• Journal of the Korean Magnetic Resonance Society
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• v.22 no.1
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• pp.10-17
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• 2018

Metabolite identification and quantification are one of the foremost important issues in metabolomics. In NMR based metabolomics, mainly one-dimensional proton NMR spectra of biofluids, such as urine and serum are measured. However, it is not always easy to identify and quantify metabolites in one-dimensional proton NMR spectra. This article introduces useful public metabolite databases, metabolic profiling software, and articles.

• Journal of Microbiology and Biotechnology
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• v.19 no.1
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• pp.51-54
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• 2009

Myxobacteria, Gram-negative soil bacteria, are a well-known producer of bioactive secondary metabolites. Therefore, this study presents a methodological approach for the high-throughput screening of secondary metabolites from 4 wild-type Myxococcus xanthus strains. First, electrospray ionization mass spectrometry (ESI-MS) was performed using extracellular crude extracts. As a result, 22 metabolite peaks were detected, and the metabolite profiling was then conducted using the m/z value, retention time, and MS/MS fragmentation pattern analyses. Among the peaks, one unknown compound peak was identified as analogous to the myxalamid A, B, and C series. An analysis of the tandem mass spectrometric fragmentation patterns and HR-MS identified myxalamid K as a new compound derived from M. xanthus. In conclusion, LC-MS/MS-based chemical screening of diverse secondary metabolites would appear to be an effective approach for discovering unknown microbial secondary metabolites.

• 한국약용작물학회:학술대회논문집
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• 2008.11a
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• pp.321-322
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• 2008

• 한국약용작물학회:학술대회논문집
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• 2008.05a
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• pp.162-163
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• 2008

• Proceedings of the Korean Society of Plant Biotechnology Conference
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• 2004.10a
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• pp.209-209
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• 2004

• Journal of Microbiology and Biotechnology
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• v.25 no.2
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• pp.217-226
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• 2015

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 chromatography-ion 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.

• Proceedings of the Korean Society of Applied Pharmacology
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• 2007.11a
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• pp.19-27
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• 2007

An important potential of metabolomics-based approach is the possibility to develop fingerprints of diseases or cellular responses to classes of compounds with known common biological effect. Such fingerprints have the potential to allow classification of disease states or compounds, to provide mechanistic information on cellular perturbations and pathways and to identify biomarkers specific for disease severity and drug efficacy. Metabolic profiles of biological fluids contain a vast array of endogenous metabolites. Changes in those profiles resulting from perturbations of the system can be observed using analytical techniques, such as NMR and MS. $^1H$ NMR was used to generate a molecular fingerprint of serum or urinary sample, and then pattern recognition technique was applied to identity molecular signatures associated with the specific diseases or drug efficiency. Several metabolites that differentiate disease samples from the control were thoroughly characterized by NMR spectroscopy. We investigated the metabolic changes in human normal and clinical samples using $^1H$ NMR. Spectral data were applied to targeted profiling and spectral binning method, and then multivariate statistical data analysis (MVDA) was used to examine in detail the modulation of small molecule candidate biomarkers. We show that targeted profiling produces robust models, generates accurate metabolite concentration data, and provides data that can be used to help understand metabolic differences between healthy and disease population. Such metabolic signatures could provide diagnostic markers for a disease state or biomarkers for drug response phenotypes.

• Journal of Microbiology and Biotechnology
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• v.23 no.2
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• pp.177-183
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• 2013

Bacterial blight, an important and potentially destructive bacterial disease in rice caused by Xanthomonas oryzae pv. oryzae (Xoo), has recently developed resistance to the available antibiotics. In this study, mass spectrometry (MS)-based metabolite profiling and multivariate analysis were employed to investigate the correlation between timedependent metabolite changes and antimicrobial activities against Xoo over the course of Phomopsis longicolla S1B4 fermentation. Metabolites were clearly differentiated based on fermentation time into phase 1 (days 4-8) and phase 2 (days 10-20) in the principal component analysis (PCA) plot. The multivariate statistical analysis showed that the metabolites contributing significantly for phases 1 and 2 were deacetylphomoxanthone B, monodeacetylphomoxanthone B, fusaristatin A, and dicerandrols A, B, and C as identified by liquid chromatography-mass spectrometry (LC-MS), and dimethylglycine, isobutyric acid, pyruvic acid, ribofuranose, galactofuranose, fructose, arabinose, hexitol, myristic acid, and propylstearic acid were identified by gas chromatography-mass spectrometry (GC-MS)-based metabolite profiling. The most significantly different secondary metabolites, especially deacetylphomoxanthone B, monodeacetylphomoxanthone B, and dicerandrol A, B and C, were positively correlated with antibacterial activity against Xoo during fermentation.

• Journal of Microbiology and Biotechnology
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• v.30 no.11
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• pp.1697-1705
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• 2020

Meju, a type of fermented soybean paste, is used as a starter in the preparation of various Korean traditional soybean-based foods. In this study, we performed Illumina-MiSeq paired-end sequencing for microbial communities and mass spectrometry analysis for metabolite profiling to investigate the differences between 11 traditional meju products from different regions across Korea. Even though the bacterial and fungal communities showed remarkable variety, major genera including Bacillus, Enterococcus, Variovorax, Pediococcus, Weissella, and Aspergillus were detected in every sample of meju. The metabolite profile patterns of the 11 samples were clustered into two main groups: group I (M1-5) and group II (M6-11). The metabolite analysis indicated a relatively higher amino acid content in group I, while group II exhibited higher isoflavone, soyasaponin, and lysophospholipid contents. The bioactivity analysis proved that the ABTS (2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid)) radical-scavenging activity was higher in group II and the FRAP (ferric reducing antioxidant power) activity was higher in group I. The correlation analysis revealed that the ABTS activity was isoflavonoid, lipid, and soyasaponin related, whereas the FRAP activity was amino acid and flavonoid related. These results suggest that the antioxidant activities of meju are critically influenced by the microbiome and metabolite dynamics.

• Biomedical Science Letters
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• v.30 no.3
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• pp.173-180
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• 2024

Hypercholesterolemia, a form of hyperlipidemia, is a significant risk factor for cardiovascular diseases, often linked to genetic variations in the APOE gene, particularly the ε4 allele, which influences LDL cholesterol levels. This study aimed to examine the association between APOE gene variants and plasma sphingomyelin levels in Korean individuals with hypercholesterolemia, using a metabolite genome-wide association study (mGWAS) approach. Data from 7,031 participants in the Korean Genome and Epidemiology Study (KoGES) were analyzed. Genetic associations with cholesterol and sphingomyelin levels were evaluated through Exome chip analysis and metabolite profiling. Significant associations were identified between specific APOE variants (e.g., rs769449, rs4420638) and serum cholesterol levels. Additionally, certain SNPs were linked to variations in plasma sphingomyelin levels, suggesting a genetic influence on both lipid and sphingomyelin metabolism. The findings underscore the relevance of mGWAS in unraveling the genetic and metabolic pathways involved in hypercholesterolemia, offering potential biomarkers for disease risk and therapeutic targets.