Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC).



Lippa, Katrice A, Aristizabal-Henao, Juan J, Beger, Richard D, Bowden, John A, Broeckling, Corey, Beecher, Chris, Clay Davis, W, Dunn, Warwick B ORCID: 0000-0001-6924-0027, Flores, Roberto, Goodacre, Royston ORCID: 0000-0003-2230-645X
et al (show 16 more authors) (2022) Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC). Metabolomics : Official journal of the Metabolomic Society, 18 (4). 24 - 24.

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Abstract

<h4>Introduction</h4>The metabolomics quality assurance and quality control consortium (mQACC) is enabling the identification, development, prioritization, and promotion of suitable reference materials (RMs) to be used in quality assurance (QA) and quality control (QC) for untargeted metabolomics research.<h4>Objectives</h4>This review aims to highlight current RMs, and methodologies used within untargeted metabolomics and lipidomics communities to ensure standardization of results obtained from data analysis, interpretation and cross-study, and cross-laboratory comparisons. The essence of the aims is also applicable to other 'omics areas that generate high dimensional data.<h4>Results</h4>The potential for game-changing biochemical discoveries through mass spectrometry-based (MS) untargeted metabolomics and lipidomics are predicated on the evolution of more confident qualitative (and eventually quantitative) results from research laboratories. RMs are thus critical QC tools to be able to assure standardization, comparability, repeatability and reproducibility for untargeted data analysis, interpretation, to compare data within and across studies and across multiple laboratories. Standard operating procedures (SOPs) that promote, describe and exemplify the use of RMs will also improve QC for the metabolomics and lipidomics communities.<h4>Conclusions</h4>The application of RMs described in this review may significantly improve data quality to support metabolomics and lipidomics research. The continued development and deployment of new RMs, together with interlaboratory studies and educational outreach and training, will further promote sound QA practices in the community.

Item Type: Article
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology
Depositing User: Symplectic Admin
Date Deposited: 20 Apr 2022 10:14
Last Modified: 13 Sep 2022 14:10
DOI: 10.1007/s11306-021-01848-6
Open Access URL: https://link.springer.com/article/10.1007/s11306-0...
URI: https://livrepository.liverpool.ac.uk/id/eprint/3153440