Reference : Discovering Pesticides and their Transformation Products in Luxembourg Waters using O...
E-prints/Working papers : Already available on another site
Life sciences : Environmental sciences & ecology
Sustainable Development
http://hdl.handle.net/10993/48327
Discovering Pesticides and their Transformation Products in Luxembourg Waters using Open Cheminformatics Approaches
English
Krier, Jessy 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]
Kondic, Todor mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Environmental Cheminformatics]
Lai, Adelene mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Environmental Cheminformatics]
Diderich, Philippe [> >]
Zhang, Jian [> >]
Thiessen, Paul A. [> >]
Bolton, Evan E. [> >]
Schymanski, Emma mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
2021
In Review
No
[en] Abstract The diversity of hundreds of thousands of potential organic pollutants and the lack of (publicly available) information about many of them is a huge challenge for environmental sciences, engineering, and regulation. Suspect screening based on high-resolution liquid chromatography-mass spectrometry (LC-HRMS) has enormous potential to help characterize the presence of these chemicals in our environment, enabling the detection of known and newly emerging pollutants, as well as their potential transformation products (TPs). Here, suspect list creation (focusing on pesticides relevant for Luxembourg, incorporating data sources in 4 languages) was coupled to an automated retrieval of related TPs from PubChem based on high confidence suspect hits, to screen for pesticides and their TPs in Luxembourgish river samples. A computational workflow was established to combine LC-HRMS analysis and pre-screening of the suspects (including automated quality control steps), with spectral annotation to determine which pesticides and, in a second step, their related TPs may be present in the samples. The data analysis with Shinyscreen (https://git-r3lab.uni.lu/eci/shinyscreen/), an open source software developed in house, coupled with custom-made scripts, revealed the presence of 162 potential pesticide masses and 135 potential TP masses in the samples. Further identification of these mass matches was performed using the open source MetFrag (https://msbi.ipb-halle.de/MetFrag/). Eventual target analysis of 36 suspects resulted in 31 pesticides and TPs confirmed at Level-1 (highest confidence), and five pesticides and TPs not confirmed due to different retention times. Spatio-temporal analysis of the results showed that TPs and pesticides followed similar trends, with a maximum number of potential detections in July. The highest detections were in the rivers Alzette and Mess and the lowest in the Sûre and Eisch. This study (a) added pesticides, classification information and related TPs into the open domain, (b) developed automated open source retrieval methods - both enhancing FAIRness (Findability, Accessibility, Interoperability and Reusability) of the data and methods; and (c) will directly support “L’Administration de la Gestion de l’Eau” on further monitoring steps in Luxembourg.
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/48327
10.21203/rs.3.rs-478324/v1
https://www.researchsquare.com/article/rs-478324/v1
This work is licensed under a CC BY 4.0 License
preprint
https://www.researchsquare.com/article/rs-478324/v1
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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