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Yang S, Bögels BWA, Wang F, Xu C, Dou H, Mann S, Fan C, de Greef TFA. DNA as a universal chemical substrate for computing and data storage. Nat Rev Chem 2024; 8:179-194. [PMID: 38337008 DOI: 10.1038/s41570-024-00576-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2024] [Indexed: 02/12/2024]
Abstract
DNA computing and DNA data storage are emerging fields that are unlocking new possibilities in information technology and diagnostics. These approaches use DNA molecules as a computing substrate or a storage medium, offering nanoscale compactness and operation in unconventional media (including aqueous solutions, water-in-oil microemulsions and self-assembled membranized compartments) for applications beyond traditional silicon-based computing systems. To build a functional DNA computer that can process and store molecular information necessitates the continued development of strategies for computing and data storage, as well as bridging the gap between these fields. In this Review, we explore how DNA can be leveraged in the context of DNA computing with a focus on neural networks and compartmentalized DNA circuits. We also discuss emerging approaches to the storage of data in DNA and associated topics such as the writing, reading, retrieval and post-synthesis editing of DNA-encoded data. Finally, we provide insights into how DNA computing can be integrated with DNA data storage and explore the use of DNA for near-memory computing for future information technology and health analysis applications.
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Affiliation(s)
- Shuo Yang
- State Key Laboratory of Metal Matrix Composites, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
- Zhangjiang Institute for Advanced Study (ZIAS), Shanghai Jiao Tong University, Shanghai, China
| | - Bas W A Bögels
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, The Netherlands
- Computational Biology Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Fei Wang
- School of Chemistry and Chemical Engineering, New Cornerstone Science Laboratory, Frontiers Science Center for Transformative Molecules and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Can Xu
- State Key Laboratory of Metal Matrix Composites, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
- Zhangjiang Institute for Advanced Study (ZIAS), Shanghai Jiao Tong University, Shanghai, China
| | - Hongjing Dou
- State Key Laboratory of Metal Matrix Composites, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
- Zhangjiang Institute for Advanced Study (ZIAS), Shanghai Jiao Tong University, Shanghai, China
| | - Stephen Mann
- State Key Laboratory of Metal Matrix Composites, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.
- Zhangjiang Institute for Advanced Study (ZIAS), Shanghai Jiao Tong University, Shanghai, China.
- Centre for Protolife Research and Centre for Organized Matter Chemistry, School of Chemistry, University of Bristol, Bristol, UK.
- Max Planck-Bristol Centre for Minimal Biology, School of Chemistry, University of Bristol, Bristol, UK.
| | - Chunhai Fan
- School of Chemistry and Chemical Engineering, New Cornerstone Science Laboratory, Frontiers Science Center for Transformative Molecules and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China.
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acids Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
| | - Tom F A de Greef
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, The Netherlands.
- Computational Biology Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
- Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands.
- Center for Living Technologies, Eindhoven-Wageningen-Utrecht Alliance, Utrecht, The Netherlands.
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Halužan Vasle A, Moškon M. Synthetic biological neural networks: From current implementations to future perspectives. Biosystems 2024; 237:105164. [PMID: 38402944 DOI: 10.1016/j.biosystems.2024.105164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 01/03/2024] [Accepted: 02/21/2024] [Indexed: 02/27/2024]
Abstract
Artificial neural networks, inspired by the biological networks of the human brain, have become game-changing computing models in modern computer science. Inspired by their wide scope of applications, synthetic biology strives to create their biological counterparts, which we denote synthetic biological neural networks (SYNBIONNs). Their use in the fields of medicine, biosensors, biotechnology, and many more shows great potential and presents exciting possibilities. So far, many different synthetic biological networks have been successfully constructed, however, SYNBIONN implementations have been sparse. The latter are mostly based on neural networks pretrained in silico and being heavily dependent on extensive human input. In this paper, we review current implementations and models of SYNBIONNs. We briefly present the biological platforms that show potential for designing and constructing perceptrons and/or multilayer SYNBIONNs. We explore their future possibilities along with the challenges that must be overcome to successfully implement a scalable in vivo biological neural network capable of online learning.
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Affiliation(s)
- Ana Halužan Vasle
- Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia
| | - Miha Moškon
- Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.
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Peng Z, Iwabuchi S, Izumi K, Takiguchi S, Yamaji M, Fujita S, Suzuki H, Kambara F, Fukasawa G, Cooney A, Di Michele L, Elani Y, Matsuura T, Kawano R. Lipid vesicle-based molecular robots. LAB ON A CHIP 2024; 24:996-1029. [PMID: 38239102 PMCID: PMC10898420 DOI: 10.1039/d3lc00860f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
A molecular robot, which is a system comprised of one or more molecular machines and computers, can execute sophisticated tasks in many fields that span from nanomedicine to green nanotechnology. The core parts of molecular robots are fairly consistent from system to system and always include (i) a body to encapsulate molecular machines, (ii) sensors to capture signals, (iii) computers to make decisions, and (iv) actuators to perform tasks. This review aims to provide an overview of approaches and considerations to develop molecular robots. We first introduce the basic technologies required for constructing the core parts of molecular robots, describe the recent progress towards achieving higher functionality, and subsequently discuss the current challenges and outlook. We also highlight the applications of molecular robots in sensing biomarkers, signal communications with living cells, and conversion of energy. Although molecular robots are still in their infancy, they will unquestionably initiate massive change in biomedical and environmental technology in the not too distant future.
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Affiliation(s)
- Zugui Peng
- Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei-shi, Tokyo185-8588, Japan.
| | - Shoji Iwabuchi
- Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei-shi, Tokyo185-8588, Japan.
| | - Kayano Izumi
- Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei-shi, Tokyo185-8588, Japan.
| | - Sotaro Takiguchi
- Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei-shi, Tokyo185-8588, Japan.
| | - Misa Yamaji
- Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei-shi, Tokyo185-8588, Japan.
| | - Shoko Fujita
- Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei-shi, Tokyo185-8588, Japan.
| | - Harune Suzuki
- Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei-shi, Tokyo185-8588, Japan.
| | - Fumika Kambara
- Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei-shi, Tokyo185-8588, Japan.
| | - Genki Fukasawa
- School of Life Science and Technology, Tokyo Institute of Technology, Ookayama 2-12-1, Meguro-Ku, Tokyo 152-8550, Japan
| | - Aileen Cooney
- Department of Chemistry, Molecular Sciences Research Hub, Imperial College London, London W12 0BZ, UK
| | - Lorenzo Di Michele
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge CB3 0AS, UK
- Department of Chemistry, Molecular Sciences Research Hub, Imperial College London, London W12 0BZ, UK
- FabriCELL, Molecular Sciences Research Hub, Imperial College London, London W12 0BZ, UK
| | - Yuval Elani
- Department of Chemical Engineering, Imperial College London, South Kensington, London SW7 2AZ, UK
- FabriCELL, Molecular Sciences Research Hub, Imperial College London, London W12 0BZ, UK
| | - Tomoaki Matsuura
- Earth-Life Science Institute, Tokyo Institute of Technology, Ookayama 2-12-1, Meguro-Ku, Tokyo 152-8550, Japan
| | - Ryuji Kawano
- Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei-shi, Tokyo185-8588, Japan.
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