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HPLC Method Development for Untargeted Metabolomics of Polar Compounds

Publikace na Přírodovědecká fakulta |
2022

Tento text není v aktuálním jazyce dostupný. Zobrazuje se verze "en".Abstrakt

Background: Metabolomic studies offer reflection of an organism actual status. Metabolite profiles can describe microbiota composition in gut microbiota-related research and lead to the discovery of biomarkers, important in the development of methods for nutritional and personalized therapies.

One of the main analytical methods employed in metabolomics is Liquid Chromatography-Mass Spectrometry (LC-MS). Polar compounds are involved in a multitude of important biological processes.

However, these compounds are usually not able to be analyzed by the well-established C18 separation systems. Hydrophilic Interaction LC (HILIC) and multimode columns can be employed to overcome this limitation and amplify the working range of C18.

Methods: In this study, the performance of four commercially available HILIC and two multimode columns was evaluated against C18. Set of conditions with different mobile phases and both ionization modes were compared for the selection of the best chromatographic conditions.

For the purpose of this study, 258 chemical standards were analyzed. The obtained raw data was processed using Agilent MassHunter software and the performance was evaluated in terms of maximal number of detected standards, ability to widened the range of analyzable compounds of C18, and evenness of retention time distribution.

Results: The behavior of polar standards was shown using spider graphs. Maximal amount of standard was detected when using BEH Amide column, using mobile phase pH 3 ammonium formate buffer in ACN and ESI- mode.

All HILIC and multimode columns showed improved retention time distribution in comparison with C18 column. Conclusion: From our results, we conclude that HILIC and multimode enhance C18 column range of polar compounds detection and methods using them have a high potential to be employed in untargeted metabolomics.

Depending on the way the data is organized, these results can be extended to other analytical purposes, etc. to analyze the metabolites involved in specific biosynthetic pathways. Support: Czech Academy of Sciences (Lumina Quaeruntur Program, project number LQ200202002) and Czech Science Foundation (project number 20-09811Y)