• Title/Summary/Keyword: metabolic engineering

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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.

Review of Current Approaches for Implementing Metabolic Reconstruction

  • Kim, Do-Gyun;Seo, Sung-Won;Cho, Byoung-Kwan;Lohumi, Santosh;Hong, Soon-jung;Lee, Wang-Hee
    • Journal of Biosystems Engineering
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    • v.43 no.1
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    • pp.45-58
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    • 2018
  • Background: Metabolic modeling has been an essential tool in metabolic reconstruction, which has dramatically advanced in the last decades as a part of systems biology. At present, the protocol for metabolic reconstruction has been systematically established, and it provides the basis for the analysis of complex systems, which has been limited in the past. Therefore, metabolic reconstruction can be adapted to analyze agricultural systems whose metabolic data has been accumulated recently. Purpose: The aim of this review is to suggest the suitability of metabolic modeling for understanding agricultural metabolic data and to encourage the potential use of this modeling in the field of agriculture. Review: We reviewed the procedure of metabolic reconstruction using computational modeling with applicable strategies and software tools. Additionally, we presented the initial attempts of metabolic reconstruction in the field of agriculture and proposed further applications.

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.

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.

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.

Effect of carbon substrate on the intracellular fluxes in succinic acid producing Escherichia coli.

  • Hong, Soon-Ho;Lee, Dong-Yup;Kim, Tae-Yong;Lee, Sang-Yup;Park, Sun-Won
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2003.10a
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    • pp.251-257
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    • 2003
  • Metabolic engineering has become a new paradigm for the more efficient production of desired bioproducts. Metabolic engineering can be defined as directed modification of cellular metabolism and properties through the introduction, deletion, and modification of metabolic pathways by using recombinant DNA and other molecular biological tools. During the last decade, metabolic flux analysis(MFA) has become an essential tool fur metabolic engineering. By MFA, the intracellular metabolic fluxes can be quantified by the measurement of extracellular metabolite concentrations in combination with the stoichiometry of intracellular reactions and mass balances. The usefulness and functionality of MFA are demonstrated by applying to metabolic pathways in E. coli. First, a large-scale in silico E. coli model is constructed, and then the effects of carbon sources on intracellular flux distributions and succinic acid production were investigated on the basis of the uptake and secretion rates of the relevant metabolites. The results indicated that succinic acid yields increased in order of gluconate, glucose and sorbitol. Acetic acid and lactic acid were produced as major products rather than when gluconate and glucose were used carbon sources. The results indicated that among three carbon sources available, the most reduced substrate is sorbitol which yields efficient succinic acid production.

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