DNA Storage Research Articles

High Net Information Density DNA Data Storage by the MOPE Encoding Algorithm.

DNA has recently been recognized as an attractive storage medium due to its high reliability, capacity, and durability. However, encoding algorithms that simply map binary data to DNA sequences have the disadvantages of low net information density and high synthesis cost. Therefore, this paper proposes an efficient, feasible, and highly robust encoding algorithm called MOPE (Modified Barnacles Mating Optimizer and Payload Encoding). The Modified Barnacles Mating Optimizer (MBMO) algorithm is used to construct the non-payload coding set, and the Payload Encoding (PE) algorithm is used to encode the payload. The results show that the lower bound of the non-payload coding set constructed by the MBMO algorithm is 3%-18% higher than the optimal result of previous work, and theoretical analysis shows that the designed PE algorithm has a net information density of 1.90 bits/nt, which is close to the ideal information capacity of 2 bits per nucleotide. The proposed MOPE encoding algorithm with high net information density and satisfying constraints can not only effectively reduce the cost of DNA synthesis and sequencing but also reduce the occurrence of errors during DNA storage.

An Information-Theoretic Approach to Nanopore Sequencing for DNA Storage

An Information-Theoretic Approach to Nanopore Sequencing for DNA Storage

Reconstruction of Sequences Distorted by Two Insertions

Reconstruction codes are generalizations of error-correcting codes that can correct errors by a given number of noisy reads. The study of such codes was initiated by Levenshtein in 2001 and developed recently due to applications in modern storage devices such as racetrack memories and DNA storage. The central problem on this topic is to design codes with redundancy as small as possible for a given number <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> of noisy reads. In this paper, the minimum redundancy of such codes for binary channels with exactly two insertions is determined asymptotically for all values of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> ≥ 5. Previously, such codes were studied only for channels with single edit errors or two-deletion errors.

Magnetic Bead Spherical Nucleic Acid Microstructure for Reliable DNA Preservation and Repeated DNA Reading.

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, and sequencing technologies. Despite progress in these subareas, the most challenging hurdle in the deployment of DNA storage remains the reliability of preservation and the repeatability of reading. Herein, we report the construction of a magnetic bead spherical nucleic acid (MB-SNA) composite microstructure and its use as a cost-effective platform for reliable DNA preservation and repeated reading. MB-SNA has an inner core of silica@γ-Fe2O3@silica microbeads and an outer spherical shell of double-stranded DNA (dsDNA) with a density as high as 34 pmol/cm2. For MB-SNA, each strand of dsDNA stored a piece of data, and the high-density packing of dsDNA achieved high-capacity storage. MB-SNA was advantageous in terms of reliable preservation over free DNA. By accelerated aging tests, the data of MB-SNA is demonstrated to be readable after 0.23 million years of preservation at -18 °C and 50% relative humidity. Moreover, MB-SNA facilitated repeated reading by facile PCR-magnetic separation. After 10 cycles of PCR access, the retention rate of dsDNA for MB-SNA is demonstrated to be as high as 93%, and the accuracy of sequencing is more than 98%. In addition, MB-SNA makes cost-effective DNA storage feasible. By serial dilution, the physical limit for MB-SNA to achieve accurate reading is probed to be as low as two microstructures.

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.

An Algorithm-optimized Scheme for In situ Synthesis of DNA Microarrays.

The cost of synthetic DNA has limited applications in frontier science and technology fields such as synthetic biology, DNA storage, and DNA chips. The objective of this study is to find an algorithm-optimized scheme for the in situ synthesis of DNA microarrays, which can reduce the cost of DNA synthesis. Here, based on the characteristics of in situ chemical synthesis of DNA microarrays, an optimization algorithm was proposed. Through data grading, the sequences with the same base at as many different features as possible were synthesized in parallel to reduce synthetic cycles. The simulation results of 10 and 100 randomly selected sequences showed that when level=2, the reduction ratio in the number of synthetic cycles was the largest, 40% and 32.5%, respectively. Subsequently, the algorithm-optimized scheme was applied to the electrochemical synthesis of 12,000 sequences required for DNA storage. The results showed that compared to the 508 cycles required by the conventional synthesis scheme, the algorithmoptimized scheme only required 342 cycles, which reduced by 32.7%. In addition, the reduced 166 cycles reduced the total synthesis time by approximately 11 hours. The algorithm-optimized synthesis scheme can not only reduce the synthesis time of DNA microarrays and improve synthesis efficiency, but more importantly, it can also reduce the cost of DNA synthesis by nearly 1/3. In addition, it is compatible with various in situ synthesis methods of DNA microarrays, including soft-lithography, photolithography, a photoresist layer, electrochemistry and photoelectrochemistry. Therefore, it has very important application value.

Sequence Reconstruction Under Single-Burst-Insertion/Deletion/Edit Channel

Motivated by applications in modern storage devices such as DNA storage and racetrack memories, we study the sequence reconstruction problem which involves two important issues. One is determining the maximum intersection size between two error balls. The other is designing reconstruction codes in which each transmitted sequence can be reconstructed from a given number of noisy reads with redundancy as small as possible. In this paper, we focus on channels that introduce single-burst-insertion/ deletion error. We fully determine the maximum intersection size between two burst-insertion/deletion balls for both fixed-length and variable-length models. Then we characterize a pair of sequences when their burst-insertion/deletion balls have intersection of a certain size. Using these characterizations, we design reconstruction codes for all values <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> of the number of noisy reads and analyze their lower bounds. In addition, we extend our results to the burst-edit channel.

BIC Codes: Bit Insertion-Based Constrained Codes With Error Correction for DNA Storage

In this paper, we propose a new coding algorithm for DNA storage over both error-free and error channels. For the error-free case, we propose a constrained code called bit insertion-based constrained (BIC) code. BIC codes convert a binary data sequence to multiple oligo sequences satisfying the maximum homopolymer run (i.e., run-length (RL)) constraint by inserting dummy bits. We show that the BIC codes nearly achieves the capacity in terms of information density while the simple structure of the BIC codes allows linear-time encoding and fast parallel decoding. Also, by combining a balancing technique with the BIC codes, we obtain the constrained coding algorithm to satisfy the GC-content constraint as well as the RL constraint. Next, for DNA storage channel with errors, we integrate the proposed constrained coding algorithm with a rate-compatible low-density parity-check (LDPC) code to correct errors and erasures. Specifically, we incorporate LDPC codes adopted in the 5G new radio standard because they have powerful error-correction capability and appealing features for the integration. Simulation results show that the proposed integrated coding algorithm outperforms existing coding algorithms in terms of information density and error correctability.

Integrating FPGA Acceleration in the DNAssim Framework for Faster DNA-Based Data Storage Simulations

DNA-based data storage emerged in this decade as a promising solution for long data durability, low power consumption, and high density. However, such technology has not yet reached a good maturity level, requiring many investigations to improve the information encoding and decoding processes. Simulations can be key to overcoming the time and the cost burdens of the many experiments imposed by thorough design space explorations. In response to this, we have developed a DNA storage simulator (DNAssim) that allows simulating the different steps in the DNA storage pipeline using a proprietary software infrastructure written in Python/C language. Among the many operations performed by the tool, the edit distance calculation used during clustering operations has been identified as the most computationally intensive task in software, thus calling for hardware acceleration. In this work, we demonstrate the integration in the DNAssim framework of a dedicated FPGA hardware accelerator based on the Xilinx VC707 evaluation kit to boost edit distance calculations by up to 11 times with respect to a pure software approach. This materializes in a clustering simulation latency reduction of up to 5.5 times and paves the way for future scale-out DNA storage simulation platforms.

A Robust and Efficient DNA Storage Architecture Based on Modulation Encoding and Decoding.

Synthetic DNA has been widely considered an attractive medium for digital data storage. However, the random insertion-deletion-substitution (IDS) errors in the sequenced reads still remain a critical challenge to reliable data recovery. Motivated by the modulation technique in the communication field, we propose a new DNA storage architecture to solve this problem. The main idea is that all binary data are modulated into DNA sequences with the same AT/GC patterns, which facilitate the detection of indels in noisy reads. The modulation signal could not only satisfy the encoding constraints but also serve as prior information to detect the potential positions of errors. Experiments on simulation and real data sets demonstrate that modulation encoding provides a simple way to comply with biological constraints for sequence encoding (i.e., balanced GC content and avoiding homopolymers). Furthermore, modulation decoding is highly efficient and extremely robust, which can correct up to ∼40% of errors. In addition, it is robust to imperfect clustering reconstruction, which is very common in practice. Although our method has a relatively low logical density of 1.0 bits/nt, its high robustness may provide a wide space for developing low-cost synthetic technologies. We believe this new architecture may boost the early coming of large-scale DNA storage applications in the future.

Magnetic DNA random access memory with nanopore readouts and exponentially-scaled combinatorial addressing

The storage of data in DNA typically involves encoding and synthesizing data into short oligonucleotides, followed by reading with a sequencing instrument. Major challenges include the molecular consumption of synthesized DNA, basecalling errors, and limitations with scaling up read operations for individual data elements. Addressing these challenges, we describe a DNA storage system called MDRAM (Magnetic DNA-based Random Access Memory) that enables repetitive and efficient readouts of targeted files with nanopore-based sequencing. By conjugating synthesized DNA to magnetic agarose beads, we enabled repeated data readouts while preserving the original DNA analyte and maintaining data readout quality. MDRAM utilizes an efficient convolutional coding scheme that leverages soft information in raw nanopore sequencing signals to achieve information reading costs comparable to Illumina sequencing despite higher error rates. Finally, we demonstrate a proof-of-concept DNA-based proto-filesystem that enables an exponentially-scalable data address space using only small numbers of targeting primers for assembly and readout.

DNA storage in thermoresponsive microcapsules for repeated random multiplexed data access.

DNA has emerged as an attractive medium for archival data storage due to its durability and high information density. Scalable parallel random access to information is a desirable property of any storage system. For DNA-based storage systems, however, this still needs to be robustly established. Here we report on a thermoconfined polymerase chain reaction, which enables multiplexed, repeated random access to compartmentalized DNA files. The strategy is based on localizing biotin-functionalized oligonucleotides inside thermoresponsive, semipermeable microcapsules. At low temperatures, microcapsules are permeable to enzymes, primers and amplified products, whereas at high temperatures, membrane collapse prevents molecular crosstalk during amplification. Our data show that the platform outperforms non-compartmentalized DNA storage compared with repeated random access and reduces amplification bias tenfold during multiplex polymerase chain reaction. Using fluorescent sorting, we also demonstrate sample pooling and data retrieval by microcapsule barcoding. Therefore, the thermoresponsive microcapsule technology offers a scalable, sequence-agnostic approach for repeated random access to archival DNA files.

Content-based filter queries on DNA data storage systems

Recent developments in DNA data storage systems have revealed the great potential to store large amounts of data at a very high density with extremely long persistence and low cost. However, despite recent contributions to robust data encoding, current DNA storage systems offer limited support for random access on DNA storage devices due to restrictive biochemical constraints. Moreover, state-of-the-art approaches do not support content-based filter queries on DNA storage. This paper introduces the first encoding for DNA that enables content-based searches on structured data like relational database tables. We provide the details of the methods for coding and decoding millions of directly accessible data objects on DNA. We evaluate the derived codes on real data sets and verify their robustness.

DNA Data Storage: The Fusion of Digital and Biological Information

With the development of Internet technology, human information data grows by a huge amount. Traditional data storage media are no longer suitable for large amounts of data storage due to their inherent shortcomings, such as high power consumption, large physical size, and short storage life. DNA information storage, on the other hand, can overcome these shortcomings to a certain extent. This paper introduces the process and mechanism of DNA storage, such as the DNA synthesis method, DNA coding, DNA preservation and sequencing, the history of DNA storage, its defects, and shortcomings. This article introduces the principles and mechanisms of DNA storage, including DNA synthesis method, data storage, and DNA preservation, as well as the history of DNA storage and its shortcomings and prospects for improvement, using the comparison of traditional storage methods and DNA storage methods as an import cut.

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.

Optimizing mycobacteria molecular diagnostics: No decontamination! Human DNA depletion? Greener storage at 4 °C!

Tuberculosis (TB) is an infectious disease caused by the group of bacterial pathogens Mycobacterium tuberculosis complex (MTBC) and is one of the leading causes of death worldwide. Timely diagnosis and treatment of drug-resistant TB is a key pillar of WHO's strategy to combat global TB. The time required to carry out drug susceptibility testing (DST) for MTBC via the classic culture method is in the range of weeks and such delays have a detrimental effect on treatment outcomes. Given that molecular testing is in the range of hours to 1 or 2 days its value in treating drug resistant TB cannot be overstated. When developing such tests, one wants to optimize each step so that tests are successful even when confronted with samples that have a low MTBC load or contain large amounts of host DNA. This could improve the performance of the popular rapid molecular tests, especially for samples with mycobacterial loads close to the limits of detection. Where optimizations could have a more significant impact is for tests based on targeted next generation sequencing (tNGS) which typically require higher quantities of DNA. This would be significant as tNGS can provide more comprehensive drug resistance profiles than the relatively limited resistance information provided by rapid tests. In this work we endeavor to optimize pre-treatment and extraction steps for molecular testing. We begin by choosing the best DNA extraction device by comparing the amount of DNA extracted by five commonly used devices from identical samples. Following this, the effect that decontamination and human DNA depletion have on extraction efficiency is explored. The best results were achieved (i.e., the lowest Ct values) when neither decontamination nor human DNA depletion were used. As expected, in all tested scenarios the addition of decontamination to our workflow substantially reduced the yield of DNA extracted. This illustrates that the standard TB laboratory practice of applying decontamination, although being vital for culture-based testing, can negatively impact the performance of molecular testing. As a complement to the above experiments, we also considered the best Mycobacterium tuberculosis DNA storage method to optimize molecular testing carried out in the near- to medium-term. Comparing Ct values following three-month storage at 4 °C and at -20 °C and showed little difference between the two. In summary, for molecular diagnostics aimed at mycobacteria this work highlights the importance of choosing the right DNA extraction device, indicates that decontamination causes significant loss of mycobacterial DNA, and shows that samples preserved for further molecular testing can be stored at 4 °C, just as well at -20 °C. Under our experimental settings, human DNA depletion gave no significant improvement in Ct values for the detection of MTBC.

Towards the improved monitoring of bacterial infections by the isolation of DNA from human serum using ionic-liquid-based aqueous biphasic systems

Early infection diagnosis is crucial to decrease morbidity and mortality rates. However, complex biological samples, like human blood or serum, contain high abundance proteins and metabolites that reduce the sensitivity of methods used to identify and quantify nucleic acids in bacterial infections diagnosis. To address this issue, we investigated aqueous biphasic systems (ABS) composed of polypropylene glycol 400 and cholinium-based ionic liquids (ILs) at different pH values for the pre-treatment of human serum, aiming the separation of DNA from human serum albumin (HSA) to reduce the interference on the DNA quantification by real-time PCR (qPCR). Remarkable extraction efficiencies of DNA to the IL-rich phase were obtained with all investigated systems, ranging between 90 and 100% in a single-step, with no significant losses of DNA observed (yield at the IL-rich phase > 90%). At low pH values HSA precipitates, whereas at neutral pH no HSA precipitation is observed. This trend suggests that IL-based ABS can be tuned to selectively isolate DNA from HSA by adjusting the pH. The most effective ABS identified is composed of cholinium glycolate at pH 5, allowing to completely precipitate HSA at the ABS interface and leading to an IL-rich phase enriched in DNA with high purity (>98%) that can be quantified by qPCR. Finally, it is shown that the IL-rich phase is able to maintain the DNA’s structural integrity at room temperature, for up to six months, implying that the IL-rich phase of the selected ABS could also be a suitable DNA storage medium. In summary, designed IL-based ABS can be applied as a pretreatment strategy of human serum, allowing to isolate bacterial DNA and opening new perspectives in the monitoring of bacterial infections.

On the Size of Balls and Anticodes of Small Diameter Under the Fixed-Length Levenshtein Metric

The rapid development of DNA storage has brought the deletion and insertion channel to the front line of research. When the number of deletions is equal to the number of insertions, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Fixed Length Levenshtein</i> (FLL) metric is the right measure for the distance between two words of the same length. Similar to any other metric, the size of a ball is one of the most fundamental parameters. In this work, we consider the minimum, maximum, and average size of a ball with radius one, in the FLL metric. The related minimum and the maximum size of a maximal anticode with diameter one are also considered.

Towards Migration-Free "Just-in-Case" Data Archival for Future Cloud Data Lakes Using Synthetic DNA

Given the growing adoption of AI, cloud data lakes are facing the need to support cost-effective "just-in-case" data archival over long time periods to meet regulatory compliance requirements. Unfortunately, current media technologies suffer from fundamental issues that will soon, if not already, make cost-effective data archival infeasible. In this paper, we present a vision for redesigning the archival tier of cloud data lakes based on a novel, obsolescence-free storage medium-synthetic DNA. In doing so, we make two contributions: (i) we highlight the challenges in using DNA for data archival and list several open research problems, (ii) we outline OligoArchive-DSM (OA-DSM)-an end-to-end DNA storage pipeline that we are developing to demonstrate the feasibility of our vision.

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.