Data storage in DNA with fewer synthesis cycles using composite DNA letters

Advances and Challenges in Random Access Techniques for In Vitro DNA Data Storage

With digital transformation and the general application of new technologies, data storage is facing new challenges with the demand for high-density loading of massive information. In response, DNA storage technology has emerged as a promising research direction. Efficient and reliable data retrieval is critical for DNA storage, and the development of random access technology plays a key role in its practicality and reliability. However, achieving fast and accurate random access functions has proven difficult for existing DNA storage efforts, which limits its practical applications in industry. In this review, we summarize the recent advances in DNA storage technology that enable random access functionality, as well as the challenges that need to be overcome and the current solutions. This review aims to help researchers in the field of DNA storage better understand the importance of the random access step and its impact on the overall development of DNA storage. Furthermore, the remaining challenges and future research trends in random access technology of DNA storage are discussed, with the goal of providing a solid foundation for achieving random access in DNA storage under large-scale data conditions.

Overcoming the High Error Rate of Composite DNA Letters-Based Digital Storage through Soft-Decision Decoding

Composite DNA letters, by merging all four DNA nucleotides in specified ratios, offer a pathway to substantially increase the logical density of DNA digital storage (DDS) systems. However, these letters are susceptible to nucleotide errors and sampling bias, leading to a high letter error rate, which complicates precise data retrieval and augments reading expenses. To address this, Derrick-cp is introduced as an innovative soft-decision decoding algorithm tailored for DDS utilizing composite letters. Derrick-cp capitalizes on the distinctive error sensitivities among letters to accurately predict and rectify letter errors, thus enhancing the error-correcting performance of Reed-Solomon codes beyond traditional hard-decision decoding limits. Through comparative analyses in the existing dataset and simulated experiments, Derrick-cp's superiority is validated, notably halving the sequencing depth requirement and slashing costs by up to 22% against conventional hard-decision strategies. This advancement signals Derrick-cp's significant role in elevating both the precision and cost-efficiency of composite letter-based DDS.

High-throughput DNA synthesis for data storage

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.

Efficient data reconstruction: The bottleneck of large-scale application of DNA storage

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.

Efficient DNA-based data storage using shortmer combinatorial encoding

Data storage in DNA has recently emerged as a promising archival solution, offering space-efficient and long-lasting digital storage solutions. Recent studies suggest leveraging the inherent redundancy of synthesis and sequencing technologies by using composite DNA alphabets. A major challenge of this approach involves the noisy inference process, obstructing large composite alphabets. This paper introduces a novel approach for DNA-based data storage, offering, in some implementations, a 6.5-fold increase in logical density over standard DNA-based storage systems, with near-zero reconstruction error. Combinatorial DNA encoding uses a set of clearly distinguishable DNA shortmers to construct large combinatorial alphabets, where each letter consists of a subset of shortmers. We formally define various combinatorial encoding schemes and investigate their theoretical properties. These include information density and reconstruction probabilities, as well as required synthesis and sequencing multiplicities. We then propose an end-to-end design for a combinatorial DNA-based data storage system, including encoding schemes, two-dimensional (2D) error correction codes, and reconstruction algorithms, under different error regimes. We performed simulations and show, for example, that the use of 2D Reed-Solomon error correction has significantly improved reconstruction rates. We validated our approach by constructing two combinatorial sequences using Gibson assembly, imitating a 4-cycle combinatorial synthesis process. We confirmed the successful reconstruction, and established the robustness of our approach for different error types. Subsampling experiments supported the important role of sampling rate and its effect on the overall performance. Our work demonstrates the potential of combinatorial shortmer encoding for DNA-based data storage and describes some theoretical research questions and technical challenges. Combining combinatorial principles with error-correcting strategies, and investing in the development of DNA synthesis technologies that efficiently support combinatorial synthesis, can pave the way to efficient, error-resilient DNA-based storage solutions.

A universal system for boosting gene expression in eukaryotic cell-lines

We demonstrate a transcriptional regulatory design algorithm that can boost expression in yeast and mammalian cell lines. The system consists of a simplified transcriptional architecture composed of a minimal core promoter and a synthetic upstream regulatory region (sURS) composed of up to three motifs selected from a list of 41 motifs conserved in the eukaryotic lineage. The sURS system was first characterized using an oligo-library containing 189,990 variants. We validate the resultant expression model using a set of 43 unseen sURS designs. The validation sURS experiments indicate that a generic set of grammar rules for boosting and attenuation may exist in yeast cells. Finally, we demonstrate that this generic set of grammar rules functions similarly in mammalian CHO-K1 and HeLa cells. Consequently, our work provides a design algorithm for boosting the expression of promoters used for expressing industrially relevant proteins in yeast and mammalian cell lines.

A dual-rule encoding DNA storage system using chaotic mapping to control GC content

MOTIVATION

DNA as a novel storage medium is considered an effective solution to the world's growing demand for information due to its high density and long-lasting reliability. However, early coding schemes ignored the biologically constrained nature of DNA sequences in pursuit of high density, leading to DNA synthesis and sequencing difficulties. This article proposes a novel DNA storage coding scheme. The system encodes half of the binary data using each of the two GC-content complementary encoding rules to obtain a DNA sequence.

RESULTS

After simulating the encoding of representative document and image file formats, a DNA sequence strictly conforming to biological constraints was obtained, reaching a coding potential of 1.66 bit/nt. In the decoding process, a mechanism to prevent error propagation was introduced. The simulation results demonstrate that by adding Reed-Solomon code, 90% of the data can still be recovered after introducing a 2% error, proving that the proposed DNA storage scheme has high robustness and reliability. Availability and implementation: The source code for the codec scheme of this paper is available at https://github.com/Mooreniah/DNA-dual-rule-rotary-encoding-storage-system-DRRC.

How close are we to storing data in DNA?

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.

Reconstruction algorithms for DNA-storage systems

Motivated by DNA storage systems, this work presents the DNA reconstruction problem, in which a length-n string, is passing through the DNA-storage channel, which introduces deletion, insertion and substitution errors. This channel generates multiple noisy copies of the transmitted string which are called traces. A DNA reconstruction algorithm is a mapping which receives t traces as an input and produces an estimation of the original string. The goal in the DNA reconstruction problem is to minimize the edit distance between the original string and the algorithm's estimation. In this work, we present several new algorithms for this problem. Our algorithms look globally on the entire sequence of the traces and use dynamic programming algorithms, which are used for the shortest common supersequence and the longest common subsequence problems, in order to decode the original string. Our algorithms do not require any limitations on the input and the number of traces, and more than that, they perform well even for error probabilities as high as 0.27. The algorithms have been tested on simulated data, on data from previous DNA storage experiments, and on a new synthesized dataset, and are shown to outperform previous algorithms in reconstruction accuracy.

How to make DNA data storage more applicable

The storage of digital data is becoming a worldwide problem. DNA has been recognized as a biological solution due to its ability to store genetic information without alteration over long periods. The first demonstrations of high-capacity long-lasting DNA digital data storage have been shown. However, high storage costs and slow retrieval of the data must be overcome to make DNA data storage more applicable and marketable. Herein, we discuss the issues and recent advances in DNA data storage methods and highlight pathways to make this technology more applicable to real-world digital data storage. We envision that a combination of molecular biology, nanotechnology, novel polymers, electronics, and automation with systematic development will allow DNA data storage sufficient for everyday use.

Digital data storage on DNA tape using CRISPR base editors

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.

Towards Chinese text and DNA shift encoding scheme based on biomass plasmid storage

DNA, as the storage medium in organisms, can address the shortcomings of existing electromagnetic storage media, such as low information density, high maintenance power consumption, and short storage time. Current research on DNA storage mainly focuses on designing corresponding encoders to convert binary data into DNA base data that meets biological constraints. We have created a new Chinese character code table that enables exceptionally high information storage density for storing Chinese characters (compared to traditional UTF-8 encoding). To meet biological constraints, we have devised a DNA shift coding scheme with low algorithmic complexity, which can encode any strand of DNA even has excessively long homopolymer. The designed DNA sequence will be stored in a double-stranded plasmid of 744bp, ensuring high reliability during storage. Additionally, the plasmid's resistance to environmental interference ensuring long-term stable information storage. Moreover, it can be replicated at a lower cost.

FrameD: framework for DNA-based data storage design, verification, and validation

MOTIVATION

DNA-based data storage is a quickly growing field that hopes to harness the massive theoretical information density of DNA molecules to produce a competitive next-generation storage medium suitable for archival data. In recent years, many DNA-based storage system designs have been proposed. Given that no common infrastructure exists for simulating these storage systems, comparing many different designs along with many different error models is increasingly difficult. To address this challenge, we introduce FrameD, a simulation infrastructure for DNA storage systems that leverages the underlying modularity of DNA storage system designs to provide a framework to express different designs while being able to reuse common components.

RESULTS

We demonstrate the utility of FrameD and the need for a common simulation platform using a case study. Our case study compares designs that utilize strand copies differently, some that align strand copies using multiple sequence alignment algorithms and others that do not. We found that the choice to include multiple sequence alignment in the pipeline is dependent on the error rate and the type of errors being injected and is not always beneficial. In addition to supporting a wide range of designs, FrameD provides the user with transparent parallelism to deal with a large number of reads from sequencing and the need for many fault injection iterations. We believe that FrameD fills a void in the tools publicly available to the DNA storage community by providing a modular and extensible framework with support for massive parallelism. As a result, it will help accelerate the design process of future DNA-based storage systems.

AVAILABILITY AND IMPLEMENTATION

The source code for FrameD along with the data generated during the demonstration of FrameD is available in a public Github repository at https://github.com/dna-storage/framed, (https://dx.doi.org/10.5281/zenodo.7757762).

Scaling logical density of DNA storage with enzymatically-ligated composite motifs

DNA is a promising candidate for long-term data storage due to its high density and endurance. The key challenge in DNA storage today is the cost of synthesis. In this work, we propose composite motifs, a framework that uses a mixture of prefabricated motifs as building blocks to reduce synthesis cost by scaling logical density. To write data, we introduce Bridge Oligonucleotide Assembly, an enzymatic ligation technique for synthesizing oligos based on composite motifs. To sequence data, we introduce Direct Oligonucleotide Sequencing, a nanopore-based technique to sequence short oligos, eliminating common preparatory steps like DNA assembly, amplification and end-prep. To decode data, we introduce Motif-Search, a novel consensus caller that provides accurate reconstruction despite synthesis and sequencing errors. Using the proposed methods, we present an end-to-end experiment where we store the text "HelloWorld" at a logical density of 84 bits/cycle (14-42× improvement over state-of-the-art).

DBTRG: De Bruijn Trim rotation graph encoding for reliable DNA storage

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.

Reducing cost in DNA-based data storage by sequence analysis-aided soft information decoding of variable-length reads

MOTIVATION

DNA-based data storage is one of the most attractive research areas for future archival storage. However, it faces the problems of high writing and reading costs for practical use. There have been many efforts to resolve this problem, but existing schemes are not fully suitable for DNA-based data storage, and more cost reduction is needed.

RESULTS

We propose whole encoding and decoding procedures for DNA storage. The encoding procedure consists of a carefully designed single low-density parity-check code as an inter-oligo code, which corrects errors and dropouts efficiently. We apply new clustering and alignment methods that operate on variable-length reads to aid the decoding performance. We use edit distance and quality scores during the sequence analysis-aided decoding procedure, which can discard abnormal reads and utilize high-quality soft information. We store 548.83 KB of an image file in DNA oligos and achieve a writing cost reduction of 7.46% and a significant reading cost reduction of 26.57% and 19.41% compared with the two previous works.

AVAILABILITY AND IMPLEMENTATION

Data and codes for all the algorithms proposed in this study are available at: https://github.com/sjpark0905/DNA-LDPC-codes.

An outlook on the current challenges and opportunities in DNA data storage

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.

DUHI: Dynamically updated hash index clustering method for DNA storage

The exponential growth of global data leads to the problem of insufficient data storage capacity. DNA storage can be an ideal storage method due to its high storage density and long storage time. However, the DNA storage process is subject to unavoidable errors that can lead to increased cluster redundancy during data reading, which in turn affects the accuracy of the data reads. This paper proposes a dynamically updated hash index (DUHI) clustering method for DNA storage, which clusters sequences by constructing a dynamic core index set and using hash lookup. The proposed clustering method is analyzed in terms of overall reliability evaluation and visualization evaluation. The results show that the DUHI clustering method can reduce the redundancy of more than 10% of the sequences within the cluster and increase the reconstruction rate of the sequences to more than 99%. Therefore, our method solves the high redundancy problem after DNA sequence clustering, improves the accuracy of data reading, and promotes the development of DNA storage.

Enabling technology and core theory of synthetic biology

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.

A biological camera that captures and stores images directly into DNA

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.

Towards long double-stranded chains and robust DNA-based data storage using the random code system

DNA has become a popular choice for next-generation storage media due to its high storage density and stability. As the storage medium of life's information, DNA has significant storage capacity and low-cost, low-power replication and transcription capabilities. However, utilizing long double-stranded DNA for storage can introduce unstable factors that make it difficult to meet the constraints of biological systems. To address this challenge, we have designed a highly robust coding scheme called the "random code system," inspired by the idea of fountain codes. The random code system includes the establishment of a random matrix, Gaussian preprocessing, and random equilibrium. Compared to Luby transform codes (LT codes), random code (RC) has better robustness and recovery ability of lost information. In biological experiments, we successfully stored 29,390 bits of data in 25,700 bp chains, achieving a storage density of 1.78 bits per nucleotide. These results demonstrate the potential for using long double-stranded DNA and the random code system for robust DNA-based data storage.

In-vitro validated methods for encoding digital data in deoxyribonucleic acid (DNA)

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.

Study on DNA Storage Encoding Based IAOA under Innovation Constraints

With the informationization of social processes, the amount of related data has greatly increased, making traditional storage media unable to meet the current requirements for data storage. Due to its advantages of a high storage capacity and persistence, deoxyribonucleic acid (DNA) has been considered the most prospective storage media to solve the data storage problem. Synthesis is an important process for DNA storage, and low-quality DNA coding can increase errors during sequencing, which can affect the storage efficiency. To reduce errors caused by the poor stability of DNA sequences during storage, this paper proposes a method that uses the double-matching and error-pairing constraints to improve the quality of the DNA coding set. First, the double-matching and error-pairing constraints are defined to solve problems of sequences with self-complementary reactions in the solution that are prone to mismatch at the 3' end. In addition, two strategies are introduced in the arithmetic optimization algorithm, including a random perturbation of the elementary function and a double adaptive weighting strategy. An improved arithmetic optimization algorithm (IAOA) is proposed to construct DNA coding sets. The experimental results of the IAOA on 13 benchmark functions show a significant improvement in its exploration and development capabilities over the existing algorithms. Moreover, the IAOA is used in the DNA encoding design under both traditional and new constraints. The DNA coding sets are tested to estimate their quality regarding the number of hairpins and melting temperature. The DNA storage coding sets constructed in this study are improved by 77.7% at the lower boundary compared to existing algorithms. The DNA sequences in the storage sets show a reduction of 9.7-84.1% in the melting temperature variance, and the hairpin structure ratio is reduced by 2.1-80%. The results indicate that the stability of the DNA coding sets is improved under the two proposed constraints compared to traditional constraints.

The emerging landscape of microfluidic applications in DNA data storage

DNA has been considered a promising alternative to the current solid-state devices for digital information storage. The past decade has witnessed tremendous progress in the field of DNA data storage contributed by researchers from various disciplines. However, the current development status of DNA storage is still far from practical use, mainly due to its high material cost and time consumption for data reading/writing, as well as the lack of a comprehensive, automated, and integrated system. Microfluidics, being capable of handling and processing micro-scale fluid samples in a massively paralleled and highly integrated manner, has gradually been recognized as a promising candidate for addressing the aforementioned issues. In this review, we provide a discussion on recent efforts of applying microfluidics to advance the development of DNA data storage. Moreover, to showcase the tremendous potential that microfluidics can contribute to this field, we will further highlight the recent advancements of applying microfluidics to the key functional modules within the DNA data storage workflow. Finally, we share our perspectives on future directions for how to continue the infusion of microfluidics with DNA data storage and how to advance toward a truly integrated system and reach real-life applications.

Mobile and Self-Sustained Data Storage in an Extremophile Genomic DNA

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.

Research Progress in Construction and Application of Enzyme-Based DNA Logic Gates

As a research hotspot in the field of information processing, DNA computing exhibits several important underlying characteristics-from parallel computing and low energy consumption to high-performance storage capabilities-thereby enabling its wide application in nanomachines, molecular encryption, biological detection, medical diagnosis, etc. Based on DNA computing, the most rapidly developed field focuses on DNA molecular logic-gates computing. In particular, the recent advances in enzyme-based DNA logic gates has emerged as ideal materials for constructing DNA logic gates. In this review, we explore protein enzymes that can manipulate DNA, especially, nicking enzymes and polymerases with high efficiency and specificity, which are widely used in constructing DNA logic gates, as well as ribozyme that can construct DNA logic gates following various mechanism with distinct biomaterials. Accordingly, the review highlights the characteristics and applications of various types of DNAzyme-based logic gates models, considering their future developments in information, biomedicine, chemistry, and computers.

GCNSA: DNA storage encoding with a graph convolutional network and self-attention

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.

Digital data storage on DNA tape using CRISPR base editors

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.

FMG: An observable DNA storage coding method based on frequency matrix game graphs

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.

Emerging Approaches to DNA Data Storage: Challenges and Prospects

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.

Levy Equilibrium Optimizer algorithm for the DNA storage code set

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%.

Robust data storage in DNA by de Bruijn graph-based de novo strand assembly

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.

Design of DNA Storage Coding with Enhanced Constraints

Traditional storage media have been gradually unable to meet the needs of data storage around the world, and one solution to this problem is DNA storage. However, it is easy to make errors in the subsequent sequencing reading process of DNA storage coding. To reduces error rates, a method to enhance the robustness of the DNA storage coding set is proposed. Firstly, to reduce the likelihood of secondary structure in DNA coding sets, a repeat tandem sequence constraint is proposed. An improved DTW distance constraint is proposed to address the issue that the traditional distance constraint cannot accurately evaluate non-specific hybridization between DNA sequences. Secondly, an algorithm that combines random opposition-based learning and eddy jump strategy with Aquila Optimizer (AO) is proposed in this paper, which is called ROEAO. Finally, the ROEAO algorithm is used to construct the coding sets with traditional constraints and enhanced constraints, respectively. The quality of the two coding sets is evaluated by the test of the number of issuing card structures and the temperature stability of melting; the data show that the coding set constructed with ROEAO under enhanced constraints can obtain a larger lower bound while improving the coding quality.

In vivo processing of digital information molecularly with targeted specificity and robust reliability

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.

Adaptive coding for DNA storage with high storage density and low coverage

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.

Preservation and Encryption in DNA Digital Data Storage

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.

Molecular and experimental tools to design synthetic enhancers

Understanding the grammar of enhancers and how they regulate gene expression is key for both basic research and for the pharma and biotech industries. The design and characterization of synthetic enhancers can expand the known regulatory space. This is achieved by the utilization of DNA Oligo Libraries (OLs), which facilitates screening of as many as millions of synthetic enhancer variants simultaneously. This review includes the latest commercial DNA OL synthesis technology and its capabilities, and a general 'know-how' guide for the design, construction, and analysis of OL-based synthetic enhancer characterization experiments. Specifically, we focus on synthetic-enhancer-based massively parallel reporter assay, Sort-seq methodologies (e.g. flow cytometry, deep sequencing), and a brief description of machine learning-based attempts for OL-analysis and follow-up validation experiments.

Design considerations for advancing data storage with synthetic DNA for long-term archiving

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.

Towards practical and robust DNA-based data archiving using the yin-yang codec system

DNA is a promising data storage medium due to its remarkable durability and space-efficient storage. Early bit-to-base transcoding schemes have primarily pursued information density, at the expense of introducing biocompatibility challenges or decoding failure. Here we propose a robust transcoding algorithm named the yin-yang codec, using two rules to encode two binary bits into one nucleotide, to generate DNA sequences that are highly compatible with synthesis and sequencing technologies. We encoded two representative file formats and stored them in vitro as 200 nt oligo pools and in vivo as a ~54 kbps DNA fragment in yeast cells. Sequencing results show that the yin-yang codec exhibits high robustness and reliability for a wide variety of data types, with an average recovery rate of 99.9% above 104 molecule copies and an achieved recovery rate of 87.53% at ≤102 copies. Additionally, the in vivo storage demonstration achieved an experimentally measured physical density close to the theoretical maximum.

DNA-Based Concatenated Encoding System for High-Reliability and High-Density Data Storage

Information storage based on DNA molecules provides a promising solution with advantages of low-energy consumption, high storage efficiency, and long lifespan. However, there are only four natural nucleotides and DNA storage is thus limited by 2 bits per nucleotide. Here, artificial nucleotides into DNA data storage to achieve higher coding efficiency than 2 bits per nucleotide is introduced. To accommodate the characteristics of DNA synthesis and sequencing, two high-reliability encoding systems suitable for four, six, and eight nucleotides, i.e., the RaptorQ-Arithmetic-LZW-RS (RALR) and RaptorQ-Arithmetic-Base64-RS (RABR) systems, are developed. The two concatenated encoding systems realize the advantages of correcting DNA sequence losses, correcting errors within DNA sequences, reducing homopolymers, and controlling specific nucleotide contents. The average coding efficiencies with error correction and without arithmetic compression by the RALR system using four, six, and eight nucleotides reach 1.27, 1.61, and 1.85 bits per nucleotide, respectively. While the average coding efficiencies by the RABR system are up to 1.50, 2.00, and 2.35 bits per nucleotide, respectively. The coding efficiency, versatility, and tunability of the developed artificial DNA systems might provide significant guidance for high-reliability and high-density data storage.

Fabrication and Decryption of a Microarray of Digital Dithiosuccinimide Oligomers

Digital polymer with precisely arranged binary units provides an important option for information storage. This is especially true if the digital polymers are assembled in a device, as it would be of great benefit to data writing and reading in practice. Herein, inspired by DNA microarray technique, the programmable information storing and reading on a mass spectrometry target plate is proposed. First, an array of 4-bit sequence-coded dithiosuccinimide oligomers was efficiently built through sequential thiol-maleimide Michael couplings with good sequence readability by tandem mass spectrometry (MS/MS). Then, toward engineering microarray for information storage, a programmed robotic arm was specifically designed for precisely loading sequence-coded oligomers onto the target plate, and a decoding software was developed for efficient readout of the data from MS/MS sequencing. Notably, short sequence-coded oligomers chains can be used to write long strings of information, and extra error-correction codes are not required as usual due to the inherent concomitant fragmentation signals. Not only text but also bitimages can be automatically stored and decoded with excellent accuracy. This work provides a promising platform of digital polymers for programmable information storing and reading. This article is protected by copyright. All rights reserved.

Encoding of non-biological information for its long-term storage in DNA

In 2019, at the World Economic Forum, DNA data storage was indicated as one of the breakthroughs expected to radically impact the global socio-economic order. Indeed, dry DNA is a relatively stable substance and an extremely capacious information carrier. One gram of DNA can hold up to 455 exabytes, provided that one nucleotide encodes two bits of information. In this critical review, the main attention is paid to nucleinography, meaning the conversion of digital data into nucleotide sequences. The evolution and diversity of approaches intended for encoding data with nucleotides are demonstrated. The most noticeable examples of storing minor as well as considerable quantities of non-biological information in DNA are given. Some issues of DNA data storage are also reported.

Extended XOR algorithm with biotechnology constraints for Data Security in DNA Storage

Background:

DNA storage is becoming a global research hotspot in recent years and today, most researches are focused on storage density and big data. The security of DNA storage needs to be observed. Some DNA-based security methods were introduced for traditional information security problems. However, few encryption algorithm considered the limitation of biotechnology and applied it for DNA storage. The difference between DNA cryptography and the traditional one is that the former is based on the limitation of biotechnology, which is unrelated to numeracy.

Objective:

An extended XOR algorithm (EXA) was introduced for encryption with constriants of biotechnology, which can solve the problems of synthesis and sequencing partly, such as GC content and homopolymer in DNA storage..

Methods:

The target file was converted by a quaternary DNA storage model to maximize the storage efficiency. The key file could be ‘anything’ converted into DNA sequence by a binary DNA storage model to make the best utilization for the length of the key file.

Results:

The input files were encrypted into DNA storage and decrypted to error-free output files.

Conclusion:

This meant error-free encryption DNA storage is feasible and EXA paves the way for encryption in large-scale DNA storage.

Electrochemical DNA synthesis and sequencing on a single electrode with scalability for integrated data storage

DNA has been considered as a compelling candidate for digital data storage due to advantages such as high coding density, long retention time, and low energy consumption. Despite many works reported, the development of a DNA-based database of full integration, high efficiency, and practical applicability is still challenging. In this work, we report the synthesis and sequencing of DNA on a single electrode with scalability for an integrated DNA-based data storage system. The synthesis of DNA is based on phosphoramidite chemistry and electrochemical deprotection. The sequencing relies on charge redistribution originated from polymerase-catalyzed primer extension, leading to a measurable current spike. By regeneration of the electrode after sequencing, repeated sequencing can be achieved to improve the accuracy. A SlipChip device is developed to simplify the liquid introduction involved in DNA synthesis and sequencing. As the proof-of-concept experiment, text information is stored in the system and then accurately retrieved.

A Hierarchical Error Correction Strategy for Text DNA Storage

DNA storage has been a thriving interdisciplinary research area because of its high density, low maintenance cost, and long durability for information storage. However, the complexity of errors in DNA sequences including substitutions, insertions and deletions hinders its application for massive data storage. Motivated by the divide-and-conquer algorithm, we propose a hierarchical error correction strategy for text DNA storage. The basic idea is to design robust codes for common characters which have one-base error correction ability including insertion and/or deletion. The errors are gradually corrected by the codes in DNA reads, multiple alignment of character lines, and finally word spelling. On one hand, the proposed encoding method provides a systematic way to design storage friendly codes, such as 50% GC content, no more than 2-base homopolymers, and robustness against secondary structures. On the other hand, the proposed error correction method not only corrects single insertion or deletion, but also deals with multiple insertions or deletions. Simulation results demonstrate that the proposed method can correct more than 98% errors when error rate is less than or equal to 0.05. Thus, it is more powerful and adaptable to the complicated DNA storage applications.

High-density information storage and random access scheme using synthetic DNA

The high-storage density, long-life cycle, and low-energy consumption of DNA molecules make it the future of next-generation storage technology. However, DNA storage has the disadvantages of high-synthesis cost and low-random access efficiency. A high-density DNA-coding scheme can effectively reduce the cost of DNA synthesis. This paper first proposes a DNA-mapping method based on codebook and a random access method for DNA information based on encoded content. The mapping method satisfies the two biological constraints of homopolymer length and GC content. The random access method can efficiently and selectively read specific files in the DNA pool. To increase storage density, convolutional neural networks are combined with mapping methods to generate base sequences. In the experiments, our method was compared with the results of existing DNA information storage methods, which showed that the proposed scheme has better information storage density.