Simultaneous Determination and Analysis of Major Ginsenosides in Wild American Ginseng Grown in Tennessee

Effects of saponins Rb1 and Re in American ginseng combined intervention on immune system of aging model

Aging is a major risk factor for the development of many pathological processes, such as reduced immunity, cancer, cardiovascular diseases or neurodegenerative diseases, while age-related chronic diseases are the most common causes of death. This paper studies the effects of American ginseng saponin Rb1 and Re alone and combined intervention on the immune system of aging mouse models, by using 30 mg/kg Rb1, 15 mg/kg Re, and Rb1 + Re (30 mg/kg Rb1 and 15 mg/kg Re (co-intervention) was used to intervene in the aging model, and immune indicators such as thymus index, spleen index, interleukin and interferon were detected to evaluate the impact of Rb1 and Re on immune function. The results show that Rb1 and Re intervention alone can increase the spleen index by 7%-12% and the thymus index by 12%-19% in the aging model. After Rb1 or Re alone intervened, the apoptotic cells in the thymus were slightly reduced, and the proportion of apoptotic cells was reduced. The combination of Rb1 + Re can promote the thymus index and spleen index to increase by 23.40% and 25.5% respectively, which is more advantageous than Rb1 or Re alone. In addition, Rb1 and Re intervention can reduce the level of interferon INF to a level comparable to that of young mice. Rb1 + Re can not only reduce the INF content, but also reduce the TNF content. The above results show that American ginseng saponin Rb1 and Re can delay the decline of the immune system in the aging model, and the combined intervention of the two is significantly better than individual intervention in the recovery of the immune system. This paper can provide theoretical basis and data support for the development of American ginseng nutritional supplements and its application in aging groups products to improve immunity.

A systematic review of ginsenoside biosynthesis, spatiotemporal distribution, and response to biotic and abiotic factors in American ginseng

American ginseng (Panax quinquefolius) has gained recognition as a medicinal and functional food homologous product with several pharmaceutical, nutritional, and industrial applications. However, the key regulators involved in ginsenoside biosynthesis, the spatiotemporal distribution characteristics of ginsenosides, and factors influencing ginsenosides are largely unknown, which make it challenging to enhance the quality and chemical extraction processes of the cultivated American ginseng. This review presents an overview of the pharmacological effects, biosynthesis and spatiotemporal distribution of ginsenosides, with emphasis on the impacts of biotic and abiotic factors on ginsenosides in American ginseng. Modern pharmacological studies have demonstrated that American ginseng has neuroprotective, cardioprotective, antitumor, antidiabetic, and anti-obesity effects. Additionally, most genes involved in the upregulation of ginsenoside biosynthesis have been identified, while downstream regulators (OSCs, CYP450, and UGTs) require further investigation. Futhermore, limited knowledge exists regarding the molecular mechanisms of the impact of biotic and abiotic factors on ginsenosides. Notably, the nonmedicinal parts of American ginseng, particularly its flowers, fibrous roots, and leaves, exhibit higher ginsenoside content than its main roots and account for a considerable amount of weight in the whole plant, representing promising resources for ginsenosides. Herein, the prospects of molecular breeding and metabolic engineering based on multi-omics to improve the unstable quality of cultivated American ginseng and the shortage of ginsenosides are proposed. This review highlights the gaps in the current research on American ginseng and proposes solutions to address these limitations, providing a guide for future investigations into American ginseng ginsenosides.

Anti-inflammatory and anti-oxidant properties of Melianodiol on DSS-induced ulcerative colitis in mice

Background

Ulcerative colitis is a unique inflammatory bowel disease with ulcerative lesions of the colonic mucosa. Melianodiol (MN), a triterpenoid, isolated from the fruits of the Chinese medicinal plant Melia azedarach, possesses significant anti-inflammatory properties.

Objective

The present study investigated the protective effects of MN on lipopolysaccharide (LPS)-induced macrophages and DSS-mediated ulcerative colitis in mice.

Methods

In the study, mice were given MN (50, 100, and 200 mg/kg) and 5-ASA (500 mg/kg) daily for 9 days after induction by DSS for 1 week. The progress of the disease was monitored daily by observation of changes in clinical signs and body weight.

Results

The results showed that MN effectively improved the overproduction of inflammatory factors (IL-6, NO, and TNF-α) and suppressed the activation of the NF-κB signalling cascade in LPS-mediated RAW264.7 cells. For DSS-mediated colitis in mice, MN can reduce weight loss and the disease activity index (DAI) score in UC mice, suppress colon shortening, and alleviate pathological colon injury. Moreover, MN treatment notably up regulated the levels of IL-10 and down regulated those of IL-1β and TNF-α, and inhibited the protein expression of p-JAK2, p-STAT3, iNOS, NF-κB P65, p-P65, p-IKKα/β, and p-IκBα in the colon. After MN treatment, the levels of MDA and NO in colonic tissue were remarkably decreased, whereas the levels of GSH, SOD, Nrf-2, Keap-1, HO-1, IκBα, and eNOS protein expression levels were significantly increased.

Conclusion

These results indicate that MN can activate the Nrf-2 signalling pathway and inhibit the JAK/STAT, iNOS/eNOS, and NF-κB signalling cascades, enhance intestinal barrier function, and effectively reduce the LPS-mediated inflammatory response in mouse macrophages and DSS-induced intestinal injury in UC.

A New Mechanism for Ginsenoside Rb1 to Promote Glucose Uptake, Regulating Riboflavin Metabolism and Redox Homeostasis

Glucose absorption promoters perform insulin mimic functions to enhance blood glucose transport to skeletal muscle cells and accelerate glucose consumption, thereby reducing blood glucose levels. In our screening exploration of food ingredients for improving glucose transportation and metabolism, we found that the saponins in American ginseng (Panaxquinquefolius L.) showed potential activity to promote glucose uptake, which can be used for stabilizing levels of postprandial blood glucose. The aim of this study was to identify key components of American ginseng with glucose uptake-promoting activity and to elucidate their metabolic regulatory mechanisms. Bio-guided isolation using zebrafish larvae and 2-NBDG indicator identified ginsenoside Rb1 (GRb1) as the most potential promotor of glucose uptake. Using UPLC-QTOF-MS/MS combined with RT-qPCR and phenotypic verification, we found that riboflavin metabolism is the hinge for GRb1-mediated facilitation of glucose transport. GRb1-induced restoration of redox homeostasis was mediated by targeting riboflavin transporters (SLC52A1 and SLC52A3) and riboflavin kinase (RFK).

Identification of key pharmacodynamic markers of American ginseng against heart failure based on metabolomics and zebrafish model

Background: American ginseng (Panax quinquefolium L., AG) is a traditional Chinese medicine with multiple cardiovascular protective properties. Many bioactive components have been discovered in AG over these years. However, the understanding of these key pharmacodynamic components of activity against heart failure is insufficient.

Methods: A heart failure model was established using AB line wild-type zebrafish (Danio rerio) to evaluate the anti-heart failure activity of AG. Untargeted metabolomics analysis based on ultra-high performance liquid chromatography-quadrupole electrostatic field orbitrap-mass spectrometry technology (UHPLC-QE-Orbitrap-MS) was performed to screen differential components from AG samples. The potential active components were verified using the zebrafish model. Simultaneously, network pharmacology and molecular docking techniques were used to predict the possible mechanism. Finally, the key targets of six key pharmacodynamic components were verified in zebrafish using quantitative real-time-polymerase chain reaction (Q-PCR) techniques.

Results: The heart failure model was successfully established in 48 h of post-fertilization (hpf) zebrafish larvae by treating with verapamil hydrochloride. The zebrafish assay showed that the anti-heart failure effects of AG varied with producing regions. The result of the herbal metabolomic analysis based on UHPLC-QE-Orbitrap-MS indicated that ginsenoside Rg3, ginsenoside Rg5, ginsenoside Rg6, malic acid, quinic acid, L-argininosuccinic acid, 3-methyl-3-butenyl-apinosyl (1→6) glucoside, pseudoginsenoside F11, and annonaine were differential components, which might be responsible for variation in efficacy. Further analysis using zebrafish models, network pharmacology, and Q-PCR techniques showed that ginsenoside Rg3, ginsenoside Rg5, ginsenoside Rg6, malic acid, quinic acid, and pseudoginsenoside F11 were the pharmacodynamic markers (P-markers) responsible for anti-heart failure.

Conclusion: We have rapidly identified the P-markers against heart failure in AG using the zebrafish model and metabolomics technology. These P-markers may provide new reference standards for quality control and new drug development of AG.

Characterization of a Group of UDP-Glycosyltransferases Involved in the Biosynthesis of Triterpenoid Saponins of Panax notoginseng

UDP-glycosyltransferase (UGT)-mediated glycosylation is a common modification in triterpene saponins, which exhibit a wide range of bioactivities and important pharmacological effects. However, few UGTs involved in saponin biosynthesis have been identified, limiting the biosynthesis of saponins. In this study, an efficient heterologous expression system was established for evaluating the UGT-mediated glycosylation process of triterpene saponins. Six UGTs (UGTPn17, UGTPn42, UGTPn35, UGTPn87, UGTPn19, and UGTPn12) from Panax notoginseng were predicted and found to be responsible for efficient and direct enzymatic biotransformation of 21 triterpenoid saponins via 26 various glycosylation reactions. Among them, UGTPn87 exhibited promiscuous sugar-donor specificity of UDP-glucose (UDP-Glc) and UDP-xylose (UDP-Xyl) by catalyzing the elongation of the second sugar chain at the C3 or/and C20 sites of protopanaxadiol-type saponins with a UDP-Glc or UDP-Xyl donor, as well as at the C20 site of protopanaxadiol-type saponins with a UDP-Glc donor. Two new saponins, Fd-Xyl and Fe-Xyl, were generated by catalyzing the C3-O-Glc xylosylations of notoginsenoside Fd and notoginsenoside Fe when incubated with UGTPn87. Moreover, the complete biosynthetic pathways of 17 saponins were elucidated, among which notoginsenoside L, vinaginsenoside R16, gypenoside LXXV, and gypenoside XVII were revealed in Panax for the first time. A yeast cell factory was constructed with a yield of Rh2 at 354.69 mg/L and a glycosylation ratio of 60.40% in flasks. Our results reveal the biosynthetic pathway of a group of saponins in P. notoginseng and provide a theoretical basis for producing rare and valuable saponins, promoting their industrial application in medicine and functional foods.

Machine learning methods to predict the cultivation age of Panacis Quinquefolii Radix

Background

American ginseng (AG) is a valuable medicine widely consumed as a herbal remedy throughout the world. Huge price difference among AG with different growth years leads to intentional adulteration for higher profits. Thus, developing reliable approaches to authenticate the cultivation ages of AG products is of great use in preventing age falsification.

Methods

A total of 106 batches of AG samples along with their 9 physicochemical features were collected and measured from experiments, which was then split into a training set and two test sets (test set 1 and 2) according to the cultivation regions. Principle component analysis (PCA) was carried out to examine the distribution of the three data sets. Four machine learning (ML) algorithms, namely elastic net, k-nearest neighbors, support vector machine and multi-layer perception (MLP) were employed to construct predictive models using the features as inputs and their growth years as outputs. In addition, a similarity-based applicability domain (AD) was defined for these models to ensure the reliability of the predictive results for AG samples produced in different regions.

Results

A positive correlation was observed between the several features and the growth years. PCA revealed diverse distributions among different cultivation regions. The most accurate model derived from MLP shows good prediction power for the fivefold cross validation and the test set 1 with mean square error (MSE) of 0.017 and 0.016 respectively, but a higher MSE value of 1.260 for the test set 2. After applying the AD, all models showed much lower prediction errors for the test samples within AD (IDs) than those outside the AD (ODs). MLP remains the best predictive model with an MSE value of 0.030 for the IDs.

Conclusion

Cultivation years have a close relationship with bioactive components of AG. The constructed models and AD are also able to predict the cultivation years and discriminate samples that have inaccurate prediction results. The AD-equipped models used in this study provide useful tools for determining the age of AG in the market and are freely available at https://github.com/dreadlesss/Panax_age_predictor.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13020-021-00511-5.