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Factors that influence the quality of metabolomics data in in vitro cell toxicity studies: a systematic survey

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Factors that influence the quality of metabolomics data in in vitro cell toxicity studies: a systematic survey

dc.contributor.author	Moreno Torres, Marta
dc.contributor.author	Garcia Llorens, Guillem
dc.contributor.author	Moro, Erika
dc.contributor.author	Méndez, Rebeca
dc.contributor.author	Quintás Soriano, Guillermo
dc.contributor.author	Castell, José V.
dc.date.accessioned	2023-05-31T13:42:22Z
dc.date.available	2023-05-31T13:42:22Z
dc.date.issued	2021
dc.identifier.citation	Moreno Torres, Marta Garcia Llorens, Guillem Moro, Erika Méndez, Rebeca Quintás Soriano, Guillermo Castell, José V. 2021 Factors that influence the quality of metabolomics data in in vitro cell toxicity studies: a systematic survey Scientific Reports 11 1 22119
dc.identifier.uri	https://hdl.handle.net/10550/87598
dc.description.abstract	REACH (Registration, Evaluation, Authorization and Restriction of Chemicals) is a global strategy and regulation policy of the EU that aims to improve the protection of human health and the environment through the better and earlier identification of the intrinsic properties of chemical substances. It entered into force on 1st June 2007 (EC 1907/2006). REACH and EU policies plead for the use of robust high-throughput 'omic' techniques for the in vitro investigation of the toxicity of chemicals that can provide an estimation of their hazards as well as information regarding the underlying mechanisms of toxicity. In agreement with the 3R's principles, cultured cells are nowadays widely used for this purpose, where metabolomics can provide a real-time picture of the metabolic effects caused by exposure of cells to xenobiotics, enabling the estimations about their toxicological hazards. High quality and robust metabolomics data sets are essential for precise and accurate hazard predictions. Currently, the acquisition of consistent and representative metabolomic data is hampered by experimental drawbacks that hinder reproducibility and difficult robust hazard interpretation. Using the differentiated human liver HepG2 cells as model system, and incubating with hepatotoxic (acetaminophen and valproic acid) and non-hepatotoxic compounds (citric acid), we evaluated in-depth the impact of several key experimental factors (namely, cell passage, processing day and storage time, and compound treatment) and instrumental factors (batch effect) on the outcome of an UPLC-MS metabolomic analysis data set. Results showed that processing day and storage time had a significant impact on the retrieved cell's metabolome, while the effect of cell passage was minor. Meta-analysis of results from pathway analysis showed that batch effect corrections and quality control (QC) measures are critical to enable consistent and meaningful estimations of the effects caused by compounds on cells. The quantitative analysis of the changes in metabolic pathways upon bioactive compound treatment remained consistent despite the concurrent causes of metabolomic data variation. Thus, upon appropriate data retrieval and correction and by an innovative metabolic pathway analysis, the metabolic alteration predictions remained conclusive despite the acknowledged sources of variability.
dc.language.iso	eng
dc.relation.ispartof	Scientific Reports, 2021, vol. 11, num. 1, p. 22119
dc.subject	Productes químics
dc.title	Factors that influence the quality of metabolomics data in in vitro cell toxicity studies: a systematic survey
dc.type	journal article
dc.date.updated	2023-05-31T13:42:23Z
dc.identifier.doi	10.1038/s41598-021-01652-1
dc.identifier.idgrec	153854
dc.rights.accessRights	open access