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Hendrik Treutler1, Hiroshi Tsugawa2, Andrea Porzel3, Karin Gorzolka1, Alain Tissier4, Steffen Neumann1, and Gerd Ulrich Balcke4*
1Leibniz Institute of Plant Biochemistry, Department of Stress and Developmental Biology, Weinberg 3, D-06120 Halle/Saale, Germany
2RIKEN Center for Sustainable Resource Science, Yokohama, Kanagawa 230-0045, Japan
3Leibniz Institute of Plant Biochemistry, Department of Bioorganic Chemistry, Weinberg 3, D-06120 Halle/Saale, Germany
4Leibniz Institute of Plant Biochemistry, Department of Cell and Metabolic Biology, Weinberg 3, D-06120 Halle/Saale, Germany
*Corresponding author: Gerd Ulrich Balcke Gerd.Balcke@ipb-halle.de
The identification of metabolites by mass spectrometry constitutes a major bottleneck which considerably limits the throughput of metabolomics studies in biomedical or plant research. Here, we present a novel approach to analyze metabolomics data from untargeted, data-independent LC-MS/MS measurements. By integrated analysis of MS¹ abundances and MS/MS spectra, the identification of regulated metabolite families is achieved. This approach offers a global view on metabolic regulation in comparative metabolomics. We implemented our approach in the web application 缬缬缬MetFamily缬缬缬, which is freely available at http://msbi.ipb-halle.de/MetFamily/. MetFamily provides a dynamic link between the patterns based on MS¹-signal intensity and the corresponding structural similarity at the MS/MS level. Structurally related metabolites are annotated as metabolite families based on a hierarchical cluster analysis of measured MS/MS spectra. Joint examination with principal component analysis of MS¹ patterns, where this annotation is preserved in the loadings, facilitates the interpretation of comparative metabolomics data at the level of metabolite families. As a proof of concept, we identified two trichome-specific metabolite families from wild-type tomato Solanum habrochaites LA1777 in a fully unsupervised manner and validated our findings based on earlier publications and with NMR.
Hendrik Treutler, Hiroshi Tsugawa, Andrea Porzel, Karin Gorzolka, Alain Tissier, Steffen Neumann, and Gerd Ulrich U. Balcke.
Discovering Regulated Metabolite Families in Untargeted Metabolomics Studies.
Analytical chemistry, 88(16):8082-8090, August 2016.
Please find a user guide for the usage of the MetFamily web application below.Download user guide
We provide a specification of the input file format. In the MetFamily publication we demonstrated the usage of MetFamily with UPLC-(-)ESI-SWATH-MS/MS data preprocessed with MS-DIAL. In the input specification, however, we demonstrate the generation of these files with GC-EI-MS data processed with xcms and CAMERA We also analyzed idMSMS spectra and LC-MS/MS spectra from DDA in MetFamily.Download input specification
The MetFamily web application is designed to support researchers in the interpretation of comparative metabolomics studies at the level of metabolite families. Please help to improve this tool by comments, bug reports, and feature requests. You can contact Dr. Gerd Balcke via EMail and issues on GitHub.