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Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
Published on: March 9, 2019
Set-reset flip-flop memory based on enzyme reactions: toward memory systems controlled by biochemical pathways.
Marcos Pita1, Guinevere Strack, Kevin MacVittie
1Department of Chemistry and Biomolecular Science, and NanoBio Laboratory (NABLAB), Clarkson University, Potsdam, New York 13699-5810, USA.
The Journal of Physical Chemistry. B
|November 13, 2009
Summary
This study introduces an enzyme-based flip-flop memory system using horseradish peroxidase and diaphorase. This biocomputing system encodes biochemical signals into optical or electrochemical outputs for advanced biosensors.
Area of Science:
- Biochemistry
- Biotechnology
- Biocomputing
Background:
- Enzyme-based systems offer potential for biocomputing and biosensing.
- Developing reliable memory elements is crucial for complex biochemical signal processing.
Purpose of the Study:
- To design and demonstrate an enzyme-based set-reset flip-flop memory system.
- To enable the transformation of biochemical signals into readable outputs.
- To explore applications in multisignal biosensors and biocomputing.
Main Methods:
- Utilized horseradish peroxidase and diaphorase for redox reactions.
- Employed 2,6-dichloroindophenol or ferrocyanide as redox species.
- Activated biocatalysis using hydrogen peroxide (H2O2) and NADH.
- Transformed biochemical signals (glucose, lactate, ethanol) into redox states.
- Read out system states optically and electrochemically.
- Encoded ASCII characters to demonstrate information storage.
Main Results:
- Successfully designed and operated an enzyme-based flip-flop memory system.
- Demonstrated the conversion of various biochemical inputs into distinct redox states.
- Achieved information encoding, exemplified by encoding "Clarkson" and "University".
- Showcased the system's potential for complex data processing.
Conclusions:
- The developed flip-flop system enhances enzyme-based biocomputing capabilities.
- It improves the performance of multisignal biosensors and actuators.
- Envisaged as foundational elements for future implantable biomedical devices controlled by physiological conditions.
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