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Linking MS1 and MS2 signals in positive and negative modes of LC-HRMS in untargeted metabolomics using the ROIMCR approach

dc.contributor.authorYamamoto, Flávia Yoshie [UNESP]
dc.contributor.authorPérez-López, Carlos
dc.contributor.authorLopez-Antia, Ana
dc.contributor.authorLacorte, Silvia
dc.contributor.authorde Souza Abessa, Denis Moledo [UNESP]
dc.contributor.authorTauler, Romà
dc.contributor.institutionJordi Girona
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2025-04-29T20:10:59Z
dc.date.issued2023-10-01
dc.description.abstractData-independent acquisition (DIA) mode in liquid chromatography (LC) high-resolution mass spectrometry (HRMS) has emerged as a powerful strategy in untargeted metabolomics for detecting a broad range of metabolites. However, the use of this approach also represents a challenge in the analysis of the large datasets generated. The regions of interest (ROI) multivariate curve resolution (MCR) approach can help in the identification and characterization of unknown metabolites in their mixtures by linking their MS1 and MS2 DIA spectral signals. In this study, it is proposed for the first time the analysis of MS1 and MS2 DIA signals in positive and negative electrospray ionization modes simultaneously to increase the coverage of possible metabolites present in biological systems. In this work, this approach has been tested for the detection and identification of the amino acids present in a standard mixture solution and in fish embryo samples. The ROIMCR analysis allowed for the identification of all amino acids present in the analyzed mixtures in both positive and negative modes. The methodology allowed for the direct linking and correspondence between the MS signals in their different acquisition modes. Overall, this approach confirmed the advantages and possibilities of performing the proposed ROIMCR simultaneous analysis of mass spectrometry signals in their differing acquisition modes in untargeted metabolomics studies. Graphical Abstract: [Figure not available: see fulltext.]en
dc.description.affiliationDepartment of Environmental Chemistry IDAEA-CSIC Jordi Girona, 18-26
dc.description.affiliationInstitute of Biosciences São Paulo State University
dc.description.affiliationUnespInstitute of Biosciences São Paulo State University
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipMinisterio de Asuntos Económicos y Transformación Digital, Gobierno de España
dc.description.sponsorshipConsejo Superior de Investigaciones Científicas
dc.description.sponsorshipIdFAPESP: 2020/14688-8
dc.description.sponsorshipIdMinisterio de Asuntos Económicos y Transformación Digital, Gobierno de España: PID2019-105732GB-C21
dc.description.sponsorshipIdConsejo Superior de Investigaciones Científicas: Project CEX2018-000794-S
dc.format.extent6213-6225
dc.identifierhttp://dx.doi.org/10.1007/s00216-023-04893-3
dc.identifier.citationAnalytical and Bioanalytical Chemistry, v. 415, n. 25, p. 6213-6225, 2023.
dc.identifier.doi10.1007/s00216-023-04893-3
dc.identifier.issn1618-2650
dc.identifier.issn1618-2642
dc.identifier.scopus2-s2.0-85168115768
dc.identifier.urihttps://hdl.handle.net/11449/308004
dc.language.isoeng
dc.relation.ispartofAnalytical and Bioanalytical Chemistry
dc.sourceScopus
dc.subjectAll-ion fragmentation (AIF)
dc.subjectMetabolite coverage improvement
dc.subjectPositive and negative acquisition modes
dc.subjectROIMCR, Regions of interest multivariate curve resolution
dc.subjectUntargeted metabolomics
dc.titleLinking MS1 and MS2 signals in positive and negative modes of LC-HRMS in untargeted metabolomics using the ROIMCR approachen
dc.typeArtigopt
dspace.entity.typePublication

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