Orthogonal Projection On Latent Structure-discriminant Analysis Research Articles

1H NMR-based metabolomics of cacao pod husk: profile comparison of three drying treatments

Aim: The aim of this study is to apply untargeted proton nuclear magnetic resonance (1H NMR) and chemometric analysis to obtain the cacao pod husk (CPH) fingerprint and evaluate the effect of dehydration in the CPH metabolome. Methods: Phosphate buffer extracts (pH 6.5) were obtained and measured using a one-dimension (1D) 1H NMR spectrometry. The 1D 1H NMR spectra were recorded without spinning and using the presaturation (PRESAT) pulse sequence to suppress the residual H2O signal. The 3-(trimethylsilyl) propionic-2,2,3,3-d4 acid sodium salt (TSP) was used as an internal reference. Analysis of processed data, applying an orthogonal projection on latent structure-discriminant analysis (OPLS-DA) model was used to highlight significant differences between the three dehydration treatments. Signal assignment of CPH metabolites was carried out based on the coupling constant, software simulation prediction, published data comparison, and metabolomics databases. Results: A total of 25 compounds were detected by 1H NMR, methylxanthines, sugars, some amino acids, fatty acids, and organic acids were found among the identified compounds. The fingerprint spectra of the three dehydration methods were clustered separately discriminating the metabolome profile of each of the dehydration treatments, finding that metabolome remarkably differed in theanine, myristic acid, fumaric acid, and aspartic acid composition. Conclusions: An untargeted metabolomics to obtain the fingerprint of CPH was successfully established. A 1H NMR spectra with a detailed signal assignment aided to identify 25 metabolites present in CPH fresh and dried by different methods. The results complement the information about CPH composition and how it is affected by the temperature used during the dehydration process. The multivariate analysis points out that freeze drying (FD) preserves the metabolites better than microwave drying (MWD) or hot air drying (HAD). FD and MWD are similar in composition maintaining most of the compounds after drying.

The Footprint of Type 1 Diabetes on Red Blood Cells: A Metabolomic and Lipidomic Study.

The prevalence of diabetes type 1 (T1D) in the world populations is continuously growing. Although treatment methods are improving, the diagnostic is still symptom-based and sometimes far after onset of the disease. In this context, the aim of the study was the search of new biomarkers of the disease in red blood cells (RBCs), until now unexplored. The metabolomic and the lipidomic profile of RBCs from T1D patients and matched healthy controls was determined by NMR spectroscopy, and different multivariate discrimination models were built to select the metabolites and lipids that change most significantly. Relevant metabolites were further confirmed by univariate statistical analysis. Robust separation in the metabolomic and lipidomic profiles of RBCs from patients and controls was confirmed by orthogonal projection on latent structure discriminant analysis (OPLS-DA), random forest analysis, and significance analysis of metabolites (SAM). The main changes were detected in the levels of amino acids, organic acids, creatine and phosphocreatine, lipid change length, and choline derivatives, demonstrating changes in glycolysis, BCAA metabolism, and phospholipid metabolism. Our study proves that robust differences exist in the metabolic and lipidomic profile of RBCs from T1D patients, in comparison with matched healthy individuals. Some changes were similar to alterations found already in RBCs of T2D patients, but others seemed to be specific for type 1 diabetes. Thus, many of the metabolic differences found could be biomarker candidates for an earlier diagnosis or monitoring of patients with T1D.

Label-Free Liquid Chromatography-Mass Spectrometry Proteomic Analysis of the Urinary Proteome for Measuring the Escitalopram Treatment Response From Major Depressive Disorder.

Major depressive disorder (MDD) is a common mental disorder that can cause substantial impairments in quality of life. Clinical treatment is usually built on a trial-and-error method, which lasts ~12 weeks to evaluate whether the treatment is efficient, thereby leading to some inefficient treatment measures. Therefore, we intended to identify early candidate urine biomarkers to predict efficient treatment response in MDD patients. In this study, urine samples were collected twice from 19 respondent and 10 non-respondent MDD patients receiving 0-, 2-, and 12-week treatments with escitalopram. Differential urinary proteins were subsequently analyzed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Our two pilot tests suggested that the urine proteome reflects changes associated with major depressive disorder at the early stage of treatment measures. On week 2, 20 differential proteins were identified in the response group compared with week 0, with 14 of these proteins being associated with the mechanisms of MDD. In the non-response group, 60 differential proteins were identified at week 2, with 28 of these proteins being associated with the mechanisms of MDD. In addition, differential urinary proteins at week 2 between the response and non-response groups can be clearly distinguished by using orthogonal projection on latent structure-discriminant analysis (OPLS-DA). Our small pilot tests indicated that the urine proteome can reflect early effects of escitalopram therapy between the response and non-response groups since at week 2, which may provide potential early candidate urine biomarkers to predict efficient treatment measures in MDD patients.

The accumulation of plasma acylcarnitines are associated with poor immune recovery in HIV-infected individuals

BackgroundAntiretroviral therapy (ART) can reduce opportunistic infections and mortality rates among individuals infected with human immunodeficiency virus (HIV); however, some HIV-infected individuals exhibit poor immune recovery after ART. Hence, we explored the association between metabolome profiles and immune recovery in HIV-infected individuals following ART.MethodsAn untargeted metabolomics approach was used to analyze plasma samples from 18 HIV-negative individuals and 20 HIV-infected individuals, including 10 immunological non-responders (INR, CD4+ T cell rise < 100 cells/μl) and 10 immunological responders (IR, CD4+ T cell rise > 300 cells/μl) after 2 years of ART. These individuals were followed for the next 6 years and viral loads and CD4+ T cell count were measured regularly. Orthogonal projection on latent structures discriminant analysis (OPLS-DA), ANOVA, correlation, receiver operating characteristic (ROC), and survival analyses were used for selection of discriminant metabolites.ResultsEighteen lipid metabolites were identified which could distinguish among control, INR, and IR groups. Among them, myristoylcarnitine (MC), palmitoylcarnitine (PC), stearoylcarnitine (SC), and oleoylcarnitine (OC) were significantly elevated in INR plasma samples compared with those from the IR and control groups and were negatively associated with CD4+ T cell count. Additionally, ROC analysis using a combination of MC, PC, SC, and OC had high sensitivity and specificity for differentiating INR from IR (AUC = 0.94). Finally, survival analysis for the combination of MC, PC, SC, and OC demonstrated that it could predict CD4+ T cell count in patients undergoing long-term ART.ConclusionsHigh levels of lipid metabolites, MC, PC, SC, and OC are associated with poor immune recovery in patients receiving ART and these data provide potential new insights into immune recovery mechanisms.

Label-free proteomics for discovering biomarker candidates of RAD140 administration to castrated horses.

Selective androgen receptor (AR) modulators (SARMs) are potent anabolic agents with a high potential of misuse in horseracing and equestrian sports. In this study, we applied label-free proteomics to discover plasma protein biomarkers in geldings (castrated horses) after administration with a popular SARM named RAD140. Tryptic peptides were prepared from plasma samples and analyzed by nano-flow ultrahigh-performance liquid chromatography-high-resolution tandem mass spectrometry (nano-UHPLC-HRMS/MS) using data-independent acquisition (DIA) method. Orthogonal projection on latent structure-discriminant analysis (OPLS-DA) has led to the development of a predictive model that could discriminate RAD140-administered samples from control samples and could also correctly classify 18 out of 19 in-training horses as control samples. The model comprises 75 proteins with variable importance in projection (VIP) score above 1. Gene Ontology (GO) enrichment analysis and literature review have identified upregulation of AR-regulated clusterin, and proteins associated with inflammation (haptoglobin, cluster of differentiation 14 [CD14], and inter-alpha-trypsin inhibitor heavy chain 4 [ITIH4]) and erythropoiesis (glycosylphosphatidylinositol-specific phospholipase D1 [GPLD1]) after RAD140 administration. Their changes were confirmed by selected reaction monitoring (SRM) experiments. Similar effects have been reported by the use of androgens and other SARMs. This is the first reported study that describes the use of a proteomic biomarker approach to detect horses that have been administered with RAD140 by applying label-free proteomic profiling of plasma samples. These results support the concept of a biomarker-driven approach to enhance the doping control of RAD140 and potentially other SARMs in the future.

Multivariate analyses of the volatile components in fresh and dried turnip (Brassica rapa L.) chips via HS-SPME-GC-MS.

Turnipisavegetablethat has many health promoting effects. To diversify the usage and increase the consumption of turnip, the effects of hot air drying, infrared drying, explosion puff drying and freeze drying (FD) on the volatiles of turnip chips were studied. The volatiles of fresh turnip and dried turnip chips were isolated by HS-SPME-GC-MS and a total of 67 volatiles were identified. However, the volatiles in turnip chips dried by different methods are quite different. Based on principal component analysis and hierarchical cluster analysis, the volatiles of fresh turnip were distinguished from those of the dried chips and FD was separated from the other drying methods. As the result of orthogonal projection on latent structure-discriminant analysis (OPLS-DA), isothiocyanato-cyclopropane and (2-isothiocyanatoethyl)-benzene were identified as the characteristic volatiles of fresh turnip. While, 2-azido-2,3,3-trimethyl-butane and hexanal were identified as the characteristic volatiles for FD dried chips.

GC-TOF/MS-based metabolomic strategy for combined toxicity effects of deoxynivalenol and zearalenone on murine macrophage ANA-1 cells

The actual health risk from exposure to combined mycotoxins is unknown, and few studies have focused on changes to cellular biological systems (e.g., metabolomics) caused by combined mycotoxic effects. To evaluate the combined mycotoxic effects of deoxynivalenol (DON) and zearalenone (ZEN) on the level of cellular biological systems, gas chromatographic, time-of-flight mass spectroscopy (GC-TOF/MS) of the complete murine macrophage ANA-1 cell metabolome was implemented in this study. Using optimized chromatography and mass spectrometry parameters, the metabolites detected by GC-TOF/MS were identified and processed using multivariate statistical analysis, including principal component analysis (PCA) and orthogonal projection on latent-structures discriminant analysis (OPLS-DA). The metabolite sets were screened for further pathway analysis under rules of t-test (P) value < 0.05, VIP value > 1, and similarity value > 500. The mainly interfered metabolism pathways were categorized into two dominant types: amino acid metabolism and glycometabolism. Four metabolites, palmitic acid, 1-monopalmitin, ribose-5-phosphate and 2-deoxy-D-galactose, occur only under combined “DON + ZEN” treatment, indicating abnormal metabolism in ANA-1 cells. The metabolic state of ANA-1 cells under induction by combined “DON + ZEN” illustrates that DON may inhibit the estrogenic effects of ZEN. Thus, the combined effect of “DON + ZEN” may exacerbate toxicity in the pentose phosphate pathway, while palmitic acid metabolism is likely a new pathway effected by the combination, “DON + ZEN.”

Rats’ Metabolic Responses to Chronic Intervention with Cantonese Herbal Tea

Cantonese Herbal Tea (CHT) is consumed in south China to alleviate feelings of discomfort due to the over-heat and humidity in the body, but the related molecular mechanisms behind its effects remain obscure. The urinary metabolic responses to CHT over time in rats were investigated during a 38-day-period using GC-MS-based metabonomics. Integrated with student’s t-test and Orthogonal Projection on Latent Structures Discriminant Analysis (OPLS-DA) at each time point revealed that the process could be divided into two stages. In the first stage, the bioefficacy was characterized by elevated antioxidant activity and the depletion of oxidative stresses. However, the effect was reduced with time and replaced by a second stage characterized by the decreased flow of energy metabolism and an imbalance in gut microbiota. In conclusion, metabonomics study gained insight into the metabolic changes induced by CHT intake and the extent to which CHT intake influences the urinary metabolome, which also provides a powerful method for understanding the mechanism of CHT.

Metabolomic approach to profile functional and metabolic changes in heart failure.

BackgroundHeart failure (HF) is characterized by a series of adaptive changes in energy metabolism. The use of metabolomics enables the parallel assessment of a wide range of metabolites. In this study, we appraised whether metabolic changes correlate with HF severity, assessed as an impairment of functional contractility, and attempted to interpret the role of metabolic changes in determining systolic dysfunction.MethodsA 500 MHz proton nuclear magnetic resonance (1H-NMR)-based analysis was performed on blood samples from three groups of individuals: 9 control subjects (Group A), 9 HF patients with mild to moderate impairment of left ventricle ejection fraction (LVEF: 41.9 ± 4.0 %; Group B), and 15 HF patients with severe LVEF impairment (25.3 ± 10.3 %; Group C). In order to create a descriptive model of HF, a supervised orthogonal projection on latent structures discriminant analysis (OPLS-DA) was applied using speckle tracking-derived longitudinal strain rate as the Y-variable in the multivariate analysis.ResultsOPLS-DA identified three metabolic clusters related to the studied groups achieving good values for R2 [R2(X) = 0.64; R2(Y) = 0.59] and Q2 (0.39). The most important metabolites implicated in the clustering were 2-hydroxybutyrate, glycine, methylmalonate, and myo-inositol.ConclusionsThe results demonstrate the suitability of metabolomics in combination with functional evaluation techniques in HF staging. This innovative tool should facilitate investigation of perturbed metabolic pathways in HF and their correlation with the impairment of myocardial function.Electronic supplementary materialThe online version of this article (doi:10.1186/s12967-015-0661-3) contains supplementary material, which is available to authorized users.

P0725 : Lipidomics analysis of fasting serum identifies novel lipid biomarkers specific for HCV genotype 3 and genotype 1 chronic hepatitis C virus infection

Background and Aims: HCV genotype 3 (G3) is now considered the most difficult to treat genotype in the era of new oral direct acting antiviral (DAAs) drugs, particularly in those with advanced liver disease. HCV-G3 is also associated with more rapid progression to cirrhosis. Evidence suggests that HCV-G3 has different effects on lipid metabolism compared to HCV-G1, associated with hepatic steatosis, low LDL cholesterol and distinct interactions in the formation of lipoviral particles. A lipidomic analysis was performed to identify lipid species differentially regulated in HCV-G3 compared to HCV-G1, to gain further insight into genotype-specific metabolic pathways. Methods: Lipidomic analysis was performed on fasting sera [N = 112 (73 G1, 39 G3); 25% cirrhosis] using a UPLC system coupled to a QToF mass spectrometer. Profiles were acquired in positive and negative ion modes. System suitability and stability was confirmed by injection of a quality control (QC) sample at regular intervals throughout the analytical run, prepared by combining equal aliquots of all the study samples. Data was pre-processed (alignment, noise filtering, normalisation) using XCMS and inhouse developed scripts, and subjected to multivariate statistical analysis using Simca-P. Principal component analysis (PCA) and orthogonal projection on latent structures-discriminant analysis (OPLS-DA) were performed on all data after pareto scaling. Results: Spectra were explored by PCA for initial visualisation to detect inherent trends and outliers. Samples clustered based on the differences between the HCV-G1 and HCV-G3. Pairwise analysis using OPLS-DA allowed establishing the lipids with the strongest contribution to the genotype separation in positive ion mode. Preliminary assignment based on mass, fragmentation pattern and retention time of lipid species upregulated in HCV-G3 included Cholesteryl linoleate [M+NH4] 666.621 m/z @ 15.47 min. Other lipid species were specifically increased in HCV genotype 1 [M+H] 784.588 m/z @ 6.29 min PC (36:30). In negative ion mode, additional novel lipid species were found to be differentially unregulated in HCV-G1. The novel lipid species are currently being identified and evaluated in an independent validation cohort. Conclusions: UPLC MS lipidomics methods identify novel lipid species differentially regulated in HCV-G3 compared to HCV-G1. Understanding of the lipidome in HCV-G3 may help identify factors associated with DAA relapse.

Differential metabolic responses of Beauveria bassiana cultured in pupae extracts, root exudates and its interactions with insect and plant

Beauveria bassiana is a kind of world-wide entomopathogenic fungus and can also colonize plant rhizosphere. Previous researches showed differential expression of genes when entomopathogenic fungi are cultured in insect or plant materials. However, so far there is no report on metabolic alterations of B. bassiana in the environments of insect or plant. The purpose of this paper is to address this problem. Herein, we first provide the metabolomic analysis of B. bassiana cultured in insect pupae extracts (derived from Euproctis pseudoconspersa and Bombyx mori, EPP and BMP), plant root exudates (derived from asparagus and carrot, ARE and CRE), distilled water and minimal media (MM), respectively. Principal components analysis (PCA) shows that mycelia cultured in pupae extracts and root exudates are evidently separated and individually separated from MM, which indicates that fungus accommodates to insect and plant environments by different metabolic regulation mechanisms. Subsequently, orthogonal projection on latent structure–discriminant analysis (OPLS-DA) identifies differential metabolites in fungus under three environments relative to MM. Hierarchical clustering analysis (HCA) is performed to cluster compounds based on biochemical relationships, showing that sphingolipids are increased in BMP but are decreased in EPP. This observation further implies that sphingolipid metabolism may be involved in the adaptation of fungus to different hosts. In the meantime, sphingolipids are significantly decreased in root exudates but they are not decreased in distilled water, suggesting that some components of the root exudates can suppress sphingolipid to down-regulate sphingolipid metabolism. Pathway analysis finds that fatty acid metabolism is maintained at high level but non-ribosomal peptides (NRP) synthesis is unaffected in mycelia cultured in pupae extracts. In contrast, fatty acid metabolism is not changed but NRP synthesis is high in mycelia cultured in root exudates and distilled water. This indicates that fungal fatty acid metabolism is enhanced when contacting insect, but when in the absence of insect hosts NRP synthesis is increased. Ornithine, arginine and GABA are decreased in mycelia cultured in pupae extracts and root exudates but remain unchanged in distilled water, which suggests that they may be associated with fungal cross-talk with insects and plants. Trehalose and mannitol are decreased while adenine is increased in three conditions, signifying carbon shortage in cells. Together, these results unveil that B. bassiana has differential metabolic responses in pupae extracts and root exudates, and metabolic similarity in root exudates and distilled water is possibly due to the lack of insect components.

Addressing marketplace gilthead sea bream (Sparus aurata L.) differentiation by 1H NMR-based lipid fingerprinting

A complete NMR-based lipid fingerprinting protocol is described for the classification of farmed and wild adult gilthead sea breams having a commercial size (between 201.5±25.2g and 335.3±21.8g) and captured during the warm season (June–October). The presented approach is able to differentiate 68 fish sold in the Italian market between wild and farmed and reared fish in different off-shore sea cage farms in Sardinia (Italy) and imported from Greece. Sample selection, preparative protocol, NMR acquisition of lipid extracts and multivariate statistical analysis of experimental data carried out by means of principal component analysis (PCA) and orthogonal projection on latent structure-discriminant analysis (OPLS-DA), are thoroughly described. In addition, statistically meaningful confirmation of the observed clustering patterns was given by bootstrap statistical analysis. Bootstrap values associate the largest scores separation to the discrimination between Greek and Sardinian fish (100%), followed by the distinction between wild and farmed fish captured in Sardinia (90%). Finally, the less relevant but significant classification (68–57%) was achieved between sea breams reared in different Sardinian off-shore sea cage farms. Differential Metabograms show that polyunsaturated fatty acids, and in particular n−3 fatty acids, differentiate farmed fish from wild counterparts.

Advantage of LC-MS metabolomics to identify marker compounds in two types of Chinese dark tea after different post-fermentation processes

Chinese dark tea (CDT) was investigated for chemical characteristics using liquid chromatography coupled with tandem mass spectrometry (LC-MS) metabolomics analysis. The LC-MSn method was used for detection of secondary metabolites in 10 CDT varieties. Pattern recognition methods, including principal component analysis (PCA) and orthogonal projection on latent structure-discriminant analysis (OPLS-DA), revealed clear differences and classified the CDT varieties into 2 categories. One category is fermented with Aspergillus niger while the other (fu teas) is fermented with Eurotium cristatum. Chemical analyses identified 25 marker compounds that contribute to the classification of the 2 CDT types. Flavonoid triglycosides and catechin derivatives were the distinctive compounds of fu teas, based on MS/MS fragmentation analysis. Although both fu teas and dark teas are commonly called CDTs, differences between these two CDT types are significant in the chemical classification.

Application of metabolomics on diagnosis and treatment of patients with psoriasis in traditional Chinese medicine

Traditional Chinese medicine (TCM) is one of the oldest forms of medical system. With syndrome as the core of diagnosis and therapy in TCM, it has the advantage of collecting macroscopic information of patients for diagnosis. To understand the in vivo mechanism of TCM, a metabolomics approach was used to investigate the global biological characterization of the urine of psoriasis patients with Blood Stasis Syndrome and the therapeutic metabolomics mechanism of the Optimized Yinxieling formula. A total of 41 cases of psoriasis patients with Blood Stasis Syndrome and 19 healthy volunteers were enrolled in this study. Fasting urine samples from patients with consecutive Optimized Yinxieling intake after 0, 4, 8 and 12weeks and from healthy volunteers were analyzed by Orthogonal Projection on Latent Structures Discriminant Analysis (OPLS-DA), which was utilized for High Performance Liquid Chromatography (HPLC) analysis and temporal metabolic changes identification. For psoriasis group, the scores of PASI of patients decreased after 12weeks of Optimized Yinxieling treating. The metabolic variations visualized not only in the healthy group and psoriasis group, but also in the psoriasis group before and after Optimized Yinxieling treatment, demonstrated that the metabolic characteristics of the two groups were significantly different. The optimized complex structure of the target proteins from Protein Data Bank was analyzed by software package Discovery Studio. With docking score of original inhibitor and the receptor as the threshold values, two compounds from Chinese medicinal chemical database were predicted to have good interactions with the target proteins. The Metabolomics technique combining molecular docking analysis enhanced our current understanding of the metabolic response to Blood Stasis Syndrome of Psoriasis and the action mechanism of Optimized Yinxieling. This article is part of a Special Issue entitled: Computational Proteomics, Systems Biology & Clinical Implications. Guest Editor: Yudong Cai.

Lipidomic profiling reveals lipid regulation in the snow alga Chlamydomonas nivalis in response to nitrate or phosphate deprivation

The snow alga Chlamydomonas nivalis in the exponential phase was subjected to nitrate or phosphate deprivation for 0–72h to study its stress responses in lipid profiles analyzed by UPLC/Q-TOF-MS (ultra performance liquid chromatography/quadrupole-time of flight-mass spectrometry). Three clusters were distinguished as the control, nitrate-deprived and phosphate-deprived groups in OPLS-DA (orthogonal projection on latent structure discriminant analysis) score plots based on their lipidome data. Altogether, the lipidomic approach identified twenty-two ions in nitrate-deprived group including nine l, 2-diacylglyceryl-3-O-4′-(N, N, N-trimethyl)-homoserine (DGTSs), one phosphatidylethanolamine (PE), two monogalactosyldiacylglycerols (MGDGs), four digalactosyldiacylglycerols (DGDGs), three phosphatidylglycerols (PGs), two sulfoquinovosyl-diacylglycerols (SQDGs) and one phosphatidylinositiol (PI), and nineteen ions in phosphate-deprived group including four DGTSs, one PE, one MGDG, seven DGDGs, three PGs, two SQDGs and one PG as “differentiating lipid biomarkers”. Moreover, the common and specific biomarkers were found in the two nutrient deprived groups by SUS (shared and unique structure) plot. Biomarkers-based z-score plot and heat map further showed how lipid biomarker expressions deviate from the control. The up- or down-regulation of these lipid biomarkers provided new insights into the lipid metabolism of the snow alga in response to nitrate or phosphate deprivation stress condition.

Fatty Acids Profiling and Biomarker Identification in Snow Alga Chlamydomonas Nivalis by NaCl Stress Using GC/MS and Multivariate Statistical Analysis

The snow alga Chlamydomonas nivalis is a model species of microalgae for the investigation of cell response mechanism and adaptation ability in natural habitats in polar regions and similar extreme environments. The alteration of fatty acids in cellular lipids is known to play a vital role for cell survival and reproduction under various stress conditions. In the present work, an integrated approach of gas chromatography/mass spectrometry (GC/MS) coupled with multivariate statistical analysis was developed to investigate the fatty acid profiles and identify the biomarkers in response to NaCl stress. The data of fatty acid profiles between the control and NaCl-stress group was classified by orthogonal projection on latent structure discriminant analysis (OPLS-DA) and hierarchical cluster analysis (HCA); six of fatty acids (C16:0, C16:3, C18:0, C18:1, C18:2, and C18:3) were identified as biomarkers. These biomarkers showed a regulatory role by decreasing the degree of lipid unsaturation (DLU), providing an expected function in reducing membrane fluidity and permeability for enhancing the tolerance to higher salinity. This is the first report to demonstrate the fatty acid biomarkers in microalgae as the physiological regulators corresponding to the response and adaptation to NaCl stress based on an integrated approach at the lipidomic level.

Metabonomic Investigation on Rats’ Dynamic Responses to Cantonese Herbal Tea Intake

GC-MS-based metabonomics was applied to investigate the urinary metabolic response to Cantonese Herbal tea (CHT) intake during a 38-day-period. Orthogonal projection on latent structures discriminant analysis (OPLS-DA) with student’s t-test revealed that the global characterization of metabolic changes at each sampling time point were different. Dynamic sampling made it possible to evaluate dynamic metabolic responses to CHT intake.

Characterization of Temporary Metabolic Changes Following Cantonese Herbal Tea Intervention

Cantonese herbal tea (CHT) has been consumed in South China to alleviate feelings of discomfort due to the heat and humidity in the body according to the theory of traditional Chinese medicine (TCM). To understand the in vivo mechanism of CHT, a ¹H-NMR-based metabonomic approach was used to investigate the global biological characterization of rat serum following the intake of CHT and to understand the mechanisms of action of CHT. Serum samples from rats with consecutive CHT intake after 10, 20 and 30 days and corresponding control rats were analysed by high-resolution ¹H-NMR spectroscopy. Principal component analysis (PCA) and orthogonal projection on latent structures discriminant analysis (OPLS-DA) were utilized for ¹H-NMR spectra analysis and temporal metabolic changes identification. For the 10-day CHT intake group, no significant metabolic response was detected, whereas the 20-day group showed elevation of glucogeneogenesis and a shift in energy metabolism from carbohydrate metabolism to lipid metabolism. In addition, a notable decrease in pyruvate content with a consistent increase in lactate content, and significant decrease in both lipoprotein and glucose contents was observed for the 30-day group, indicating potential metabolic dysfunction. The metabonomics technique combining metabolic profiles with multivariate analysis enhanced our current understanding of the host's metabolic response to CHT intake.

Metabolic Dependence of Green Tea on Plucking Positions Revisited: A Metabolomic Study

The dependence of global green tea metabolome on plucking positions was investigated through (1)H nuclear magnetic resonance (NMR) analysis coupled with multivariate statistical data set. Pattern recognition methods, such as principal component analysis (PCA) and orthogonal projection on latent structure-discriminant analysis (OPLS-DA), were employed for a finding metabolic discrimination among fresh green tea leaves plucked at different positions from young to old leaves. In addition to clear metabolic discrimination among green tea leaves, elevations in theanine, caffeine, and gallic acid levels but reductions in catechins, such as epicatechin (EC), epigallocatechin (EGC), epicatechin-3-gallate (ECG), and epigallocatechin-3-gallate (EGCG), glucose, and sucrose levels were observed, as the green tea plant grows up. On the other hand, the younger the green tea leaf is, the more theanine, caffeine, and gallic acid but the lesser catechins accumlated in the green tea leaf, revealing a reverse assocation between theanine and catechins levels due to incorporaton of theanine into catechins with growing up green tea plant. Moreover, as compared to the tea leaf, the observation of marked high levels of theanine and low levels of catechins in green tea stems exhibited a distinct tea plant metabolism between the tea leaf and the stem. This metabolomic approach highlights taking insight to global metabolic dependence of green tea leaf on plucking position, thereby providing distinct information on green tea production with specific tea quality.

Geographical and Climatic Dependencies of Green Tea (Camellia sinensis) Metabolites: A 1H NMR-Based Metabolomics Study

The effects of climatic conditions on green tea metabolites in three different growing areas of Jeju Island, South Korea, were investigated through global metabolite profiling by (1)H nuclear magnetic resonance (NMR) spectroscopy. Pattern recognition methods, such as principal component analysis (PCA) and orthogonal projection on latent structure-discriminant analysis (OPLS-DA), revealed clear discriminations of green teas from the three different growing areas. Variations of theanine, isoleucine, leucine, valine, alanine, threonine, glutamine, quinic acid, glucose, epicatechin (EC), epigallocatechin (EGC), epigallocatechin-3-gallate (EGCG), and caffeine levels were responsible for the discriminations. Green teas grown in an area with high temperature, long sun exposure time, and high rainfall had higher levels of theanine but lower levels of isoleucine, leucine, valine, alanine, EC, EGC, EGCG, and caffeine than those grown in areas with relatively low temperature, short sun exposure time, and low rainfall. These results indicate that high temperature, long sun exposure, and high preciptation stimulate theanine synthesis in green tea during the spring season. This study highlights how metabolomics coupled with multivariate statistical analysis can illuminate the metabolic characteristics of green tea associated with climatic variables, thereby allowing for the assessment of quality strategy in green tea production.