Search

Ginseng, which contains ginsenosides as bioactive compounds, has been regarded as an important traditional medicine for several millennia. However, the genetic background of ginseng remains poorly understood, partly because of the plant's large and complex genome composition. We report the entire genome sequence of Panax ginseng using next-generation sequencing. The 3.5-Gb nucleotide sequence contains more than 60% repeats and encodes 42 006 predicted genes. Twenty-two transcriptome datasets and mass spectrometry images of ginseng roots were adopted to precisely quantify the functional genes. Thirty-one genes were identified to be involved in the mevalonic acid pathway. Eight of these genes were annotated as 3-hydroxy-3-methylglutaryl-CoA reductases, which displayed diverse structures and expression characteristics. A total of 225 UDP-glycosyltransferases (UGTs) were identified, and these UGTs accounted for one of the largest gene families of ginseng. Tandem repeats contributed to the duplication and divergence of UGTs. Molecular modeling of UGTs in the 71st, 74th, and 94th families revealed a regiospecific conserved motif located at the N-terminus. Molecular docking predicted that this motif captures ginsenoside precursors. The ginseng genome represents a valuable resource for understanding and improving the breeding, cultivation, and synthesis biology of this key herb.

In the face of the global epidemic of metabolic syndrome (MetS) and its strong association with the increasing rate of cardiovascular morbidity and mortality, it is critical to detect MetS at an early stage in the clinical setting to implement preventive intervention long before the complications arise. Lipopolysaccharide, the cell wall component of Gram-negative bacteria produced from diet-disrupted gut microbiota, has been shown to induce metabolic endotoxemia, chronic low-grade inflammation, and ultimately insulin resistance. Therefore, ameliorating the inflammation and insulin resistance underlying MetS by gut microbiota-targeted, dietary intervention has gained increasing attention. In this review, we propose using dynamic monitoring of a set of translational biomarkers related with the etiological role of gut microbiota, including lipopolysaccharide binding protein (LBP), C-reactive protein (CRP), fasting insulin, and homeostasis model assessment of insulin resistance (HOMA-IR), for early detection and prevention of MetS via nutritional modulation. LBP initiates the recognition and monomerization of lipopolysaccharide and amplifies host immune responses, linking the gut-derived antigen load and inflammation indicated by the plasma levels of CRP. Fasting plasma insulin and HOMA-IR are measured to evaluate insulin sensitivity that is damaged by pro-inflammatory cytokines. The dynamic monitoring of these biomarkers in high-risk populations may provide translational methods for the quantitative and dynamic evaluation of dysbiosis-induced insulin resistance and the effectiveness of dietary treatment for MetS.