Metabolomics method to comprehensively analyze amino acids in different domains

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dc.contributor.authorGu, Haiwei
dc.contributor.authorDu, Jianhai
dc.contributor.authorCarnevale Neto, Fausto [UNESP]
dc.contributor.authorCarroll, Patrick A.
dc.contributor.authorTurner, Sally J.
dc.contributor.authorChiorean, E. Gabriela
dc.contributor.authorEisenmane, Robert N.
dc.contributor.authorRaftery, Daniel
dc.contributor.institutionUniversity of Washington
dc.contributor.institutionEast China Institute of Technology
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionFred Hutchinson Cancer Research Center
dc.contributor.institutionIndiana University
dc.date.accessioned2015-10-21T20:24:18Z
dc.date.available2015-10-21T20:24:18Z
dc.date.issued2015-01-01
dc.description.abstractAmino acids play essential roles in both metabolism and the proteome. Many studies have profiled free amino acids (FAAs) or proteins; however, few have connected the measurement of FAA with individual amino acids in the proteome. In this study, we developed a metabolomics method to comprehensively analyze amino acids in different domains, using two examples of different sample types and disease models. We first examined the responses of FAAs and insoluble-proteome amino acids (IPAAs) to the Myc oncogene in Tet21N human neuroblastoma cells. The metabolic and proteomic amino acid profiles were quite different, even under the same Myc condition, and their combination provided a better understanding of the biological status. In addition, amino acids were measured in 3 domains (FAAs, free and soluble-proteome amino acids (FSPAAs), and IPAAs) to study changes in serum amino acid profiles related to colon cancer. A penalized logistic regression model based on the amino acids from the three domains had better sensitivity and specificity than that from each individual domain. To the best of our knowledge, this is the first study to perform a combined analysis of amino acids in different domains, and indicates the useful biological information available from a metabolomics analysis of the protein pellet. This study lays the foundation for further quantitative tracking of the distribution of amino acids in different domains, with opportunities for better diagnosis and mechanistic studies of various diseases.en
dc.description.affiliationUniversity of Washington, Department of Anesthesiology and Pain Medicine
dc.description.affiliationUniversity of Washington, Department of Biochemistry
dc.description.affiliationUniversity of Washington, Department of Medicine
dc.description.affiliationEast China Institute of Technology, Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation
dc.description.affiliationFred Hutchinson Cancer Research Center, Division os Basic Sciences
dc.description.affiliationFred Hutchinson Cancer Research Center, Public Health Sciences Division
dc.description.affiliationUnespUniversidade Estadual Paulista, Departamento de Química Orgânica, Instituto de Química de Araraquara
dc.description.sponsorshipInstitute of Translational Health Sciences (ITHS)
dc.description.sponsorshipCancer Care Engineering Project at Purdue University (Department of Defense, USAMRMC)
dc.description.sponsorshipChromosome Metabolism and Cancer Training grant
dc.description.sponsorshipChinese National Instrumentation Program
dc.description.sponsorshipNational Natural Science Foundation of China
dc.description.sponsorshipCancer Care Engineering Project at Purdue University (Walther Cancer Foundation)
dc.description.sponsorshipCancer Care Engineering Project at Purdue University (Regenstrief Foundation)
dc.description.sponsorshipIdITHS: 2R01GM085291
dc.description.sponsorshipIdITHS: RO1 CA57138
dc.description.sponsorshipId(Department of Defense, USAMRMC: W81XWH-08-1-0065
dc.description.sponsorshipIdDepartment of Defense, USAMRMC: W81XWH-10-1-0540
dc.description.sponsorshipIdChromosome Metabolism and Cancer Training grant: T32 CA009657
dc.description.sponsorshipIdChinese National Instrumentation Program: 2011YQ170067
dc.description.sponsorshipIdNational Natural Science Foundation of China: 21365001
dc.format.extent2726-2734
dc.identifierhttp://pubs.rsc.org/en/Content/ArticleLanding/2015/AN/C4AN02386B#!divAbstract
dc.identifier.citationAnalyst. Cambridge: Royal Soc Chemistry, v. 140, n. 8, p. 2726-2734, 2015.
dc.identifier.doi10.1039/c4an02386b
dc.identifier.issn0003-2654
dc.identifier.urihttp://hdl.handle.net/11449/129120
dc.identifier.wosWOS:000352141800024
dc.language.isoeng
dc.publisherRoyal Soc Chemistry
dc.relation.ispartofAnalyst
dc.relation.ispartofjcr3.864
dc.relation.ispartofsjr1,249
dc.rights.accessRightsAcesso restrito
dc.sourceWeb of Science
dc.titleMetabolomics method to comprehensively analyze amino acids in different domainsen
dc.typeArtigo
dcterms.licensehttp://www.rsc.org/journals-books-databases/open-access/
dcterms.rightsHolderRoyal Soc Chemistry
unesp.campusUniversidade Estadual Paulista (Unesp), Instituto de Química, Araraquarapt

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