Improving data quality in liquid chromatography-mass spectrometry metabolomics of human urine

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dc.creatorRosilene Cristina Rossetto Burgos
dc.creatorAdriana Nori de Macedo
dc.creatorPedro Luis Rocha da Cruz
dc.creatorHélio Tedesco-Silva Júnior
dc.creatorKarina Helena Morais Cardozo
dc.creatorValdemir Melechco Carvalho
dc.creatorMarina Franco Maggi Tavares
dc.date.accessioned2023-06-29T17:02:31Z
dc.date.accessioned2025-09-09T01:00:58Z
dc.date.available2023-06-29T17:02:31Z
dc.date.issued2021
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
dc.description.sponsorshipFAPESP - Fundação de Amparo à Pesquisa do Estado de São Paulo
dc.description.sponsorshipOutra Agência
dc.identifier.doihttps://doi.org/10.1016/j.chroma.2021.462457
dc.identifier.issn0021-9673
dc.identifier.urihttps://hdl.handle.net/1843/55546
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofJournal of Chromatography A
dc.rightsAcesso Restrito
dc.subjectCromatografia líquida
dc.subjectControle de qualidade
dc.subjectEspectrometria de massa
dc.subjectPreparação de amostra (Química)
dc.subjectUrina - Análise
dc.subject.otherDivert valve
dc.subject.otherColumn cleanup
dc.subject.otherUntargeted metabolomics
dc.subject.otherLiquid chromatography
dc.subject.otherQuality control
dc.subject.otherMass spectrometry
dc.titleImproving data quality in liquid chromatography-mass spectrometry metabolomics of human urine
dc.typeArtigo de periódico
local.citation.spage462457
local.citation.volume1654
local.description.resumoSignal variation is a common drawback in untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS), mainly due to the complexity of biological matrices and reduced sample preparation, which results in the accumulation of sample components in the column and the ion source. Here we propose a simple, easy to implement approach to improve data quality in untargeted metabolomics by LC-MS. This approach involves the use of a divert valve to direct the column effluent to waste at the beginning of the chromatographic run and during column cleanup and equilibration, in combination with longer column cleanups in between injections. Our approach was tested using urine samples collected from patients after renal transplantation. Analytical responses were contrasted before and after introducing these modifications by analyzing a batch of untargeted metabolomics data. A significant improvement in peak area repeatability was observed for the quality controls, with relative standard deviations (RSDs) for several metabolites decreasing from ∼60% to ∼10% when our approach was introduced. Similarly, RSDs of peak areas for internal standards improved from ∼40% to ∼10%. Furthermore, calibrant solutions were more consistent after introducing these modifications when comparing peak areas of solutions injected at the beginning and the end of each analytical sequence. Therefore, we recommend the use of a divert valve and extended column cleanup as a powerful strategy to improve data quality in untargeted metabolomics, especially for very complex types of samples where minimum sample preparation is required, such as in this untargeted metabolomics study with urine from renal transplanted patients.
local.identifier.orcidhttps://orcid.org/0000-0002-4125-3755
local.identifier.orcidhttps://orcid.org/0000-0002-7734-6056
local.identifier.orcidhttps://orcid.org/0000-0002-9896-323X
local.identifier.orcidhttps://orcid.org/0000-0002-0333-794X
local.identifier.orcidhttps://orcid.org/0000-0002-9816-8615
local.publisher.countryBrasil
local.publisher.departmentICX - DEPARTAMENTO DE QUÍMICA
local.publisher.initialsUFMG
local.url.externahttps://www.sciencedirect.com/science/article/pii/S0021967321005811

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