable Development
http://hdl.handle.net/10993/48330
Retrospective non-target analysis to support regulatory water monitoring: from masses of interest to recommendations via in silico workflows
English
Lai, Adelene mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Environmental Cheminformatics]
Singh, Randolph mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Environmental Cheminformatics]
Kovalova, Lubomira [> >]
Jaeggi, Oliver [> >]
Kondic, Todor mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Environmental Cheminformatics]
Schymanski, Emma mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
2021
Environmental Sciences Europe
33
1
43
Yes (verified by ORBilu)
International
2190-4707
[en] Abstract Background Applying non-target analysis (NTA) in regulatory environmental monitoring remains challenging—instead of having exploratory questions, regulators usually already have specific questions related to environmental protection aims. Additionally, data analysis can seem overwhelming because of the large data volumes and many steps required. This work aimed to establish an open in silico workflow to identify environmental chemical unknowns via retrospective NTA within the scope of a pre-existing Swiss environmental monitoring campaign focusing on industrial chemicals. The research question addressed immediate regulatory priorities: identify pollutants with industrial point sources occurring at the highest intensities over two time points. Samples from 22 wastewater treatment plants obtained in 2018 and measured using liquid chromatography–high resolution mass spectrometry were retrospectively analysed by (i) performing peak-picking to identify masses of interest; (ii) prescreening and quality-controlling spectra, and (iii) tentatively identifying priority “known unknown” pollutants by leveraging environmentally relevant chemical information provided by Swiss, Swedish, EU-wide, and American regulators. This regulator-supplied information was incorporated into MetFrag, an in silico identification tool replete with “post-relaunch” features used here. This study’s unique regulatory context posed challenges in data quality and volume that were directly addressed with the prescreening, quality control, and identification workflow developed. Results One confirmed and 21 tentative identifications were achieved, suggesting the presence of compounds as diverse as manufacturing reagents, adhesives, pesticides, and pharmaceuticals in the samples. More importantly, an in-depth interpretation of the results in the context of environmental regulation and actionable next steps are discussed. The prescreening and quality control workflow is openly accessible within the R package Shinyscreen, and adaptable to any (retrospective) analysis requiring automated quality control of mass spectra and non-target identification, with potential applications in environmental and metabolomics analyses. Conclusions NTA in regulatory monitoring is critical for environmental protection, but bottlenecks in data analysis and results interpretation remain. The prescreening and quality control workflow, and interpretation work performed here are crucial steps towards scaling up NTA for environmental monitoring.
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/48330
10.1186/s12302-021-00475-1
https://enveurope.springeropen.com/articles/10.1186/s12302-021-00475-1
All rights reserved
FnR ; FNR12341006 > Emma Schymanski > ECHIDNA > Environmental Cheminformatics To Identify Unknown Chemicals And Their Effects > 01/10/2018 > 30/09/2023 > 2018

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