Primary Metabolite Chromatographic Profiling as a Tool for Chemotaxonomic Classification of Seeds from Berry Fruits

Abstract

Research background. Considering the importance of consumption of berry fruits with proven health-beneficial properties and difficulties in quality control of products of specific botanical and geographic origin, a fingerprint method was developed, based on advanced data analysis (pattern recognition, classification), in order to relate the variability of nutrients in the selected cultivars to primary metabolite profile. Experimental approach. Forty-five samples of genuine berry fruit cultivars (strawberry, raspberry, blackberry, black currant, blueberry, gooseberry, chokeberry, cape gooseberry and goji berry) were characterized according to chromatographic profiles of primary metabolites (sugars, lipids and fatty acids) obtained by three chromatographic techniques (high-performance thin-layer chromatography, gas chromatography coupled to mass spectrometry, and high-performance anion-exchange chromatography with pulsed amperometric detection). Results and conclusions. Comprehensive analysis allowed monitoring and identification of metabolites belonging to polar lipids, mono-, di- and triacylglycerols, free fatty acids, free sterols, sterol esters, mono- to heptasaccharides and sugar alcohols. Chemical fingerprint of berry seeds showed the uniformity of primary metabolites within each fruit species, but revealed differences depending on the botanical origin. All three chromatographic methods provided a discriminative, informative and predictive metabolomics methodology, which proved to be useful for chemotaxonomic classification. Novelty and scientific contribution. A novel methodology for the identification of bioactive compounds from primary metabolites of natural products was described. The proposed untargeted metabolite profiling approach could be used in the future as a routine method for tracing of novel bioactive compounds. The knowledge of metabolite composition obtained in this study can provide a better assessment of genotypic and phenotypic differences between berry fruit species and varieties, and could contribute to the development of new breeding programs.