• International Journal of Oral Biology
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• v.44 no.2
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• pp.31-36
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• 2019

Streptococcus mutans is one of the important bacteria that forms dental biofilm and cause dental caries. Virulence genes in S. mutans can be classified into the genes involved in bacterial adhesion, extracellular polysaccharide formation, biofilm formation, sugar uptake and metabolism, acid tolerance, and regulation. The genes involved in bacterial adhesion are gbps (gbpA, gbpB, and gbpC) and spaP. The gbp genes encode glucan-binding protein (GBP) A, GBP B, and GBP C. The spaP gene encodes cell surface antigen, SpaP. The genes involved in extracellular polysaccharide formation are gtfs (gtfB, gtfC, and gtfD) and ftf, which encode glycosyltransferase (GTF) B, GTF C, and GTF D and fructosyltransferase, respectively. The genes involved in biofilm formation are smu630, relA, and comDE. The smu630 gene is important for biofilm formation. The relA and comDE genes contribute to quorumsensing and biofilm formation. The genes involved in sugar uptake and metabolism are eno, ldh, and relA. The eno gene encodes bacterial enolase, which catalyzes the formation of phosphoenolpyruvate. The ldh gene encodes lactic acid dehydrogenase. The relA gene contributes to the regulation of the glucose phosphotransferase system. The genes related to acid tolerance are atpD, aguD, brpA, and relA. The atpD gene encodes $F_1F_0$-ATPase, a proton pump that discharges $H^+$ from within the bacterium to the outside. The aguD gene encodes agmatine deiminase system and produces alkali to overcome acid stress. The genes involved in regulation are vicR, brpA, and relA.

• The Korean Journal of Physiology and Pharmacology
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• v.15 no.1
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• pp.23-29
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• 2011

Melatonin, which is the main product of the pineal gland, has well documented antioxidant and immune-modulatory effects. Macrophages produce molecules that are known to play roles in inflammatory responses. We conducted microarray analysis to evaluate the global gene expression profiles in response to treatment with melatonin in lipopolysaccharide (LPS) activated RAW 264.7 macrophage cells. In addition, eight genes were subjected to real-time reverse transcription polymerase chain reaction (RT-PCR) to confirm the results of the microarray. The cells were treated with LPS or melatonin plus LPS for 24 hr. LPS induced the up-regulation of 1073 genes and the down-regulation of 1144 genes when compared to the control group. Melatonin pretreatment of LPS-stimulated RAW 264.7 cells resulted in the down regulation of 241 genes and up regulation of 164 genes. Interestingly, among genes related to macrophage-mediated immunity, LPS increased the expression of seven genes (Adora2b, Fcgr2b, Cish, Cxcl10, Clec4n, Il1a, and Il1b) and decreased the expression of one gene (Clec4a3). These changes in expression were attenuated by melatonin. Furthermore, the results of real-time PCR were similar to those of the microarray. Taken together, these results suggest that melatonin may have a suppressive effect on LPS-induced expression of genes involved in the regulation of immunity and defense in RAW 264.7 macrophage cells. Moreover, these results may explain beneficial effects of melatonin in the treatment of various inflammatory conditions.

• International Journal of Oral Biology
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• v.32 no.1
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• pp.1-5
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• 2007

Receptor activator of nuclear factor ${\kappa}B$ ligand (RANKL) induces osteoclast formation from hematopoietic cells via up-regulation of positive regulators, including $NF-{\kappa}B$, c-Fos, microphthalmia transcription factor (Mitf), PU.1, and nuclear factor of activated T cells (NFAT) c1. In addition to the positive regulation by these transcription factors, RANKL appears to regulate negative regulators such as MafB and inhibitors of differentiation (Ids). Ids and MafB are abundantly expressed in osteoclast precursors, bone marrowderived monocyte/macrophage lineage cells (BMMs). Expression levels of these genes are significantly reduced by RANKL during osteoclastogenesis. Overexpression of these genes in BMMs inhibits the formation of tartarate-resistant acid phosphatase (TRAP)-positive multinuclear osteoclasts by down-regulation of NFATc1 and osteoclast-associated receptor (OSCAR), which are important for osteoclast differentiation. Furthermore, reduced expression of these genes enhances osteoclastogenesis and increases expression of NFATc1 and OSCAR. Taken together, RANKL induces osteoclastogenesis via up-regulation of positive regulators as well as down-regulation of negative regulators.

• Genes and Genomics
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• v.40 no.12
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• pp.1331-1338
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• 2018

Although there have been plenty of dominance deviation analysis, few studies have dealt with multiple phenotypes. Because researchers focused on multiple phenotypes (final weight and backfat thickness) of Landrace pigs, the classification of the genes was possible. With genome-wide association studies (GWASs), we analyzed the additive and dominance effects of the single nucleotide polymorphisms (SNPs). The classification of the pig genes into four categories (overdominance in final weight, overdominance in backfat thickness and overdominance in final weight, underdominance in backfat thickness, etc.) can enable us not only to analyze each phenotype's dominant effects, but also to illustrate the gene ontology (GO) analysis with different aspects. We aimed to determine the additive and dominant effect in backfat thickness and final weight and performed GO analysis. Using additive model and dominance deviation analysis in GWASs, Landrace pigs' overdominant and underdominant SNP effects in final weight and backfat thickness were surveyed. Then through GO analysis, we investigated the genes that were classified in the GWASs. The major GO terms of the underdominant effects in final weight and overdominant effects in backfat thickness were ion transport with the SLC8A3, KCNJ16, P2RX7 and TRPC3 genes. Interestingly, the major GO terms in the underdominant effects in the final weight and the underdominant effects in the backfat thickness were the regulation of ion transport with the STAC, GCK, TRPC6, UBASH3B, CAMK2D, CACNG4 and SCN4B genes. These results demonstrate that ion transport and ion transport regulation genes have distinct dominant effects. Through GWASs using the mode of linear additive model and dominance deviation, overdominant effects and underdominant effects in backfat thickness was contrary to each other in GO terms (ion transport and ion transport regulation, respectively). Additionally, because ion transport and ion transport regulation genes are associative with adipose tissue accumulation, we could infer that these two groups of genes had to do with unique fat accumulation mechanisms in Landrace pigs.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.23
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• pp.10355-10361
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• 2015

Background: MicroRNAs (miRNAs) are small non-coding RNA molecules found in multicellular eukaryotes which are implicated in development of cancer, including cutaneous squamous cell carcinoma (cSCC). Expression is controlled by transcription factors (TFs) that bind to specific DNA sequences, thereby controlling the flow (or transcription) of genetic information from DNA to messenger RNA. Interactions result in biological signal control networks. Materials and Methods: Molecular components involved in cSCC were here assembled at abnormally expressed, related and global levels. Networks at these three levels were constructed with corresponding biological factors in term of interactions between miRNAs and target genes, TFs and miRNAs, and host genes and miRNAs. Up/down regulation or mutation of the factors were considered in the context of the regulation and significant patterns were extracted. Results: Participants of the networks were evaluated based on their expression and regulation of other factors. Sub-networks with two core TFs, TP53 and EIF2C2, as the centers are identified. These share self-adapt feedback regulation in which a mutual restraint exists. Up or down regulation of certain genes and miRNAs are discussed. Some, for example the expression of MMP13, were in line with expectation while others, including FGFR3, need further investigation of their unexpected behavior. Conclusions: The present research suggests that dozens of components, miRNAs, TFs, target genes and host genes included, unite as networks through their regulation to function systematically in human cSCC. Networks built under the currently available sources provide critical signal controlling pathways and frequent patterns. Inappropriate controlling signal flow from abnormal expression of key TFs may push the system into an incontrollable situation and therefore contributes to cSCC development.

• Genomics & Informatics
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• v.5 no.3
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• pp.107-112
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• 2007

MicroRNAs (miRNAs) are known to negatively control protein-coding genes by binding to messenger RNA (mRNA) in the cytoplasm. In innate immunity, the role of miRNA gene silencing is largely unknown. In this study, we performed microarray-based experiments using lipopolysaccharide (LPS)-stimulated macrophages derived from wild-type, MyD88 knockout (KO), TRIF KO, and MyD88/TRIF double KO mice. We employed a statistical approach to determine the importance of the commonality and specificity of miRNA binding sites among groups of temporally co-regulated genes. We demonstrate that both commonality and specificity are irrelevant to define a priori groups of co-down regulated genes. In addition, analyzing the various experimental conditions, we suggest that miRNA regulation may not only be a late-phase process (after transcription) but can also occur even early (1h) after stimulation in knockout conditions. This further indicates the existence of dynamic interactions between miRNA and signaling molecules/transcription factor regulation; this is another proof for the need of shifting from a 'hard-wired' paradigm of gene regulation to a dynamical one in which the gene co-regulation is established on a case-by-case basis.

• Genomics & Informatics
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• v.12 no.3
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• pp.105-113
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• 2014

A subset of mammalian genes differ functionally between two alleles due to genomic imprinting, and seven such genes (Peg3, Usp29, APeg3, Zfp264, Zim1, Zim2, Zim3) are localized within the 500-kb genomic interval of the human and mouse genomes, constituting the Peg3 imprinted domain. This Peg3 domain shares several features with the other imprinted domains, including an evolutionarily conserved domain structure, along with transcriptional co-regulation through shared cis regulatory elements, as well as functional roles in controlling fetal growth rates and maternal-caring behaviors. The Peg3 domain also displays some unique features, including YY1-mediated regulation of transcription and imprinting; conversion and adaptation of several protein-coding members as ncRNA genes during evolution; and its close connection to human cancers through the potential tumor suppressor functions of Peg3 and Usp29. In this review, we summarize and discuss these features of the Peg3 domain.

• Journal of Life Science
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• v.5 no.4
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• pp.162-169
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• 1995

The glpD genes encoding gly-3-p dehydrogenase is essential for the aerobic growth of E. coli on glycerol or gly-3-p. The glpE gene, the function of which is unknownm is transcribed divergently with respect to glpD gene. Expression of the adjacent but divergently transcribed glpD the glpE genes is positively regulated by the cAMP-CRP complex. In this study, for a precise investigation of the functional elements in the regulatory region for transcription activation by cAMP-CRP, deletion mutation have been introducted into the regulatory region. The effect of the deletion mutant on transcriptional regulation was tested in vivo by $\beta$-galctosidase activity. Deletion mutants in the regulatory region of glpD demonstrated that the presence of the CRP-binding site resulted in an sixfold increase in promoter activity. And also deletion mutants of glpE gene demonstrated that the presence of the CRP-binding site resulted in an eightfold increase in promoter activity. Insertion of 22 bp oligomer in the deletion mutants has shown that the CRP binding site is need for maximal expression of glpD and glpE genes. glpD and glpE gene, cAMP-CRP complex, deletion mutant, transcriptional regulation.

• Journal of Microbiology and Biotechnology
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• v.28 no.2
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• pp.181-189
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• 2018

Candida albicans is a major pathogenic fungus in humans, and meets at first the innate immune cells, such as macrophages, in its host. One important strategy of the host cell to kill C. albicans is to produce reactive oxygen species (ROS) by the macrophages. In response to ROS produced by the macrophages, C. albicans operates its defense mechanisms against them by expressing its oxidative stress response genes. Although there have been many research studies explaining the specific transcription factors and the expression of the oxidative stress genes in C. albicans, the regulation of the oxidative stress genes by chromatin structure is little known. Epigenetic regulation by the chromatin structure is very important for the regulation of eukaryotic gene expression, including the chromatin structure dynamics by histone modifications. Among various histone modifications, histone acetylation is reported for its direct relationship to the regulation of gene expression. Recent studies reported that histone acetyltransferases regulate genes to respond to the oxidative stress in C. albicans. In this review, we introduce all histone acetyltransferases that C. albicans contains and some papers that explain how histone acetyltransferases participate in the oxidative stress response in C. albicans.

• Proceedings of the Korean Biophysical Society Conference
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• 2003.06a
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• pp.77-77
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• 2003

Gene expression in a cell is regulated by mutual activations or repressions between genes. Identifying the gene regulation network will be one of the most important research topics in the post genomic era. We propose a linear dynamic model of gene regulation for the yeast cell cycle. A small gene network consisting of about 40 genes is reconstructed from the analysis of micro-array gene expression data of yeast S. cerevisiae published by P. Spellman et al. We show that the network construction is consistent with the result of the hierarchical cluster analysis.