An optimized quantum dot-ligand system for biosensing applications: Evaluation as a glucose biosensor

A highly active quantum dot (QD)-ligand system is proposed for biosensing applications based on a novel optimization technique. The optimization is here applied to nine QD-ligand combinations, made out of three core–shell QDs (CdSe-CdS, CdSe-ZnS and CdS-ZnS) and three mercaptothiol ligands (mercaptoacetic acid, mercaptopropionic acid and glutathione). The nine QD-ligand systems are synthesized by the microemulsion extraction technique (published earlier by our group), at room temperature. The optimization parameters are the three critical properties relevant to glucose biosensing; Sensitivity to H2O2 concentration, Initial enzyme activity and Stability of enzyme activity over four weeks. A scaling factor, Performance Index (PI), is modeled here for quantitative comparison between the nine systems. The optimized QD-ligand system, conjugated with Glucose Oxidase (OQLG), is evaluated for Michaelis–Menten kinetics. The Michaelis constant Km is evaluated to be 0.28 mM, indicating very high activity towards glucose. The OQLG system is then calibrated with known glucose concentrations to give a linear relationship between relative fluorescence intensity and glucose concentration. The linear model developed is then employed for estimating glucose levels in ten unknown blood (plasma) samples. The proposed optimization technique is quite generic and can be extended to other ligands too. The resultant OQLG system seems to be a promising platform for devising a novel Integrated Multi-analyte Nanobiosensor.

Graphical abstractThe scaled values for the three parameters (SI, EA and ESC) of the nine QD-ligand systems. The resultant PI values are shown at the top of each system.Figure optionsDownload full-size imageDownload as PowerPoint slideHighlights► Core–shell quantum dots (QDs) prepared by a simple room-temperature microemulsion method. ► Extraction of these QDs into PBS by a green-chemistry route published by our group earlier. ► An optimization of nine core–shell QDs based on three critical parameters relevant to glucose biosensing: sensitivity, enzyme activity and enzyme stability. ► The optimized QD-enzyme systems evaluated for Michaelis–Menten kinetics. ► The optimized QD-enzyme system now employed for glucose sensing in unknown patient blood samples and validation with the laboratory data.