• Korean Journal of Microbiology
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• v.30 no.5
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• pp.347-354
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• 1992

New regulatory, loci which participate in the regulation of anaerobic inducible gene expression in Salmonella typhimurium were identified. We observed the regulatory network of new regulator mutations to various anaerobic inducible gene (1). Some anaerobic inducible lac fusions were also induced at low pH condition which was severe environment to withstand for its virulence at the place like phagolysosome. Sic oxygen-regulated regulatory mutants (oxr) isolated by Tn10 mutagenesis were divided into two groups. Five of them were found to show negative effect on the regulation of anaerobic gene expression, while on e showed positive effect on the regulation. Genetic loci of four oxr were identified with 54 Mud-P22 lysogens covering the whole chromosome of S. typhimurium, in the nearby region of map unit 87 min (oxr101), 63 min (oxr104), 97 min (oxr 105), and 57 min (oxr 106), respectively. Two oxr mutants were subjected to two-dimensional polyacrylamide electrophoretic analysis of anaerobic inducible proteins for searching the control circuitry of our oxr mutants.

• 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.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6347-6350
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• 2013

Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2003.10a
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• pp.29-29
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• 2003

Incompatible plant-pathogen interactions result in the rapid cell death response known as hypersensitive response (HR) and activation of host defense-related genes. To understand the molecular and cellular mechanism controlling defense response better, several approaches including isolation and characterization of novel genes, promoter analysis of those genes, protein-protein interaction analysis and reverse genetic approach etc. By using the yeast two-hybrid system a clone named Tsipl, Tsil -interacting protein 1, was isolated whose translation product apparently interacted with Tsil, an EREBP/AP2 type DNA binding protein. RNA gel blot analysis showed that the expression of Tsipl was increased by treatment with NaCl, ethylene, salicylic acid, or gibberellic acid. Transient expression analysis using a Tsipl::smGFP fusion gene in Arabidopsis protoplasts indicated that the Tsipl protein was targeted to the outer surface of chloroplasts. The targeted Tsipl::smGFP proteins were diffused to the cytoplasm of protoplasts in the presence of salicylic acid (SA) The PEG-mediated co-transfection analysis showed that Tsipl could interact with Tsil in the nucleus. These results suggest that Tsipl-Tsil interaction might serve to regulate defense-related gene expression. Basically the useful promoters are valuable tools for effective control of gene expression related to various developmental and environmental condition.(중략)

• Genomics & Informatics
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• v.10 no.3
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• pp.153-166
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• 2012

A variety of ligands differ in their capacity to bind the receptor, elicit gene expression, and modulate physiological responses. Such receptors include Toll-like receptors (TLRs), which recognize various patterns of pathogens and lead to primary innate immune activation against invaders, and G-protein coupled receptors (GPCRs), whose interaction with their cognate ligands activates heterotrimeric G proteins and regulates specific downstream effectors, including immuno-stimulating molecules. Once TLRs are activated, they lead to the expression of hundreds of genes together and bridge the arm of innate and adaptive immune responses. We characterized the gene expression profile of Toll-like receptor 4 (TLR4) in RAW 264.7 cells when it bound with its ligand, 2-keto-3-deoxyoctonate (KDO), the active part of lipopolysaccharide. In addition, to determine the network communications among the TLR, Janus kinase (JAK)/signal transducer and activator of transcription (STAT), and GPCR, we tested RAW 264.7 cells with KDO, interferon-${\beta}$, or cAMP analog 8-Br. The ligands were also administered as a pair of double and triple combinations.

• IMMUNE NETWORK
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• v.11 no.4
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• pp.203-209
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• 2011

Background: T cell immunoglobulin mucin containing molecule (TIM)-3 is expressed in differentiated Th1 cells and is involved in the suppression of the cytokine production by these cells. However, the regulation of the expression of other T cell genes by TIM-3 is unclear. Herein, we attempted to identify differentially expressed genes in cells abundantly expressing TIM-3 compared to cells with low expression of TIM-3. Methods: TIM-3 overexpressing cell clones were established by transfection of Jurkat T cells with TIM-3 expression vector. For screening of differentially expressed genes, gene fishing technology based on reverse transcription-polymerase chain reaction (RT-PCR) using an annealing control primer system was used. The selected candidate genes were validated by semi quantitative and real-time RT-PCR. Results: The transcription of TIMP-1, IFITM1, PAR3 and CCL1 was different between TIM-3 overexpressing cells and control cells. However, only CCL1 transcription was significantly different in cells transiently transfected with TIM3 expression vector compared with control cells. CCL1 transcription was increased in primary human $CD4^+$ T cells abundantly expressing TIM-3 but not in cells with low expression of TIM-3. Conclusion: CCL1 was identified as a differentially transcribed gene in TIM-3-expressing $CD4^+$ T cells.

• Biomolecules & Therapeutics
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• v.26 no.3
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• pp.290-297
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• 2018

We aimed to understand the molecular changes in host cells that accompany infection by the seasonal influenza A H1N1 virus because the initial response rapidly changes owing to the fact that the virus has a robust initial propagation phase. Human epithelial alveolar A549 cells were infected and total RNA was extracted at 30 min, 1 h, 2 h, 4 h, 8 h, 24 h, and 48 h post infection (h.p.i.). The differentially expressed host genes were clustered into two distinct sets of genes as the infection progressed over time. The patterns of expression were significantly different at the early stages of infection. One of the responses showed roles similar to those associated with the enrichment gene sets to known 'gp120 pathway in HIV.' This gene set contains genes known to play roles in preventing the progress of apoptosis, which infected cells undergo as a response to viral infection. The other gene set showed enrichment of 'Drug Metabolism Enzymes (DMEs).' The identification of two distinct gene sets indicates that the virus regulates the cell's mechanisms to create a favorable environment for its stable replication and protection of gene metabolites within 8 h.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.10
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• pp.4251-4256
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• 2015

Background: Exposure to cigarette may affect human health and increase risk of a wide range of diseases including pulmonary diseases, such as chronic obstructive pulmonary disease (COPD), asthma, lung fibrosis and lung cancer. However, the molecular mechanisms of pathogenesis induced by cigarettes still remain obscure even with extensive studies. With systemic view, we attempted to identify the specific gene modules that might relate to injury caused by cigarette smoke and identify hub genes for potential therapeutic targets or biomarkers from specific gene modules. Materials and Methods: The dataset GSE18344 was downloaded from the Gene Expression Omnibus (GEO) and divided into mouse cigarette smoke exposure and control groups. Subsequently, weighted gene co-expression network analysis (WGCNA) was used to construct a gene co-expression network for each group and detected specific gene modules of cigarette smoke exposure by comparison. Results: A total of ten specific gene modules were identified only in the cigarette smoke exposure group but not in the control group. Seven hub genes were identified as well, including Fip1l1, Anp32a, Acsl4, Evl, Sdc1, Arap3 and Cd52. Conclusions: Specific gene modules may provide better understanding of molecular mechanisms, and hub genes are potential candidates of therapeutic targets that may possible improve development of novel treatment approaches.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4607-4611
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• 2012

Objective: Endometrial cancer (EC) is the most common gynecologic malignancy. Identification of potential biomarkers of EC would be helpful for the detection and monitoring of malignancy, improving clinical outcomes. Methods: The Weighted Gene Co-expression Network Analysis method was used to identify prognostic markers for EC in this study. Moreover, underlying molecular mechanisms were characterized by KEGG pathway enrichment and transcriptional regulation analyses. Results: Seven gene co-expression modules were obtained, but only the turquoise module was positively related with EC stage. Among the genes in the turquoise module, COL5A2 (collagen, type V, alpha 2) could be regulated by PBX (pre-B-cell leukemia homeobox 1)1/2 and HOXB1(homeobox B1) transcription factors to be involved in the focal adhesion pathway; CENP-E (centromere protein E, 312kDa) by E2F4 (E2F transcription factor 4, p107/p130-binding); MYCN (v-myc myelocytomatosis viral related oncogene, neuroblastoma derived [avian]) by PAX5 (paired box 5); and BCL-2 (B-cell CLL/lymphoma 2) and IGFBP-6 (insulin-like growth factor binding protein 6) by GLI1. They were predicted to be associated with EC progression via Hedgehog signaling and other cancer related-pathways. Conclusions: These data on transcriptional regulation may provide a better understanding of molecular mechanisms and clues to potential therapeutic targets in the treatment of EC.

• IMMUNE NETWORK
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• v.12 no.1
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• pp.1-7
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• 2012

Interleukin-24 (IL-24) belongs to the IL-10 family of cytokines and is well known for its tumor suppressor activity. This cytokine is released by both immune and nonimmune cells and acts on non-hematopoietic tissues such as skin, lung and reproductive tissues. Apart from its ubiquitous tumor suppressor function, IL-24 is also known to be involved in the immunopathology of autoimmune diseases like psoriasis and rheumatoid arthritis. Although the cellular sources and functions of IL-24 are being increasingly investigated, the molecular mechanisms of IL-24 gene expression at the levels of signal transduction, epigenetics and transcription factor binding are still unclear. Understanding the specific molecular events that regulate the production of IL-24 will help to answer the remaining questions that are important for the design of new strategies of immune intervention involving IL-24. Herein, we briefly review the signaling pathways and transcription factors that facilitate, induce, or repress production of this cytokine along with the cellular sources and functions of IL-24.