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In this study, we investigated the clinical changes induced by a high fat diet (HFD) and caffeine consumption in a rat model. The mean body weight of the HFD with caffeine (HFDC)-fed rat was decreased compared to that of the HFD-fed rat without caffeine. The levels of cholesterol, triglycerides (TGs), and free fatty acid, as well as the size of adipose tissue altered by HFD, were improved by caffeine consumption. To investigate the metabolites that affected the change of the clinical factors, the urine and serum of rats fed a normal diet (ND), HFD, and HFDC were analyzed using ultra performance liquid chromatography quadruple time-of-flight mass spectrometry (UPLC-Q-TOF-MS), gas chromatography (GC-TOF-MS), and linear trap quadruple mass spectrometry (LTQ-XL-MS) combined with multivariate analysis. A total of 68 and 52 metabolites were found to be different in urine and serum, respectively. After being fed caffeine, some glucuronide-conjugated compounds, lysoPCs, CEs, DGs, TGs, taurine, and hippuric acid were altered compared to the HFD group. In this study, caffeine might potentially inhibit HFD-induced obesity and we suggest possible biomarker candidates using MS-based metabolite profiling.

Metabolite profiles of seven commercial vinegars and two traditional vinegars were performed by gas chromatography time-of-flight mass spectrometry with multivariate statistical analysis. During alcohol fermentation, yeast, nuruk, and koji were used as sugars for nutrients and as fermentation substrates. Commercial and traditional vinegars were significantly separated in the principal component analysis and orthogonal partial least square discriminant analysis. Six sugars and sugar alcohols, three organic acids, and two other components were selected as different metabolites. Target analysis by ultra-performance liquid chromatography quadruple-time-of-flight mass spectrometry and liquid chromatographyion trap-mass spectrometry/mass spectrometry were used to detect several metabolites having antioxidant activity, such as cyanidin-3-xylosylrutinoside, cyanidin-3-rutinoside, and quercetin, which were mainly detected in Rural Korean Black raspberry vinegar (RKB). These metabolites contributed to the highest antioxidant activity measured in RKB among the nine vinegars. This study revealed that MS-based metabolite profiling was useful in helping to understand the metabolite differences between commercial and traditional vinegars and to evaluate the association between active compounds of vinegar and antioxidant activity.

In this study, 39 specimens belonging to Lespedeza species (Lespedeza cyrtobotrya, L. bicolor, L. maximowiczii, and Lespedeza cuneata) (Leguminosae) were classified phenotypically and genotypically. We constructed a phylogenetic tree based on the combined nrDNA (internal transcribed spacer; ITS) and cpDNA (trnL-trnF) sequences with the aim of classifying the genotypes. Samples were mainly divided into three genotypes. Samples of L. cyrtobotrya and L. bicolor were mixed in a single branch, whereas samples of L. maximowiczii and L. cuneata were clustered within species, respectively. We performed a liquid chromatography-electrospray ionization-mass spectrometry-based metabolite profiling analysis to classify the phenotypes. Multivariate statistical analyses such as principal component analysis (PCA) and hierarchical clustering analysis (HCA) were used for the clustering pattern analysis and distance analysis between species, respectively. According to the PCA and HCA results, leaves were classified into four phenotypes according to species. In both the genetic and chemotaxonomic classification methods, the distance between L. cyrtobotrya and L. bicolor was the closest between species, and L. cuneata was the farthest away from the other three species. Additionally, orthogonal partial least squares-discriminant analysis was employed to identify significantly different phytochemicals between species. We classified L. cyrtobotrya and L. bicolor by identifying significantly different phytochemicals. Interestingly, leaves and stems showed different phenotypic classifications based on the chemotaxonomic classification. Stem samples of the other three species were mixed regardless of species, whereas L. cyrtobotrya stem samples were clustered within species. The phenotypic classification of leaves coincided more with the genotypic classification than that of stems. Key message We classified four wild-type Lespedeza sp. by analyzing the combined nrDNA (ITS) and cpDNA (trnL-trnF) sequences. We also classified leaves and stems of Lespedeza sp. by applying liquid chromatography-mass spectroscopy-based metabolite profiling.

In this study, 4 Penicillium species (17 strains) were classified on the basis of metabolite profile (chemotaxonomy) by using liquid chromatography-electrospray ionization ion trap-mass spectrometry (LC-ESI-MS), gas chromatography-ion trap-mass spectrometry (GC-IT-MS) and multivariate statistical analysis. The LC-ESI-MS-based dendrogram was similar to the internal transcribed spacer (ITS)-based dendrogram, in that Penicillium oxalicum was separated from the other 3 species. Moreover, vermiculidiol, meleagrin, oxaline, glandicolin A and B, and secalonic acid D were identified as metabolites that enable discrimination of Penicillium species by partial least squares discriminant analysis (PLS-DA). Evaluation of the species-specific metabolites produced by P. expansum, P. echinulatum, and P. solitum revealed that the 3 species differed from each other. On the other hand, GC-IT-MS-based dendrogram revealed that P. expansum was clearly classified separately from the other 3 species, and this result correlated with the antioxidant activity of the 4 species: P. expansum had a higher radical scavenging activity than the other 3 species. The metabolites produced in higher amounts in P. expansum were gluconic acid (12, 29, 33); andrastin A (16), B (15), and C (17); chaetoglobosin C (14), a class of sugar (31, 32); and salicylic acid (28). The results of this study demonstrated that metabolite-based chemotaxonomy could be used not only as a classification method but also as a tool for evaluation of species-specific activities.