• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.95-102
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• 2013

In metabolomics, metabolic pathway is represented by well-displayed graph. Metabolic pathways, especially, have a complex binding structure, which makes the graphical representation hard to visualize. There is a problem that edge crossings exponentially increase as the number of nodes grows. To apply automatic graph layout techniques to the genome-scale metabolic flow of metabolism domains, it is very important to reduce unnecessary edge crossing on a metabolic pathway layout. we proposed a metabolic pathway layout algorithm based on 2-layer layout. Our algorithm searches any meaningful component existing in a pathway, such as circular components, highly connected nodes, and the components are drawn in upper layer. Then the remaining subgraphs except meaningful components are drawn in lower layer by utilizing a new radial layout algorithm. It reduces ultimately reduced the number of edge crossings. This algorithm is the basis of flexible analysis for metabolic pathways.

• 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.

• Genomics & Informatics
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• v.12 no.4
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• pp.195-202
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• 2014

Metabolic syndrome (MetS) is a complex disorder related to insulin resistance, obesity, and inflammation. Genetic and environmental factors also contribute to the development of MetS, and through genome-wide association studies (GWASs), important susceptibility loci have been identified. However, GWASs focus more on individual single-nucleotide polymorphisms (SNPs), explaining only a small portion of genetic heritability. To overcome this limitation, pathway analyses are being applied to GWAS datasets. The aim of this study is to elucidate the biological pathways involved in the pathogenesis of MetS through pathway analysis. Cohort data from the Korea Associated Resource (KARE) was used for analysis, which include 8,842 individuals (age, $52.2{\pm}8.9years$ ; body mass index, $24.6{\pm}3.2kg/m^2$). A total of 312,121 autosomal SNPs were obtained after quality control. Pathway analysis was conducted using Meta-analysis Gene-Set Enrichment of Variant Associations (MAGENTA) to discover the biological pathways associated with MetS. In the discovery phase, SNPs from chromosome 12, including rs11066280, rs2074356, and rs12229654, were associated with MetS (p < $5{\times}10^{-6}$), and rs11066280 satisfied the Bonferroni-corrected cutoff (unadjusted p < $1.38{\times}10^{-7}$, Bonferroni-adjusted p < 0.05). Through pathway analysis, biological pathways, including electron carrier activity, signaling by platelet-derived growth factor (PDGF), the mitogen-activated protein kinase kinase kinase cascade, PDGF binding, peroxisome proliferator-activated receptor (PPAR) signaling, and DNA repair, were associated with MetS. Through pathway analysis of MetS, pathways related with PDGF, mitogen-activated protein kinase, and PPAR signaling, as well as nucleic acid binding, protein secretion, and DNA repair, were identified. Further studies will be needed to clarify the genetic pathogenesis leading to MetS.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.1
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• pp.91-98
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• 2005

In order to investigate central metabolic changes in Beijerinckia indica, cells were grown on different carbon sources and intracellular flux distributions were studied under varying concentrations of nitrogen. Metabolic fluxes were estimated by combining material balances with extracellular substrate uptake rate, biomass formation rate, and exopolysaccharide (EPS) accumulation rate. Thirty-one metabolic reactions and 30 intracellular metabolites were considered for the flux analysis. The results revealed that most of the carbon source was directed into the Entner-Doudoroff pathway, followed by the recycling of triose-3-phosphate back to Hexose­6-phosphate. The pentose phosphate pathway was operated at a minimal level to supply the precursors for biomass formation. The different metabolic behaviors under varying nitrogen concentrations were observed with flux analysis.

• Allergy, Asthma & Immunology Research
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• v.10 no.6
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• pp.628-647
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• 2018

Purpose: Obesity is associated with metabolic dysregulation, but the underlying metabolic signatures involving clinical and inflammatory profiles of obese asthma are largely unexplored. We aimed at identifying the metabolic signatures of obese asthma. Methods: Eligible subjects with obese (n = 11) and lean (n = 22) asthma underwent body composition and clinical assessment, sputum induction, and blood sampling. Sputum supernatant was assessed for interleukin $(IL)-1{\beta}$, -4, -5, -6, -13, and tumor necrosis factor $(TNF)-{\alpha}$, and serum was detected for leptin, adiponectin and C-reactive protein. Untargeted gas chromatography time-of-flight mass spectrometry (GC-TOF-MS)-based metabolic profiles in sputum, serum and peripheral blood monocular cells (PBMCs) were analyzed by orthogonal projections to latent structures-discriminate analysis (OPLS-DA) and pathway topology enrichment analysis. The differential metabolites were further validated by correlation analysis with body composition, and clinical and inflammatory profiles. Results: Body composition, asthma control, and the levels of $IL-1{\beta}$, -4, -13, leptin and adiponectin in obese asthmatics were significantly different from those in lean asthmatics. OPLS-DA analysis revealed 28 differential metabolites that distinguished obese from lean asthmatic subjects. The validation analysis identified 18 potential metabolic signatures (11 in sputum, 4 in serum and 2 in PBMCs) of obese asthmatics. Pathway topology enrichment analysis revealed that cyanoamino acid metabolism, caffeine metabolism, alanine, aspartate and glutamate metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, pentose phosphate pathway in sputum, and glyoxylate and dicarboxylate metabolism, glycerolipid metabolism and pentose phosphate pathway in serum are suggested to be significant pathways related to obese asthma. Conclusions: GC-TOF-MS-based metabolomics indicates obese asthma is characterized by a metabolic profile different from lean asthma. The potential metabolic signatures indicated novel immune-metabolic mechanisms in obese asthma with providing more phenotypic and therapeutic implications, which needs further replication and validation.

• Journal of the Korean Magnetic Resonance Society
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• v.22 no.3
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• pp.46-53
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• 2018

NMR-based metabolomics needs various knowledge to elucidate metabolic perturbation such as NMR experiments, NMR spectrum processing, raw data processing, metabolite identification, statistical analysis, and metabolic pathway analysis regarding technical aspects. Among them, some concepts of raw data processing and multivariate analysis are not easy to understand but are important to correctly interpret metabolic profile. This article introduces NMR spectrum processing, raw data processing, and multivariate analysis.

• Molecules and Cells
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• v.40 no.9
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• pp.685-695
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• 2017

Obesity and the metabolic disorders that constitute metabolic syndrome are a primary cause of morbidity and mortality in the world. Nonetheless, the changes in the proteins and the underlying molecular pathways involved in the relevant pathogenesis are poorly understood. In this study a proteomic analysis of the visceral adipose tissue isolated from metabolically healthy and unhealthy obese patients was used to identify presence of altered pathway(s) leading to metabolic dysfunction. Samples were obtained from 18 obese patients undergoing bariatric surgery and were subdivided into two groups based on the presence or absence of comorbidities as defined by the International Diabetes Federation. Two dimensional difference in-gel electrophoresis coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry was carried out. A total of 28 proteins were identified with a statistically significant difference in abundance and a 1.5-fold change (ANOVA, $p{\leq}0.05$) between the groups. 11 proteins showed increased abundance while 17 proteins were decreased in the metabolically unhealthy obese compared to the healthy obese. The differentially expressed proteins belonged broadly to three functional categories: (i) protein and lipid metabolism (ii) cytoskeleton and (iii) regulation of other metabolic processes. Network analysis by Ingenuity pathway analysis identified the $NF{\kappa}B$, IRK/MAPK and PKC as the nodes with the highest connections within the connectivity map. The top network pathway identified in our protein data set related to cellular movement, hematological system development and function, and immune cell trafficking. The VAT proteome between the two groups differed substantially between the groups which could potentially be the reason for metabolic dysfunction.

• 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 Journal of Microbiology
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• v.54 no.1
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• pp.46-52
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• 2018

Biodegradation pathway of dibenzofuran (DBF) of Novosphingobium pentaromativorans US6-1, a high-molecular-weight polycyclic aromatic hydrocarbons degrading strain, was investigated via analysis of metabolic intermediates and transcriptome. As a result, 3(2H)-benzofuranone, a basic skeleton of the metabolic intermediates produced by lateral dioxygenation process, was detected as an intermediate. RNA-Seq analysis confirmed that most of the expressed genes upon exposure to DBF were related to the lateral degradation pathway. Based on these results, the biodegradation pathway of DBF by N. pentaromativorans US6-1 was proposed.

• Journal of Microbiology and Biotechnology
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• v.31 no.4
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• pp.621-629
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• 2021

Shigella flexneri is a facultative intracellular pathogen that causes bacillary dysentery in humans. Infection with S. flexneri can result in more than a million deaths yearly and most of the victims are children in developing countries. Therefore, identifying novel and unique drug targets against this pathogen is instrumental to overcome the problem of drug resistance to the antibiotics given to patients as the current therapy. In this study, a comparative analysis of the metabolic pathways of the host and pathogen was performed to identify this pathogen's essential enzymes for the survival and propose potential drug targets. First, we extracted the metabolic pathways of the host, Homo sapiens, and pathogen, S. flexneri, from the KEGG database. Next, we manually compared the pathways to categorize those that were exclusive to the pathogen. Further, all enzymes for the 26 unique pathways were extracted and submitted to the Geptop tool to identify essential enzymes for further screening in determining the feasibility of the therapeutic targets that were predicted and analyzed using PPI network analysis, subcellular localization, druggability testing, gene ontology and epitope mapping. Using these various criteria, we narrowed it down to prioritize 5 novel drug targets against S. flexneri and one vaccine drug targets against all strains of Shigella. Hence, we suggest the identified enzymes as the best putative drug targets for the effective treatment of S. flexneri.