Switchable Electrode Controlled by Enzyme Logic Network System: Approaching Physiologically Regulated Bioelectronics

The logic network composed of three enzymes (alcohol dehydrogenase, glucose dehydrogenase, and glucose oxidase) operating in concert as four concatenated logic gates (AND/OR), was designed to process four different chemical input signals (NADH, acetaldehyde, glucose, and oxygen). The cascade of biochemical reactions culminated in pH changes controlled by the pattern of the applied biochemical input signals. The successful set of inputs produced gluconic acid as the final product and yielded an acidic medium, lowering the pH of a solution from its initial value of pH 6-7 to the final value of ca. 4. The whole set of the input signal combinations included 16 variants resulting in different output signals. Those that corresponded to the logic output 1, according to the Boolean logic encoded in the logic circuitry, resulted in the acidic medium. The pH changes produced in situ were coupled with a pH-sensitive polymer-brush-functionalized electrode, resulting in the interface switching from the OFF state, when the electrochemical reactions are inhibited, to the ON state, when the interface is electrochemically active. Soluble [Fe(CN)(6)](3-/4-) was used as an external redox probe to analyze the state of the interface and to follow the changes produced in situ by the enzyme logic network, depending on the pattern of the applied biochemical signals. The chemical signals processed by the enzyme logic system and transduced by the sensing interface were read out by electrochemical means (cyclic voltammetry and Faradaic impedance spectroscopy). This read out step features a sigmoid processing of the signals that provides filtering and significantly suppresses errors. Coupling between signal-processing enzyme logic networks and electronic transducers will allow future smart bioelectronic devices to respond to immediate physiological changes and provide autonomous signaling/actuation depending on the concentration patterns of the physiological markers.