• Molecules and Cells
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• v.19 no.2
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• pp.279-282
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• 2005

In mammals, 7-dehydrocholesterol reductase (Dhcr7) is the terminal enzyme in cholesterol biosynthesis. We previously reported that the Dhcr7 proximal promoter (-179 to +1), which contains CpG islands, is responsible for sterol-mediated expression of the rat gene. In the present study, we examined whether methylation of this region affects the transcriptional activity of the Dhcr7 gene. In vitro DNA methylation of the Dhcr7 promoter and luciferase-reporter assays showed that DNA methylation of the CpG islands suppressed transcription. Furthermore, treatment of the methylated Dhcr7 promoter with the demethylating agent, 5-aza-2'-deoxycytidine (5-Aza-CdR), reversed the suppression of promoter activity. These results indicate that methylation of the CpG islands is an important transcriptional regulatory mechanism in the Dhcr7 promoter.

• Journal of Microbiology and Biotechnology
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• v.16 no.5
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• pp.799-803
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• 2006

It was reported that an accumulation of Sadenosyl-L-methionine increases production of actinorhodin in Streptomyces lividans and induces antibiotic biosynthetic genes. We also obtained the same result in Streptomyces coelicolor A3(2). Therefore, in order to identify proteins changed by the addition of S-adenosyl-L-methionine in S. coelicolor A3(2), LC/MS/MS analyses were carried out. Thirteen proteins that were not observed in the control were found.

• Bioinformatics and Biosystems
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• v.1 no.2
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• pp.89-94
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• 2006

Mass spectrometry (MS) is widely applied for high throughput proteomics analysis. When large-scale proteome analysis experiments are performed, it generates massive amount of data. To search these proteomics data against protein databases, fully automated database search algorithms, such as Mascot and SEQUEST are routinely employed. At present, it is critical to reduce false positives and false negatives during such analysis. In this review we have focused on aspects of automated protein identification using tandem mass spectrometry (MS/MS) spectra and validation of the protein identifications of two most common automated protein identification algorithms Mascot and SEQUEST.

• Genomics & Informatics
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• v.9 no.4
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• pp.197-199
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• 2011

The biological interpretation of two-dimensional (2D) gel electrophoresis experiments is a key step toward understanding the functions of biological systems. We here present a web-based integrated database, called 2DSpotDB, for the management of proteome data derived from several pathogens. The 2DSpotDB was established as a part of the management of a pathogen proteome project at the Korea National Institute of Health. The goals of the 2DSpotDB implementation are to store and define important pathogen genes, retrieve information obtained by 2D polyacrylamide gel electrophoresis and mass spectrometry, and create an integrated system to provide pathogen proteome information for biological scientists. This database currently contains 14 gels and information on 387 protein spots, among which 329 proteins were identified and annotated.

• Genomics & Informatics
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• v.11 no.4
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• pp.289-291
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• 2013

Human papillomavirus (HPV) infection is the leading cause of cancer mortality among women worldwide. The molecular understanding of HPV proteins has significant connotation for understanding their intrusion in the host and designing novel protein vaccines and anti-viral agents, etc. Genomic, proteomic, structural, and disease-related information on HPV is available on the web; yet, with trivial annotations and more so, it is not well customized for data analysis, host-pathogen interaction, strain-disease association, drug designing, and sequence analysis, etc. We attempted to design an online reserve with comprehensive information on HPV for the end users desiring the same. The Human Papillomavirus Proteome Database (hpvPDB) domiciles proteomic and genomic information on 150 HPV strains sequenced to date. Simultaneous easy expandability and retrieval of the strain-specific data, with a provision for sequence analysis and exploration potential of predicted structures, and easy access for curation and annotation through a range of search options at one platform are a few of its important features. Affluent information in this reserve could be of help for researchers involved in structural virology, cancer research, drug discovery, and vaccine design.

• Genomics & Informatics
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• v.21 no.1
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• pp.5.1-5.13
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• 2023

Neisseria gonorrhoeae is a Gram-negative aerobic diplococcus bacterium that primarily causes sexually transmitted infections through direct human sexual contact. It is a major public health threat due to its impact on reproductive health, the widespread presence of antimicrobial resistance, and the lack of a vaccine. In this study, we used a bioinformatics approach and performed subtractive genomic methods to identify potential drug targets against the core proteome of N. gonorrhoeae (12 strains). In total, 12,300 protein sequences were retrieved, and paralogous proteins were removed using CD-HIT. The remaining sequences were analyzed for non-homology against the human proteome and gut microbiota, and screened for broad-spectrum analysis, druggability, and anti-target analysis. The proteins were also characterized for unique interactions between the host and pathogen through metabolic pathway analysis. Based on the subtractive genomic approach and subcellular localization, we identified one cytoplasmic protein, 2Fe-2S iron-sulfur cluster binding domain-containing protein (NGFG RS03485), as a potential drug target. This protein could be further exploited for drug development to create new medications and therapeutic agents for the treatment of N. gonorrhoeae infections.

• Genomics & Informatics
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• v.14 no.1
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• pp.2-11
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• 2016

The advances in mass spectrometry-based proteomics technologies have enabled the generation of global proteome data from tissue or body fluid samples collected from a broad spectrum of human diseases. Comparative proteomic analysis of global proteome data identifies and prioritizes the proteins showing altered abundances, called differentially expressed proteins (DEPs), in disease samples, compared to control samples. Protein biomarker candidates that can serve as indicators of disease states are then selected as key molecules among these proteins. Recently, it has been addressed that cellular pathways can provide better indications of disease states than individual molecules and also network analysis of the DEPs enables effective identification of cellular pathways altered in disease conditions and key molecules representing the altered cellular pathways. Accordingly, a number of network-based approaches to identify disease-related pathways and representative molecules of such pathways have been developed. In this review, we summarize analytical platforms for network-based protein biomarker discovery and key components in the platforms.

• Molecules and Cells
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• v.26 no.2
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• pp.171-174
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• 2008

Flavone (2-phenyl chromone) is a well-known plant flavonoid, but its bioactivity has been little explored. Treatment of Caenorhabditis elegans or C. brissage with flavones induced embryonic and larval lethality that was pronounced in early larval stages. This anti-nematodal effect was also observed in the pinewood nematode, B. xylophilus. $LD_{50}$ values were approximately $100{\mu}M$ for both B. xylophilus and C. elegans. Our results indicate that flavone is an active nematicidal compound that should be further investigated with the aim of developing a potent drug against B. xylophilus.

• Genomics & Informatics
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• v.4 no.1
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• pp.40-44
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• 2006

Toxicogenomics combines transcriptome, proteome and metabolome profiling with conventional toxicology to investigate the interaction between biological molecules and toxicant or environmental stress in disease caution. Toxicogenomics faces the problems of comparison and integration across different sources of data. Cause of unusual characteristics of toxicogenomic data, researcher should be assisted by data analysis and annotation for getting meaningful information. There are already existing repositories which claim to stand for toxicogenomics database. However, those just contain limited abilities for toxicogenomic research. For supporting toxicologist who comes up against toxicogenomic data flood, now we propose novel toxicogenomics knowledgebase system, XPERANTO-TOX. XPERANTO-TOX is an integrated system for toxicogenomic data management and analysis. It is composed of three distinct but closely connected parts. Firstly, Data Storage System is for reposit many kinds of '-omics' data and conventional toxicology data. Secondly, Data Analysis System consists of analytical modules for integrated toxicogenomics data. At last, Data Annotation System is for giving extensive insight of data to researcher.

• Genomics & Informatics
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• v.8 no.4
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• pp.165-169
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• 2010

The Korean Bioinformation Center (KOBIC) is a national bioinformatics research center in Korea. We developed many bioinformatics algorithms and applications to facilitate the biological interpretation of OMICS data. Here we present an introduction to major bioinformatics resources of databases and tools developed at KOBIC. These resources are classified into three main fields: genome, proteome, and literature. In the genomic resources, we constructed several pipelines for next generation sequencing (NGS) data processing and developed analysis algorithms and web-based database servers including miRGator, ESTpass, and CleanEST. We also built integrated databases and servers for microarray expression data such as MDCDP. As for the proteome data, VnD database, WDAC, Localizome, and CHARMM_HM web servers are available for various purposes. We constructed IntoPub server and Patome database in the literature field. We continue constructing and maintaining the bioinformatics infrastructure and developing algorithms.