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Hybrid Chip Device for Automated 2-D Protein Separation


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One of the principal limitations in proteomics is lack of efficient tools for protein analysis, although significant progress has been made. 2-DE was the first that was able to achieve proteomic analysis and it is still the major workhorse for separations of proteins for complex biological samples. However, it is far from dealing with the real complexity of proteomes. Because IEF and SDS-PAGE are two isolated separation steps, their operations are labor intensive and automation is challenging. Due to the numerous manual processes involved with 2-DE, gel-to-gel reproducibility is poor, which make the standardization of 2-DE assay methods difficult. The limit of detection (LOD) of traditional 2-DE is inadequate for detecting low abundance proteins and its linear dynamic range (LDR) is insufficient for handling the extremely divergent protein concentrations in cells. Additionally, the separation speed and throughput of current 2-DE are also low, which inhibits its applications for large-scale proteomic investigations. Furthermore, the technique usually requires tens of micrograms of sample for each assay, which restrains its use when samples are scarce. We propose to develop hybrid device to integrate capillary IEF (CIEF) with capillary gel electrophoresis (CGE) for automated protein separation. CIEF will be performed in a microchip channel. After CIEF, the microchip channel is segmented into 200 shorter channels and the samples inside these channels are simultaneously and respectively injected into 200 capillaries for parallel CGE separations. We will develop a three-color laser-induced fluorescence confocal scanner for the hybrid device to increase protein detection sensitivity and dynamic range. One color will be used to measure the CGE separated proteins, the second color will be used to monitor a set of pl markers, and the third color will be used to detect a set of size markers. We will then validate the practical applicability of the platform by applying it to separate, detect and quantitate the isoforms of four disease-associated proteins that have already been identified in cerebrospinal fluid (CSF) and blood. The platform will advance 2-DE technology by integrating CIEF and parallel CGE for automated 2-DE with improved reproducibility, reduced LOD, increased LDR, decreased separation time and enhanced throughput.


Collapse sponsor award id
R01GM078592

Collapse Time 
Collapse start date
2006-08-01
Collapse end date
2012-01-31