Enzyme-Based Logic Systems for Information Processing

TL;DR

This paper reviews enzyme-based biocomputing systems, focusing on logic gate networks, sensor integration, noise control, and future directions for scalable biochemical information processing.

Contribution

It provides a comprehensive overview of recent advances in enzyme-based logic networks, including experimental realizations, noise management, and future research avenues.

Findings

First multi-gate enzyme networks realized experimentally

Strategies for noise reduction in enzyme logic gates

Potential for scalable biochemical information processing

Abstract

We review enzymatic systems which involve biocatalytic reactions utilized for information processing (biocomputing). Extensive ongoing research in biocomputing, mimicking Boolean logic gates has been motivated by potential applications in biotechnology and medicine. Furthermore, novel sensor concepts have been contemplated with multiple inputs processed biochemically before the final output is coupled to transducing "smart-material" electrodes and other systems. These applications have warranted recent emphasis on networking of biocomputing gates. First few-gate networks have been experimentally realized, including coupling, for instance, to signal-responsive electrodes for signal readout. In order to achieve scalable, stable network design and functioning, considerations of noise propagation and control have been initiated as a new research direction. Optimization of single enzyme-based gates for avoiding analog noise amplification has been explored, as were certain network-optimization concepts. We review and exemplify these developments, as well as offer an outlook for possible future research foci. The latter include design and uses of non-Boolean network elements, e.g., filters, as well as other developments motivated by potential novel sensor and biotechnology applications.