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Retention projection enables accurate calculation of liquid chromatographic retention times across labs and methods.
Abate-Pella, Daniel; Freund, Dana M; Ma, Yan; Simón-Manso, Yamil; Hollender, Juliane; Broeckling, Corey D; Huhman, David V; Krokhin, Oleg V; Stoll, Dwight R; Hegeman, Adrian D; Kind, Tobias; Fiehn, Oliver; Schymanski, Emma L; Prenni, Jessica E; Sumner, Lloyd W; Boswell, Paul G.
Afiliação
  • Abate-Pella D; Department of Horticultural Science, University of Minnesota, 1970 Folwell Ave., St. Paul, MN 55108, USA. Electronic address: abate006@umn.edu.
  • Freund DM; Department of Horticultural Science, University of Minnesota, 1970 Folwell Ave., St. Paul, MN 55108, USA. Electronic address: dfreund@umn.edu.
  • Ma Y; UC Davis Genome Center, Metabolomics, University of California, Davis, Health Sciences Drive, Davis, CA 95616, USA. Electronic address: yanma@ucdavis.edu.
  • Simón-Manso Y; Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, MD 20899-8380, USA. Electronic address: yamil.simon@nist.gov.
  • Hollender J; Eawag: Swiss Federal Institute for Aquatic Science and Technology, Überlandstrasse 133, 8600 Dübendorf, Switzerland. Electronic address: Juliane.Hollender@eawag.ch.
  • Broeckling CD; Proteomics and Metabolomics Facility, Colorado State University, Fort Collins, CO 80523, USA. Electronic address: corey.broeckling@colostate.edu.
  • Huhman DV; The Samuel Roberts Noble Foundation, Ardmore, OK 73401, USA. Electronic address: DVHUHMAN@noble.org.
  • Krokhin OV; Department of Internal Medicine, University of Manitoba, 799 JBRC, 715 McDermot Avenue, Winnipeg R3E 3P4, Canada. Electronic address: krokhino@cc.umanitoba.ca.
  • Stoll DR; Department of Chemistry, Gustavus Adolphus College, 800 West College Avenue, Saint Peter, MN 56082, USA. Electronic address: dstoll@gustavus.edu.au.
  • Hegeman AD; Department of Horticultural Science, University of Minnesota, 1970 Folwell Ave., St. Paul, MN 55108, USA. Electronic address: hegem007@umn.edu.
  • Kind T; UC Davis Genome Center, Metabolomics, University of California, Davis, Health Sciences Drive, Davis, CA 95616, USA. Electronic address: tkind@ucdavis.edu.
  • Fiehn O; UC Davis Genome Center, Metabolomics, University of California, Davis, Health Sciences Drive, Davis, CA 95616, USA; King Abdullaziz University, Department of Biochemistry, Jeddah, Saudi Arabia. Electronic address: ofiehn@ucdavis.edu.
  • Schymanski EL; Eawag: Swiss Federal Institute for Aquatic Science and Technology, Überlandstrasse 133, 8600 Dübendorf, Switzerland. Electronic address: emma.schymanski@eawag.ch.
  • Prenni JE; Proteomics and Metabolomics Facility, Colorado State University, Fort Collins, CO 80523, USA. Electronic address: Jessica.Prenni@colostate.edu.
  • Sumner LW; The Samuel Roberts Noble Foundation, Ardmore, OK 73401, USA. Electronic address: lwsumner@noble.org.
  • Boswell PG; Department of Horticultural Science, University of Minnesota, 1970 Folwell Ave., St. Paul, MN 55108, USA. Electronic address: boswell@umn.edu.
J Chromatogr A ; 1412: 43-51, 2015 Sep 18.
Article em En | MEDLINE | ID: mdl-26292625
Identification of small molecules by liquid chromatography-mass spectrometry (LC-MS) can be greatly improved if the chromatographic retention information is used along with mass spectral information to narrow down the lists of candidates. Linear retention indexing remains the standard for sharing retention data across labs, but it is unreliable because it cannot properly account for differences in the experimental conditions used by various labs, even when the differences are relatively small and unintentional. On the other hand, an approach called "retention projection" properly accounts for many intentional differences in experimental conditions, and when combined with a "back-calculation" methodology described recently, it also accounts for unintentional differences. In this study, the accuracy of this methodology is compared with linear retention indexing across eight different labs. When each lab ran a test mixture under a range of multi-segment gradients and flow rates they selected independently, retention projections averaged 22-fold more accurate for uncharged compounds because they properly accounted for these intentional differences, which were more pronounced in steep gradients. When each lab ran the test mixture under nominally the same conditions, which is the ideal situation to reproduce linear retention indices, retention projections still averaged 2-fold more accurate because they properly accounted for many unintentional differences between the LC systems. To the best of our knowledge, this is the most successful study to date aiming to calculate (or even just to reproduce) LC gradient retention across labs, and it is the only study in which retention was reliably calculated under various multi-segment gradients and flow rates chosen independently by labs.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Espectrometria de Massas / Cromatografia Líquida de Alta Pressão Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Espectrometria de Massas / Cromatografia Líquida de Alta Pressão Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2015 Tipo de documento: Article