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Lookup NU author(s): Hyeyun Jung, Ethan Collinson, Alexander Hawes, Dr Harold FellermannORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
This review article poses the overarching question: Can complex dynamic DNA nanodevices based on strand displacement reactions be operated within, and can they inter-operate with living cells? Reviewing recent literature from DNA nanotechnology and molecular computing we explore the background, state-of-the-art, and current challenges towards intra-cellular strand displacement reactions. We first introduce the underlying principles, seminal achievements and current limitations of DNA strand displacement circuits. We discuss the potential for biological molecules to serve as inputs to DNA nanocircuits. This comprises cellular nucleic acids such as messenger RNA and microRNA, as well as other biological molecules which can trigger DNA nanodevices through the aid of aptamer-binding. We investigate challenges and recent successes of operating DNA strand displacement devices in cellular lysates as well as delivering or integrating DNA nanodevices into cells. Finally, we discuss biocompatible models of computation, with particular emphasis on molecular neural networks, which can be seamlessly mapped onto DNA strand displacement networks and offer promise to mimic the self-organizing, adaptive, and fault-tolerant nature of living organisms. Taking the efforts of numerous research groups in DNA nanotechnology and molecular computing together, the review identifies remaining challenges and future directions toward the creation of programmable intra-cellular DNA nanomachines able to interrogate biological signals, perform complex computation over acquired information and in response actuate on their biological environment—similar to the interactions of a robot with its environment.
Author(s): Jung H, Collinson E, Hawes AP, Fellermann H
Publication type: Article
Publication status: Published
Journal: Intelligent Computing
Year: 2025
Volume: 4
Online publication date: 04/03/2025
Acceptance date: 05/01/2025
Date deposited: 27/02/2025
ISSN (electronic): 2771-5892
Publisher: AAAS
URL: https://doi.org/10.34133/icomputing.0112
DOI: 10.34133/icomputing.0112
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