Reservoir Computing-Based Glucose Sensing With an Enzymatic Reaction Network.

Area of Science:

• Biochemical Engineering
• Systems Biology
• Biosensors

Background:

• Living systems process environmental information for survival.
• Enzymatic reactions can be harnessed for biosensing applications.

Purpose of the Study:

• To develop a scalable protease-peptide-based reservoir sensor for glucose detection.
• To investigate the information processing capabilities of an enzymatic network.

Main Methods:

• Utilized glucose oxidase (GOx) to convert glucose into a pH signal.
• Investigated the impact of pH changes on a protease-peptide network.
• Applied reservoir computation principles to analyze sensor output.

Main Results:

• The sensor detected glucose stimuli by altering protease activity via pH changes.
• Demonstrated linear sensing and binary switch-like responses to glucose concentrations.
• Showcased response to dynamic glucose inputs, including pulse periodicity and amplitude variations.

Conclusions:

• Developed a versatile enzymatic reservoir sensor for glucose.
• The system exhibits information processing capabilities inspired by biological systems.
• Potential applications in dynamic glucose monitoring and complex signal processing.