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Zhang J, Chen M, Lin G, Liu S, Yang C, Song Y. Advanced DNA Amplification for Efficient Data Storage. ACS APPLIED MATERIALS & INTERFACES 2024. [PMID: 39254000 DOI: 10.1021/acsami.4c12102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/11/2024]
Abstract
DNA amplification technologies have significantly advanced biotechnology, particularly in DNA storage. However, adaptation of these technologies to DNA storage poses substantial challenges. Key bottlenecks include achieving high throughput to manage large data sets, ensuring rapid and efficient DNA amplification, and minimizing bias to maintain data fidelity. This perspective begins with an overview of natural and artificial amplification strategies, such as polymerase chain reaction and isothermal amplification, highlighting their respective advantages and limitations. It then explores the prospective applications of these techniques in DNA storage, emphasizing the need to optimize protocols for scalability and robustness in handling diverse digital data. Concurrently, we identify promising avenues, including advancements in enzymatic processes and novel amplification methodologies, poised to mitigate existing constraints and propel the field forward. Ultimately, we provide insights into how to utilize advanced DNA amplification strategies poised to revolutionize the efficiency and feasibility of data storage, ushering in enhanced approaches to data retrieval in the digital age.
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Affiliation(s)
- Jialu Zhang
- MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, Fujian 361005, People's Republic of China
- School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China
| | - Mingying Chen
- MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, Fujian 361005, People's Republic of China
| | - Guihong Lin
- MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, Fujian 361005, People's Republic of China
| | - Sinong Liu
- MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, Fujian 361005, People's Republic of China
| | - Chaoyong Yang
- MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, Fujian 361005, People's Republic of China
- Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, People's Republic of China
| | - Yanling Song
- MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Xiamen University, Xiamen, Fujian 361005, People's Republic of China
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2
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Jo S, Shin H, Joe SY, Baek D, Park C, Chun H. Recent progress in DNA data storage based on high-throughput DNA synthesis. Biomed Eng Lett 2024; 14:993-1009. [PMID: 39220021 PMCID: PMC11362454 DOI: 10.1007/s13534-024-00386-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 04/24/2024] [Accepted: 04/26/2024] [Indexed: 09/04/2024] Open
Abstract
DNA data storage has emerged as a solution for storing massive volumes of data by utilizing nucleic acids as a digital information medium. DNA offers exceptionally high storage density, long durability, and low maintenance costs compared to conventional storage media such as flash memory and hard disk drives. DNA data storage consists of the following steps: encoding, DNA synthesis (i.e., writing), preservation, retrieval, DNA sequencing (i.e., reading), and decoding. Out of these steps, DNA synthesis presents a bottleneck due to imperfect coupling efficiency, low throughput, and excessive use of organic solvents. Overcoming these challenges is essential to establish DNA as a viable data storage medium. In this review, we provide the overall process of DNA data storage, presenting the recent progress of each step. Next, we examine a detailed overview of DNA synthesis methods with an emphasis on their limitations. Lastly, we discuss the efforts to overcome the constraints of each method and their prospects.
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Affiliation(s)
- Seokwoo Jo
- Department of Biomedical Engineering, Korea University, 466 Hana Science Hall, Seoul, 02841 Korea
- Interdisciplinary Program in Precision Public Health, Korea University, 466 Hana Science Hall, Seoul, 02841 Korea
| | - Haewon Shin
- Department of Biomedical Engineering, Korea University, 466 Hana Science Hall, Seoul, 02841 Korea
- Interdisciplinary Program in Precision Public Health, Korea University, 466 Hana Science Hall, Seoul, 02841 Korea
| | - Sung-yune Joe
- Department of Biomedical Engineering, Korea University, 466 Hana Science Hall, Seoul, 02841 Korea
- Interdisciplinary Program in Precision Public Health, Korea University, 466 Hana Science Hall, Seoul, 02841 Korea
| | - David Baek
- Department of Biomedical Engineering, Korea University, 466 Hana Science Hall, Seoul, 02841 Korea
- Interdisciplinary Program in Precision Public Health, Korea University, 466 Hana Science Hall, Seoul, 02841 Korea
| | - Chaewon Park
- Department of Biomedical Engineering, Korea University, 466 Hana Science Hall, Seoul, 02841 Korea
- Interdisciplinary Program in Precision Public Health, Korea University, 466 Hana Science Hall, Seoul, 02841 Korea
| | - Honggu Chun
- Department of Biomedical Engineering, Korea University, 466 Hana Science Hall, Seoul, 02841 Korea
- Interdisciplinary Program in Precision Public Health, Korea University, 466 Hana Science Hall, Seoul, 02841 Korea
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3
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Song L, Zuo X, Li M. Concept and Development of Algebraic Topological Framework Nucleic Acids. Chempluschem 2024; 89:e202300760. [PMID: 38529703 DOI: 10.1002/cplu.202300760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 03/06/2024] [Accepted: 03/25/2024] [Indexed: 03/27/2024]
Abstract
Nucleic acids are considered as promising materials for developing exquisite nanostructures from one to three dimensions. The advances of DNA nanotechnology facilitate ingenious design of DNA nanostructures with diverse shapes and sizes. Especially, the algebraic topological framework nucleic acids (ATFNAs) are functional DNA nanostructures that engineer guest molecules (e. g., nucleic acids, proteins, small molecules, and nanoparticles) stoichiometrically and spatially. The intrinsic precise properties and tailorable functionalities of ATFNAs hold great promise for biological applications, such as cell recognition and immunotherapy. This Perspective highlights the concept and development of precisely assembled ATFNAs, and outlines the new frontiers and opportunities for exploiting the structural advantages of ATFNAs for biological applications.
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Affiliation(s)
- Lu Song
- Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 200127, Shanghai, China
| | - Xiaolei Zuo
- Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 200127, Shanghai, China
| | - Min Li
- Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 200127, Shanghai, China
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4
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Prince E, Cheng HF, Banal JL, Johnson JA. Reversible Nucleic Acid Storage in Deconstructable Glassy Polymer Networks. J Am Chem Soc 2024; 146:17066-17074. [PMID: 38865160 DOI: 10.1021/jacs.4c01925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2024]
Abstract
The rapid decline in DNA sequencing costs has fueled the demand for nucleic acid collection to unravel genomic information, develop treatments for genetic diseases, and track emerging biological threats. Current approaches to maintaining these nucleic acid collections hinge on continuous electricity for maintaining low-temperature and intricate cold-chain logistics. Inspired by the millennia-long preservation of fossilized biological specimens in calcified minerals or glassy amber, we present Thermoset-REinforced Xeropreservation (T-REX): a method for storing DNA in deconstructable glassy polymer networks. Key to T-REX is the development of polyplexes for nucleic acid encapsulation, streamlining the transfer of DNA from aqueous to organic phases, replete with initiators, monomers, cross-linkers, and thionolactone-based cleavable comonomers required to form the polymer networks. This process successfully encapsulates DNA that spans different length scales, from tens of bases to gigabases, in a matter of hours compared to days with traditional silica-based encapsulation. Further, T-REX permits the extraction of DNA using comparatively benign reagents, unlike the hazardous hydrofluoric acid required for recovery from silica. T-REX provides a path toward low-cost, time-efficient, and long-term nucleic acid preservation for synthetic biology, genomics, and digital information storage, potentially overcoming traditional low-temperature storage challenges.
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Affiliation(s)
- Elisabeth Prince
- Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
| | - Ho Fung Cheng
- Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
| | - James L Banal
- Cache DNA, Inc., 733 Industrial Road, San Carlos, California 94070, United States
| | - Jeremiah A Johnson
- Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
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5
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Wang Q, Zhang S, Li Y. Efficient DNA Coding Algorithm for Polymerase Chain Reaction Amplification Information Retrieval. Int J Mol Sci 2024; 25:6449. [PMID: 38928155 PMCID: PMC11204281 DOI: 10.3390/ijms25126449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Revised: 06/02/2024] [Accepted: 06/07/2024] [Indexed: 06/28/2024] Open
Abstract
Polymerase Chain Reaction (PCR) amplification is widely used for retrieving information from DNA storage. During the PCR amplification process, nonspecific pairing between the 3' end of the primer and the DNA sequence can cause cross-talk in the amplification reaction, leading to the generation of interfering sequences and reduced amplification accuracy. To address this issue, we propose an efficient coding algorithm for PCR amplification information retrieval (ECA-PCRAIR). This algorithm employs variable-length scanning and pruning optimization to construct a codebook that maximizes storage density while satisfying traditional biological constraints. Subsequently, a codeword search tree is constructed based on the primer library to optimize the codebook, and a variable-length interleaver is used for constraint detection and correction, thereby minimizing the likelihood of nonspecific pairing. Experimental results demonstrate that ECA-PCRAIR can reduce the probability of nonspecific pairing between the 3' end of the primer and the DNA sequence to 2-25%, enhancing the robustness of the DNA sequences. Additionally, ECA-PCRAIR achieves a storage density of 2.14-3.67 bits per nucleotide (bits/nt), significantly improving storage capacity.
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Affiliation(s)
| | - Shufang Zhang
- School of Electrical Automation and Information Engineering, Tianjin University, Tianjin 300072, China
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6
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Yu M, Tang X, Li Z, Wang W, Wang S, Li M, Yu Q, Xie S, Zuo X, Chen C. High-throughput DNA synthesis for data storage. Chem Soc Rev 2024; 53:4463-4489. [PMID: 38498347 DOI: 10.1039/d3cs00469d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/20/2024]
Abstract
With the explosion of digital world, the dramatically increasing data volume is expected to reach 175 ZB (1 ZB = 1012 GB) in 2025. Storing such huge global data would consume tons of resources. Fortunately, it has been found that the deoxyribonucleic acid (DNA) molecule is the most compact and durable information storage medium in the world so far. Its high coding density and long-term preservation properties make itself one of the best data storage carriers for the future. High-throughput DNA synthesis is a key technology for "DNA data storage", which encodes binary data stream (0/1) into quaternary long DNA sequences consisting of four bases (A/G/C/T). In this review, the workflow of DNA data storage and the basic methods of artificial DNA synthesis technology are outlined first. Then, the technical characteristics of different synthesis methods and the state-of-the-art of representative commercial companies, with a primary focus on silicon chip microarray-based synthesis and novel enzymatic DNA synthesis are presented. Finally, the recent status of DNA storage and new opportunities for future development in the field of high-throughput, large-scale DNA synthesis technology are summarized.
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Affiliation(s)
- Meng Yu
- Institute of Medical Chips, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China.
- School of Microelectronics, Shanghai University, 201800, Shanghai, China
- Shanghai Industrial μTechnology Research Institute, 201800, Shanghai, China
| | - Xiaohui Tang
- Institute of Medical Chips, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China.
- Shanghai Industrial μTechnology Research Institute, 201800, Shanghai, China
| | - Zhenhua Li
- Institute of Medical Chips, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China.
- Shanghai Industrial μTechnology Research Institute, 201800, Shanghai, China
| | - Weidong Wang
- Shanghai Industrial μTechnology Research Institute, 201800, Shanghai, China
| | - Shaopeng Wang
- Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 200127, Shanghai, China.
| | - Min Li
- Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 200127, Shanghai, China.
| | - Qiuliyang Yu
- Shenzhen Key Laboratory for the Intelligent Microbial Manufacturing of Medicines, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, 518055, Shenzhen, China
| | - Sijia Xie
- Institute of Medical Chips, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China.
- School of Microelectronics, Shanghai University, 201800, Shanghai, China
- Shanghai Industrial μTechnology Research Institute, 201800, Shanghai, China
| | - Xiaolei Zuo
- Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 200127, Shanghai, China.
| | - Chang Chen
- Institute of Medical Chips, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China.
- School of Microelectronics, Shanghai University, 201800, Shanghai, China
- Shanghai Industrial μTechnology Research Institute, 201800, Shanghai, China
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 200050, Shanghai, China
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Cao B, Zheng Y, Shao Q, Liu Z, Xie L, Zhao Y, Wang B, Zhang Q, Wei X. Efficient data reconstruction: The bottleneck of large-scale application of DNA storage. Cell Rep 2024; 43:113699. [PMID: 38517891 DOI: 10.1016/j.celrep.2024.113699] [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: 08/09/2023] [Revised: 11/15/2023] [Accepted: 01/05/2024] [Indexed: 03/24/2024] Open
Abstract
Over the past decade, the rapid development of DNA synthesis and sequencing technologies has enabled preliminary use of DNA molecules for digital data storage, overcoming the capacity and persistence bottlenecks of silicon-based storage media. DNA storage has now been fully accomplished in the laboratory through existing biotechnology, which again demonstrates the viability of carbon-based storage media. However, the high cost and latency of data reconstruction pose challenges that hinder the practical implementation of DNA storage beyond the laboratory. In this article, we review existing advanced DNA storage methods, analyze the characteristics and performance of biotechnological approaches at various stages of data writing and reading, and discuss potential factors influencing DNA storage from the perspective of data reconstruction.
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Affiliation(s)
- Ben Cao
- School of Computer Science and Technology, Dalian University of Technology, Lingshui Street, Dalian, Liaoning 116024, China; Centre for Frontier AI Research, Agency for Science, Technology, and Research (A(∗)STAR), 1 Fusionopolis Way, Singapore 138632, Singapore
| | - Yanfen Zheng
- School of Computer Science and Technology, Dalian University of Technology, Lingshui Street, Dalian, Liaoning 116024, China
| | - Qi Shao
- Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Xuefu Street, Dalian, Liaoning 116622, China
| | - Zhenlu Liu
- Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Xuefu Street, Dalian, Liaoning 116622, China
| | - Lei Xie
- Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Xuefu Street, Dalian, Liaoning 116622, China
| | - Yunzhu Zhao
- Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Xuefu Street, Dalian, Liaoning 116622, China
| | - Bin Wang
- Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Xuefu Street, Dalian, Liaoning 116622, China
| | - Qiang Zhang
- School of Computer Science and Technology, Dalian University of Technology, Lingshui Street, Dalian, Liaoning 116024, China.
| | - Xiaopeng Wei
- School of Computer Science and Technology, Dalian University of Technology, Lingshui Street, Dalian, Liaoning 116024, China
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Berleant JD, Banal JL, Rao DK, Bathe M. Scalable search of massively pooled nucleic acid samples enabled by a molecular database query language. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.12.24305660. [PMID: 38699348 PMCID: PMC11064994 DOI: 10.1101/2024.04.12.24305660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
The surge in nucleic acid analytics requires scalable storage and retrieval systems akin to electronic databases used to organize digital data. Such a system could transform disease diagnosis, ecological preservation, and molecular surveillance of biothreats. Current storage systems use individual containers for nucleic acid samples, requiring single-sample retrieval that falls short compared with digital databases that allow complex and combinatorial data retrieval on aggregated data. Here, we leverage protective microcapsules with combinatorial DNA labeling that enables arbitrary retrieval on pooled biosamples analogous to Structured Query Languages. Ninety-six encapsulated pooled mock SARS-CoV-2 genomic samples barcoded with patient metadata are used to demonstrate queries with simultaneous matches to sample collection date ranges, locations, and patient health statuses, illustrating how such flexible queries can be used to yield immunological or epidemiological insights. The approach applies to any biosample database labeled with orthogonal barcodes, enabling complex post-hoc analysis, for example, to study global biothreat epidemiology.
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Affiliation(s)
- Joseph D. Berleant
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - James L. Banal
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Present address: Cache DNA, Inc. 733 Industrial Rd., San Carlos, CA 94070 USA
| | | | - Mark Bathe
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02139 USA
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Hou Z, Qiang W, Wang X, Chen X, Hu X, Han X, Shen W, Zhang B, Xing P, Shi W, Dai J, Huang X, Zhao G. "Cell Disk" DNA Storage System Capable of Random Reading and Rewriting. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2305921. [PMID: 38332565 PMCID: PMC11022697 DOI: 10.1002/advs.202305921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 11/23/2023] [Indexed: 02/10/2024]
Abstract
DNA has emerged as an appealing material for information storage due to its great storage density and durability. Random reading and rewriting are essential tasks for practical large-scale data storage. However, they are currently difficult to implement simultaneously in a single DNA-based storage system, strongly limiting their practicability. Here, a "Cell Disk" storage system is presented, achieving high-density in vivo DNA data storage that enables both random reading and rewriting. In this system, each yeast cell is used as a chamber to store information, similar to a "disk block" but with the ability to self-replicate. Specifically, each genome of yeast cell has a customized CRISPR/Cas9-based "lock-and-key" module inserted, which allows selective retrieval, erasure, or rewriting of the targeted cell "block" from a pool of cells ("disk"). Additionally, a codec algorithm with lossless compression ability is developed to improve the information density of each cell "block". As a proof of concept, target-specific reading and rewriting of the compressed data from a mimic cell "disk" comprising up to 105 "blocks" are demonstrated and achieve high specificity and reliability. The "Cell Disk" system described here concurrently supports random reading and rewriting, and it should have great scalability for practical data storage use.
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Affiliation(s)
- Zhaohua Hou
- School of Ecology and EnvironmentNorthwestern Polytechnical University1 Dongxiang Road, Chang'an DistrictXi'anShaanxi710129P. R. China
| | - Wei Qiang
- Shenzhen Key Laboratory of Synthetic GenomicsGuangdong Provincial Key Laboratory of Synthetic GenomicsShenzhen Institute of Synthetic BiologyShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhenGuangdong518055P. R. China
| | - Xiangxiang Wang
- School of Ecology and EnvironmentNorthwestern Polytechnical University1 Dongxiang Road, Chang'an DistrictXi'anShaanxi710129P. R. China
| | - Xiaoxu Chen
- School of Ecology and EnvironmentNorthwestern Polytechnical University1 Dongxiang Road, Chang'an DistrictXi'anShaanxi710129P. R. China
| | - Xin Hu
- School of Ecology and EnvironmentNorthwestern Polytechnical University1 Dongxiang Road, Chang'an DistrictXi'anShaanxi710129P. R. China
| | - Xuye Han
- School of Ecology and EnvironmentNorthwestern Polytechnical University1 Dongxiang Road, Chang'an DistrictXi'anShaanxi710129P. R. China
| | - Wenlu Shen
- School of Ecology and EnvironmentNorthwestern Polytechnical University1 Dongxiang Road, Chang'an DistrictXi'anShaanxi710129P. R. China
| | - Bing Zhang
- School of Ecology and EnvironmentNorthwestern Polytechnical University1 Dongxiang Road, Chang'an DistrictXi'anShaanxi710129P. R. China
| | - Peng Xing
- School of Ecology and EnvironmentNorthwestern Polytechnical University1 Dongxiang Road, Chang'an DistrictXi'anShaanxi710129P. R. China
| | - Wenping Shi
- School of Ecology and EnvironmentNorthwestern Polytechnical University1 Dongxiang Road, Chang'an DistrictXi'anShaanxi710129P. R. China
| | - Junbiao Dai
- Shenzhen Key Laboratory of Synthetic GenomicsGuangdong Provincial Key Laboratory of Synthetic GenomicsShenzhen Institute of Synthetic BiologyShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhenGuangdong518055P. R. China
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhenP. R. China
| | - Xiaoluo Huang
- Shenzhen Key Laboratory of Synthetic GenomicsGuangdong Provincial Key Laboratory of Synthetic GenomicsShenzhen Institute of Synthetic BiologyShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhenGuangdong518055P. R. China
| | - Guanghou Zhao
- School of Ecology and EnvironmentNorthwestern Polytechnical University1 Dongxiang Road, Chang'an DistrictXi'anShaanxi710129P. R. China
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10
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Huang X, Cui J, Qiang W, Ye J, Wang Y, Xie X, Li Y, Dai J. Storage-D: A user-friendly platform that enables practical and personalized DNA data storage. IMETA 2024; 3:e168. [PMID: 38882485 PMCID: PMC11170965 DOI: 10.1002/imt2.168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 10/30/2023] [Accepted: 11/14/2023] [Indexed: 06/18/2024]
Abstract
Deoxyribonucleic acid (DNA) has been suggested as a very promising medium for data storage in recent years. Although numerous studies have advocated for DNA data storage, its practical application remains obscure and there is a lack of a user-oriented platform. Here, we developed a DNA data storage platform, named Storage-D, which allows users to convert their data into DNA sequences of any length and vice versa by selecting algorithms, error-correction, random-access, and codec pin strategies in terms of their own choice. It incorporates a newly designed "Wukong" algorithm, which provides over 20 trillion codec pins for data privacy use. This algorithm can also control GC content to the selected standard, as well as adjust the homopolymer run length to a defined level, while maintaining a high coding potential of ~1.98 bis/nt, allowing it to outperform previous algorithms. By connecting to a commercial DNA synthesis and sequencing platform with "Storage-D," we successfully stored "Diagnosis and treatment protocol for COVID-19 patients" into 200 nt oligo pools in vitro, and 500 bp genes in vivo which replicated in both normal and extreme bacteria. Together, this platform allows for practical and personalized DNA data storage, potentially with a wide range of applications.
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Affiliation(s)
- Xiaoluo Huang
- Shenzhen Key Laboratory of Synthetic Genomics Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Shenzhen China
| | - Junting Cui
- Shenzhen Key Laboratory of Synthetic Genomics Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Shenzhen China
| | - Wei Qiang
- Shenzhen Key Laboratory of Synthetic Genomics Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Shenzhen China
| | - Jianwen Ye
- School of Biology and Biological Engineering South China University of Technology Guangzhou China
| | - Yu Wang
- Shenzhen Key Laboratory of Synthetic Genomics Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Shenzhen China
| | - Xinying Xie
- School of Biology and Biological Engineering South China University of Technology Guangzhou China
| | - Yuanzhen Li
- Shenzhen Key Laboratory of Synthetic Genomics Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Shenzhen China
| | - Junbiao Dai
- Shenzhen Key Laboratory of Synthetic Genomics Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Shenzhen China
- Shenzhen Branch Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences Shenzhen China
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11
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Li Y, Zhang H, Chen Y, Shen Y, Ping Z. DNA Bloom Filter enables anti-contamination and file version control for DNA-based data storage. Brief Bioinform 2024; 25:bbae125. [PMID: 38555478 PMCID: PMC10981766 DOI: 10.1093/bib/bbae125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 02/09/2024] [Accepted: 02/27/2024] [Indexed: 04/02/2024] Open
Abstract
DNA storage is one of the most promising ways for future information storage due to its high data storage density, durable storage time and low maintenance cost. However, errors are inevitable during synthesizing, storing and sequencing. Currently, many error correction algorithms have been developed to ensure accurate information retrieval, but they will decrease storage density or increase computing complexity. Here, we apply the Bloom Filter, a space-efficient probabilistic data structure, to DNA storage to achieve the anti-error, or anti-contamination function. This method only needs the original correct DNA sequences (referred to as target sequences) to produce a corresponding data structure, which will filter out almost all the incorrect sequences (referred to as non-target sequences) during sequencing data analysis. Experimental results demonstrate the universal and efficient filtering capabilities of our method. Furthermore, we employ the Counting Bloom Filter to achieve the file version control function, which significantly reduces synthesis costs when modifying DNA-form files. To achieve cost-efficient file version control function, a modified system based on yin-yang codec is developed.
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Affiliation(s)
- Yiming Li
- BGI Research, Shenzhen, 518083, China
- BGI Research, Changzhou, 213299, China
| | - Haoling Zhang
- BGI Research, Shenzhen, 518083, China
- Living Systems Lab, BESE, CEMSE, King Abdullah University of Science and Technology, Thuwal, 23955, Saudi Arabia
| | | | - Yue Shen
- BGI Research, Shenzhen, 518083, China
- BGI Research, Changzhou, 213299, China
| | - Zhi Ping
- BGI Research, Shenzhen, 518083, China
- BGI Research, Changzhou, 213299, China
- School of Medicine, The Chinese University of Hong Kong, Shenzhen, 518172, China
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12
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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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13
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Wang S, Mao X, Wang F, Zuo X, Fan C. Data Storage Using DNA. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2307499. [PMID: 37800877 DOI: 10.1002/adma.202307499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 10/01/2023] [Indexed: 10/07/2023]
Abstract
The exponential growth of global data has outpaced the storage capacities of current technologies, necessitating innovative storage strategies. DNA, as a natural medium for preserving genetic information, has emerged as a highly promising candidate for next-generation storage medium. Storing data in DNA offers several advantages, including ultrahigh physical density and exceptional durability. Facilitated by significant advancements in various technologies, such as DNA synthesis, DNA sequencing, and DNA nanotechnology, remarkable progress has been made in the field of DNA data storage over the past decade. However, several challenges still need to be addressed to realize practical applications of DNA data storage. In this review, the processes and strategies of in vitro DNA data storage are first introduced, highlighting recent advancements. Next, a brief overview of in vivo DNA data storage is provided, with a focus on the various writing strategies developed to date. At last, the challenges encountered in each step of DNA data storage are summarized and promising techniques are discussed that hold great promise in overcoming these obstacles.
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Affiliation(s)
- Shaopeng Wang
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acids Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Xiuhai Mao
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acids Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Fei Wang
- School of Chemistry and Chemical Engineering, New Cornerstone Science Laboratory, Frontiers Science Center for Transformative Molecules, Zhangjiang Institute for Advanced Study and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Xiaolei Zuo
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acids Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
- School of Chemistry and Chemical Engineering, New Cornerstone Science Laboratory, Frontiers Science Center for Transformative Molecules, Zhangjiang Institute for Advanced Study and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Chunhai Fan
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acids Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
- School of Chemistry and Chemical Engineering, New Cornerstone Science Laboratory, Frontiers Science Center for Transformative Molecules, Zhangjiang Institute for Advanced Study and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, 200240, China
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14
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Lu JY, Guo Z, Huang WT, Bao M, He B, Li G, Lei J, Li Y. Peptide-graphene logic sensing system for dual-mode detection of exosomes, molecular information processing and protection. Talanta 2024; 267:125261. [PMID: 37801930 DOI: 10.1016/j.talanta.2023.125261] [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: 07/01/2023] [Revised: 09/26/2023] [Accepted: 09/30/2023] [Indexed: 10/08/2023]
Abstract
Peptides with highly sequence-dependent recognition, assembly, and encoding abilities can perform functions similar to DNA or even better, such as biosensing, molecular information processing, coding, or storage. However, the combination of versatile peptides and 2D materials are rarely used for multipurpose integrated applications, including biosensing, information processing and security. Herein, peptide-graphene sensing system was comprehensively used for dual-signal sensing of tumor-derived exosomes (TDEs), logic computing, and information protection. The system used fluorescent-labeled CD63-binding peptide CP05 and graphene oxide (GO) to selectively detect CD63 and TDEs by fluorescence and resonance light scattering. From three levels such as matter, energy, and information analysis, the matter and energy changes in GO-CP05 peptide sensing system were transformed into valuable information, which achieve the dual-mode quantitative detection of TDEs and its marker CD63, and the actual serum analysis. This matter-energy interaction network was also informationized, and utilized for parallel and batch logic computing, two kinds of molecular crypto-steganography (based on peptide sequence and Boolean logic relationships), which facilitates development of intelligent sensing and advanced information technology. This work not only provides a new method for sensitive detection of important disease markers, but also provides ideas for integrating molecular sensing and informatization to open molecular digitization.
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Affiliation(s)
- Jiao Yang Lu
- Hunan Provincial University Key Laboratory of the Fundamental and Clinical Research on Functional Nucleic Acid, Hunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, "the 14th Five-Year Plan" Application Characteristic Discipline of Hunan Province (Clinical Medicine), Changsha Medical University, Changsha, 410219, PR China; Wuzhou Medical College, Wuzhou, 543100, PR China
| | - Zhen Guo
- Hunan Provincial University Key Laboratory of the Fundamental and Clinical Research on Functional Nucleic Acid, Hunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, "the 14th Five-Year Plan" Application Characteristic Discipline of Hunan Province (Clinical Medicine), Changsha Medical University, Changsha, 410219, PR China
| | - Wei Tao Huang
- State Key Laboratory of Developmental Biology of Freshwater Fish, Hunan Provincial Key Laboratory of Microbial Molecular Biology, College of Life Science, Hunan Normal University, Changsha, 410081, PR China
| | - Meihua Bao
- Hunan Provincial University Key Laboratory of the Fundamental and Clinical Research on Functional Nucleic Acid, Hunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, "the 14th Five-Year Plan" Application Characteristic Discipline of Hunan Province (Clinical Medicine), Changsha Medical University, Changsha, 410219, PR China
| | - Binsheng He
- Hunan Provincial University Key Laboratory of the Fundamental and Clinical Research on Functional Nucleic Acid, Hunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, "the 14th Five-Year Plan" Application Characteristic Discipline of Hunan Province (Clinical Medicine), Changsha Medical University, Changsha, 410219, PR China
| | - Guangyi Li
- Hunan Provincial University Key Laboratory of the Fundamental and Clinical Research on Functional Nucleic Acid, Hunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, "the 14th Five-Year Plan" Application Characteristic Discipline of Hunan Province (Clinical Medicine), Changsha Medical University, Changsha, 410219, PR China
| | - Jieni Lei
- Hunan Provincial University Key Laboratory of the Fundamental and Clinical Research on Functional Nucleic Acid, Hunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, "the 14th Five-Year Plan" Application Characteristic Discipline of Hunan Province (Clinical Medicine), Changsha Medical University, Changsha, 410219, PR China
| | - Yaqian Li
- Hunan Provincial University Key Laboratory of the Fundamental and Clinical Research on Functional Nucleic Acid, Hunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, "the 14th Five-Year Plan" Application Characteristic Discipline of Hunan Province (Clinical Medicine), Changsha Medical University, Changsha, 410219, PR China.
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15
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Yu M, Lim D, Kim J, Song Y. Processing DNA Storage through Programmable Assembly in a Droplet-Based Fluidics System. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2303197. [PMID: 37755129 PMCID: PMC10646262 DOI: 10.1002/advs.202303197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 07/11/2023] [Indexed: 09/28/2023]
Abstract
DNA can be used to store digital data, and synthetic short-sequence DNA pools are developed to store high quantities of digital data. However, synthetic DNA data cannot be actively processed in DNA pools. An active DNA data editing process is developed using splint ligation in a droplet-controlled fluidics (DCF) system. DNA fragments of discrete sizes (100-500 bps) are synthesized for droplet assembly, and programmed sequence information exchange occurred. The encoded DNA sequences are processed in series and parallel to synthesize the determined DNA pools, enabling random access using polymerase chain reaction amplification. The sequencing results of the assembled DNA data pools can be orderly aligned for decoding and have high fidelity through address primer scanning. Furthermore, eight 90 bps DNA pools with pixel information (png: 0.27-0.28 kB), encoded by codons, are synthesized to create eight 270 bps DNA pools with an animation movie chip file (mp4: 12 kB) in the DCF system.
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Affiliation(s)
- Minsang Yu
- Standard Bioelectronics. Co., 511 Michuhol Tower, Gaetbeol-ro 12, Incheon, 21999, South Korea
| | - Doyeon Lim
- Department of Nano-Bioengineering, Incheon National University, Academy-ro 119, Incheon, 22012, South Korea
| | - Jungwoo Kim
- Department of Nano-Bioengineering, Incheon National University, Academy-ro 119, Incheon, 22012, South Korea
| | - Youngjun Song
- Standard Bioelectronics. Co., 511 Michuhol Tower, Gaetbeol-ro 12, Incheon, 21999, South Korea
- Department of Nano-Bioengineering, Incheon National University, Academy-ro 119, Incheon, 22012, South Korea
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16
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Tobiason M, Yurke B, Hughes WL. Generation of DNA oligomers with similar chemical kinetics via in-silico optimization. Commun Chem 2023; 6:226. [PMID: 37853171 PMCID: PMC10584830 DOI: 10.1038/s42004-023-01026-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 10/10/2023] [Indexed: 10/20/2023] Open
Abstract
Networks of interacting DNA oligomers are useful for applications such as biomarker detection, targeted drug delivery, information storage, and photonic information processing. However, differences in the chemical kinetics of hybridization reactions, referred to as kinetic dispersion, can be problematic for some applications. Here, it is found that limiting unnecessary stretches of Watson-Crick base pairing, referred to as unnecessary duplexes, can yield exceptionally low kinetic dispersions. Hybridization kinetics can be affected by unnecessary intra-oligomer duplexes containing only 2 base-pairs, and such duplexes explain up to 94% of previously reported kinetic dispersion. As a general design rule, it is recommended that unnecessary intra-oligomer duplexes larger than 2 base-pairs and unnecessary inter-oligomer duplexes larger than 7 base-pairs be avoided. Unnecessary duplexes typically scale exponentially with network size, and nearly all networks contain unnecessary duplexes substantial enough to affect hybridization kinetics. A new method for generating networks which utilizes in-silico optimization to mitigate unnecessary duplexes is proposed and demonstrated to reduce in-vitro kinetic dispersions as much as 96%. The limitations of the new design rule and generation method are evaluated in-silico by creating new oligomers for several designs, including three previously programmed reactions and one previously engineered structure.
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Affiliation(s)
- Michael Tobiason
- Department of Computer Science, Boise State University, Boise, ID, USA.
- Micron School of Materials Science & Engineering, Boise State University, Boise, ID, USA.
| | - Bernard Yurke
- Micron School of Materials Science & Engineering, Boise State University, Boise, ID, USA
- Department of Electrical & Computer Engineering, Boise State University, Boise, ID, USA
| | - William L Hughes
- School of Engineering, University of British Columbia Okanagan Campus, Kelowna, BC, Canada.
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17
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Sadremomtaz A, Glass RF, Guerrero JE, LaJeunesse DR, Josephs EA, Zadegan R. Digital data storage on DNA tape using CRISPR base editors. Nat Commun 2023; 14:6472. [PMID: 37833288 PMCID: PMC10576057 DOI: 10.1038/s41467-023-42223-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 10/04/2023] [Indexed: 10/15/2023] Open
Abstract
While the archival digital memory industry approaches its physical limits, the demand is significantly increasing, therefore alternatives emerge. Recent efforts have demonstrated DNA's enormous potential as a digital storage medium with superior information durability, capacity, and energy consumption. However, the majority of the proposed systems require on-demand de-novo DNA synthesis techniques that produce a large amount of toxic waste and therefore are not industrially scalable and environmentally friendly. Inspired by the architecture of semiconductor memory devices and recent developments in gene editing, we created a molecular digital data storage system called "DNA Mutational Overwriting Storage" (DMOS) that stores information by leveraging combinatorial, addressable, orthogonal, and independent in vitro CRISPR base-editing reactions to write data on a blank pool of greenly synthesized DNA tapes. As a proof of concept, this work illustrates writing and accurately reading of both a bitmap representation of our school's logo and the title of this study on the DNA tapes.
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Affiliation(s)
- Afsaneh Sadremomtaz
- Department of Nanoengineering, Joint School of Nanoscience and Nanoengineering, NC A&T State University, Greensboro, NC, USA
| | - Robert F Glass
- Department of Nanoscience, Joint School of Nanoscience and Nanoengineering, UNC Greensboro, Greensboro, NC, USA
| | - Jorge Eduardo Guerrero
- Department of Nanoengineering, Joint School of Nanoscience and Nanoengineering, NC A&T State University, Greensboro, NC, USA
| | - Dennis R LaJeunesse
- Department of Nanoscience, Joint School of Nanoscience and Nanoengineering, UNC Greensboro, Greensboro, NC, USA
| | - Eric A Josephs
- Department of Nanoscience, Joint School of Nanoscience and Nanoengineering, UNC Greensboro, Greensboro, NC, USA.
| | - Reza Zadegan
- Department of Nanoengineering, Joint School of Nanoscience and Nanoengineering, NC A&T State University, Greensboro, NC, USA.
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18
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Wang B, Wang SS, Chalk C, Ellington AD, Soloveichik D. Parallel molecular computation on digital data stored in DNA. Proc Natl Acad Sci U S A 2023; 120:e2217330120. [PMID: 37669382 PMCID: PMC10500265 DOI: 10.1073/pnas.2217330120] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 07/10/2023] [Indexed: 09/07/2023] Open
Abstract
DNA is an incredibly dense storage medium for digital data. However, computing on the stored information is expensive and slow, requiring rounds of sequencing, in silico computation, and DNA synthesis. Prior work on accessing and modifying data using DNA hybridization or enzymatic reactions had limited computation capabilities. Inspired by the computational power of "DNA strand displacement," we augment DNA storage with "in-memory" molecular computation using strand displacement reactions to algorithmically modify data in a parallel manner. We show programs for binary counting and Turing universal cellular automaton Rule 110, the latter of which is, in principle, capable of implementing any computer algorithm. Information is stored in the nicks of DNA, and a secondary sequence-level encoding allows high-throughput sequencing-based readout. We conducted multiple rounds of computation on 4-bit data registers, as well as random access of data (selective access and erasure). We demonstrate that large strand displacement cascades with 244 distinct strand exchanges (sequential and in parallel) can use naturally occurring DNA sequence from M13 bacteriophage without stringent sequence design, which has the potential to improve the scale of computation and decrease cost. Our work merges DNA storage and DNA computing, setting the foundation of entirely molecular algorithms for parallel manipulation of digital information preserved in DNA.
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Affiliation(s)
- Boya Wang
- Electrical and Computer Engineering, University of Texas at Austin, Austin, TX78712
| | - Siyuan Stella Wang
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX78712
- Department of Chemistry and Biochemistry, University of Texas at Austin, Austin, TX78712
| | - Cameron Chalk
- Electrical and Computer Engineering, University of Texas at Austin, Austin, TX78712
| | - Andrew D. Ellington
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX78712
- Department of Chemistry and Biochemistry, University of Texas at Austin, Austin, TX78712
| | - David Soloveichik
- Electrical and Computer Engineering, University of Texas at Austin, Austin, TX78712
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19
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Zhao Y, Cao B, Wang P, Wang K, Wang B. DBTRG: De Bruijn Trim rotation graph encoding for reliable DNA storage. Comput Struct Biotechnol J 2023; 21:4469-4477. [PMID: 37736298 PMCID: PMC10510065 DOI: 10.1016/j.csbj.2023.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 09/04/2023] [Accepted: 09/05/2023] [Indexed: 09/23/2023] Open
Abstract
DNA is a high-density, long-term stable, and scalable storage medium that can meet the increased demands on storage media resulting from the exponential growth of data. The existing DNA storage encoding schemes tend to achieve high-density storage but do not fully consider the local and global stability of DNA sequences and the read and write accuracy of the stored information. To address these problems, this article presents a graph-based De Bruijn Trim Rotation Graph (DBTRG) encoding scheme. Through XOR between the proposed dynamic binary sequence and the original binary sequence, k-mers can be divided into the De Bruijn Trim graph, and the stored information can be compressed according to the overlapping relationship. The simulated experimental results show that DBTRG ensures base balance and diversity, reduces the likelihood of undesired motifs, and improves the stability of DNA storage and data recovery. Furthermore, the maintenance of an encoding rate of 1.92 while storing 510 KB images and the introduction of novel approaches and concepts for DNA storage encoding methods are achieved.
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Affiliation(s)
- Yunzhu Zhao
- The Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Dalian, Liaoning 116622, China
| | - Ben Cao
- School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Penghao Wang
- The Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Dalian, Liaoning 116622, China
| | - Kun Wang
- The Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Dalian, Liaoning 116622, China
| | - Bin Wang
- The Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Dalian, Liaoning 116622, China
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20
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Raza MH, Desai S, Aravamudhan S, Zadegan R. An outlook on the current challenges and opportunities in DNA data storage. Biotechnol Adv 2023; 66:108155. [PMID: 37068530 PMCID: PMC11060094 DOI: 10.1016/j.biotechadv.2023.108155] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 03/23/2023] [Accepted: 04/12/2023] [Indexed: 04/19/2023]
Abstract
Silicon is the gold standard for information storage systems. The exponential generation of digital information will exhaust the global supply of refined silicon. Therefore, investing in alternative information storage materials such as DNA has gained momentum. DNA as a memory material possesses several advantages over silicon-based data storage, including higher storage capacity, data retention, and lower operational energy. Routine DNA data storage approaches encode data into chemically synthesized nucleotide sequences. The scalability of DNA data storage depends on factors such as the cost and the generation of hazardous waste during DNA synthesis, latency of writing and reading, and limited rewriting capacity. Here, we review the current status of DNA data storage encoding, writing, storing, retrieving and reading, and discuss the technology's challenges and opportunities.
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Affiliation(s)
- Muhammad Hassan Raza
- Department of Nanoengineering, Joint School of Nanoscience & Nanoengineering, Greensboro, NC 27401, USA
| | - Salil Desai
- Department of Industrial & Systems Engineering, North Carolina Agricultural & Technical State University, Greensboro, NC 27411, USA; Center of Excellence in Product Design and Advanced Manufacturing (CEPDAM), North Carolina Agricultural & Technical State University, Greensboro, NC 27411, USA
| | - Shyam Aravamudhan
- Department of Nanoengineering, Joint School of Nanoscience & Nanoengineering, Greensboro, NC 27401, USA; Center of Excellence in Product Design and Advanced Manufacturing (CEPDAM), North Carolina Agricultural & Technical State University, Greensboro, NC 27411, USA
| | - Reza Zadegan
- Department of Nanoengineering, Joint School of Nanoscience & Nanoengineering, Greensboro, NC 27401, USA; Center of Excellence in Product Design and Advanced Manufacturing (CEPDAM), North Carolina Agricultural & Technical State University, Greensboro, NC 27411, USA.
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21
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Ding L, Chen X, Ma W, Li J, Liu X, Fan C, Yao G. DNA-mediated regioselective encoding of colloids for programmable self-assembly. Chem Soc Rev 2023; 52:5684-5705. [PMID: 37522252 DOI: 10.1039/d2cs00845a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/01/2023]
Abstract
How far we can push chemical self-assembly is one of the most important scientific questions of the century. Colloidal self-assembly is a bottom-up technique for the rational design of functional materials with desirable collective properties. Due to the programmability of DNA base pairing, surface modification of colloidal particles with DNA has become fundamental for programmable material self-assembly. However, there remains an ever-lasting demand for surface regioselective encoding to realize assemblies that require specific, directional, and orthogonal interactions. Recent advances in surface chemistry have enabled regioselective control over the formation of DNA bonds on the particle surface. In particular, the structural DNA nanotechnology provides a simple yet powerful design strategy with unique regioselective addressability, bringing the complexity of colloidal self-assembly to an unprecedented level. In this review, we summarize the state-of-art advances in DNA-mediated regioselective surface encoding of colloids, with a focus on how the regioselective encoding is introduced and how the regioselective DNA recognition plays a crucial role in the self-assembly of colloidal structures. This review highlights the advantages of DNA-based regioselective modification in improving the complexity of colloidal assembly, and outlines the challenges and opportunities for the construction of more complex architectures with tailored functionalities.
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Affiliation(s)
- Longjiang Ding
- School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Xiaoliang Chen
- School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Wenhe Ma
- School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Jiang Li
- Institute of Materiobiology, Department of Chemistry, College of Science, Shanghai University, Shanghai 200444, China
| | - Xiaoguo Liu
- School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Chunhai Fan
- School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Guangbao Yao
- School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.
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22
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Bögels BWA, Nguyen BH, Ward D, Gascoigne L, Schrijver DP, Makri Pistikou AM, Joesaar A, Yang S, Voets IK, Mulder WJM, Phillips A, Mann S, Seelig G, Strauss K, Chen YJ, de Greef TFA. DNA storage in thermoresponsive microcapsules for repeated random multiplexed data access. NATURE NANOTECHNOLOGY 2023; 18:912-921. [PMID: 37142708 PMCID: PMC10427423 DOI: 10.1038/s41565-023-01377-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 03/19/2023] [Indexed: 05/06/2023]
Abstract
DNA has emerged as an attractive medium for archival data storage due to its durability and high information density. Scalable parallel random access to information is a desirable property of any storage system. For DNA-based storage systems, however, this still needs to be robustly established. Here we report on a thermoconfined polymerase chain reaction, which enables multiplexed, repeated random access to compartmentalized DNA files. The strategy is based on localizing biotin-functionalized oligonucleotides inside thermoresponsive, semipermeable microcapsules. At low temperatures, microcapsules are permeable to enzymes, primers and amplified products, whereas at high temperatures, membrane collapse prevents molecular crosstalk during amplification. Our data show that the platform outperforms non-compartmentalized DNA storage compared with repeated random access and reduces amplification bias tenfold during multiplex polymerase chain reaction. Using fluorescent sorting, we also demonstrate sample pooling and data retrieval by microcapsule barcoding. Therefore, the thermoresponsive microcapsule technology offers a scalable, sequence-agnostic approach for repeated random access to archival DNA files.
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Affiliation(s)
- 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
| | - Bichlien H Nguyen
- Microsoft, Redmond, WA, USA
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
| | - David Ward
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
| | - Levena Gascoigne
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, The Netherlands
- Laboratory of Self-Organizing Soft Matter, Department of Chemical Engineering and Chemistry, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - David P Schrijver
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Anna-Maria Makri Pistikou
- 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
| | - Alex Joesaar
- 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
| | - Shuo Yang
- 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
| | - Ilja K Voets
- Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, The Netherlands
- Laboratory of Self-Organizing Soft Matter, Department of Chemical Engineering and Chemistry, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Willem J M Mulder
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | | | - Stephen Mann
- Centre for Protolife Research and Centre for Organized Matter Chemistry, School of Chemistry, University of Bristol, Bristol, UK
- School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
- Zhangjiang Institute for Advanced Study (ZIAS), Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Georg Seelig
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
- Department of Electrical Engineering, University of Washington, Seattle, WA, USA
| | - Karin Strauss
- Microsoft, Redmond, WA, USA
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
| | - Yuan-Jyue Chen
- Microsoft, Redmond, WA, USA.
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA.
| | - 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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23
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Zhang XE, Liu C, Dai J, Yuan Y, Gao C, Feng Y, Wu B, Wei P, You C, Wang X, Si T. Enabling technology and core theory of synthetic biology. SCIENCE CHINA. LIFE SCIENCES 2023; 66:1742-1785. [PMID: 36753021 PMCID: PMC9907219 DOI: 10.1007/s11427-022-2214-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 10/04/2022] [Indexed: 02/09/2023]
Abstract
Synthetic biology provides a new paradigm for life science research ("build to learn") and opens the future journey of biotechnology ("build to use"). Here, we discuss advances of various principles and technologies in the mainstream of the enabling technology of synthetic biology, including synthesis and assembly of a genome, DNA storage, gene editing, molecular evolution and de novo design of function proteins, cell and gene circuit engineering, cell-free synthetic biology, artificial intelligence (AI)-aided synthetic biology, as well as biofoundries. We also introduce the concept of quantitative synthetic biology, which is guiding synthetic biology towards increased accuracy and predictability or the real rational design. We conclude that synthetic biology will establish its disciplinary system with the iterative development of enabling technologies and the maturity of the core theory.
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Affiliation(s)
- Xian-En Zhang
- Faculty of Synthetic Biology, Shenzhen Institute of Advanced Technology, Shenzhen, 518055, China.
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Chenli Liu
- Faculty of Synthetic Biology, Shenzhen Institute of Advanced Technology, Shenzhen, 518055, China.
- Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
| | - Junbiao Dai
- Faculty of Synthetic Biology, Shenzhen Institute of Advanced Technology, Shenzhen, 518055, China.
- Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
| | - Yingjin Yuan
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China.
| | - Caixia Gao
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yan Feng
- State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Bian Wu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Ping Wei
- Faculty of Synthetic Biology, Shenzhen Institute of Advanced Technology, Shenzhen, 518055, China.
- Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
| | - Chun You
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.
| | - Xiaowo Wang
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing, 100084, China.
| | - Tong Si
- Faculty of Synthetic Biology, Shenzhen Institute of Advanced Technology, Shenzhen, 518055, China.
- Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
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24
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Lim CK, Yeoh JW, Kunartama AA, Yew WS, Poh CL. A biological camera that captures and stores images directly into DNA. Nat Commun 2023; 14:3921. [PMID: 37400476 DOI: 10.1038/s41467-023-38876-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 05/19/2023] [Indexed: 07/05/2023] Open
Abstract
The increasing integration between biological and digital interfaces has led to heightened interest in utilizing biological materials to store digital data, with the most promising one involving the storage of data within defined sequences of DNA that are created by de novo DNA synthesis. However, there is a lack of methods that can obviate the need for de novo DNA synthesis, which tends to be costly and inefficient. Here, in this work, we detail a method of capturing 2-dimensional light patterns into DNA, by utilizing optogenetic circuits to record light exposure into DNA, encoding spatial locations with barcoding, and retrieving stored images via high-throughput next-generation sequencing. We demonstrate the encoding of multiple images into DNA, totaling 1152 bits, selective image retrieval, as well as robustness to drying, heat and UV. We also demonstrate successful multiplexing using multiple wavelengths of light, capturing 2 different images simultaneously using red and blue light. This work thus establishes a 'living digital camera', paving the way towards integrating biological systems with digital devices.
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Affiliation(s)
- Cheng Kai Lim
- Synthetic Biology for Clinical and Technological Innovation, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore
- Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, 14 Medical Drive, Singapore, 117599, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117597, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore
- Integrative Sciences and Engineering Programme (ISEP), NUS Graduate School, National University of Singapore, Singapore, Singapore
| | - Jing Wui Yeoh
- Synthetic Biology for Clinical and Technological Innovation, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore
| | - Aurelius Andrew Kunartama
- Synthetic Biology for Clinical and Technological Innovation, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore
| | - Wen Shan Yew
- Synthetic Biology for Clinical and Technological Innovation, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore
- Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, 14 Medical Drive, Singapore, 117599, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore, 117597, Singapore
| | - Chueh Loo Poh
- Synthetic Biology for Clinical and Technological Innovation, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore.
- Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore, Singapore.
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25
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Lau B, Chandak S, Roy S, Tatwawadi K, Wootters M, Weissman T, Ji HP. Magnetic DNA random access memory with nanopore readouts and exponentially-scaled combinatorial addressing. Sci Rep 2023; 13:8514. [PMID: 37231057 DOI: 10.1038/s41598-023-29575-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 02/07/2023] [Indexed: 05/27/2023] Open
Abstract
The storage of data in DNA typically involves encoding and synthesizing data into short oligonucleotides, followed by reading with a sequencing instrument. Major challenges include the molecular consumption of synthesized DNA, basecalling errors, and limitations with scaling up read operations for individual data elements. Addressing these challenges, we describe a DNA storage system called MDRAM (Magnetic DNA-based Random Access Memory) that enables repetitive and efficient readouts of targeted files with nanopore-based sequencing. By conjugating synthesized DNA to magnetic agarose beads, we enabled repeated data readouts while preserving the original DNA analyte and maintaining data readout quality. MDRAM utilizes an efficient convolutional coding scheme that leverages soft information in raw nanopore sequencing signals to achieve information reading costs comparable to Illumina sequencing despite higher error rates. Finally, we demonstrate a proof-of-concept DNA-based proto-filesystem that enables an exponentially-scalable data address space using only small numbers of targeting primers for assembly and readout.
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Affiliation(s)
- Billy Lau
- Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, 94304, USA
| | - Shubham Chandak
- Department of Electrical Engineering, Stanford University, Stanford, CA, 94305, USA
| | - Sharmili Roy
- Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Kedar Tatwawadi
- Department of Electrical Engineering, Stanford University, Stanford, CA, 94305, USA
| | - Mary Wootters
- Department of Electrical Engineering, Stanford University, Stanford, CA, 94305, USA
| | - Tsachy Weissman
- Department of Electrical Engineering, Stanford University, Stanford, CA, 94305, USA.
| | - Hanlee P Ji
- Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, 94304, USA.
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26
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Xu C, Ma B, Dong X, Lei L, Hao Q, Zhao C, Liu H. Assembly of Reusable DNA Blocks for Data Storage Using the Principle of Movable Type Printing. ACS APPLIED MATERIALS & INTERFACES 2023; 15:24097-24108. [PMID: 37184884 DOI: 10.1021/acsami.3c01860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
Due to its high coding density and longevity, DNA is a compelling data storage alternative. However, current DNA data storage systems rely on the de novo synthesis of enormous DNA molecules, resulting in low data editability, high synthesis costs, and restrictions on further applications. Here, we demonstrate the programmable assembly of reusable DNA blocks for versatile data storage using the ancient movable type printing principle. Digital data are first encoded into nucleotide sequences in DNA hairpins, which are then synthesized and immobilized on solid beads as modular DNA blocks. Using DNA polymerase-catalyzed primer exchange reaction, data can be continuously replicated from hairpins on DNA blocks and attached to a primer in tandem to produce new information. The assembly of DNA blocks is highly programmable, producing various data by reusing a finite number of DNA blocks and reducing synthesis costs (∼1718 versus 3000 to 30,000 US$ per megabyte using conventional methods). We demonstrate the flexible assembly of texts, images, and random numbers using DNA blocks and the integration with DNA logic circuits to manipulate data synthesis. This work suggests a flexible paradigm by recombining already synthesized DNA to build cost-effective and intelligent DNA data storage systems.
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Affiliation(s)
- Chengtao Xu
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University Institution, 2# Sipailou, Nanjing, Jiangsu 210096, China
| | - Biao Ma
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University Institution, 2# Sipailou, Nanjing, Jiangsu 210096, China
| | - Xing Dong
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University Institution, 2# Sipailou, Nanjing, Jiangsu 210096, China
| | - Lanjie Lei
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University Institution, 2# Sipailou, Nanjing, Jiangsu 210096, China
| | - Qing Hao
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University Institution, 2# Sipailou, Nanjing, Jiangsu 210096, China
| | - Chao Zhao
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University Institution, 2# Sipailou, Nanjing, Jiangsu 210096, China
| | - Hong Liu
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University Institution, 2# Sipailou, Nanjing, Jiangsu 210096, China
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27
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El-Shaikh A, Seeger B. Content-based filter queries on DNA data storage systems. Sci Rep 2023; 13:7053. [PMID: 37120614 PMCID: PMC10148835 DOI: 10.1038/s41598-023-34160-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 04/25/2023] [Indexed: 05/01/2023] Open
Abstract
Recent developments in DNA data storage systems have revealed the great potential to store large amounts of data at a very high density with extremely long persistence and low cost. However, despite recent contributions to robust data encoding, current DNA storage systems offer limited support for random access on DNA storage devices due to restrictive biochemical constraints. Moreover, state-of-the-art approaches do not support content-based filter queries on DNA storage. This paper introduces the first encoding for DNA that enables content-based searches on structured data like relational database tables. We provide the details of the methods for coding and decoding millions of directly accessible data objects on DNA. We evaluate the derived codes on real data sets and verify their robustness.
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Affiliation(s)
- Alex El-Shaikh
- Departement of Mathematics and Computer Science, University of Marburg, 35037, Marburg, Germany.
| | - Bernhard Seeger
- Departement of Mathematics and Computer Science, University of Marburg, 35037, Marburg, Germany
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28
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De A, Mohammad H, Wang Y, Kubendran R, Das AK, Anantram MP. Performance analysis of DNA crossbar arrays for high-density memory storage applications. Sci Rep 2023; 13:6650. [PMID: 37095117 PMCID: PMC10126128 DOI: 10.1038/s41598-023-33004-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 04/05/2023] [Indexed: 04/26/2023] Open
Abstract
Deoxyribonucleic acid (DNA) has emerged as a promising building block for next-generation ultra-high density storage devices. Although DNA has high durability and extremely high density in nature, its potential as the basis of storage devices is currently hindered by limitations such as expensive and complex fabrication processes and time-consuming read-write operations. In this article, we propose the use of a DNA crossbar array architecture for an electrically readable read-only memory (DNA-ROM). While information can be 'written' error-free to a DNA-ROM array using appropriate sequence encodings its read accuracy can be affected by several factors such as array size, interconnect resistance, and Fermi energy deviations from HOMO levels of DNA strands employed in the crossbar. We study the impact of array size and interconnect resistance on the bit error rate of a DNA-ROM array through extensive Monte Carlo simulations. We have also analyzed the performance of our proposed DNA crossbar array for an image storage application, as a function of array size and interconnect resistance. While we expect that future advances in bioengineering and materials science will address some of the fabrication challenges associated with DNA crossbar arrays, we believe that the comprehensive body of results we present in this paper establishes the technical viability of DNA crossbar arrays as low power, high-density storage devices. Finally, our analysis of array performance vis-à-vis interconnect resistance should provide valuable insights into aspects of the fabrication process such as proper choice of interconnects necessary for ensuring high read accuracies.
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Affiliation(s)
- Arpan De
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, 98195, USA
| | - Hashem Mohammad
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, 98195, USA
- Department of Electrical Engineering, Kuwait University, P.O. Box 5969, 13060, Safat, Kuwait
| | - Yiren Wang
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, 98195, USA
| | - Rajkumar Kubendran
- Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Arindam K Das
- Department of Computer Science and Electrical Engineering, Eastern Washington University, Cheney, WA, 99004, USA
| | - M P Anantram
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, 98195, USA.
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29
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Mortuza GM, Guerrero J, Llewellyn S, Tobiason MD, Dickinson GD, Hughes WL, Zadegan R, Andersen T. In-vitro validated methods for encoding digital data in deoxyribonucleic acid (DNA). BMC Bioinformatics 2023; 24:160. [PMID: 37085766 PMCID: PMC10120115 DOI: 10.1186/s12859-023-05264-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 03/30/2023] [Indexed: 04/23/2023] Open
Abstract
Deoxyribonucleic acid (DNA) is emerging as an alternative archival memory technology. Recent advancements in DNA synthesis and sequencing have both increased the capacity and decreased the cost of storing information in de novo synthesized DNA pools. In this survey, we review methods for translating digital data to and/or from DNA molecules. An emphasis is placed on methods which have been validated by storing and retrieving real-world data via in-vitro experiments.
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Affiliation(s)
- Golam Md Mortuza
- Department of Computer Science, Boise State University, Boise, Idaho, USA
| | - Jorge Guerrero
- Department of Nanoengineering, Joint School of Nanoscience and Nanoengineering, North Carolina A&T State University, Greensboro, NC, USA
| | | | | | | | - William L Hughes
- School of Engineering, Kelowna, University of British Columbia, Kelowna, British Columbia, Canada
| | - Reza Zadegan
- Department of Nanoengineering, Joint School of Nanoscience and Nanoengineering, North Carolina A&T State University, Greensboro, NC, USA.
| | - Tim Andersen
- Department of Computer Science, Boise State University, Boise, Idaho, USA.
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30
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GCNSA: DNA storage encoding with a graph convolutional network and self-attention. iScience 2023; 26:106231. [PMID: 36876131 PMCID: PMC9982308 DOI: 10.1016/j.isci.2023.106231] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 01/31/2023] [Accepted: 02/14/2023] [Indexed: 02/22/2023] Open
Abstract
DNA Encoding, as a key step in DNA storage, plays an important role in reading and writing accuracy and the storage error rate. However, currently, the encoding efficiency is not high enough and the encoding speed is not fast enough, which limits the performance of DNA storage systems. In this work, a DNA storage encoding system with a graph convolutional network and self-attention (GCNSA) is proposed. The experimental results show that DNA storage code constructed by GCNSA increases by 14.4% on average under the basic constraints, and by 5%-40% under other constraints. The increase of DNA storage codes effectively improves the storage density of 0.7-2.2% in the DNA storage system. The GCNSA predicted more DNA storage codes in less time while ensuring the quality of codes, which lays a foundation for higher read and write efficiency in DNA storage.
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31
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Mao C, Wang S, Li J, Feng Z, Zhang T, Wang R, Fan C, Jiang X. Metal-Organic Frameworks in Microfluidics Enable Fast Encapsulation/Extraction of DNA for Automated and Integrated Data Storage. ACS NANO 2023; 17:2840-2850. [PMID: 36728704 DOI: 10.1021/acsnano.2c11241] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
DNA as an exceptional data storage medium offers high information density. However, DNA storage requires specialized equipment and tightly controlled environments for storage. Fast encapsulation within minutes for enhanced DNA stability to do away with specialized equipment and fast DNA extraction remain a challenge. Here, we report a DNA microlibrary that can be encapsulated by metal-organic frameworks (MOFs) within 10 min and extracted (5 min) in a single microfluidic chip for automated and integrated DNA-based data storage. The DNA microlibrary@MOFs enhances the stability of data-encoded DNA against harsh environments. The encoded information can be read out perfectly after accelerated aging, equivalent to being readable after 10 years of storage at 25 °C, 50% relative humidity, and 10 000 lx sunlight radiation. Moreover, the library enables fast retrieval of target data via flow cytometry and can be reproduced after each access.
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Affiliation(s)
- Cuiping Mao
- Guangdong Provincial Key Laboratory of Advanced Biomaterials, Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Road, Nanshan District, Shenzhen, Guangdong 518055, People's Republic of China
| | - Shuchen Wang
- Guangdong Provincial Key Laboratory of Advanced Biomaterials, Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Road, Nanshan District, Shenzhen, Guangdong 518055, People's Republic of China
| | - Jiankai Li
- Guangdong Provincial Key Laboratory of Advanced Biomaterials, Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Road, Nanshan District, Shenzhen, Guangdong 518055, People's Republic of China
| | - Zhuowei Feng
- Guangdong Provincial Key Laboratory of Advanced Biomaterials, Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Road, Nanshan District, Shenzhen, Guangdong 518055, People's Republic of China
| | - Tong Zhang
- Department of Electronic and Electrical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Road, Nanshan District, Shenzhen, Guangdong 518055, People's Republic of China
| | - Rui Wang
- Department of Electronic and Electrical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Road, Nanshan District, Shenzhen, Guangdong 518055, People's Republic of China
| | - Chunhai Fan
- Frontiers Science Center for Transformative Molecules, School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, No 800, DongChuan Road, Minhang District, Shanghai 200240, People's Republic of China
| | - Xingyu Jiang
- Guangdong Provincial Key Laboratory of Advanced Biomaterials, Shenzhen Key Laboratory of Smart Healthcare Engineering, Department of Biomedical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Road, Nanshan District, Shenzhen, Guangdong 518055, People's Republic of China
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32
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Sadremomtaz A, Glass RF, Guerrero JE, LaJeunesse DR, Josephs EA, Zadegan R. Digital data storage on DNA tape using CRISPR base editors. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.07.527074. [PMID: 36798394 PMCID: PMC9934529 DOI: 10.1101/2023.02.07.527074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
While the archival digital memory industry approaches its physical limits, the demand is significantly increasing, therefore alternatives emerge. Recent efforts have demonstrated DNA's enormous potential as a digital storage medium with superior information durability, capacity, and energy consumption. However, the majority of the proposed systems require on-demand de-novo DNA synthesis techniques that produce a large amount of toxic waste and therefore are not industrially scalable and environmentally friendly. Inspired by the architecture of semiconductor memory devices and recent developments in gene editing, we created a molecular digital data storage system called "DNA Mutational Overwriting Storage" (DMOS) that stores information by leveraging combinatorial, addressable, orthogonal, and independent in vitro CRISPR base-editing reactions to write data on a blank pool of greenly synthesized DNA tapes. As a proof of concept, we wrote both a bitmap representation of our school's logo and the title of this study on the DNA tapes, and accurately recovered the stored data.
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33
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Welzel M, Schwarz PM, Löchel HF, Kabdullayeva T, Clemens S, Becker A, Freisleben B, Heider D. DNA-Aeon provides flexible arithmetic coding for constraint adherence and error correction in DNA storage. Nat Commun 2023; 14:628. [PMID: 36746948 PMCID: PMC9902613 DOI: 10.1038/s41467-023-36297-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 01/25/2023] [Indexed: 02/08/2023] Open
Abstract
The extensive information capacity of DNA, coupled with decreasing costs for DNA synthesis and sequencing, makes DNA an attractive alternative to traditional data storage. The processes of writing, storing, and reading DNA exhibit specific error profiles and constraints DNA sequences have to adhere to. We present DNA-Aeon, a concatenated coding scheme for DNA data storage. It supports the generation of variable-sized encoded sequences with a user-defined Guanine-Cytosine (GC) content, homopolymer length limitation, and the avoidance of undesired motifs. It further enables users to provide custom codebooks adhering to further constraints. DNA-Aeon can correct substitution errors, insertions, deletions, and the loss of whole DNA strands. Comparisons with other codes show better error-correction capabilities of DNA-Aeon at similar redundancy levels with decreased DNA synthesis costs. In-vitro tests indicate high reliability of DNA-Aeon even in the case of skewed sequencing read distributions and high read-dropout.
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Affiliation(s)
- Marius Welzel
- Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany.,Center for Synthetic Microbiology (SYNMIKRO), University of Marburg, Marburg, Germany
| | - Peter Michael Schwarz
- Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany.,Center for Synthetic Microbiology (SYNMIKRO), University of Marburg, Marburg, Germany
| | - Hannah F Löchel
- Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany.,Center for Synthetic Microbiology (SYNMIKRO), University of Marburg, Marburg, Germany
| | - Tolganay Kabdullayeva
- Center for Synthetic Microbiology (SYNMIKRO), University of Marburg, Marburg, Germany
| | - Sandra Clemens
- Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany.,Center for Synthetic Microbiology (SYNMIKRO), University of Marburg, Marburg, Germany
| | - Anke Becker
- Center for Synthetic Microbiology (SYNMIKRO), University of Marburg, Marburg, Germany
| | - Bernd Freisleben
- Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany.,Center for Synthetic Microbiology (SYNMIKRO), University of Marburg, Marburg, Germany
| | - Dominik Heider
- Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany. .,Center for Synthetic Microbiology (SYNMIKRO), University of Marburg, Marburg, Germany.
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34
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Parsons MF, Allan MF, Li S, Shepherd TR, Ratanalert S, Zhang K, Pullen KM, Chiu W, Rouskin S, Bathe M. 3D RNA-scaffolded wireframe origami. Nat Commun 2023; 14:382. [PMID: 36693871 PMCID: PMC9872083 DOI: 10.1038/s41467-023-36156-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 01/18/2023] [Indexed: 01/26/2023] Open
Abstract
Hybrid RNA:DNA origami, in which a long RNA scaffold strand folds into a target nanostructure via thermal annealing with complementary DNA oligos, has only been explored to a limited extent despite its unique potential for biomedical delivery of mRNA, tertiary structure characterization of long RNAs, and fabrication of artificial ribozymes. Here, we investigate design principles of three-dimensional wireframe RNA-scaffolded origami rendered as polyhedra composed of dual-duplex edges. We computationally design, fabricate, and characterize tetrahedra folded from an EGFP-encoding messenger RNA and de Bruijn sequences, an octahedron folded with M13 transcript RNA, and an octahedron and pentagonal bipyramids folded with 23S ribosomal RNA, demonstrating the ability to make diverse polyhedral shapes with distinct structural and functional RNA scaffolds. We characterize secondary and tertiary structures using dimethyl sulfate mutational profiling and cryo-electron microscopy, revealing insight into both global and local, base-level structures of origami. Our top-down sequence design strategy enables the use of long RNAs as functional scaffolds for complex wireframe origami.
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Affiliation(s)
- Molly F Parsons
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Matthew F Allan
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Microbiology, Harvard Medical School, Boston, MA, USA
- Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Shanshan Li
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
- MOE Key Laboratory for Cellular Dynamics and Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027, China
| | - Tyson R Shepherd
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Inscripta, Inc., Boulder, CO, 80027, USA
| | - Sakul Ratanalert
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Kaiming Zhang
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
- MOE Key Laboratory for Cellular Dynamics and Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027, China
| | - Krista M Pullen
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Wah Chiu
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
- CryoEM and Bioimaging Division, Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA, 94025, USA
| | - Silvi Rouskin
- Department of Microbiology, Harvard Medical School, Boston, MA, USA
| | - Mark Bathe
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
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35
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Chen C, Wen J, Wen Z, Song S, Shi X. DNA strand displacement based computational systems and their applications. Front Genet 2023; 14:1120791. [PMID: 36911397 PMCID: PMC9992816 DOI: 10.3389/fgene.2023.1120791] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Accepted: 02/13/2023] [Indexed: 02/24/2023] Open
Abstract
DNA computing has become the focus of computing research due to its excellent parallel processing capability, data storage capacity, and low energy consumption characteristics. DNA computational units can be precisely programmed through the sequence specificity and base pair principle. Then, computational units can be cascaded and integrated to form large DNA computing systems. Among them, DNA strand displacement (DSD) is the simplest but most efficient method for constructing DNA computing systems. The inputs and outputs of DSD are signal strands that can be transferred to the next unit. DSD has been used to construct logic gates, integrated circuits, artificial neural networks, etc. This review introduced the recent development of DSD-based computational systems and their applications. Some DSD-related tools and issues are also discussed.
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Affiliation(s)
- Congzhou Chen
- School of Computer Science, Beijing University of Technology, Beijing, China
| | - Jinda Wen
- Institute of Computing Science and Technology, Guangzhou University, Guangzhou, China
| | - Zhibin Wen
- Institute of Computing Science and Technology, Guangzhou University, Guangzhou, China
| | - Sijie Song
- Institute of Computing Science and Technology, Guangzhou University, Guangzhou, China
| | - Xiaolong Shi
- Institute of Computing Science and Technology, Guangzhou University, Guangzhou, China
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36
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FMG: An observable DNA storage coding method based on frequency matrix game graphs. Comput Biol Med 2022; 151:106269. [PMID: 36356390 DOI: 10.1016/j.compbiomed.2022.106269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 10/20/2022] [Accepted: 10/30/2022] [Indexed: 11/06/2022]
Abstract
Using complex biomolecules for storage is a new carbon-based storage method. For example, DNA has the potential to be a good method for archival long-term data storage. Reasonable and efficient coding is the first and most important step in DNA storage. However, current coding methods, such as altruism algorithm, have the problem of low coding efficiency and high complexity, and coding constraints and sets make it difficult to see the coding results visually. In this study, a new DNA storage coding method based on frequency matrix game graph (FMG) is proposed to generate DNA storage coding satisfying combinatorial constraints. Compared with the randomness of the heuristic algorithm that satisfies the constraints, the coding method based on the FMG is deterministic and can clearly explain the coding process. In addition, the constraints and coding results have observable characteristics and are better than the previously published results for the size of the coding set. For example, when length of the code n = 10, hamming distance d = 4, the results obtained by proposed approach combining chaos game and graph are 24% better than the previous results. The proposed coding scheme successfully constructs high-quality coding sets with less complexity, which effectively promotes the development of carbon-based storage coding.
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37
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Doricchi A, Platnich CM, Gimpel A, Horn F, Earle M, Lanzavecchia G, Cortajarena AL, Liz-Marzán LM, Liu N, Heckel R, Grass RN, Krahne R, Keyser UF, Garoli D. Emerging Approaches to DNA Data Storage: Challenges and Prospects. ACS NANO 2022; 16:17552-17571. [PMID: 36256971 PMCID: PMC9706676 DOI: 10.1021/acsnano.2c06748] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
With the total amount of worldwide data skyrocketing, the global data storage demand is predicted to grow to 1.75 × 1014 GB by 2025. Traditional storage methods have difficulties keeping pace given that current storage media have a maximum density of 103 GB/mm3. As such, data production will far exceed the capacity of currently available storage methods. The costs of maintaining and transferring data, as well as the limited lifespans and significant data losses associated with current technologies also demand advanced solutions for information storage. Nature offers a powerful alternative through the storage of information that defines living organisms in unique orders of four bases (A, T, C, G) located in molecules called deoxyribonucleic acid (DNA). DNA molecules as information carriers have many advantages over traditional storage media. Their high storage density, potentially low maintenance cost, ease of synthesis, and chemical modification make them an ideal alternative for information storage. To this end, rapid progress has been made over the past decade by exploiting user-defined DNA materials to encode information. In this review, we discuss the most recent advances of DNA-based data storage with a major focus on the challenges that remain in this promising field, including the current intrinsic low speed in data writing and reading and the high cost per byte stored. Alternatively, data storage relying on DNA nanostructures (as opposed to DNA sequence) as well as on other combinations of nanomaterials and biomolecules are proposed with promising technological and economic advantages. In summarizing the advances that have been made and underlining the challenges that remain, we provide a roadmap for the ongoing research in this rapidly growing field, which will enable the development of technological solutions to the global demand for superior storage methodologies.
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Affiliation(s)
- Andrea Doricchi
- Istituto
Italiano di Tecnologia, via Morego 30, I-16163 Genova, Italy
- Dipartimento
di Chimica e Chimica Industriale, Università
di Genova, via Dodecaneso
31, 16146 Genova, Italy
| | - Casey M. Platnich
- Cavendish
Laboratory, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0HE, U.K.
| | - Andreas Gimpel
- Institute
for Chemical and Bioengineering, ETH Zurich, Vladimir-Prelog-Weg 1, 8093 Zurich, Switzerland
| | - Friederikee Horn
- Technical
University of Munich, Department of Electrical
and Computer Engineering Munchen, Bayern, DE 80333, Germany
| | - Max Earle
- Cavendish
Laboratory, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0HE, U.K.
| | - German Lanzavecchia
- Istituto
Italiano di Tecnologia, via Morego 30, I-16163 Genova, Italy
- Dipartimento
di Fisica, Università di Genova, via Dodecaneso 33, 16146 Genova, Italy
| | - Aitziber L. Cortajarena
- Center
for Cooperative Research in Biomaterials (CICbiomaGUNE), Basque Research and Technology Alliance (BRTA), Paseo de Miramón 194, 20014 Donostia-San Sebastián, Spain
- Ikerbasque, Basque
Foundation for Science, 48009 Bilbao, Spain
| | - Luis M. Liz-Marzán
- Center
for Cooperative Research in Biomaterials (CICbiomaGUNE), Basque Research and Technology Alliance (BRTA), Paseo de Miramón 194, 20014 Donostia-San Sebastián, Spain
- Ikerbasque, Basque
Foundation for Science, 48009 Bilbao, Spain
- Biomedical
Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Av. Monforte de Lemos, 3-5. Pabellón 11.
Planta 0, 28029 Madrid, Spain
| | - Na Liu
- Second
Physics Institute, University of Stuttgart, 70569 Stuttgart, Germany
- Max Planck Institute for Solid State Research, 70569 Stuttgart, Germany
| | - Reinhard Heckel
- Technical
University of Munich, Department of Electrical
and Computer Engineering Munchen, Bayern, DE 80333, Germany
| | - Robert N. Grass
- Institute
for Chemical and Bioengineering, ETH Zurich, Vladimir-Prelog-Weg 1, 8093 Zurich, Switzerland
| | - Roman Krahne
- Istituto
Italiano di Tecnologia, via Morego 30, I-16163 Genova, Italy
| | - Ulrich F. Keyser
- Cavendish
Laboratory, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0HE, U.K.
| | - Denis Garoli
- Istituto
Italiano di Tecnologia, via Morego 30, I-16163 Genova, Italy
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38
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Zhang J. Levy Equilibrium Optimizer algorithm for the DNA storage code set. PLoS One 2022; 17:e0277139. [PMID: 36395269 PMCID: PMC9671426 DOI: 10.1371/journal.pone.0277139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 10/10/2022] [Indexed: 11/18/2022] Open
Abstract
The generation of massive data puts forward higher requirements for storage technology. DNA storage is a new storage technology which uses biological macromolecule DNA as information carrier. Compared with traditional silicon-based storage, DNA storage has the advantages of large capacity, high density, low energy consumption and high durability. DNA coding is to store data information with as few base sequences as possible without errors. Coding is a key technology in DNA storage, and its results directly affect the performance of storage and the integrity of data reading and writing. In this paper, a Levy Equilibrium Optimizer (LEO) algorithm is proposed to construct a DNA storage code set that satisfies combinatorial constraints. The performance of the proposed algorithm is tested on 13 benchmark functions, and 4 new global optima are obtained. Under the same constraints, the DNA storage code set is constructed. Compared with previous work, the lower bound of DNA storage code set is improved by 4-13%.
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Affiliation(s)
- Jianxia Zhang
- School of Intelligent Engineering, Henan Institute of Technology, Xinxiang, China
- * E-mail:
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39
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Yang Lu J, Qi Bu Z, Tao Huang W. Peptide-based sensing of Pb2+, molecular logic computing, information encoding, cryptography, and steganography. Microchem J 2022. [DOI: 10.1016/j.microc.2022.108198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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40
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Lu JY, Jiang Q, Lei JJ, He YX, Huang WT. Molecular ‘email’: Electrochemical aptasensing of fish pathogens, molecular information encoding, encryption and hiding applications. Anal Chim Acta 2022; 1232:340483. [DOI: 10.1016/j.aca.2022.340483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 09/30/2022] [Accepted: 10/03/2022] [Indexed: 11/01/2022]
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41
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Lee AJ, Rackers JA, Bricker WP. Predicting accurate ab initio DNA electron densities with equivariant neural networks. Biophys J 2022; 121:3883-3895. [PMID: 36057785 PMCID: PMC9674991 DOI: 10.1016/j.bpj.2022.08.045] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 07/22/2022] [Accepted: 08/29/2022] [Indexed: 11/19/2022] Open
Abstract
One of the fundamental limitations of accurately modeling biomolecules like DNA is the inability to perform quantum chemistry calculations on large molecular structures. We present a machine learning model based on an equivariant Euclidean neural network framework to obtain accurate ab initio electron densities for arbitrary DNA structures that are much too large for conventional quantum methods. The model is trained on representative B-DNA basepair steps that capture both base pairing and base stacking interactions. The model produces accurate electron densities for arbitrary B-DNA structures with typical errors of less than 1%. Crucially, the error does not increase with system size, which suggests that the model can extrapolate to large DNA structures with negligible loss of accuracy. The model also generalizes reasonably to other DNA structural motifs such as the A- and Z-DNA forms, despite being trained on only B-DNA configurations. The model is used to calculate electron densities of several large-scale DNA structures, and we show that the computational scaling for this model is essentially linear. We also show that this machine learning electron density model can be used to calculate accurate electrostatic potentials for DNA. These electrostatic potentials produce more accurate results compared with classical force fields and do not show the usual deficiencies at short range.
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Affiliation(s)
- Alex J Lee
- Department of Chemical and Biological Engineering, University of New Mexico, Albuquerque, New Mexico
| | - Joshua A Rackers
- Center for Computing Research, Sandia National Laboratories, Albuquerque, New Mexico.
| | - William P Bricker
- Department of Chemical and Biological Engineering, University of New Mexico, Albuquerque, New Mexico.
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42
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Luo Y, Wang S, Feng Z, Li J, Mao C, Wang R, Jiang X. Integrated Microfluidic DNA Storage Platform with Automated Sample Handling and Physical Data Partitioning. Anal Chem 2022; 94:13153-13162. [DOI: 10.1021/acs.analchem.2c02667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Yuan Luo
- Shenzhen Key Laboratory of Smart Healthcare Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Rd., Xili, Nanshan District, Shenzhen518055, Guangdong, P. R. China
- Guangdong Provincial Key Laboratory of Advanced Biomaterials, No 1088, Xueyuan Rd., Xili, Nanshan
District, Shenzhen518055, Guangdong, P. R. China
- State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai200050, China
| | - Shuchen Wang
- Shenzhen Key Laboratory of Smart Healthcare Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Rd., Xili, Nanshan District, Shenzhen518055, Guangdong, P. R. China
- Guangdong Provincial Key Laboratory of Advanced Biomaterials, No 1088, Xueyuan Rd., Xili, Nanshan
District, Shenzhen518055, Guangdong, P. R. China
| | - Zhuowei Feng
- Shenzhen Key Laboratory of Smart Healthcare Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Rd., Xili, Nanshan District, Shenzhen518055, Guangdong, P. R. China
- Guangdong Provincial Key Laboratory of Advanced Biomaterials, No 1088, Xueyuan Rd., Xili, Nanshan
District, Shenzhen518055, Guangdong, P. R. China
| | - Jie Li
- Department of Electronic and Electrical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Rd., Xili, Nanshan District, Shenzhen518055, Guangdong, P. R. China
| | - Cuiping Mao
- Shenzhen Key Laboratory of Smart Healthcare Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Rd., Xili, Nanshan District, Shenzhen518055, Guangdong, P. R. China
- Guangdong Provincial Key Laboratory of Advanced Biomaterials, No 1088, Xueyuan Rd., Xili, Nanshan
District, Shenzhen518055, Guangdong, P. R. China
| | - Rui Wang
- Department of Electronic and Electrical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Rd., Xili, Nanshan District, Shenzhen518055, Guangdong, P. R. China
| | - Xingyu Jiang
- Shenzhen Key Laboratory of Smart Healthcare Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Rd., Xili, Nanshan District, Shenzhen518055, Guangdong, P. R. China
- Guangdong Provincial Key Laboratory of Advanced Biomaterials, No 1088, Xueyuan Rd., Xili, Nanshan
District, Shenzhen518055, Guangdong, P. R. China
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43
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Song L, Geng F, Gong ZY, Chen X, Tang J, Gong C, Zhou L, Xia R, Han MZ, Xu JY, Li BZ, Yuan YJ. Robust data storage in DNA by de Bruijn graph-based de novo strand assembly. Nat Commun 2022; 13:5361. [PMID: 36097016 PMCID: PMC9468002 DOI: 10.1038/s41467-022-33046-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 08/31/2022] [Indexed: 11/16/2022] Open
Abstract
DNA data storage is a rapidly developing technology with great potential due to its high density, long-term durability, and low maintenance cost. The major technical challenges include various errors, such as strand breaks, rearrangements, and indels that frequently arise during DNA synthesis, amplification, sequencing, and preservation. In this study, a de novo strand assembly algorithm (DBGPS) is developed using de Bruijn graph and greedy path search to meet these challenges. DBGPS shows substantial advantages in handling DNA breaks, rearrangements, and indels. The robustness of DBGPS is demonstrated by accelerated aging, multiple independent data retrievals, deep error-prone PCR, and large-scale simulations. Remarkably, 6.8 MB of data is accurately recovered from a severely corrupted sample that has been treated at 70 °C for 70 days. With DBGPS, we are able to achieve a logical density of 1.30 bits/cycle and a physical density of 295 PB/g.
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Affiliation(s)
- Lifu Song
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjin, 300072, China
- School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
| | - Feng Geng
- College of Pharmacy, Binzhou Medical University, Yantai, 264003, Shandong Province, China
| | - Zi-Yi Gong
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjin, 300072, China
- School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
| | - Xin Chen
- Centor for Applied Mathematics, Tianjin University, Tianjin, 300072, China
| | - Jijun Tang
- School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin, 300350, China
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Chunye Gong
- National SuperComputer Center in Tianjin, Tianjin, 300457, China
| | - Libang Zhou
- College of Food Science and Technology, Nanjing Agricultural University, Nanjing, 210095, Jiangsu Province, China
| | - Rui Xia
- National SuperComputer Center in Tianjin, Tianjin, 300457, China
| | - Ming-Zhe Han
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjin, 300072, China
- School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
| | - Jing-Yi Xu
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjin, 300072, China
- School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
| | - Bing-Zhi Li
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjin, 300072, China.
- School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China.
| | - Ying-Jin Yuan
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjin, 300072, China.
- School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China.
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44
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Liu Y, Ren Y, Li J, Wang F, Wang F, Ma C, Chen D, Jiang X, Fan C, Zhang H, Liu K. In vivo processing of digital information molecularly with targeted specificity and robust reliability. SCIENCE ADVANCES 2022; 8:eabo7415. [PMID: 35930647 PMCID: PMC9355361 DOI: 10.1126/sciadv.abo7415] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 06/22/2022] [Indexed: 05/28/2023]
Abstract
DNA has attracted increasing interest as an appealing medium for information storage. However, target-specific rewriting of the digital data stored in intracellular DNA remains a grand challenge because the highly repetitive nature and uneven guanine-cytosine content render the encoded DNA sequences poorly compatible with endogenous ones. In this study, a dual-plasmid system based on gene editing tools was introduced into Escherichia coli to process information accurately. Digital data containing large repeat units in binary codes, such as text, codebook, or image, were involved in the realization of target-specific rewriting in vivo, yielding up to 94% rewriting reliability. An optical reporter was introduced as an advanced tool for presenting data processing at the molecular level. Rewritten information was stored stably and amplified over hundreds of generations. Our work demonstrates a digital-to-biological information processing approach for highly efficient data storage, amplification, and rewriting, thus robustly promoting the application of DNA-based information technology.
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Affiliation(s)
- Yangyi Liu
- Department of Chemistry, Tsinghua University, Beijing, China
| | - Yubin Ren
- Department of Chemistry, Tsinghua University, Beijing, China
| | - Jingjing Li
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, China
| | - Fan Wang
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, China
| | - Fei Wang
- Frontiers Science Center for Transformative Molecules, School of Chemistry and Chemical Engineering, and Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Chao Ma
- Department of Chemistry, Tsinghua University, Beijing, China
| | - Dong Chen
- College of Energy Engineering and State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, China
| | - Xingyu Jiang
- Department of Biomedical Engineering, Southern University of Science and Technology, No. 1088 Xueyuan Road, Nanshan District, Shenzhen, Guangdong, China
| | - Chunhai Fan
- Frontiers Science Center for Transformative Molecules, School of Chemistry and Chemical Engineering, and Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Hongjie Zhang
- Department of Chemistry, Tsinghua University, Beijing, China
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, China
| | - Kai Liu
- Department of Chemistry, Tsinghua University, Beijing, China
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, China
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45
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Wang P, Mu Z, Sun L, Si S, Wang B. Hidden Addressing Encoding for DNA Storage. Front Bioeng Biotechnol 2022; 10:916615. [PMID: 35928958 PMCID: PMC9344065 DOI: 10.3389/fbioe.2022.916615] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Accepted: 06/21/2022] [Indexed: 11/13/2022] Open
Abstract
DNA is a natural storage medium with the advantages of high storage density and long service life compared with traditional media. DNA storage can meet the current storage requirements for massive data. Owing to the limitations of the DNA storage technology, the data need to be converted into short DNA sequences for storage. However, in the process, a large amount of physical redundancy will be generated to index short DNA sequences. To reduce redundancy, this study proposes a DNA storage encoding scheme with hidden addressing. Using the improved fountain encoding scheme, the index replaces part of the data to realize hidden addresses, and then, a 10.1 MB file is encoded with the hidden addressing. First, the Dottup dot plot generator and the Jaccard similarity coefficient analyze the overall self-similarity of the encoding sequence index, and then the sequence fragments of GC content are used to verify the performance of this scheme. The final results show that the encoding scheme indexes with overall lower self-similarity, and the local thermodynamic properties of the sequence are better. The hidden addressing encoding scheme proposed can not only improve the utilization of bases but also ensure the correct rate of DNA storage during the sequencing and decoding processes.
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46
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Adaptive coding for DNA storage with high storage density and low coverage. NPJ Syst Biol Appl 2022; 8:23. [PMID: 35788589 PMCID: PMC9253015 DOI: 10.1038/s41540-022-00233-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 06/10/2022] [Indexed: 11/09/2022] Open
Abstract
The rapid development of information technology has generated substantial data, which urgently requires new storage media and storage methods. DNA, as a storage medium with high density, high durability, and ultra-long storage time characteristics, is promising as a potential solution. However, DNA storage is still in its infancy and suffers from low space utilization of DNA strands, high read coverage, and poor coding coupling. Therefore, in this work, an adaptive coding DNA storage system is proposed to use different coding schemes for different coding region locations, and the method of adaptively generating coding constraint thresholds is used to optimize at the system level to ensure the efficient operation of each link. Images, videos, and PDF files of size 698 KB were stored in DNA using adaptive coding algorithms. The data were sequenced and losslessly decoded into raw data. Compared with previous work, the DNA storage system implemented by adaptive coding proposed in this paper has high storage density and low read coverage, which promotes the development of carbon-based storage systems.
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Winston C, Organick L, Ward D, Ceze L, Strauss K, Chen YJ. Combinatorial PCR Method for Efficient, Selective Oligo Retrieval from Complex Oligo Pools. ACS Synth Biol 2022; 11:1727-1734. [PMID: 35191684 DOI: 10.1021/acssynbio.1c00482] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
With the rapidly decreasing cost of array-based oligo synthesis, large-scale oligo pools offer significant benefits for advanced applications including gene synthesis, CRISPR-based gene editing, and DNA data storage. The selective retrieval of specific oligos from these complex pools traditionally uses polymerase chain reaction (PCR). Designing a large number of primers to use in PCR presents a serious challenge, particularly for DNA data storage, where the size of an oligo pool is orders of magnitude larger than other applications. Although a nested primer address system was recently developed to increase the number of accessible files for DNA storage, it requires more complicated lab protocols and more expensive reagents to achieve high specificity, as well as more DNA address space. Here, we present a new combinatorial PCR method that has none of those drawbacks and outperforms in retrieval specificity. In experiments, we accessed three files that each comprised 1% of a DNA prototype database that contained 81 different files and enriched them to over 99.9% using our combinatorial primer method. Our method provides a viable path for scaling up DNA data storage systems and has broader utility whenever one must access a specific target oligo and can design their own primer regions.
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Affiliation(s)
- Claris Winston
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
| | - Lee Organick
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
| | - David Ward
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
| | - Luis Ceze
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
| | - Karin Strauss
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
- Microsoft Research, Redmond, Washington 98052, United States
| | - Yuan-Jyue Chen
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
- Microsoft Research, Redmond, Washington 98052, United States
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Song J, Nötzel R. Noise logic with an InGaN/SiN x/Si uniband diode photodetector. Sci Rep 2022; 12:8376. [PMID: 35589857 PMCID: PMC9120468 DOI: 10.1038/s41598-022-12481-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 05/11/2022] [Indexed: 11/24/2022] Open
Abstract
Noise logic is introduced by the wavelength dependent photocurrent noise of an InGaN/SiNx/Si uniband diode photodetector. A wavelength versus photocurrent noise discrimination map is constructed from the larger photocurrent noise for red light than that for green light. A minimum measurement time of four seconds is deduced from the standard deviation of the photocurrent noise for a safe wavelength distinction. A logic NOT gate is realized as representative with on or off red or green light as binary 1 or 0 inputs and the photocurrent noise above or below a defined threshold as binary 1 or 0 outputs.
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Affiliation(s)
- Jiaxun Song
- Guangdong Provincial Key Laboratory of Optical Information Materials and Technology, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, People's Republic of China.
| | - Richard Nötzel
- Guangdong Provincial Key Laboratory of Optical Information Materials and Technology, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, People's Republic of China.
- National Center for International Research on Green Optoelectronics, South China Normal University, Guangzhou, 510006, People's Republic of China.
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Ezekannagha C, Becker A, Heider D, Hattab G. Design considerations for advancing data storage with synthetic DNA for long-term archiving. Mater Today Bio 2022; 15:100306. [PMID: 35677811 PMCID: PMC9167972 DOI: 10.1016/j.mtbio.2022.100306] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 05/05/2022] [Accepted: 05/22/2022] [Indexed: 11/22/2022]
Abstract
Deoxyribonucleic acid (DNA) is increasingly emerging as a serious medium for long-term archival data storage because of its remarkable high-capacity, high-storage-density characteristics and its lasting ability to store data for thousands of years. Various encoding algorithms are generally required to store digital information in DNA and to maintain data integrity. Indeed, since DNA is the information carrier, its performance under different processing and storage conditions significantly impacts the capabilities of the data storage system. Therefore, the design of a DNA storage system must meet specific design considerations to be less error-prone, robust and reliable. In this work, we summarize the general processes and technologies employed when using synthetic DNA as a storage medium. We also share the design considerations for sustainable engineering to include viability. We expect this work to provide insight into how sustainable design can be used to develop an efficient and robust synthetic DNA-based storage system for long-term archiving.
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Affiliation(s)
- Chisom Ezekannagha
- Department of Mathematics and Computer Science, Philipps-Universität Marburg, Hans-Meerwein-Str. 6, D-35043, Marburg, Germany
- Corresponding author.
| | - Anke Becker
- Center for Synthetic Microbiology (SYNMIKRO), Philipps-Universität Marburg, Karl-von-Frisch-Str. 14, D-35043, Marburg, Germany
| | - Dominik Heider
- Department of Mathematics and Computer Science, Philipps-Universität Marburg, Hans-Meerwein-Str. 6, D-35043, Marburg, Germany
| | - Georges Hattab
- Department of Mathematics and Computer Science, Philipps-Universität Marburg, Hans-Meerwein-Str. 6, D-35043, Marburg, Germany
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Barclay MS, Wilson CK, Roy SK, Mass OA, Obukhova OM, Svoiakov RP, Tatarets AL, Chowdhury AU, Huff JS, Turner DB, Davis PH, Terpetschnig EA, Yurke B, Knowlton WB, Lee J, Pensack RD. Oblique Packing and Tunable Excitonic Coupling in DNA‐Templated Squaraine Rotaxane Dimer Aggregates. CHEMPHOTOCHEM 2022. [DOI: 10.1002/cptc.202200039] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Matthew S. Barclay
- Boise State University Micron School of Materials Science & Engineering UNITED STATES
| | - Christopher K. Wilson
- Boise State University Micron School of Materials Science & Engineering UNITED STATES
| | - Simon K. Roy
- Boise State University Micron School of Materials Science & Engineering UNITED STATES
| | - Olga A. Mass
- Boise State University Micron School of Materials Science & Engineering UNITED STATES
| | - Olena M. Obukhova
- SSI Institute for Single Crystals NAS of Ukraine: Naukovo-tehnologicnij kompleks Institut monokristaliv Nacional'na akademia nauk Ukraini Department of Luminescent Materials and Dyes UKRAINE
| | - Rostyslav P. Svoiakov
- SSI Institute for Single Crystals NAS of Ukraine: Naukovo-tehnologicnij kompleks Institut monokristaliv Nacional'na akademia nauk Ukraini Department of Luminescent Materials and Dyes UKRAINE
| | - Anatoliy L. Tatarets
- SSI Institute for Single Crystals NAS of Ukraine: Naukovo-tehnologicnij kompleks Institut monokristaliv Nacional'na akademia nauk Ukraini Department of Luminescent Materials and Dyes UKRAINE
| | - Azhad U. Chowdhury
- Boise State University Micron School of Materials Science & Engineering UNITED STATES
| | - Jonathan S. Huff
- Boise State University Micron School of Materials Science & Engineering UNITED STATES
| | - Daniel B. Turner
- Boise State University Micron School of Materials Science & Engineering UNITED STATES
| | - Paul H. Davis
- Boise State University Micron School of Materials Science & Engineering UNITED STATES
| | | | - Bernard Yurke
- Boise State University Micron School of Materials Science & Engineering; Department of Electrical & Computer Engineering UNITED STATES
| | - William B. Knowlton
- Boise State University Micron School of Materials Science & Engineering; Department of Electrical & Computer Engineering UNITED STATES
| | - Jeunghoon Lee
- Boise State University Micron School of Materials Science & Engineering; Department of Chemistry & Biochemistry UNITED STATES
| | - Ryan D. Pensack
- Boise State University Micron School of Materials Science & Engineering 1435 W University Dr 83706 Boise UNITED STATES
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