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Over the past decades, remarkable progress on phosphoramidite chemistry-based large-scale de novo oligonucleotide synthesis has been achieved, enabling numerous novel and exciting applications. Among them, de novo genome synthesis and DNA data storage are striking. However, to make these two applications more practical, the synthesis length, speed, cost, and throughput require vast improvements, which is a challenge to be met by the phosphoramidite chemistry. Harnessing the power of enzymes, the recently emerged enzymatic methods provide a competitive route to overcome this challenge. In this review, we first summarize the status of large-scale oligonucleotide synthesis technologies including the basic methodology and large-scale synthesis approaches, with special focus on the emerging enzymatic methods. Afterward, we discuss the opportunities and challenges of large-scale oligonucleotide synthesis on de novo genome synthesis and DNA data storage respectively.

DNA has emerged as a promising storage medium to meet the soaring need for archival data storage because of its exceptional storage density and stability. However, current DNA‐based data storage systems are incompetent of achieving high‐quality random multiplexed access and frequently accessed data storage, which impedes its practical applications. Here, a dual‐mode storage system is proposed that combines DNA‐based archival data and nanodot‐based active data. This novel data‐storage system is constructed by writing the active and archival data on the same substrate through a facile two‐step process involving scanning probe lithography (SPL), DNA synthesis, and chemical immobilization. The data files are categorized and stored orderly in different microregions of the substrate to achieve efficient random access. On each microregion, the nanodot array stores not only the concise information for the archival DNA data but also contains the corresponding primer sequence. Such interrelation between active and archival data allows for facilely data reading by efficient microscopic modalities and in situ polymerase chain reaction (PCR). Facilitated by the integration of nanodot and DNA, this novel dual‐mode storage system demonstrates efficient data access and the potential of excellent storing capacity, paving the way for the advancement of DNA‐based data storage. This study proposes a dual‐mode data storage system, which combines nanodot‐based frequently accessed data (concise data) and DNA‐based archival data (detailed data). Concise data writing/reading is achieved through scanning probe lithography (SPL)/microscopy, and detailed data writing/reading is achieved through DNA immobilization and in situ polymerase chain reaction (PCR). This system accomplishes efficient data access, and provides a new management idea.

The field of storing information in DNA has expanded exponentially. Most common modalities involve encoding information from bits into synthesized nucleotides, storage in liquid or dry media, and decoding via sequencing. However, limitations to this paradigm include the cost of DNA synthesis and sequencing, along with low throughput. Further unresolved questions include the appropriate media of storage and the scalability of such approaches for commercial viability. In this review, we examine various storage modalities involving the use of DNA from a systems-level perspective. We compare novel methods that draw inspiration from molecular biology techniques that have been devised to overcome the difficulties posed by standard workflows and conceptualize potential applications that can arise from these advances. Viable information storage in DNA is largely limited by cost and throughput.Advances in synthesis and sequencing are key in driving adoption.Different novel methods of storing information outside of nucleotide conversion are being explored.The key workflows are not established, giving significant room for exploration.The integration of molecular biology, engineering, and computing will drive further innovation.

DNA is a more efficient and long-lasting data storage method. It offers better compression, higher physical density, longer stability, and lower energetic cost than traditional digital methods. Metadata should be embedded in the DNA sequence.Biocybersecurity must be prioritized to prevent attacks with synthetic DNA that could encode malware triggered during DNA sequence analysis.Standardization of the coding and decoding process is necessary for long-term accessibility. Errors in methodology can lead to data loss, emphasizing the need for a reliable protocol for handling samples.Inclusion of identifying features in the DNA is crucial for future recognition of it as data storage. Markers or sequences can indicate that the DNA is synthetic, not biological. This ensures that future generations can recognize and access the stored data even if knowledge of DNA data storage is lost. DNA is an intelligent data storage medium due to its stability and high density. It has been used by nature for over 3.5 billion years. Compared with traditional methods, DNA offers better compression and physical density. DNA can retain information for thousands of years. However, challenges exist in scalability, standardization, metadata gathering, biocybersecurity, and specialized tools. Addressing these challenges is crucial for widespread implementation. Collaboration among experts, as well as keeping the future in mind, is needed to unlock the full potential of DNA data storage, which promises low energy costs, high-density storage, and long-term stability. DNA is an intelligent data storage medium due to its stability and high density. It has been used by nature for over 3.5 billion years. Compared with traditional methods, DNA offers better compression and physical density. DNA can retain information for thousands of years. However, challenges exist in scalability, standardization, metadata gathering, biocybersecurity, and specialized tools. Addressing these challenges is crucial for widespread implementation. Collaboration among experts, as well as keeping the future in mind, is needed to unlock the full potential of DNA data storage, which promises low energy costs, high-density storage, and long-term stability.

Although DNA-based data storage theoretically provides an information density of 2 bits per nucleotide, biochemical constraints transform sequence design into a high-dimensional constrained combinatorial optimization problem. The high computational cost and low encoding efficiency of conventional rule-based approaches make metaheuristic methods an effective alternative. This study proposes the TC-HUR hybrid algorithm to simultaneously optimize information density and conflicting biophysical constraints, including homopolymer (HP) length, GC content, melting temperature (Tm), and reverse-complement (RC) similarity. The method escapes local optima using Cauchy jump-enhanced Hunger Games Search (HGS), performs high-precision exploitation via Runge–Kutta (RUN) operators, and refines constraint violations at the nucleotide level through an adaptive intensive mutation mechanism. The algorithm is evaluated on a complex dataset of 1853 nucleotides under different noise regimes. TC-HUR outperforms RUN by 2.5% and HGS by 16.7% in average fitness. While maintaining homopolymer length near the ideal threshold, it reduces reverse-complement similarity to 19.10%, ensuring high sequence diversity. Under high-noise conditions, TC-HUR achieves a normalized edit distance of 0.1290, reducing insertion–deletion (indel) errors by approximately 14%. The results demonstrate that the proposed model effectively generates biophysically synthesizable and noise-resilient DNA codes.

The exponential growth of the total amount of global data presents a huge challenge to mainstream storage media. The emergence of molecular digital storage inspires the development of the new‐generation higher‐density digital data storage. In particular, DNA with high storage density, reproducibility, and long recoverable lifetime behaves the ideal representative of molecular digital storage media. With the development of DNA synthesis and sequencing technologies and the reduction of cost, DNA digital storage has attracted more and more attention and achieved significant breakthroughs. Herein, this Review briefly describes the workflow of DNA storage, and highlights the storage step of DNA digital data storage. Then, according to different information storage forms, the current DNA information encryption methods are emphatically expounded. Finally, the brief perspectives on the current challenges and optimizing proposals in DNA information preservation and encryption are presented. DNA‐based data storage is regarded as the optimal next‐generation information storage strategy. This Review summarizes the recent advances in preservation method of DNA data storage, including in vivo, in vitro and protective storage. Meanwhile, information encryption and steganography based on different preservation strategies are also highlighted.

In the face of exponential data growth, DNA‐based storage offers a promising solution for preserving big data. However, most existing DNA storage methods, akin to traditional block printing, require costly chemical synthesis for each individual data file, adopting a sequential, one‐time‐use synthesis approach. To overcome these limitations, a novel, cost‐effective “DNA‐movable‐type storage” system, inspired by movable type printing, is introduced. This system utilizes prefabricated DNA movable types‐short, double‐stranded DNA oligonucleotides encoding specific payload, address, and checksum data. These DNA‐MTs are enzymatically ligated/assembled into cohesive sequences, termed “DNA movable type blocks,” streamlining the assembly process with the automated BISHENG‐1 DNA‐MT inkjet printer. Using BISHENG‐1, 43.7 KB of data files are successfully printed, assembled, stored, and accurately retrieved in diverse formats (text, image, audio, and video) in vitro and in vivo, using only 350 DNA‐MTs. Notably, each DNA‐MT, synthesized once (2 OD), can be used up to 10000 times, reducing costs to$122/MB—outperforming existing DNA storage methods. This innovation circumvents the need to synthesize entire DNA sequences encoding files from scratch, offering significant cost and efficiency advantages. Furthermore, it has considerable untapped potential to advance a robust DNA storage system, better meeting the extensive data storage demands of the big‐data era. This study presents a cost‐effective “DNA‐movable‐type storage” system inspired by movable type printing. Utilizing reusable prefabricated DNA‐MTs and an automated inkjet printer, BISHENG‐1 stores and retrieves 43.7 KB of data in vitro and in vivo with only 350 DNA‐MTs, achieving storage costs of $ 122 MB−1–significantly more cost‐efficient than traditional DNA synthesis methods.

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. 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 modularized essential functions for DNA data storage and provided personalized codec choices for users. A new codec algorithm called “Wukong” was specially designed and integrated into the tool, which outperforms previous algorithms in key practical application considerations. By connecting to commercial DNA synthesis and sequencing platform with “Storage‐D,” “Diagnosis and treatment protocol for COVID‐19 patients” was successfully stored in DNA both in vitro and in vivo. This platform allows for practical and personalized DNA data storage, potentially with a wide range of applications. The web server and codes of the platform are available at http://storage.dailab.xyz:16666/ and https://github.com/DNAstorage-iSynBio/Storage-D/, respectively. Highlights Deoxyribonucleic acid (DNA) data storage exhibits remarkable advantages, such as high density and long lifespan, and is suggested to be one of the most promising media for coping with future data storage crises. A user‐friendly platform, “Storage‐D” was developed, which enables users to store any format of practical data with personalized choice. Specifically, a new algorithm, named “Wukong” was developed, which contains a sizeable collection of codec pins that enables encoding data into any DNA sequence with considerable privacy. The “Wukong” algorithm shows overall better performance than earlier algorithms in encoding a suitable length of DNA sequence matching downstream biochemical working flow for in vitro and in vivo storage. The tool provides an open‐frame for integrating other codec algorithms and can be easily connected to commercial DNA synthesis and sequencing platform for building a complete pipeline for practical data storage into DNA. The web server and codes of the platform are available at http://storage.dailab.xyz:16666/ and https://github.com/DNAstorage-iSynBio/Storage-D/, respectively.

DNA has emerged as an attractive medium for storing large amounts of data due to its high information density, long-term stability, and low energy consumption. However, in contrast to commercially available storage media, DNA-based data storage currently falls behind in terms of writing and reading speeds, waste as well as cost. To harness the full potential of DNA as a data storage medium, it is imperative to advance high-throughput DNA synthesis without compromising cost and pollution. Industry-standard phosphoramidite DNA synthesis has reached its limitation because of its short nucleotide length (< 200), overconsumption of organic solvents leading to the production of toxic wastes, and slow writing speed. Enzymatic DNA synthesis shows promise as a replacement with long nucleotides, an environmentally friendly process, and fast writing speed. In this review, we overview enzymatic DNA synthesis methods, evaluate current methods that utilize high-throughput and parallel synthesis, and conclude with comments on how enzymatic DNA synthesis can be the answer to DNA data storage.

DNA has been pursued as a novel biomaterial for digital data storage. While large‐scale data storage and random access have been achieved in DNA oligonucleotide pools, repeated data accessing requires constant data replenishment, and these implementations are confined in professional facilities. Here, a mobile data storage system in the genome of the extremophile Halomonas bluephagenesis, which enables dual‐mode storage, dynamic data maintenance, rapid readout, and robust recovery. The system relies on two key components: A versatile genetic toolbox for the integration of 10–100 kb scale synthetic DNA into H. bluephagenesis genome and an efficient error correction coding scheme targeting noisy nanopore sequencing reads. The storage and repeated retrieval of 5 KB data under non‐laboratory conditions are demonstrated. The work highlights the potential of DNA data storage in domestic and field scenarios, and expands its application domain from archival data to frequently accessed data. In this study, a data storage system in Halomonas bluephagenesis genomes, which supports frequent and rapid data retrieval and automated data regeneration in non‐professional environments, are developed. This system expands the application scenarios of DNA data storage to frequent “warm data” accessing in household and field settings, and also underscores the potentials of living cells and long‐fragment DNA for data storage.