Wang, T., Fan, X., Ma, Y., Li, Z., & He, C. (2024). Dual enzymes proteinosome with cascade activity for ultrasensitive glucose biosensing. Sensors and Actuators B: Chemical, 402, 135067. https://doi.org/10.1016/j.snb.2023.135067
Abstract:
Catalytic cascades derived from the combination of multiple enzymes with efficient catalytic activity and high
selectivity have attracted widespread attention in biosensing and biomedical applications. A key consideration in
the development of cascade reaction systems is the combination of multiple enzymes to improve overall catalytic
performance. Inspired by natural protein self-assembly, herein, proteinosomes formed by enzyme-surfactant
complexes based on an interfacial assembly strategy are developed and they exhibit significant enhanced activity via cascade reaction of glucose oxidase (GOX) and horseradish peroxidase (HRP) that are located in
proximity. The proteinosomes not only exhibit significantly elevated stability and reusability, but also possess
enhanced cascade catalytic performance. These enhanced activities can be explained on the basis of the proximity effect of multiple enzymes within proteinosomes. Moreover, we employed highly efficient and reusability
dual-enzyme-based proteinosomes to demonstrate the ultrasensitive detection of glucose, achieving a detection
limit as low as 1.08 µM. Finally, the proteinosomes can be immobilized in a test strip for easy and fast glucose
detection. Due to their ultra-sensitive detection limit, they can be used for non-invasive glucose detection. They
can accurately assess glucose levels in saliva, yielding results highly congruent with those from commercially
available assay kits. We further indicate the rapid capability of our system to detect glucose, as compared to
commercial glucose kit. These finds demonstrate the potential of the test strip as a promising tool for daily
glucose monitoring, and the facile approach presents an inventive solution for test strip development.
License type:
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Funding Info:
This research is supported by the Agency for Science, Technology and Research (A*STAR) of Singapore