• Journal of Microbiology and Biotechnology
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• v.24 no.2
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• pp.217-224
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• 2014

Chicken are considered as the most important source of human infection by Campylobacter jejuni, which primarily arises from contaminated poultry meats. However, the genes expressed in vivo of the interaction between chicken and C. jejuni have not been screened. In this regard, in vivo-induced antigen technology (IVIAT) was applied to identify expressed genes in vivo during interaction between chicken and C. jejuni, a prevalent foodborne pathogen worldwide. Chicken sera were obtained by inoculating C. jejuni NCTC 11168 into Leghorn chickens through oral and intramuscular administration. Pooled chicken sera, adsorbed against in vitro-grown cultures of C. jejuni, were used to screen the inducible expression library of genomic proteins from sequenced C. jejuni NCTC 11168. Finally, 28 unique genes expressed in vivo were successfully identified after secondary and tertiary screenings with IVIAT. The genes were implicated in metabolism, molecular biosynthesis, genetic information processing, transport, regulation and other processes, in addition to Cj0092, with unknown function. Several potential virulence-associated genes were found to be expressed in vivo, including chuA, flgS, cheA, rplA, and Cj0190c. We selected four genes with different functions to compare their expression levels in vivo and in vitro using real-time RT-PCR. The results indicated that these selected genes were significantly upregulated in vivo but not in vitro. In short, the expressed genes in vivo may act as potential virulence-associated genes, the protein encoded by which may be meaningful vaccine candidate antigens for campylobacteriosis. IVIAT provides an important and efficient strategy for understanding the interaction mechanisms between Campylobacter and hosts.

• Genomics & Informatics
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• v.18 no.4
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• pp.38.1-38.9
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• 2020

Chronotype is an important moderator of psychiatric illnesses, which seems to be controlled in some part by genetic factors. Clock genes are the most relevant genes for chronotype. In addition to the roles of individual genes, gene-gene interactions of clock genes substantially contribute to chronotype. We investigated genetic associations and gene-gene interactions of the clock genes BHLHB2, CLOCK, CSNK1E, NR1D1, PER1, PER2, PER3, and TIMELESS for chronotype in 1,293 healthy Korean individuals. Regression analysis was conducted to find associations between single nucleotide polymorphism (SNP) and chronotype. For gene-gene interaction analyses, the quantitative multifactor dimensionality reduction (QMDR) method, a nonparametric model-free method for quantitative phenotypes, were performed. No individual SNP or haplotype showed a significant association with chronotype by both regression analysis and single-locus model of QMDR. QMDR analysis identified NR1D1 rs2314339 and TIMELESS rs4630333 as the best SNP pairs among two-locus interaction models associated with chronotype (cross-validation consistency [CVC] = 8/10, p = 0.041). For the three-locus interaction model, the SNP combination of NR1D1 rs2314339, TIMELESS rs4630333, and PER3 rs228669 showed the best results (CVC = 4/10, p < 0.001). However, because the mean differences between genotype combinations were minor, the clinical roles of clock gene interactions are unlikely to be critical.

• The Korean Journal of Physiology and Pharmacology
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• v.24 no.1
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• pp.53-68
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• 2020

The purpose of this study was to characterize the genetic contribution to endothelial adaptation to exercise training. Vasoreactivity was assessed in aortas from four inbred mouse strains (129S1, B6, NON, and SJL) after 4 weeks of moderate intensity continuous exercise training (MOD), high intensity interval training (HIT) or in sedentary controls (SED). Intrinsic variations in endothelium-dependent vasorelaxation (EDR) to acetylcholine (ACh) as well as vasocontractile responses were observed across SED groups. For responses to exercise training, there was a significant interaction between mouse strain and training intensity on EDR. Exercise training had no effect on EDR in aortas from 129S1 and B6 mice. In NON, EDR was improved in aortas from MOD and HIT compared with respective SED, accompanied by diminished responses to PE in those groups. Interestingly, EDR was impaired in aorta from SJL HIT compared with SED. The transcriptional activation of endothelial genes was also influenced by the interaction between mouse strain and training intensity. The number of genes altered by HIT was greater than MOD, and there was little overlap between genes altered by HIT and MOD. HIT was associated with gene pathways for inflammatory responses. NON MOD genes showed enrichment for vessel growth pathways. These findings indicate that exercise training has non-uniform effects on endothelial function and transcriptional activation of endothelial genes depending on the interaction between genetic background and training intensity.

• BMB Reports
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• v.50 no.11
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• pp.535-536
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• 2017

A novel approach has been used to identify functional interactions relevant to human disease. Using high-throughput human-yeast genetic interaction screens, a first draft of disease interactome was obtained. This was achieved by first searching for candidate human disease genes that confer toxicity in yeast, and second, identifying modulators of toxicity. This study found potentially disease-relevant interactions by analyzing the network of functional interactions and focusing on genes implicated in amyotrophic lateral sclerosis (ALS), for example. In the subsequent proof-of-concept study focused on ALS, similar functional relationships between a specific kinase and ALS-associated genes were observed in mammalian cells and zebrafish, supporting findings in human-yeast genetic interaction screens. Results of combined analyses highlighted MAP2K5 kinase as a potential therapeutic target in ALS.

• Genes and Genomics
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• v.40 no.12
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• pp.1363-1371
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• 2018

One of the main concerns in biology is extracting sophisticated features from DNA sequence for gene interaction determination, receiving a great deal of researchers' attention. The epigenetic modifications along with their patterns have been intensely recognized as dominant features affecting on gene expression. However, studying sequenced-based features highly correlated to this key element has remained limited. The main objective in this research was to propose a new feature highly correlated to epigenetic modifications capable of classification of genes. In this paper, classification of 34 genes in PPAR signaling pathway associated with muscle fat tissue in human was performed. Using different statistical outlier detection methods, we proposed that 5-mers highly correlated to epigenetic modifications can correctly categorize the genes involved in the same biological pathway or process. Thirty-four genes in PPAR signaling pathway were classified via applying a proposed feature, 5-mers strongly associated to 17 different epigenetic modifications. For this, diverse statistical outlier detection methods were applied to specify the group of thoroughly correlated genes. The results indicated that these 5-mers can appropriately identify correlated genes. In addition, our results corresponded to GeneMania interaction information, leading to support the suggested method. The appealing findings imply that not only epigenetic modifications but also their highly correlated 5-mers can be applied for reconstructing gene regulatory networks as supplementary data as well as other applications like physical interaction, genes prioritization, indicating some sort of data fusion in this analysis.

• Genomics & Informatics
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• v.21 no.1
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• pp.6.1-6.8
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• 2023

Glaucoma is the second leading cause of irreversible blindness, and primary open-angle glaucoma (POAG) is the most common type. Due to inadequate diagnosis, treatment is often not administered until symptoms occur. Hence, approaches enabling earlier prediction or diagnosis of POAG are necessary. We aimed to identify novel drugs for glaucoma through bioinformatics and network analysis. Data from 36 samples, obtained from the trabecular meshwork of healthy individuals and patients with POAG, were acquired from a dataset. Next, differentially expressed genes (DEGs) were identified to construct a protein-protein interaction (PPI) network. In both stages, the genes were enriched by studying the critical biological processes and pathways related to POAG. Finally, a drug-gene network was constructed, and novel drugs for POAG treatment were proposed. Genes with p < 0.01 and |log fold change| > 0.3 (1,350 genes) were considered DEGs and utilized to construct a PPI network. Enrichment analysis yielded several key pathways that were upregulated or downregulated. For example, extracellular matrix organization, the immune system, neutrophil degranulation, and cytokine signaling were upregulated among immune pathways, while signal transduction, the immune system, extracellular matrix organization, and receptor tyrosine kinase signaling were downregulated. Finally, novel drugs including metformin hydrochloride, ixazomib citrate, and cisplatin warrant further analysis of their potential roles in POAG treatment. The candidate drugs identified in this computational analysis require in vitro and in vivo validation to confirm their effectiveness in POAG treatment. This may pave the way for understanding life-threatening disorders such as cancer.

• Genomics & Informatics
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• v.18 no.4
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• pp.39.1-39.8
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• 2020

Alzheimer's disease (AD) is a chronic, progressive brain disorder that slowly destroys affected individuals' memory and reasoning faculties, and consequently, their ability to perform the simplest tasks. This study investigated the hub genes of AD. Proteins interact with other proteins and non-protein molecules, and these interactions play an important role in understanding protein function. Computational methods are useful for understanding biological problems, in particular, network analyses of protein-protein interactions. Through a protein network analysis, we identified the following top 10 hub genes associated with AD: PTGER3, C3AR1, NPY, ADCY2, CXCL12, CCR5, MTNR1A, CNR2, GRM2, and CXCL8. Through gene enrichment, it was identified that most gene functions could be classified as integral to the plasma membrane, G-protein coupled receptor activity, and cell communication under gene ontology, as well as involvement in signal transduction pathways. Based on the convergent functional genomics ranking, the prioritized genes were NPY, CXCL12, CCR5, and CNR2.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.21 no.3
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• pp.36-51
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• 2008

Objective : This study investigated the effects of PR(Pinelliae Rhizoma) on gene expression of lung tissue resected from asthma induced mice using intra-nasal instillation. Methods : Gene expression levels were measured using a microarray technique, and a functional analysis on these genes was conducted. Results : A total of 3270 genes were up-regulated or down-regulated, 860 genes which were lowered by induction of asthma were restored to those of naive animals, Furthermore hand, 1235 genes were lowered to normal levels, which were elevated by induction of asthma. Most of changed genes were involved in signalling pathways. Genes in which expression levels were restored by oral administration of PR were involved in MAPK pathway, focal adhesion, and regulation of actin cytoskeleton etc. Genes of which expression levels were lowered by oral administration of PR were involved in rhodopsin-like receptor activity, zinc ion binding and ATP binding. These genes were also involved in neuroactive ligand receptor interaction, the JAK-STAT signaling pathway and also the T-cell receptor signaling pathway. Conclusion : These results demonstrate the strong possibility that the mechanisms of PR on asthma are involved in neuroactive ligand receptor interaction pathway or related molecules.

• Proceedings of the Botanical Society of Korea Conference
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• 1999.07a
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• pp.21-35
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• 1999

We have previously isolated OsMADS4 gene that is a member of the class B MADS box genes from rice. In this study, another member of the class B MADS box genes was isolated from rice flower by the yeast two-hybrid screening method using OsMADS4 as bait. RNA blot analyses revealed that the clone, OsMADS16, was expressed in the second and third whorls, whereas the OsMADS4 transcripts were present in the second, third, and fourth whorls. These expression patterns of the OsMADS16 and OsMADS4 genes are very similar with those of AP3 and PI, the class B genes of Arabidopsis, respectively. In the yeast two-hybrid system, OsMADS4 interacted only with OsMADS16 among several rice MADS genes investigated, suggesting that OsMADS4 and OsMADS16 function as a heterodimer in specifying sepal and petal identities. We have also isolated OsMADS6 gene using OsMADS1 as a probe. Both are members of the AGL2 MADS family. Various MADS genes that encode for protein-protein interaction partners of the OsMADS6 protein were isolated by the yeast two-hybrid screening method. A majority of these genes belong to the AGL2 family. Sequence Homology, expression pattern, and ectopic expression phenotypes indicated that one of the interaction partners, OsMADS14, appears to be homologous to API, the class A MADS gene of Arabidopsis.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.1731-1735
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• 2013

Objective: We aimed to identify key genes, pathways and function modules in the development of diffuse large B-cell lymphoma (DLBCL) with microarray data and interaction network analysis. Methods: Microarray data sets for 7 DLBCL samples and 7 normal controls was downloaded from the Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were identified with Student's t-test. KEGG functional enrichment analysis was performed to uncover their biological functions. Three global networks were established for immune system, signaling molecules and interactions and cancer genes. The DEGs were compared with the networks to observe their distributions and determine important key genes, pathways and modules. Results: A total of 945 DEGs were obtained, 272 up-regulated and 673 down-regulated. KEGG analysis revealed that two groups of pathways were significantly enriched: immune function and signaling molecules and interactions. Following interaction network analysis further confirmed the association of DEGs in immune system, signaling molecules and interactions and cancer genes. Conclusions: Our study could systemically characterize gene expression changes in DLBCL with microarray technology. A range of key genes, pathways and function modules were revealed. Utility in diagnosis and treatment may be expected with further focused research.