Pseudotargeted Metabolomics Approach Enabling the Classification-Induced Ginsenoside Characterization and Differentiation of Ginseng and Its Compound Formulation Products

Development of a leaf metabolite-based intact sample distinguishing algorithm for the three varieties of Panax Vietnamensis

Panax vietnamensis, indigenous to Vietnam and southern China, is classified into three subspecies: Panax vietnamensis Ha et Grushv. (PVV), Panax vietnamensis var. fuscidiscus (PVF), and Panax vietnamensis var. langbianensis (PVL). A method to distinguish these varieties in their intact form is absent, which poses a possible risk of misclassification. Here, we aimed to devise a plant metabolite-based discrimination algorithm for the three varieties, without causing significant damage to individual plants. A multivariate analysis on mass spectral data of PVV, PVF, and PVL revealed that a peak at m/z 426, which was subsequently identified as an indole alkaloid glycoside, was exclusive to PVF and therefore clearly distinguished PVF from PVV and PVL. Additionally, global metabolic profiling was conducted to elucidate the discrimination markers between PVV and PVL, and lysophospholipids and hydroxy fatty acids were selected as potential discrimination markers. The performance of these markers was validated by cross-validation using machine learning algorithm.

HerbMet: Enhancing metabolomics data analysis for accurate identification of Chinese herbal medicines using deep learning

INTRODUCTION

Chinese herbal medicines have been utilized for thousands of years to prevent and treat diseases. Accurate identification is crucial since their medicinal effects vary between species and varieties. Metabolomics is a promising approach to distinguish herbs. However, current metabolomics data analysis and modeling in Chinese herbal medicines are limited by small sample sizes, high dimensionality, and overfitting.

OBJECTIVES

This study aims to use metabolomics data to develop HerbMet, a high-performance artificial intelligence system for accurately identifying Chinese herbal medicines, particularly those from different species of the same genus.

METHODS

We propose HerbMet, an AI-based system for accurately identifying Chinese herbal medicines. HerbMet employs a 1D-ResNet architecture to extract discriminative features from input samples and uses a multilayer perceptron for classification. Additionally, we design the double dropout regularization module to alleviate overfitting and improve model's performance.

RESULTS

Compared to 10 commonly used machine learning and deep learning methods, HerbMet achieves superior accuracy and robustness, with an accuracy of 0.9571 and an F1-score of 0.9542 for distinguishing seven similar Panax ginseng species. After feature selection by 25 different feature ranking techniques in combination with prior knowledge, we obtained 100% accuracy and an F1-score for discriminating P. ginseng species. Furthermore, HerbMet exhibits acceptable inference speed and computational costs compared to existing approaches on both CPU and GPU.

CONCLUSIONS

HerbMet surpasses existing solutions for identifying Chinese herbal medicines species. It is simple to use in real-world scenarios, eliminating the need for feature ranking and selection in classical machine learning-based methods.

Integration of deep neural network modeling and LC-MS-based pseudo-targeted metabolomics to discriminate easily confused ginseng species

Metabolomics covers a wide range of applications in life sciences, biomedicine, and phytology. Data acquisition (to achieve high coverage and efficiency) and analysis (to pursue good classification) are two key segments involved in metabolomics workflows. Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups. However, insufficient feature extraction, inappropriate feature selection, overfitting, or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused. Using two ginseng varieties, namely Panax japonicus (PJ) and Panax japonicus var. major (PJvm), containing the similar ginsenosides, we integrated pseudo-targeted metabolomics and deep neural network (DNN) modeling to achieve accurate species differentiation. A pseudo-targeted metabolomics approach was optimized through data acquisition mode, ion pairs generation, comparison between multiple reaction monitoring (MRM) and scheduled MRM (sMRM), and chromatographic elution gradient. In total, 1980 ion pairs were monitored within 23 min, allowing for the most comprehensive ginseng metabolome analysis. The established DNN model demonstrated excellent classification performance (in terms of accuracy, precision, recall, F1 score, area under the curve, and receiver operating characteristic (ROC)) using the entire metabolome data and feature-selection dataset, exhibiting superior advantages over random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). Moreover, DNNs were advantageous for automated feature learning, nonlinear modeling, adaptability, and generalization. This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples. This established approach holds promise for plant metabolomics and is not limited to ginseng.

Holistic Comparison of the Lipidomes Simultaneously From 12 Panax Herbal Medicines By Ultra-High-Performance Supercritical Fluid Chromatography Coupled With Ion Mobility-Quadrupole Time-of-Flight Mass Spectrometry

Researches regarding quality control of ginseng focusing on the lipids are rare. Herein, ultra-high-performance supercritical fluid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (UHPSFC/IM-QTOF-MS) combined with untargeted metabolomic analysis was utilized to holistically characterize and compare the lipidomic difference among 12 Panax-derived herbal medicines. The established UHPSFC/IM-QTOF-MS method, using a Torus 1-AA column with CO2/CH3OH (modifier) as the mobile phase, well resolved the ginseng lipidome within 30 min. The lipid isomers and those easily co-eluted by conventional reversed-phase chromatography got separated, and integrated analyses of the positive-/negative-mode MS data and IM-derived collision cross section (CCS) greatly enhanced lipids identification. By the pattern recognition chemometric analysis of 90 batches of ginseng samples, the root ginseng samples showed significant differences in lipidome composition from those stem/leaf and flower samples. In contrast, red ginseng also contained lipids significantly different from the other root ginseng. Totally 82 potential differential lipids were discovered and identified based on the positive-mode data and 90 ones in the negative mode. Some of these lipid markers might be diagnostic for their authentication. Conclusively, we first report the lipidomic difference among 12 ginseng varieties, and the information obtained can lay foundation for the accurate identification of ginseng from the lipidome level.

Identification strategy of wild and cultivated Astragali Radix based on REIMS combined with two-dimensional LC-MS

A rapid and real-time method was established based on the combination of rapid evaporative ionization mass spectrometry (REIMS) and two-dimensional liquid chromatography mass spectrometry (2DLC-MS) for identification of wild Astragali Radix (WAR) and cultivated AR (CAR). The samples were analyzed under ambient ionization without time-consuming sample preparation. The phenotypic data of WAR and CAR were used to develop a real-time recognition model. Subsequently, the compounds in these two species were comprehensively characterized based on 2DLC-MS, and 45 different compounds were screened out by multivariate statistical analysis. A semi-quantitative method for 45 different compounds was established based on ultrahigh-performance liquid chromatography/quadrupole-linear ion trap mass spectrometry (UHPLC-QTRAP-MS). The results showed that the relative content of most compounds in WAR was higher than in CAR. In summary, the method has demonstrated remarkable performance in distinguishing between WAR and CAR, providing a reference in the field of traditional Chinese medicine (TCM) analysis and identification.

Online Comprehensive Two-Dimensional Liquid Chromatography/Quadrupole Time-of-Flight Mass Spectrometry-Based Metabolic Profiling and Comparison Enabling the Characterization of 1146 Ginsenosides and More Explicit Differentiation of Ginseng

This work was designed for the in-depth characterization and holistic comparison of up to 12 ginseng varieties, which can benefit the development of functional foods and ensure their authenticity in the food industry. An online comprehensive two-dimensional liquid chromatography/quadrupole time-of-flight mass spectrometry (2D-LC/QTOF-MS) approach was established by configurating the XCharge C18 and HSS Cyano columns. Under the optimal conditions, we characterized a total of 1146 ginsenosides (including 876 potentially new compounds) from 12 ginseng varieties by reference to an in-house library of 573 known ginsenosides and 70 reference compounds. The online 2D-LC/QTOF-MS-based untargeted metabolomics workflows were developed, by which 126 potential ginsenoside markers were unveiled and utilized to establish the key identification points for each ginseng species. Compared with the conventional liquid chromatography/mass spectrometry metabolomics, our multidimensional chromatography approach performed better in discriminating multiple ginseng varieties. This work demonstrates a potent and practical methodology to identify easily confused functional plants.

The crucial quality marker of Panax ginseng: Glycosylated modified ribonuclease-like storage protein

Panax ginseng C.A.Mey is a famous natural herbal medicine worldwide. Mountain-cultivated ginseng (MCG) and garden-cultivated ginseng (GCG) are two types of Panax ginseng. There is a significant difference in economic benefits between MCG and GCG, which can always lead to problems such as adulteration and substitution of MCG with lower-priced alternatives. We explored the quality marker of ginseng at the intact protein level and established a foundation for the quality control of ginseng. Cellulose nanocrystal assisted sample preparation combined with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) equipped with a high mass detector was performed to analyze intact proteins in ginseng. The results revealed that the ribonuclease-like storage protein is the most abundant protein in MCG and GCG. Meanwhile, the molecular weight of the ribonuclease-like storage protein showed great difference between different ginseng species, which is 26.2 kDa in MCG and 24.2 kDa in GCG. The ribonuclease-like storage protein glycosylation modification difference provides data support for the differentiation between MCG and GCG. This study showed that glycosylated modified ribonuclease-like storage protein can be a crucial quality marker of ginseng, facilitating the rapid distinction between MCG and GCG.

Phytochemistry, quality control and biosynthesis in ginseng research from 2021 to 2023: A state-of-the-art review concerning advances and challenges

Panax L. (Araliaceae) has a long history of medicinal and edible use due to its significant tonifying effects, and ginseng research has been a hot topic in natural products research and food science. In continuation of our recent ginseng review, we highlighted the advances in ginseng research from 2021 to 2023 with 157 citations, which exhibited the increasingly systematic, collaborative, and intelligent characteristics. In this review, we firstly updated the progress in phytochemistry involving the ginsenosides and polysaccharides and summarized the researches on the active components. Then, some specific applications by feat of the multidimensional chromatography, mass spectrometry imaging, DNA barcoding, and metabolomics, were analyzed, which could provide rich information supporting the multi-component characterization, authentication, and quality control of ginseng and the versatile products. Finally, the recent biosynthesis studies concerning ginsenosides were retrospected. Additionally, the current challenges and future trends with respect to ginseng research were discussed.

Software-aided efficient identification of the components of compound formulae and their metabolites in rats by UHPLC/IM-QTOF-MS and an in-house high-definition MS2 library: Sishen formula as a case

Identifying the compound formulae-related xenobiotics in bio-samples is full of challenges. Conventional strategies always exhibit the insufficiencies in overall coverage, analytical efficiency, and degree of automation, and the results highly rely on the personal knowledge and experience. The goal of this work was to establish a software-aided approach, by integrating ultra-high performance liquid chromatography/ion-mobility quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS) and in-house high-definition MS2 library, to enhance the identification of prototypes and metabolites of the compound formulae in vivo, taking Sishen formula (SSF) as a template. Seven different MS2 acquisition methods were compared, which demonstrated the potency of a hybrid scan approach (namely high-definition data-independent/data-dependent acquisition (HDDIDDA)) in the identification precision, MS1 coverage, and MS2 spectra quality. The HDDIDDA data for 55 reference compounds, four component drugs, and SSF, together with the rat bio-samples (e.g., plasma, urine, feces, liver, and kidney), were acquired. Based on the UNIFI™ platform (Waters), the efficient data processing workflows were established by combining mass defect filtering (MDF)-induced classification, diagnostic product ions (DPIs), and neutral loss filtering (NLF)-dominated structural confirmation. The high-definition MS2 spectral libraries, dubbed in vitro-SSF and in vivo-SSF, were elaborated, enabling the efficient and automatic identification of SSF-associated xenobiotics in diverse rat bio-samples. Consequently, 118 prototypes and 206 metabolites of SSF were identified, with the identification rate reaching 80.51% and 79.61%, respectively. The metabolic pathways mainly involved the oxidation, reduction, hydrolysis, sulfation, methylation, demethylation, acetylation, glucuronidation, and the combined reactions. Conclusively, the proposed strategy can drive the identification of compound formulae-related xenobiotics in vivo in an intelligent manner.

Characterization and identification of the wide-polarity multicomponents from Prunella vulgaris by offline two-dimensional liquid chromatography and hydrophilic interaction chromatography coupled to ion mobility-quadrupole time-of-flight mass spectrometry

Metabolites identification is crucial to develop functional foods or perform quality control. Prunella vulgaris (Xia-Ku-Cao) is a medicinal and edible plant used as the herbal medicine or main additive in functional beverage. However, current analytical strategies can only on-line characterize tens of compounds, restricted by insufficient chromatographic resolution and low coverage of the mass spectrometric scan methods. This work was designed to characterize the wide-polarity components from the ear of P. vulgaris. The total extract was fractionated by semi-preparative high-performance liquid chromatography into the retained medium-polarity fraction and unretained polar fraction, which were further analyzed by offline two-dimensional liquid chromatography (2D-LC) and hydrophilic interaction chromatography, respectively. Data-independent high-definition MSE of the Vion™ ion mobility time-of-flight mass spectrometer was utilized enabling the high-coverage acquisition of collision-induced dissociation-MS2 data. The offline 2D-LC, configuring the XBridge Amide and HSS T3 columns, gave high orthogonality (0.81) and effective peak capacity (1555). Automatic peak annotation facilitated by the UNIFI™ bioinformatics platform and comparison with 62 reference compounds achieved the efficient and more reliable structural elucidation. We could characterize 255 compounds from P. vulgaris, with numerous phenylpropanoid phenolic acids and triterpenoid O-glycosides newly reported. Especially, collision cross section (CCS) prediction and targeted isolation of three compounds assisted in the identification of 39 groups of isomers. Additionally, 17 hydrophilic compounds, involving oligosaccharides and organic acids, were characterized from the unretained polar fraction. Conclusively, the in-depth metabolites identification of P. vulgaris was accomplished, and the results can benefit the development and better quality control of this valuable plant.

Aqueous preparation of arginyl-fructosyl-glucose (a maltose-arginine AC) and determination of Amadori compounds (ACs) in red ginseng by ultra-high performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS)

Amadori compounds (ACs) are key Maillard intermediates in various foods after thermal processing, and are also important non-saponin components in red ginseng. Currently, due to the difficulty in obtaining AC standards, the determination of multiple ACs is limited and far from optimal. In this study, an ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed and validated. A green synthetic method was developed for arginyl-fructosyl-glucose (AFG), the major AC in red ginseng with potential health benefits. The UPLC-MS/MS method was then applied in identification and quantification of ACs in red ginseng samples, which showed for the first time that 12 other ACs also exist in red ginseng in addition to AFG and arginyl-fructose (total 98.88 % of all ACs). Contents of AFG and arginyl-fructose in whole red ginseng were 36.23 and 10.80 mg/g dry weight, respectively. Raw ginseng can be steamed and then dried whole to obtain whole red ginseng, or sliced before drying to obtain sliced red ginseng. Slicing before drying was found to reduce ACs content. Results of the present study will help to reveal the biological functions of red ginseng and related products associated with ACs and promote the standardization of red ginseng manufacture.

Analysis Transcriptome and Phytohormone Changes Associated with the Allelopathic Effects of Ginseng Hairy Roots Induced by Different-Polarity Ginsenoside Components

The allelopathic autotoxicity of ginsenosides is an important cause of continuous cropping obstacles in ginseng planting. There is no report on the potential molecular mechanism of the correlation between polarity of ginsenoside components and their allelopathic autotoxicity. This study applied a combination of metabolomics and transcriptomics analysis techniques, combined with apparent morphology, physiological indexes, and cell vitality detection of the ginseng hairy roots, through which the molecular mechanism of correlation between polarity and allelopathic autotoxicity of ginsenosides were comprehensively studied. The hairy roots of ginseng presented more severe cell apoptosis under the stress of low-polarity ginsenoside components (ZG70). ZG70 exerted allelopathic autotoxicity by regulating the key enzyme genes of cis-zeatin (cZ) synthesis pathway, indole-3-acetic acid (IAA) synthesis pathway, and jasmonates (JAs) signaling transduction pathway. The common pathway for high-polarity ginsenoside components (ZG50) and ZG70 to induce the development of allelopathic autotoxicity was through the expression of key enzymes in the gibberellin (GA) signal transduction pathway, thereby inhibiting the growth of ginseng hairy roots. cZ, indole-3-acetamid (IAM), gibberellin A1 (GA1), and jasmonoyl-L-isoleucine (JA-ILE) were the key response factors in this process. It could be concluded that the polarity of ginsenoside components were negatively correlated with their allelopathic autotoxicity.

Specific fractionation of ginsenosides based on activated carbon fibers and online fast screening of ginseng extract by mass spectrometry

Ginseng is beneficial in the prevention of many diseases and provides benefits for proper growth and development owing to the presence of various useful bioactive substances of diverse chemical heterogeneity (e.g., triterpenoid saponins, polysaccharides, volatile oils, and amino acids). As a result, understanding the therapeutic advantages of ginseng requires an in-depth compositional evaluation employing a simple and rapid analytical technique. In this work, three types of surface-activated carbon fibers (ACFs) were prepared by gas-phase oxidation, strong acid treatment, and Plasma treatment to obtain CO2-ACFs, acidified-ACFs, and plasma-ACFs, respectively. Three prepared ACFs were compared in terms of their physicochemical characterization (i.e., surface roughness and functional groups). A separation system was built using a column with modified ACFs, followed by mass spectrometry detection to investigate and determine substances of different polarities. Among the three columns, CO2-ACFs showed the optimum separation effect. 13 strong polar compounds (12 amino acids and1 oligosaccharide) and 15 lesser polar compounds (ginsenosides) were separated and identified successfully within 4 min in the ginseng sample. The data obtained by CO2-ACFs-TOF-MS/MS and UHPLC-TOF-MS/MS were compared. Our approach was found to be faster (4 min vs. 36 min) and greener, requiring much less solvent (1 mL vs. 10.8 mL), and power (0.06 vs. 0.6 kWh). The developed methodology can provide a faster, eco-friendly, and more reliable tool for the high-throughput screening of complex natural matrices and the simultaneous evaluation of several compounds in diverse samples.

Comprehensive metabolome characterization and comparison between two sources of Dragon's blood by integrating liquid chromatography/mass spectrometry and chemometrics

Dragon's Blood (DB) serves as a precious Chinese medicine facilitating blood circulation and stasis dispersion. Daemonorops draco (D. draco; Qi-Lin-Jie) and Dracaena cochinchinensis (D. cochinchinenesis; Long-Xue-Jie) are two reputable plant sources for preparing DB. This work was designed to comprehensively characterize and compare the metabolome differences between D. draco and D. cochinchinenesis, by integrating liquid chromatography/mass spectrometry and untargeted metabolomics analysis. Offline two-dimensional liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS), by utilizing a powerful hybrid scan approach, was elaborated for multicomponent characterization. Configuration of an XBridge Amide column and an HSS T3 column in offline mode exhibited high orthogonality (A0 0.80) in separating the complex components in DB. Particularly, the hybrid high-definition MSE-high definition data-dependent acquisition (HDMSE-HDDDA) in both positive and negative ion modes was applied for data acquisition. Streamlined intelligent data processing facilitated by the UNIFI™ (Waters) bioinformatics platform and searching against an in-house chemical library (recording 223 known compounds) enabled efficient structural elucidation. We could characterize 285 components, including 143 from D. draco and 174 from D. cochinchinensis. Holistic comparison of the metabolomes among 21 batches of DB samples by the untargeted metabolomics workflows unveiled 43 significantly differential components. Separately, four and three components were considered as the marker compounds for identifying D. draco and D. cochinchinenesis, respectively. Conclusively, the chemical composition and metabolomic differences of two DB resources were investigated by a dimension-enhanced analytical approach, with the results being beneficial to quality control and the differentiated clinical application of DB.

Multiple heart-cutting two-dimensional liquid chromatography/charged aerosol detector assay of ginsenosides for quality evaluation of ginseng from diverse Chinese patent medicines

For quality control of Chinese patent medicines (CPMs) containing the same herbal medicine or different herbal medicines that have similar chemical composition, current ″one standard for one species″ research mode leads to poor universality of the analytical approaches unfavorable to discriminate easily confused species. Herein, we were aimed to elaborate a multiple heart-cutting two-dimensional liquid chromatography/charged aerosol detector (MHC-2DLC/CAD) approach to quantitatively assess ginseng from multiple CPMs. Targeting baseline resolution of 16 ginsenosides (noto-R1/Rg1/Re/Rf/Ra2/Rb1/Rc/Ro/Rb2/Rb3/Rd/Rh1/Rg2/Rg3/Rg3(R)/24(R)-p-F11), experiments were conducted to optimize key parameters and validate its performance. A Poroshell 120 EC-C18 column and an XBridge Shield RP18 column were separately utilized in the first-dimensional (1D) and the second-dimensional (2D) chromatography. Eight consecutive cuttings could achieve good separation of 16 ginsenosides within 85 min. The developed MHC-2DLC/CAD method showed good linearity (R2 > 0.999), repeatability (RSD < 6.73%), stability (RSD < 5.63%), inter- and intra-day precision (RSD < 5.57%), recovery (93.76-111.14%), and the limit of detection (LOD) and limit of quantification (LOQ) varied between 0.45-2.37 ng and 0.96-4.71 ng, respectively. We applied it to the content determination of 16 ginsenosides simultaneously from 28 different ginseng-containing CPMs, which unveiled the ginsenoside content difference among the tested CPMs, and gave useful information to discriminate ginseng in the preparation samples, as well. The MHC-2DLC/CAD approach exhibited advantages of high specificity, good separation ability, and relative high analysis efficiency, which also justified the feasibility of our proposed ″Monomethod Characterization of Structure Analogs″ strategy in quality evaluation of diverse CPMs that contained different ginseng.

Characterization of ginsenosides from Panax japonicus var. major (Zhu-Zi-Shen) based on ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry and desorption electrospray ionization-mass spectrometry imaging

BACKGROUND

Panax japonicus var. major (PJM) belongs to the well-known ginseng species used in west China for hundreds of years, which has the effects of lung tonifying and yin nourishing, and exerts the analgesic, antitussive, and hemostatic activities. Compared with the other Panax species, the chemical composition and the spatial tissue distribution of the bioactive ginsenosides in PJM have seldom been investigated.

METHODS

Ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC/QTOF-MS) and desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) were integrated for the systematic characterization and spatial tissue distribution studies of ginsenosides in the rhizome of PJM. Considering the great difficulty in exposing the minor saponins, apart from the conventional Auto MS/MS (M1), two different precursor ions list-including data-dependent acquisition (PIL-DDA) approaches, involving the direct input of an in-house library containing 579 known ginsenosides (M2) and the inclusion of the target precursors screened from the MS1 data by mass defect filtering (M3), were developed. The in situ spatial distribution of various ginsenosides in PJM was profiled based on DESI-MSI with a mass range of m/z 100-1500 in the negative ion mode, with the imaging data processed by the High Definition Imaging (HDI) software.

RESULTS

Under the optimized condition, 272 ginsenosides were identified or tentatively characterized, and 138 thereof were possibly not ever reported from the Panax genus. They were composed by 75 oleanolic acid type, 22 protopanaxadiol type, 52 protopanaxatriol type, 16 octillol type, 19 malonylated, 35 C-17 side-chain varied, and 53 others. In addition, the DESI-MSI experiment unveiled the differentiated distribution of saponins, but the main location in the cork layer and phloem of the rhizome. The abundance of the oleanolic acid ginsenosides was high in the rhizome slice of PJM, which was consistent with the results obtained by UHPLC/QTOF-MS.

CONCLUSION

Comprehensive characterization of the ginsenosides in the rhizome of PJM was achieved, with a large amount of unknown structures unveiled primarily. We, for the first time, reported the spatial tissue distribution of different subtypes of ginsenosides in the rhizome slice of PJM. These results can benefit the quality control and further development of PJM and the other ginseng species.

Pseudotargeted metabolomics-based random forest model for tracking plant species from herbal products

BACKGROUND

The "one-to-multiple" phenomenon is prevalent in medicinal herbs. Accurate species identification is critical to ensure the safety and efficacy of herbal products but is extremely challenging due to their complex matrices and diverse compositions.

PURPOSE

This study aimed to identify the determinable chemicalome of herbs and develop a reasonable strategy to track their relevant species from herbal products.

METHODS

Take Astragali Radix-the typical "one to multiple" herb, as a case. An in-house database-driven identification of the potentially bioactive chemicalome (saponins and flavonoids) in AR was performed. Furthermore, a pseudotargeted metabolomics method was first developed and validated to obtain high-quality semi-quantitative data. Then based on the data matrix, the random forest algorithm was trained to predict Astragali Radix species from commercial products.

RESULTS

The pseudotargeted metabolomics method was first developed and validated to obtain high-quality semi-quantitative data (including 56 saponins and 49 flavonoids) from 26 batches of AR. Then the random forest algorithm was well-trained by importing the valid data matrix and showed high performance in predicting Astragalus species from ten commercial products.

CONCLUSION

This strategy could learn species-special combination features for accurate herbal species tracing and could be expected to promote the traceability of herbal materials in herbal products, contributing to manufacturing standardization.

Identification of Metabolite Interference Is Necessary for Accurate LC-MS Targeted Metabolomics Analysis

Targeted metabolomics has been broadly used for metabolite measurement due to its good quantitative linearity and simple metabolite annotation workflow. However, metabolite interference, the phenomenon where one metabolite generates a peak in another metabolite's MRM setting (Q1/Q3) with a close retention time (RT), may lead to inaccurate metabolite annotation and quantification. Besides isomeric metabolites having the same precursor and product ions that may interfere with each other, we found other metabolite interferences as the result of inadequate mass resolution of triple-quadruple mass spectrometry and in-source fragmentation of metabolite ions. Characterizing the targeted metabolomics data using 334 metabolite standards revealed that about 75% of the metabolites generated measurable signals in at least one other metabolite's MRM setting. Different chromatography techniques can resolve 65-85% of these interfering signals among standards. Metabolite interference analysis combined with the manual inspection of cell lysate and serum data suggested that about 10% out of ∼180 annotated metabolites were mis-annotated or mis-quantified. These results highlight that a thorough investigation of metabolite interference is necessary for accurate metabolite measurement in targeted metabolomics.

Three-dimensional characteristic chromatogram by online comprehensive two-dimensional liquid chromatography: Application to the identification and differentiation of ginseng from herbal medicines to various Chinese patent medicines

One bottleneck problem in the quality control of traditional Chinese medicine (TCM) is the accurate identification of easily confused herbal medicines from Chinese patent medicine (CPM). Ginseng products derived from the multiple parts (e.g., root/rhizome, leaf, and flower bud) of multiple Panax species (P. ginseng, P. quinquefolius, P. notoginseng, P. japonicus, and P. japonicus var. major) are globally popular; however, their authentication is very challenging. Using online comprehensive two-dimensional liquid chromatography (LC × LC), we propose the concept of a three-dimensional characteristic chromatogram (3D CC) by integrating enhanced LC × LC separation and a contour plot that visualizes the stereoscopic chromatographic peaks and examine its performance in authenticating various ginseng products. Targeted at the resolution of 17 ginsenoside markers, an online LC × LC/UV system with a 56 min analysis time was constructed: a CORTECS UPLC Shield RP 18 column running at 0.1 mL/min for the first-dimensional chromatography and a Poroshell SB-Aq column at 2.0 mL/min in shift gradient mode in the second dimension of separation. In particular, ginsenosides Rg1/Re and Rc/Ra1 were well resolved. According to the presence/absence of stereo peaks consistent with the main ginsenoside markers in the 3D CC and the depth of shade (depending on peak volume), it was feasible to use a single method to identify and distinguish among 12 different ginseng species as the drug materials and the use of ginseng simultaneously from 21 CPMs. Conclusively, a practical solution enabling the accurate identification of easily confused TCMs was provided, covering both the drug materials and the compound preparations.