Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/36611
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dc.contributor.authorKipura, Tobiasen_UK
dc.contributor.authorHotze, Madlenen_UK
dc.contributor.authorHofer, Alexaen_UK
dc.contributor.authorEgger, Anna-Sophiaen_UK
dc.contributor.authorTimpen, Lea Een_UK
dc.contributor.authorOpitz, Christiane Aen_UK
dc.contributor.authorTownsend, Paul Aen_UK
dc.contributor.authorGethings, Lee Aen_UK
dc.contributor.authorThedieck, Kathrinen_UK
dc.contributor.authorKwiatkowski, Marcelen_UK
dc.date.accessioned2025-03-05T01:02:22Z-
dc.date.available2025-03-05T01:02:22Z-
dc.date.issued2024-06-30en_UK
dc.identifier.other370en_UK
dc.identifier.urihttp://hdl.handle.net/1893/36611-
dc.description.abstractAmino acids (AAs) and their metabolites are important building blocks, energy sources, and signaling molecules associated with various pathological phenotypes. The quantification of AA and tryptophan (TRP) metabolites in human serum and plasma is therefore of great diagnostic interest. Therefore, robust, reproducible sample extraction and processing workflows as well as rapid, sensitive absolute quantification are required to identify candidate biomarkers and to improve screening methods. We developed a validated semi-automated robotic liquid extraction and processing workflow and a rapid method for absolute quantification of 20 free, underivatized AAs and six TRP metabolites using dual-column U(H)PLC-MRM-MS. The extraction and sample preparation workflow in a 96-well plate was optimized for robust, reproducible high sample throughput allowing for transfer of samples to the U(H)PLC autosampler directly without additional cleanup steps. The U(H)PLC-MRM-MS method, using a mixed-mode reversed-phase anion exchange column with formic acid and a high-strength silica reversed-phase column with difluoro-acetic acid as mobile phase additive, provided absolute quantification with nanomolar lower limits of quantification within 7.9 min. The semi-automated extraction workflow and dual-column U(H)PLC-MRM-MS method was applied to a human prostate cancer study and was shown to discriminate between treatment regimens and to identify metabolites responsible for discriminating between healthy controls and patients on active surveillance.en_UK
dc.language.isoenen_UK
dc.publisherMDPI AGen_UK
dc.relationKipura T, Hotze M, Hofer A, Egger A, Timpen LE, Opitz CA, Townsend PA, Gethings LA, Thedieck K & Kwiatkowski M (2024) Automated Liquid Handling Extraction and Rapid Quantification of Underivatized Amino Acids and Tryptophan Metabolites from Human Serum and Plasma Using Dual-Column U(H)PLC-MRM-MS and Its Application to Prostate Cancer Study. <i>Metabolites</i>, 14 (7), Art. No.: 370. https://doi.org/10.3390/metabo14070370en_UK
dc.rights© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_UK
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_UK
dc.subjectamino acidsen_UK
dc.subjecttryptophan metabolites analysisen_UK
dc.subjectautomationen_UK
dc.subjectLC-MSen_UK
dc.subjectmixed-mode chromatographyen_UK
dc.subjectprostate canceren_UK
dc.titleAutomated Liquid Handling Extraction and Rapid Quantification of Underivatized Amino Acids and Tryptophan Metabolites from Human Serum and Plasma Using Dual-Column U(H)PLC-MRM-MS and Its Application to Prostate Cancer Studyen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.3390/metabo14070370en_UK
dc.identifier.pmid39057693en_UK
dc.citation.jtitleMetabolitesen_UK
dc.citation.issn2218-1989en_UK
dc.citation.volume14en_UK
dc.citation.issue7en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderEuropean Commission (Horizon 2020)en_UK
dc.contributor.funderEuropean Commission (Horizon 2020)en_UK
dc.author.emailcatherine.stewart@stir.ac.uken_UK
dc.citation.date30/06/2024en_UK
dc.contributor.affiliationUniversity of Innsbrucken_UK
dc.contributor.affiliationUniversity of Innsbrucken_UK
dc.contributor.affiliationUniversity of Innsbrucken_UK
dc.contributor.affiliationUniversity of Innsbrucken_UK
dc.contributor.affiliationUniversity of Innsbrucken_UK
dc.contributor.affiliationGerman Cancer Research Center (DKFZ)en_UK
dc.contributor.affiliationUniversity of Manchesteren_UK
dc.contributor.affiliationUniversity of Surreyen_UK
dc.contributor.affiliationAlbert Ludwigs University of Freiburgen_UK
dc.contributor.affiliationUniversity of Innsbrucken_UK
dc.identifier.isiWOS:001277410900001en_UK
dc.identifier.scopusid2-s2.0-85199510317en_UK
dc.identifier.wtid2087818en_UK
dc.contributor.orcid0009-0007-4733-893Xen_UK
dc.contributor.orcid0009-0001-1816-2089en_UK
dc.contributor.orcid0009-0003-3207-0230en_UK
dc.contributor.orcid0000-0001-8956-9508en_UK
dc.contributor.orcid0000-0002-5804-6031en_UK
dc.date.accepted2024-06-26en_UK
dcterms.dateAccepted2024-06-26en_UK
dc.date.filedepositdate2025-01-13en_UK
rioxxterms.apcnot requireden_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorKipura, Tobias|0009-0007-4733-893Xen_UK
local.rioxx.authorHotze, Madlen|0009-0001-1816-2089en_UK
local.rioxx.authorHofer, Alexa|en_UK
local.rioxx.authorEgger, Anna-Sophia|en_UK
local.rioxx.authorTimpen, Lea E|0009-0003-3207-0230en_UK
local.rioxx.authorOpitz, Christiane A|en_UK
local.rioxx.authorTownsend, Paul A|0000-0001-8956-9508en_UK
local.rioxx.authorGethings, Lee A|en_UK
local.rioxx.authorThedieck, Kathrin|en_UK
local.rioxx.authorKwiatkowski, Marcel|0000-0002-5804-6031en_UK
local.rioxx.projectInternal Project|University of Stirling|https://isni.org/isni/0000000122484331en_UK
local.rioxx.projectProject ID unknown|European Commission (Horizon 2020)|en_UK
local.rioxx.freetoreaddate2025-03-04en_UK
local.rioxx.licencehttp://creativecommons.org/licenses/by/4.0/|2025-03-04|en_UK
local.rioxx.filenamemetabolites-14-00370.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source2218-1989en_UK
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