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A Multilayer Microfluidic Platform for the Conduction of Prolonged Cell-Free Gene Expression

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Published on: October 6, 2019

Biofuel cell controlled by enzyme logic network--approaching physiologically regulated devices.

Tsz Kin Tam¹, Marcos Pita, Maryna Ornatska

¹Department of Chemistry and Biomolecular Science, and NanoBio Laboratory (NABLAB), Clarkson University, Potsdam, NY 13699-5810, USA.

Bioelectrochemistry (Amsterdam, Netherlands)

|April 9, 2009

Summary

A novel biofuel cell acts as a smart switch, controlled by an enzyme logic network. This biocomputing system processes chemical signals to reversibly turn the cell ON and OFF, enabling new bioelectronic devices.

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Area of Science:

Bioelectronics
Biocomputing
Enzyme-based logic systems

Background:

Traditional biofuel cells lack sophisticated control mechanisms.
Enzyme logic networks offer potential for complex signal processing in bio-devices.

Purpose of the Study:

To design a "smart" biofuel cell switchable ON and OFF using an enzyme logic network.
To demonstrate reversible control of biofuel cell output via biocomputing principles.

Main Methods:

Constructed a biocomputing system with four enzymes (ADH, AGS, INV, GDH) processing chemical inputs (NADH, acetaldehyde, maltose, sucrose).
Modeled enzyme reactions as concatenated AND/OR logic gates to process input signals.
Utilized a pH-sensitive cathode activated by gluconic acid production to switch the biofuel cell ON.
Employed urease to revert pH and switch the cell OFF.

Main Results:

The enzyme logic network successfully processed specific chemical signal patterns.
Formation of gluconic acid led to an acidic pH, activating the biofuel cell and increasing power output.
Reversible ON/OFF switching was achieved by controlling pH with enzymatic reactions.

Conclusions:

Developed a switchable biofuel cell controlled by a biocomputing system.
Demonstrated a new class of bioelectronic devices integrating biocomputing for functional control.
Highlights potential for advanced bioelectronic applications through enzyme logic networks.