Chemical programmability in food-safety nanobiosensing: a pathway-centric framework for autonomous analytical systems

Area of Science:

• Analytical Chemistry
• Biosensing Technology
• Food Science

Background:

• Food-safety sensors exhibit high analytical sensitivity in labs but fail in complex food matrices.
• This performance gap stems from matrix components interfering with signal-transduction pathways.
• Competing recognition, transduction, and output routes lead to systematic misidentification.

Purpose of the Study:

• Introduce the concept of chemical programmability for food-safety sensors.
• Provide a unified framework for designing robust, adaptive, and autonomous food-safety sensing systems.
• Shift focus from sensitivity optimization to pathway controllability.

Main Methods:

• Define chemical programmability as rational control of sensing pathways via pre-encoded chemical instructions.
• Establish a 3x2 programmability matrix (programming node vs. timing).
• Discuss strategies in molecular-layer recognition, material-layer energy/electron-transfer, and system-layer signal conversion.

Main Results:

• Chemical programmability enables control over signal generation, transduction, amplification, and readout.
• Energy landscape engineering is the foundation, favoring target pathways by modulating energy barriers.
• Diverse strategies share a common physical basis in controlling competing pathways.

Conclusions:

• Controlling signal-transduction pathways is key to overcoming matrix effects in food-safety sensors.
• Chemical programmability offers a framework for developing reliable and adaptive food-safety detection systems.
• Future food-safety sensors should prioritize pathway controllability for real-world applications.