• 한국식품영양과학회지
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• 제43권3호
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• pp.419-424
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• 2014

본 연구에서는 LC-MS/MS를 이용한 블루베리의 methanol과 ethyl acetate 추출 분획에 존재하는 대사체의 분석을 통해 효율적인 대사체 profiling의 가능성을 탐색하였다. LC-MS/MS에서 검출되는 대사체를 통계 처리한 결과, methanol 추출 분획에서는 5-O-feruloylquinic acid, malvidin hexoside, malvidin-3-arabinoside, petunidin-3-arabinoside, delphinidin hexoside, delphinidin, petunidin hexoside와 같은 안토시아닌 계열의 화합물들이 존재하였고, ethyl acetate 분획에서는 chlorogenic acid, chlorogenic acid dimer, 6,8-di-C-arabinopyranosylluteolin, luteolin과 같은 플라보노이드 계열의 화합물이 검출되었다. 본 연구는 기존 연구와 달리 대사체학 기법을 이용한 블루베리 추출물 전체 대사물질의 profiling을 시도한 최초의 연구로서 블루베리에 함유된 유용 성분의 스크리닝 등 향후 응용 연구에 유용한 기반으로 이용될 수 있을 것으로 기대된다.

• Journal of Applied Biological Chemistry
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• 제64권2호
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• pp.141-151
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• 2021

Insects affect crop harvest yield and quality, making plant response mechanisms to insect herbivores a heavily studied topic. However, analysis of plant responses to honeybees is rare. In this study, comprehensive metabolic profiling of Arabidopsis thaliana exposed to honeybees was performed to investigate which metabolites were changed by the insect. A total of 85 metabolites-including chlorophylls, carotenoids, glucosinolates, policosanols, tocopherols, phytosterols, β-amyrin, amino acids, organic acids, sugars, and starch-were identified using high performance liquid chromatography, gas chromatography-mass spectrometry, and gas chromatography-time-of-flight mass spectrometry. The metabolite profiling analysis of Arabidopsis exposed to honeybees showed higher levels of stress-related metabolites. The levels of glucosinolates (glucoraphanin, 4-methoxyglucobrassicin), policosanols (eicosanol, docosanol, tricosanol, tetracosanol), tocopherols (β-tocopherol, γ-tocopherol), putrescine, lysine, and sugars (arabinose, fructose, glucose, mannitol, mannose, raffinose) in Arabidopsis exposed to honeybees were higher than those in unexposed Arabidopsis. Glucosinolates act as defensive compounds against herbivores; policosanols are components of plant waxes; tocopherols act as an antioxidant; and putrescine, lysine, and sugars contribute to stress regulation. Our results suggest that Arabidopsis perceives honeybees as a stress and changes its metabolites to overcome the stress. This is the first step to determining how Arabidopsis reacts to exposure to honeybees.

• Bulletin of the Korean Chemical Society
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• 제34권5호
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• pp.1467-1472
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• 2013

Metabolomics is a field that studies systematic dynamics and secretion of metabolites from cells to understand biological pathways based on metabolite changes. The metabolic profiling of intact human colorectal tissues was performed using high-resolution magic angle spinning (HR-MAS) NMR spectroscopy, which was unnecessary to extract metabolites from tissues. We used two different groups of samples, which were defined as normal and cancer, from 9 patients with colorectal cancer and investigated the samples in NMR experiments with a water suppression pulse sequence. We applied target profiling and multivariative statistical analysis to the analyzed 1D NMR spectra to identify the metabolites and discriminate between normal and cancer tissues. Cancer tissue showed higher levels of arginine, betaine, glutamate, lysine, taurine and lower levels of glutamine, hypoxanthine, isoleucine, lactate, methionine, pyruvate, tyrosine relative to normal tissue. In the OPLS-DA (orthogonal partial least square discriminant analysis), the score plot showed good separation between the normal and cancer groups. These results suggest that metabolic profiling of colorectal cancer could provide new biomarkers.

• Journal of Microbiology and Biotechnology
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• 제19권1호
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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.

• 대한유전성대사질환학회지
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• 제6권1호
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• pp.40-51
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• 2006

Purpose: A personal computer-based system was developed for automated metabolic profiling of organic aciduria and aminoacidopathy by gas chromatography-mass spectrometry and data interpretation for the diagnosis of metabolic disorders Methods: For automatic data profiling and interpretation, we compiled retention time, two target ions and their intensity ratio for 77 organic acids and 13 amino acids metabolites. Metabolites above the cut-off values were flagged as abnormal compounds. The data interpretation was a based on combination of flagged metabolites. Diagnostic or index metabolites were categorized into three groups, "and", "or" and "NO" compiled for each disorder to improve the specificity of the diagnosis. Groups "and" and "or" comprised essential and optional compounds, respectively, to reach a specific diagnosis. Group "NO" comprised metabolites that must be absent to make a definite diagnosis. We tested this system by analyzing patients with confirmed Propionic aciduria and others. Results: In all cases, the diagnostic metabolites were identified and correct diagnosis was founded to be made among the possible disease suggested by the system. Conclusion: The study showed that the developed method could be the method of choices in rapid, sensitive and simultaneous screening for organic aciduria and amino acidopathy with this simplified automated system.

• Mycobiology
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• 제50권2호
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• pp.110-120
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• 2022

The goal of the present study was to investigate the antibacterial properties, enzyme production, and metabolic profiling of a new Ceratorhiza hydrophila strain isolated from the submerged aquatic plant Myriophyllum spicatum. Furthermore, the fungus' morphological characterization and DNA sequencing have been described. The fungus has been identified and submitted to the GenBank as Ceratorhiza hydrophila isolate EG19 and the fungus ID is MK387081. The enzyme analyses showed its ability to produce protease and cellulase enzymes. According to the CSLI standard, the ethyl acetate extract of C. hydrophila showed intermediate antibacterial activity against Streptococcus pneumonia, Micrococcus luteus, and Staphylococcus aureus. Metabolic profiling has been carried out using 700 MHz NMR spectroscopy. Based on the ¹H and ¹H-¹³C heteronuclear single quantum coherence (HSQC) NMR data and NMR databases, 23 compounds have been identified. The identified metabolites include 31% amino acids, 9% sugars, 9% amines, 4% sugar alcohols, and 4% alkaloids. This is the first report for the metabolic characterization of C. hydrophila, which gave preliminary information about the fungus. It is expected that our findings not only will pave the way to other perspectives in enormous applications using C. hydrophila as a new promising source of antimicrobial agents and essential metabolites, but also it will be valuable in the classification and chemotaxonomy of the species.

• 한국자기공명학회논문지
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• 제17권1호
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• pp.1-10
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• 2013

Metabolomics is the study which detects the changes of metabolites level. Metabolomics is a terminal view of the biological system. The end products of the metabolism, metabolites, reflect the responses to external environment. Therefore metabolomics gives the additional information about understanding the metabolic pathways. These metabolites can be used as biomarkers that indicate the disease or external stresses such as exposure to toxicant. Many kinds of biological samples are used in metabolomics, for example, cell, tissue, and bio fluids. NMR spectroscopy is one of the tools of metabolomics. NMR data are analyzed by multivariate statistical analysis and target profiling technique. Recently, NMR-based metabolomics is a growing field in various studies such as disease diagnosis, forensic science, and toxicity assessment.

• The Plant Pathology Journal
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• 제32권6호
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• pp.489-499
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• 2016

Green shoot cuttings of 10 different grapevine species were inoculated with Agrobacterium vitis to find disease-related metabolites in the grapevine. Crown galls formed 60 days after inoculation varied in gall severity (GS) evaluated by gall incidence (GI) and gall diameter (GD), which were classified into three response types as RR (low GI and small GD), SR (high GI and small GD), and SS (high GI and large GD), corresponding to resistant, moderately resistant, and susceptible responses, respectively. In this, 4, 4, and 2 Vitis species were classified into RR, SR, and SS, respectively. Gas chromatography mass spectrometry (GC-MS) analysis of the grapevine stem metabolites with A. vitis infection showed 134 metabolites in various compound classes critically occurred, which were differentially clustered with the response types by the principal component analysis. Multivariate analysis of the metabolite profile revealed that 11 metabolites increased significantly in relation to the response types, mostly at post-inoculation stages, more prevalently (8 metabolites) at two days after inoculation than other stages, and more related to SS (7 metabolites) than RR (3 metabolites) or SR (one metabolite). This suggests most of the disease-related metabolites may be rarely pre-existing but mostly induced by pathogen infection largely for facilitating gall development except stilbene compound resveratrol, a phytoalexin that may be involved in the resistance response. All of these aspects may be used for the selection of resistant grapevine cultivars and their rootstocks for the control of the crown gall disease of the grapevine.

• 한국응용약물학회:학술대회논문집
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• 한국응용약물학회 2007년도 Proceedings of The Convention
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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.

• 한국자기공명학회논문지
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• 제14권1호
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• pp.28-37
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• 2010

Metabolites of urine samples from 6 colorectal cancer patients were analyzed by two-dimensional NMR spectroscopy, where the samples were collected before and after the surgical treatments per patient. NMR data were analyzed with the help of the metabolome database and the statistics software. Urine samples before and after the treatments showed significantly different metabolic profiles from each other. We were able to compare 10 different metabolites. Most of the assigned metabolites of every patient showed a tendency of increase after the surgery except for a few cases. The amount of changes in individual metabolites varied significantly from patient to patient, but the combination of such changes could be used to distinguish the condition before the surgery from after, which could be done by PCA analysis. The analysis via $^{1}H-^{13}C$ HSQC spectra proved to be applicable in assessing and classifying global metabolic profiles of the urines from colorectal cancer patients.