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Optimizing MS Parameters for Data-Independent Acquisition (DIA) to Enhance Untargeted Metabolomics

2025-11-12Artigo científico Acesso restrito
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datacite.subject.fosCiências Naturais
dc.contributor.authorPinto, Frederico G.
dc.contributor.authorGiddey, Alexander D.
dc.contributor.authorAlmarri, Rouda S. B.
dc.contributor.authorAlkhnbashi, Omer S.
dc.contributor.authorGarrett, Timothy J.
dc.contributor.authorUddin, Mohammed J.
dc.contributor.authorSoares, Nelson C.
dc.date.accessioned2026-01-20T15:54:25Z
dc.date.available2026-01-20T15:54:25Z
dc.date.issued2025-11-12
dc.description.abstractData-Independent Acquisition (DIA) has emerged as a powerful mass spectrometry (MS) strategy for comprehensive metabolomics. This study presents a novel short gradient (13 min) nanosensitive analytical method for human plasma analysis using DIA LC-MS/MS, focusing on in-depth optimization of MS parameters to maximize data quality and metabolite coverage. Key MS parameters, including scan speed, isolation window width, resolution, automatic gain control, and collision energy, were systematically tuned to balance the sensitivity and specificity while minimizing interferences. The optimized method enabled the detection of 2,907 features with 675 annotated compounds, leveraging recent progress in nano-LC-MS/MS for multiomics applications and showcasing the possibility of combining proteomics and metabolomics within a single chromatographic system. Ultimately, a comparison was performed between the data acquired through the DIA and DDA MS approaches in the context of untargeted metabolomics. This optimized analytical method yields more robust and reproducible results, thereby expanding the potential for meaningful discoveries across diverse biological fields.eng
dc.description.sponsorshipThis study was supported by the Center for Applied and Translational Genomics (CATG), Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU), Dubai Health, Dubai, United Arab Emirates. Internal grant MBRU, Dubai Health, College of Medicine grants cycle 2025/2027. Grant Reference No: MRBU-CM-RG2025-14, title; Development of multiomics biomarker test to predict the risk of premature myocardial infarction (MI) in the UAE. Frederico G. Pinto thanks the National Council for Scientific and Technological Development - CNPq/Brazil (308264/2022-3). TOC graphic created BioRender.com.
dc.identifier.citationJ Proteome Res. 2025 Dec 5;24(12):6311-6319. doi: 10.1021/acs.jproteome.5c00622. Epub 2025 Nov 12
dc.identifier.doi10.1021/acs.jproteome.5c00622
dc.identifier.eissn1535-3907
dc.identifier.issn1535-3893
dc.identifier.urihttp://hdl.handle.net/10400.18/10728
dc.language.isoeng
dc.peerreviewedyes
dc.publisherAmerican Chemical Society
dc.relation.hasversionhttps://pubs.acs.org/doi/10.1021/acs.jproteome.5c00622
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectData-Independent Acquisition
dc.subjectHuman Plasma
dc.subjectMass Spectrometry
dc.subjectMetabolomics
dc.subjectGenómica Funcional e Estrutural
dc.titleOptimizing MS Parameters for Data-Independent Acquisition (DIA) to Enhance Untargeted Metabolomicseng
dc.typejournal article
dcterms.referenceshttps://pubs.acs.org/doi/10.1021/acs.jproteome.5c00622?goto=supporting-info
dspace.entity.typePublication
oaire.citation.endPage6319
oaire.citation.issue12
oaire.citation.startPage6311
oaire.citation.titleJournal of Proteome Research
oaire.citation.volume24
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85

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