Monitoring of enzymatic proteolysis on a electroluminescent-CCD microchip platform using quantum dot-peptide substrates
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- 作者：Kim E. Sapsford ; Dorothy Farrell ; Steven Sun ; Avraham Rasooly ; Hedi Mattoussi ; Igor L. Medintz
- 关键词：Electroluminescent excitation ; CCD ; Resonance energy transfer ; FRET ; Quantum dots ; Peptides ; Protease sensor ; Trypsin ; Microfabricated device ; Biosensor
- 刊名：Sensors and Actuators B: Chemical
- 出版年：2009
- 出版时间：20 May 2009
- 年：2009
- 卷：139
- 期：1
- 页码：13-21
- 全文大小：982 K
文摘
Microfabricated devices will have a large impact on many aspects of analytical chemistry from clinical diagnostics to security applications due to their small size, ease of fabrication, portability and low sample volumes. In this report we compare quantum dot (QD)-peptide fluorescence resonance energy transfer (FRET) and subsequent FRET-based monitoring of enzymatic proteolysis on both a conventional laboratory fluorescent assay plate reader and an electroluminescent-charged-coupled device (EL-CCD) microchip detection platform. The EL-CCD setup combines the spatial detection of CCD with the simple illumination provided by EL strips to measure fluorescence from multi-well credit card-sized sample chips. Data on FRET between a QD donor and a dye-labeled peptide acceptor along with their usage as a substrate for trypsin proteolysis were collected on both platforms and analyzed. Despite a greater than 12-fold reduction in assay volumes in the microchip format and simplification of excitation/emission monitoring, the data reflected a general agreement including an analysis of the QD donor–dye acceptor FRET efficiency and the determination of proteolytic kinetic parameters such as enzymatic velocity Vmax and the Michaelis constant KM. The EL-CCD was further utilized to monitor specific ovomucoid inhibition of trypsin activity. The results suggest that the unique properties inherent to QDs can be combined with the reduced-scale nature of microfabricated devices to make them suitable for a variety of focused bioanalytical applications, including point-of-care diagnostics and global healthcare applications.