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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

  • Sarah Lennon
  • , Jade Chaker
  • , Elliott J. Price
  • , Juliane Hollender
  • , Carolin Huber
  • , Tobias Schulze
  • , Lutz Ahrens
  • , Frederic Béen
  • , Nicolas Creusot
  • , Laurent Debrauwer
  • , Gaud Dervilly
  • , Catherine Gabriel
  • , Thierry Guérin
  • , Baninia Habchi
  • , Emilien L. Jamin
  • , Jana Klánová
  • , Tina Kosjek
  • , Bruno Le Bizec
  • , Jeroen Meijer
  • , Hans Mol
  • Rosalie Nijssen, Herbert Oberacher, Nafsika Papaioannou, Julien Parinet, Dimosthenis Sarigiannis, Michael A. Stravs, Žiga Tkalec, Emma L. Schymanski, Marja Lamoree, Jean Philippe Antignac, Arthur David*
*Corresponding author for this work

Research output: Contribution to JournalReview articleAcademicpeer-review

213 Downloads (Pure)

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.

Original languageEnglish
Article number117674
Pages (from-to)1-13
Number of pages13
JournalTrAC - Trends in Analytical Chemistry
Volume174
Early online date27 Mar 2024
DOIs
Publication statusPublished - May 2024

Bibliographical note

Publisher Copyright:
© 2024 Elsevier B.V.

Funding

This work was supported by the project Partnership for the Assessment of Risks from Chemicals (PARC) funded by the European Union research and innovation program Horizon Europe [grant numbers 101057014]. SL, JC and AD acknowledge the research infrastructure France Exposome. EJP, JK and \u017DT acknowledge the research infrastructure RECETOX RI (LM2023069), H2020 CETOCOEN Excellence 857560 and OP RDE CZ.02.1.01/0.0/0.0/17_043/0009632).

FundersFunder number
European Union research and innovation program Horizon Europe101057014, LM2023069
Horizon 2020 Framework Programme857560, OP RDE CZ.02.1.01/0.0/0.0/17_043/0009632
Horizon 2020 Framework Programme

    Keywords

    • Chemical exposome
    • Contaminants of emerging concern
    • Data preprocessing
    • Exposomics
    • Harmonized QA/QC
    • High-resolution mass spectrometry
    • Metabolomics
    • Non-targeted analysis
    • Suspect screening analysis

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