High-speed countercurrent chromatography with offline detection by electrospray mass spectrometry and nuclear magnetic resonance detection as a tool to resolve complex mixtures: A practical approach using Coffea arabica leaf extract

IntroductionMany secondary metabolites isolated from plants have been described in the literature owing to their important biological properties and possible pharmacological applications. However, the identification of compounds present in complex plant extracts has remained a great scientific challenge, is often laborious, and requires a long research time with high financial cost. ObjectivesThe aim of this study was to develop a method that allows the identification of secondary metabolites in plant extracts with a high degree of confidence in a short period of time. Material and methodsIn this study, an ethanolic extract of Coffea arabica leaves was used to validate the proposed method. Countercurrent chromatography was chosen as the initial step for extraction fractionation using gradient elution. Resulting fractions presented a variation of compounds concentrations, allowing for statistical total correlation spectroscopy (STOCSY) calculations between liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) and NMR across fractions. ResultsThe proposed method allowed the identification of 57 compounds. Of the annotated compounds, 20 were previously described in the literature for the species and 37 were reported for the first time. Among the inedited compounds, we identified flavonoids, alkaloids, phenolic acids, coumarins, and terpenes. ConclusionThe proposed method presents itself as a valid alternative for the study of complex extracts in an effective, fast, and reliable way that can be reproduced in the study of other extracts.

Automated summary

This study aimed to develop a method for the identification of secondary metabolites in plant extracts with high confidence in a short time. By using countercurrent chromatography, liquid chromatography coupled with high-resolution tandem mass spectrometry, and statistical total correlation spectroscopy, a total of 57 compounds were identified in an ethanolic extract of Coffea arabica leaves, with 20 compounds previously described and 37 compounds reported for the first time. This method can be effectively, rapidly, and reliably applied to the study of other complex extracts.