Characterization of Chemical Component Variations in Different Growth Years and Tissues of Morindae Officinalis Radix by Integrating Metabolomics and Glycomics

Impact of Sulfur Fumigation on the Chemistry of Dioscoreae Rhizoma (Chinese Yam)

Dioscoreae Rhizoma (Chinese yam; derived from the rhizome of Dioscorea opposita Thunb.) (DR), commonly consumed as a food or supplement, is often sulfur-fumigated during post-harvest handling, but it remains largely unknown if and how sulfur fumigation impacts the chemistry of DR. In this study, we report the impact of sulfur fumigation on the chemical profile of DR and then the molecular and cellular mechanisms potentially involved in the chemical variations induced by sulfur fumigation. The results show that sulfur fumigation significantly and specifically changed the small metabolites (molecular weight lower than 1000 Da) and polysaccharides of DR at both qualitative and quantitative levels. Multifaceted molecular and cellular mechanisms involving chemical transformations (e.g., acidic hydrolysis, sulfonation, and esterification) and histological damage were found to be responsible for the chemical variations in sulfur-fumigated DR (S-DR). The research outcomes provide a chemical basis for further comprehensive and in-depth safety and functional evaluations of sulfur-fumigated DR.

The Impact of Growth Years on the Medicinal Material Characteristics and Metabolites of Stellaria dichotoma L. var. lanceolata Bge. Reveals the Optimal Harvest Age

The original plant of Chinese medicine Stellariae Radix (Yin Chai Hu) is Stellaria dichotoma L. var. lanceolata Bge (abbreviated as SDL). SDL is a perennial herbaceous plant and a characteristic crop in Ningxia. Growth years are vital factors that affect the quality of perennial medicinal materials. This study aims to investigate the impact of growth years on SDL and screen for the optimal harvest age by comparing the medicinal material characteristics of SDL with different growth years. Additionally, metabolomics analysis using UHPLC-Q-TOF MS was employed to investigate the impact of growth years on the accumulation of metabolites in SDL. The results show that the characteristics of medicinal materials and the drying rate of SDL gradually increase with the increase in growth years. The fastest development period of SDL occurred during the first 3 years, after which the development slowed down. Medicinal materials characteristics of 3-year-old SDL exhibited mature qualities with a high drying rate, methanol extract content, and the highest content of total sterols and total flavonoids. A total of 1586 metabolites were identified, which were classified into 13 major classes with more than 50 sub-classes. Multivariate statistical analysis indicated significant differences in the diversity of metabolites of SDL in different growth years, with greater differences observed in metabolites as the growth years increased. Moreover, different highly expressed metabolites in SDL at different growth years were observed: 1-2 years old was beneficial to the accumulation of more lipids, while 3-5 years old was conducive to accumulating more alkaloids, benzenoids, etc. Furthermore, 12 metabolites accumulating with growth years and 20 metabolites decreasing with growth years were screened, and 17 significantly different metabolites were noted in 3-year-old SDL. In conclusion, growth years not only influenced medicinal material characteristics, drying rate, content of methanol extract, and total sterol and flavonoid contents, but also had a considerable effect on SDL metabolites and metabolic pathways. SDL planted for 3 years presented the optimum harvest time. The screened significantly different metabolites with biological activity, such as rutin, cucurbitacin e, isorhamnetin-3-o-glucoside, etc., can be utilized as potential quality markers of SDL. This research provides references for studying the growth and development of SDL medicinal materials, the accumulation of metabolites, and the selection of optimal harvest time.

Research on Processing-Induced Chemical Variations in Polygonatum Cyrtonema Rhizome by Integrating Metabolomics and Glycomics

Polygonatum cyrtonema rhizome (PCR), the dried sweet rhizome of Polygonatum cyrtonema Hua, is commonly used as a tonic remedy and a functional food in Asia, Europe, and North America. Multiple components, including secondary metabolites, monosaccharides, oligosaccharides, and polysaccharides, collectively contribute to the therapeutic effects of PCR. Processing time exerts a significant influence on the quality of PCR, but the various processing stages have not been comprehensively chemically profiled. It is urgent to study processing-induced chemical variations in PCR to control the processing degree. In this study, multiple chromatographic and mass spectrometric techniques were used in combination with multivariate statistical analysis to perform qualitative and quantitative research on secondary metabolites and carbohydrates in PCR during processing. The results demonstrated that PCR processing can be divided into three stages, namely the raw stage (0 h), the middle stage (1–6 h), and the late stage (8–18 h). Twenty differential compounds were screened from secondary metabolites and oligosaccharides to distinguish PCR in different processing stages. Furthermore, the chemical variations of Polygonatum cyrtonema polysaccharides (PCP) also entered a new stage after processing for 6 h. Multiple chemical mechanisms, including hydrolysis, oxidative decomposition, dehydration, Maillard reaction, and polymerization were involved in the processing. This work provides a scientific basis to reveal the relationship between processing stage and chemical variations.

Phenotypic, chemical component and molecular assessment of genetic diversity and population structure of Morinda officinalis germplasm

Background

Morinda officinalis How (MO) is a perennial herb distributed in tropical and subtropical regions, which known as one of the “Four Southern Herbal Medicines”. The extent of genetic variability and the population structure of MO are presently little understood. Here, nine morphological traits, six chemical components and Single nucleotide polymorphism (SNP) markers were used in integrative research of MO germplasm variation among 88 individuals collected from ten populations across four geographical provinces of China.

Results

Both phenotype and chemical composition have significant genetic variation, and there is a certain correlation between them such as root diameter and the nystose content, as well as geographical distribution. The principal component analysis (PCA) showed the leaf length, leaf width, nystose, 1^F-furanosaccharide nystose, and the section color were the major contributors to diversity. The cluster analysis based on phenotypic and oligosaccharide data distinguished three significant groups, which was consistent with the result of a corresponding analysis with 228,615 SNP markers, and importantly, they all showed a significant correlation with geographical origin. However, there was little similarity between two cluster results. The Shannon’s information index (I) varied from 0.17 to 0.53 with a mean of 0.37, suggesting a high level of genetic diversity in MO populations, which mainly existed among individuals within populations, accounting for 99.66% of the total according to the analysis of molecular variance (AMOVA) results. Each population also maintains the connection because of certain gene communication, so that the genetic differentiation between populations was not very significant. The STRUCTURE software was used to analyse the population structure and the result showed that 88 accessions were clustered into three groups, and 67% of them were pure type, which was also confirmed through PCA.

Conclusions

The comprehensive study of phenotypic, chemical and molecular markers will provide valuable information for future breeding plans and understanding the phylogenetic relationship of MO population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08817-w.

Analysis of Fungal Microbiomes in Edible Medicinal Morindae Officinalis Radix and Alpiniae Oxyphyllae Fructus Using DNA Metabarcoding

Morindae Officinalis Radix (MOR) and Alpiniae Oxyphyllae Fructus (AOF) have been widely used as dietary supplements and traditional herbal medicines for centuries. Fungal and mycotoxin contamination in MOR and AOF has been reported recently. In this study, fungi in MOR and AOF are first investigated using DNA metabarcoding, and the differences in fungal microbiome between moldy and non−moldy samples are analyzed. The results show that Ascomycota is the most prevailing fungus at the phylum level in MOR and AOF with relative abundances of 49.53–94.32% and 14.81–81.85%, respectively. Penicillium (1.86–76.14%), Cladosporium (1.82–56.65%), and Trichoderma (0.12–19.71%) are the dominant genera in MOR. Penicillium (0.27–56.06%), Papiliotrema (0.04–51.71%), and Cladosporium (3.08–44.41%) are the dominant genera in AOF. Two potential toxigenic fungi were detected, namely, Trichoderma atroviride and Fusarium equiseti. Moreover, the differences in fungal communities between moldy and non−moldy samples were monitored. In conclusion, DNA metabarcoding can be used to assess the fungal microbiome in edible medicinal herbs, thereby providing a basis for ensuring food safety and drug efficacy.

A metabolomics strategy for authentication of plant medicines with multiple botanical origins, a case study of Uncariae Rammulus Cum Uncis

Source authentication of herbal medicines was essential for ensuring their safety, efficacy and quality consistency, especially those with multiple botanical origins. This study proposed a metabolomics strategy for species discrimination and source recognition. Uncariae Rammulus Cum Uncis, officially stipulating the stems with hooks of five Uncaria species as its origins, was taken as a case study. Firstly, an untargeted MS^E method was developed by ultra-high performance liquid chromatography hyphenated with quadrupole time-of-flight mass spectrometry for global metabolite characterization. Subsequently, data pretreatment was conducted by using Progenesis QI software and screening rules. The obtained metabolite features were defined as variables for statistical analyses. Principal component analysis and chemical fingerprinting spectra suggested that five official species were differentiated from each other except for Uncaria hirsuta and Uncaria sinensis. Furthermore, orthogonal partial least squares discrimination analysis was performed to discriminate confused two species, and resulted in the discovery of nine contributing markers. Ultimately, a Support Vector Machine model was developed to recognize five species and predict origins of commercial materials. The study demonstrated that the developed strategy was effective in discrimination and recognition of confused species, and promising in tracking botanical origins of commercial materials.