Journal Articles Trends in Analytical Chemistry Year : 2024

Harmonized quality assurance/quality control provisions to assess completeness and robustness of MS1 data preprocessing for LC-HRMS-based suspect screening and non-targeted analysis

1 Irset - Institut de recherche en santé, environnement et travail
2 EHESP - École des Hautes Études en Santé Publique
3 MU / MUNI - Masaryk University [Brno] = Masarykova univerzita [Brno] = Université Masaryk [Brno]
4 EAWAG - Swiss Federal Institute of Aquatic Science and Technology [Dübendorf]
5 IBP - Institute of Biogeochemistry and Pollutant Dynamics [ETH Zürich]
6 UFZ - Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research
7 UBA - German Federal Environmental Agency / Umweltbundesamt
8 SLU - Swedish University of Agricultural Sciences = Sveriges lantbruksuniversitet
9 KWR Watercycle Research Institute
10 VU - Vrije Universiteit Amsterdam [Amsterdam]
11 UR EABX - Ecosystèmes aquatiques et changements globaux
12 Plateforme Bordeaux Metabolome
13 E20 - Metatoul AXIOM
14 ToxAlim - ToxAlim
15 LABERCA - Laboratoire d'étude des Résidus et Contaminants dans les Aliments
16 Aristotle University of Thessaloniki
17 CIRI - Center for Interdisciplinary Research and Innovation
18 DSP - Direction de la Stratégie et des Programmes
19 INRS ( Vandoeuvre lès Nancy) - Institut national de recherche et de sécurité (Vandoeuvre lès Nancy)
20 RECETOX / MUNI - Research Centre for Toxic Compounds in the Environment [Brno]
21 IJS - Jozef Stefan Institute [Ljubljana]
22 WFSR - Wageningen Food Safety Research
23 IMU - Innsbruck Medical University = Medizinische Universität Innsbruck
24 PBM - Pesticides et Biotoxines Marines
25 uni.lu - Université du Luxembourg = University of Luxembourg = Universität Luxemburg
Emilien Jamin
Tina Kosjek
Hans Mol
Julien Parinet

Abstract

Non-targeted and suspect screening analysis using liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) holds great promise to comprehensively characterize complex chemical mixtures. Data preprocessing is a crucial part of the process, however, some limitations are observed: (i) peak-picking and feature extraction might be incomplete, especially for low abundant compounds, and (ii) limited reproducibility has been observed between laboratories and software for detected features and their relative quantification. We first conducted a critical review of existing solutions that could improve the reproducibility of preprocessing for LC-HRMS. Solutions include providing repositories and reporting guidelines, open and modular processing workflows, public benchmark datasets, tools to optimize the data preprocessing and to filter out false positive detections. We then propose harmonized quality assurance/quality control guidelines that would allow to assess the sensitivity of feature detection, reproducibility, integration accuracy, precision, accuracy, and consistency of data preprocessing for human biomonitoring, food and environmental communities.

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hal-04528878 , version 1 (30-05-2024)

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Sarah Lennon, Jade Chaker, Elliott Price, Juliane Hollender, Carolin Huber, et al.. Harmonized quality assurance/quality control provisions to assess completeness and robustness of MS1 data preprocessing for LC-HRMS-based suspect screening and non-targeted analysis. Trends in Analytical Chemistry, 2024, 174, pp.117674. ⟨10.1016/j.trac.2024.117674⟩. ⟨hal-04528878⟩
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