• Bulletin of the Korean Chemical Society
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• v.33 no.12
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• pp.4041-4046
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• 2012

The recombinant expression of proteins has been the method of choice to meet the demands from proteomics and structural genomics studies. Despite its successful production of many heterologous proteins, Escherichia coli failed to produce many other proteins in their native forms. This may be related to the fact that the stresses resulting from the overproduction interfere with cellular processes. To better understand the physiological change during the overproduction phase, we profiled the metabolites along the time course of the recombinant protein expression. We identified 32 metabolites collected from different time points in the protein production phase. The stress induced by protein production can be characterized by (A) the increased usage of aspartic acid, choline, glycerol, and N-acetyllysine; and (B) the accumulation of adenosine, alanine, oxidized glutathione, glycine, N-acetylputrescine, and uracil. We envision that this work can be used to create a strategy for the production of usable proteins in large quantities.

• Proceedings of the Microbiological Society of Korea Conference
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• 2005.05a
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• pp.212.1-212
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• 2005

• Journal of Microbiology and Biotechnology
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• v.11 no.6
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• pp.907-914
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• 2001

A whole genome analysis for monitoring specific changes in gene expression, using microarrays or proteome profiling of the same, are the two tools that have already revolutionized current approaches for studying disease. These methods are particularly important in cancer research as there are many overexpressed genes, and their products remain uncharacterized. This article presents a general overview of these technologies and their applications for studying cancer.

• 대한생식의학회:학술대회논문집
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• 2004.06a
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• pp.88-89
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• 2004

• The Korea Genome Conference
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• 2002.08a
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• pp.42.2-42.2
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• 2002

• Molecules and Cells
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• v.26 no.2
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• pp.121-130
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• 2008

Methamphetamine, a commonly used addictive drug, is a powerful addictive stimulant that dramatically affects the CNS. Repeated METH administration leads to a rewarding effect in a state of addiction that includes sensitization, dependence, and other phenomena. It is well known that susceptibility to the development of addiction is influenced by sources of reinforcement, variable neuroadaptive mechanisms, and neurochemical changes that together lead to altered homeostasis of the brain reward system. These behavioral abnormalities reflect neuroadaptive changes in signal transduction function and cellular gene expression produced by repeated drug exposure. To provide a better understanding of addiction and the mechanism of the rewarding effect, it is important to identify related genes. In the present study, we performed gene expression profiling using microarray analysis in a reward effect animal model. We also investigated gene expression in four important regions of the brain, the nucleus accumbens, striatum, hippocampus, and cingulated cortex, and analyzed the data by two clustering methods. Genes related to signaling pathways including G-protein-coupled receptor-related pathways predominated among the identified genes. The genes identified in our study may contribute to the development of a gene modeling network for methamphetamine addiction.

• The Journal of Korean Academy of Prosthodontics
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• v.43 no.3
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• pp.393-408
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• 2005

Statement of problem. In the process of bone formation, titanium (Ti) surface roughness is an important factor modulating osteoblastic function. Purpose. This study was carried out to determine the effect of different Ti surface on biologic responses of a human osteoblast-like cell line (MG63). Materials and methods. MG63 cells were cultured on S (smooth), SLA (sandblasted largegrit & acid etching), HA (hydroxyapatite) Ti. The morphology and attachment of the cells were examined by SEM. The cDNAs prepared from total RNAs of MG63 were hybridized to a human cDNA microarray (1,152 elements). Results. The appearances of the surfaces observed with SEM were different in the three types of dental substrates. The surface of SLA and HA were shown to be rougher than S. MG63 cells cultured on SLA and HA were cell-matrix interaction. In the expression of genes involved in osseointegration, upregulated genes were bone morphogenetic protein, Villin, Integrin, Insulin-like growth factors in different surfaces. Downregulated genes were fibroblast growth factor receptor 4, Bcl 2-related protein, collagen, CD4 in different surfaces. Conclusion. The attachment and expression of key osteogenic regulatory genes were enhanced by surface roughness of the dental materials.

• Reproductive and Developmental Biology
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• v.37 no.1
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• pp.1-8
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• 2013

In order to investigate genetic stability and gene expression profile after cloning procedure, two groups of cloned pigs were used for swine leukocyte antigen (SLA) gene nucleotide alteration and microarray analyses. Each group was consist of cloned pigs derived from same cell line (n=3 and 4, respectively). Six SLA loci were analyzed for cDNA sequences and protein translations. In total, 16 SLA alleles were identified and there were no evidence of SLA nucleotide alteration. All SLA sequences and protein translations were identical among the each pig in the same group. On the other hand, microarray assay was performed for profiling gene expression of the cloned pigs. In total, 43,603 genes were analyzed and 2,150~4,300 reliably hybridized spots on the each chip were selected for further analysis. Even though the cloned pigs in the same group had identical genetic background, 18.6~47.3% of analyzed genes were differentially expressed in between each cloned pigs. Furthermore, on gene clustering analysis, some cloned pigs showed abnormal physiological phenotypes such as inflammation, cancer or cardiomyopathy. We assumed that individual environmental adaption, sociality and rank in the pen might have induced these different phenotypes. In conclusion, the results of the present study indicate that SLA locus genes appear to be stable following SCNT. However, gene expressions and phenotypes between cloned pigs derived from the same cell line were not identical even under the same rearing conditions.

• Molecules and Cells
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• v.21 no.3
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• pp.343-355
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• 2006

Stem cells are unique cell populations with the ability to undergo both self-renewal and differentiation, although a wide variety of adult stem cells as well as embryonic stem cells have been identified and stem cell plasticity has recently been reported. To identify genes implicated in the control of the stem cell state as well as the characteristics of each stem cell line, we analyzed the expression profiles of genes in human embryonic, hematopoietic ($CD34^+$ and $CD133^+$), and mesenchymal stem cells using cDNA microarrays, and identified genes that were differentially expressed in specific stem cell populations. In particular we were able to identify potential hESC signature-like genes that encode transcription factors (TFAP2C and MYCN), an RNA binding protein (IMP-3), and a functionally uncharacterized protein (MAGEA4). The overlapping sets of 22 up-regulated and 141 down-regulated genes identified in this study of three human stem cell types may also provide insight into the developmental mechanisms common to all human stem cells. Furthermore, our comprehensive analyses of gene expression profiles in various adult stem cells may help to identify the genetic pathways involved in self-renewal as well as in multi-lineage specific differentiation.

• Genomics & Informatics
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• v.4 no.3
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• pp.97-102
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• 2006

In acute leukemia patients, several successful methods of expression profiling have been used for various purposes, i.e., to identify new disease class, to select a therapeutic target, or to predict chemo-sensitivity and clinical outcome. In the present study, we tested the peripheral blood of 47 acute leukemia patients in an attempt to identify differentially expressed genes in AML and ALL using a Korean-made 10K oligo-nucleotide microarray. Methods: Total RNA was prepared from peripheral blood and amplified for microarray experimentation. SAM (significant analysis of microarray) and PAM (prediction analysis of microarray) were used to select significant genes. The selected genes were tested for in a test group, independently of the training group. Results: We identified 345 differentially expressed genes that differentiated AML and ALL patients (FWER<0.05). Genes were selected using the training group (n=35) and tested for in the test group (n=12). Both training group and test group discriminated AML and ALL patients accurately. Genes that showed relatively high expression in AML patients were deoxynucleotidyl transferase, pre-B lymphocyte gene 3, B-cell linker, CD9 antigen, lymphoid enhancer-binding factor 1, CD79B antigen, and early B-cell factor. Genes highly expressed in ALL patients were annexin A 1, amyloid beta (A4) precursor protein, amyloid beta (A4) precursor-like protein 2, cathepsin C, lysozyme (renal amyloidosis), myeloperoxidase, and hematopoietic prostaglandin D2 synthase. Conclusion: This study provided genome wide molecular signatures of Korean acute leukemia patients, which clearly identify AML and ALL. Given with other reported signatures, these molecular signatures provide a means of achieving a molecular diagnosis in Korean acute leukemia patents.