Description
Proteins play a central role to human body and biological activities. As powerful tools for protein detections, many surface plasmon resonance based techniques have been developed to enhance the sensitivity. However, sensitivity is not the only final goal. As a biosensor, four things really matter: sensitivity, specificity, resolution (temporal/spatial) and throughput.
This dissertation presents several works on developing novel plasmonic based techniques for protein detections on the last two aspects to extend the application field. A fast electrochemically controlled plasmonic detection technique is first developed with the capability of monitoring electrochemical signal with nanosecond response time. The study reveals that the conformational gating of electron transfer in a redox protein (cytochrome c) takes place over a broad range of time scales (sub-µs to ms). The second platform integrates ultra-low volume piezoelectric liquid dispensing and plasmonic imaging detection to monitor different protein binding processes simultaneously with low sample cost. Experiment demonstrates the system can observe binding kinetics in 10×10 microarray of 6 nL droplet, with variations of kinetic rate constants among spots less than ±5%. A focused plasmonic imaging system with bi-cell algorithm is also proposed for spatial resolution enhancement. The two operation modes, scanning mode and focus mode, can be applied for different purposes. Measurement of bacterial aggregation demonstrates the higher spatial resolution. Detections of polystyrene beads binding and 50 nm gold nanoparticles oscillation show a high signal to noise ratio of the system.
The real properties of protein rely on its dynamic personalities. The above works shed light upon fast and high throughput detection of protein kinetics, and enable more applications for plasmonic imaging techniques. It is anticipated that such methods will help to invoke a new surge to unveil the mysteries of biological activities and chemical process.
This dissertation presents several works on developing novel plasmonic based techniques for protein detections on the last two aspects to extend the application field. A fast electrochemically controlled plasmonic detection technique is first developed with the capability of monitoring electrochemical signal with nanosecond response time. The study reveals that the conformational gating of electron transfer in a redox protein (cytochrome c) takes place over a broad range of time scales (sub-µs to ms). The second platform integrates ultra-low volume piezoelectric liquid dispensing and plasmonic imaging detection to monitor different protein binding processes simultaneously with low sample cost. Experiment demonstrates the system can observe binding kinetics in 10×10 microarray of 6 nL droplet, with variations of kinetic rate constants among spots less than ±5%. A focused plasmonic imaging system with bi-cell algorithm is also proposed for spatial resolution enhancement. The two operation modes, scanning mode and focus mode, can be applied for different purposes. Measurement of bacterial aggregation demonstrates the higher spatial resolution. Detections of polystyrene beads binding and 50 nm gold nanoparticles oscillation show a high signal to noise ratio of the system.
The real properties of protein rely on its dynamic personalities. The above works shed light upon fast and high throughput detection of protein kinetics, and enable more applications for plasmonic imaging techniques. It is anticipated that such methods will help to invoke a new surge to unveil the mysteries of biological activities and chemical process.
Details
Title
- Novel Plasmonic Imaging Techniques for Measuring Protein Kinetics
Contributors
- Wang, Yan (Author)
- Tao, Nongjian (Thesis advisor)
- Chae, Junseok (Committee member)
- Goryll, Michael (Committee member)
- Wang, Shaopeng (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2018
Subjects
Resource Type
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Note
- Doctoral Dissertation Electrical Engineering 2018