• Title/Summary/Keyword: Metabolites profiling

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Metabolic profiling of serum and urine in lactating dairy cows affected by subclinical ketosis using proton nuclear magnetic

  • Eom, Jun Sik;Lee, Shin Ja;Kim, Hyun Sang;Choi, Youyoung;Jo, Seong Uk;Lee, Sang Suk;Kim, Eun Tae;Lee, Sung Sill
    • Journal of Animal Science and Technology
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    • v.64 no.2
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    • pp.247-261
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    • 2022
  • Ketosis is associated with high milk yield during lactating or insufficient feed intake in lactating dairy cows. However, few studies have been conducted on the metabolomics of ketosis in Korean lactating dairy cows. The present study aimed to investigate the serum and urine metabolites profiling of lactating dairy cows through proton nuclear magnetic resonance (1H-NMR) spectroscopy and comparing those between healthy (CON) and subclinical ketosis (SCK) groups. Six lactating dairy cows were categorized into CON and SCK groups. All experimental Holstein cows were fed total mixed ration. Serum and urine samples were collected from the jugular vein of the neck and by hand sweeping the perineum, respectively. The metabolites in the serum and urine were determined using 1H-NMR spectroscopy. Identification and quantification of metabolites was performed by Chenomx NMR Suite 8.4 software. Metabolites statistical analysis was performed by Metaboanalyst version 5.0 program. In the serum, the acetoacetate level was significantly (p < 0.05) higher in the SCK group than in the CON group, and whereas acetate, galactose and pyruvate levels tended to be higher. CON group had significantly (p < 0.05) higher levels of 5-aminolevulinate and betaine. Indole-3-acetate, theophylline, p-cresol, 3-hydroxymandelate, gentisate, N-acetylglucosamine, N-nitrosodimethylamine, xanthine and pyridoxine levels were significantly (p < 0.05) higher in the urine of the SCK group than that in the CON group, which had higher levels of homogentisate, ribose, gluconate, ethylene glycol, maltose, 3-methyl-2-oxovalerate and glycocholate. Some significantly (p < 0.05) different metabolites in the serum and urine were associated with ketosis diseases, inflammation, energy balance and body weight. This study will be contributed useful a future ketosis metabolomics studies in Korea.

Comparison of Traditional and Commercial Vinegars Based on Metabolite Profiling and Antioxidant Activity

  • Jang, Yu Kyung;Lee, Mee Youn;Kim, Hyang Yeon;Lee, Sarah;Yeo, Soo Hwan;Baek, Seong Yeol;Lee, Choong Hwan
    • 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.

Metabolic Changes of Phomopsis longicolla Fermentation and Its Effect on Antimicrobial Activity Against Xanthomonas oryzae

  • Choi, Jung Nam;Kim, Jiyoung;Ponnusamy, Kannan;Lim, Chaesung;Kim, Jeong Gu;Muthaiya, Maria John;Lee, Choong Hwan
    • 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.

Practical Guide to NMR-based Metabolomics - II : Metabolite Identification & Quantification

  • Jung, Young-Sang
    • 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.

Molecular Identification, Enzyme Assay, and Metabolic Profiling of Trichoderma spp.

  • Bae, Soo-Jung;Park, Young-Hwan;Bae, Hyeun-Jong;Jeon, Junhyun;Bae, Hanhong
    • Journal of Microbiology and Biotechnology
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    • v.27 no.6
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    • pp.1157-1162
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    • 2017
  • The goal of this study was to identify and characterize selected Trichoderma isolates by metabolic profiling and enzyme assay for evaluation of their potential as biocontrol agents against plant pathogens. Trichoderma isolates were obtained from the Rural Development Administration Genebank Information Center (Wanju, Republic of Korea). Eleven Trichoderma isolates were re-identified using ribosomal DNA internal transcribed spacer (ITS) regions. ITS sequence results showed new identification of Trichoderma isolates. In addition, metabolic profiling of the ethyl acetate extracts of the liquid cultures of five Trichoderma isolates that showed the best anti-Phytophthora activities was conducted using gas chromatography-mass spectrometry. Metabolic profiling revealed that Trichoderma isolates shared common metabolites with well-known antifungal activities. Enzyme assays indicated strong cell wall-degrading enzyme activities of Trichoderma isolates. Overall, our results indicated that the selected Trichoderma isolates have great potential for use as biocontrol agents against plant pathogens.

Stress Adaptation of Escherichia coli as Monitored via Metabolites by Using Two-Dimensional NMR Spectroscopy

  • Chae, Young Kee;Kim, Seol Hyun
    • Journal of the Korean Magnetic Resonance Society
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    • v.21 no.3
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    • pp.102-108
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    • 2017
  • Escherichia coli responds to ever-changing external and internal stresses by rapidly adjusting its physiology for better survival. This adjustment occurs at all levels including metabolites as well as mRNAs and proteins. Although there has been many reports describing E. coli's adaptation to various stresses regarding transcriptomics or proteomics, only a few investigations have been reported regarding this adaptation viewed from metabolites' perspective. We applied four different types of stresses at four different doses as imposed by NaCl, sorbitol, ethanol, and pH to investigate the similarities or differences among the stresses, and which stress causes the largest perturbation of the metabolite composition. We profiled the metabolites under such external stresses by using two-dimensional NMR spectroscopy and identified 39 metabolites including amino acids, sugars, organic acids, and nucleic acids. According to our statistical analysis, the osmotic stress caused by sorbitol differentiated itself from others, while NaCl showed the largest dose dependent metabolic perturbations. We hope this work will form a foundation on which an approach to a successful protein production is systematically provided by a favorable metabolic environment by imposing proper external stresses.

APPLICATION OF METABOLITE PROFILE KINETICS FOR EXPOSURE AND RISK ASSESSMENT

  • Lee, Byung-Mu
    • Proceedings of the Korean Society of Toxicology Conference
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    • 2006.11a
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    • pp.34-45
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    • 2006
  • Chemical toxicants are metabolically converted to numerous metabolites in the body. Toxicokinetic characteristics of metabolites could be therefore used as biomarker of exposure for human risk assessment. Biologically based dose response (BBDR) model was proposed for future direction of risk assessment. However, this area has not been developed well enough for human application. Benzo(a)pyrene (BP), for example, is a well-known environmental carcinogen and may produce more than 100 metabolites and BPDE-DNA adduct, a covalently bound form of DNA with benzo(a)pyrene diolepoxides (BPDES), has been applied to qualitatively or quantitaively estimate human exposure to BP. In addition, di(2-ethylhexyl) phthalate (DEHP), a widely used plasticize. in the polymer industry, is one of endocrine-disrupting chemicals (EDCs) and has been monitored in humans using urinary or serum concentrations of DEHP or its monomer MEHP for exposure and risk assessment. However, it is difficult to estimate the actual level of toxicants using these biomarkers in humans using. This presentation will discuss a methodology of exposure and risk assessment by application of metabolic profiling kinetics.

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The difference of metabolic profile between male and female zebrafish

  • Yoon, Dahye;Choi, Jin;Choi, Hyeonsoo;Kim, Suhkmann
    • Journal of the Korean Magnetic Resonance Society
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    • v.20 no.1
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    • pp.13-16
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    • 2016
  • Various experiments using zebrafish have been highlighted recently in the scientific community. Because it is possible to conduct practical experiment from various neurological research to area of genetic study or toxicity experiment. However, gender difference effects are nearly not considered. If the gender differences of zebrafish are considered it is possible to obtain more accurate data. In this study, zebrafish which have different genders were compared each other with NMR-based metabolomics. The extracts of male and female zebrafish were measured by 600 MHz NMR spectrometer. Statistical analysis and target profiling were conducted. As a result, muscle related metabolites were observed in male zebrafish and nerve related metabolites were observed in female zebrafish.

Chemotaxonomy of Trichoderma spp. Using Mass Spectrometry-Based Metabolite Profiling

  • Kang, Dae-Jung;Kim, Ji-Young;Choi, Jung-Nam;Liu, Kwang-Hyeon;Lee, Choong-Hwan
    • Journal of Microbiology and Biotechnology
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    • v.21 no.1
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    • pp.5-13
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    • 2011
  • In this study, seven Trichoderma species (33 strains) were classified using secondary metabolite profile-based chemotaxonomy. Secondary metabolites were analyzed by liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS-MS) and multivariate statistical methods. T. longibrachiatum and T. virens were independently clustered based on both internal transcribed spacer (ITS) sequence and secondary metabolite analyses. T. harzianum formed three subclusters in the ITS-based phylogenetic tree and two subclusters in the metabolitebased dendrogram. In contrast, T. koningii and T. atroviride strains were mixed in one cluster in the phylogenetic tree, whereas T. koningii was grouped in a different subcluster from T. atroviride and T. hamatum in the chemotaxonomic tree. Partial least-squares discriminant analysis (PLS-DA) was applied to determine which metabolites were responsible for the clustering patterns observed for the different Trichoderma strains. The metabolites were hetelidic acid, sorbicillinol, trichodermanone C, giocladic acid, bisorbicillinol, and three unidentified compounds in the comparison of T. virens and T. longibrachiatum; harzianic acid, demethylharzianic acid, homoharzianic acid, and three unidentified compounds in T. harzianum I and II; and koninginin B, E, and D, and six unidentified compounds in T. koningii and T. atroviride. The results of this study demonstrate that secondary metabolite profiling-based chemotaxonomy has distinct advantages relative to ITS-based classification, since it identified new Trichoderma clusters that were not found using the latter approach.