Phytochemical Analysis最新文献

Introduction: Stemona tuberosa Lour. (ST) is a significant traditional Chinese medicine (TCM) renowned for its antitussive and insecticidal properties. ST is commonly subjected to processing in clinical practice before being utilized as a medicinal substance. Currently, the customary technique for processing ST is honey-fried. Nevertheless, the specific variations in chemical constituents of ST before and after honey-fried remain unclear.

Objective: This work aimed to analyze the variations in chemical constituents of ST before and after honey-fried and to study the distribution of differential markers in the roots.

Methods: UPLC-Orbitrap Fusion MS combined with molecular network analysis was used to analyze the metabolome of ST and honey-fried ST (HST) and to screen the differential metabolites by multivariate statistical analysis. Spatial metabolomics was applied to study the distribution of differential metabolites by desorption electrospray ionization mass spectrometry imaging (DESI-MSI).

Results: The ST and HST exhibited notable disparities, with 56 and 61 chemical constituents found from each, respectively. After processing, the types of alkaloids decreased, and 12 differential metabolites were screened from the common compounds. The notable component variations were epibisdehydro-tuberostemonine J, neostenine, tuberostemonine, croomine, neotuberostemonine, and so forth. MSI visualized the spatial distribution of differential metabolites.

Conclusions: Our research provided a rapid and effective visualization method for the identification and spatial distribution of metabolites in ST. Compared with the traditional method, this method offered more convincing data supporting the processing mechanism investigations of Stemona tuberosa from a macroscopic perspective.

Introduction: Magnoliae officinalis cortex (MOC) has been used for thousands of years as a traditional Chinese herb. In Chinese Pharmacopoeia (2020 edition), it has two types of decoction pieces, raw Magnoliae officinalis cortex (RMOC) and ginger juice processed Magnoliae officinalis cortex (GMOC). The quality difference between RMOC and GMOC has not been explored systemically.

Objective: This study aimed to discover the quality difference between RMOC and GMOC, and clarify the effect of ginger juice during processing comprehensively.

Methods: Ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS) and gas chromatography-mass spectrometry (GC-MS) were applied to study the non-volatile and volatile components of RMOC and GMOC; electronic eye was applied for color measurement. Meanwhile, water processed Magnoliae officinalis cortex (WMOC) was studied as the blank sample.

Results: There were 155 non-volatile and 72 volatile substances identified. Between RMOC and GMOC, 29 distinctive non-volatile and 34 distinctive volatile compounds were detected, among which 23 new compounds appeared and five compounds disappeared due to the addition of ginger juice during processing. The intensities of 12 common non-volatile compounds and the relative percentage contents of four common volatile compounds showed significant differences between RMOC and GMOC. In color measurement of RMOC, GMOC, and WMOC, 14 common compounds with significant differences were discovered related to their color values, and their mathematical prediction functions were built.

Conclusion: There were significant differences between RMOC and GMOC; the processing mechanism of GMOC would be carried out based on the differential compounds in further investigation.

Introduction: Rosa rugosa var. plena Rehd (CBR) and Rosa chinensis cv. "JinBian" (JBR) are two common species used in rose tea among different original species. CBR, the officially documented original plant of the rose species for food and medicinal purposes, is more costly than JBR. With increasing demand for different rose teas, it is meaningful to compare the chemical constituents for their quality control and reveal their skin-whitening components that will provide in-depth insights for the expansion of the rose tea industry.

Objective: This study aims to reveal the chemical variances between CBR and JBR and determine their skin-whitening components.

Methodology: A strategy obtained by combining MS-based plant-metabolomics with spectrum-effect relationship analysis has been proposed for unveiling chemical differences between CBR and JBR and further exploring their potential skin-whitening components.

Results: A total of 2030 metabolites were found that revealed considerable differences between CBR and JBR. The results of bioactivity assay demonstrated that JBR exhibited stronger tyrosinase inhibition activity than CBR. Six potential skin-whitening compounds (di-O-galloyl-HHDP-glucoside, tri-O-galloyl-HHDP-glucoside, spiraeoside, quinic acid, rugosin A, and 1,2,3,6-tetra-O-galloyl-glucose) were discovered as potential tyrosinase inhibitors, via spectrum-effect relationship analysis. This is the first time that di-O-galloyl-HHDP-glucoside, tri-O-galloyl-HHDP-glucoside, rugosin A, and 1,2,3,6-tetra-O-galloyl-glucose have been reported with tyrosinase inhibitory activity. Additionally, molecular docking analysis was used to reveal the inhibition mechanism of these compounds toward tyrosinase.

Conclusion: The finding of this study will be of great importance for the quality control of the two types of rose teas, and the revealed active ingredients will provide in-depth insights for the expansion of the rose tea industry.

Introduction: Marsdeniae tenacissimae Caulis (MTC), a popular traditional Chinese medicine, has been widely used in the treatment of tumor diseases. Paederiae scandens Caulis (PSC), which is similar in appearance to MTC, is a common counterfeit product. It is difficult for traditional methods to effectively distinguish between MTC and PSC. Therefore, there is an urgent need for a rapid and accurate method to identify MTC and PSC.

Objectives: The aim is to distinguish between MTC and PSC by analyzing the differences in nonvolatile organic compounds (NVOCs), taste, odor, and volatile organic compounds (VOCs).

Methods: Liquid chromatography-mass spectrometry (LC-MS) was utilized to analyze the NVOCs of MTC and PSC. Electronic tongue (E-tongue) and electronic nose (E-nose) were used to analyze their taste and odor respectively. Gas chromatography-ion mobility spectrometry (GC-IMS) was applied to analyze VOCs. Finally, multivariate statistical analyses were conducted to further investigate the differences between MTC and PSC, including principal component analysis, orthogonal partial least squares discriminant analysis, discriminant factor analysis, and soft independent modeling of class analysis.

Results: The results of this study indicate that the integrated strategy of LC-MS, E-tongue, E-nose, GC-IMS, and multivariate statistical analysis can be effectively applied to distinguish between MTC and PSC. Using LC-MS, 25 NVOCs were identified in MTC, while 18 NVOCs were identified in PSC. The major compounds in MTC are steroids, while the major compounds in PSC are iridoid glycosides. Similarly, the distinct taste difference between MTC and PSC was precisely revealed by the E-tongue. Specifically, the pronounced bitterness in PSC was proven to stem from iridoid glycosides, whereas the bitterness evident in MTC was intimately tied to steroids. The E-nose detected eight odor components in MTC and six in PSC, respectively. The subsequent statistical analysis uncovered notable differences in their odor profiles. GC-IMS provided a visual representation of the differences in VOCs between MTC and PSC. The results indicated a relatively high relative content of 82 VOCs in MTC, contrasted with 32 VOCs exhibiting a similarly high relative content in PSC.

Conclusion: In this study, for the first time, the combined use of LC-MS, E-tongue, E-nose, GC-IMS, and multivariate statistical analysis has proven to be an effective method for distinguishing between MTC and PSC from multiple perspectives. This approach provides a valuable reference for the identification of other visually similar traditional Chinese medicines.

Introduction: Untargeted metabolomics is a powerful tool that provides strategies for gaining a systematic understanding of quantitative changes in the levels of metabolites, especially when combining different metabolomic platforms. Vanilla is one of the world's most popular flavors originating from cured pods of the orchid Vanilla planifolia. However, only a few studies have investigated the metabolome of V. planifolia, and no LC-MS or GC-MS metabolomics studies with respect to leaves have been performed.

Objective: The aim of the study was to comprehensively characterize the metabolome of different organs (leaves, internodes, and aerial roots) of V. planifolia.

Material and methods: Characterization of the metabolome was achieved using two complementary platforms (GC × GC-MS, LC-QToF-MS), and metabolite identification was based on a comparison with in-house databases or curated external spectral libraries.

Results: In total, 127 metabolites could be identified with high certainty (confidence level 1 or 2) including sugars, amino acids, fatty acids, organic acids, and amines/amides but also secondary metabolites such as vanillin-related metabolites, flavonoids, and terpenoids. Ninty-eight metabolites showed significantly different intensities between the plant organs. Most strikingly, aglycons of flavonoids and vanillin-related metabolites were elevated in aerial roots, whereas its O-glycoside forms tended to be higher in leaves and/or internodes. This suggests that the more bioactive aglycones may accumulate where preferably needed, e.g. for defense against pathogens.

Conclusion: The results derived from the study substantially expand the knowledge regarding the vanilla metabolome forming a valuable basis for more targeted investigations in future studies, e.g. towards an optimization of vanilla plant cultivation.

Introduction: Nicotine, a highly addictive substance, is naturally produced in the Solanaceae family of plants, particularly tobacco. The presence of nicotine in plant foods has adverse effects on the lungs, kidneys, heart, and reproductive system.

Objective: A novel three-phase microchip flat electromembrane coupled with online high-performance liquid chromatography (HPLC) was developed to analyze nicotine in tomato, mushroom, eggplant, bell pepper, and red pepper.

Methods: The microchip was connected to the HPLC in online mode. All effective variables were optimized to achieve the best extraction response. The use of electric potential and 2-nitrophenyl octyl ether -5% di(2-ethylhexyl) phosphate as a modified supported liquid membrane (SLM) increased the sensitivity and selectivity.

Results: The optimal extraction voltage, extraction time, and ion balance were 40 V, 10 min and 0, respectively. The dynamic linear range was 0.5-1000 ng g^-1. The obtained recovery, relative standard deviation, and enrichment factor were 98%, 7%, and 35, respectively. The limits of detection 0.4 ng g^-1 and the limits of quantification were obtained 1.3 ng g^-1. The highest (105.0 ng g^-1) and lowest (3.4 ng g^-1) concentrations of nicotine were obtained for eggplant and tomato, respectively.

Conclusion: Selective electromembrane extraction of nicotine from the donor phase to the acceptor phase was performed by optimizing the main variables influencing the method mechanism. The new channel design in this analytical system and online injection increased efficiency, stability, and repeatability. The results revealed that this method is capable for the efficient determination of trace amount of nicotine in edible vegetables.

Introduction: Corydalis DC., the largest genus of Papaveraceae, comprises numerous species known for their abundant alkaloid content and historical use in clinical medicine. Recently, a new species of genus Corydalis named Corydalis huangshanensis Lu Q. Huang & H. S. Peng was discovered in the Huangshan Mountains of Anhui Province, China.

Objective: To compare the chemical characteristics of C. huangshanensis and other 13 Corydalis species, aiming to elucidate the potential medicinal value of this new species.

Materials and methods: The chemical constituents of C. huangshanensis and other 13 medicinal plants of genus Corydalis were analyzed using ultra-high-performance liquid chromatography Q-Exactive Plus hybrid quadrupole-Orbitrap mass spectrometer (Q-Orbitrap) mass technology. The differences in the alkaloids in the 14 species were distinguished by chemometrics.

Results: The mass spectrometry fragmentation information and relative content of 72 alkaloids were obtained. Orthogonal partial least squares discriminant analysis (OPLS-DA) and cluster heat mapping analysis showed that these 14 species were divided into two groups. The clustering relationship between C. huangshanensis and C. decumbens (Thunb.) Pers. was similar, exhibiting similar chemical compositions and characteristics. These results indicate the potential pharmacological effects of C. huangshanensis.

Conclusion: This study enhances our understanding of the chemical classification of Corydalis and provides a basis for speculations on the medicinal value of C. huangshanensis.

Introduction: Screening of novel pancreatic lipase inhibitors from complex natural products is a meaningful task.

Objectives: Through accurately screening and separating pancreatic lipase inhibitors from Clematis tangutica (C. tangutica), to discover new leading compounds for slimming and accelerate the development and utilization of Tibetan medicine resources.

Methods: An integrated strategy that combines affinity ultrafiltration and high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (AU-HPLC-QTOFMS), targeted separation, in vitro validation, and molecular docking was developed to screen pancreatic lipase inhibitors from C. tangutica. The AU-HPLC-QTOFMS technique was performed to fish for the potential active substances. Macroporous resin, preparative liquid chromatography, and high-speed countercurrent chromatography were implemented for the accurate and targeted separation of active compounds. The inhibitory activities of target compounds to pancreatic lipase were detected by the inhibition experiments in vitro. The binding affinities and binding sites were analyzed using molecular docking.

Results: A total of eleven kinds of pancreatic lipase inhibitory substances were screened from C. tangutica. Seven triterpenoid saponins were screened for the first time as lipase inhibitors and successfully prepared with purities higher than 97%. Tanguticoside B, clematangoticoside J, hederoside H₁, and rutin showed stronger inhibitory effects with IC₅₀ values of 1.539 ± 0.048, 1.661 ± 0.092, 1.793 ± 0.069, and 1.792 ± 0.094 mmol/l. Moreover, they have the lowest ΔG values of -10.84, -9.97, -10.87, and -9.39 kcal/mol to pancreatic lipase.

Conclusion: The integrated strategy using AU-HPLC-QTOFMS, targeted separation, in vitro validation, and molecular docking was feasible for rapidly screening and directionally isolating pancreatic lipase inhibitors from C. tangutica.

Introduction: The genus Salvia L., a member of the family Lamiaceae, is a keystone genus with a wide range of medicinal properties. It possesses a rich metabolite source that has long been used to treat different disorders.

Objectives: Due to a deficiency of untargeted metabolomic profiling in the genus Salvia, this work attempts to investigate a comprehensive mass spectral library matching, computational data annotations, exclusive biomarkers, specific chemotypes, intraspecific metabolite profile variation, and metabolite enrichment by a case study of five medicinal species of Salvia.

Material and methods: Aerial parts of each species were subjected to QTRAP liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis workflow based on untargeted metabolites. A comprehensive and multivariate analysis was acquired on the metabolite dataset utilizing MetaboAnalyst 6.0 and the Global Natural Products Social Molecular Networking (GNPS) Web Platform.

Results: The untargeted approach empowered the identification of 117 metabolites by library matching and 92 nodes annotated by automated matching. A machine learning algorithm as substructural topic modeling, MS2LDA, was further implemented to explore the metabolite substructures, resulting in four Mass2Motifs. The automated library newly discovered a total of 23 metabolites. In addition, 87 verified biomarkers of library matching, 58 biomarkers of GNPS annotations, and 11 specific chemotypes were screened.

Conclusion: Integrative spectral library matching and automated annotation by the GNPS platform provide comprehensive metabolite profiling through a workflow. In addition, QTRAP LC-MS/MS with multivariate analysis unveiled reliable information about inter and intraspecific levels of differentiation. The rigorous investigation of metabolite profiling presents a large-scale overview and new insights for chemotaxonomy and pharmaceutical studies.

Introduction: Licorice, the dried roots and rhizomes of the Glycyrrhiza uralensis Fisch., holds a prominent status in various formulations within the realm of Chinese medicinal practices. The traditional processing methods of licorice hinder quality assurance, thus prompting Chinese medicine researchers to focus on the fresh processing methods to enhancing processing efficiency and quality.

Objective: This study aimed to identify the differential compounds of licorice between traditional and fresh processing methods and provide a scientific basis for the fresh processing of licorice and for further research on the processing mechanism.

Methodology: A methodology integrating ultra-performance liquid chromatography with quadrupole-time-of-flight tandem mass spectrometry combined with multivariate statistical analysis was employed to characterize the differential compounds present in licorice between traditional processing and fresh processing.

Results: The results derived from principal component analysis and heat map analyses underscored significant differences in the content of bioactive compounds between the two processing methods. By applying conditions of VIP > 1.5 and p < 0.05, a total of 38 differential compounds were identified through t tests, and the transformation mechanisms of select compounds were illustrated.

Conclusion: The adoption of fresh processing techniques not only improved processing efficiency but also significantly enhanced the preservation of bioactive compounds within licorice. This research has established a rapid and efficient analytical method for the identification of differential compounds present in differently processed licorice products.