The integration of GC–MS and LC–MS to assay the metabolomics profiling in Panax ginseng and Panax quinquefolius reveals a tissue- and species-specific connectivity of primary metabolites and ginsenosides accumulation

Abstract

The traditional medicine Ginseng mainly including Panax ginseng and Panax quinquefolius is the most widely consumed herbal product in the world. Despite the extensive investigation of biosynthetic pathway of the active compounds ginsenosides, our current understanding of the metabolic interlink between ginsenosides synthesis and primary metabolism at the whole-plant level. In this study, the tissue-specific profiling of primary and the secondary metabolites in two different species of ginseng were investigated by gas chromatography- and liquid chromatography coupled to mass spectrometry. A complex continuous coordination of primary- and secondary-metabolic network was modulated by tissues and species factors during growth. The results showed that altogether 149 primary compounds and 10 ginsenosides were identified from main roots, lateral roots, stems, petioles and leaves in P. ginseng and P. quinquefolius. The partial least squares-discriminate analysis (PLS-DA) revealed obvious compounds distinction among tissue-specific districts relative to species. To survey the dedication of carbon and nitrogen metabolism in different tissues to the accumulation of ginsenosides, we inspected the tissue-specific metabolic changes. Our study testified that the ginsenosides content was dependent on main roots and lateral roots energy metabolism, whereas independent of leaves and petiole photosynthesis during ginsenosides accumulation. When tow species were compared, the results indicated that high rates of C assimilation to C accumulation are closely associated with ginsenosides accumulation in P. ginseng main roots and P. quinquefolius lateral roots, respectively. Taken together, our results suggest that tissue-specific metabolites profiling dynamically changed in process of ginsenosides biosynthesis, which may offer a new train of thoughts to the mechanisms of the ginsenosides biosynthesis at the metabolite level.

Resolving coral photoacclimation dynamics through coupled photophysiological and metabolomic profiling

“…In order to fully characterize the effect of light shifts on the A. muricata metabolome, we paired GC-MS and LC-MS metabolomic profiling approaches. GC-MS is well recognized as a useful method for identifying primary metabolites with low molecular weight, such as sugars, fatty acids and amino acids (De Vos et al, 2007;Liu et al, 2017). An advantage of GC-MS is that it is highly reproducible, and a number of libraries have been developed to facilitate identification of primary metabolites (De Vos et al, 2007;Lee et al, 2013).…”

“…for distinguishing secondary metabolites, such as terpenoids, alkaloids and phenols (De Vos et al, 2007;Liu et al, 2017). Because secondary metabolites are often species specific (Lee et al, 2013), their identification can be far more challenging, particularly in the absence of species-specific metabolite databases.…”

UV-B Radiation Largely Promoted the Transformation of Primary Metabolites to Phenols in Astragalus mongholicus Seedlings

“…Regarding the complex primary and secondary metabolites fluctuations of higher plants, metabolomics plays a vital role as a suitable tool [15,30]. Metabolomics approaches are becoming more widely used in modern biology [28,31,32].…”

A Widely Metabolomic Analysis Revealed Metabolic Alterations of Epimedium Pubescens Leaves at Different Growth Stages

“…Due to its wide metabolome coverage, high sensitivity and accuracy, LC-MS has been greatly used in medicinal plant metabolomics to analyze a wide range of compounds such as flavonoids, alkaloids, terpenoids, steroids, coumarins, and lignans [11]. It also has gradually been used to characterize the spatio-temporal distribution of medicinal plant metabolites at the metabolomic level [12][13][14]. According to the aim and scope of the undergoing research, metabolomics experiments are generally classified into two types: Untargeted metabolomics analysis and targeted metabolomics analysis [15,16].…”