Optimization of a Concanavalin A-based glucose sensor using fluorescence anisotropy.

To date, the dependent nature of the recognition and transduction mechanisms in optical glucose sensors based upon Concanavalin A (ConA) has tended to prevent the sensors' full potential from being realized. In this paper, these mechanisms are independently optimized for a given assay configuration in order to decrease the predictive error of a ConA-based glucose sensor and to give a more accurate demonstration of its potential. To this end, we used fluorescence anisotropy as the transduction mechanism to determine the binding of ConA to 4 kDa FITC-dextran by measuring the change in the rotational correlation lifetime between the bound and unbound populations. By tracking the fluorescence anisotropy of this ligand, the ranges of ConA and 4 kDa FITC-dextran concentrations capable of being explored were not limited by the transduction mechanism. Using predetermined association constants, the binding responses to physiological glucose concentrations were predicted for different assay configurations, and experimentally collected fluorescence anisotropy data displayed the predicted trends for these assay configurations. From the experimental results, a calibration fit was generated for the optimized assay configuration to predict the glucose concentrations using the fluorescence anisotropy. This optimized assay displayed a mean standard error of prediction of 7.5 mg/dL (0-300 mg/dL), and 100% of the data points fell within clinically acceptable zones (A and B) upon the Clarke Error Grid Analysis. This indicates that, by independently optimizing the recognition and transduction mechanisms for the final assay configuration, the sensitivity of a competitive binding chemistry using ConA can be appropriately configured for continuous glucose monitoring applications.