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

Promotion of a quality standard for Paris polyphylla var. yunnanensis based on the efficacy-oriented effect-constituent index

Multi-component determination and bioassays used for the quality control of traditional Chinese medicine (TCM) may have certain shortcomings. The effect-constituent index (ECI) is a quality evaluation index weighted by chemical composition analysis and effect detection. This index can be established by the dose-effect relationship of the active ingredients in TCM. In this study, Paris polyphylla var. yunnanensis (PY) was selected as the representative drug. Chemical evaluation and bioactivity evaluation were combined to establish the ECI, to compensate for the deficiency of a single evaluation method to some extent, and can be related to the efficacy of PY, in order to improve its quality standard. The ECI not only reflects the contribution of component content to the quality of PY, but also relates to clinical efficacy and reflects the influence of different components on the biological activity. Moreover, this study provided a reference method for the quality control of other TCMs.

Integrative strategy for quality control of Radix Bupleuri based on non-targeted metabolomic profiling and molecular networking

Quality control of Radix Bupleuri (RB) can be challenging due to the complexity of origin, the similar morphological characteristics, and the diversity of the multiple components. In this study, an integrated strategy for extensive identification of metabolites in plants based on multiple data processing methods was proposed to distinguish four commercially available RB species. First, the pre-processed mass spectrometry data was uploaded to Global Natural Products Social Molecular Networking (GNPS) for spectral library search and molecular network analysis, which can effectively differentiate isomers and reduce molecular redundancy. Second, the possible cleavage mode was summarized from the characteristic MS/MS fragment ions of saikoside standard, and then the possible structure of saikoside in the sample was deduced according to the cleavage patterns. Third, collected all kinds of RB components reported in the literature and matched the information in the samples to obtain more comprehensive information about metabolites. Finally, chemical markers were found employing chemometrics. This strategy not only increases the variety and number of identified components, but also improves the accuracy of the data. Based on this strategy, a total of 132 components were identified from different species of RB, and 14 chemical constituents were considered to be potential chemical markers to distinguish four kinds of RB. Among them, saikogenin a, hydroxy-saikosaponin a, hydroxy-saikosaponin d, and rutinum were of great significance for identification. The method proposed in this study not only successfully identified and distinguished four species of RB, but also laid a good theoretical foundation for regulating the RB market. This strategy provides promising perspectives in the accurate analysis of the ingredients of traditional Chinese medicine.

Characterization of volatile organic compounds with anti-atherosclerosis effects in Allium macrostemon Bge. and Allium chinense G. Don by head space solid phase microextraction coupled with gas chromatography tandem mass spectrometry

Introduction

Allium macrostemon Bge. (AMB) and Allium chinense G. Don (ACGD) are both edible Allium vegetables and named officinal Xiebai (or Allii Macrostemonis Bulbus) in East Asia. Their medicinal qualities involve in lipid lowering and anti-atherosclerosis effects. And steroidal saponins, nitrogenous compounds and sulfur compounds are like the beneficial components responsible for medicinal functions. Sulfur compounds are the recognized main components both in the volatile oils of AMB and ACGD. Besides, few researches were reported about their holistic chemical profiles of volatile organic compounds (VOCs) and pharmacodynamic effects.

Methods

In this study, we first investigated the lipid-lowering and anti-atherosclerotic effects of volatile oils derived from AMB and ACGD in ApoE ^-/- mice with high fat and high cholesterol diets.

Results

The results showed the volatile oils of AMB and ACGD both could markedly reduce serum levels of TG, TC, and LDL-C (p < 0.05), and had no alterations of HDL-C, ALT, and AST levels (p > 0.05). Pathological results displayed they both could obviously improve the morphology of cardiomyocytes and the degree of myocardial fibrosis in model mice. Meanwhile, oil red O staining results also proved they could apparently decrease the lesion areas of plaques in the aortic intima (p < 0.05). Furthermore, head space solid phase microextraction coupled with gas chromatography tandem mass spectrometry combined with metabolomics analysis was performed to characterize the VOCs profiles of AMB and ACGD, and screen their differential VOCs. A total of 121 and 115 VOCs were identified or tentatively characterized in the volatile oils of AMB and ACGD, respectively. Relative-quantification results also confirmed sulfur compounds, aldehydes, and heterocyclic compounds accounted for about 85.6% in AMB bulbs, while approximately 86.6% in ACGD bulbs were attributed to sulfur compounds, ketones, and heterocyclic compounds. Multivariate statistical analysis showed 62 differentially expressed VOCs were observed between AMB and ACGD, of which 17 sulfur compounds were found to be closely associated with the garlic flavor and efficacy.

Discussion

Taken together, this study was the first analysis of holistic chemical profiles and anti-atherosclerosis effects of AMB and ACGD volatile oils, and would benefit the understanding of effective components in AMB and ACGD.

Extraction and Identification of Antioxidant Ingredients from Cyclocarya paliurus (Batal.) Iljinsk Using UHPLC-Q-Orbitrap-MS/MS-Based Molecular Networking

Cyclocarya paliurus (Batal.) Iljinskaja (LCP) leaves have been widely employed in food and traditional medicine for treating hyperlipidaemia and its complications, possibly owing to their antioxidant properties. The aim of the present study is to identify the chemical ingredients of antioxidant extracts from LCP by using UHPLC-Q-Orbitrap-MS/MS-based molecular networking, a very recent and useful tool for annotation of chemical constituents in mixtures. The extraction conditions of antioxidant extracts from LCP were optimised by single-factor analysis and response surface methodology (RSM). The optimised conditions were a methanol concentration of 32%, a liquid-to-solid ratio of 0.4 ml/mg, an extraction temperature of 25°C, and an extraction time of 32 min. Under these conditions, the antioxidant yield was 516.20 ± 28.52 μmol TE/ml. The main active ingredients in the antioxidants were identified by UHPLC-Q-Exactive Orbitrap-MS-based molecular networking. In total, 42 compounds were identified, including 20 flavonoids, 16 quinic acid derivatives, 4 caffeoyl derivatives, and 2 coumaroyl derivatives. The findings of the present work suggest that LCP could be a suitable source of natural antioxidant compounds, which might be applicable in the development of potential pharmaceutical drugs targeting diseases related to oxidative stress.

Integrated molecular networking strategy enhance the accuracy and visualization of components identification: A case study of Ginkgo biloba leaf extract

Molecular networking (MN) is an efficient tool for natural product research. However, single MN might lead to false annotation due to the limited information, and the importance of combining MN with chromatogram is always ignored. In this study, we proposed a comprehensive MN strategy combining feature-based molecular networking (FBMN) and dual ionization mode MS/MS to improve the annotation accuracy and to achieve structural feature visualization in a chemotaxonomic chromatogram. Three steps were taken: (1) employing FBMN and dual ionization mode MS/MS to distinguish isomers and improve components' identification accuracy. (2) Using a 3-level initiative supported by in-house database to evaluate the annotation confidence. As a result, 95 compounds were successfully identified from Ginkgo biloba leaf extract (GBE) and Ginkgo biloba leaf (GBL), and 70 compounds mainly consisting of flavonoid glycosides, ginkgolides, and lignan glycosides were assigned as high-confidence molecules. (3) Building color-dependent chemotaxonomic chromatograms, to achieve component visualization by connecting FBMN with chromatogram in which the peaks of the same color indicated the compounds with similar structural features. Our research provided a new and efficient strategy for component identification and visualization of herbal medicine.

Advancements in capturing and mining mass spectrometry data are transforming natural products research

Covering: 2016 up to 2021Mass spectrometry (MS) is an essential technology in natural products research with MS fragmentation (MS/MS) approaches becoming a key tool. Recent advancements in MS yield dense metabolomics datasets which have been, conventionally, used by individual labs for individual projects; however, a shift is brewing. The movement towards open MS data (and other structural characterization data) and accessible data mining tools is emerging in natural products research. Over the past 5 years, this movement has rapidly expanded and evolved with no slowdown in sight; the capabilities of today vastly exceed those of 5 years ago. Herein, we address the analysis of individual datasets, a situation we are calling the '2021 status quo', and the emergent framework to systematically capture sample information (metadata) and perform repository-scale analyses. We evaluate public data deposition, discuss the challenges of working in the repository scale, highlight the challenges of metadata capture and provide illustrative examples of the power of utilizing repository data and the tools that enable it. We conclude that the advancements in MS data collection must be met with advancements in how we utilize data; therefore, we argue that open data and data mining is the next evolution in obtaining the maximum potential in natural products research.

UHPLC-(ESI)-HRMS and NMR-Based Metabolomics Approach to Access the Seasonality of Byrsonima intermedia and Serjania marginata From Brazilian Cerrado Flora Diversity

Seasonality is one of the major environmental factors that exert influence over the synthesis and accumulation of secondary metabolites in medicinal plants. The application of the metabolomics approach for quality control of plant extracts is essentially important because it helps one to establish a standard metabolite profile and to analyze factors that affect the effectiveness of the medicinal plants. The Brazilian Cerrado flora is characterized by a rich diversity of native plant species, and a number of these plant species have been found to have suitable medicinal properties. Some of these plant species include Byrsonima intermedia and Serjania marginata. To better understand the chemical composition of these plant species, we conducted a study using the state-of-the-art techniques including the HPLC system coupled to an Exactive-Orbitrap high resolution mass spectrometer with electrospray ionization interface UHPLC-(ESI)-HRMS and by NMR being performed 2D J-resolved and proton NMR spectroscopy. For the analysis, samples were harvested bimonthly during two consecutive years. UHPLC-(ESI)-HRMS data were preprocessed and the output data uploaded into an in-house Excel macro for peak dereplication. MS and NMR data were concatenated using the data fusion method and submitted to multivariate statistical analysis. The dereplication of LC-HRMS data helped in the annotation of the major compounds present in the extracts of the three plant species investigated allowing the annotation of 68 compounds in the extracts of B. intermedia (cinnamic acids, phenolic acids derived from galloyl quinic and shikimic acid, proanthocyanidins, glycosylated flavonoids, triterpenes and other phenols) and 81 compounds in the extracts of S. marginata (phenolic acids, saponins, proanthocyanidins, glycosylated flavonoids among other compounds). For a better assessment of the great number of responses, the significance of the chemical variables for the differentiation and correlation of the seasons was determined using the variable importance on projection (VIP) technique and through the application of the false discovery rate (FDR) estimation. The statistical data obtained showed that seasonal factors played an important role on the production of metabolites in each plant species. Temperature conditions, drought and solar radiation were found to be the main factors that affected the variability of phenolic compounds in each species.