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Integration of non-targeted metabolomics and automated determination of elemental compositions for comprehensive alkaloid profiling in plants. | LitMetric

Integration of non-targeted metabolomics and automated determination of elemental compositions for comprehensive alkaloid profiling in plants.

Phytochemistry

Neuchâtel Platform of Analytical Chemistry, University of Neuchâtel, Avenue de Bellevaux 51, CH-2000 Neuchâtel, Switzerland. Electronic address:

Published: October 2018

AI Article Synopsis

Article Abstract

Plants produce a large array of specialized metabolites to protect themselves. Among these allelochemicals, alkaloids display highly diverse and complex structures that are directly related to their biological activities. Plant alkaloid profiling traditionally requires extensive and time-consuming sample preparation and analysis. Herein, we developed a rapid and efficient approach for the comprehensive profiling of alkaloids in plants using ultrahigh performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS)-based metabolomics. Using automated compound extraction and elemental composition assignment, our method achieved >83% correct alkaloid identification and even >90% for medium to high intensity peaks. This represented a significant improvement in identification rate compared to generic methods used for EC determination with no a priori, such as in untargeted metabolomics studies. The developed approach was then applied to identify specific alkaloids of Aconitum lycoctonum L. and A. napellus L. (Ranunculaceae) using different parts of the plant (leaf, perianth and pollen). Significant differences in alkaloid profiles between the two species were highlighted and discussed under taxonomic and evolutionary perspectives. Taken together, the presented approach constitutes a valuable chemotaxonomic tool in the search for known and unknown alkaloids from plants.

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Source
http://dx.doi.org/10.1016/j.phytochem.2018.06.011DOI Listing

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