• KSBB Journal
• /
• v.22 no.4
• /
• pp.260-264
• /
• 2007

Peptides are frequently studied as candidates for new drug development. Recently, synthesized peptide library is screened for a certain functionality on a microarray biochip format. In this study, in order to replace the conventional cellulose membrane with glass for a microarray chip substrate for peptide library screening, we modified the glass surface from amines to thiols and covalently immobilized the peptides. Using trypsin-FITC (fluorescein isothiocyanate) conjugate that could specifically bind to a trypsin binding domain consisting of a 7-amino acid peptide, we checked the degree of surface modification. Because of the relatively lower hydrophilicity and reduced surface roughness, the conjugation reaction to the glass required a longer reaction time and a higher temperature. It took approximately 12 hr for the reaction to be completed. From the fluorescence signal intensity, we could differentiate between the target and the control peptides. This difference was confirmed by a separate experiment using QCM. Furthermore, a smaller volume and higher concentration of a spot showed a higher fluorescence intensity. These data would provide the basic conditions for the development of microarray peptide biochips.

• Asian-Australasian Journal of Animal Sciences
• /
• v.21 no.1
• /
• pp.11-18
• /
• 2008

We created a cDNA microarray representing approximately 3,500 pig genes for functional genomic studies. The array elements were selected from 6,494 cDNA clones identified in a large-scale expressed sequence tag (EST) project. These cDNA clones came from normalized and subtracted porcine adipose tissue cDNA libraries. Sequence similarity searches of the 3,426 ESTs represented on the array using BLASTN identified 2,790 (81.4%) as putative human orthologs, with the remainder consisting of "novel" genes or highly divergent orthologs. We used the gene microarray to profile transcripts expressed by adipose tissue of fatty Chinese Xiang pig (XP) and muscley Large White (LW). Microarray analysis of RNA extracted from adipose tissue of fatty XP and muscley LW identified 81 genes that were differently expressed two fold or more. Transcriptional differences of four of these genes, adipocyte fatty acid binding protein (aP2), stearyl-CoA desaturase (SCD), sterol regulatory element binding transcription factor 1 (SREBF1) and lipoprotein lipase (LPL) were confirmed using SYBR Green quantitative RT-PCR technology. Our results showed that high expression of SCD and SREBF1 may be one of the reasons that larger fat deposits are observed in the XP. In addition, our findings also illustrate the potential power of microarrays for understanding the molecular mechanisms of porcine development, disease resistance, nutrition, fertility and production traits.

• KOGO NEWS
• /
• v.5 no.4
• /
• pp.9-16
• /
• 2005

Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic expression data transforms the challenges m biomedical research into ones in bioinformatics. Clinical informatics has long developed technologies to imp개ve biomedical research by integrating experimental and clinical information systems. Biomedical informatics, powered by high throughput techniques, genomic-scale databases and advanced clinical information system, is likely to transform our biomedical understanding forever much the same way that biochemistry did to biology a generation ago. The emergence of healthcare and biomedical informatics revolutionizing both bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics and prognostics.

• Journal of Digital Contents Society
• /
• v.11 no.1
• /
• pp.99-104
• /
• 2010

Numerous bio-digital contents have been produced by new technology using biochip and others for analyzing early chemical-induced genes. These contents have little meaning by themselves, and so they should be modified and extracted after consideration of biological meaning. These include genomics, transcriptomics, protenomics, metabolomics, which combined into omics. Omics tools could be applied into toxicology, forming a new field of toxicogenomics. It is possible that approach of toxicogenomics can estimate toxicity more quickly and accurately by analyzing gene/protein/metabolite profiles. These approaches should help not only to discover highly sensitive and predictive biomarkers but also to understand molecular mechanism(s) of toxicity, based on the development of analysing technology. Furthermore, it is important that bio-digital contents should be obtained from specific cells having biological events more than from whole cells. Taken together, many bio-digital contents should be analyzed by careful calculating algorism under well-designed experimental protocols, network analysis using computational algorism and related profound databases.