Metabolomic Approach for Discrimination of Cultivation Age and Ripening Stage in Ginseng Berry Using Gas Chromatography-Mass Spectrometry

Research of saccharides and related biocomplexes: A review with recent techniques and applications

Saccharides and biocompounds as saccharide (sugar) complexes have various roles and biological functions in living organisms due to modifications via nucleophilic substitution, polymerization, and complex formation reactions. Mostly, mono-, di-, oligo-, and polysaccharides are stabilized to inactive glycosides, which are formed in metabolic pathways. Natural saccharides are important in food and environmental monitoring. Glycosides with various functionalities are significant in clinical and medical research. Saccharides are often studied with the chromatographic methods of hydrophilic interaction liquid chromatography and anion exchange chromatograpy, but also with capillary electrophoresis and mass spectrometry with their on-line coupling systems. Sample preparation is important in the identification of saccharide compounds. The cases discussed here focus on bioscience, clinical, and food applications.

Metabolomics approach to growth-age discrimination in mountain-cultivated ginseng (Panax ginseng C. A. Meyer) using ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry

Mountain-cultivated ginseng is typically harvested after 10 years, while ginseng aged over 15 years is considered wild ginseng. This study aims to differentiate mountain-cultivated ginseng by age, as the fraudulent practice of selling low-aged cultivated ginseng disguised as high-aged one is damaging the market. In this study, LC-MS analyzed 98 ginseng samples, and multivariate statistical analysis identified patterns between samples to select influential components. Machine learning models were developed to identify ginseng samples of different ages. The untargeted metabolomic analysis clearly divided samples aged 4-20 years into three age groups. Twenty-two potential age-dependent biomarkers were discovered to differentiate the three sample groups. Three machine learning models were used to predict new samples, and the optimal model was selected. Some biomarkers could determine age phases according to the differentiation of mountain-cultivated ginseng samples. These biomarkers were thoroughly analyzed for variation trends. The machine learning models established using the screened biomarkers successfully predicted the age group of new samples.

GC-MS based comparative metabolomic analysis of human cancellous bone reveals the critical role of linoleic acid metabolism in femur head necrosis

INTRODUCTION

Femur head necrosis (FHN) is a challenging clinical disease with unclear underlying mechanism, which pathologically is associated with disordered metabolism. However, the disordered metabolism in cancellous bone of FHN was never analyzed by gas chromatography-mass spectrometry (GC-MS).

OBJECTIVES

To elucidate altered metabolism pathways in FHN and identify putative biomarkers for the detection of FHN.

METHODS

We recruited 26 patients with femur head necrosis and 22 patients with femur neck fracture in this study. Cancellous bone tissues from the femoral heads were collected after the surgery and were analyzed by GC-MS based untargeted metabolomics approach. The resulting data were analyzed via uni- and multivariate statistical approaches. The changed metabolites were used for the pathway analysis and potential biomarker identification.

RESULTS

Thirty-seven metabolites distinctly changed in FHN group were identified. Among them, 32 metabolites were upregulated and 5 were downregulated in FHN. The pathway analysis showed that linoleic acid metabolism were the most relevant to FHN pathology. On the basis of metabolites network, L-lysine, L-glutamine and L-serine were deemed as the junctions of the whole metabolites. Finally, 9,12-octadecadienoic acid, inosine, L-proline and octadecanoic acid were considered as the potential biomarkers of FHN.

CONCLUSION

This study provides a new insight into the pathogenesis of FHN and confirms linoleic acid metabolism as the core.

A novel method for age identification of mountain-cultivated ginseng

Panax ginseng, a slow-growing perennial herb, is the most praised and popular traditional medicinal herb. Mountain-cultivated ginseng (MCG) and cultivated ginseng (CG) both belong to Panax ginseng C. A. Meyer. The market price and medical effects of this popular health product are closely related to its age. It is widely acknowledged that CG is typically harvested after 4-6 years of growth, but MCG is often collected after 10 years. Until now, the age identification of MCG or mountain wild ginseng (MWG) has remained a major challenge. In this study, we established a novel and rapid method for staining xylem vessels with phloroglucinol and identifying the "annual growth rings" of ginseng by utilizing a stereoscope, which serves as a reliable indicator of the age of MCG. Statistical analysis of the ring radius and the ring density of MCG aged from 1 to 20 years shows that the secondary xylem of MCG increases rapidly in the first 3 years but then gradually slows down from 4 to 10 years, and minor fluctuation is observed in the next 10 years. Meanwhile, the space between the growth rings (ring density) becomes increasingly small with age. This straightforward staining approach can reveal the age of MCG with remarkable clarity and can distinguish MCG from CG. RESEARCH HIGHLIGHTS: A novel rapid staining method for Panax ginseng was established. The age of mountain-cultivated ginseng (MCG) can be identified by microscopic techniques. MCG and cultivated ginseng (CG) can be discriminated by microstructure characteristics.

Differentiation of Mountain- and Garden-Cultivated Ginseng with Different Growth Years Using HS-SPME-GC-MS Coupled with Chemometrics

Although there are differences in the appearance of Mountain-Cultivated Ginseng (MCG) and Garden-Cultivated Ginseng (GCG), it is very difficult to distinguish them when the samples are processed to slices or powder. Moreover, there is significant price difference between them, which leads to the widespread adulteration or falsification in the market. Thus, the authentication of MCG and GCG is crucial for the effectiveness, safety, and quality stability of ginseng. In the present study, a headspace solid-phase microextraction gas chromatography mass spectrometry (HS-SPME-GC-MS) coupled with chemometrics approach was developed to characterize the volatile component profiles in MCG and GCG with 5-,10-,15-growth years, and subsequently to discover differentiating chemical markers. As a result, we characterized, for the first time, 46 volatile components from all the samples by using the NIST database and the Wiley library. The base peak intensity chromatograms were subjected to multivariate statistical analysis to comprehensively compare the chemical differences among the above samples. MCG_{5-,10-,15-years} and GCG_{5-,10-,15-years} samples were mainly divided into two groups by unsupervised principal component analysis (PCA), and 5 potential cultivation-dependent markers were discovered based on orthogonal partial least squares-discriminant analysis (OPLS-DA). Moreover, MCG_{5-,10-,15-years} samples were divided into three blocks, and 12 potential growth-year-dependent markers enabled differentiation. Similarly, GCG_{5-,10-,15-years} samples were also separated into three groups, and six potential growth-year-dependent markers were determined. The proposed approach could be applied to directly distinguish MCG and GCG with different growth years and to identify the differentiation chemo-markers, which is an important criterion for evaluating the effectiveness, safety, and quality stability of ginseng.

Research progress on metabolomics in the quality evaluation and clinical study of Panax ginseng

Panax ginseng, an essential component of traditional medicine and often referred to as the king of herbs, has played a pivotal role in medicine globally for several millennia. Previously, traditional phytochemical methods were mainly used for quality evaluation and pharmacological mechanism studies of ginseng, resulting in the lack of systematicness and innovation and hindering the development and utilization of ginseng resources. Since the beginning of the new century, systems biology technology represented by metabolomics has shown unique advantages in the modernization and internationalization of herbal medicine, establishing a bridge for communication between traditional medicine and modern medicine. P. ginseng, a special herb used in medicine and food, is one of the main research objects for qualitative and quantitative analysis of metabolomics and has gradually become the focus of researchers globally. Here, we conducted a comprehensive summary and analysis of numerous studies published in ginseng metabolomics. This review aims to provide more novel ideas for the quality evaluation, development, and clinical application of ginseng in the future and offer more useful technical references for the modernization and internationalization of herbal medicine based on metabolomics.

Research Progress and Trends in Metabolomics of Fruit Trees

Metabolomics is an indispensable part of modern systems biotechnology, applied in the diseases' diagnosis, pharmacological mechanism, and quality monitoring of crops, vegetables, fruits, etc. Metabolomics of fruit trees has developed rapidly in recent years, and many important research results have been achieved in combination with transcriptomics, genomics, proteomics, quantitative trait locus (QTL), and genome-wide association study (GWAS). These research results mainly focus on the mechanism of fruit quality formation, metabolite markers of special quality or physiological period, the mechanism of fruit tree's response to biotic/abiotic stress and environment, and the genetics mechanism of fruit trait. According to different experimental purposes, different metabolomic strategies could be selected, such as targeted metabolomics, non-targeted metabolomics, pseudo-targeted metabolomics, and widely targeted metabolomics. This article presents metabolomics strategies, key techniques in metabolomics, main applications in fruit trees, and prospects for the future. With the improvement of instruments, analysis platforms, and metabolite databases and decrease in the cost of the experiment, metabolomics will prompt the fruit tree research to achieve more breakthrough results.

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.

Intervention with kimchi microbial community ameliorates obesity by regulating gut microbiota

The objective of this study was to evaluate anti-obesity effects of kimchi microbial community (KMC) on obesity and gut microbiota using a high fat diet-induced mouse model compared to effects of a single strain. Administration of KMC decreased body weight, adipose tissue, and liver weight gains. Relative content of Muribaculaceae in the gut of the KMC-treated group was higher than that in the high-fat diet (HFD) group whereas relative contents of Akkermansiaceae, Coriobacteriaceae, and Erysipelotrichaceae were lower in KMC-treated group. Metabolic profile of blood was found to change differently according to the administration of KMC and a single strain of Lactobacillus plantarum. Serum metabolites significantly increased in the HFD group but decreased in the KMC-treated group included arachidic acid, stearic acid, fumaric acid, and glucose, suggesting that the administration of KMC could influence energy metabolism. The main genus in KMC was not detected in guts of mice in KMC-treated group. Since the use of KMC has advantages in terms of safety, it has potential to improve gut microbial community for obese people.

Characterization and Antioxidant Activity Determination of Neutral and Acidic Polysaccharides from Panax Ginseng C. A. Meyer

Panax ginseng (P. ginseng) is the most widely consumed herbal plant in Asia and is well-known for its various pharmacological properties. Many studies have been devoted to this natural product. However, polysaccharide’s components of ginseng and their biological effects have not been widely studied. In this study, white ginseng neutral polysaccharide (WGNP) and white ginseng acidic polysaccharide (WGAP) fractions were purified from P. ginseng roots. The chemical properties of WGNP and WGAP were investigated using various chromatography and spectroscopy techniques, including high-performance gel permeation chromatography, Fourier-transform infrared spectroscopy, and high-performance liquid chromatography with an ultra-violet detector. The antioxidant, anti-radical, and hydrogen peroxide scavenging activities were evaluated in vitro and in vivo using Caenorhabditis elegans as the model organism. Our in vitro data by ABTS (2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid), reducing power, ferrous ion chelating, and hydroxyl radical scavenging activity suggested that the WGAP with significantly higher uronic acid content and higher molecular weight exhibits a much stronger antioxidant effect as compared to that of WGNP. Similar antioxidant activity of WGAP was also confirmed in vivo by evaluating internal reactive oxygen species (ROS) concentration and lipid peroxidation. In conclusion, WGAP may be used as a natural antioxidant with potent scavenging and metal chelation properties.