Krstić Đurđa, Tosti Tomislav, Đurović Saša, Fotirić Akšić Milica, Đorđević Boban, Milojković-Opsenica Dušanka, Andrić Filip, Trifković Jelena
University of Belgrade, Faculty of Chemistry, Studentski trg 12-16, 11158 Belgrade, Serbia.
Institute of General and Physical Chemistry, Studentski trg 12/V, 11158 Belgrade, Serbia.
Food Technol Biotechnol. 2022 Sep;60(3):406-417. doi: 10.17113/ftb.60.03.22.7505.
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.
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).
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.
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.
鉴于食用具有已证实的有益健康特性的浆果的重要性以及特定植物和地理来源产品质量控制方面的困难,基于先进的数据分析(模式识别、分类)开发了一种指纹图谱方法,以便将所选品种中营养成分的变异性与初级代谢物谱相关联。
根据通过三种色谱技术(高效薄层色谱、气相色谱 - 质谱联用和带脉冲安培检测的高效阴离子交换色谱)获得的初级代谢物(糖、脂质和脂肪酸)的色谱图谱,对45个真正的浆果品种(草莓、树莓、黑莓、黑加仑、蓝莓、醋栗、阿月浑子、灯笼果和枸杞)的样本进行了表征。
综合分析允许监测和鉴定属于极性脂质、单酰基甘油、二酰基甘油、三酰基甘油、游离脂肪酸、游离甾醇、甾醇酯、单糖至七糖以及糖醇的代谢物。浆果种子的化学指纹图谱显示了每个果实物种内初级代谢物的一致性,但根据植物来源显示出差异。所有三种色谱方法都提供了一种具有判别性、信息丰富且具有预测性的代谢组学方法,事实证明该方法对化学分类学分类很有用。
描述了一种从天然产物初级代谢物中鉴定生物活性化合物的新方法。所提出的非靶向代谢物谱分析方法未来可作为追踪新型生物活性化合物的常规方法使用。本研究中获得的代谢物组成知识可以更好地评估浆果果实物种和品种之间的基因型和表型差异,并有助于新育种计划的制定。