Low cost DNA data storage using photolithographic synthesis and advanced information reconstruction and error correction

Recent progress in DNA data storage based on high-throughput DNA synthesis

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.

Phase transition-driven encapsulation of biomolecules using liquid metal with on-demand release for biomedical applications

Robust encapsulation and controllable release of biomolecules have wide biomedical applications ranging from biosensing, drug delivery to information storage. However, conventional biomolecule encapsulation strategies have limitations in complicated operations, optical instability, and difficulty in decapsulation. Here, we report a simple, robust, and solvent-free biomolecule encapsulation strategy based on gallium liquid metal featuring low-temperature phase transition, self-healing, high hermetic sealing, and intrinsic resistance to optical damage. We sandwiched the biomolecules with the solid gallium films followed by low-temperature welding of the films for direct sealing. The gallium can not only protect DNA and enzymes from various physical and chemical damages but also allow the on-demand release of biomolecules by applying vibration to break the liquid gallium. We demonstrated that a DNA-coded image file can be recovered with up to 99.9% sequence retention after an accelerated aging test. We also showed the practical applications of the controllable release of bioreagents in a one-pot RPA-CRISPR/Cas12a reaction for SARS-COV-2 screening with a low detection limit of 10 copies within 40 min. This work may facilitate the development of robust and stimuli-responsive biomolecule capsules by using low-melting metals for biotechnology.

A Deniable Encryption Method for Modulation-Based DNA Storage

Recent advancements in synthesis and sequencing techniques have made deoxyribonucleic acid (DNA) a promising alternative for next-generation digital storage. As it approaches practical application, ensuring the security of DNA-stored information has become a critical problem. Deniable encryption allows the decryption of different information from the same ciphertext, ensuring that the "plausible" fake information can be provided when users are coerced to reveal the real information. In this paper, we propose a deniable encryption method that uniquely leverages DNA noise channels. Specifically, true and fake messages are encrypted by two similar modulation carriers and subsequently obfuscated by inherent errors. Experiment results demonstrate that our method not only can conceal true information among fake ones indistinguishably, but also allow both the coercive adversary and the legitimate receiver to decrypt the intended information accurately. Further security analysis validates the resistance of our method against various typical attacks. Compared with conventional DNA cryptography methods based on complex biological operations, our method offers superior practicality and reliability, positioning it as an ideal solution for data encryption in future large-scale DNA storage applications.

Accelerated, high-quality photolithographic synthesis of RNA microarrays in situ

Nucleic acid photolithography is the only microarray fabrication process that has demonstrated chemical versatility accommodating any type of nucleic acid. The current approach to RNA microarray synthesis requires long coupling and photolysis times and suffers from unavoidable degradation postsynthesis. In this study, we developed a series of RNA phosphoramidites with improved chemical and photochemical protection of the 2'- and 5'-OH functions. In so doing, we reduced the coupling time by more than half and the photolysis time by a factor of 4. Sequence libraries that would otherwise take over 6 hours to synthesize can now be prepared in half the time. Degradation is substantially lowered, and concomitantly, hybridization signals can reach over seven times those of the previous state of the art. Under those conditions, high-density RNA microarrays and RNA libraries can now be synthesized at greatly accelerated rates. We also synthesized fluorogenic RNA Mango aptamers on microarrays and investigated the effect of sequence mutations on their fluorogenic properties.

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.

Design of DNA Storage Coding Scheme With LDPC Codes and Interleaving

In this paper, we propose a new coding scheme for DNA storage using low-density parity-check (LDPC) codes and interleaving techniques. While conventional coding schemes generally employ error correcting codes in both inter and intra-oligo directions, we show that inter-oligo LDPC codes, optimized by differential evolution, are sufficient in ensuring the reliability of DNA storage due to the powerful soft decoding of LDPC codes. In addition, we apply interleaving techniques for handling non-uniform error characteristics of DNA storage to enhance the decoding performance. Consequently, the proposed coding scheme reduces the required number of oligo reads for perfect recovery by 26.25% ~ 38.5% compared to existing state-of-the-art coding schemes. Moreover, we develop an analytical DNA channel model in terms of non-uniform binary symmetric channels. This mathematical model allows us to demonstrate the superiority of the proposed coding scheme while isolating the experimental variation, as well as confirm the independent effects of LDPC codes and interleaving techniques.

Fast multiple sequence alignment via multi-armed bandits

SUMMARY

Multiple sequence alignment is an important problem in computational biology with applications that include phylogeny and the detection of remote homology between protein sequences. UPP is a popular software package that constructs accurate multiple sequence alignments for large datasets based on ensembles of hidden Markov models (HMMs). A computational bottleneck for this method is a sequence-to-HMM assignment step, which relies on the precise computation of probability scores on the HMMs. In this work, we show that we can speed up this assignment step significantly by replacing these HMM probability scores with alternative scores that can be efficiently estimated. Our proposed approach utilizes a multi-armed bandit algorithm to adaptively and efficiently compute estimates of these scores. This allows us to achieve similar alignment accuracy as UPP with a significant reduction in computation time, particularly for datasets with long sequences.

AVAILABILITY AND IMPLEMENTATION

The code used to produce the results in this paper is available on GitHub at: https://github.com/ilanshom/adaptiveMSA.

Multi-file dynamic compression method based on classification algorithm in DNA storage

The exponential growth in data volume has necessitated the adoption of alternative storage solutions, and DNA storage stands out as the most promising solution. However, the exorbitant costs associated with synthesis and sequencing impeded its development. Pre-compressing the data is recognized as one of the most effective approaches for reducing storage costs. However, different compression methods yield varying compression ratios for the same file, and compressing a large number of files with a single method may not achieve the maximum compression ratio. This study proposes a multi-file dynamic compression method based on machine learning classification algorithms that selects the appropriate compression method for each file to minimize the amount of data stored into DNA as much as possible. Firstly, four different compression methods are applied to the collected files. Subsequently, the optimal compression method is selected as a label, as well as the file type and size are used as features, which are put into seven machine learning classification algorithms for training. The results demonstrate that k-nearest neighbor outperforms other machine learning algorithms on the validation set and test set most of the time, achieving an accuracy rate of over 85% and showing less volatility. Additionally, the compression rate of 30.85% can be achieved according to k-nearest neighbor model, more than 4.5% compared to the traditional single compression method, resulting in significant cost savings for DNA storage in the range of $0.48 to 3 billion/TB. In comparison to the traditional compression method, the multi-file dynamic compression method demonstrates a more significant compression effect when compressing multiple files. Therefore, it can considerably decrease the cost of DNA storage and facilitate the widespread implementation of DNA storage technology.

An Effective DNA-Based File Storage System for Practical Archiving and Retrieval of Medical MRI Data

DNA-based data storage is a new technology in computational and synthetic biology, that offers a solution for long-term, high-density data archiving. Given the critical importance of medical data in advancing human health, there is a growing interest in developing an effective medical data storage system based on DNA. Data integrity, accuracy, reliability, and efficient retrieval are all significant concerns. Therefore, this study proposes an Effective DNA Storage (EDS) approach for archiving medical MRI data. The EDS approach incorporates three key components (i) a novel fraction strategy to address the critical issue of rotating encoding, which often leads to data loss due to single base error propagation; (ii) a novel rule-based quaternary transcoding method that satisfies bio-constraints and ensure reliable mapping; and (iii) an indexing technique designed to simplify random search and access. The effectiveness of this approach is validated through computer simulations and biological experiments, confirming its practicality. The EDS approach outperforms existing methods, providing superior control over bio-constraints and reducing computational time. The results and code provided in this study open new avenues for practical DNA storage of medical MRI data, offering promising prospects for the future of medical data archiving and retrieval.

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.

GradHC: highly reliable gradual hash-based clustering for DNA storage systems

MOTIVATION

As data storage challenges grow and existing technologies approach their limits, synthetic DNA emerges as a promising storage solution due to its remarkable density and durability advantages. While cost remains a concern, emerging sequencing and synthetic technologies aim to mitigate it, yet introduce challenges such as errors in the storage and retrieval process. One crucial task in a DNA storage system is clustering numerous DNA reads into groups that represent the original input strands.

RESULTS

In this paper, we review different methods for evaluating clustering algorithms and introduce a novel clustering algorithm for DNA storage systems, named Gradual Hash-based clustering (GradHC). The primary strength of GradHC lies in its capability to cluster with excellent accuracy various types of designs, including varying strand lengths, cluster sizes (including extremely small clusters), and different error ranges. Benchmark analysis demonstrates that GradHC is significantly more stable and robust than other clustering algorithms previously proposed for DNA storage, while also producing highly reliable clustering results.

AVAILABILITY AND IMPLEMENTATION

https://github.com/bensdvir/GradHC.

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.

A Novel DNA Synthesis Platform Design with High-Throughput Paralleled Addressability and High-Density Static Droplet Confinement

Using DNA as the next-generation medium for data storage offers unparalleled advantages in terms of data density, storage duration, and power consumption as compared to existing data storage technologies. To meet the high-speed data writing requirements in DNA data storage, this paper proposes a novel design for an ultra-high-density and high-throughput DNA synthesis platform. The presented design mainly leverages two functional modules: a dynamic random-access memory (DRAM)-like integrated circuit (IC) responsible for electrode addressing and voltage supply, and the static droplet array (SDA)-based microfluidic structure to eliminate any reaction species diffusion concern in electrochemical DNA synthesis. Through theoretical analysis and simulation studies, we validate the effective addressing of 10 million electrodes and stable, adjustable voltage supply by the integrated circuit. We also demonstrate a reaction unit size down to 3.16 × 3.16 μm2, equivalent to 10 million/cm2, that can rapidly and stably generate static droplets at each site, effectively constraining proton diffusion. Finally, we conducted a synthesis cycle experiment by incorporating fluorescent beacons on a microfabricated electrode array to examine the feasibility of our design.

A novel approach to encode melodies in DNA

DNA data storage has gained more attention last decades. DNA molecules can be used for encoding of non-biological information and as promising carriers due to greater data capacity, higher duration of the storage, and better technical failures stability. Here we propose a new method for encoding of notes and music in DNA. The encoding technique takes into account the duration and tonality of each note, enabling to encode all seven octaves by assigning a nucleotide sequence to each key. A certain set of short sequences is suggested to define the duration of note sound. The proposed method allows to encode more complicated melodies compared to the approach based on Huffman algorithm.

An open-source, 3D printed inkjet DNA synthesizer

Synthetic oligonucleotides have become a fundamental tool in a wide range of biological fields, including synthetic biology, biosensing, and DNA storage. Reliable access to equipment for synthesizing high-density oligonucleotides in the laboratory ensures research security and the freedom of research expansion. In this study, we introduced the Open-Source Inkjet DNA Synthesizer (OpenIDS), an open-source inkjet-based microarray synthesizer that offers ease of construction, rapid deployment, and flexible scalability. Utilizing 3D printing, Arduino, and Raspberry Pi, this newly designed synthesizer achieved robust stability with an industrial inkjet printhead. OpenIDS maintains low production costs and is therefore suitable for self-fabrication and optimization in academic laboratories. Moreover, even non-experts can create and control the synthesizer with a high degree of freedom for structural modifications. Users can easily add printheads or alter the design of the microarray substrate according to their research needs. To validate its performance, we synthesized oligonucleotides on 144 spots on a 15 × 25-mm silicon wafer filled with controlled pore glass. The synthesized oligonucleotides were analyzed using urea polyacrylamide gel electrophoresis.

Nonaqueous Oxidation in DNA Microarray Synthesis Improves the Oligonucleotide Quality and Preserves Surface Integrity on Gold and Indium Tin Oxide Substrates

Nucleic acids attached to electrically conductive surfaces are very frequently used platforms for sensing and analyte detection as well as for imaging. Synthesizing DNA on these uncommon substrates and preserving the conductive layer is challenging as this coating tends to be damaged by the repeated use of iodine and water, which is the standard oxidizing medium following phosphoramidite coupling. Here, we thoroughly investigate the use of camphorsulfonyl oxaziridine (CSO), a nonaqueous alternative to I2/H2O, for the synthesis of DNA microarrays in situ. We find that CSO performs equally well in producing high hybridization signals on glass microscope slides, and CSO also protects the conductive layer on gold and indium tin oxide (ITO)-coated slides. DNA synthesis on conductive substrates with CSO oxidation yields microarrays of quality approaching that of conventional glass with intact physicochemical properties.

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.

Limit and screen sequences with high degree of secondary structures in DNA storage by deep learning method

BACKGROUND

In single-stranded DNAs/RNAs, secondary structures are very common especially in long sequences. It has been recognized that the high degree of secondary structures in DNA sequences could interfere with the correct writing and reading of information in DNA storage. However, how to circumvent its side-effect is seldom studied.

METHOD

As the degree of secondary structures of DNA sequences is closely related to the magnitude of the free energy released in the complicated folding process, we first investigate the free-energy distribution at different encoding lengths based on randomly generated DNA sequences. Then, we construct a bidirectional long short-term (BiLSTM)-attention deep learning model to predict the free energy of sequences.

RESULTS

Our simulation results indicate that the free energy of DNA sequences at a specific length follows a right skewed distribution and the mean increases as the length increases. Given a tolerable free energy threshold of 20 kcal/mol, we could control the ratio of serious secondary structures in the encoding sequences to within 1% of the significant level through selecting a feasible encoding length of 100 nt. Compared with traditional deep learning models, the proposed model could achieve a better prediction performance both in the mean relative error (MRE) and the coefficient of determination (R2). It achieved MRE = 0.109 and R2 = 0.918 respectively in the simulation experiment. The combination of the BiLSTM and attention module can handle the long-term dependencies and capture the feature of base pairing. Further, the prediction has a linear time complexity which is suitable for detecting sequences with severe secondary structures in future large-scale applications. Finally, 70 of 94 predicted free energy can be screened out on a real dataset. It demonstrates that the proposed model could screen out some highly suspicious sequences which are prone to produce more errors and low sequencing copies.

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).

A digital twin for DNA data storage based on comprehensive quantification of errors and biases

Archiving data in synthetic DNA offers unprecedented storage density and longevity. Handling and storage introduce errors and biases into DNA-based storage systems, necessitating the use of Error Correction Coding (ECC) which comes at the cost of added redundancy. However, insufficient data on these errors and biases, as well as a lack of modeling tools, limit data-driven ECC development and experimental design. In this study, we present a comprehensive characterisation of the error sources and biases present in the most common DNA data storage workflows, including commercial DNA synthesis, PCR, decay by accelerated aging, and sequencing-by-synthesis. Using the data from 40 sequencing experiments, we build a digital twin of the DNA data storage process, capable of simulating state-of-the-art workflows and reproducing their experimental results. We showcase the digital twin's ability to replace experiments and rationalize the design of redundancy in two case studies, highlighting opportunities for tangible cost savings and data-driven ECC development.

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.

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.

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.

Assembly of Reusable DNA Blocks for Data Storage Using the Principle of Movable Type Printing

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.

Encoding, Decoding, and Rendering Information in DNA Nanoswitch Libraries

DNA-based construction allows the creation of molecular devices that are useful in information storage and processing. Here, we combine the programmability of DNA nanoswitches and stimuli-responsive conformational changes to demonstrate information encoding and graphical readout using gel electrophoresis. We encoded information as 5-bit binary codes for alphanumeric characters using a combination of DNA and RNA inputs that can be decoded using molecular stimuli such as a ribonuclease. We also show that a similar strategy can be used for graphical visual readout of alphabets on an agarose gel, information that is encoded by nucleic acids and decoded by a ribonuclease. Our method of information encoding and processing could be combined with DNA actuation for molecular computation and diagnostics that require a nonarbitrary visual readout.

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.

Study of the error correction capability of multiple sequence alignment algorithm (MAFFT) in DNA storage

Synchronization (insertions-deletions) errors are still a major challenge for reliable information retrieval in DNA storage. Unlike traditional error correction codes (ECC) that add redundancy in the stored information, multiple sequence alignment (MSA) solves this problem by searching the conserved subsequences. In this paper, we conduct a comprehensive simulation study on the error correction capability of a typical MSA algorithm, MAFFT. Our results reveal that its capability exhibits a phase transition when there are around 20% errors. Below this critical value, increasing sequencing depth can eventually allow it to approach complete recovery. Otherwise, its performance plateaus at some poor levels. Given a reasonable sequencing depth (≤ 70), MSA could achieve complete recovery in the low error regime, and effectively correct 90% of the errors in the medium error regime. In addition, MSA is robust to imperfect clustering. It could also be combined with other means such as ECC, repeated markers, or any other code constraints. Furthermore, by selecting an appropriate sequencing depth, this strategy could achieve an optimal trade-off between cost and reading speed. MSA could be a competitive alternative for future DNA storage.

DNA storage-from natural biology to synthetic biology

Natural DNA storage allows cellular differentiation, evolution, the growth of our children and controls all our ecosystems. Here, we discuss the fundamental aspects of DNA storage and recent advances in this field, with special emphasis on natural processes and solutions that can be exploited. We point out new ways of efficient DNA and nucleotide storage that are inspired by nature. Within a few years DNA-based information storage may become an attractive and natural complementation to current electronic data storage systems. We discuss rapid and directed access (e.g. DNA elements such as promotors, enhancers), regulatory signals and modulation (e.g. lncRNA) as well as integrated high-density storage and processing modules (e.g. chromosomal territories). There is pragmatic DNA storage for use in biotechnology and human genetics. We examine DNA storage as an approach for synthetic biology (e.g. light-controlled nucleotide processing enzymes). The natural polymers of DNA and RNA offer much for direct storage operations (read-in, read-out, access control). The inbuilt parallelism (many molecules at many places working at the same time) is important for fast processing of information. Using biology concepts from chromosomal storage, nucleic acid processing as well as polymer material sciences such as electronical effects in enzymes, graphene, nanocellulose up to DNA macramé , DNA wires and DNA-based aptamer field effect transistors will open up new applications gradually replacing classical information storage methods in ever more areas over time (decades).

An image cryptography method by highly error-prone DNA storage channel

Introduction: Rapid development in synthetic technologies has boosted DNA as a potential medium for large-scale data storage. Meanwhile, how to implement data security in the DNA storage system is still an unsolved problem. Methods: In this article, we propose an image encryption method based on the modulation-based storage architecture. The key idea is to take advantage of the unpredictable modulation signals to encrypt images in highly error-prone DNA storage channels. Results and Discussion: Numerical results have demonstrated that our image encryption method is feasible and effective with excellent security against various attacks (statistical, differential, noise, and data loss). When compared with other methods such as the hybridization reactions of DNA molecules, the proposed method is more reliable and feasible for large-scale applications.

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.

Information decay and enzymatic information recovery for DNA data storage

Synthetic DNA has been proposed as a storage medium for digital information due to its high theoretical storage density and anticipated long storage horizons. However, under all ambient storage conditions, DNA undergoes a slow chemical decay process resulting in nicked (broken) DNA strands, and the information stored in these strands is no longer readable. In this work we design an enzymatic repair procedure, which is applicable to the DNA pool prior to readout and can partially reverse the damage. Through a chemical understanding of the decay process, an overhang at the 3' end of the damaged site is identified as obstructive to repair via the base excision-repair (BER) mechanism. The obstruction can be removed via the enzyme apurinic/apyrimidinic endonuclease I (APE1), thereby enabling repair of hydrolytically damaged DNA via Bst polymerase and Taq ligase. Simulations of damage and repair reveal the benefit of the enzymatic repair step for DNA data storage, especially when data is stored in DNA at high storage densities (=low physical redundancy) and for long time durations.

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.

Clover: tree structure-based efficient DNA clustering for DNA-based data storage

Deoxyribonucleic acid (DNA)-based data storage is a promising new storage technology which has the advantage of high storage capacity and long storage time compared with traditional storage media. However, the synthesis and sequencing process of DNA can randomly generate many types of errors, which makes it more difficult to cluster DNA sequences to recover DNA information. Currently, the available DNA clustering algorithms are targeted at DNA sequences in the biological domain, which not only cannot adapt to the characteristics of sequences in DNA storage, but also tend to be unacceptably time-consuming for billions of DNA sequences in DNA storage. In this paper, we propose an efficient DNA clustering method termed Clover for DNA storage with linear computational complexity and low memory. Clover avoids the computation of the Levenshtein distance by using a tree structure for interval-specific retrieval. We argue through theoretical proofs that Clover has standard linear computational complexity, low space complexity, etc. Experiments show that our method can cluster 10 million DNA sequences into 50 000 classes in 10 s and meet an accuracy rate of over 99%. Furthermore, we have successfully completed an unprecedented clustering of 10 billion DNA data on a single home computer and the time consumption still satisfies the linear relationship. Clover is freely available at https://github.com/Guanjinqu/Clover.

Combinatorial PCR Method for Efficient, Selective Oligo Retrieval from Complex Oligo Pools

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.

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.

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.

Synthetic DNA applications in information technology

Synthetic DNA is a growing alternative to electronic-based technologies in fields such as data storage, product tagging, or signal processing. Its value lies in its characteristic attributes, namely Watson-Crick base pairing, array synthesis, sequencing, toehold displacement and polymerase chain reaction (PCR) capabilities. In this review, we provide an overview of the most prevalent applications of synthetic DNA that could shape the future of information technology. We emphasize the reasons why the biomolecule can be a valuable alternative for conventional electronic-based media, and give insights on where the DNA-analog technology stands with respect to its electronic counterparts.

Scaling DNA data storage with nanoscale electrode wells

Synthetic DNA is an attractive medium for long-term data storage because of its density, ease of copying, sustainability, and longevity. Recent advances have focused on the development of new encoding algorithms, automation, preservation, and sequencing technologies. Despite progress in these areas, the most challenging hurdle in deployment of DNA data storage remains the write throughput, which limits data storage capacity. We have developed the first nanoscale DNA storage writer, which we expect to scale DNA write density to 25 × 10⁶ sequences per square centimeter, three orders of magnitude improvement over existing DNA synthesis arrays. We show confinement of DNA synthesis to an area under 1 square micrometer, parallelized over millions of nanoelectrode wells and then successfully write and decode a message in DNA. DNA synthesis on this scale will enable write throughputs to reach megabytes per second and is a key enabler to a practical DNA data storage system.

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.

Chemical and photochemical error rates in light-directed synthesis of complex DNA libraries

Nucleic acid microarrays are the only tools that can supply very large oligonucleotide libraries, cornerstones of the nascent fields of de novo gene assembly and DNA data storage. Although the chemical synthesis of oligonucleotides is highly developed and robust, it is not error free, requiring the design of methods that can correct or compensate for errors, or select for high-fidelity oligomers. However, outside the realm of array manufacturers, little is known about the sources of errors and their extent. In this study, we look at the error rate of DNA libraries synthesized by photolithography and dissect the proportion of deletion, insertion and substitution errors. We find that the deletion rate is governed by the photolysis yield. We identify the most important substitution error and correlate it to phosphoramidite coupling. Besides synthetic failures originating from the coupling cycle, we uncover the role of imperfections and limitations related to optics, highlight the importance of absorbing UV light to avoid internal reflections and chart the dependence of error rate on both position on the array and position within individual oligonucleotides. Being able to precisely quantify all types of errors will allow for optimal choice of fabrication parameters and array design.

Enzymatic Synthesis of Chimeric DNA Oligonucleotides by in Vitro Transcription with dTTP, dCTP, dATP, and 2'-Fluoro Modified dGTP

Efficient ways to produce single-stranded DNA are of great interest for diverse applications in molecular biology and nanotechnology. In the present study, we selected T7 RNA polymerase mutants with reduced substrate specificity to employ an in vitro transcription reaction for the synthesis of chimeric DNA oligonucleotides, either individually or in pools. We performed in vitro evolution based on fluorescence-activated droplet sorting and identified mutations V783M, V783L, V689Q, and G555L as novel variants leading to relaxed substrate discrimination. Transcribed chimeric oligonucleotides were tested in PCR, and the quality of amplification products as well as fidelity of oligonucleotide synthesis were assessed by NGS. We concluded that enzymatically produced chimeric DNA transcripts contain significantly fewer deletions and insertions compared to chemically synthesized counterparts and can successfully serve as PCR primers, making the evolved enzymes superior for simple and cheap one-pot synthesis of multiple chimeric DNA oligonucleotides in parallel using a plethora of premixed templates.

Sequence Preference and Initiator Promiscuity for De Novo DNA Synthesis by Terminal Deoxynucleotidyl Transferase

The untemplated activity of terminal deoxynucleotidyl transferase (TdT) represents its most appealing feature. Its use is well established in applications aiming for extension of a DNA initiator strand, but a more recent focus points to its potential in enzymatic de novo synthesis of DNA. Whereas its low substrate specificity for nucleoside triphosphates has been studied extensively, here we interrogate how the activity of TdT is modulated by the nature of the initiating strands, in particular their length, chemistry, and nucleotide composition. Investigation of full permutational libraries of mono- to pentamers of d-DNA, l-DNA, and 2′O-methyl-RNA of differing directionality immobilized to glass surfaces, and generated via photolithographic in situ synthesis, shows that the efficiency of extension strongly depends on the nucleobase sequence. We also show TdT being catalytically active on a non-nucleosidic substrate, hexaethylene glycol. These results offer new perspectives on constraints and strategies for de novo synthesis of DNA using TdT regarding the requirements for initiation of enzymatic generation of DNA.

Uncertainties in synthetic DNA-based data storage

Deoxyribonucleic acid (DNA) has evolved to be a naturally selected, robust biomacromolecule for gene information storage, and biological evolution and various diseases can find their origin in uncertainties in DNA-related processes (e.g. replication and expression). Recently, synthetic DNA has emerged as a compelling molecular media for digital data storage, and it is superior to the conventional electronic memory devices in theoretical retention time, power consumption, storage density, and so forth. However, uncertainties in the in vitro DNA synthesis and sequencing, along with its conjugation chemistry and preservation conditions can lead to severe errors and data loss, which limit its practical application. To maintain data integrity, complicated error correction algorithms and substantial data redundancy are usually required, which can significantly limit the efficiency and scale-up of the technology. Herein, we summarize the general procedures of the state-of-the-art DNA-based digital data storage methods (e.g. write, read, and preservation), highlighting the uncertainties involved in each step as well as potential approaches to correct them. We also discuss challenges yet to overcome and research trends in the promising field of DNA-based data storage.

Cooperative Sequence Clustering and Decoding for DNA Storage System with Fountain Codes

MOTIVATION

In DNA storage systems, there are tradeoffs between writing and reading costs. Increasing the code rate of error-correcting codes may save writing cost, but it will need more sequence reads for data retrieval. There is potentially a way to improve sequencing and decoding processes in such a way that the reading cost induced by this tradeoff is reduced without increasing the writing cost. In past researches, clustering, alignment, and decoding processes were considered as separate stages but we believe that using the information from all these processes together may improve decoding performance. Actual experiments of DNA synthesis and sequencing should be performed because simulations cannot be relied on to cover all error possibilities in practical circumstances.

RESULTS

For DNA storage systems using fountain code and Reed-Solomon (RS) code, we introduce several techniques to improve the decoding performance. We designed the decoding process focusing on the cooperation of key components: Hamming-distance based clustering, discarding of abnormal sequence reads, RS error correction as well as detection, and quality score-based ordering of sequences. We synthesized 513.6KB data into DNA oligo pools and sequenced this data successfully with Illumina MiSeq instrument. Compared to Erlich's research, the proposed decoding method additionally incorporates sequence reads with minor errors which had been discarded before, and thuswas able to make use of 10.6-11.9% more sequence reads from the same sequencing environment, this resulted in 6.5-8.9% reduction in the reading cost. Channel characteristics including sequence coverage and read-length distributions are provided as well.

AVAILABILITY

The raw data files and the source codes of our experiments are available at: https://github.com/jhjeong0702/dna-storage.

Novel Modalities in DNA Data Storage

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.