Application of Authentication Evaluation Techniques of Ethnobotanical Medicinal Plant Genus Paris: A Review

Characterization of a glycosyltransferase from Paris polyphylla for application in biosynthesis of rare ophiopogonins and ginsenosides

Saponins are bioactive components of many medicinal plants, possessing complicated chemical structures and extensive pharmacological activities, but the production of high-value saponins remains challenging. In this study, a 6'-O-glucosyltransferase PpUGT7 (PpUGT91AH7) was functionally characterized from Paris polyphylla Smith var. yunnanensis (Franch.) Hand. -Mazz., which can transfer a glucosyl group to the C-6' position of diosgenin-3-O-rhamnosyl-(1 → 2)-glucoside (1), pennogenin-3-O-rhamnosyl-(1 → 2)-glucoside (2), and diosgenin-3-O-glucoside (5). The KM and Kcat values of PpUGT7 towards the substrate 2 were 8.4 μM and 2 × 10-3 s-1, respectively. Through molecular docking and site-directed mutagenesis, eight residues were identified to interact with the sugar acceptor 2 and be crucial for enzyme activity. Moreover, four rare ophiopogonins and ginsenosides were obtained by combinatorial biosynthesis, including an undescribed compound ruscogenin-3-O-glucosyl-(1 → 6)-glucoside (10). Firstly, two monoglycosides 9 and 11 were generated using a known sterol 3-O-β-glucosyltransferase PpUGT80A40 with ruscogenin (7) and 20(S)-protopanaxadiol (8) as substrates, which were further glycosylated to the corresponding diglycosides 10 and 12 under the catalysis of PpUGT7. In addition, compounds 7-11 were found to show inhibitory effects on the secretion of TNF-α and IL-6 in macrophages RAW264.7. The findings provide valuable insights into the enzymatic glycosylation processes in the biosynthesis of bioactive saponins in P. polyphylla var. yunnanensis, and also serve as a reference for utilizing UDP-glycosyltransferases to construct high-value or rare saponins for development of new therapeutic agents.

Two previously undescribed cholestanol saponins from the rhizomes of Paris fargesii var. petiolata

Two previously undescribed cholestanol saponins, parpetiosides F - G (1-2), and six known analogs (3-8) were isolated from the rhizomes of Paris fargesii var. petiolata. Their structures were elucidated by extensive spectroscopic data analysis and chemical methods. Compound 1 was a rare 6/6/6/5/5 fused-rings cholestanol saponin with disaccharide moiety linked at C-26 of aglycone which was hardly seen in genus Paris. All of these compounds were discovered in this plant for the first time. In addition, the cytotoxicities of saponins (1-8) against three human cancer cell lines (U87, HepG2 and SGC-7901) were evaluated by CCK-8 method, and saponins 5-8 displayed certain cytotoxicities. The strong interactions between saponins 5-8 and SCUBE3, an oncogene for glioma cells, were displayed by molecular docking.

Comparative metabolome profiling of Paris polyphylla var. yunnanensis cultivars and Paris luquanensis and their biological activity in zebrafish model

ETHNOPHARMACOLOGICAL RELEVANCE

Paris polyphylla var. Yunnanensis (Franch.) Hand.-Mazz., a perennial medicinal herb commonly known as "Chonglou" in Chinese, is mainly effective against innominate toxin swelling, insect sting, snake bite, traumatic injuries and various inflammatory. It is also recorded with mild toxicity. The rare species Paris luquanensis H. Li has been also used as folk medicine in Yunnan province for the same effects. Compared with P. polyphylla var. Yunnanensis (35-100 cm in height), this species has variegated leaves, and grows slower and is therefore shorter (6-23 cm in height). There are a number of different cultivars based on the shape of the petal and the height of Paris plant. However, currently, investigations into the differences of the chemical profiling of these cultivars are lacking.

AIM OF THE STUDY

This study aims to: (1) examine metabolites variations in Paris polyphylla var. Yunnanensis cultivars and Paris luquanensis; (2) investigate the different metabolite accumulation patterns between rhizomes and leaves and provide more useful information for the application of P. polyphylla var. Yunnanensis leaves; (3) compare in vivo effects on the recruitment of reactive oxygen species (ROS) and Neutrophils and toxic effects in zebrafish model between leaves and rhizomes of P. polyphylla var. Yunnanensis and P. luquanensis.

MATERIALS AND METHODS

The change patterns of metabolites in the leaves and rhizomes of four P. polyphylla var. Yunnanensis cultivars and one P. luquanensis cultivar were analyzed using an UPLC-ESI-MS/MS system. The total phenolic acid, total flavonoid, total saponin components and in vitro antioxidant activities were determined by spectrophotometric methods. The in vivo toxicity and their effects on the recruitment of ROS and neutrophils in zebrafish model were performed.

RESULTS

The widely targeted metabolomics method detected 695 metabolites in tested samples and classified as 15 known classes according to structures of the metabolites. By overall-comparing the SDMs discerned between leaves and rhizomes of each samples, 161 metabolites were substantially altered in all the cultivars. There are 62 and 64 SDMs showing constitutive differential accumulation between leaves and rhizomes of P. polyphylla var. Yunnanensis (samples A-D) and P. luquanensis (sample E), respectively. The levels of TSC, TPC and TFC decreased significantly in leaves as compared to rhizomes for all cultivars, with the exception of TPC in cultivar A, which is almost the same in leave and rhizome. The DPPH scavenging property and FRAP values of rhizomes are higher than those of leaves for all cultivars. However, there is no distinct different between leaves and rhizomes of different sample extracts for in vivo effects on the recruitment of ROS and neutrophils in zebrafish model. BL extracts showed high toxicity to the developing embryos.

CONCLUSION

As far as we are concerned, this study analyzes the P. polyphylla var. Yunnanensis and P. luquanensis variegation from the perspective of the metabolites pattern for the first time. The results give a valuable insight into the specie metabolic profiling and in vivo anti-oxidant, anti-inflammatory and toxic effects of these Paris plants.

Machine learning applications for multi-source data of edible crops: A review of current trends and future prospects

The quality and safety of edible crops are key links inseparable from human health and nutrition. In the era of rapid development of artificial intelligence, using it to mine multi-source information on edible crops provides new opportunities for industrial development and market supervision of edible crops. This review comprehensively summarized the applications of multi-source data combined with machine learning in the quality evaluation of edible crops. Multi-source data can provide more comprehensive and rich information from a single data source, as it can integrate different data information. Supervised and unsupervised machine learning is applied to data analysis to achieve different requirements for the quality evaluation of edible crops. Emphasized the advantages and disadvantages of techniques and analysis methods, the problems that need to be overcome, and promising development directions were proposed. To monitor the market in real-time, the quality evaluation methods of edible crops must be innovated.

A MS-feature-based medicinal plant database-driven strategy for ingredient identification of Chinese medicine prescriptions

Identification of the individual herbs that constitute the Chinese medicine prescription (CMP) is a key step to control the quality and ensure the efficacy of traditional Chinese medicine (TCM), but also a challenging task for analysts from all over the world. In this study, a MS-feature-based medicinal plant database-driven strategy was proposed for quick and automatic interpretation of CMP ingredients. The single herb database consisting of stable ions of sixty-one common TCM medicinal herbs was first constructed. And then, the data of CMP was imported into a self-built searching program to achieve quick and automatic identification with four steps including level 1 candidate herb screening based on stable ions (step 1), level 2 candidate herb screening based on unique ions (step 2), difficult-to-distinguish herb differentiation (step 3) and results integration (step 4). The identification model was optimized and validated with homemade Shaoyaogancao Decoction, Mahuang Decoction, Banxiaxiexin Decoction, and their related negative prescriptions and homemade fakes. Another nine batches of homemade and commercial CMPs were applied to this new approach and most of composed herbs in the corresponding CMPs were correctly identified. This work provided a promising and universal strategy for the clarification of CMP ingredients.

Cytotoxic steroidal glycosides from the rhizomes of Paris polyphylla var. yunnanensis

Paris polyphylla var. yunnanensis (Franch.) Hand.-Mazz. (Melanthiaceae), an important specie of the genus Paris, has long been in a traditional Chinese medicine (TCM) for a long time. This study aimed to isolate and identify the structures of bioactive saponins from the rhizomes of P. polyphylla var. yunnanensis and evaluate their cytotoxicity against BxPC-3, HepG2, U373 and SGC-7901 carcinoma cell lines. Seven previously undescribed and seven known saponins were identified, and Paris saponins VII (PSVII) showed significant cytotoxicity against the BxPC-3 cell line with IC₅₀ values of 3.59 μM. Furthermore, flow cytometry, transmission electron microscopy and western-bolt analysis revealed that PSVII inhibited the proliferation of BxPC-3 cells and might be involved in inducing apoptosis and pyroptosis by activating caspase-3, -7 and caspase-1, respectively.

Cytotoxic and pro-apoptotic effects of botanical drugs derived from the indigenous cultivated medicinal plant Paris polyphylla var. yunnanensis

Background: Cancer is one of the top two leading causes of death worldwide. Ethnobotanical research, it is one of methods, which is able to discover effective anticancer drugs based on "prototype" of indigenous people's historical experiences and practices. The rhizomes of Paris polyphylla var. yunnanensis (Franch.) Hand.-Mazz. have been used as botanical drugs to treat cancer by Yi, Bai, Dai, and Naxi ethnic groups in Yunnan, China, where this species is widely cultivated in a large scale in Yunnan. Materials and methods: To identify the substances of anticancer activities based on indigenous medicine knowledge, chromatography was performed to separate saponins from the rhizomes of P. polyphylla var. yunnanensis, followed by spectroscopy to determine the structure of six isolated saponins. The cytotoxicity of five extracts and six pure compounds were evaluated by MTS method. Quantitative determination of total saponins of P. polyphylla var. yunnanensis was analyzed by HPLC. Cell cycle assay, apoptosis assay, and mitochondrial membrane potential were used to evaluate the pro-apoptotic activity in vitro. Results: Five extracts and six pure saponins showed significant inhibitory cytotoxic activities of three human liver cancer cell lines (SMMC-7721, HepG2, and SK-HEP-1) and one non-small-cell lung cancer cell line (A549). The contents of Paris saponins I, II, and VII were 6.96% in the rhizomes of P. polyphylla var. yunnanensis, much higher than Chinese Pharmacopoeia standards (0.6%). Six saponins induced significant apoptosis and cell cycle arrest in three human cancer cell lines (A549, SMMC-7721, and HepG2), which was associated with the loss of mitochondrial membrane potential. Conclusion: The result of this study support that cultivated P. polyphylla var. yunnanensis could be a substitute for wild resource as an anticancer medicine based on indigenous medicine knowledge.

Comparative transcriptome analysis reveals key genes for polyphyllin difference in five Paris species

Paris species accumulate a large amount of steroidal saponins, which have numerous pharmacological activities and have become an essential component in many patented drugs. However, only two among all Paris species. Paris are identified as official sources due to high level of bioactive compounds. To clarify the composition of steroidal saponins and the molecular basis behind the differences between species, we investigated transcriptome and metabolic profiles of leaves and rhizomes in Paris polyphylla var. chinensis (PPC), Paris polyphylla var. yunnanensis (PPY), Paris polyphylla var. stenophylla (PPS), Paris fargesii (PF), and Paris mairei (PM). Phytochemical results displayed that the accumulation of steroidal saponins was tissue- and species-specific. PF and PPS contained more steroidal saponins in leaves than rhizomes, while PPY accumulated more steroidal saponins in rhizomes than leaves. PPC and PM contained similar amounts of steroidal saponins in leaves and rhizomes. Transcriptome analysis illustrated that most differentially expressed genes related to the biosynthesis of steroidal saponins were abundantly expressed in rhizomes than leaves. Meanwhile, more biosynthetic genes had significant correlations with steroidal saponins in rhizomes than in leaves. The result of CCA indicated that ACAT, DXS, DWF1, and CYP90 constrained 97.35% of the variance in bioactive compounds in leaves, whereas CYP72, UGT73, ACAT, and GPPS constrained 98.61% of the variance in phytochemicals in rhizomes. This study provided critical information for enhancing the production of steroidal saponins by biotechnological approaches and methodologies.

Application of Analytical Technologies in the Discrimination and Authentication of Herbs from Fritillaria: A Review

Medicinal plants of Fritillaria are widely distributed in numerous countries around the world and possess excellent antitussive and expectorant effects. In particular, Fritillariae Bulbus (FB) as a precious traditional medicine has thousands of years of medical history in China. Herbs of Fritillaria have a high market value and demand while limited by harsh growing circumstances and scarce wild resources. As a consequence, fraudulent behaviors are regularly engaged by the unscrupulous merchants in an attempt to reap greater profits. It is of an urgent need to evaluate the quality of Fritillaria herbs and their products using various analytical instruments and techniques. This review has scrutinized approximately 160 articles from 1995 to 2022 published on the investigation of Fritillaria herbs and related herbal products. The botanical classification of genus Fritillaria, types of counterfeits, technologies applied for differentiating Fritillaria species were comprehensively summarized and discussed in the current review. Molecular and chromatographic identification were the dominant technologies in the authentication of Fritillaria herbs. Additionally, we brought some potential and promising technologies and analytical strategies into attention, which are worthy attempting in the future researches. This review could conduce to excellent reference value for further investigations of the authenticity assessment of Fritillaria species.

Anticoagulant activity analysis and origin identification of Panax notoginseng using HPLC and ATR-FTIR spectroscopy

INTRODUCTION

Panax notoginseng is one of the traditional precious and bulk-traded medicinal materials in China. Its anticoagulant activity is related to its saponin composition. However, the correlation between saponins and anticoagulant activities in P. notoginseng from different origins and identification of the origins have been rarely reported.

OBJECTIVES

We aimed to analyze the correlation of components and activities of P. notoginseng from different origins and develop a rapid P. notoginseng origin identification method.

MATERIALS AND METHODS

Pharmacological experiments, HPLC, and ATR-FTIR spectroscopy (variable selection) combined with chemometrics methods of P. notoginseng main roots from four different origins (359 individuals) in Yunnan Province were conducted.

RESULTS

The pharmacological experiments and HPLC showed that the saponin content of P. notoginseng main roots was not significantly different. It was the highest in main roots from Wenshan Prefecture (9.86%). The coagulation time was prolonged to observe the strongest effect (4.99 s), and the anticoagulant activity was positively correlated with the contents of the three saponins. The content of ginsenoside Rg₁ had the greatest influence on the anticoagulant effect. The results of spectroscopy combined with chemometrics show that the variable selection method could extract a small number of variables containing valid information and improve the performance of the model. The variable importance in projection has the best ability to identify the origins of P. notoginseng; the accuracy of the training set and the test set was 0.975 and 0.984, respectively.

CONCLUSION

This method is a powerful analytical tool for the activity analysis and identification of Chinese medicinal materials from different origins.

Verified the rapid evaluation of the edible safety of wild porcini mushrooms, using deep learning and PLS-DA

BACKGROUND

How to quickly identify poisonous mushrooms is a worldwide problem, because poisonous mushrooms and edible mushrooms have very similar appearances. Even some edible mushrooms must be processed further before they can be eaten. In addition, mushrooms from different geographical origins contain different levels of heavy metals. Eating frequent mushrooms with excessive heavy metal content can also cause food poisoning. This information is very important and needs to be informed to consumers in advance. Through the demand for the safety of porcini mushrooms in the Yunnan area we propose a hierarchical identification system based on Fourier-transform near-infrared (FT-NIR) spectroscopy to evaluate the edible safety of porcini species.

RESULTS

We found that deep learning is the most effective means to identify the edible safety of porcini, and the recognition accuracy was 100%, by comparing two pattern recognition tools, deep learning and partial least square discriminant analysis (PLS-DA). Although the accuracy of the PLS-DA test set is 96.10%, the poisonous porcini is not allowed to be wrongly judged. In addition, the cadmium (Cd) content of Leccinum rugosiceps in the Midu area exceeded the standard. Deep learning can trace Le. rugosiceps geographic origin with an accuracy of 100%.

CONCLUSION

The overall results show that deep learning methods based on FT-NIR can identify porcini that is at risk of being eaten. This has useful application prospects in food safety. © 2021 Society of Chemical Industry.

Extended application of deep learning combined with 2DCOS: Study on origin identification in the medicinal plant of Paris polyphylla var. yunnanensis

INTRODUCTION

Medicinal plants are very important to human health, and ensuring their quality and rapid evaluation are the current research concerns. Deep learning has a strong ability in recognition. This study extended it to the identification of medicinal plants from the perspective of spectrum.

OBJECTIVE

In order to realise the rapid identification and provide a reference for the selection of high-quality resources of medicinal plants, a combination of deep learning and two-dimensional correlation spectroscopy (2DCOS) was proposed.

METHODS

For the first time, Fourier transform mid-infrared (FT-MIR) and near-infrared (NIR) spectroscopy 2DCOS images combined with residual neural network (ResNet) was used for the origin identification of Paris polyphylla var. yunnanensis. In total 1593 samples were collected and 12821 2DCOS images were drawn. The climate of different origins was briefly analysed.

RESULTS

The xishuangbanna, puer, lincang, honghe and wenshan are the five regions with more ecological advantages. The synchronous 2DCOS models of FT-MIR and NIR could realise origin identification with the accuracy of 100%. The synchronous images were suitable for the identification of medicinal plants with complex systems. The full band, feature band and different contour models had no big difference in distinguishing ability, so they were not the key factors affecting the discrimination results.

CONCLUSION

The ResNet models established were stable, reliable, and robust, which not only solved the problem of origin identification, expanded the application field of deep learning, but also provided practical reference for the related research of other medicinal plants.

New Steroidal Saponins Isolated from the Rhizomes of Paris mairei

The genus Paris is an excellent source of steroidal saponins that exhibit various bioactivities. Paris mairei is a unique species and has been widely used as folk medicine in Southwest China for a long time. With the help of chemical methods and modern spectra analysis, five new steroidal saponins, pamaiosides A–E (1–5), along with five known steroidal saponins 6–10, were isolated from the rhizomes of Paris mairei. The cytotoxicity of all the new saponins was evaluated against human pancreatic adenocarcinoma PANC-1 and BxPC3 cell lines.

The traditional uses, phytochemistry, and pharmacological properties of Paris L. (Liliaceae): A review

ETHNOPHARMACOLOGICAL RELEVANCE

Paris L. (Liliaceae) consisted of 33 species, of which the study focused on Paris polyphylla Smith, P. polyphylla var. chinensis (Franch.) Hara, and P. polyphylla Smith var. yunnanensis (Franch.) Hand. -Mazz. Due of course to the good effects of analgesia and hemostasis, it was traditionally used to treat trauma by folk herbalists.

AIM OF THIS REVIEW

This study summarized the traditional uses, distributions, phytochemical components, pharmacological properties, and toxicity evaluation of the genus Paris, and reviewed the economic value of cultivate P. polyphylla. This aim was that of providing a new and comprehensive recognition of these medicinal plants for the further utilization of Paris plants.

MATERIALS AND METHODS

The literature about traditional and folk uses of genus Paris was obtained from Duxiu Search, and China National Knowledge Infrastructure (CNKI). The other literature about genus Paris was searched online on Web of Science, PubMed, Google Scholar, Baidu Scholar, Scifinder database, and Springer research. The Scientific Database of China Plant Species (DCP) (http://db.kib.ac.cn/Default.aspx) databases were used to check the scientific names and provide species, varieties, and distribution of genus Paris. The botany studies information of genus Paris was available online from Plant Plus of China (www.iplant.cn). All the molecular structures of chemical compounds displayed in the text were produced by ChemBioDraw Ultra 14.0.

RESULTS

The plants of genus Paris, containing about 33 species and 15 varieties, are mainly distributed in Southwest China (Yunnan, Sichuan, and Guizhou provinces). More than 320 chemical components have been isolated from genus Paris since 2020, including steroidal saponins, C-21 steroids, phytosterols, insect hormones, pentacyclic triterpenes, flavonoids, and other compounds. Arrays of pharmacological investigations revealed that compounds and extracts of Paris species possess a wide spectrum of pharmacological effects, such as antitumor, cytotoxic, antimicrobial, antifungal, hemostatic, and anti-inflammatory activities. The studies about toxicity evaluation suggested that Rhizome Paridis had slight liver toxicity.

CONCLUSIONS

The dried rhizomes of P. polyphylla, P. polyphylla var. chinensis, and P. polyphylla var. yunnanensis were used to treat wound, bleeding, and stomachache, etc. in folk medicine. Phytochemistry researches showed that different species had pretty similarities especially in terms of chemical constituents. Pharmacological studies witnessed that Rhizome Paridis has various activities. Among these activities, steroidal saponins were the main active ingredients. Furthermore, an important aspect responsible for increasing interest in genus Paris is the use of antifertility-nonhormonal contraceptives by women. Also, the development of TCM (Traditional Chinese medicine) planting industry can improve the income of ethnic minorities and promote economic development.

Superiority Verification of Deep Learning in the Identification of Medicinal Plants: Taking Paris polyphylla var. yunnanensis as an Example

Medicinal plants have a variety of values and are an important source of new drugs and their lead compounds. They have played an important role in the treatment of cancer, AIDS, COVID-19 and other major and unconquered diseases. However, there are problems such as uneven quality and adulteration. Therefore, it is of great significance to find comprehensive, efficient and modern technology for its identification and evaluation to ensure quality and efficacy. In this study, deep learning, which is superior to conventional identification techniques, was extended to the identification of the part and region of the medicinal plant Paris polyphylla var. yunnanensis from the perspective of spectroscopy. Two pattern recognition models, partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM), were established, and the overall discrimination performance of the three types of models was compared. In addition, we also compared the effects of different sample sizes on the discriminant performance of the models for the first time to explore whether the three models had sample size dependence. The results showed that the deep learning model had absolute superiority in the identification of medicinal plant. It was almost unaffected by factors such as data type and sample size. The overall identification ability was significantly better than the PLS-DA and SVM models. This study verified the superiority of the deep learning from examples, and provided a practical reference for related research on other medicinal plants.

Genetic Diversity, Chemical Components, and Property of Biomass Paris polyphylla var. yunnanensis

Paris polyphylla var. yunnanensis is a kind of biomass resource, which has important medicinal and economical values with a huge market. This review article aims to summarize the recent development of biomass P. polyphylla var. yunnanensis. The genetic diversity and chemical components of biomass P. polyphylla var. yunnanensis were reviewed based on the literature. Both the genetic diversity and genetic structure of biomass P. polyphylla var. yunnanensis were compared by using molecular marker technologies. All the extraction processes, harvest time, and drying methods on the chemical components were summarized in detail. The differences of arbuscular mycorrhizal fungi on the infection rate, diosgenin content, microorganisms, enzyme activities, rhizospheric environment, and endogenous hormones were discussed. This review article is beneficial for the applications of biomass P. polyphylla var. yunnanensis as a biomass resource in the biomedical field.

Fraud Detection of Herbal Medicines Based on Modern Analytical Technologies Combine with Chemometrics Approach: A Review

Fraud in herbal medicines (HMs), commonplace throughout human history, is significantly related to medicinal effects with sometimes lethal consequences. Major HMs fraud events seem to occur with a certain regularity, such as substitution by counterfeits, adulteration by addition of inferior production-own materials, adulteration by chemical compounds, and adulteration by addition of foreign matter. The assessment of HMs fraud is in urgent demand to guarantee consumer protection against the four fraudulent activities. In this review, three analysis platforms (targeted, non-targeted, and the combination of non-targeted and targeted analysis) were introduced and summarized. Furthermore, the integration of analysis technology and chemometrics method (e.g., class-modeling, discrimination, and regression method) have also been discussed. Each integration shows different applicability depending on their advantages, drawbacks, and some factors, such as the explicit objective analysis or the nature of four types of HMs fraud. In an attempt to better solve four typical HMs fraud, appropriate analytical strategies are advised and illustrated with several typical studies. The article provides a general workflow of analysis methods that have been used for detection of HMs fraud. All analysis technologies and chemometrics methods applied can conduce to excellent reference value for further exploration of analysis methods in HMs fraud.