R&D: Six Articles on DNA Data Storage

R&D: Linked data storage using DNA Origami nanostructures
Authors present a DNA origami nanostructure-enabled linked data storage (DONLDS) system that implements a linked list architecture.

Nature Communications has published an article written by Chenhao Zhang, Mo Xie, Lianhui Wang, State Key Laboratory for Flexible Electronics (LoFE), Nanjing University of Posts and Telecommunications, Nanjing, China, Jiangsu Key Laboratory for Biosensors, Nanjing University of Posts and Telecommunications, Nanjing, China, and School of Materials Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China, Chunhai Fan, School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai, China, New Cornerstone Science Laboratory, Shanghai, China, Frontiers Science Center for Transformative Molecules, Shanghai Jiao Tong University, Shanghai, China, Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai, China, and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China, and Jie Chao, State Key Laboratory for Flexible Electronics (LoFE), Nanjing University of Posts and Telecommunications, Nanjing, China, Jiangsu Key Laboratory for Biosensors, Nanjing University of Posts and Telecommunications, Nanjing, China, and School of Materials Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China.

Abstract: “DNA-based storage is an alternative solution for archiving vast cold data. Its future development aims to meet the demands of hot data storage, which requires rapid random access and efficient data modification. Here, we present a DNA origami nanostructure-enabled linked data storage (DONLDS) system that implements a linked list architecture. This system uses distinct DNA origami shapes as nodes to store diverse data (English letters, numerals, Chinese characters) in binary locations, achieving a storage density of 222.22 Gbit/cm². Pointers, defined by DNA strands at the nanostructure edges, establish data positions. Furthermore, detachable DNA strands serve as instructions, enabling dynamic linking of pointers for accurate storage and their reversible detachment for dynamic data retrieval. The DONLDS system eliminates the need for full-structure traversal, enables parallel data storage, and supports data insertion and removal. This highlights its adaptability and accuracy in managing complex datasets.“

R&D: High-speed 3D DNA PAINT and unsupervised clustering for unlocking 3D DNA Origami cryptography
Authors’ findings show that DNA-based cryptography is a secure and versatile solution for storing information.

Nature Communications has published an article written by Gde Bimananda Mahardika Wisna, Department of Physics, Arizona State University, Tempe, AZ, USA, Center for Molecular Design and Biomimetics at the Biodesign Institute, Arizona State University, Tempe, AZ, USA, and Center for Biological Physics, Arizona State University, Tempe, AZ, USA, Daria Sukhareva, Center for Molecular Design and Biomimetics at the Biodesign Institute, Arizona State University, Tempe, AZ, USA, and School of Molecular Sciences, Arizona State University, Tempe, AZ, USA, Jonathan Zhao, Center for Molecular Design and Biomimetics at the Biodesign Institute, Arizona State University, Tempe, AZ, USA, and School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, USA, Prathamesh Chopade, Center for Molecular Design and Biomimetics at the Biodesign Institute, Arizona State University, Tempe, AZ, USA, Deeksha Satyabola, Center for Molecular Design and Biomimetics at the Biodesign Institute, Arizona State University, Tempe, AZ, USA, and School of Molecular Sciences, Arizona State University, Tempe, AZ, USA, Michael Matthies, Center for Molecular Design and Biomimetics at the Biodesign Institute, Arizona State University, Tempe, AZ, USA, Subhajit Roy, Department of Physics, Arizona State University, Tempe, AZ, USA, Center for Molecular Design and Biomimetics at the Biodesign Institute, Arizona State University, Tempe, AZ, USA, and Center for Biological Physics, Arizona State University, Tempe, AZ, USA, Chao Wang, Center for Molecular Design and Biomimetics at the Biodesign Institute, Arizona State University, Tempe, AZ, USA, and School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, USA, Petr Šulc, Center for Molecular Design and Biomimetics at the Biodesign Institute, Arizona State University, Tempe, AZ, USA, Center for Biological Physics, Arizona State University, Tempe, AZ, USA, and School of Molecular Sciences, Arizona State University, Tempe, AZ, USA, Hao Yan, Center for Molecular Design and Biomimetics at the Biodesign Institute, Arizona State University, Tempe, AZ, USA, and School of Molecular Sciences, Arizona State University, Tempe, AZ, USA, and Rizal F. Hariadi, Department of Physics, Arizona State University, Tempe, AZ, USA, Center for Molecular Design and Biomimetics at the Biodesign Institute, Arizona State University, Tempe, AZ, USA, and Center for Biological Physics, Arizona State University, Tempe, AZ, USA.

Abstract: “DNA origami information storage is a promising alternative to silicon-based data storage, offering a molecular cryptography technique concealing information within DNA origami. Routing, sliding, and interlacing staple strands lead to a large 700-bit key size. Practical DNA data storage requires high information density, robust security, and accurate and rapid information retrieval. Consequently, advanced readout techniques and large encryption key sizes are essential. Here, we report an enhanced DNA origami cryptography protocol in 2D and 3D DNA origami, increasing the encryption key size. We employ all-DNA-based steganography with fast readout through high-speed DNA-PAINT super-resolution imaging. By combining DNA-PAINT data with unsupervised clustering, we achieve an accuracy of up to 89%, despite the flexibility in the 3D DNA origami shown by oxDNA simulation. Furthermore, we propose criteria that ensure complete information retrieval for the DNA origami cryptography. Our findings show that DNA-based cryptography is a secure and versatile solution for storing information.“

R&D: DNA storage in the short molecule regime
Authors study the amount of reliable information that can be stored in a DNA-based storage system composed of short DNA molecules.

arXiv has published an article written by R. Tamir, Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain, N. Weinberger, Department of Electrical and Computer Engineering, Technion, Haifa 3200003, Israel, A. Guillén i Fàbregas, Department of Engineering, University of Cambridge, CB2 1PZ Cambridge, UK, and Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain

Abstract: “We study the amount of reliable information that can be stored in a DNA-based storage system composed of short DNA molecules. In this regime, Shomorony and Heckel (2022) put forward a conjecture on the scaling of the number of information bits that can be reliably stored. In this paper, we complete the proof of this conjecture. We analyze a random-coding scheme in which each codeword is obtained by quantizing a randomly generated probability mass function drawn from the probability simplex. By analyzing the optimal maximum-likelihood decoder, we derive an achievability bound that matches a recently established converse bound across the entire short-molecule regime. We also propose a second coding scheme, which operates with significantly lower computational complexity but achieves the optimal scaling, except for a specific range of very short molecules.“

R&D: NEURODNAAI, Neural pipeline approaches for advancing dna-based information storage as a sustainable digital medium using deep learning framework
NeuroDNAAI encodes binary data streams into symbolic DNA sequences, transmits them through a noisy channel with substitutions, insertions, and deletions, and reconstructs them with high fidelity.

arXiv has published an article written by Rakesh Thakur, Amity Centre for Artificial Intelligence, Amity University, India, Lavanya Singh, Yashika, Amity School of Engineering and Technology, Amity University, India, Manomay Bundawala, and Aruna Kumar, Amity Institute of Biotechnology, Amity University, India.

Abstract: “DNA is a promising medium for digital information storage for its exceptional density and durability. While prior studies advanced coding theory, workflow design, and simulation tools, challenges such as synthesis costs, sequencing errors, and biological constraints (GC-content imbalance, homopolymers) limit practical deployment. To address this, our framework draws from quantum parallelism concepts to enhance encoding diversity and resilience, integrating biologically informed constraints with deep learning to enhance error mitigation in DNA storage. NeuroDNAAI encodes binary data streams into symbolic DNA sequences, transmits them through a noisy channel with substitutions, insertions, and deletions, and reconstructs them with high fidelity. Our results show that traditional prompting or rule-based schemes fail to adapt effectively to realistic noise, whereas NeuroDNAAI achieves superior accuracy. Experiments on benchmark datasets demonstrate low bit error rates for both text and images. By unifying theory, workflow, and simulation into one pipeline, NeuroDNAAI enables scalable, biologically valid archival DNA storage.“

R&D: Coding for ordered composite DNA sequences
Authors propose a novel channel model for composite DNA in which composite sequences are decomposed into ordered standard non-composite sequences.

arXiv has published an article written by Besart Dollma, Eitan Yaakobi, Department of Computer Science, Technion – Israel Institute of Technology, Israel, and Ohad Elishco, School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Israel.

Abstract: “To increase the information capacity of DNA storage, composite DNA letters were introduced. We propose a novel channel model for composite DNA in which composite sequences are decomposed into ordered standard non-composite sequences. The model is designed to handle any alphabet size and composite resolution parameter. We study the problem of reconstructing composite sequences of arbitrary resolution over the binary alphabet under substitution errors. We define two families of error-correcting codes and provide lower and upper bounds on their cardinality. In addition, we analyze the case in which a single deletion error occurs in the channel and present a systematic code construction for this setting. Finally, we briefly discuss the channel’s capacity, which remains an open problem.“

R&D: Block length gain for nanopore channels
DNA is an attractive candidate for data storage; its millennial durability and nanometer scale offer exceptional data density and longevity.

arXiv has published an article written by Yu-Ting Lin, Hsin-Po Wang, and Venkatesan Guruswami.

Abstract: “DNA is an attractive candidate for data storage. Its millennial durability and nanometer scale offer exceptional data density and longevity. Its relevance to medical applications also drives advances in DNA-related biotechnology.“
“To protect our data against errors, a straightforward approach uses one error-correcting code per DNA strand, with a Reed–Solomon code protecting the collection of strands. A downside is that current technology can only synthesize strands 200–300 nucleotides long. At this block length, the inner code rate suffers a significant finite-length penalty, making its effective capacity hard to characterize.“
“Last year, we proposed \textit{Geno-Weaving} in a JSAIT publication. The idea is to protect the same position across multiple strands using one code; this provably achieves capacity against substitution errors. In this paper, we extend the idea to combat deletion errors and show two more advantages of Geno-Weaving: (1) Because the number of strands is 3–4 orders of magnitude larger than the strand length, the finite-length penalty vanishes. (2) At realistic deletion rates 0.1\%–10\%, Geno-Weaving designed for BSCs works well empirically, bypassing the need to tailor the design for deletion channels.“