Cargando…

Online Prioritization of Toxic Compounds in Water Samples through Intelligent HRMS Data Acquisition

[Image: see text] LC-HRMS-based nontarget screening (NTS) has become the method of choice to monitor organic micropollutants (OMPs) in drinking water and its sources. OMPs are identified by matching experimental fragmentation (MS2) spectra with library or in silico-predicted spectra. This requires i...

Descripción completa

Detalles Bibliográficos
Autores principales: Meekel, Nienke, Vughs, Dennis, Béen, Frederic, Brunner, Andrea M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8153395/
https://www.ncbi.nlm.nih.gov/pubmed/33724776
http://dx.doi.org/10.1021/acs.analchem.0c04473
_version_ 1783698789612126208
author Meekel, Nienke
Vughs, Dennis
Béen, Frederic
Brunner, Andrea M.
author_facet Meekel, Nienke
Vughs, Dennis
Béen, Frederic
Brunner, Andrea M.
author_sort Meekel, Nienke
collection PubMed
description [Image: see text] LC-HRMS-based nontarget screening (NTS) has become the method of choice to monitor organic micropollutants (OMPs) in drinking water and its sources. OMPs are identified by matching experimental fragmentation (MS2) spectra with library or in silico-predicted spectra. This requires informative experimental spectra and prioritization to reduce feature numbers, currently performed post data acquisition. Here, we propose a different prioritization strategy to ensure high-quality MS2 spectra for OMPs that pose an environmental or human health risk. This online prioritization triggers MS2 events based on detection of suspect list entries or isotopic patterns in the full scan or an additional MS2 event based on fragment ion(s)/patterns detected in a first MS2 spectrum. Triggers were determined using cheminformatics; potentially toxic compounds were selected based on the presence of structural alerts, in silico-fragmented, and recurring fragments and mass shifts characteristic for a given structural alert identified. After MS acquisition parameter optimization, performance of the online prioritization was experimentally examined. Triggered methods led to increased percentages of MS2 spectra and additional MS2 spectra for compounds with a structural alert. Application to surface water samples resulted in additional MS2 spectra of potentially toxic compounds, facilitating more confident identification and emphasizing the method’s potential to improve monitoring studies.
format Online
Article
Text
id pubmed-8153395
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher American Chemical Society
record_format MEDLINE/PubMed
spelling pubmed-81533952021-05-27 Online Prioritization of Toxic Compounds in Water Samples through Intelligent HRMS Data Acquisition Meekel, Nienke Vughs, Dennis Béen, Frederic Brunner, Andrea M. Anal Chem [Image: see text] LC-HRMS-based nontarget screening (NTS) has become the method of choice to monitor organic micropollutants (OMPs) in drinking water and its sources. OMPs are identified by matching experimental fragmentation (MS2) spectra with library or in silico-predicted spectra. This requires informative experimental spectra and prioritization to reduce feature numbers, currently performed post data acquisition. Here, we propose a different prioritization strategy to ensure high-quality MS2 spectra for OMPs that pose an environmental or human health risk. This online prioritization triggers MS2 events based on detection of suspect list entries or isotopic patterns in the full scan or an additional MS2 event based on fragment ion(s)/patterns detected in a first MS2 spectrum. Triggers were determined using cheminformatics; potentially toxic compounds were selected based on the presence of structural alerts, in silico-fragmented, and recurring fragments and mass shifts characteristic for a given structural alert identified. After MS acquisition parameter optimization, performance of the online prioritization was experimentally examined. Triggered methods led to increased percentages of MS2 spectra and additional MS2 spectra for compounds with a structural alert. Application to surface water samples resulted in additional MS2 spectra of potentially toxic compounds, facilitating more confident identification and emphasizing the method’s potential to improve monitoring studies. American Chemical Society 2021-03-16 2021-03-30 /pmc/articles/PMC8153395/ /pubmed/33724776 http://dx.doi.org/10.1021/acs.analchem.0c04473 Text en © 2021 The Authors. Published by American Chemical Society Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Meekel, Nienke
Vughs, Dennis
Béen, Frederic
Brunner, Andrea M.
Online Prioritization of Toxic Compounds in Water Samples through Intelligent HRMS Data Acquisition
title Online Prioritization of Toxic Compounds in Water Samples through Intelligent HRMS Data Acquisition
title_full Online Prioritization of Toxic Compounds in Water Samples through Intelligent HRMS Data Acquisition
title_fullStr Online Prioritization of Toxic Compounds in Water Samples through Intelligent HRMS Data Acquisition
title_full_unstemmed Online Prioritization of Toxic Compounds in Water Samples through Intelligent HRMS Data Acquisition
title_short Online Prioritization of Toxic Compounds in Water Samples through Intelligent HRMS Data Acquisition
title_sort online prioritization of toxic compounds in water samples through intelligent hrms data acquisition
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8153395/
https://www.ncbi.nlm.nih.gov/pubmed/33724776
http://dx.doi.org/10.1021/acs.analchem.0c04473
work_keys_str_mv AT meekelnienke onlineprioritizationoftoxiccompoundsinwatersamplesthroughintelligenthrmsdataacquisition
AT vughsdennis onlineprioritizationoftoxiccompoundsinwatersamplesthroughintelligenthrmsdataacquisition
AT beenfrederic onlineprioritizationoftoxiccompoundsinwatersamplesthroughintelligenthrmsdataacquisition
AT brunnerandream onlineprioritizationoftoxiccompoundsinwatersamplesthroughintelligenthrmsdataacquisition