• BMB Reports
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• v.41 no.8
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• pp.609-614
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• 2008

The concentrations and catalytic activities of enzymes control metabolic rates. Previous studies have focused on enzyme concentrations because there are no genome-wide techniques used for the measurement of enzyme activity. We propose a method for evaluating the significance of enzyme activity by integrating metabolic network topologies and genome-wide microarray gene expression profiles. We quantified the enzymatic activity of reactions and report the 388 significant reactions in five perturbation datasets. For the 388 enzymatic reactions, we identified 70 that were significantly regulated (P-value < 0.001). Thirty-one of these reactions were part of anaerobic metabolism, 23 were part of low-pH aerobic metabolism, 8 were part of high-pH anaerobic metabolism, 3 were part of low-pH aerobic reactions, and 5 were part of high-pH anaerobic metabolism.

• 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.

• 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.

• Korean Chemical Engineering Research
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• v.51 no.2
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• pp.226-232
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• 2013

To produce biobutanol, fermentation processes using clostridia that mainly produce acetone, butanol and ethanol are used. In this work, a dynamic model describing the metabolic reactions in an acetone-butanol-ethanol (ABE)-producing clostridium, Clostridium acetobutylicum ATCC824, was proposed. To estimate the 58 kinetic parameters of the metabolic network model with experimental data obtained from a batch fermentor, we used an efficient optimization method combining a genetic algorithm and the Levenberg-Marquardt method because of the complexity of the metabolism of the clostridium. For the verification of the determined parameters, the developed metabolic model was evaluated by experiments where genetically modified clostridium was used and the initial concentration of glucose was changed. Consequently, we found that the developed kinetic model for the metabolic network was considered to describe the dynamic metabolic state of the clostridium sufficiently. Thus, this dynamic model for the metabolic reactions will contribute to designing the clostridium as well as the fermentor for higher productivity.

• Journal of Microbiology and Biotechnology
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• v.33 no.10
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• pp.1351-1360
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• 2023

Endocrine-disrupting chemicals (EDCs) are compounds that disturb hormonal homeostasis by binding to receptors. EDCs are metabolized through hepatic enzymes, causing altered transcriptional activities of hormone receptors, and thus necessitating the exploration of the potential endocrine-disrupting activities of EDC-derived metabolites. Accordingly, we have developed an integrative workflow for evaluating the post-metabolic activity of potential hazardous compounds. The system facilitates the identification of metabolites that exert hormonal disruption through the integrative application of an MS/MS similarity network and predictive biotransformation based on known hepatic enzymatic reactions. As proof-of-concept, the transcriptional activities of 13 chemicals were evaluated by applying the in vitro metabolic module (S9 fraction). Identified among the tested chemicals were three thyroid hormone receptor (THR) agonistic compounds that showed increased transcriptional activities after phase I+II reactions (T3, 309.1 ± 17.3%; DITPA, 30.7 ± 1.8%; GC-1, 160.6 ± 8.6% to the corresponding parents). The metabolic profiles of these three compounds showed common biotransformation patterns, particularly in the phase II reactions (glucuronide conjugation, sulfation, GSH conjugation, and amino acid conjugation). Data-dependent exploration based on molecular network analysis of T3 profiles revealed that lipids and lipid-like molecules were the most enriched biotransformants. The subsequent subnetwork analysis proposed 14 additional features, including T4 in addition to 9 metabolized compounds that were annotated by prediction system based on possible hepatic enzymatic reaction. The other 10 THR agonistic negative compounds showed unique biotransformation patterns according to structural commonality, which corresponded to previous in vivo studies. Our evaluation system demonstrated highly predictive and accurate performance in determining the potential thyroid-disrupting activity of EDC-derived metabolites and for proposing novel biotransformants.

• Toxicological Research
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• v.23 no.3
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• pp.189-196
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• 2007

Cytochrome P450 (P450) enzymes are the major catalysts involved in the biotransformation of various drugs, pollutants, carcinogens, and many endogenous compounds. Most of chemical carcinogens are not active by themselves but they require metabolic activation. P450 isozymes playa pivotal role in the metabolic activation. The activation of arylamines and heterocyclic arylamines (HAAs) involves critical N-hydroxylation, usually by P450. CYP1A2 plays an important role in these reactions. Broad exposure to many of these compounds might cause carcinogenicity in animals and humans. On the other hand, P450s can be also involved in the bioactivation of other chemicals including alcohols, aflatoxin B1, acetaminophen, and trichloroethylene, both in humans and in experimental animals. Understanding the P450 metabolic activation of many chemicals is necessary to develop rational strategies for prevention of their toxicities in human health. An important part is the issues of extrapolation between species in predicting risks and variation of P450 enzyme activities in humans.

• Korean Journal of Environmental Agriculture
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• v.15 no.2
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• pp.246-261
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• 1996

Organophosphorus pesticides, which are an important part of synthetic pesticides in current use contain sulfur atom in their molecules and can be activated or detoxified by environmental and/or biological metabolism. Among the related metabolic reactions, oxidative processes are particularly important with their final products and the study on the reactive intermediates formed in those reactions is essential to elucidate the metabolic pathways and mechanisms and to understand the toxicological properties. This review dealt with the reactive intermediates formed in various reactions from the structural and mechanistic point of view for organophosphorus pesticides and related compounds.

• Proceedings of the Korean Society of Applied Pharmacology
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• 1994.11a
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• pp.135-140
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• 1994

Over past decades, numerous in vitro model has been developed to investigate drug metabolism. In the order of complexity we found the isolated perfused liver, hepatocytes in co-culture with epithelial cells, hepatocytes in suspension and in primary culture and subcellular hepatic microsomal fractions. Because they can be easily prepared from both animals (pharmacological and toxicological species) and humans (whole livers as well as biopsies obtained during surgery) hepatocytes in primary culture provide the most powerful model to better elucidate drug behavior at an early stage of preclinical development such as : 1. the characterization of main biotransformation reactions. 2. the identification of phase I and phase II isozymes involved in such reactions 3. the evaluation of interspecies differences allowing the selection of a second toxicological animal species more closely related to man on the basis of metabolic profiles 4. the detection of the inducing and/or inhibitory effects of a drug on metabolic enzymes, the prediction of drug interactions 5. the estimation of inter-individual variability in biotransformation reactions. The use of hepatocytes, and in particular those obstained from humans, at an early stage of drug development allows the obtention of more predictive preclinical data and a better knowledge of drug behavior in humans before the first administration of the drug in healthy volunteers.

• KSBB Journal
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• v.24 no.3
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• pp.287-290
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• 2009

Metabolic network is composed of more than thousands of metabolic reactions. Therefore, understanding of metabolic behavior of microorganisms is required to engineer metabolism of microorganisms. In this paper, we employed ARACNE (Algorithm for the Reconstruction of Accurate Cellular Networks) to quantify relationships among metabolic subpathways. The results showed that ARACNE analysis can give new insight into the study of bacterial metabolism.

• 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.