• Title/Summary/Keyword: Metabolic Analysis

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A Review on Metabolic Pathway Analysis with Emphasis on Isotope Labeling Approach

  • Azuyuki, Shimizu
    • Biotechnology and Bioprocess Engineering:BBE
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    • v.7 no.5
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    • pp.237-251
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    • 2002
  • The recent progress on metabolic systems engineering was reviewed based on our recent research results in terms of (1) metabolic signal flow diagram approach, (2) metabolic flux analysis (MFA) in particular with intracellular isotopomer distribution using NMR and/or GC-MS, (3) synthesis and optimization of metabolic flux distribution (MFD), (4) modification of MFD by gene manipulation and by controlling culture environment, (5) metabolic control analysis (MCA), (6) design of metabolic regulation structure, and (7) identification of unknown pathways with isotope tracing by NMR. The main characteristics of metabolic engineering is to treat metabolism as a network or entirety instead of individual reactions. The applications were made for poly-3-hydroxybutyrate (PHB) production using Ralstonia eutropha and recombinant Escherichia coli, lactate production by recombinant Saccharomyces cerevisiae, pyruvate production by vitamin auxotrophic yeast Toluropsis glabrata, lysine production using Corynebacterium glutamicum, and energetic analysis of photosynthesic microorganisms such as Cyanobateria. The characteristics of each approach were reviewed with their applications. The approach based on isotope labeling experiments gives reliable and quantitative results for metabolic flux analysis. It should be recognized that the next stage should be toward the investigation of metabolic flux analysis with gene and protein expressions to uncover the metabolic regulation in relation to genetic modification and/ or the change in the culture condition.

Accurate Metabolic Flux Analysis through Data Reconciliation of Isotope Balance-Based Data

  • Kim Tae-Yong;Lee Sang-Yup
    • Journal of Microbiology and Biotechnology
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    • v.16 no.7
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    • pp.1139-1143
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    • 2006
  • Various techniques and strategies have been developed for the identification of intracellular metabolic conditions, and among them, isotope balance-based flux analysis with gas chromatography/mass spectrometry (GC/ MS) has recently become popular. Even though isotope balance-based flux analysis allows a more accurate estimation of intracellular fluxes, its application has been restricted to relatively small metabolic systems because of the limited number of measurable metabolites. In this paper, a strategy for incorporating isotope balance-based flux data obtained for a small network into metabolic flux analysis was examined as a feasible alternative allowing more accurate quantification of intracellular flux distribution in a large metabolic system. To impose GC/MS based data into a large metabolic network and obtain optimum flux distribution profile, data reconciliation procedure was applied. As a result, metabolic flux values of 308 intracellular reactions could be estimated from 29 GC/ MS based fluxes with higher accuracy.

Systems-Level Analysis of Genome-Scale In Silico Metabolic Models Using MetaFluxNet

  • Lee, Sang-Yup;Woo, Han-Min;Lee, Dong-Yup;Choi, Hyun-Seok;Kim, Tae-Yong;Yun, Hong-Seok
    • Biotechnology and Bioprocess Engineering:BBE
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    • v.10 no.5
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    • pp.425-431
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    • 2005
  • The systems-level analysis of microbes with myriad of heterologous data generated by omics technologies has been applied to improve our understanding of cellular function and physiology and consequently to enhance production of various bioproducts. At the heart of this revolution resides in silico genome-scale metabolic model, In order to fully exploit the power of genome-scale model, a systematic approach employing user-friendly software is required. Metabolic flux analysis of genome-scale metabolic network is becoming widely employed to quantify the flux distribution and validate model-driven hypotheses. Here we describe the development of an upgraded MetaFluxNet which allows (1) construction of metabolic models connected to metabolic databases, (2) calculation of fluxes by metabolic flux analysis, (3) comparative flux analysis with flux-profile visualization, (4) the use of metabolic flux analysis markup language to enable models to be exchanged efficiently, and (5) the exporting of data from constraints-based flux analysis into various formats. MetaFluxNet also allows cellular physiology to be predicted and strategies for strain improvement to be developed from genome-based information on flux distributions. This integrated software environment promises to enhance our understanding on metabolic network at a whole organism level and to establish novel strategies for improving the properties of organisms for various biotechnological applications.

Metabolic Rebalancing of CR6 Interaction Factor 1-Deficient Mouse Embryonic Fibroblasts: A Mass Spectrometry-Based Metabolic Analysis

  • Tadi, Surendar;Kim, Soung Jung;Ryu, Min Jeong;Park, Taeseong;Jeong, Ji-Seon;Kim, Young Hwan;Kweon, Gi Ryang;Shong, Minho;Yim, Yong-Hyeon
    • Bulletin of the Korean Chemical Society
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    • v.34 no.1
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    • pp.35-41
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    • 2013
  • Metabolic analysis of CR6 interacting factor 1 (Crif1) deficient mouse embryonic fibroblasts with impaired oxidative phosphorylation has been carried out using LC-MS/MS and GC-MS methods. Metabolic profiles of the Crif1 deficient cells were comprehensively obtained for the first time. Loss of oxidative phosphorylation functions in mitochondria resulted in cancer-like metabolic reprogramming with consumption of majority of glucose carbon from up-regulated glycolysis to produce lactate, suppressed utilization of glucose carbon in the TCA cycle, increased amounts of amino acids. The changes in metabolic profile of the Crif1 deficient cells are most probably a consequence of metabolic reprogramming to meet the needs of energy balance and anabolic precursors in compensation for the loss of major oxidative phosphorylation functions.

Influencing Factors for the Development of Metabolic Syndrome by the Number of Metabolic Syndrome Diagnostic Components in Korean Adolescents (청소년의 대사증후군 진단개수에 따른 영향요인 분석; 국민건강영양조사(2016) 자료 이용)

  • Oh, Hyunsook;Lee, Wonjae
    • The Journal of Korean Society for School & Community Health Education
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    • v.19 no.3
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    • pp.1-14
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    • 2018
  • Objectives: The purpose of this study was to investigate the prevalence of metabolic syndrome and to find related factors according to the number of metabolic syndrome diagnostic components in Korean adolescents. Methods: The subjects of this study were 469 Korean adolescents aged from 12 to 18 enrolled in the 2016 Korea National Health and Nutrition Examination Survey. Statistical package R 3.4.2 was used for programming to apply diagnostic criterion of adolescent metabolic syndrome and for the analysis of the data such as weighted frequent analysis, weighted mean analysis and complex sampling design logistic regression analysis. Results: For adolescents 12 to 18 years of age, 2.55% had more than 2(${\geq_-}3$), 9.88% had more than 1(${\geq_-}2$) and 33.17% had more than 0(${\geq_-}1$) metabolic syndrome diagnostic components. It has been found that risk factors for no less than 2 metabolic syndrome diagnostic components were higher body mass index and higher stress, and risk factors for no less than 1 were higher body mass index, younger teenager and female. Conclusion: Obesity is the primary risk factor for the development of adolescent metabolic syndrome. Female or younger teenager are more likely to have one or more metabolic syndrome diagnostic components, and higher stress develop to the risk level of having two or more metabolic syndrome diagnostic components. Therefore, it is important to focus on obesity and stress management for the prevention and control of Korean adolescent metabolic syndrome.

Resources for Systems Biology Research

  • Kim Jin-Sik;Yun Hong-Seok;Kim Hyun-Uk;Choi Hyung-Seok;Kim Tae-Yong;Woo Han-Min;Lee Sang-Yup
    • Journal of Microbiology and Biotechnology
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    • v.16 no.6
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    • pp.832-848
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    • 2006
  • Systems biology has recently become an important research paradigm that is anticipated to decipher the metabolic, regulatory, and signaling networks of complex living organisms on the whole organism level. Thus, various research outputs are being generated, along with the development of many tools and resources for systems biology research. Accordingly, this review provides a comprehensive summary of the current resources and tools for systems biology research that will hopefully be helpful to researchers involved in this field. The resources are categorized into the following five groups: genome information and analysis, transcriptome and proteome databases, metabolic profiling and metabolic control analysis, metabolic and regulatory information, and software for computational systems biology. A summary table and some future perspectives are also provided.

Prediction of Maximum Yields of Metabolites and Optimal Pathways for Their Production by Metabolic Flux Analysis

  • Hong, Soon-Ho;Moon, Soo-Yun;Lee, Sang-Yup
    • Journal of Microbiology and Biotechnology
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    • v.13 no.4
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    • pp.571-577
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    • 2003
  • The intracellular metabolic fluxes can be calculated by metabolic flux analysis, which uses a stoichiometric model for the intracellulal reactions along with mass balances around the intracellular metabolites. In this study, metabolic flux analyses were carried out to estimate flux distributions for the maximum in silico yields of various metabolites in Escherichia coli. The maximum in silico yields of acetic acid and lactic acid were identical to their theoretical yields. On the other hand, the in silico yields of succinic acid and ethanol were only 83% and 6.5% of their theoretical yields, respectively. The lower in silico yield of succinic acid was found to be due to the insufficient reducing power. but this lower yield could be increased to its theoretical yield by supplying more reducing power. The maximum theoretical yield of ethanol could be achieved, when a reaction catalyzed by pyruvate decarboxylase was added in the metabolic network. Futhermore, optimal metabolic pathways for the production of various metabolites could be proposed, based on the results of metabolic flux analyses. In the case of succinic acid production, it was found that the pyruvate carboxylation pathway should be used for its optimal production in E. coli rather than the phosphoenolpyruvate carboxylation pathway.

Metabolic Syndrome and Bone Mineral Density among Elderly Korean Women (여성 노인의 대사증후군과 골밀도의 관련성 조사연구)

  • Lee, Hae-Young;ChoiKwon, Smi
    • Journal of Korean Biological Nursing Science
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    • v.13 no.2
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    • pp.134-141
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    • 2011
  • Purpose: Although the risk factors of metabolic syndrome have been extensively studied, the association between osteoporosis and metabolic syndrome has remained unclear in Korean elderly women. Yet to be determined are the effect of risk factors of metabolic syndrome on osteoporosis in these subjects. The purpose of this study was to investigate how the risk factors of metabolic syndrome affect the bone mineral density in Korean elderly women. Methods: One hundred twenty one elderly women from a community center in Seoul elderly welfare center participated in this study. A structured questionnare was used to assess their demographics and lifestyles. Participants' anthropometric information was also obtained by measuring heights, weights, and waist circumferences. The blood samples were also obtained to measure blood glucoses and blood lipids. Bone mineral density was measured with the use of ultra sono. Results: The prevalence of metabolic syndrome in our subjects was 58%. In multivariate regression analysis, fasting plasma glucose level (p=.036) and triglycerides (p=.006) were significant factors predicting bone mineral density after adjusting age and other factors of metabolic syndrome. In age-adjusted analysis, women with metabolic syndrome had significantly higher bone mineral density as compared to those without metabolic syndrome (p=.026). Conclusion: Bone mineral density among elderly Korean women is associated with the level of blood glucose and triglycerides.

Relationships between Metabolic Syndrome Component and Depression, Stress

  • Shim, Moon-Jung;Kang, Yun-Jung
    • Korean Journal of Clinical Laboratory Science
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    • v.46 no.2
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    • pp.68-74
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    • 2014
  • The purpose of this study is to provide an academic basis regarding the necessity of managing depression and stress among metabolic syndrome patients by understanding 5 components of metabolic syndrome, perceived stress, and degree of depression, and by investigating their association using the national nutrition survey reference. This study was conducted by using mental health surveys and health screening test data of the 5th (2010~2012) primitive data of the national health and nutrition survey. A total of 19,599 respondents over 19 years of age were selected for the final analysis. The level of depression and stress was set as the dependent variable to identify its connection with 5 components of the metabolic syndrome. For the stress recognition, none of the metabolic syndrome components showed a significant correlation. For experiencing the depression symptom, the fasting glucose among the factors showed a significant correlation (p<0.05) among the metabolic syndrome factors. When it falls within the criteria of fasting glucose of metabolic syndrome, it has a great probability of falling under the group who experienced greater depression symptoms. As a result of the analysis by controlling cardiovascular and cerebrovascular disease which is tightly related with metabolic syndrome and depression, this study observed that glucose out of 5 metabolic syndrome components is related with depression.

In Silico Analysis of Lactic Acid Secretion Metabolism through the Top-down Approach: Effect of Grouping in Enzyme kinetics

  • Jin, Jong-Hwa;Lee, Jin-Won
    • Biotechnology and Bioprocess Engineering:BBE
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    • v.10 no.5
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    • pp.462-469
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    • 2005
  • A top-down approach is known to be a useful and effective technique for the design and analysis of metabolic systems. In this Study, we have constructed a grouped metabolic network for Lactococcus lactis under aerobic conditions using grouped enzyme kinetics. To test the usefulness of grouping work, a non-grouped system and grouped systems were compared quantitatively with each other. Here, grouped Systems were designed as two groups according to the extent of grouping. The overall simulated flux values in grouped and non-grouped models had pretty similar distribution trends, but the details on flux ratio at the pyruvate branch point showed a little difference. This result indicates that our grouping technique can be used as a good model for complicated metabolic networks, however, for detailed analysis of metabolic network, a more robust mechanism Should be considered. In addition to the data for the pyruvate branch point analysis, Some major flux control coefficients were obtained in this research.