Phytochemistry by design: a case study of the chemical composition of Ocotea guianensis optimized extracts focused on untargeted metabolomics analysis

Abstract

Untargeted metabolomics aim to provide a global chemical fingerprint of biological matrices. This research field can be used in phytochemical screenings for bioactive species or in the identification of species. Despite its importance in providing a global chemical profile, little research has focused on the optimization of the extraction methods, as each type of matrix requires a specific procedure. Therefore, we propose to evaluate the effect of different extraction features in an ultrasound-assisted extraction for the untargeted metabolomic study of an Ocotea species, a genus of great economical interest but little chemical exploitation. Method optimization was performed in a full factorial 2²3² design, evaluating the solvent composition, extraction temperature, sample particle size and sample : solvent ratio effects in the metabolomic response. The effect of these parameters on the quality of the untargeted metabolomic profiles was studied by analysis of the extraction yield as well as the chromatographic and spectrometric profiles. Most substances identified were glycosylated flavonoids and aporphinic alkaloids. The application of 70% ethanol enhanced the extraction of several specialized metabolites. Statistical analysis of extraction yield and chemical profiles indicates that high temperatures and low proportion between sample and extracting solvent reduce the quality and modify the chemical profile, both qualitatively and quantitatively. The use of 70% ethanol as the extracting solvent, 1 : 12 sample : solvent ratio, 40 °C as the extraction temperature and particle size of 0.595 mm were the optimized conditions to produce a comprehensive chemical profile for Ocotea guianensis.