Untargeted metabolomics coupled with chemometrics analysis reveals potential non-volatile markers during oolong tea shaking

The Fermentation Degree Prediction Model for Tieguanyin Oolong Tea Based on Visual and Sensing Technologies

The fermentation of oolong tea is a critical process that determines its quality and flavor. Current fermentation control relies on tea makers' sensory experience, which is labor-intensive and time-consuming. In this study, using Tieguanyin oolong tea as the research object, features including the tea water loss rate, aroma, image color, and texture were obtained using weight sensors, a tin oxide-type gas sensor, and a visual acquisition system. Support vector regression (SVR), random forest (RF) machine learning, and long short-term memory (LSTM) deep learning algorithms were employed to establish models for assessing the fermentation degree based on both single features and fused multi-source features, respectively. The results showed that in the test set of the fermentation degree models based on single features, the mean absolute error (MAE) ranged from 4.537 to 6.732, the root mean square error (RMSE) ranged from 5.980 to 9.416, and the coefficient of determination (R2) values varied between 0.898 and 0.959. In contrast, the data fusion models demonstrated superior performance, with the MAE reduced to 2.232-2.783, the RMSE reduced to 2.693-3.969, and R2 increased to 0.982-0.991, confirming that feature fusion enhanced characterization accuracy. Finally, the Sparrow Search Algorithm (SSA) was applied to optimize the data fusion models. After optimization, the models exhibited a MAE ranging from 1.703 to 2.078, a RMSE from 2.258 to 3.230, and R2 values between 0.988 and 0.994 on the test set. The application of the SSA further enhanced model accuracy, with the Fusion-SSA-LSTM model demonstrating the best performance. The research results enable online real-time monitoring of the fermentation degree of Tieguanyin oolong tea, which contributes to the automated production of Tieguanyin oolong tea.

Effect of shaking and piling processing on improving the aroma quality of green tea

Aroma plays a crucial role in the quality of pure green tea beverage. However, there are limited methods to improve their aroma. In this study, green tea produced using shaking and piling process (SPGT) demonstrated a notable improvement in aromatic intensity, particularly in floral, fruity, and sweet notes. A total of 58 volatile compounds were detected, with SPGT exhibiting the highest concentration of aroma compounds among the tested green teas. Eight key aroma compounds were selected based on a relative odor activity value (ROAV) greater than 1 in SPGT: dimethyl sulfide (71.14, cooked corn-like), 2-methylbutanal (3.17, cereal), octanal (1.31, fruity), linalool (5.25, floral), nonanal (5.00, floral), (E)-2-nonenal (2.81, cucumber), decanal (22.90, fruity), and β-ionone (60.51, floral). The concentration of aroma compounds, especially for floral and fruity key volatile compounds significantly increased during the shaking and piling process (p < 0.05), and their formation pathways help explained these changes. Our results provided a new theoretical foundation and practical guidelines for producing the high-aroma green tea.

Analytical approaches to flavor research and discovery: from sensory-guided techniques to flavoromics methods

This review examines analytical methodology for food flavor analysis. Traditionally, flavor chemistry research has relied on sensory-guided chromatography techniques to identify individual compounds responsible for aroma or taste activity. Among the over 12,000 volatile compounds identified in foods, hundreds have been linked to aroma characteristics, and many taste-active compounds have also been discovered. However analytical methods based on singular compound evaluation are not without limitation and can overlook drivers of flavor perception by ignoring potential stimuli (i.e. antagonists, modulators), interactions among stimuli, and sub-threshold activity. More recently, chemical profiling methods coupled with multivariate analysis, termed flavoromics, have led to advances in flavor research. Utilization of flavoromic methods provides additional opportunities to define chemical stimuli that influence flavor profiles and qualities of food, as well as their contributions to complex perceptions, such as consumer acceptance.

Targeted quantitative metabolomic and flavor objective quantification technique reveal the impact mechanism of shaking on black tea quality and non-volatile metabolites

Shaking constitutes a pivotal technique for enhancing black tea quality; nevertheless, its impact on the transformation mechanism of non-volatile metabolites (NVMs) in black tea remains obscure. The present study aimed to investigate the impact of shaking-withering methods (SWM) and traditional-withering methods (TWM) on black tea quality and NVMs conversion. A total of 57 NVMs and 14 objective quantitative indicators were obtained. SWM enhanced sweetness and umami taste, as well as appearance and liquor color brightness of black tea. Eight key differential NVMs were identified by multivariate statistical and dose over threshold value analysis. Metabolic pathway and evolution law analysis revealed that SWM enhanced the oxidation of catechins and flavonol glycosides, promoted the decarboxylation of glutamic acid, then facilitated the formation of theaflavin-3,3'-digallate, finally enhanced the taste and color quality of black tea. This study offers theoretical guidance and technical support for the targeted processing of high-quality black tea.

Spatio-temporal plant hormonomics: from tissue to subcellular resolution

Due to technological advances in mass spectrometry, significant progress has been achieved recently in plant hormone research. Nowadays, plant hormonomics is well established as a fully integrated scientific field focused on the analysis of phytohormones, mainly on their isolation, identification, and spatiotemporal quantification in plants. This review represents a comprehensive meta-study of the advances in the phytohormone analysis by mass spectrometry over the past decade. To address current trends and future perspectives, Web of Science data were systematically collected and key features such as mass spectrometry-based analyses were evaluated using multivariate data analysis methods. Our findings showed that plant hormonomics is currently divided into targeted and untargeted approaches. Both aim to miniaturize the sample, allowing high-resolution quantification to be covered in plant organs as well as subcellular compartments. Therefore, we can study plant hormone biosynthesis, metabolism, and signalling at a spatio-temporal resolution. Moreover, this trend has recently been accelerated by technological advances such as fluorescence-activated cell sorting or mass spectrometry imaging.

A Gas Sensors Detection System for Real-Time Monitoring of Changes in Volatile Organic Compounds during Oolong Tea Processing

The oxidation step in Oolong tea processing significantly influences its final flavor and aroma. In this study, a gas sensors detection system based on 13 metal oxide semiconductors with strong stability and sensitivity to the aroma during the Oolong tea oxidation production is proposed. The gas sensors detection system consists of a gas path, a signal acquisition module, and a signal processing module. The characteristic response signals of the sensor exhibit rapid release of volatile organic compounds (VOCs) such as aldehydes, alcohols, and olefins during oxidative production. Furthermore, principal component analysis (PCA) is used to extract the features of the collected signals. Then, three classical recognition models and two convolutional neural network (CNN) deep learning models were established, including linear discriminant analysis (LDA), k-nearest neighbors (KNN), back-propagation neural network (BP-ANN), LeNet5, and AlexNet. The results indicate that the BP-ANN model achieved optimal recognition performance with a 3-4-1 topology at pc = 3 with accuracy rates for the calibration and prediction of 94.16% and 94.11%, respectively. Therefore, the proposed gas sensors detection system can effectively differentiate between the distinct stages of the Oolong tea oxidation process. This work can improve the stability of Oolong tea products and facilitate the automation of the oxidation process. The detection system is capable of long-term online real-time monitoring of the processing process.

Metabolite Profiling Reveals the Dynamic Changes in Non-Volatiles and Volatiles during the Enzymatic-Catalyzed Processing of Aijiao Oolong Tea

The enzymatic reaction stage (ECS) of oolong tea processing plays an important role in the formation of the flavor quality of the oolong tea. To investigate the dynamic changes in the volatile and non-volatile components in the leaves of oolong tea during the ECS, metabolomic studies were carried out using the leaf samples collected at different stages of the ECS of Aijiao oolong tea. Out of the identified 306 non-volatile metabolites and 85 volatile metabolites, 159 non-volatile metabolites and 42 volatile metabolites were screened out as key differential metabolites for dynamic changes during the ECS. A multivariate statistical analysis on the key differential metabolites showed that the accumulations of most metabolites exhibited dynamic changes, while some amino acids, nucleosides, and organic acids accumulated significantly after turning-over treatment. The evolution characteristics of 27 key precursors or transformed VOCs during the ECS of Aijiao oolong tea were clarified, and it was found that the synthesis of aroma substances was mainly concentrated in lipids as precursors and glycosides as precursor pathways. The results revealed the dynamic changes in the flavor metabolites in the ECS during the processing of Aijiao oolong tea, which provided valuable information for the formation of the characteristic flavor of Aijiao oolong tea.

Effect of shaking on the improvement of aroma quality and transformation of volatile metabolites in black tea

Shaking is an innovative technology employed in black tea processing to enhance flavor. However, the effects of shaking on the evolutionary mechanisms of volatile metabolites (VMs) remain unclear. In this study, we compared the effects of a shaking-withering method with those of traditional withering on the flavor and VMs transformation of black tea. The results showed that black tea treated with shaking exhibited excellent quality with floral and fruity aroma. Based on gas chromatography-tandem mass spectrometry, 128 VMs (eight categories) were detected. Combining variable importance projection with odor activity value analysis, eight key differential VMs were identified. Shaking could promote the oxidative degradation of fatty acids and carotenoids and modulate the biosynthesis of terpenoids to facilitate the formation of floral/fruity VMs (such as (Z)-hexanoic acid-3-hexenyl ester, ethyl hexanoate, trans-β-ionone, and decanal). Our findings provide theoretical guidance for the production of high-quality black tea with floral and fruity aromas.

Optimizing Processing Techniques of Oolong Tea Balancing between High Retention of Catechins and Sensory Quality

Catechins are the major flavor substances in teas, which have a variety of health effects; however, high catechin and high sensory quality are a pair of contradictions that are difficult to coordinate. To explore the processing procedure with high catechins and high sensory quality, a single-factor processing experiment was carried out over the processing production of oolong tea. Combined with orthogonal partial least square discriminant analysis (OPLS-DA), correlation analysis, and principal component analysis (PCA), the optimal production procedure for oolong tea is as follows: red light withering for 8 h, leaf rotating for 10 min with a total standing time for 8 h, drum roasting for 5 min at 290 °C, low-temperature rolling (flattening at 4 °C for 5 min, without pressure for 1 min and under pressure for 5 min), microwave drying (800 W for 7.5 min). This study demonstrates a significant increase in the retention of catechins, which contributes to the mellow and brisk tastes of oolong tea, addressing the challenge of catechin content and sensory quality. Our study provides a novel insight into the relationship between the oolong tea processing and flavor formation.

Contribution of traditional deep fermentation to volatile metabolites and odor characteristics of Wuyi rock tea

Fermentation is extremely important for the formation of the special flavor of Wuyi rock tea. This study determined volatile metabolite contents using GC-MS technique and futher analyzed their odor characteristics during the traditional deep fermentation technology of Wuyi rock tea. The results showed that 17 characteristic compounds significantly changed during the first stage of the preliminary processing, namely fresh leaves, withering and fermentation. The key to the formation of floral aroma lied in dihydromyrcenol, and the woody aroma derived from six terpenoids, and their synthesis depended on dihydromyrcenol content. The fruity aroma was dominated by six esters, and the fruity aroma mainly came from (Z) -3-hexen-1-yl butyrate, (E) -3-hexen-1-yl butyrate and 5-Hexenyl butyrate. This study provided an important theoretical and practical basis for improving the preliminary processing of Wuyi rock tea.

Aroma characteristics of Wuyi rock tea prepared from 16 different tea plant varieties

Wuyi rock tea (WRT) is famous for its long history and unique characteristic of floral, fruity and nutty flavors. This study investigated the aroma characteristics of WRTs prepared from 16 different oolong tea plant varieties. The sensory evaluation results showed that all WRTs had an 'Yan flavor' taste, and the odor was strong and lasting. Roasted, floral and fruity odors were the prime aroma profiles for WRTs. Furthermore, a total of 368 volatile compounds were detected using HS-SPME-GC-MS and analyzed with OPLS-DA and HCA methods. The volatile compounds heterocyclic compounds, esters, hydrocarbons, terpenoids and ketones were the major aromatic components of the WRTs. Specifically, the volatile profiles among newly selected cultivars were comparatively analyzed, and 205 differential volatile compounds were found with variable importance in the projection (VIP) values above 1.0. These results indicated that the aroma profiles of WRTs were mainly dependent on the cultivar specificities of volatile compounds.

Identification and Analysis of Metabolites That Contribute to the Formation of Distinctive Flavour Components of Laoxianghuang

In addition to volatile compounds, metabolites also have a great effect on the flavour of food. Fresh finger citron cannot be eaten directly because of its spicy and bitter taste, so it is made into a preserved fruit product known as Laoxianghuang (LXH). To investigate the metabolites that have an effect on the flavour of LXH, untargeted metabolomics was performed using an ultrahigh-performance liquid chromatography with tandem mass spectrometry (UPLC-MS/MS), and the metabolites of the Laoxianghuang samples from different locations in the Chaoshan area were compared and analysed. A total of 756 metabolites were identified and distinct differences were revealed among the different Laoxianghuang samples. A total of 33 differential metabolites with the most significant changes were screened through further multivariate analytical steps, and each group of samples had unique metabolites. For instance, pomolic acid had the highest content in the JG sample, while L-glycyl-L-isoleucine was rich in the QS sample. Moreover, flavonoid metabolites made the greatest contribution to the unique flavour of Laoxianghuang. The metabolic pathways involved are the biosynthetic pathways of flavonoids, isoflavonoids, flavones, and flavonols. This study can provide some creative information for distinguishing the quality differences of Laoxianghuang from the perspective of metabolites and offer preliminary theoretical support to characterise the formation of flavour substances in Laoxianghuang.

Analysis of metabolites in green tea during the roasting process using non-targeted metabolomics

BACKGROUND

Roasting plays an important role in the formation of flavor of roasted green tea; however, the changes in chemicals during this process have not been systematically studied until now. To reveal the dynamic changes in chemicals in green tea during roasting, non-targeted metabolomics, coupled with chemometrics, was employed.

RESULTS

A total of 101 non-volatile metabolites were identified in tea samples, and 29 metabolites were identified as characteristic metabolites of roasting. A significant increase in catechins and their derivatives, organic acids, and flavonoid glycosides was observed, while the content of some amino acids and their derivatives decreased over 50% during roasting. The content of theanine glucoside increased dramatically (by 21.23-fold at the roasting stage), and Maillard-derived compounds also increased to varying degrees.

CONCLUSION

Glycosylation, oxidative polymerization, and pyrolysis were important reactions responsible for the formation and transformation of flavor compounds in roasted green tea during roasting. © 2022 Society of Chemical Industry.

Directed Accumulation of Nitrogen Metabolites through Processing Endows Wuyi Rock Tea with Singular Qualities

The execution of specific processing protocols endows Wuyi rock tea with distinctive qualities produced through signature metabolic processes. In this work, tea leaves were collected before and after each of three processing stages for both targeted and untargeted metabolomic analysis. Metabolic profiles of processing stages through each processing stage of rotation, pan-firing and roasting were studied. Overall, 614 metabolites were significantly altered, predominantly through nitrogen- enriching (N) pathways. Roasting led to the enrichment of 342 N metabolites, including 34 lipids, 17 organic acids, 32 alkaloids and 25 amino acids, as well as secondary derivatives beneficial for tea quality. This distinctive shift towards enrichment of N metabolites strongly supports concluding that this directed accumulation of N metabolites is how each of the three processing stages endows Wuyi rock tea with singular quality.

The chemistry, processing, and preclinical anti-hyperuricemia potential of tea: a comprehensive review

Hyperuricemia is an abnormal purine metabolic disease that occurs when there is an excess of uric acid in the blood, associated with cardiovascular diseases, hypertension, gout, and renal disease. Dietary intervention is one of the most promising strategies for preventing hyperuricemia and controlling uric acid concentrations. Tea (Camellia sinensis) is known as one of the most common beverages and the source of dietary polyphenols. However, the effect of tea on hyperuricemia is unclear. Recent evidence shows that a lower risk of hyperuricemia is associated with tea intake. To better understand the anti-hyperuricemia effect of tea, this review first briefly describes the pathogenesis of hyperuricemia and the processing techniques of different types of tea. Next, the epidemiological and experimental studies of tea and its bioactive compounds on hyperuricemia in recent years were reviewed. Particular attention was paid to the anti-hyperuricemia mechanisms targeting the hepatic uric acid synthase, renal uric acid transporters, and intestinal microbiota. Additionally, the desirable intake of tea for preventing hyperuricemia is provided. Understanding the anti-hyperuricemia effect and mechanisms of tea can better utilize it as a preventive dietary strategy.HighlightsHigh purine diet, excessive alcohol/fructose consumption, and less exercise/sleep are the induction factors of hyperuricemia.Tea and tea compounds showed alleviated effects for hyperuricemia, especially polyphenols.Tea (containing caffeine or not) is not associated with a higher risk of hyperuricemia.Xanthine oxidase inhibition (reduce uric acid production), Nrf2 activation, and urate transporters regulation (increase uric acid excretion) are the potential molecular targets of anti-hyperuricemic effect of tea.About 5 g tea intake per day may be beneficial for hyperuricemia prevention.

Fatty Acid Profiling in Kernels Coupled with Chemometric Analyses as a Feasible Strategy for the Discrimination of Different Walnuts

Walnuts have high oil content in their kernels, and they have attracted considerable attention in the food, beverage, nutrient, and health fields because of their delicious taste and potential health benefits. Fatty acid profiles of kernels vary depending on walnuts species, ontogenic variations, and planting environments. To determine the key indicators that can be used to distinguish different walnuts using chemometric analyses, the fatty acid compositions and contents of 72 walnut samples were measured and evaluated. Three fatty acids, oleic acid (21.66%), linoleic acid (56.40%), and linolenic acid (10.50%), were the most common fatty acid components in the kernels. Palmitic acid and linolenic acid in kernels were found to be indicators to rank the walnuts into five levels. Three groups were identified based on of several chemometrics. Oleic acid in kernels was typical fatty acid that could be used to distinguish three walnut groups based on the results of discriminant analysis, while oleic acid and linoleic acid were key differential fatty acids on the discrimination of each group based on the result of orthogonal partial least squares discriminant analysis. This study provides information on how to classify walnuts from different geographical locations based on kernel fatty acid profiling and provides an approach to identify possible adulterations in walnuts on the markets. Moreover, the results are potentially relevant to quality assessments of walnuts.

Analysis of the characteristic compounds of Citri Sarcodactylis Fructus from different geographical origins

INTRODUCTION

Citri Sarcodactylis Fructus (CSF) is widely used as a food ingredient and a traditional Chinese medicine. In China, CSF is cultivated in many places, including Sichuan, Guangdong, Zhejiang, and Fujian provinces. The types and chemical contents of CSF from different origins may vary greatly due to the difference in climate and environmental conditions. Therefore, comparing the chemical composition of CSF from various places is vital.

OBJECTIVE

To rapidly select potential characteristic compounds for differentiating CSF from different origins.

MATERIAL AND METHODS

Thirty-one batches of CSF samples from different regions were analysed using ultra-performance liquid chromatography with hybrid quadrupole-orbitrap high-resolution mass spectrometry. Thereafter, chemometric methods, including principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA), were employed to find differential metabolites among the CSF samples from various origins.

RESULTS

PCA revealed 77.9% of the total variance and divided all CSF samples into three categories corresponding to their origins. OPLS-DA displayed better discrimination of CSF from different sources, with R² X, R² Y, and Q² of 0.801, 0.985, and 0.849, respectively. Finally, 203 differential metabolites were obtained from CSF from different origins using the variable importance in projection of the OPLS-DA model, 30 of which were identified, and five coumarin compounds were selected as marker compounds discriminating CSF from different origins.

CONCLUSION

This work provides a practical strategy for classifying CSF from different origins and offers a research foundation for the quality control of CSF.

Volatile Oil Profile of Prickly Ash (Zanthoxylum) Pericarps from Different Locations in China

Volatile oils of prickly ash (Zanthoxylum) pericarps have various potential biological functions with considerable relevance to food, pharmacological, and industrial applications. The volatile profile of oils extracted from prickly ash pericarps obtained from 72 plantations in China was determined by gas chromatography and mass spectrometry. Several chemometric analyses were used to better understand the volatile oil profile differences among different pericarps and to determine the key factors that affected geographical variations in the main volatile constituents of oils. A total of 47 constituents were detected with D-limonene, alfa-myrcene, and linalool as the most abundant. The volatile profile of pericarp oils was significantly affected by prickly ash species and some environmental factors, and the key factors that affected volatile profile variations for different prickly ash species were diverse. Chemometric analyses based on the volatile oil profile could properly distinguish Z. armatum pericarps from other pericarps. This study provides comprehensive information on the volatile oil profile of pericarps from different prickly ash species and different plantations, and it can be beneficial to a system for evaluating of pericarp quality. Moreover, this study speculates on the key environmental factors that cause volatile oil variations for each species, and can help to obtain better prickly ash pericarp volatile oils by improving the cultivated environments.

Quality chemical analysis of crush-tear-curl (CTC) black tea from different geographical regions based on UHPLC-Orbitrap-MS

Crush-tear-curl (CTC) black tea is a popular beverage, owing to its unique taste characteristics and health benefits. However, differences in the taste quality and chemical profiles of CTC black tea from different geographical regions remain unclear. In this study, 28 CTC black tea samples were collected from six geographical regions and analyzed using electronic tongue and ultrahigh performance liquid chromatography-Orbitrap-mass spectroscopy. The e-tongue analysis indicated that each region's CTC black tea has its own relatively prominent taste characteristics: Sri Lanka (more umami and astringent), North India (more umami), China (more sweetness and astringent), South India (moderate umami and sweetness), and Kenya (moderate umami and astringent). Based on multivariate statistical analysis, 78 metabolites were tentatively identified and used as potential markers for CTC black tea of different origins, mainly including amino acids, flavone/flavonol glycosides, and pigments. Different metabolites, which contributed to the taste characteristics of CTC black tea, were clarified by partial least squares regression correlation analysis. Our findings may serve as useful references for future studies on origin traceability and quality characteristic determination of CTC black teas. PRACTICAL APPLICATION: This study provides useful references for future studies on the origin traceability and taste characteristic determination of CTC black teas from different geographical regions.

Alkylamide Profiling of Pericarps Coupled with Chemometric Analysis to Distinguish Prickly Ash Pericarps

Because of extensive cultivation areas, various cultivars, nonstandard naming notations, and morphology similarity among relative cultivars, adulteration and associated business fraud may happen in the marketplaces of prickly ash pericarps due to higher financial gain and high-frequency trading. This study presents variations in the chemical components and contents of different prickly ash species from different plantations. Alkylamide profiling of pericarps derived from Zanthoxylum armatum, Z. bungeanum, and some relative Zanthoxylum species from 72 plantations across China were tested using ultra-performance liquid chromatography. Then, several chemometrics were applied to classify the prickly ash pericarps to reveal potential indicators that distinguish prickly ash pericarps and to identify the key factors that affect pericarp alkylamide profiling. The dominating alkylamides in the prickly ash pericarps were Z. piperitum (ZP)-amide C (0–20.64 mg/g) and ZP-amide D (0–30.43 mg/g). Alkylamide profiling of prickly ash pericarps varied significantly across species and geographical variations. ZP-amide D in prickly ash pericarps was identified as a potential indicator to distinguish prickly ash species. Longitude and aluminum content in soils were identified as key factors that affected alkylamide profiling of prickly ash pericarps. This study provides a useful tool to classify prickly ash species based on pericarp alkylamide profiling and to determine the key influence factors on pericarp alkylamide variations.

Combining solid dispersion-based spray drying with cyclodextrin to improve the functionality and mitigate the beany odor of pea protein isolate

The beany flavor of pea protein limits its application in the food industry. This study aimed at addressing this problem by combining the advantages of solid-based spray drying technique and the ability of cyclodextrins (CD) to entrap volatiles. Pea protein isolates (PPI) was extracted by alkaline extraction-isoelectric precipitation, followed by co-spray drying with CD. The resulted PPI-CD showed no major structure changes. HS-SPME-GC-MS coupled to untargeted metabolomics successfully identified 23 aroma compounds that represent the different odorants among PPI-control, physically mixed PPI-CD, and co-spray dried PPI-CD samples. Heat map analysis also showed a remarkable beany odor mitigation effect upon the addition of CD, which was further proved to be due to CD entrapping aroma compounds during spray drying. In the meantime, the functional attributes of PPI-CD were not adversely impacted by the addition of CD.

Spleen and thymus metabolomics strategy to explore the immunoregulatory mechanism of total withanolides from the leaves of Datura metel L. on imiquimod-induced psoriatic skin dermatitis in mice

Our previous work demonstrated that total withanolides of Datura metel L. leaves (TWD) exhibited excellent therapeutic effects on psoriasis. However, current knowledge of its mechanisms is incomplete. In this study, integrated spleen and thymus untargeted metabolomics were used to analyze the changes in endogenous metabolites underlying the immunosuppressive activity of TWD on psoriasis animal models induced by imiquimod. The results suggested that TWD treatment markedly attenuated imiquimod-induced psoriasis and showed significant immunosuppressive activity as evidenced by decreased elevation index of spleen and thymus. Meanwhile, TWD significantly reversed the elevation of immunoregulatory factors, including IL-10, IL-17, IL-22 and IL-23. Multivariate trajectory analysis revealed that TWD treatment could restore the psoriasis-disturbed spleen and thymus metabolite profiles towards the normal metabolic status. A total of 25 and 27 metabolites associated with the immunomodulatory effects for which levels changed markedly upon treatment have been identified in spleen and thymus, respectively. These differential metabolites were mainly involved in amino acid metabolism, nucleotide metabolism, fatty acid metabolism and lipid metabolism. Our investigation provided a holistic view of TWD for intervention in psoriasis through immunoregulation and provided further scientific information in vivo about a clinical value of TWD for psoriasis.

Analytical strategy coupled to chemometrics to differentiate Camellia sinensis tea types based on phenolic composition, alkaloids, and amino acids

Catechins, amino acids, and alkaloids are primary chemical components of tea and play a crucial role in determining tea quality. Their composition and content largely vary among different types of tea. In this study, a convenient chemical classification method was developed for six Camellia sinensis tea types (white, green, oolong, black, dark, and yellow) based on the quantification of their major components. Twenty-one free amino acids, 6 catechins, 2 alkaloids, and gallic acid in 24 teas were quantified using ultra-high-performance liquid chromatography (UHPLC). The total catechin contents in these tea samples ranged from 10.96 to 95.67 mg/g, while total free amino acid content ranged from 2.63 to 25.89 mg/g. Theanine (Thea) was the most abundant amino acid in all tea varieties. Catechin and amino acid levels in tea were markedly reduced upon fermentation of tea. Furthermore, high-temperature processing (roasting) during tea production induced degradation and epimerization of catechins, yielding epimerized catechins, simple catechins, and gallic acid. Principal component analysis revealed that major ester-catechins (EGCG and ECG), major amino acids (Thea), and major alkaloids (caffeine) are potential factors for distinguishing different types of tea. Linear discriminant analysis showed that 100% of teas were correctly classified in which (+)-catechin, ECG, EGC, gallic acid, GABA, cysteine, lysine, and threonine were the most discriminating compounds. This study shows that quantification of the major tea components combined with chemometric analysis, can serve as a simple, convenient, and reliable approach for classifying tea according to fermentation level. PRACTICAL APPLICATION: Different Camellia sinensis tea types can be produced worldwide but it is still challenging to know which chemical markers can be used to trace their production. in this paper we used a targeted methodology to classify six tea types (white, green, oolong, black, dark, and yellow) based on phenolic composition, alkaloids, and amino acids. The main chemical markers responsible for the discrimination were pinpointed with the use of chemometric tools.

Bridging Targeted and Untargeted Mass Spectrometry-Based Metabolomics via Hybrid Approaches

This mini-review aims to discuss the development and applications of mass spectrometry (MS)-based hybrid approaches in metabolomics. Several recently developed hybrid approaches are introduced. Then, the overall workflow, frequently used instruments, data handling strategies, and applications are compared and their pros and cons are summarized. Overall, the improved repeatability and quantitative capability in large-scale MS-based metabolomics studies are demonstrated, in comparison to either targeted or untargeted metabolomics approaches alone. In summary, we expect this review to serve as a first attempt to highlight the development and applications of emerging hybrid approaches in metabolomics, and we believe that hybrid metabolomics approaches could have great potential in many future studies.

Integrated serum metabolomics and network pharmacology approach to reveal the potential mechanisms of withanolides from the leaves of Datura metel L. on psoriasis

Psoriasis is a chronic, immune-mediated inflammatory skin disease and highly depends on inflammation and angiogenesis as well as other pathways. Our previous study showed that the withanolides from the leaves of Datura metel L. exhibited significant therapeutically effect on psoriasis, but the mechanisms concerning this effect have not been systematically studied. The purpose of this paper was to investigate the possible mechanism of withanolides for treating psoriasis using an integrated metabolomics and network pharmacology strategy. Untargeted metabolomics profiling of serum with UHPLC/Orbitrap MS and a multivariate data method were performed to discover the potential biomarkers and metabolic pathways. Afterward, the compound-target-pathway network of withanolides for psoriasis was constructed by virtue of network pharmacology. Finally, the crucial pathways were selected by integrating the results of metabolomics and network pharmacology, and then validated by ELISA and western blot analysis. The results showed that withanolides could exert excellent effects on psoriasis through regulating two types of pathways, angiogenesis and inflammation, including sphingolipids metabolism and HIF-1α/VEGF pathway, reflected by inhibiting the production of inflammatory cytokines (IL-1β, IL-6, IL-8, IFN-γ, TNF-α, HIF-1α and VEGF), as well as reducing the protein expressions of HIF-1α and VEGF. Our study successfully explained the polypharmcological mechanisms underlying the efficiency of withanolides from the D. metel L. leaves on treating psoriasis. Meanwhile, it was also valuable for performing a systematical investigation of herb medicines, as well as for efficiently predicting the therapeutic mechanisms of traditional Chinese medicine.

Qualitative discrimination of Chinese dianhong black tea grades based on a handheld spectroscopy system coupled with chemometrics

The evaluation of Chinese dianhong black tea (CDBT) grades was an important indicator to ensure its quality. A handheld spectroscopy system combined with chemometrics was utilized to assess CDBT from eight grades. Both variables selection methods, namely genetic algorithm (GA) and successive projections algorithm (SPA), were employed to acquire the feature variables of each sample spectrum. A partial least-squares discriminant analysis (PLS-DA) and support vector machine (SVM) algorithms were applied for the establishment of the grading discrimination models based on near-infrared spectroscopy (NIRS). Comparisons of the portable and benchtop NIRS systems were implemented to obtain the optimal discriminant models. Experimental results showed that GA-SVM models by the handheld sensors yielded the best predictive performance with the correct discriminant rate (CDR) of 98.75% and 100% in the training set and prediction set, respectively. This study demonstrated that the handheld system combined with a suitable chemometric and feature information selection method could successfully be used for the rapid and efficient discrimination of CDBT rankings. It was promising to establish a specific economical portable NIRS sensor for in situ quality assurance of CDBT grades.