In-source fragmentation and correlation analysis as tools for metabolite identification exemplified with CE-TOF untargeted metabolomics

Godzien, J., Armitage, E. G. , Angulo, S., Martinez-Alcazar, M. P., Alonso-Herranz, V., Otero, A., Lopez-Gonzalvez, A. and Barbas, C. (2015) In-source fragmentation and correlation analysis as tools for metabolite identification exemplified with CE-TOF untargeted metabolomics. Electrophoresis, 36(18), pp. 2188-2195. (doi: 10.1002/elps.201500016) (PMID:25754920)

Abstract

The role of non-targeted metabolomics with its discovery power is constantly growing in many different fields of science. However, its biggest advantage of uncovering the unexpected is turning into one of its biggest bottlenecks, particularly in metabolite identification. Among different methods for metabolite identification or ID confirmation, tandem MS analysis plays a very important role. However, this method is limited to only certain types of MS analysers, making for example TOF-MS inaccessible for this type of metabolite identification. To overcome this, in-source fragmentation has been used to fragment molecules and obtain product ions. Since the molecule of interest is not isolated prior to its fragmentation, the acquired spectrum contains many different signals arising from the fragmentation of all compounds present in the sample. Therefore, to assign product ions to their precursors, a novel use of correlation analysis was tested with r ≥0.9 as an assignation of a product ion belonging to the precursor. This method and chosen cut-off was tested on three different sample complexity levels: conducting the analysis on a single standard, mix of co-eluting standards and on a plasma sample. Obtained results clearly proved the effectiveness of the proposed methodology for metabolite ID confirmation. Moreover, the proposed strategy can be successfully applied for semi-quantification of co-eluting molecules with the same monoisotopic mass but that differ in fragmentation pattern. The proposed methodology can greatly improve the robustness and throughput of identification in metabolomics studies by use of TOF-MS, which is crucial to obtain meaningful and trustful results.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Armitage, Dr Emily Grace
• Authors: Godzien, J., Armitage, E. G., Angulo, S., Martinez-Alcazar, M. P., Alonso-Herranz, V., Otero, A., Lopez-Gonzalvez, A., and Barbas, C.
• College/School: College of Medical Veterinary and Life Sciences > School of Infection & Immunity
• Journal Name: Electrophoresis
• Publisher: Wiley-VHC Verlag
• ISSN: 0173-0835
• ISSN (Online): 1522-2683
• Published Online: 06 May 2015