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://gitlab.lcsb.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 96 potential TP masses in the samples. Further identification of these mass matches was performed using the open source approach 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.
Highlights
Human and ecosystem exposure to a broad range of substances, including a multitude of new chemicals introduced into the environment necessitates careful and increasingly high throughput characterization and examination of their effects. (Escher et al, 2020) One substance group of high relevance for human health is pesticides
As a part of “FAIRifying” this dataset, the LUXPEST list is openly available on the NORMAN-SLE (NORMAN Suspect List Exchange, 2021), PubChem (Kim et al, 2019) and CompTox (Williams et al, 2017; Krier, 2021) websites, and the detailed classification information was added to the PubChem NORMAN-SLE Classification Browser and into the individual records for the pesticides
This study describes open cheminformatics approaches to screen for emerging contaminants and their transformation products (TPs) in nontarget High resolution mass spectrometry (HR-MS) measurements
Summary
Human and ecosystem exposure to a broad range of substances, including a multitude of new chemicals introduced into the environment necessitates careful and increasingly high throughput characterization and examination of their effects. (Escher et al, 2020) One substance group of high relevance for human health (both via food production and for exposure) is pesticides. (Escher et al, 2020) One substance group of high relevance for human health (both via food production and for exposure) is pesticides. Despite their usefulness, they pose po tential risks to food safety, the environment, and living organisms. (Sinclair and Boxall, 2003) While their occurrence and significance are reasonably well-known in research circles, it is still difficult to access information on TPs in a central and “FAIR” (Findable, Accessible, Interoperable and Reusable) (Sansone et al, 2019) manner, with much valuable information documented as detailed reaction schemes (e.g. as images) or descriptive text in regulatory reports that are not always or publicly accessible. The SWISSPEST suspect list was a starting point for the pesticide suspect list developed in this work, with addi tional chemicals of local relevance added as described below (note: SWISSPEST19 was published in parallel during the early stages of this work)
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