Ki Baek Yeo

Surface immobilization of protein via biosilification catalyzed by silicatein fused to glutathione S-transferase (GST)

Silicatein from Suberites domuncula was known to catalyze silica deposition in vitro under near neutral pH and ambient temperature conditions. In this study, we employed GST–glutathione (GSH) interaction system to increase the production of silicatein and develop an efficient protein immobilization method. Recombinant silicatein fused with GST (GST-SIL) was produced in E. coli and the GST-SIL protein was employed on GSH-coated glass plate. GST-SIL bound surface or matrix can catalyze the formation of silica layer in the presence of tetraethyl orthosilicate as a substrate at an ambient temperature and neutral pH. During silicatein-mediated silicification, green fluorescent protein (GFP) or horseradish peroxidase (HRP) can be efficiently immobilized on the silica surface. Immobilized GFP or HRP retained their activity and were released gradually. This biocompatible silica coating technique can be employed to prepare biomolecule-immobilized surfaces or matrixes, which are useful for the development of biocatalytic, diagnostic and biosensing system, or tissue culture scaffolds.

Highly effective detection of inflamed cells using a modified bradykinin ligand labeled with FITC fluorescence.

Detection of inflammation in live cells is important because long-lasting inflammation is considered to be a primary cause of several diseases. However, few reports have been published on imaging analysis of inflammation in live cells. In this study, we developed an effective imaging system for detection of inflamed cells using a bradykinin ligand (BK) or a modified BK (mBK), which has specific affinity with the cellular B1R receptor. Synthetic BK or mBK labeled with FITC at the N-terminus was employed for discriminating between inflamed and normal cells; this method was found to be effective for detection of inflammation in live cells. In addition, using the mBK-based cell imaging system, we successfully performed flow-based analysis of live cell inflammation on a micro-chip channel, composed of a Starna flow cell and PDMS (Polydimethylsiloxane) walls. The BK-based cell imaging methods designed here would be a useful platform for development of a high-throughput live cell analysis system for investigating the factors underlying inflammation or for screening of anti-inflammation candidate drugs.

Specific detection of inflamed cells using TLR1 antibody and its secondary antibody-conjugated nano-beads

Chronic inflammation can lead to several diseases, thus analysis of the inflammation state of live cells may have important clinical applications. However, there is not currently well-established method for specific detection of inflamed cells via live cell imaging. In this study, we developed an effective antibody (Ab)-based cell imaging method for the detection of inflamed cells using Ab-conjugated nano-beads. Several receptors were tested as potential biomarkers for cell inflammation, and corresponding fluorescence-labeled Abs and/or Ab-conjugated nano-beads were used to detect inflamed cells via fluorescence imaging. Interestingly, when we employed sequential use of TLR1 primary Ab and size-optimized nano-beads conjugated with secondary Ab, we were able to clearly discriminate inflamed cells from normal ones. The Ab-based cell-imaging method described herein provides an important basis for the development of high-throughput analysis of cell inflammation, potentially leading to the identification of factors involved in inflammation and anti-inflammatory drug candidates.

Shadow image based high-throughput continuous cell monitoring for point-of-care and telemedicine applications

Shadow image based high-throughput continuous cell monitoring technique is proposed. Shadow image variations of human alveolar epithelial cells (A549) cultured in a custom built incubator are analyzed qualitatively and quantitatively. Two measures which correspond to the morphology change of the cells are suggested and defined. Within this platform, it is demonstrated that a single image of a 5M pixel CMOS image sensor can monitor thousands of biological cells simultaneously and continuously. This compact, low-cost, and high-throughput cell monitoring technique holds great promise in the fields of point-of-care testing and telemedicine especially for the resource limited settings.