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Multiplexed Fluorescent Microarray for Human Salivary Protein Analysis Using Polymer Microspheres and Fiber-optic Bundles
Published on: October 10, 2013
Hyperbranched Aggregation-Induced Emission Luminogen-Based Sensor Array for Highly Sensitive Discrimination of
Shiyu Zang1, Xiao Dong2, Haozhi Song1
1School of Chemistry, Dalian University of Technology, Dalian 116024, PR China.
Abstract:
Simultaneous discrimination of multiple proteins with high sensitivity is of great importance for point-of-care prediction and diagnosis of diseases. Herein, a fluorescent sensor array with three hyperbranched aggregation-induced emission luminogens as sensing elements is fabricated for the simultaneous discrimination of 15 kinds of proteins with a low limit of detection of 0.05 μM, which is lower than those of most of the reported sensor arrays. The three probes with a symmetrical structure tailored with hydrophilic termini are easy to synthesize and are soluble in aqueous systems. Upon detection, these probes show multivalent interactions with proteins by either electrostatic interaction, hydrogen bond, or van der Waals forces, along with their fluorescence emission modulated by the protein's hydrophobic pocket, heme center, and the polarity and viscosity changes. Using the algorithm of linear discrimination analysis, the three-element sensor array realizes highly sensitive detection of proteins with a high accuracy of 100%. It can accurately distinguish proteins and their mixtures with different concentrations as well as exclude the interference from amino acids and inorganic salts, thus enabling the accurate identification of proteins in urine and serum samples. In summary, the analytical strategy is simple; the three hyperbranched AIE probes are easy to synthesize, and the sensor array features low cost, high sensitivity, good selectivity, rapid response, and good repeatability. Regarding these merits, this fluorescent sensor array may provide a platform for the prediction and diagnosis of protein-related diseases, which has great application prospects in point-of-care detection fields.

