Extensively Targeted Metabolomics Analysis of Red and Yellow Wolfberries
-
Graphical Abstract
-
Abstract
In the pursuit of a comprehensive understanding of differential metabolites and metabolic pathways between red wolfberry (Lycium barbarum L.) and yellow wolfberry (Lycium barbarum L. var. auranticarpum K.F.Ching), an analytical approach integrating ultra-performance liquid chromatography with tandem high-resolution mass spectrometry was employed, alongside a broadly targeted metabolomics strategy. Through multivariate statistical methods such as principal component analysis, orthogonal partial least squares discriminant analysis, and cluster analysis, under the conditions of fold change ≥2 or ≤0.5, variable importance projection value ≥1, and P<0.05, 202 differential metabolites (148 up-regulated and 54 down-regulated) were detected in red and yellow wolfberries under positive ion mode. A total of 240 differential metabolites (183 up-regulated and 57 down-regulated) were detected in the negative ion mode. Subsequent KEGG pathway enrichment analysis revealed that these differential metabolites were predominantly associated with secondary metabolite, tryptophan, glucosinolate, valine, isoleucine, leucine, and flavonoid biosynthesis pathways. The data suggested that the differential metabolites in Lycium barbarum L. and Lycium barbarum L. var. auranticarpum K.F.Ching were predominantly flavonoids, alkaloids, phenolic acids, amino acids, and their derivatives, with a general trend of up-regulation. These metabolites might be linked to the growth, development, disease resistance, and nutritional value of Lycium barbarum L. var. auranticarpum K.F.Ching, potentially through their involvement in tryptophan metabolism and biosynthesis pathways for valine, leucine, isoleucine, and flavonoids. The objective of this study was to contribute to the existing knowledge base on the nutritional value of these two wolfberry species and to offer a theoretical foundation for the refinement of wolfberry-related products through extensive metabolomics profiling.
-
-