A Rapid UPLC Method for Simultaneous Analysis of Caffeine and 13 Index Polyphenols in Black Tea

Identification of Epigallocatechin-3-Gallate (EGCG) from Green Tea Using Mass Spectrometry

In an era where humanity is reinstating its lost hope and expectation on natural products, green tea occupies quite a position for what it has proven to be, in its endeavors for human welfare and health. Epigallocatechin-3-gallate (EGCG) is the key to the vast biological activities of green tea. Green tea is no longer in the backdrop; it has emerged as the most viral, trending bioactive molecule when it comes to health benefits for human beings. This review focuses on the use of various analytical techniques for the analysis of EGCG. That which has been achieved so far, in terms of in vitro, pure component analysis, as well as those spikes in biological fluids and those in vivo in animal and human samples, was surveyed and presented. The use of MS-based techniques for the analysis of EGCG is elaborately reviewed and the need for improvising the applications is explained. The review emphasizes that there is plenty of room to explore matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) applications in this subject area.

Recent techniques for the authentication of the geographical origin of tea leaves from camellia sinensis: A review

Tea is one of the most important beverages worldwide, is produced in several distinct geographical regions, and is traded on the global market. The ability to determine the geographical origin of tea products helps to ensure authenticity and traceability. This paper reviews the recent research on authentication of tea using a combination of instrumental and chemometric methods. To determine the production region of a tea sample, instrumental methods based on analyzing isotope and mineral element contents are suitable because they are less affected by tea variety and processing methods. Chemometric analysis has proven to be a valuable method to identify tea. Principal component analysis (PCA) and linear discriminant analysis (LDA) are the most preferred methods for processing large amounts of data obtained through instrumental component analysis.

Advanced Analytical Approaches for the Analysis of Polyphenols in Plants Matrices—A Review

Phenolic compounds are plants’ bioactive metabolites that have been studied for their ability to confer extensive benefits to human health. As currently there is an increased interest in natural compounds identification and characterization, new analytical methods based on advanced technologies have been developed. This paper summarizes current advances in the state of the art for polyphenols identification and quantification. Analytical techniques ranging from high-pressure liquid chromatography to hyphenated spectrometric methods are discussed. The topic of high-resolution mass spectrometry, from targeted quantification to untargeted comprehensive chemical profiling, is particularly addressed. Structure elucidation is one of the important steps for natural products research. Mass spectral data handling approaches, including acquisition mode selection, accurate mass measurements, elemental composition, mass spectral library search algorithms and structure confirmation through mass fragmentation pathways, are discussed.

SS, Kumar K. R, Narayan Sinha S. Method development and validation for rapid identification of epigallocatechin gallate using ultra-high performance liquid chromatography

Although Epigallocatechin gallate (EGCG) is the most available and beneficial catechin found in tea, its auto-oxidation property may lead to toxicity when consumed in large quantities. Thus, there is a need to quantify the EGCG, which enables to study the pharmacological characteristics of the compound. The study aimed to develop and validate a rapid and accurate analytical method for quantitative determination of EGCG. Standard EGCG was used to conduct trials for the optimization of the analytical method using Ultra-High Performance Liquid Chromatography (UHPLC). Tests for validation (specificity, linearity, accuracy, system suitability, method precision, robustness, and ruggedness) were performed. The preliminary trials yielded an analytical method with good peak shape and acceptable system suitability which was further validated. The method was shown to be specific, with a linear correlation coefficient of > 0.9996 and accurate with acceptable recovery rate (99.1% to 100.4%). Acceptable system suitability and method precision were confirmed with a relative standard deviation (less than 2%). Further, robustness and ruggedness experiments also demonstrated the suitability of the present analytical method. The method developed for determination of EGCG was validated as per the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) guidelines and thus can be used in routine compliance tests in the laboratory for further studying/characterizing the properties of EGCG.

Cross-Category Tea Polyphenols Evaluation Model Based on Feature Fusion of Electronic Nose and Hyperspectral Imagery

Tea polyphenols are important ingredients for evaluating tea quality. The rapid development of sensors provides an efficient method for nondestructive detection of tea polyphenols. Previous studies have shown that features obtained from single or multiple sensors yield better results in detecting interior tea quality. However, due to their lack of external features, it is difficult to meet the general evaluation model for the quality of the interior and exterior of tea. In addition, some features do not fully reflect the sensor signals of tea for several categories. Therefore, a feature fusion method based on time and frequency domains from electronic nose (E-nose) and hyperspectral imagery (HSI) is proposed to estimate the polyphenol content of tea for cross-category evaluation. The random forest and the gradient boosting decision tree (GBDT) are used to evaluate the feature importance to obtain the optimized features. Three models based on different features for cross-category tea (black tea, green tea, and yellow tea) were compared, including grid support vector regression (Grid-SVR), random forest (RF), and extreme gradient boosting (XGBoost). The results show that the accuracy of fusion features based on the time and frequency domain from the electronic nose and hyperspectral image system is higher than that of the features from single sensor. Whether based on all original features or optimized features, the performance of XGBoost is the best among the three regression algorithms (R² = 0.998, RMSE = 0.434). Results indicate that the proposed method in this study can improve the estimation accuracy of tea polyphenol content for cross-category evaluation, which provides a technical basis for predicting other components of tea.

Anti-obesity effects of instant fermented teas in vitro and in mice with high-fat-diet-induced obesity

Obesity is a chronic metabolic disorder that is associated with higher risks of developing diabetes and cardiovascular disease. Chinese dark tea is a fermented beverage with many biological effects and could be considered for the management of obesity. This study is aimed to assess the possible anti-obesity properties of instant dark tea (IDT) and instant pu-erh tea (PET) in high fat diet (HFD)-fed mice. Male C57BL/6 mice were divided into 5 groups. They received low-fat diet (LFD), HFD, HFD supplemented with drinking IDT infusion (5 mg mL-1), PET infusion (5 mg mL-1) or water for 8 weeks. The results showed IDT exhibited better inhibitory effect than PET on body weight gain and visceral fat weights. IDT also improved the serum high-density lipoprotein cholesterol (HDL-C) level, but decreased the low-density lipoprotein cholesterol (LDL-C) and leptin levels more effectively than PET. Both IDT and PET lowered the levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) in the plasma and significantly increased the ratio of albumin to globin (A/G) in the serum compared to the control group. IDT treatment reduced the malondialdehyde (MDA) level in the liver. Histomorphology evidenced that the liver tissue architecture was well preserved by IDT administration. Moreover, IDT regulated the expression of obesity-related genes more effectively than PET. Overall, the present findings have provided the proof of concept that dietary IDT could provide a safer and cost-effective option for people with HFD-induced obesity.

Effect of Acute Ingestion of Green Tea Extract and Lemon Juice on Oxidative Stress and Lipid Profile in Pigs Fed a High-Fat Diet

Green tea and its catechins have been shown to ameliorate high fat diet-induced oxidative stress and hyperlipidemia. However, low bioavailability of catechins limits their therapeutic potential. Lemon juice (LJ) has been suggested to enhance the bioavailability of catechins in vitro. This study investigated the antioxidative and hypolipidemic efficacy of a single dose of green tea extract (GTE) or GTE plus LJ (GTE + LJ) in high-fat diet fed pigs. Sixteen pigs ingested a single dose of GTE (190 mg/kg/day) or GTE + LJ (0.75 mL/kg/day) mixed with low-fat (LF; 5% fat) or high-fat (HF; 22% fat) diets and blood samples were collected for 24 h. Plasma catechin level peaked at two hours, and gradually returned to baseline after six hours following the intake. The addition of LJ significantly increased plasma catechin level. The diet containing GTE did not lower plasma cholesterol and triacylglycerol (TG) concentrations, superoxide dismutase (SOD) and catalase activity, or malondialdehyde concentration in 24 h in HF-fed pigs. Addition of a single dose of LJ, however, significantly decreased plasma TG level in LF groups but did not cause further changes on any other markers compared to the GTE alone. Our findings indicate limited effect of a single meal containing GTE on plasma antioxidant enzymes, lipid profile, and lipid peroxidation in pigs and no significant synergistic/additive action of adding LJ to GTE within 24 h in pigs. A study with a longer treatment period is warranted to further understand the potential role of GTE in reducing HF diet-induced oxidative stress and the possible synergistic role of LJ.

Theaflavins Improve Insulin Sensitivity through Regulating Mitochondrial Biosynthesis in Palmitic Acid-Induced HepG2 Cells

Theaflavins, the characteristic and bioactive polyphenols in black tea, possess the potential improving effects on insulin resistance-associated metabolic abnormalities, including obesity and type 2 diabetes mellitus. However, the related molecular mechanisms are still unclear. In this research, we investigated the protective effects of theaflavins against insulin resistance in HepG2 cells induced by palmitic acid. Theaflavins significantly increased glucose uptake of insulin-resistant cells at noncytotoxic doses. This activity was mediated by upregulating the total and membrane bound glucose transporter 4 protein expressions, increasing the phosphor-Akt (Ser473) level, and decreasing the phosphorylation of IRS-1 at Ser307. Moreover, theaflavins were found to enhance the mitochondrial DNA copy number, down-regulate the PGC-1β mRNA level and increase the PRC mRNA expression. Mdivi-1, a selective mitochondrial division inhibitor, could attenuate TFs-induced promotion of glucose uptake in insulin-resistant HepG2 cells. Taken together, these results suggested that theaflavins could improve hepatocellular insulin resistance induced by free fatty acids, at least partly through promoting mitochondrial biogenesis. Theaflavins are promising functional food ingredients and medicines for improving insulin resistance-related disorders.

Gene Discovery of Characteristic Metabolic Pathways in the Tea Plant (Camellia sinensis) Using 'Omics'-Based Network Approaches: A Future Perspective

Characteristic secondary metabolites, including flavonoids, theanine and caffeine, in the tea plant (Camellia sinensis) are the primary sources of the rich flavors, fresh taste, and health benefits of tea. The decoding of genes involved in these characteristic components is still significantly lagging, which lays an obstacle for applied genetic improvement and metabolic engineering. With the popularity of high-throughout transcriptomics and metabolomics, 'omics'-based network approaches, such as gene co-expression network and gene-to-metabolite network, have emerged as powerful tools for gene discovery of plant-specialized (secondary) metabolism. Thus, it is pivotal to summarize and introduce such system-based strategies in facilitating gene identification of characteristic metabolic pathways in the tea plant (or other plants). In this review, we describe recent advances in transcriptomics and metabolomics for transcript and metabolite profiling, and highlight 'omics'-based network strategies using successful examples in model and non-model plants. Further, we summarize recent progress in 'omics' analysis for gene identification of characteristic metabolites in the tea plant. Limitations of the current strategies are discussed by comparison with 'omics'-based network approaches. Finally, we demonstrate the potential of introducing such network strategies in the tea plant, with a prospects ending for a promising network discovery of characteristic metabolite genes in the tea plant.