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Solutions for low and high accuracy mass spectrometric data matching. A data-driven annotation strategy in non-targeted metabolomics.

Anal. Chem. 87, 8917-8924 (2015)
Postprint DOI PMC
Open Access Green
Ultra High Pressure Liquid Chromatography coupled to mass spectrometry (UHPLC-MS) has become a widespread analytical technique in metabolomics investigations, however the benefit of high performance chromatographic separation is often blunted due to insufficient mass spectrometric accuracy. A strategy that allows for the matching of UHPLC-MS data to highly accurate Direct Infusion Electrospray Ionization (DI-ESI) Fourier Transform Ion Cyclotron Resonance / Mass Spectrometry (FT-ICR/MS) data is developed in this manuscript. Mass difference network (MDiN) based annotation of FT-ICR/MS data and matching to unique UHPLC-MS peaks enables the consecutive annotation of the chromatographic dataset. A direct comparison of experimental m/z values provided no basis for the matching of both platforms. The matching of annotation-based exact neutral masses finally enabled the integration of platform specific multivariate statistical evaluations, minimizing the danger to compare artifacts generated on either platform. The approach was developed on a Non-Alcoholic Fatty Liver disease (NAFLD) dataset.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Sprache englisch
Veröffentlichungsjahr 2015
HGF-Berichtsjahr 2015
ISSN (print) / ISBN 0003-2700
e-ISSN 1520-6882
Zeitschrift Analytical Chemistry
Quellenangaben Band: 87, Heft: 17, Seiten: 8917-8924 Artikelnummer: , Supplement: ,
Verlag American Chemical Society (ACS)
Begutachtungsstatus Peer reviewed
POF Topic(s) 30202 - Environmental Health
90000 - German Center for Diabetes Research
Forschungsfeld(er) Environmental Sciences
Helmholtz Diabetes Center
PSP-Element(e) G-504800-001
G-502400-001
G-502400-002
G-501900-481
PubMed ID 26197019
Scopus ID 84941007543
Erfassungsdatum 2015-08-05