Cordyceps militaris (C. militaris) is a unique and valuable medicinal fungus belonging to the Cordyceps species. C. militaris is the only fungus that contains cordycepin which is a biologically active compound. In previous studies, light-emitting diodes (LEDs) are known to be effective in increasing cordycepin content, but metabolic profiling of LED-stimulated C. militaris has not been confirmed. Metabolic profiling is essential to understanding the metabolic regulation of cordycepin. This study studied the physiologically active secondary metabolites of C. militaris according to the presence or absence of stimulation of LEDs through GC-MS analysis. Most of the metabolites were detected in both samples, but there was a clear difference in the detected concentration. In particular, C. militaris had a significant difference in amino acid levels when stimulated with LEDs. Our results suggested that LEDs could stimulate amino acid synthesis in C. militaris mycelium to increase the cordycepin content.

Chrysanthemum boreal, C. indicum, and C. indicum var. albescens are well-known wild Chrysanthemum species used for traditional medicine in Korea. In this study, volatile compounds from three wild Chrysanthemums were identified according to four different flowering stages and analyzed using HS-SPME-GC-MS to determine the temporal variation of the volatiles. As a result, 132, 151, and 142 peaks were identified from C. boreale, C. indicum, and C. indicum var. albescens, respectively. Furthermore, 70 out of 132 peaks were identified in C. boreale with a matching ratio of >90% from library search. In addition, 85/151 and 76/142 peaks were identified from C. indicum and C. indicum var. albescens. Forty-nine volatile compounds were found commonly in all three wild Chrysanthemums through all four different flowering stages. However, six, seven, and five unique compounds were detected only in C. boreale, C. indicum, and C. indicum var. albescens, respectively. One hundred volatile compounds were selected for multivariate analysis considering volatile compounds overlapped with each other. The one-way ANOVA (p < 0.05) detected significant differences from 77 out of 100 volatile compounds. In addition, PLS-DA showed the different profiles of volatile compounds according to four different flowering stages in each wild Chrysanthemum. PC1 of each Chrysanthemum accounted for 45.8 56.9, and 11.9% in C. boreale, C. indicum, and C. indicum var. albescens, respectively. PC1 of C. boreale and C. indicum clearly separated the BF stage and the other three stages. Conversely, PC1 of C . indicum var. albescens showed a difference in the composition of volatile compounds between the BF/BO and HO/FO stages. In addition, the different profiles of volatile compounds could be visualized using a heatmap from three wild Chrysanthemums according to four different flowering stages. This study will help improve particular volatile compounds in three wild Chrysanthemums both in quality and quantity.

Volatile organic compounds (VOCs) in plants are various organic compounds with small molecular weight and high vapor pressure. The metabolomics approach was recently introduced to analyze VOCs involved in biological processes, such as abiotic and biotic stresses, spatial and temporal distribution, and genotypic differences. In addition, this approach is widely used in combination with identification of VOCs analysis and statistical analysis using multivariate analysis, such as principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), hierarchical cluster analysis (HCA), etc. First, in this review, the current condition of the metabolomics approach to analyze VOCs synthesized in plants using head space-solid phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) is discussed. In addition, metabolomics approach, such as extraction and analysis of VOCs using HS-SPME-GC-MS, conversion, and processing of mass spectral (MS) data, a database for VOCs identification, useful statistical methods, and statistical tools and applications, are explained. Finally, multi-omics in combination with other omics techniques, such as genomics, transcriptomics, etc. are suggested as prospects of a metabolomics approach for VOC analysis in floricultural plants using HS-SPMEGC- MS. Therefore, the metabolomics approach of HS-SPMEGC- MS will facilitate our understanding of VOCs synthesized in plants. Furthermore, the multi-omics approach will help understand gene functions involved in the biosynthesis of VOCs and help develop new development cultivars with nicer floral scents by contributing to the development of the floricultural industry.

As the fruit and vegetable beverage market grows, a variety of foods are continually increasing. Therefore, when ingredients other than those indicated are added to achieve economic benefits, cases of adulteration and falsification concurrently follow. Among these, blueberry as expensive fruits, is one of the target for adulteration in juice production. This study was conducted based on the reports regarding the forgery of blueberry juice and grape juice; 32 kinds of blueberry juices, which are sold on the market, were collected and their metabolomics analysis was performed to screen out possible discriminants for blueberry juice adulteration. Metabolomes were extracted with 80% methanol and analyzed through LC-MS/MS followed by data processing with multivariate statistical analysis. Based on OPLS (orthogonal partial least squared) model, four metabolites were screened as significant discriminants among 209 metabolites found in blueberry juice and anthocyanin compounds occupied a main groups for discrimination. Marvidin-3-O-glucoside and cyanidin-3-O-rutinoside were identified as significant indicators for the existence of blueberry compared to grape juice which is main adulterates in blueberry juices. These candidates were assessed for monitoring commercial blueberry juices, which were proved as useful determinant for adulteration.

Nuruk, a Korean fermentation starter for Makgeolli, contains a variety of microflora according to province and natural environment. However, the metabolites profiles in traditional Korean Nuruk were not defined yet. In this study, Nuruk were prepared with 20 different fungi originated from Gangwon province (Rhizomucor variabilis, Lichtheimia corymbifera, and Aspergillus species) and their metabolites were profiled / compared with commercial strains (Aspergillus kawachii) through metabolomics analysis. Metabolites were extracted with solvent mixture (Isopropanol: Methanol: Distilled water) and put into MS spectrometry analysis. After processing of full mass spectra data from LC-MS/MS, the characteristics of each strain were compared and analyzed by multivariate statistical analysis such as hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA).Interestingly, strain specific classification was observed by HCA and PCA among samples and significant differences were also indicated from commercial strain Aspergillus kawachii. As a results, 26 metabolites were successfully screened with a validity from a total of 189 metabolites by using of VIP plot through OPLS-DA. These results suggested the uniqueness of Korean traditional home brewed liquor compared to commercial liquor and could be useful information for Korean brewing industry.

Background : Ribes fasciculatum var. chinense Maxim. has been traditionally used as febrifuge, diuretic and antidote against urushiol in Korea. This study described a metabolomics approach used to discriminate the genus Ribes from different sources. Methods and Results : Four different types of Ribes from Korea were analyzed by ultra-high-resolution mass spectrometry (UHPLC-HR-MS/MS) based metabolomics. Multivariate statistical method such as principal component analysis (PCA) were used to compare the derived patterns among the samples. The data set was subsequently applied to various metabolite selection methods for sophisticated classification with the optimal number of metabolites. The results showed variations in accuracy among the classification methods for the samples of different origins, especially for cultivation region. Conclusion : This proposed analytical method coupled with multivariate analysis is fast, accurate, and reliable for discriminating the origin of the genus Ribes samples and is a potential tool to standardize quality control in the genus Ribes related products.

Background: A set of logical criteria that can accurately identify and verify the cultivation region of raw materials is a critical tool for the scientific management of traditional herbal medicine. Methods and Results: Volatile compounds were obtained from 19 and 32 samples of Angelica gigas Nakai cultivated in Korea and China, respectively, by using steam distillation extraction. The metabolites were identified using GC/MS by querying against the NIST reference library. Data binning was performed to normalize the number of variables used in statistical analysis. Multivariate statistical analyses, such as Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) were performed using the SIMCA-P software. Significant variables with a Variable Importance in the Projection (VIP) score higher than 1.0 as obtained through OPLS-DA and those that resulted in p-values less than 0.05 through one-way ANOVA were selected to verify the marker compounds. Among the 19 variables extracted, styrene, α-pinene, and β-terpinene were selected as markers to indicate the origin of A. gigas. Conclusions: The statistical model developed was suitable for determination of the geographical origin of A. gigas. The cultivation regions of six Korean and eight Chinese A. gigas. samples were predicted using the established OPLS-DA model and it was confirmed that 13 of the 14 samples were accurately classified

Seed color is an important trait affecting flour yield and quality in wheat. Seed color also is either tightly linked to or pleiotropically controls seed dormancy in wheat, because most of the red-seeded wheats are tolerant to pre-harvest sprouting in comparison to white-seeded wheats. Recently, metabolomics approaches have recently been used to assess the natural variance in metabolite content between individual plants, an approach with great potential for the improvement of the compositional quality of crops. Basically, in the study here, the simultaneous proteomic and metablomic approaches are being investigated to identify the expressed proteins of genes and specific metabolism responsible for the expression of red and white colors of seed. Red seed “Jinpum” and white seed “Kumkang” cultivars were used in this study to identify the storage proteins use of 2-DE, MALDI-TOF/MS. Here we optimize tissue extraction methods compatible with high-throughput, reproducible nuclear magnetic resonance (NMR) spectroscopy based metabolomics. It appears that the proteins expressed were different each other according to two different cultivars from the seeds of hexaploid wheat. Some selected protein spots were identified as follows: B3-hordein, Gamma-hordein-3,bifunctionalalpha amylase/subtilisin Inhibitor. To monitor metabolic profile, wheat grain was ground in liquid nitrogen, ensuring a homogeneous mix of the tissue, solution samples extracted from seed grains of two wheat cultivars were conducted to measurement of metabolite using 1H-1D NMR method. Representative 1H-1D NMR spectra showing the metabolic fingerprints of wheat grain extracted and presented in Fig. The different peaks, observed at 3.4 and 4.3 ppm, were detected and difference in each two cultivars. The metabolic fingerprint of each two wheat cultivars by 1H-1D NMR were analysed using partial least squares (PLS) in mutivariate analysis to confirm metabolic profiling between different cultivars and to screen chemical shift spectrum corresponding to metabolite specifically abundant in each cultivars. Profiling using 1H-1D NMR was applied to measure of abundance of major metabolite. In total metabolites were compared between “Jinpum” and “Kumkang” cultivars. Therefore, NMR based on the metabolic-phenotyping should be mostly applicable to systematic exploration of plant genetic resources as well as to metabolite based on the breeding program involved in crops productivity.