Nuclear Magnetic Resonance (NMR) Spectroscopy For Metabolic Profiling of Medicinal Plants and Their Products

Integrated UPLC/Q-TOF-MS/MS Analysis and Network Pharmacology to Reveal the Neuroprotective Mechanisms and Potential Pharmacological Ingredients of Aurantii Fructus Immaturus and Aurantii Fructus

Aurantii Fructus (AF) and Aurantii Fructus Immaturus (AFI) have been used for thousands of years as traditional Chinese medicine (TCM) with sedative effects. Modern studies have shown that Citrus plants also have protective effects on the nervous system. However, the effective substances and mechanisms of action in Citrus TCMs still remain unclear. In order to explore the pharmacodynamic profiles of identified substances and the action mechanism of these herbs, a comprehensive approach combining ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS/MS) analysis and network pharmacology was employed. Firstly, UNIFI 2.1.1 software was used to identify the chemical characteristics of AF and AFI. Secondly, the SwissTargetPrediction database was used to predict the targets of chemical components in AF and AFI. Targets for neuroprotection were also collected from GeneCards: The Human Gene Database (GeneCards-Human Genes|Gene Database|Gene Search). The networks between targets and compounds or diseases were then constructed using Cytoscape 3.9.1. Finally, the Annotation, Visualization and Integrated Discovery Database (DAVID) (DAVID Functional Annotation Bioinformatics Microarray Analysis) was used for GO and pathway enrichment analysis. The results showed that 50 of 188 compounds in AF and AFI may have neuroprotective biological activities. These activities are associated with the regulatory effects of related components on 146 important signaling pathways, derived from the KEGG (KEGG: Kyoto Encyclopedia of Genes and Genomes), such as neurodegeneration (hsa05022), the Alzheimer's disease pathway (hsa05010), the NF-kappa B signaling pathway (hsa04064), the hypoxia-inducible factor (HIF)-1 signaling pathway (hsa04066), apoptosis (hsa04210), the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor resistance signaling pathway (hsa01521), and others, by targeting 108 proteins, including xanthine dehydrogenase (XDH), glutamate ionotropic receptor NMDA type subunit 2B (GRIN2B), and glucose-6-phosphate dehydrogenase (G6PD), among others. These targets are thought to be related to inflammation, neural function and cell growth.

Metabolomics as a tool for geographic origin assessment of roasted and green coffee beans

Coffee is widely consumed across the globe. The most sought out varieties are Arabica and Robusta which differ significantly in their aroma and taste. Furthermore, varieties cultivated in different regions are perceived to have distinct characteristics encouraging some producers to adopt the denomination of origin label. These differences arise from variations on metabolite content related to edaphoclimatic conditions and post-harvest management among other factors. Although sensory analysis is still standard for coffee brews, instrumental analysis of the roasted and green beans to assess the quality of the final product has been encouraged. Metabolomic profiling has risen as a promising approach not only for quality purposes but also for geographic origin assignment. Many techniques can be applied for sample analysis: chromatography, mass spectrometry, and NMR have been explored. The data collected is further sorted by multivariate analysis to identify similar characteristics among the samples, reduce dimensionality and/or even propose a model for predictive purposes. This review focuses on the evolution of metabolomic profiling for the geographic origin assessment of roasted and green coffee beans in the last 21 years, the techniques that are usually applied for sample analysis and also the most common approaches for the multivariate analysis of the collected data. The prospect of applying a wide range of analytical techniques is becoming an unbiased approach to determine the origin of different roasted and green coffee beans samples with great correlation. Predictive models worked accurately for the geographic assignment of unknown samples once the variety was known.

Metabolic Footprinting-Based DNA-AuNP Encoders for Extracellular Metabolic Response Profiling

Metabolic footprinting as a convenient and non-invasive cell metabolomics strategy relies on monitoring the whole extracellular metabolic process. It covers nutrient consumption and metabolite secretion of in vitro cell culture, which is hindered by low universality owing to pre-treatment of the cell medium and special equipment. Here, we report the design and a variety of applicability, for quantifying extracellular metabolism, of fluorescently labeled single-stranded DNA (ssDNA)-AuNP encoders, whose multi-modal signal response is triggered by extracellular metabolites. We constructed metabolic response profiling of cells by detecting extracellular metabolites in different tumor cells and drug-induced extracellular metabolites. We further assessed the extracellular metabolism differences using a machine learning algorithm. This metabolic response profiling based on the DNA-AuNP encoder strategy is a powerful complement to metabolic footprinting, which significantly applies potential non-invasive identification of tumor cell heterogeneity.

Chemometric-Guided Approaches for Profiling and Authenticating Botanical Materials

Botanical supplements with broad traditional and medicinal uses represent an area of growing importance for American health management; 25% of U.S. adults use dietary supplements daily and collectively spent over $9. 5 billion in 2019 in herbal and botanical supplements alone. To understand how natural products benefit human health and determine potential safety concerns, careful in vitro, in vivo, and clinical studies are required. However, botanicals are innately complex systems, with complicated compositions that defy many standard analytical approaches and fluctuate based upon a plethora of factors, including genetics, growth conditions, and harvesting/processing procedures. Robust studies rely upon accurate identification of the plant material, and botanicals' increasing economic and health importance demand reproducible sourcing, as well as assessment of contamination or adulteration. These quality control needs for botanical products remain a significant problem plaguing researchers in academia as well as the supplement industry, thus posing a risk to consumers and possibly rendering clinical data irreproducible and/or irrelevant. Chemometric approaches that analyze the small molecule composition of materials provide a reliable and high-throughput avenue for botanical authentication. This review emphasizes the need for consistent material and provides insight into the roles of various modern chemometric analyses in evaluating and authenticating botanicals, focusing on advanced methodologies, including targeted and untargeted metabolite analysis, as well as the role of multivariate statistical modeling and machine learning in phytochemical characterization. Furthermore, we will discuss how chemometric approaches can be integrated with orthogonal techniques to provide a more robust approach to authentication, and provide directions for future research.

The Role of High-Resolution Analytical Techniques in the Development of Functional Foods

The approaches based on high-resolution analytical techniques, such as nuclear magnetic resonance or mass spectrometry coupled to chromatographic techniques, have a determining role in several of the stages necessary for the development of functional foods. The analyses of botanical extracts rich in bioactive compounds is one of the fundamental steps in order to identify and quantify their phytochemical composition. However, the compounds characterized in the extracts are not always responsible for the bioactive properties because they generally undergo metabolic reactions before reaching the therapeutic targets. For this reason, analytical techniques are also applied to analyze biological samples to know the bioavailability, pharmacokinetics and/or metabolism of the compounds ingested by animal or human models in nutritional intervention studies. In addition, these studies have also been applied to determine changes of endogenous metabolites caused by prolonged intake of compounds with bioactive potential. This review aims to describe the main types and modes of application of high-resolution analytical techniques in all these steps for functional food development.

Development and perspectives of rapid detection technology in food and environment

Food safety become a hot issue currently with globalization of food trade and food supply chains. Chemical pollution, microbial contamination and adulteration in food have attracted more attention worldwide. Contamination with antibiotics, estrogens and heavy metals in water environment and soil environment have also turn into an enormous threat to food safety. Traditional small-scale, long-term detection technologies have been unable to meet the current needs. In the monitoring process, rapid, convenient, accurate analysis and detection technologies have become the future development trend. We critically synthesizing the current knowledge of various rapid detection technology, and briefly touched upon the problem which still exist in research process. The review showed that the application of novel materials promotes the development of rapid detection technology, high-throughput and portability would be popular study directions in the future. Of course, the ultimate aim of the research is how to industrialization these technologies and apply to the market.

Metabotyping of different soybean genotypes and distinct metabolism in their seeds and leaves

The metabolome of three soybean genotypes, Glycine max Hwangkeum (elite or domesticated cultivar), Glycine max Napjakong (landrace or semi-wild cultivar) and Glycine soja Dolkong (wild cultivar), were characterized in seeds and leaves using a 1H NMR-based metabolomics approach. Expression of primary and secondary metabolites were different in seeds and leaves as well as amongst soybean genotypes. Different kaempferol glycosides were observed in the leaves but not in the seeds, and quercetin derivatives were found only in G. max Napjakong and G. soja Dolkong. Moreover, epicatechin was found only in the seeds of G. max Napjakong and G. soja Dolkong. These results demonstrate distinct adaptations of different soybean genotypes to given environmental conditions. The current study, therefore, provides useful information on global metabolic compositions that might be used to develop soybean-based products through better understanding of the metabolic phenotypes of existing soybean genotypes.

Identifying unknown metabolites using NMR-based metabolic profiling techniques

Metabolic profiling of biological samples provides important insights into multiple physiological and pathological processes but is hindered by a lack of automated annotation and standardized methods for structure elucidation of candidate disease biomarkers. Here we describe a system for identifying molecular species derived from nuclear magnetic resonance (NMR) spectroscopy-based metabolic phenotyping studies, with detailed information on sample preparation, data acquisition and data modeling. We provide eight different modular workflows to be followed in a recommended sequential order according to their level of difficulty. This multi-platform system involves the use of statistical spectroscopic tools such as Statistical Total Correlation Spectroscopy (STOCSY), Subset Optimization by Reference Matching (STORM) and Resolution-Enhanced (RED)-STORM to identify other signals in the NMR spectra relating to the same molecule. It also uses two-dimensional NMR spectroscopic analysis, separation and pre-concentration techniques, multiple hyphenated analytical platforms and data extraction from existing databases. The complete system, using all eight workflows, would take up to a month, as it includes multi-dimensional NMR experiments that require prolonged experiment times. However, easier identification cases using fewer steps would take 2 or 3 days. This approach to biomarker discovery is efficient and cost-effective and offers increased chemical space coverage of the metabolome, resulting in faster and more accurate assignment of NMR-generated biomarkers arising from metabolic phenotyping studies. It requires a basic understanding of MATLAB to use the statistical spectroscopic tools and analytical skills to perform solid phase extraction (SPE), liquid chromatography (LC) fraction collection, LC-NMR-mass spectroscopy and one-dimensional and two-dimensional NMR experiments.

Toona sinensis modulates autophagy and cytokines in lipopolysaccharide-induced RAW 264.7 macrophages

Toona sinensis (TS) is a medicinal herb possessing anti-apoptotic, anti-oxidant, and anti-inflammatory properties and is used to treat diabetes, cancer, and inflammatory diseases. In traditional Chinese medicine theory, TS clears dampness and heat, strengthens the stomach function, and regulates vital energy flow. TS is also used as an astringent and a pesticide. In this study, we aimed to evaluate how TS influences autophagy and cytokines during the inflammatory process in RAW 264.7 macrophages. The treatment groups were pre-supplemented with TS leaf extract; rapamycin was used to enhance autophagy and lipopolysaccharide (LPS) was used to induce inflammation. The expression of autophagy-related proteins was analyzed by western blotting. The survival rate of, and chemokine expression and oxidative stress in the cells were also assessed. TS leaf extract inhibited mammalian target of rapamycin (mTOR) phosphorylation at site S2448 in the macrophages. At relatively higher concentrations (50 and 75 μg/mL), TS elevated the expression of light chain 3 II (LC3-II), which further modulated autophagy. Pre-supplementation with TS leaf extract elevated the total glutathione (GSH) level and GSH/oxidized GSH (GSSG) ratio, but it decreased the GSSG, total nitric oxide, nitrate, nitrite, malondialdehyde, and superoxide anion levels. TS reversed the effects of LPS-induced cytokines, including interleukin (IL)-6 and IL-10. TS did not induce significant toxicity at the studied concentrations. In conclusion, TS leaf extract may modulate autophagy during inflammation. Furthermore, it may prevent cell damage via anti-inflammation and anti-oxidation. Thus, this study supports the ethnomedical use of TS in the prevention of inflammation-related diseases.

High-Resolution Liquid Chromatography-Mass Spectrometry-Based Metabolomic Discrimination of Citrus-Type Crude Drugs and Comparison with Nuclear Magnetic Resonance Spectroscopy-Based Metabolomics

Five Citrus-type crude drugs (40 samples) were classified using liquid chromatography-mass spectrometry (LC-MS)-based metabolomics. The following six flavonoid derivatives were identified as contributors from the loading plots of multivariate analysis: naringin (1), neohesperidin (2), neoeriocitrin (3), narirutin (9), hesperidin (10), and 3,5,6,7,8,3',4'-heptamethoxyflavone (12). Three coumarin derivatives, namely, meranzin (6), meranzin hydrate (7), and meranzin glucoside (8), were also identified as contributors. Furthermore, compared with our previous studies on proton (¹H) and ¹³C NMR spectroscopy-based metabolomics, the present study revealed that the Citrus-type crude drugs were distinguished with the same pattern; however, the contributors differed between the ¹H and ¹³C NMR spectroscopy-based metabolomics. The high dynamic range of NMR spectroscopy provided broad coverage of the metabolomes including the primary and secondary metabolites. However, LC-MS appeared to be superior in detecting secondary metabolites with high sensitivity, some of which occurred in quantities that were undetectable using NMR spectroscopy.

Selection and characterization of botanical natural products for research studies: a NaPDI center recommended approach

Covering: up to the end of 2018 Dietary supplements, which include botanical (plant-based) natural products, constitute a multi-billion-dollar industry in the US. Regulation and quality control for this industry is an ongoing challenge. While there is general agreement that rigorous scientific studies are needed to evaluate the safety and efficacy of botanical natural products used by consumers, researchers conducting such studies face a unique set of challenges. Botanical natural products are inherently complex mixtures, with composition that differs depending on myriad factors including variability in genetics, cultivation conditions, and processing methods. Unfortunately, many studies of botanical natural products are carried out with poorly characterized study material, such that the results are irreproducible and difficult to interpret. This review provides recommended approaches for addressing the critical questions that researchers must address prior to in vitro or in vivo (including clinical) evaluation of botanical natural products. We describe selection and authentication of botanical material and identification of key biologically active compounds, and compare state-of-the-art methodologies such as untargeted metabolomics with more traditional targeted methods of characterization. The topics are chosen to be of maximal relevance to researchers, and are reviewed critically with commentary as to which approaches are most practical and useful and what common pitfalls should be avoided.

Chemical Barcoding: A Nuclear-Magnetic-Resonance-Based Approach To Ensure the Quality and Safety of Natural Ingredients

One of the greatest challenges facing the functional food and natural health product (NHP) industries is sourcing high-quality, functional, natural ingredients for their finished products. Unfortunately, the lack of ingredient standards, modernized analytical methodologies, and industry oversight creates the potential for low quality and, in some cases, deliberate adulteration of ingredients. By exploring a diverse library of NHPs provided by the independent certification organization ISURA, we demonstrated that nuclear magnetic resonance (NMR) spectroscopy provides an innovative solution to authenticate botanicals and warrant the quality and safety of processed foods and manufactured functional ingredients. Two-dimensional NMR experiments were shown to be a robust and reproducible approach to capture the content of complex chemical mixtures, while a binary normalization step allows for emphasizing the chemical diversity in each sample, and unsupervised statistical methodologies provide key advantages to classify, authenticate, and highlight the potential presence of additives and adulterants.

Application of Metabolomics to Osteoarthritis: from Basic Science to the Clinical Approach

PURPOSE OF THE REVIEW

Osteoarthritis (OA) is a multifactorial and progressive disease affecting whole synovial joint. The extract pathogenic mechanisms and diagnostic biomarkers of OA remain unclear. In this article, we review the studies related to metabolomics of OA, discuss the biomarkers as a tool for early OA diagnosis. Furthermore, we examine the major studies on the application of metabolomics methodology in the complex context of OA and create a bridge from findings in basic science to their clinical utility.

RECENT FINDINGS

Recently, the tissue metabolomics signature permits a view into transitional phases between the healthy and OA joint. Both nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry-based metabolomics approaches have been used to interrogate the metabolic alterations that may indicate the complex progression of OA. Specifically, studies on alterations pertaining to lipids, glucose, and amino acid metabolism have aided in the understanding of the complex pathogenesis of OA. The discovery of identified metabolites could be important for diagnosis and staging of OA, as well as for the assessment of efficacy of new drugs.

Application of multiple chemical and biological approaches for quality assessment of Carthamus tinctorius L. (safflower) by determining both the primary and secondary metabolites

BACKGROUND

The florets of Carthamus tinctorius L. (safflower) serve as the source of a reputable herbal medicine targeting gynecological diseases. Conventional investigations regarding the quality control of safflower, however, mainly focused on the secondary metabolites with primary metabolites ignored.

PURPOSE

To holistically evaluate the quality difference of safflower samples collected from five different producing regions by multiple chemical and biological approaches with both the primary and secondary metabolites considered.

METHODS

A precursor ions list-triggered data-dependent MS² approach was established by ultra-high performance liquid chromatography/Q-Orbitrap mass spectrometry (UHPLC/Q-Orbitrap MS) to comprehensively identify the secondary metabolites from safflower. Primary metabolites were identified by various 1D and 2D nuclear magnetic resonance (NMR) experiments. Similarity evaluation and quantitative assays of all the characterized primary metabolites and a quinochalcone C-glycoside (QCG) marker, hydroxysafflor yellow A (HSYA), were performed by quantitative ¹H NMR (qNMR) using an external standard method. Multiple in vitro models with respect to the antioxidant, anti-platelet aggregation, and antioxidant stress injury effects, were assayed to determine the efficacy differences.

RESULTS

Totally thirteen primary metabolites (including one nucleoside, two sugars, five organic alkali/acids, and five amino acids) and 135 secondary metabolites (97 QCGs and 38 flavonoids) could be identified or tentatively characterized from safflower. Good chemical consistency was observed between the commercial safflower samples and a standard safflower sample, with similarity varying in the range of 0.95‒0.99. The results from qNMR-oriented quantitative experiments (thirteen primary metabolites and HSYA) and biological assays indicated the quality of safflower samples from Xinjiang (XJ-2 and XJ-4), Hunan (HuN-1 and HuN-2), and Sichuan (SC), was comparable to the standard safflower sample.

CONCLUSION

The integration of multiple chemical (using two analytical platforms, UHPLC/Q-Orbitrap MS and NMR) and biological (four in vitro models) approaches by determining both the primary and secondary metabolites demonstrated a powerful strategy that could facilitate the holistic quality evaluation of traditional Chinese medicine.

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.