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Forcisi, S. ; Moritz, F. ; Lucio, M. ; Lehmann, R. ; Stefan, N. ; Schmitt-Kopplin, P.

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)

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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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Publication type Article: Journal article

Document type Scientific Article

Corresponding Author

ISSN (print) / ISBN 0003-2700

e-ISSN 1520-6882

Journal Analytical Chemistry

Quellenangaben Volume: 87, Issue: 17, Pages: 8917-8924

Publisher American Chemical Society (ACS)

Non-patent literature Publications

Reviewing status Peer reviewed

Institute(s) Research Unit BioGeoChemistry and Analytics (BGC)
Institute of Diabetes Research and Metabolic Diseases (IDM)
German Center for Diabetes Reseach (DZD)