Gas Chromatography Time-of-flight Mass Spectrometry Research Articles

Identification of differential metabolites in liquid diet fermented with Bacillus subtilis using gas chromatography time of flight mass spectrometry.

Growth and health responses of pigs fed fermented liquid diet are not always consistent and causes for this issue are still not very clear. Metabolites produced at different fermentation time points should be one of the most important contributors. However, currently no literatures about differential metabolites of fermented liquid diet are reported. The aim of this experiment was to explore the difference of metabolites in a fermented liquid diet between different fermentation time intervals. A total of eighteen samples that collected from Bacillus subtilis fermented liquid diet on days 7, 21 and 35 respectively were used for the identification of metabolites by gas chromatography time of flight mass spectrometry (GC-TOF-MS). Fifteen differential metabolites including melibiose, sortitol, ribose, cellobiose, maltotriose, sorbose, isomaltose, maltose, fructose, d-glycerol-1-phosphate, 4-aminobutyric acid, beta-alanine, tyrosine, pyruvic acid and pantothenic acid were identified between 7-d samples and 21-d samples. The relative level of melibiose, ribose, maltotriose, d-glycerol-1-phosphate, tyrosine and pyruvic acid in samples collected on day 21 was significantly higher than that in samples collected on day 7 (P < 0.01), respectively. Eight differential metabolites including ribose, sorbose, galactinol, cellobiose, pyruvic acid, galactonic acid, pantothenic acid and guanosine were found between 21-d samples and 35-d samples. Samples collected on day 35 had a higher relative level of ribose than that in samples collected on day 21 (P < 0.01). In conclusion, many differential metabolites which have important effects on the growth and health of pigs are identified and findings contribute to explain the difference in feeding response of fermented liquid diet.

Metabolomic Quality Assessment of EDTA Plasma and Serum Samples.

Handling and processing of blood can significantly alter the molecular composition and consistency of biobank samples and can have a major impact on the identification of biomarkers. It is thus crucial to identify tools to determine the quality of samples to be used in biomarker discovery studies. In this study, a non-targeted gas chromatography/time-of-flight mass spectrometry (GC-TOFMS) metabolomic strategy was used with the aim of identifying quality markers for serum and plasma biobank collections lacking proper documentation of preanalytical handling. The effect of postcentrifugation delay was examined in serum stored in tubes with gel separation plugs and ethylenediaminetetraacetic acid (EDTA) plasma in tubes with or without gel separation plugs. The change in metabolic pattern was negligible in all sample types processed within 3 hours after centrifugation regardless of whether the samples were kept at 4°C or 22°C. After 8 and 24 hours postcentrifugation delay before aliquoting, there was a pronounced increase in the number of affected metabolites, as well as in the magnitude of the observed changes. No protective effect on the metabolites was observed in gel-separated EDTA plasma samples. In a separate series of experiments, lactate and glucose levels were determined in plasma to estimate the effect of precentrifugation delay. This separate experiment indicates that the lactate to glucose ratio may serve as a marker to identify samples with delayed time to centrifugation. Although our data from the untargeted GC-TOFMS analysis did not identify any specific markers, we conclude that plasma and serum metabolic profiles remain quite stable when plasma and serum are centrifuged and separated from the blood cells within 3 hours.

Metabolite fingerprinting, pathway analyses, and bioactivity correlations for plant species belonging to the Cornaceae, Fabaceae, and Rosaceae families.

A multi-parallel approach gauging the mass spectrometry-based metabolite fingerprinting coupled with bioactivity and pathway evaluations could serve as an efficacious tool for inferring plant taxonomic orders. Thirty-four species from three plant families, namely Cornaceae (7), Fabaceae (9), and Rosaceae (18) were subjected to metabolite profiling using gas chromatography-time-of-flight-mass spectrometry (GC-TOF-MS) and ultrahigh performance liquid chromatography-linear trap quadrupole-ion trap-mass spectrometry (UHPLC-LTQ-IT-MS/MS), followed by multivariate analyses to determine the metabolites characteristic of these families. The partial least squares discriminant analysis (PLS-DA) revealed the distinct clustering pattern of metabolites for each family. The pathway analysis further highlighted the relatively higher proportions of flavonols and ellagitannins in the Cornaceae family than in the other two families. Higher levels of phenolic acids and flavan-3-ols were observed among species from the Rosaceae family, while amino acids, flavones, and isoflavones were more abundant among the Fabaceae family members. The antioxidant activities of plant extracts were measured using ABTS, DPPH, and FRAP assays, and indicated that extracts from the Rosaceae family had the highest activity, followed by those from Cornaceae and Fabaceae. The correlation map analysis positively links the proportional concentration of metabolites with their relative antioxidant activities, particularly in Cornaceae and Rosaceae. This work highlights the pre-eminence of the multi-parallel approach involving metabolite profiling and bioactivity evaluations coupled with metabolic pathways as an efficient methodology for the evaluation of plant phylogenies.

Ultrahigh Pressure Processing Produces Alterations in the Metabolite Profiles of Panax ginseng.

Ultrahigh pressure (UHP) treatments are non-thermal processing methods that have customarily been employed to enhance the quality and productivity of plant consumables. We aimed to evaluate the effects of UHP treatments on ginseng samples (white ginseng: WG; UHP-treated WG: UWG; red ginseng: RG; UHP-treated RG: URG; ginseng berries: GB; and UHP-treated GB: UGB) using metabolite profiling based on ultrahigh performance liquid chromatography-linear trap quadrupole-ion trap-tandem mass spectrometry (UHPLC-LTQ-IT-MS/MS) and gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). Multivariate data analyses revealed a clear demarcation among the GB and UGB samples, and the phenotypic evaluations correlated the highest antioxidant activities and the total phenolic and flavonoid compositions with the UGB samples. Overall, eight amino acids, seven organic acids, seven sugars and sugar derivatives, two fatty acids, three notoginsenosides, three malonylginsenosides, and three ginsenosides, were identified as significantly discriminant metabolites between the GB and UGB samples, with relatively higher proportions in the latter. Ideally, these metabolites can be used as quality biomarkers for the assessment of ginseng products and our results indicate that UHP treatment likely led to an elevation in the proportions of total extractable metabolites in ginseng samples.

Effect of total saponins of Clematidis Radix et Rhizoma on serum metabolic profile in adjuvant arthritis rats based on GC-TOF-MS

To observe the effect of total saponins of Clematidis Radix et Rhizoma (TSCR) on serum metabolic profile changes in adjuvant arthritis(AA) rats, and explore its possible action mechanism for AA rats. The AA rat models were induced by Freund's complete adjuvant(FCA), and their histopathological changes were observed. Gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS), principal component analysis(PCA) and partial least squares-discriminant analysis (PLS-DA) were employed to analyze the metabolic profile among normal group, AA model group and TSCR group. Potential biomarkers in the serum were screened based on the variable importance projection(VIP) value>1, P<0.05. As compared with the normal group, 17 potential biomarkers such as aspartic acid, inositol and phenylacetaldehyde were found and identified in the serum of model group rats. As compared with the model group, the above biomarkers were regulated nearly to a normal state after TSCR administration for 16 days. Metabolomic analysis revealed that the total saponins of Clematidis Radix et Rhizoma has a certain therapeutic effect for AA rats, and the mechanism may be related to regulation of lipid metabolism, amino acid metabolism and energy metabolism.

Metabolomic Profiles of Aspergillus oryzae and Bacillus amyloliquefaciens During Rice Koji Fermentation.

Rice koji, used early in the manufacturing process for many fermented foods, produces diverse metabolites and enzymes during fermentation. Using gas chromatography time-of-flight mass spectrometry (GC-TOF-MS), ultrahigh-performance liquid chromatography linear trap quadrupole ion trap tandem mass spectrometry (UHPLC-LTQ-IT-MS/MS), and multivariate analysis we generated the metabolite profiles of rice koji produced by fermentation with Aspergillus oryzae (RK_AO) or Bacillus amyloliquefaciens (RK_BA) for different durations. Two principal components of the metabolomic data distinguished the rice koji samples according to their fermenter species and fermentation time. Several enzymes secreted by the fermenter species, including α-amylase, protease, and β-glucosidase, were assayed to identify differences in expression levels. This approach revealed that carbohydrate metabolism, serine-derived amino acids, and fatty acids were associated with rice koji fermentation by A. oryzae, whereas aromatic and branched chain amino acids, flavonoids, and lysophospholipids were more typical in rice koji fermentation by B. amyloliquefaciens. Antioxidant activity was significantly higher for RK_BA than for RK_AO, as were the abundances of flavonoids, including tricin, tricin glycosides, apigenin glycosides, and chrysoeriol glycosides. In summary, we have used MS-based metabolomics and enzyme activity assays to evaluate the effects of using different microbial species and fermentation times on the nutritional profile of rice koji.

Global Metabolic Regulation of the Snow Alga Chlamydomonas nivalis in Response to Nitrate or Phosphate Deprivation by a Metabolome Profile Analysis.

In the present work, Chlamydomonas nivalis, a model species of snow algae, was used to illustrate the metabolic regulation mechanism of microalgae under nutrient deprivation stress. The seed culture was inoculated into the medium without nitrate or phosphate to reveal the cell responses by a metabolome profile analysis using gas chromatography time-of-flight mass spectrometry (GC/TOF-MS). One hundred and seventy-one of the identified metabolites clustered into five groups by the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Among them, thirty of the metabolites in the nitrate-deprived group and thirty-nine of the metabolites in the phosphate-deprived group were selected and identified as “responding biomarkers” by this metabolomic approach. A significant change in the abundance of biomarkers indicated that the enhanced biosynthesis of carbohydrates and fatty acids coupled with the decreased biosynthesis of amino acids, N-compounds and organic acids in all the stress groups. The up- or down-regulation of these biomarkers in the metabolic network provides new insights into the global metabolic regulation and internal relationships within amino acid and fatty acid synthesis, glycolysis, the tricarboxylic acid cycle (TCA) and the Calvin cycle in the snow alga under nitrate or phosphate deprivation stress.

GC/TOF-MS-based metabolomic profiling in cultured fibroblast-like synoviocytes from rheumatoid arthritis

ObjectivesRheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by synovial inflammation and hyperplasia. Fibroblast-like synoviocytes (FLS) in RA exhibit a tumor cell-like aggressive phenotype. Thus, gas chromatography/time-of-flight-mass spectrometry (GC/TOF-MS) was employed to identify the characteristic metabolic profiling of RA FLS. MethodsMetabolite profiling of RA FLS and osteoarthritis (OA) FLS was performed using GC/TOF-MS in conjunction with statistical analyses. We performed metabolite set enrichment analysis to establish which pathways are affected. ResultsA total of 129 metabolites were identified. A principal component analysis and hierarchical clustering analysis demonstrated clear differentiation of the metabolic profiling between RA FLS and OA FLS. The levels of 35 metabolites that belonged to the amines, fatty acids, phosphates, and organic acids class were significantly increased in RA FLS compared to those in OA FLS. Also, the levels of 26 metabolites that belonged to the amino acids, sugars, and sugar alcohols class were significantly decreased in RA FLS compared to those in OA FLS. The sugar metabolism (glycolysis and pentose phosphate pathway) and amino acid metabolism (tyrosine and catecholamine biosynthesis, and protein biosynthesis) were severely disturbed in RA FLS compared to those in OA FLS. ConclusionsOur metabolic results suggested that the alteration of sugar metabolism, lipolysis, and amino acid metabolism in RA FLS is related to synovial hyperplasia and inflammation. This is the first metabolomic study to determine metabolic changes characteristic of RA FLS, which will provide valuable information to gain in-depth insights into the pathogenesis of RA.

Chemical Profiling and Antioxidant Activity of Thai Basil (Ocimum basilicum)

The chemical constituents and antioxidant activity of the crude extracts of Thai basil (Ocimum basilicum) were investigated. Phytochemical analysis indicated the presence of flavonoids, anthraquinones and tannins in the crude extracts of Ocimum basilicum. GC-TOFMS (Gas Chromatography Time-of-Flight Mass Spectrometry) analysis indicated the presence of sequiterpenoids, diterpene alcohol, fatty methyl esters (linoleic acid, gamma linoleic acid, arachidonic acid). Total phenolic components of the crude extracts was found to be 45.38 ± 0.66 mg gallic acid equivalents/g which was determined by Folinciocalteu method. The DPPH (2,2diphenyl-1-1-picrylhydrazyl radical) radical scavenging activity was found to increase with increasing concentrations, it was found to be 73.75% with IC50 values of 22 μg/ml. The highest antioxidant activity may be due to the presence of flavonoids which has the scavenging potential by reducing the free radicals. Fatty acid methyl esters are proven to possess antimicrobial, antioxidant and anti-tumor activity and they ere polymers with low molecular weight and highly hydrophilic which may be the factor which enhances cytotoxicity and scavenging potential.

Environmental Metabolomics of the Tomato Plant Surface Provides Insights on Salmonella enterica Colonization.

Foodborne illness-causing enteric bacteria are able to colonize plant surfaces without causing infection. We lack an understanding of how epiphytic persistence of enteric bacteria occurs on plants, possibly as an adaptive transit strategy to maximize chances of reentering herbivorous hosts. We used tomato (Solanum lycopersicum) cultivars that have exhibited differential susceptibilities to Salmonella enterica colonization to investigate the influence of plant surface compounds and exudates on enteric bacterial populations. Tomato fruit, shoot, and root exudates collected at different developmental stages supported growth of S. enterica to various degrees in a cultivar- and plant organ-dependent manner. S. enterica growth in fruit exudates of various cultivars correlated with epiphytic growth data (R(2) = 0.504; P = 0.006), providing evidence that plant surface compounds drive bacterial colonization success. Chemical profiling of tomato surface compounds with gas chromatography-time of flight mass spectrometry (GC-TOF-MS) provided valuable information about the metabolic environment on fruit, shoot, and root surfaces. Hierarchical cluster analysis of the data revealed quantitative differences in phytocompounds among cultivars and changes over a developmental course and by plant organ (P < 0.002). Sugars, sugar alcohols, and organic acids were associated with increased S. enterica growth, while fatty acids, including palmitic and oleic acids, were negatively correlated. We demonstrate that the plant surface metabolite landscape has a significant impact on S. enterica growth and colonization efficiency. This environmental metabolomics approach provides an avenue to understand interactions between human pathogens and plants that could lead to strategies to identify or breed crop cultivars for microbiologically safer produce. In recent years, fresh produce has emerged as a leading food vehicle for enteric pathogens. Salmonella-contaminated tomatoes represent a recurrent human pathogen-plant commodity pair. We demonstrate that Salmonella can utilize tomato surface compounds and exudates for growth. Surface metabolite profiling revealed that the types and amounts of compounds released to the plant surface differ by cultivar, plant developmental stage, and plant organ. Differences in exudate profiles explain some of the variability in Salmonella colonization susceptibility seen among tomato cultivars. Certain medium- and long-chain fatty acids were associated with restricted Salmonella growth, while sugars, sugar alcohols, and organic acids correlated with larger Salmonella populations. These findings uncover the possibility of selecting crop varieties based on characteristics that impair foodborne pathogen growth for enhanced safety of fresh produce.

Identification of three cannabimimetic indazole and pyrazole derivatives, APINACA 2H-indazole analogue, AMPPPCA, and 5F-AMPPPCA.

This paper reports analytical properties of three cannabimimetic indazole and pyrazole derivatives seized from a clandestine laboratory. These three new synthetic cannabinoids include N-(1-adamantyl)-2-pentyl-2H-indazole-3-carboxamide (APINACA 2H-indazole analogue, 1), N-(1-adamantyl)-4-methyl-1-pentyl-5-phenyl-1H-pyrazole-3-carboxamide (AMPPPCA, 2), and N-(1-adamantyl)-1-(5-fluoropentyl)-4-methyl-5-phenyl-1H-pyrazole-3-carboxamide (5F-AMPPPCA, 3). These compounds were identified by liquid chromatography-quadrupole time-of-flight-mass spectrometry (LC-QTOF-MS), gas chromatography-time-of-flight-mass spectrometry (GC-TOF-MS), and nuclear magnetic resonance (NMR) spectroscopy. No analytical properties and pharmacological activities about compounds 1-3 have appeared until now, making this the first report on these compounds. Copyright © 2016 John Wiley & Sons, Ltd.

Urinary metabolite profiling provides potential differentiation to explore the mechanisms of adjuvant-induced arthritis in rats.

To explore the pathogenesis of rheumatoid arthritis (RA) from the perspective of metabolomics, gas chromatography time-of-flight mass spectrometry (GC-TOF/MS) technology was used to observe changes in the metabolic profiles of urine output from rats with adjuvant-induced arthritis (AA). Sprague-Dawley rats were randomly divided into a control group and an experimental group, with eight in each. Rats in the experimental group were induced by intracutaneous innoculation of 0.1 mL Freund's complete adjuvant to right paws. On day 20 after immunization, the metabolic profiles between rat control and experimental groups were compared by combining GC-TOF/MS technology with multivariate statistical approaches, including principal component analysis, partial least squares discriminant analysis and orthogonal projections to latent structures-discriminant analysis. Nine potential biomarkers were identified, including 2,2-dimethylsuccinic acid, tartronic acid, dehydroshikimic acid, hippuric acid, adenine, phenaceturic acid, l-dopa, 1,4-dihydroxy-2-naphthoic acid and melibiose. The findings indicate that the rats with AA are disturbed in metabolism of purine, amino acid, fat and energy. This study also demonstrates that the dysfunction in a range of biosynthetic and catabolic pathways, which leads to increased oxygen free radicals and inflammation, could cause underlying pathogenesis of RA. Copyright © 2016 John Wiley & Sons, Ltd.

Identification of hydroxy- and keto-dicarboxylic acids in remote marine aerosols using gas chromatography/quadruple and time-of-flight mass spectrometry.

The identification of hydroxy- and keto-dicarboxylic acids (diacids) in remote marine aerosol samples is important for a better understanding of the composition of organic particulate matter, as this chemical composition is essential for predicting the effects on climate, air quality, and human health. Molecular characterization of these compounds provides insights into sources and formation pathways of organic aerosols. The method of chemical derivatization followed by gas chromatography-flame ionization detection (GC-FID), gas chromatography/quadruple mass spectrometry (GC/QMS) and gas chromatography/time-of-flight mass spectrometry (GC/TOFMS) was used to identify hydroxy- and keto-diacids in remote marine aerosols. Atmospheric samples were collected at Chichijima Island in the western North Pacific and the diacids and related compounds were extracted with organic-free ultrapure water. A two-step derivatization technique was employed, using 14% BF3 /n-butanol for the butylation of carboxyl groups and acidic ketones followed by N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA) for the trimethylsilylation of hydroxyl groups. Several new peaks were detected in the gas chromatogram after trimethylsilylation of the dibutyl ester fraction. Based on mass spectral interpretation with authentic standards, we successfully identified and quantified a homologous series of hydroxydiacids, including tartaric and oxaloacetic acids. In addition, transformation of oxaloacetic acid into its enol form was elucidated. Utilizing GC-FID, GC/QMS and GC/TOFMS, hydroxy- and keto-diacids were identified in the remote marine aerosols. A complete structural characterization was achieved with extensive mass spectral analysis. Molecular distributions of hydroxydiacids generally showed the predominance of malic acid followed by tartronic acid. We consider that these hydroxydiacids are important intermediates in the atmospheric oxidation of organic aerosols to result in smaller diacids. Copyright © 2016 John Wiley & Sons, Ltd.

Metabolomics of papillary thyroid carcinoma tissues: potential biomarkers for diagnosis and promising targets for therapy.

Papillary thyroid carcinoma (PTC) is the most common pathological type of thyroid cancer. Our study was to construct a tissue-targeted metabolomics analysis method based on untargeted and targeted metabolic multi-platforms to identify a comprehensive PTC metabolic network in clinical samples. We applied untargeted gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS) for preliminary screening of potential biomarkers. With diagnostic models constructed using principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA), 45 differentially abundant metabolites with a variable importance in the projection (VIP) value greater than 1 and a P value less than 0.05 were identified, and we show that our approach was able to discriminate PTC tissues from healthy tissues. We then performed validation experiments based on targeted GC-TOF-MS combined with ultra-high-performance liquid chromatography-triple-quadrupole mass spectrometry (UHPLC-QqQ-MS) through constructing linear standard curves of analytes. Ultimately, galactinol, melibiose, and melatonin were validated as significantly altered metabolites (p < 0.05). These three metabolites were defined as a combinatorial biomarker to assist needle biopsy for PTC diagnosis as demonstrated by receiver operating characteristic (ROC) curve analysis, which revealed an area under the ROC curve (AUC) value of 0.96. Based on the metabolite enrichment analysis results, the galactose metabolism pathway was regarded as an important factor influencing PTC development by affecting energy metabolism. Alpha-galactosidase (GLA) was considered to be a potential target for PTC therapy.

Isotopic Ratio Outlier Analysis of the S. cerevisiae Metabolome Using Accurate Mass Gas Chromatography/Time-of-Flight Mass Spectrometry: A New Method for Discovery.

Isotopic ratio outlier analysis (IROA) is a (13)C metabolomics profiling method that eliminates sample to sample variance, discriminates against noise and artifacts, and improves identification of compounds, previously done with accurate mass liquid chromatography/mass spectrometry (LC/MS). This is the first report using IROA technology in combination with accurate mass gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS), here used to examine the S. cerevisiae metabolome. S. cerevisiae was grown in YNB media, containing randomized 95% (13)C, or 5%(13)C glucose as the single carbon source, in order that the isotopomer pattern of all metabolites would mirror the labeled glucose. When these IROA experiments are combined, the abundance of the heavy isotopologues in the 5%(13)C extracts, or light isotopologues in the 95%(13)C extracts, follows the binomial distribution, showing mirrored peak pairs for the molecular ion. The mass difference between the (12)C monoisotopic and the (13)C monoisotopic equals the number of carbons in the molecules. The IROA-GC/MS protocol developed, using both chemical and electron ionization, extends the information acquired from the isotopic peak patterns for formulas generation. The process that can be formulated as an algorithm, in which the number of carbons, as well as the number of methoximations and silylations are used as search constraints. In electron impact (EI/IROA) spectra, the artifactual peaks are identified and easily removed, which has the potential to generate "clean" EI libraries. The combination of chemical ionization (CI) IROA and EI/IROA affords a metabolite identification procedure that enables the identification of coeluting metabolites, and allowed us to characterize 126 metabolites in the current study.

Global Urine Metabolomics in Patients Treated with First-Line Tuberculosis Drugs and Identification of a Novel Metabolite of Ethambutol.

Population level variation of drug metabolism phenotype (DMP) has great implications in treatment outcome, drug-related side effects, and resistance development. In this study, we used a gas chromatography-time of flight-mass spectrometry (GC-TOF-MS)-based untargeted urine metabolomics approach to understand the DMP of a tuberculosis (TB) patient cohort (n= 20) from Tripura, a state in the northeastern part of India. Urine samples collected at different postdose time points (2 h, 6 h, 12 h, 24 h, 36 h, and 48 h) from these newly diagnosed TB patients receiving first-line anti-TB drugs were analyzed, and we have successfully detected three of the four first-line drugs,viz, isoniazid (INH), ethambutol (ETB), and pyrazinamide (PZA). The majority of their known metabolites, acetyl-isoniazid (AcINH), isonicotinic acid (INA), isonicotinuric acid (INTA), 2,2'-(ethylenediimino)-dibutyric acid (EDBA), 5-hydroxypyrazinamide (5OH-PZA), pyrazinoic acid (POA), and 5-hydroxypyrazinoic acid (5OH-POA), were also detected. Analyzing the variation in abundances of drugs and their known metabolites and calculating the metabolic ratios in these samples, we offer comprehensive DMP information on this small patient cohort that represents Tripura, India. The majority (75%) of these patients are found to be slow acetylators of INH. The average metabolic ratios of POA/PZA and 5OH-POA/POA are 3.16 ± 3.03 and 6.09 ± 6.15, respectively. Employing correlation analysis of the metabolomics metadata and a manual prediction of drug catabolism, we have proposed 2-aminobutyric acid (AABA) as a novel metabolite of ETB. These observations indicate the usefulness of GC-MS-based metabolomics to characterize the DMP at a population level and also to identify novel drug metabolites.

Metabolic Profiling and Antioxidant Assay of Metabolites from Three Radish Cultivars (Raphanus sativus).

A total of 13 anthocyanins and 33 metabolites; including organic acids, phenolic acids, amino acids, organic compounds, sugar acids, sugar alcohols, and sugars, were profiled in three radish cultivars by using high-performance liquid chromatography (HPLC) and gas chromatography time-of-flight mass spectrometry (GC-TOFMS)-based metabolite profiling. Total phenolics and flavonoids and their in vitro antioxidant activities were assessed. Pelargonidins were found to be the major anthocyanin in the cultivars studied. The cultivar Man Tang Hong showed the highest level of anthocyanins (1.89 ± 0.07 mg/g), phenolics (0.0664 ± 0.0033 mg/g) and flavonoids (0.0096 ± 0.0004 mg/g). Here; the variation of secondary metabolites in the radishes is described, as well as their association with primary metabolites. The low-molecular-weight hydrophilic metabolite profiles were subjected to principal component analysis (PCA), hierarchical clustering analysis (HCA), Pearson’s correlation analysis. PCA fully distinguished the three radish cultivars tested. The polar metabolites were strongly correlated between metabolites that participate in the TCA cycle. The chemometrics results revealed that TCA cycle intermediates and free phenolic acids as well as anthocyanins were higher in the cultivar Man Tang Hong than in the others. Furthermore; superoxide radical scavenging activities and 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging were investigated to elucidate the antioxidant activity of secondary metabolites in the cultivars. Man Tang Hong showed the highest superoxide radical scavenging activity (68.87%) at 1000 μg/mL, and DPPH activity (20.78%), followed by Seo Ho and then Hong Feng No. 1. The results demonstrate that GC-TOFMS-based metabolite profiling, integrated with chemometrics, is an applicable method for distinguishing phenotypic variation and determining biochemical reactions connecting primary and secondary metabolism. Therefore; this study might provide information on the relationship between primary and secondary metabolites and a synergistic antioxidant ability derived from the secondary metabolites in the radish cultivars.

Metabolite Profiling Reveals the Effect of Dietary Rubus coreanus Vinegar on Ovariectomy-Induced Osteoporosis in a Rat Model.

The study was aimed at exploring the curative effects of Rubus coreanus (RC) vinegar against postmenopausal osteoporosis by using ovariectomized rats as a model. The investigations were performed in five groups: sham, ovariectomized (OVX) rats without treatment, low-dose RC vinegar (LRV)-treated OVX rats, high-dose RC vinegar (HRV)-treated OVX rats and alendronate (ALEN)-treated OVX rats. The efficacy of RC vinegar was evaluated using physical, biochemical, histological and metabolomic parameters. Compared to the OVX rats, the LRV and HRV groups showed positive effects on the aforementioned parameters, indicating estrogen regulation. Plasma metabolome analysis of the groups using gas chromatography-time of flight mass spectrometry (GC-TOF-MS) and ultra-performance liquid chromatography quadrupole-TOF-MS (UPLC-Q-TOF-MS) with multivariate analysis revealed 19 and 16 metabolites, respectively. Notably, the levels of butyric acid, phenylalanine, glucose, tryptophan and some lysophosphatidylcholines were marginally increased in RC vinegar-treated groups compared to OVX. However, the pattern of metabolite levels in RC vinegar-treated groups was found similar to ALEN, but differed significantly from that in sham group. The results highlight the prophylactic and curative potential of dietary vinegar against postmenopausal osteoporosis. RC vinegar could be an effective natural alternative for the prevention of postmenopausal osteoporosis.

Non-targeted determination of 13C-labeling in the Methylobacterium extorquens AM1 metabolome using the two-dimensional mass cluster method and principal component analysis

A novel analytical workflow is presented for the analysis of time-dependent 13C-labeling of the metabolites in the methylotrophic bacterium Methylobacterium extorquens AM1 using gas chromatography time-of-flight mass spectrometry (GC-TOFMS). Using 13C-methanol as the substrate in a time course experiment, the method provides an accurate determination of the number of carbons converted to the stable isotope. The method also extracts a quantitative isotopic dilution time course profile for 13C uptake of each metabolite labeled that could in principle be used to obtain metabolic flux rates. The analytical challenges encountered require novel analytical platforms and chemometric techniques. GC-TOFMS offers advanced separation of mixtures, identification of individual components, and high data density for the application of advanced chemometrics. This workflow combines both novel and traditional chemometric techniques, including the recently reported two-dimensional mass cluster plot method (2D m/z cluster plot method) as well as principal component analysis (PCA). The 2D m/z cluster plot method effectively indexed all metabolites present in the sample and deconvoluted metabolites at ultra-low chromatographic resolution (RS≈0.04). Using the pure mass spectra extracted, two PCA models were created. Firstly, PCA was used on the first and last time points of the time course experiment to determine and quantify the extent of 13C uptake. Secondly, PCA modeled the full time course in order to quantitatively extract the time course profile for each metabolite. The 2D m/z cluster plot method found 152 analytes (metabolites and reagent peaks), with 54 pure analytes, and 98 were convoluted, with 65 of the 98 requiring mathematical deconvolution. Of the 152 analytes surveyed, 83 were metabolites determined by the PCA model to have incorporated 13C while 69 were determined to be either metabolites or reagent peaks that remained unlabeled.

Mechanism of Xinfeng Capsule on Adjuvant-Induced Arthritis via Analysis of Urinary Metabolomic Profiles.

We aimed to explore the potential effects of Xinfeng capsule (XFC) on urine metabolic profiling in adjuvant-induced arthritis (AA) rats by using gas chromatography time-of-flight mass spectrometry (GC-TOF/MS). GC-TOF/MS technology was combined with multivariate statistical approaches, such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal projections to latent structures discriminant analysis (OPLS-DA). These methods were used to distinguish the healthy group, untreated group, and XFC treated group and elucidate potential biomarkers. Nine potential biomarkers such as hippuric acid, adenine, and L-dopa were identified as potential biomarkers, indicating that purine metabolism, fat metabolism, amino acid metabolism, and energy metabolism were disturbed in AA rats. This study demonstrated that XFC is efficacious for RA and explained its potential metabolomics mechanism.