Differentiation of Ficus deltoidea varieties and chemical marker determination by UHPLC-TOFMS metabolomics for establishing quality control criteria of this popular Malaysian medicinal herb

Chemical characterizations dataset of flavonoid glycoside isomers and other constituents from Ficus deltoidea Jack

Phytochemical data for Ficus deltoidea Jack, a plant widely studied for its anti-hyperglycemic effect, are scarce. In the pursuit of characterizing the chemical constituents of this species, extraction and purifications were conducted using multiple chromatographic procedures on selected varieties (var. deltoidea, var. kunstleri and var. trengganuensis). Twenty-two constituents were unambiguously identified through NMR, MS and UV data. These included gallocatechin (S1), afzelechin-4-8″-gallocatechin (S2), catechin (S3), afzelechin-4-8″-catechin (S4), afzelechin (S5), epicatechin (S6), hovetrichoside C (S7), 6,8-di-C-glucopyranosylapigenin (vicenin-2) (S8), afzelechin-4-8″-epiafzelechin (S9), epiafzelechin (S10), 6-C-xylopyranosyl-8-C-glucopyranosylapigenin (vicenin-1) (S11), orientin (S13), schaftoside (S14), 6-C-glucopyranosyl-8-C-xylopyranosylapigenin (vicenin-3) (S16), vitexin (S17), vitexin 2″-O-rhamnoside (S19), isovitexin 2″-O-rhamnoside (S20), 6,8-di-C-arabinopyranosylapigenin (S21), 6,8-di-C-xylopyranosylapigenin (S22), 6-C-arabinopyranosyl-8-C-xylopyranosylapigenin (S23), rhoifolin (S24) and cerberic acid A (S26). The presented phytochemical data can assist ethnobotanists, chemists, and natural product researchers in investigating the medicinal properties of F. deltoidea by facilitating the dereplication of its constituents.

Distinguishing features of Prunus humilis, P. japonica, P. pedunculata seeds and their adulterant based on DNA barcoding, morphological characterization, and chemical profiles

Pruni Semen, the dried ripe seed of Prunus humilis, P. japonica, or P. pedunculata as recorded in the Chinese Pharmacopoeia, has been widely used in pharmaceutical and food industries. The adulteration of the marketed product with morphologically similar plants of the same genus has led to variable product quality and clinical effectiveness. This study systematically investigated the phylogenetic relationships, morphological traits, and chemical profiles of 37 Pruni Semen samples from planting bases, markets, and fields. DNA barcoding could successfully distinguish the genuine and counterfeit Pruni Semen, and the results indicated that there was almost no authentic Pruni Semen available in the market. The samples were divided into "big seed" (P. pedunculata and P. salicina seeds) and "small seed" (P. humilis, P. japonica, P. tomentosa, and P. avium seeds) categories based on morphology results. The notable discrepancy in the chemical characteristics of "big seed" and "small seed" was that "small seeds" were rich in flavonoids and low in amygdalin, whereas "big seeds" were the opposite. Furthermore, principal component analysis and clustered heatmap analysis verified the distinguishing features of "big seed" and "small seed" based on morphological and chemical characteristics. This study suggested that a combination of DNA barcoding and morphological and chemical characteristics can aid in the identification and quality evaluation of authentic and adulterated Pruni Semen. These findings may help standardize Pruni Semen available in the market and protect the rights and interests of customers.

Comparative metabolite analysis of Piper sarmentosum organs approached by LC-MS-based metabolic profiling

Piper sarmentosum Roxb. (Piperaceae) is a traditional medicinal and food plant widely distributed in the tropical and subtropical regions of Asia, offering both health and culinary benefits. In this study the secondary metabolites in different organs of P. sarmentosum were identified and their relative abundances were characterized. The metabolic profiles of leaves, roots, stems and fruits were comprehensively investigated by liquid chromatography high-resolution mass spectrometry (LC-HR-MS) and the data subsequently analyzed using multivariate statistical methods. Manual interpretation of the tandem mass spectrometric (MS/MS) fragmentation patterns revealed the presence of 154 tentatively identified metabolites, mostly represented by alkaloids and flavonoids. Principle component analysis and hierarchical clustering indicated the predominant occurrence of flavonoids, lignans and phenyl propanoids in leaves, aporphines in stems, piperamides in fruits and lignan-amides in roots. Overall, this study provides extensive data on the metabolite composition of P. sarmentosum, supplying useful information for bioactive compounds discovery and patterns of their preferential biosynthesis or storage in specific organs. This can be used to optimize production and harvesting as well as to maximize the plant's economic value as herbal medicine or in food applications.

Production of Polyphenolic Natural Products by Bract-Derived Tissue Cultures of Three Medicinal Tilia spp.: A Comparative Untargeted Metabolomics Study

Medicinal plant tissue cultures are potential sources of bioactive compounds. In this study, we report the chemical characterization of the callus cultures of three medicinal Tilia spp. (Tilia cordata, Tilia vulgaris and Tilia tomentosa), along with the comparison to bracts and flowers of the same species. Our aim was to show that calli of Tilia spp. are good alternatives to the calli of T. americana for the production of polyphenols and are better sources of a subset of polyphenolic metabolites, compared to the original organs. Calli were initiated from young bracts and grown on woody plant medium containing 1 mg L-1 2,4-D and 0.1 mg L-1 BAP. For chemical characterization, a quality-controlled untargeted metabolomics approach and the quantification of several bioactive compounds was performed with the use of LC-ESI-MS/MS. While bracts and flowers contained flavonoid glycosides (astragalin, isoquercitrin) as major polyphenols, calli of all species contained catechins, coumarins (fraxin, esculin and scopoletin) and flavane aglyca. T. tomentosa calli contained 5397 µg g DW-1 catechin, 201 µg g DW-1 esculin, 218 µg g DW-1 taxifolin and 273 µg g DW-1 eriodictyol, while calli from other species contained lower amounts. T. cordata and T. tomentosa flowers were rich in isoquercitrin, containing 8134 and 6385 µg g DW-1, respectively. The currently tested species contained many of the bioactive metabolites described from T. americana. The production of catechin was shown to be comparable to the most efficient tissue cultures reported. Flowers and bracts contained flavonoid glycosides, including tiliroside, resembling bioactive fractions of T. americana. In addition, untargeted metabolomics has shown fingerprint-like differences among species, highlighting possible chemotaxonomic and quality control applications, especially for bracts.

Quality evaluation methods of chinese medicine based on scientific supervision: recent research progress and prospects

Traditional Chinese medicine (TCM) is increasingly getting attention worldwide, as it has played a very satisfactory role in treating COVID-19 during these past 3 years, and the Chinese government highly supports the development of TCM. The therapeutical theory and efficacies of Chinese medicine (CM) involve the safety, effectiveness and quality evaluation of CM, which requires a standard sound system. Constructing a scientific and reasonable CM quality and safety evaluation system, and establishing high-quality standards are the key cores to promote the high-quality development of CM. Through the traditional quality control methods of CM, the progress of the Q-marker research and development system proposed in recent years, this paper integrated the research ideas and methods of CM quality control and identified effective quality parameters. In addition, we also applied these effective quality parameters to create a new and supervision model for the quality control of CM. In conclusion, this review summarizes the methods and standards of quality control research used in recent years, and provides references to the quality control of CM and how researchers conduct quality control experiments.

From single- to multi-omics: future research trends in medicinal plants

Medicinal plants are the main source of natural metabolites with specialised pharmacological activities and have been widely examined by plant researchers. Numerous omics studies of medicinal plants have been performed to identify molecular markers of species and functional genes controlling key biological traits, as well as to understand biosynthetic pathways of bioactive metabolites and the regulatory mechanisms of environmental responses. Omics technologies have been widely applied to medicinal plants, including as taxonomics, transcriptomics, metabolomics, proteomics, genomics, pangenomics, epigenomics and mutagenomics. However, because of the complex biological regulation network, single omics usually fail to explain the specific biological phenomena. In recent years, reports of integrated multi-omics studies of medicinal plants have increased. Until now, there have few assessments of recent developments and upcoming trends in omics studies of medicinal plants. We highlight recent developments in omics research of medicinal plants, summarise the typical bioinformatics resources available for analysing omics datasets, and discuss related future directions and challenges. This information facilitates further studies of medicinal plants, refinement of current approaches and leads to new ideas.

Blood pressure and urine metabolite changes in spontaneously hypertensive rats treated with leaf extract of Ficus deltoidea var angustifolia

Ficus deltoidea var angustifolia (FD-A) reduces blood pressure in spontaneously hypertensive rats (SHR) but the mechanism remains unknown. Changes in urine metabolites following FD-A treatment in SHR were, therefore, examined to identify the mechanism of its antihypertensive action. Male SHR were given either FD-A (1000 mg kg^-1 day^-1) or losartan (10 mg kg^-1 day^-1) or 0.5 mL of ethanolic-water (control) daily for 4 weeks. Systolic blood pressure (SBP) was measured every week and urine spectra data acquisition, on urine collected after four weeks of treatment, were compared using multivariate data analysis. SBP in FD-A and losartan treated rats was significantly lower than that in the controls after four weeks of treatment. Urine spectra analysis revealed 24 potential biomarkers with variable importance projections (VIP) above 0.5. These included creatine, hippurate, benzoate, trimethylamine N-oxide, taurine, dimethylamine, homocysteine, allantoin, methylamine, n-phenylacetylglycine, guanidinoacetate, creatinine, lactate, glucarate, kynurenine, ethanolamine, betaine, 3-hydroxybutyrate, glycine, lysine, glutamine, 2-hydroxyphenylacetate, 3-indoxylsulfate and sarcosine. From the profile of these metabolites, it seems that FD-A affects urinary levels of metabolites like taurine, hypotaurine, glycine, serine, threonine, alanine, aspartate and glutamine. Alterations in these and the pathways involved in their metabolism might underlie the molecular mechanism of its antihypertensive action.

A Mass Spectrometry Based Metabolite Profiling Workflow for Selecting Abundant Specific Markers and Their Structurally Related Multi-Component Signatures in Traditional Chinese Medicine Multi-Herb Formulae

In Traditional Chinese Medicine (TCM), herbal preparations often consist of a mixture of herbs. Their quality control is challenging because every single herb contains hundreds of components (secondary metabolites). A typical 10 herb TCM formula was selected to develop an innovative strategy for its comprehensive chemical characterization and to study the specific contribution of each herb to the formula in an exploratory manner. Metabolite profiling of the TCM formula and the extract of each single herb were acquired with liquid chromatography coupled to high-resolution mass spectrometry for qualitative analyses, and to evaporative light scattering detection (ELSD) for semi-quantitative evaluation. The acquired data were organized as a feature-based molecular network (FBMN) which provided a comprehensive view of all types of secondary metabolites and their occurrence in the formula and all single herbs. These features were annotated by combining MS/MS-based in silico spectral match, manual evaluation of the structural consistency in the FBMN clusters, and taxonomy information. ELSD detection was used as a filter to select the most abundant features. At least one marker per herb was highlighted based on its specificity and abundance. A single large-scale fractionation from the enriched formula enabled the isolation and formal identification of most of them. The obtained markers allowed an improved annotation of associated features by manually propagating this information through the FBMN. These data were incorporated in the high-resolution metabolite profiling of the formula, which highlighted specific series of related components to each individual herb markers. These series of components, named multi-component signatures, may serve to improve the traceability of each herb in the formula. Altogether, the strategy provided highly informative compositional data of the TCM formula and detailed visualizations of the contribution of each herb by FBMN, filtered feature maps, and reconstituted chromatogram traces of all components linked to each specific marker. This comprehensive MS-based analytical workflow allowed a generic and unbiased selection of specific and abundant markers and the identification of multiple related sub-markers. This exploratory approach could serve as a starting point to develop more simple and targeted quality control methods with adapted marker specificity selection criteria to given TCM formula.

Chemotype classification and biomarker screening of male Eucommia ulmoides Oliv. flower core collections using UPLC-QTOF/MS-based non-targeted metabolomics

Background

In the Chinese health care industry, male Eucommia ulmoides Oliv. flowers are newly approved as a raw material of functional food. Core collections have been constructed from conserved germplasm resources based on phenotypic traits and molecular markers. However, little is known about these collections’ phytochemical properties. This study explored the chemical composition of male E. ulmoides flowers, in order to provide guidance in the quality control, sustainable cultivation, and directional breeding of this tree species.

Methods

We assessed the male flowers from 22 core collections using ultra-performance liquid chromatography and quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) non-targeted metabolomics, and analyzed them using multivariate statistical methods including principal component analysis (PCA), hierarchical cluster analysis (HCA), and orthogonal partial least squares discriminant analysis (OPLS-DA).

Results

We annotated a total of 451 and 325 metabolites in ESI+ and ESI− modes, respectively, by aligning the mass fragments of the secondary mass spectra with those in the database. Four chemotypes were well established using the ESI+ metabolomics data. Of the 29 screened biomarkers, 21, 6, 19, and 5 markers corresponded to chemotypes I, II, III, and IV, respectively. More than half of the markers belonged to flavonoid and amino acid derivative classes.

Conclusion

Non-targeted metabolomics is a suitable approach to the chemotype classification and biomarker screening of male E. ulmoides flower core collections. We first evaluated the metabolite profiles and compositional variations of male E. ulmoides flowers in representative core collections before establishing possible chemotypes and significant biomarkers denoting the variations. We used genetic variations to infer the metabolite compositional variations of male E. ulmoides flower core collections instead of using the geographical origins of the germplasm resources. The newly proposed biomarkers sufficiently classified the chemotypes to be applied for germplasm resource evaluation.

Simultaneous Quantitative Analysis of Q-Marker with One Single Reference in Glycyrrhiza uralensis Fisch

In traditional Chinese medicine (TCM) studies, it is difficult to choose evaluation markers for the strict quality control of herbs. A high performance liquid chromatography coupled with metabolomics for simultaneous quantitative analysis of quality markers (Q-markers) in Glycyrrhiza uralensis Fisch was established, which could not only ensure the quality and batch-to-batch consistency of TCMs, but also achieve a quantitative analysis of multi-components by the single reference standard. Based on the construction of chromatographic profiles by high performance liquid chromatography (HPLC) and HPLC-Q-Exactive/MS methods, different multivariate analyses were employed. Seven quantitative indices were selected as the Q-markers, and a reliable quantification method was established. The quantitative method was acceptable with good linearity with correlation coefficients >0.9993 and satisfactory repeatability (relative standard deviation (RSD) < 0.05%), precision (RSD < 0.24%), reproducibility (RSD < 0.97%), stability (RSD < 2.52%) and recoveries (96.96%-98.52%, RSD < 3.24%), and no significant differences were observed between the external standard method and the new method as determined by calculating standard method difference. Overall, the study suggests that the simultaneous quantitative analysis of main Q-marker in G. uralensis Fisch with one single marker can be considered good quality criteria for performing quality control of G. uralensis Fisch.

Bioinformatics-assisted, integrated omics studies on medicinal plants

The immense therapeutic and economic values of medicinal plants have attracted increasing attention from the worldwide researchers. It has been recognized that production of the authentic and high-quality herbal drugs became the prerequisite for maintaining the healthy development of the traditional medicine industry. To this end, intensive research efforts have been devoted to the basic studies, in order to pave a way for standardized authentication of the plant materials, and bioengineering of the metabolic pathways in the medicinal plants. In this paper, the recent advances of omics studies on the medicinal plants were summarized from several aspects, including phenomics and taxonomics, genomics, transcriptomics, proteomics and metabolomics. We proposed a multi-omics data-based workflow for medicinal plant research. It was emphasized that integration of the omics data was important for plant authentication and mechanistic studies on plant metabolism. Additionally, the computational tools for proper storage, efficient processing and high-throughput analyses of the omics data have been introduced into the workflow. According to the workflow, authentication of the medicinal plant materials should not only be performed at the phenomics level but also be implemented by genomic and metabolomic marker-based examination. On the other hand, functional genomics studies, transcriptional regulatory networks and protein-protein interactions will contribute greatly for deciphering the secondary metabolic pathways. Finally, we hope that our work could inspire further efforts on the bioinformatics-assisted, integrated omics studies on the medicinal plants.

Identification of Constituents Affecting the Secretion of Pro-Inflammatory Cytokines in LPS-Induced U937 Cells by UHPLC-HRMS-Based Metabolic Profiling of the Traditional Chinese Medicine Formulation Huangqi Jianzhong Tang

Within non-communicable diseases, chronic inflammatory conditions represent one of the biggest challenges for modern medicine. Traditional Chinese Medicine (TCM) has been practiced over centuries and has accumulated tremendous empirical knowledge on the treatment of such diseases. Huangqi Jianzhong Tang (HQJZT) is a famous TCM herbal formula composed of Radix Astragali, Ramulus Cinnamomi, Radix et Rhizoma Glycyrrhizae Praeparata cum Melle, Radix Paeoniae Alba, Rhizoma Zingiberis Recens, Fructus Jujubae and Saccharum Granorum (maltose), which has been used for the treatment of various chronic inflammatory gastrointestinal diseases. However, there is insufficient knowledge about its active constituents and the mechanisms responsible for its effects. The present study aimed at identifying constituents contributing to the bioactivity of HQJZT by combining in vitro cytokine production assays and LC-MS metabolomics techniques. From the HQJZT decoction as well as from its single herbal components, extracts of different polarities were prepared. Phytochemical composition of the extracts was analyzed by means of UPLC-QTOF-MS/MS. The inhibitory effects of the extracts on TNF-α, IL-1β and IFN-γ production were studied in U937 cells. Phytochemical and pharmacological bioactivity data were correlated by orthogonal projection to latent structures discriminant analysis (OPLS-DA) in order to identify those HQJZT constituents which may be relevant for the observed pharmacological activities. The investigations resulted in the identification of 16 HQJZT constituents, which are likely to contribute to the activities observed in U937 cells. Seven of them, namely calycosin, formononetin, astragaloside I, liquiritigenin, 18β-glycyrrhetinic acid, paeoniflorin and albiflorin were unambiguously identified. The predicted results were verified by testing these compounds in the same pharmacological assays as for the extracts. In conclusion, the anti-inflammatory activity of HQJZT could be substantiated by in vitro pharmacological screening, and the predicted activities of the OPLS-DA hits could be partially verified. Moreover, the benefits and limitations of MVDA for prediction pharmacologically active compounds contributing to the activity of a TCM mixture could be detected.