Direct analysis of traditional Chinese medicines by mass spectrometry

Based on UPLC-Q-TOF/MS and Network Pharmacology to Explore the Mechanism of Qingre Lishi Decoction in the Treatment of Psoriasis

Background

Psoriasis is an immune-mediated chronic inflammatory disease. Qingre Lishi Decoction (QRLSD) has achieved great clinical effect in the treatment of psoriasis. However, the potential bioactive components and the mechanisms are yet unclear.

Aim

To analyze the serum parameters of rats fed with QRLSD, screen out the active components of QRLSD, and explore the potential targets and pathway of QRLSD in the treatment of psoriasis.

Materials and Methods

The active components of serum containing QRLSD were analyzed using ultra-high performance liquid chromatography quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF/MS). The targets of QRLSD in the treatment of psoriasis were predicted by network pharmacology and molecular docking. In vitro experiments verified the underlying mechanism.

Results

By UPLC-Q-TOF/MS, 15 prototype components and 22 metabolites were identified in serum containing QRLSD. Subsequently, 260 chemical composition targets and 218 psoriasis targets were overlapped to obtain 23 intersection targets, including LGALS3, TNF, F10, DPP4, EGFR, MAPK14, STAT3 and others. TNF, IL-10, GAPDH, STAT3, EGFR, ITGB1, LGALS3 genes were identified as potential drug targets in the PPI network analyzed by CytoHubba. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that QRLSD may improve psoriasis by regulating immune and inflammatory pathways, the cytokine mediated signal transduction pathways and other signaling pathways. Molecular docking results showed that the main active components of the serum containing QRLSD had higher affinities for TNF and LGALS3. In vitro experiments confirmed that QRLSD may decrease levels of inflammatory cytokines by suppressing the NF-κB signaling pathway activated by TNF-α in human keratinocytes.

Conclusion

This study explores the potential compounds, targets and signaling pathways of QRLSD in the treatment of psoriasis, which will help clarify the efficacy and mechanism of QRLSD.

Identification of geographic origins of Morus alba Linn. through surfaced enhanced Raman spectrometry and machine learning algorithms

The leaves of Morus alba Linn., which is also known as white mulberry, have been commonly used in many of traditional systems of medicine for centuries. In traditional Chinese medicine (TCM), mulberry leaf is mainly used for anti-diabetic purpose due to its enrichment in bioactive compounds such as alkaloids, flavonoids and polysaccharides. However, these components are variable due to the different habitats of the mulberry plant. Therefore, geographic origin is an important feature because it is closely associated with bioactive ingredient composition that further influences medicinal qualities and effects. As a low-cost and non-invasive method, surface enhanced Raman spectrometry (SERS) is able to generate the overall fingerprints of chemical compounds in medicinal plants, which holds the potential for the rapid identification of their geographic origins. In this study, we collected mulberry leaves from five representative provinces in China, namely, Anhui, Guangdong, Hebei, Henan and Jiangsu. SERS spectrometry was applied to characterize the fingerprints of both ethanol and water extracts of mulberry leaves, respectively. Through the combination of SERS spectra and machine learning algorithms, mulberry leaves were well discriminated with high accuracies in terms of their geographic origins, among which the deep learning algorithm convolutional neural network (CNN) showed the best performance. Taken together, our study established a novel method for predicting the geographic origins of mulberry leaves through the combination of SERS spectra with machine learning algorithms, which strengthened the application potential of the method in the quality evaluation, control and assurance of mulberry leaves.

Linking electron ionization mass spectra of organic chemicals to toxicity endpoints through machine learning and experimentation

Quantitative structure-activity relationship (QSAR) modeling has been widely used to predict the potential harm of chemicals, in which the prediction heavily relies on the accurate annotation of chemical structures. However, it is difficult to determine the accurate structure of an unknown compound in many cases, such as in complex water environments. Here, we solved the above problem by linking electron ionization mass spectra (EI-MS) of organic chemicals to toxicity endpoints through various machine learning methods. The proposed method was verified by predicting 50% growth inhibition of Tetrahymena pyriformis (T. pyriformis) and liver toxicity. The optimal model performance obtained an R² > 0.7 or balanced accuracy > 0.72 for both the training set and test set. External experimentation further verified the application potential of our proposed method in the toxicity prediction of unknown chemicals. Feature importance analysis allowed us to identify critical spectral features that were responsible for chemical-induced toxicity. Our approach has the potential for toxicity prediction in such fields that it is difficult to determine accurate chemical structures.

Characterization of effective phytochemicals in traditional Chinese medicine by mass spectrometry

Traditional Chinese medicines (TCMs) have been widely used in clinical and healthcare applications around the world. The characterization of the phytochemical components in TCMs is very important for studying the therapeutic mechanism of TCMs. In the analysis process, sample preparation and instrument analysis are key steps to improve analysis performance and accuracy. In recent years, chromatography combined with mass spectrometry (MS) has been widely used for the separation and detection of trace components in complex TCM samples. This article reviews various sample preparation techniques and chromatography-MS techniques, including the application of gas chromatography-MS and liquid chromatography-MS and other MS techniques in the characterization of phytochemicals in TCM materials and Chinese medicine products. This article also describes a new ambient ionization MS method for rapid and high-throughput analysis of TCM components.

Comprehensive characterization and identification of chemical constituents in Yangwei decoction using ultra-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry

Yangwei decoction, a classical traditional Chinese medicine prescription, has been widely used to treat exogenous cold and internal injury with damp stagnation for many centuries. However, its systematic chemical profiling remains ambiguous, which has hampered the interpretation of pharmacology and the mechanism of its formula. In the present study, a ultra-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry method was successfully established for the first time to separate and identify the complicated components of Yangwei decoction. The accurate mass data of the protonated molecules, deprotonated molecules, and fragment ions were detected in positive and negative ion modes. A total of 226 compounds in Yangwei decoction were tentatively identified and unambiguously characterized by comparing their retention times and mass spectrometry data with those of reference standards and literature, including 24 lignans, 18 alkaloids, 9 phenylpropanoid glycosides, 76 flavonoids, 59 triterpenoids, 17 organic acids, 7 gingerols, 8 lactones, and 8 other compounds. The present study provides a novel method of constituents characterization for well-known Chinese medicine prescriptions. The study aims to lay a robust foundation for future research, providing the holistic quality control and pharmacology of Yangwei decoction. This article is protected by copyright. All rights reserved.

ANALYSIS OF CARBOHYDRATES AND GLYCOCONJUGATES BY MATRIX-ASSISTED LASER DESORPTION/IONIZATION MASS SPECTROMETRY: AN UPDATE FOR 2015-2016

This review is the ninth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2016. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation and arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals. Much of this material is presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented over 30 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show no sign of deminishing. © 2020 Wiley Periodicals, Inc.

Metabolomic approach for rapid differentiation of Fritillaria bulbs by matrix-assisted laser desorption/ionization mass spectrometry and multivariate statistical analysis

The bulbs of Fritillaria have been used for centuries as food and medicinal products in many Asian countries. Different Fritillaria species have distinct pharmacological effects despite of their similar appearances. Effective differentiation of Fritillaria species can avoid adulteration and is crucial to its clinical uses. In this paper, a hybrid method of matrix assisted laser desorption/ionization mass spectrometry and multivariate statistical analysis was developed for the rapid and reliable differentiation of Fritillaria species for the first time. Significantly different patterns for five Fritillaria species were obtained by MALDI-MS after instant sample extractions. Different groups of Fritillaria were confidently differentiated via an orthogonal partial least square model. In addition, a metabolomic taxonomy of five Fritillaria species was obtained based on MALDI-MS data.

Sample preparation for mass spectrometry imaging of leaf tissues: a case study on analyte delocalization

Appropriate sample preparation is pivotally important to obtain high-quality mass spectrometry imaging (MSI) data. Unlike mammalian tissues, preparation of cryosections from plant tissues for MSI measurement is quite challenging due to its intrinsic complex texture and cellular structure. This is especially true for leaf samples which are generally thin, water-rich, and fragile. In this work, a systematic study was performed, aiming to evaluate three embedding materials and five mounting approaches for matrix-assisted laser desorption ionization (MALDI) MSI of secondary metabolites in cross sections of the ginkgo leaf. Delocalization of endogenous metabolites was chosen as a major indicator for evaluation of three embedding materials including ice, carboxymethyl cellulose (CMC), and gelatin and different mounting approaches. Image distortion and analyte delocalization were observed when ice was used as an embedding medium. CMC embedding provided better results compared to the ice by using modified mounting approach. Among three embedding materials, no delocalization was observed in specimens embedded with gelatin, and gelatin embedding is the least affected by different mounting approaches. An alternative approach to mitigate analyte delocalization is the removal of embedding media embraced the tissue sections before mounting, which is particularly suitable for ice-embedded samples. Additionally, the extent of analyte delocalization was closely related to their lipophilicity/hydrophilicity properties, and less analyte diffusion was observed for hydrophobic analytes than for the water-soluble compounds.

Recent development in mass spectrometry and its hyphenated techniques for the analysis of medicinal plants

INTRODUCTION

Medicinal plants are gaining increasing attention worldwide due to their empirical therapeutic efficacy and being a huge natural compound pool for new drug discovery and development. The efficacy, safety and quality of medicinal plants are the main concerns, which are highly dependent on the comprehensive analysis of chemical components in the medicinal plants. With the advances in mass spectrometry (MS) techniques, comprehensive analysis and fast identification of complex phytochemical components have become feasible, and may meet the needs, for the analysis of medicinal plants.

OBJECTIVE

Our aim is to provide an overview on the latest developments in MS and its hyphenated technique and their applications for the comprehensive analysis of medicinal plants.

METHODOLOGY

Application of various MS and its hyphenated techniques for the analysis of medicinal plants, including but not limited to one-dimensional chromatography, multiple-dimensional chromatography coupled to MS, ambient ionisation MS, and mass spectral database, have been reviewed and compared in this work.

RESULTS

Recent advancs in MS and its hyphenated techniques have made MS one of the most powerful tools for the analysis of complex extracts from medicinal plants due to its excellent separation and identification ability, high sensitivity and resolution, and wide detection dynamic range.

CONCLUSION

To achieve high-throughput or multi-dimensional analysis of medicinal plants, the state-of-the-art MS and its hyphenated techniques have played, and will continue to play a great role in being the major platform for their further research in order to obtain insight into both their empirical therapeutic efficacy and quality control.

Efficient discovery and capture of new neuronal nitric oxide synthase-postsynaptic density protein-95 uncouplers from herbal medicines using magnetic molecularly imprinted polymers as artificial antibodies

In the scope of stroke treatment, new neuronal nitric oxide synthase-postsynaptic density protein-95 uncouplers from herbal medicines were discovered and captured. To do so, highly selective magnetic molecularly imprinted polymers with a core-shell structure were prepared as artificial antibodies. According to the results of computational simulations, we designed and synthesized various polymers with varying amounts and types of template, functional monomer, cross-linker, and solvent. Characterization and performance tests revealed that the most appropriate artificial antibodies showed uniform spherical morphologies, large adsorption capacities, fast-binding kinetics, high selectivity, and quick separation. These artificial antibodies were then used as sorbents for dispersive magnetic solid-phase extraction coupled with high-performance liquid chromatography and mass spectrometry to capture and identify structural analogs to ZL006 from extracts of Scutellariae radix, Psoraleae fructus, and Trifolium pratense. Furthermore, according to the neuroprotective effect and coimmunoprecipitation test, Baicalein, Neobavaisoflavone, Corylifol A, and Biochanin A can be the potential uncouplers of neuronal nitric oxide synthase-postsynaptic density protein-95. Therefore, this present study contributes valuable information for the discovery of neuronal nitric oxide synthase-postsynaptic density protein-95 uncouplers from herbal medicines.

Fast and comprehensive characterization of chemical ingredients in traditional Chinese herbal medicines by extractive atmospheric pressure photoionization (EAPPI) mass spectrometry

RATIONALE

The goal of this work is to employ extractive atmospheric pressure photoionization mass spectrometry (EAPPI-MS) to characterize the constituents in traditional Chinese herbal medicine (TCHM) directly without chromatographic separation.

METHODS

Sample was placed in 4 mL of methanol/water (v/v, 3:1) in the nebulization cell, and then the ultrasonic nebulizer was switched on. The ultrasonic nebulization system allows the simultaneous sample extraction and introduction of extract aerosols. The extract aerosols were vaporized in a transfer tube. Mixed with a gaseous dopant, vaporized analytes were ionized through ambient photon-induced ion-molecule reactions, and were mass-analyzed by high-resolution time-of-flight mass spectrometry (TOF-MS).

RESULTS

The major ingredients including alkaloids, flavonoids, amino acids, saccarides, ginsenosides, lignans and terpenoids were readily detected. Compared with electrospray ionization (ESI), EAPPI allowed the ionization of a wider range of compounds, which is desirable for the integral characterization of TCHMs containing numerous constituents. The significant discrepancies for both alkaloids and terpenoids in tripterygium glycoside tablets from two different manufacturers could be simultaneously reflected from EAPPI mass spectra.

CONCLUSIONS

Our results demonstrate that EAPPI-MS can be regarded as a supplementary ambient method for the fast and comprehensive analysis of TCHMs, which is important for the quality control and safety assurance of these products.

Direct Analysis in Real-time Mass Spectrometry for Rapid Identification of Traditional Chinese Medicines with Coumarins as Primary Characteristics

INTRODUCTION

The increasing popularity of traditional Chinese medicines (TCMs) necessitates rapid and reliable methods for controlling their quality. Direct analysis in real-time mass spectrometry (DART-MS) represents a novel approach to analysing TCMs.

OBJECTIVE

To develop a quick and reliable method of identifying TCMs with coumarins as primary characteristics.

METHODOLOGY

DART-MS coupled with ion trap mass spectrometry was employed to rapidly identify TCMs with coumarins as primary characteristics and to explore the ionisation mechanisms of simple coumarins, furocoumarins and pyranocoumarins in detail. With minimal sample pretreatment, mass spectra of Fraxini Cortex, Angelicae Pubescentis Radix, Peucedani Radix and Psoraleae Fructus samples were obtained within seconds. The operating parameters of the DART ion source (e.g. grid electrode voltage and ionisation gas temperature) were carefully investigated to obtain high-quality mass spectra. The mass spectra of samples and DART-MS/MS spectra of marker compounds were used to identify sample materials.

RESULTS

Successful authentication was achieved by analysing the same materials of different origins. Some simple coumarins, furocoumarins and pyranocoumarins can be directly detected by DART-MS as marker compounds.

CONCLUSION

Our results demonstrated that DART-MS can provide a rapid and reliable method for the identification of TCMs containing different configurations of coumarins; the method may also be applicable to other plants. Copyright © 2016 John Wiley & Sons, Ltd.

Boronlectin/Polyelectrolyte Ensembles as Artificial Tongue: Design, Construction, and Application for Discriminative Sensing of Complex Glycoconjugates from Panax ginseng

Ginsenoside is a large family of triterpenoid saponins from Panax ginseng, which possesses various important biological functions. Due to the very similar structures of these complex glycoconjugates, it is crucial to develop a powerful analytic method to identify ginsenosides qualitatively or quantitatively. We herein report an eight-channel fluorescent sensor array as artificial tongue to achieve the discriminative sensing of ginsenosides. The fluorescent cross-responsive array was constructed by four boronlectins bearing flexible boronic acid moieties (FBAs) with multiple reactive sites and two linear poly(phenylene-ethynylene) (PPEs). An "on-off-on" response pattern was afforded on the basis of superquenching of fluorescent indicator PPEs and an analyte-induced allosteric indicator displacement (AID) process. Most importantly, it was found that the canonical distribution of ginsenoside data points analyzed by linear discriminant analysis (LDA) was highly correlated with the inherent molecular structures of the analytes, and the absence of overlaps among the five point groups reflected the effectiveness of the sensor array in the discrimination process. Almost all of the unknown ginsenoside samples at different concentrations were correctly identified on the basis of the established mathematical model. Our current work provided a general and constructive method to improve the quality assessment and control of ginseng and its extracts, which are useful and helpful for further discriminating other complex glycoconjugate families.