• Proceedings of the Zoological Society Korea Conference
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• 1995.10b
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• pp.76-76
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• 1995

No Abstract, See Full Text

• Proceedings of the PSK Conference
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• 2005.11a
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• pp.162-163
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• 2005

• Journal of Ginseng Research
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• v.40 no.2
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• pp.141-150
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• 2016

Background: Adipocyte-macrophage communication plays a critical role regulating white adipose tissue (WAT) inflammatory gene expression. Because WAT inflammation contributes to the development of metabolic diseases, there is significant interest in understanding how exogenous compounds regulate the adipocyte-macrophage crosstalk. An aqueous (AQ) extract of North American (NA) ginseng (Panax quinquefolius) was previously shown to have strong inflammo-regulatory properties in adipocytes. This study examined whether different ginseng extracts influence adipocyte-macrophage crosstalk, as well as WAT inflammatory gene expression. Methods: The effects of AQ and ethanol (EtOH) ginseng extracts ($5{\mu}g/mL$) on adipocyte and macrophage inflammatory gene expression were studied in 3T3-L1 and RAW264.7 cells, respectively, using real-time reverse transcription polymerase chain reaction. Adipose tissue organ culture was also used to examine the effects of ginseng extracts on epididymal WAT (EWAT) and inguinal subcutaneous WAT (SWAT) inflammatory gene expression. Results: The AQ extract caused significant increases in the expression of common inflammatory genes (e.g., Mcp1, Ccl5, Tnf-${\alpha}$, Nos2) in both cell types. Culturing adipocytes in media from macrophages treated with the AQ extract, and vice versa, also induced inflammatory gene expression. Adipocyte Ppar-${\gamma}$ expression was reduced with the AQ extract. The AQ extract strongly induced inflammatory gene expression in EWAT, but not in SWAT. The EtOH extract had no effect on inflammatory gene expression in either both cell types or WAT. Conclusion: These findings provide important new insights into the inflammo-regulatory role of NA ginseng in WAT.

• The Korean Journal of Physiology and Pharmacology
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• v.3 no.2
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• pp.157-164
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• 1999

To determine molecular mechanisms of Aquaporin-CD (AQP2) gene regulation, the promoter region of the AQP2 gene was examined by transiently transfecting a promoter-luciferase reporter fusion gene into mouse renal collecting duct cell lines such as mIMCD-3, mIMCD-K2, and M-1 cells, and NIH3T3 mouse embryo fibroblast cells. PCR-Southern analysis reveals that mIMCD-3 and mIMCD-K2 cells express AQP2, but M-1 and NIH3T3 cells do not, and that the treatment with cpt-cAMP $(400\;{\mu}M)$) or forskolin/isobutylmethylxanthine (IBMX) increased the AQP2 expression in IMCD cells. In both IMCD and NIH3T3 cells, the constructs containing the promoter of AQP2 gene showed promoter activities, indicating lack of tissue-specific element in the 1.4 kb 5'-flanking region of the mouse AQP2 gene. Luciferase activity in the IMCD cells transfected with the construct containing 5-flanking region showed responsiveness to cpt-cAMP, indicating that the 1.4 kb 5'-flanking region contains the element necessary for the regulatory mechanism by cAMP. The promoter-luciferase constructs which do not have a cAMP-responsible element (CRE) still showed the cAMP responsiveness in IMCD cells, but not in NIH3T3 cells. Increase in medium osmolarity did not affect AQP2 promoter activity in mIMCD-K2 cells. These results demonstrate that AQP2 gene transcription is increased with cAMP treatment through multiple motifs including CRE in the 5'-flanking region of the gene in vitro, and the regulatory mechanism may be important for in vivo regulation of AQP2 expression.

• Journal of Microbiology and Biotechnology
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• v.18 no.1
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• pp.28-34
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• 2008

Biofilm formation in association with the intercellular adhesion (icaADBC) gene cluster is a serious problem in nosocomial infections of Staphylococcus aureus. In all 112 S. aureus strains tested, the ica genes were present, and none of these strains formed biofilms. The biofilm formation is known to be changeable by environmental factors. We have found about 30% of phase variation in these strains with treatment of tetracycline, pristinamycin, and natrium chloride. However, this phenotype disappeared without these substances. Therefore, we have constructed stable biofilm-producing variants through a passage culture method. To explain the mechanism of this variation, nucleotide changes of ica genes were tested in strain S. aureus 483 and the biofilm-producing variants. No differences of DNA sequence in ica genes were found between the strains. Additionally, molecular analysis of three regulatory genes, the accessory gene regulator (agr) and the staphylococcal accessory regulator (sarA), and in addition, alternative transcription factor ${\sigma}^B$ (sigB), was performed. The data of Northern blot and complementation showed that SigB plays an important role for this biofilm variation in S. aureus 483 and the biofilm-producing variants. Sequence analysis of the sigB operon indicated three point mutations in the rsbU gene, especially in the stop codon, and two point mutations in the rsbW gene. This study shows that this variation of biofilm formation in S. aureus is deduced by the role of sigB, not agr and sarA.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.202-205
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• 2005

Cell phenotypes are determined by the concerted activity of thousands of genes and their products. This activity is coordinated by a complex network that regulates the expression of genes. Understanding this organization is crucial to elucidate cellular activities, and many researches have tried to construct gene regulatory networks from mRNA expression data which are nowadays the most available and have a lot of information for cellular processes. Several computational tools, such as Boolean network, Qualitative network, Bayesian network, and so on, have been applied to infer these networks. Among them, Bayesian networks that we chose as the inference tool have been often used in this field recently due to their well-established theoretical foundation and statistical robustness. However, the relative insufficiency of experiments with respect to the number of genes leads to many false positive inferences. To alleviate this problem, we had developed the algorithm of MONET(MOdularized NETwork learning), which is a new method for inferring modularized gene networks by utilizing two complementary sources of information: biological annotations and gene expression. Afterward, we have packaged and improved MONET by combining dispersed functional blocks, extending species which can be inputted in this system, reducing the time complexities by improving algorithms, and simplifying input/output formats and parameters so that it can be utilized in actual fields. In this paper, we present the architecture of MONET system that we have improved.

• Interdisciplinary Bio Central
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• v.3 no.1
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• pp.5.1-5.5
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• 2011

Introduction: Many signal transduction pathways mediate cell's behavior by regulating expression level of involved genes. Abnormal behavior indicates loss of regulatory potential of pathways, and this can be attributed to loss of expression regulation of downstream genes. Therefore, function of pathways should be assessed by activity of a pathway itself and relative activity between a pathway and downstream genes, simultaneously. Results and Discussion: In this study, we suggested a new method to assess pathway's function by introducing concept of 'responsiveness'. The responsiveness was defined as a relative activity between a pathway itself and its downstream genes. The expression level of a downstream gene as a function of an upstream pathway activation characterizes disease status. In this aspect, by using the responsiveness we predicted potential progress in cancer development. We applied our method to predict primary and metastatic status of melanoma cancer. The result shows that the responsiveness-based approach achieves better performance than using gene or pathway information alone. The mean of ROC scores in the responsiveness-based approach was 0.90 for GSE7553 data set, increased more than 40% compared to a gene-based method. Moreover, identifying the abnormal regulatory patterns between pathway and its downstream genes provided more biologically interpretable information compared to gene or pathway based approaches.

• Molecules and Cells
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• v.26 no.6
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• pp.554-557
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• 2008

Double-stranded RNA (dsRNA) induces gene silencing in a sequence-specific manner by a process known as RNA interference (RNAi). The RNA-induced silencing complex (RISC) is a multi-subunit ribonucleoprotein complex that plays a key role in RNAi. VIG (Vasa intronic gene) has been identified as a component of Drosophila RISC; however, the role VIG plays in regulating RNAi is poorly understood. Here, we examined the spatial and temporal expression patterns of VIG-1, the C. elegans ortholog of Drosophila VIG, using a vig-1::gfp fusion construct. This construct contains the 908-bp region immediately upstream of vig-1 gene translation initiation site. Analysis by confocal microscopy demonstrated GFP-VIG-1 expression in a number of tissues including the pharynx, body wall muscle, hypodermis, intestine, reproductive system, and nervous system at the larval and adult stages. Furthermore, western blot analysis showed that VIG-1 is present in each developmental stage examined. To investigate regulatory sequences for vig-1 gene expression, we generated constructs containing deletions in the upstream region. It was determined that the GFP expression pattern of a deletion construct (${\Delta}-908$ to -597) was generally similar to that of the non-deletion construct. In contrast, removal of a larger segment (${\Delta}-908$ to -191) resulted in the loss of GFP expression in most cell types. Collectively, these results indicate that the 406-bp upstream region (-596 to -191) contains essential regulatory sequences required for VIG-1 expression.

• Bulletin of the Korean Chemical Society
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• v.22 no.8
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• pp.903-908
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• 2001

The gene aeg-46.5, which is expressed under anaerobic condition, has putative triple -10 regions and four transcription start sites. The mRNA transcription level and its start point change depending on the aerobic/anaerobic growth condition. RNA polymerase and its regulatory proteins must choose which of three -10 region to use. The putative triple 10 region was mutated to make only one of them function with consensus -10 region sequence (TATAAT) and the other two as non-functional region. The results show that the second and third -10 regions are used for the aerobic/anaerobic expression. The third -10 region is responsible for the high aerobic to anaerobic switch ratio. This suggests that only the last two of the putative triple -10 region have functions on aeg-46.5 gene expression switch control. The phenotype of the mutated promoter was tested in the wild type cell and narL - cell. The results indicate that the control by NarL is independent from the selection of -10 region. The expression patterns on multi-copy plasmids and on single-copy chromosome were compared. These results show that the aerobic/anaerobic switch control of aeg-46.5 is through the choice of -10 region. The mechanism of choosing different -10 region remains to be seen.

• Genomics & Informatics
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• v.5 no.4
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• pp.143-151
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• 2007

To understand the mechanism of transcriptional regulation, it is essential to detect promoters and regulatory elements. Various kinds of methods have been introduced to improve the prediction accuracy of regulatory elements. Since there are few experimentally validated regulatory elements, previous studies have used criteria based solely on the level of scores over background sequences. However, selecting the detection criteria for different prediction methods is not feasible. Here, we studied the calibration of thresholds to improve regulatory element prediction. We predicted a regulatory element using MATCH, which is a powerful tool for transcription factor binding site (TFBS) detection. To increase the prediction accuracy, we used a regulatory potential (RP) score measuring the similarity of patterns in alignments to those in known regulatory regions. Next, we calibrated the thresholds to find relevant scores, increasing the true positives while decreasing possible false positives. By applying various thresholds, we compared predicted regulatory elements with validated regulatory elements from the Open Regulatory Annotation (ORegAnno) database. The predicted regulators by the selected threshold were validated through enrichment analysis of muscle-specific gene sets from the Tissue-Specific Transcripts and Genes (T-STAG) database. We found 14 known muscle-specific regulators with a less than a 5% false discovery rate (FDR) in a single TFBS analysis, as well as known transcription factor combinations in our combinatorial TFBS analysis.