• Korean Journal of Poultry Science
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• v.37 no.3
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• pp.275-282
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• 2010

Chicken is an important livestock as a valuable biomedical model as well as food for human, and there is a strong rationale for improving our understanding on metabolism and physiology of this organism. The first draft of chicken genome assembly was released in 2004, which enables elaboration on the linkage between genetic and metabolic traits of chicken. The objectives of this study were thus to reconstruct metabolic pathway of the chicken genome and to construct a chicken specific pathway genome database (PGDB). We developed a comprehensive genome database for chicken by integrating all the known annotations for chicken genes and proteins using a pipeline written in Perl. Based on the comprehensive genome annotations, metabolic pathways of the chicken genome were reconstructed using the PathoLogic algorithm in Pathway Tools software. We identified a total of 212 metabolic pathways, 2,709 enzymes, 71 transporters, 1,698 enzymatic reactions, 8 transport reactions, and 1,360 compounds in the current chicken genome build, Gallus_gallus-2.1. Comparative metabolic analysis with the human, mouse and cattle genomes revealed that core metabolic pathways are highly conserved in the chicken genome. It was indicated the quality of assembly and annotations of the chicken genome need to be improved and more researches are required for improving our understanding on function of genes and metabolic pathways of avian species. We conclude that the chicken PGDB is useful for studies on avian and chicken metabolism and provides a platform for comparative genomic and metabolic analysis of animal biology and biomedicine.

• Proceedings of the Korean Society of Toxicology Conference
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• 2001.10a
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• pp.199-199
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• 2001

Both hypoxia and insulin induce same target genes including vascular endothelial growth factor (VEGF), glycolitic enzymes and glucose transporters. However these two signals eventually trigger quite different metabolic pathways. Hypoxia induces glycolysis for anaerobic ATP production, while insulin increase glycolysis for lipogenesis and energy storage. Hypoxia-induced gene expression is mediated by Hypoxia-inducible Factorl (HIF-1) that consists of HIF-1 $\alpha$ and $\beta$ subunit.(omitted)

• The Korean Journal of Physiology and Pharmacology
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• v.9 no.5
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• pp.299-304
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• 2005

Cardiac hypertrophy contributes an increased risk to major cerebrovascular events. However, the molecular mechanisms underlying cerebrovascular dysfunction during cardiac hypertrophy have not yet been characterized. In the present study, we examined the molecular mechanism of isoproterenol (ISO)-evoked activation of Ras/Raf/MAPK pathways as well as PKA activity in cerebral artery of rabbits, and we also studied whether the activations of these signaling pathways were altered in cerebral artery, during ISO-induced cardiac hypertrophy compared to heart itself. The results show that the mRNA level of c-fos (not c-jun and c-myc) in heart and these genes in cerebral artery were considerably increased during cardiac hypertrophy. These results that the PKA activity and activations of Ras/Raf/ERK cascade as well as c-fos expression in rabbit heart during cardiac hypertrophy were consistent with previous reports. Interestingly, however, we also showed a novel finding that the decreased PKA activity might have differential effects on Ras and Raf expression in cerebral artery during cardiac hypertrophy. In conclusion, there are differences in molecular mechanisms between heart and cerebral artery during cardiac hypertrophy when stimulated with β2 adrenoreceptor (AR), suggesting a possible mechanism underlying cerebrovascular dysfunction during cardiac hypertrophy.

• Journal of Microbiology and Biotechnology
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• v.15 no.1
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• pp.161-174
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• 2005

Abstract Glycolysis has a main function to provide ATP and precursor metabolites for biomass production. Although glycolysis is one of the most important pathways in cellular metabolism, the details of its regulation mechanism and regulating chemicals are not well known yet. The regulation of the glycolytic pathway is very robust to allow for large fluxes at almost constant metabolite levels in spite of changing environmental conditions and many reaction effectors like inhibitors, activating compounds, cofactors, and related metal ions. These changing environmental conditions and metabolic reaction effectors were focused on to understand their roles in the metabolic networks. In this study, we have investigated for construction of the regulatory map of the glycolytic metabolic network and tried to collect all the effectors as much as possible which might affect the glycolysis metabolic pathway. Using the results of this study, it is expected that a complex metabolic situation can be more precisely analyzed and simulated by using available programs and appropriate kinetic data.

• Genomics & Informatics
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• v.6 no.2
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• pp.68-71
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• 2008

The static approach of representing metabolic pathway diagrams offers no flexibility. Thus, many systems adopt automatic graph layout techniques to visualize the topological architecture of pathways. There are weaknesses, however, because automatically drawn figures are generally difficult to understand. The problem becomes even more serious when we attempt to visualize all of the information in a single, big picture, which usually results in a confusing diagram. To provide a partial solution to this thorny issue, we propose J2dpathway, a metabolic pathway atlas viewer that has node-abstracting features.

• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2005.06a
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• pp.233-244
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• 2005

Guanosine fermentation process can be well predicted and analyzed by the proposed state equations describing the dynamic change of a bioreactor. Pyruvate and alanine were found to be characteristically accumulated along with the decline of the guanosine formation rate during the mid-late phase of the process. The enzymological study of the main pathways in glucose catabolism and the quantitative stoichiometric calculation of metabolic flux distribution revealed that it was entirely attributed to the shift of metabolic flux from hexose monophosphate (HMP) pathway to glycolysis pathway. The process optimization by focusing on the restore of the shift of metabolic flux was conducted and the overcoming the decrease of oxygen uptake rate (OUR) was taken as the relevant factor of the trans-scale operation. As a result, the production of guanosinewas increased from 17 g/L to over 34 g/I.

• Genomics & Informatics
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• v.2 no.4
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• pp.191-194
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• 2004

Exponentially increasing biopathway data in recent years provide us with means to elucidate the large-scale modular organization of the cell. Given the existing information on metabolic and regulatory networks, inferring biopathway information through scientific reasoning or data mining of large scale array data or proteomics data get great attention. Naturally, there is a need for a user-friendly system allowing the user to combine large and diverse pathway data sets from different resources. We built a data warehouse - BIOWAY - for analyzing and visualizing biological pathways, by integrating and customizing resources. We have collected many different types of data in regards to pathway information, including metabolic pathway data from KEGG/LIGAND, signaling pathway data from BIND, and protein information data from SWISS-PROT. In addition to providing general data retrieval mechanism, a successful user interface should provide convenient visualization mechanism since biological pathway data is difficult to conceptualize without graphical representations. Still, the visual interface in the previous systems, at best, uses static images only for the specific categorized pathways. Thus, it is difficult to cope with more complex pathways. In the BIOWAY system, all the pathway data can be displayed in computer generated graphical networks, rather than manually drawn image data. Furthermore, it is designed in such a way that all the pathway maps can be expanded or shrinked, by introducing the concept of super node. A subtle graphic layout algorithm has been applied to best display the pathway data.

• Asian-Australasian Journal of Animal Sciences
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• v.22 no.6
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• pp.871-884
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• 2009

Gene expression profiling is a useful tool for identifying critical genes and pathways in metabolism. The objective of this study was to determine the major differences in the expression of genes associated with metabolism and metabolic regulation in liver and mammary tissues of lactating cows. We used the Michigan State University bovine metabolism (BMET) microarray; previously, we have designed a bovine metabolism-focused microarray containing known genes of metabolic interest using publicly available genomic internet database resources. This is a high-density array of 70mer oligonucleotides representing 2,349 bovine genes. The expression of 922 genes was different at p<0.05, and 398 genes (17%) were differentially expressed by two-fold or more with 222 higher in liver and 176 higher in mammary tissue. Gene ontology categories with a high percentage of genes more highly expressed in liver than mammary tissues included carbohydrate metabolism (glycolysis, glucoenogenesis, propanoate metabolism, butanoate metabolism, electron carrier and donor activity), lipid metabolism (fatty acid oxidation, chylomicron/lipid transport, bile acid metabolism, cholesterol metabolism, steroid metabolism, ketone body formation), and amino acid/nitrogen metabolism (amino acid biosynthetic process, amino acid catabolic process, urea cycle, and glutathione metabolic process). Categories with more genes highly expressed in mammary than liver tissue included amino acid and sugar transporters and MAPK, Wnt, and JAK-STAT signaling pathways. Real-time PCR analysis showed consistent results with those of microarray analysis for all 12 genes tested. In conclusion, microarray analyses clearly identified differential gene expression profiles between hepatic and mammary tissues that are consistent with the differences in metabolism of these two tissues. This study enables understanding of the molecular basis of metabolic adaptation of the liver and mammary gland during lactation in bovine species.

• Journal of Environmental Analysis, Health and Toxicology
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• v.21 no.4
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• pp.243-251
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• 2018

Pharmaceuticals in wastewater effluents have been recognized as emerging pollutants threatening freshwater organisms. To extend understanding for bioaccumulation and toxicity in those organisms, information on biotransformation products (or metabolites) and their metabolic pathway are crucial. The aim of the present study is to identify and elucidate metabolites of pharmaceuticals formed in exposed organisms using suspect and nontarget screening approach using LC-HRMS. As the target pharmaceuticals, carbamazepine, ketoprofen, metoprolol, propranolol, and verapamil were selected whereas Daphnia magna and Gammarus pulex were used as test organisms. After 24h exposure, metabolites formed in the organisms were identified using LC-HRMS. The structures of metabolites were elucidated via analysis of MS/MS fragment pattern and the comparison with fragment database. As the results, a total of 10 metabolites were identified for 5 parent compounds (C253/C356 for carbamazepine, K211 for ketoprofen, M256 for metoprolol, P218/P276/P306 for propranolol, V196/V291/V441 for verapamil). Among them, the presence of C253 and V291 was confirmed using standard materials. Most of the identified metabolites were formed through oxidative reactions such as hydroxylation, N-demethylation, and dealkylation. Cysteine conjugation (phase II reaction) metabolite (C356) for carbamazepine was found in daphnia. The metabolic pathway of verapamil showed similar metabolic pathways and metabolic pathways for both species. Although the toxicological information on the identified metabolites could not be confirmed, the molecular structure information of the proposed metabolites can be used for future evaluation and prediction of toxicity.

• Biotechnology and Bioprocess Engineering:BBE
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• v.9 no.4
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• pp.252-255
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• 2004

A pfl ldhA double mutant Escherichia coli strain NZN 111 was used to produce succinic acid by overexpressing the E. coli malic enzyme gene (sfcA). This strain, however, produced a large amount of malic acid as well as succinic acid. After the analyses of the metabolic pathways, the fumB gene encoding the anaerobic fumarase of E. coli was co-amplified to solve the problem of malic acid accumulation. A plasmid, pTrcMLFu, was constructed, which contains an artificial operon (sfcA-fumB) under the control of the inducible trc promoter. From the batch culture of recombinant E. coli NZN 111 harboring pTrcMLFu, 7 g/L of succinic acid was produced from 20 g/L of glucose, with no accumulation of malic acid. From the metabolic flux analysis the strain was found under reducing power limiting conditions by severe reorientation of metabolic fluxes.