Nucleic acid memory

Nucleic acid-responsive smart systems for controlled cargo delivery

Stimulus-responsive delivery systems allow controlled, highly regulated, and efficient delivery of various cargos while minimizing side effects. Owing to the unique properties of nucleic acids, including the ability to adopt complex structures by base pairing, their easy synthesis, high specificity, shape memory, and configurability, they have been employed in autonomous molecular motors, logic circuits, reconfigurable nanoplatforms, and catalytic amplifiers. Moreover, the development of nucleic acid (NA)-responsive intelligent delivery vehicles is a rapidly growing field. These vehicles have attracted much attention in recent years due to their programmable, controllable, and reversible properties. In this work, we review several types of NA-responsive controlled delivery vehicles based on locks and keys, including DNA/RNA-responsive, aptamer-responsive, and CRISPR-responsive, and summarize their advantages and limitations.

A monodispersed metal-complexing peptide-based polymer for mass cytometry enabling spectral applications

We report the synthesis of a novel class of metal-complexing peptide-based polymers, which we name HyperMAPs (Hyper-loaded MetAl-complexed Polymers). The controlled solid-phase synthesis of HyperMAPs' scaffold peptide provides our polymer with a well-defined molecular structure that allows for an accurate on-design assembly of a wide variety of metals. The peptide-scaffold features a handle for direct conjugation to antibodies or any other biomolecules by means of a thiol-maleimide-click or aldehyde-oxime reaction, a fluorogenic moiety for biomolecule conjugation tracking, and a well-defined number of functional groups for direct incorporation of metal-chelator complexes. Since metal-chelator complexes are prepared in a separate reaction prior to incorporation to the peptide scaffold, polymers can be designed to contain specific ratios of metal isotopes, providing each polymer with a unique CyTOF spectral fingerprint. We demonstrate the complexing of 21 different metals using two different chelators and provide evidence of the application of HyperMAPs on a 13 parameter CyTOF panel and compare its performance to monoisotopic metal-conjugated antibodies.

Portable SERS biosensor based on aptamer-assisted catalytic hairpin assembly signal amplification for ultrasensitive detection of Staphylococcus aureus

Bacteria infections pose a serious threat to public health, and it is urgent to develop facile and accurate detection methods. To meet the important need, a potable and high-sensitive surface enhanced Raman scattering (SERS) biosensor based on aptamer recognition and catalytic hairpin assembly (CHA) signal amplification was proposed for point-of-care detection of Staphylococcus aureus (S. aureus). The SERS biosensor contains three parts: recognition probes, SERS sensing chip, and SERS tags. The feasibility of the strategy was verified by gel electrophoresis, and the one-step test route was optimized. The bacteria SERS biosensor has a good linear relationship ranging from 10 to 107 CFU mL-1 with high sensitivity low to 5 CFU mL-1, and shows excellent specificity, uniformity, and repeatability on S. aureus identification and enumeration, which can distinguish S. aureus from other bacteria. The SERS biosensor shows a good recovery rate (95.73 %-109.65 %) for testing S. aureus spiked in milk, and has good practicability for detecting S. aureus infected mouse wound, which provides a facile and reliable approach for detection of trace bacteria in the real samples.

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.

Label-free colorimetric detection platform based on catalytic hairpin self-assembly and G-quadruplex/hemin DNAzyme for comprehensive biomarker profiling

The expression level of human apurinic/apyrimidinic endonuclease 1 (APE1) is closely associated with the onset of various diseases, establishing it as a crucial clinical biomarker and a target in anti-cancer efforts. This study accomplished colorimetric and visual detection of APE1 by harnessing its endonuclease activity through catalytic hairpin self-assembly (CHA) and G-quadruplex/hemin DNAzyme. Optimization of the freedom degrees of the G-rich sequence significantly improved the detection performance of the strategy by influencing DNAzyme formation. Additionally, we replaced the signal reporting system with a molecular beacon to develop a fluorescence detection strategy, which served as an extension of the signal amplification system for validation and signal readout. The fluorescent probe method achieved a detection limit of 3.37 × 10-4 U/mL, while the colorimetric method yielded a detection limit of 6.5 × 10-3 U/mL, with a linear range spanning from 0.01 to 0.25 U/mL. Subsequently, the colorimetric approach effectively assessed APE1 activity in biological samples and facilitated the screening of APE1 activity inhibitors. Furthermore, this CHA/G-quadruplex/hemin DNAzyme strategy was adapted for the colorimetric detection of adenosine, showcasing its broad applicability across various biomarkers. The developed colorimetric analytical strategy represents a pivotal biosensing platform for diagnosing and treating diseases.

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.

Chemical and linguistic considerations for encoding Chinese characters: an embodiment using chain-end degradable sequence-defined oligourethanes created by consecutive solid phase click chemistry

Sequence-defined polymers (SDPs) are currently being investigated for use as information storage media. As the number of monomers in the SDPs increases, with a corresponding increase in mathematical base, the use of tandem-MS for de novo sequencing becomes more challenging. In contrast, chain-end degradation routines are truly de novo, potentially allowing very large mathematical bases for encoding. While alphabetic scripts have a few dozen symbols, logographic scripts, such as Chinese, can have several thousand symbols. Using a new in situ consecutive click reaction approach on an oligourethane backbone for writing, and a previously reported chain-end degradation routine for reading, we encoded/decoded a confucius proverb written in Chinese characters using two encoding schemes: Unicode and Zhèng Mă. Unicode is an internationally standardized arbitrary string of hexadecimal (base-16) symbols which efficiently encodes uniquely identifiable symbols but requires complete fidelity of transmission, or context-based inferential strategies to be interpreted. The Zhèng Mă approach encodes with a base-26 system using the visual characteristics and internal composition of Chinese characters themselves, which leads to greater ambiguity of encoded strings, but more robust retrievability of information from partial or corrupted encodings. The application of information-encoded oligourethanes to two different encoding systems allowed us to establish their flexibility and versatility for data storage. We found the oligourethanes immensely adaptable to both encoding schemes for Chinese characters, and we highlight the expected tradeoff between the efficiency and uniqueness of Unicode encoding on the one hand, and the fidelity to a scripts' particular visual characteristics on the other.

Coding, Decoding and Retrieving a Message Using DNA: An Experience from a Brazilian Center Research on DNA Data Storage

DNA data storage based on synthetic oligonucleotides is a major attraction due to the possibility of storage over long periods. Nowadays, the quantity of data generated has been growing exponentially, and the storage capacity needs to keep pace with the growth caused by new technologies and globalization. Since DNA can hold a large amount of information with a high density and remains stable for hundreds of years, this technology offers a solution for current long-term data centers by reducing energy consumption and physical storage space. Currently, research institutes, technology companies, and universities are making significant efforts to meet the growing need for data storage. DNA data storage is a promising field, especially with the advancement of sequencing techniques and equipment, which now make it possible to read genomes (i.e., to retrieve the information) and process this data easily. To overcome the challenges associated with developing new technologies for DNA data storage, a message encoding and decoding exercise was conducted at a Brazilian research center. The exercise performed consisted of synthesizing oligonucleotides by the phosphoramidite route. An encoded message, using a coding scheme that adheres to DNA sequence constraints, was synthesized. After synthesis, the oligonucleotide was sequenced and decoded, and the information was fully recovered.

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.

DNA as a universal chemical substrate for computing and data storage

DNA computing and DNA data storage are emerging fields that are unlocking new possibilities in information technology and diagnostics. These approaches use DNA molecules as a computing substrate or a storage medium, offering nanoscale compactness and operation in unconventional media (including aqueous solutions, water-in-oil microemulsions and self-assembled membranized compartments) for applications beyond traditional silicon-based computing systems. To build a functional DNA computer that can process and store molecular information necessitates the continued development of strategies for computing and data storage, as well as bridging the gap between these fields. In this Review, we explore how DNA can be leveraged in the context of DNA computing with a focus on neural networks and compartmentalized DNA circuits. We also discuss emerging approaches to the storage of data in DNA and associated topics such as the writing, reading, retrieval and post-synthesis editing of DNA-encoded data. Finally, we provide insights into how DNA computing can be integrated with DNA data storage and explore the use of DNA for near-memory computing for future information technology and health analysis applications.

Improving error-correcting capability in DNA digital storage via soft-decision decoding

Error-correcting codes (ECCs) employed in the state-of-the-art DNA digital storage (DDS) systems suffer from a trade-off between error-correcting capability and the proportion of redundancy. To address this issue, in this study, we introduce soft-decision decoding approach into DDS by proposing a DNA-specific error prediction model and a series of novel strategies. We demonstrate the effectiveness of our approach through a proof-of-concept DDS system based on Reed-Solomon (RS) code, named as Derrick. Derrick shows significant improvement in error-correcting capability without involving additional redundancy in both in vitro and in silico experiments, using various sequencing technologies such as Illumina, PacBio and Oxford Nanopore Technology (ONT). Notably, in vitro experiments using ONT sequencing at a depth of 7× reveal that Derrick, compared with the traditional hard-decision decoding strategy, doubles the error-correcting capability of RS code, decreases the proportion of matrices with decoding-failure by 229-fold, and amplifies the potential maximum storage volume by impressive 32 388-fold. Also, Derrick surpasses 'state-of-the-art' DDS systems by comprehensively considering the information density and the minimum sequencing depth required for complete information recovery. Crucially, the soft-decision decoding strategy and key steps of Derrick are generalizable to other ECCs' decoding algorithms.

Highly Accurate Sequence- and Position-Independent Error Profiling of DNA Synthesis and Sequencing

A comprehensive error analysis of DNA-stored data during processing, such as DNA synthesis and sequencing, is crucial for reliable DNA data storage. Both synthesis and sequencing errors depend on the sequence and the transition of bases of nucleotides; ignoring either one of the error sources leads to technical challenges in minimizing the error rate. Here, we present a methodology and toolkit that utilizes an oligonucleotide library generated from a 10-base-shifted sequence array, which is individually labeled with unique molecular identifiers, to delineate and profile DNA synthesis and sequencing errors simultaneously. This methodology enables position- and sequence-independent error profiling of both DNA synthesis and sequencing. Using this toolkit, we report base transitional errors in both synthesis and sequencing in general DNA data storage as well as degenerate-base-augmented DNA data storage. The methodology and data presented will contribute to the development of DNA sequence designs with minimal error.

Rapid Information Retrieval from DNA Storage with Microfluidic Very Large-Scale Integration Platform

Due to its high information density, DNA is very attractive as a data storage system. However, a major obstacle is the high cost and long turnaround time for retrieving DNA data with next-generation sequencing. Herein, the use of a microfluidic very large-scale integration (mVLSI) platform is described to perform highly parallel and rapid readout of data stored in DNA. Additionally, it is demonstrated that multi-state data encoded in DNA can be deciphered with on-chip melt-curve analysis, thereby further increasing the data content that can be analyzed. The pairing of mVLSI network architecture with exquisitely specific DNA recognition gives rise to a scalable platform for rapid DNA data reading.

Generation of DNA oligomers with similar chemical kinetics via in-silico optimization

Networks of interacting DNA oligomers are useful for applications such as biomarker detection, targeted drug delivery, information storage, and photonic information processing. However, differences in the chemical kinetics of hybridization reactions, referred to as kinetic dispersion, can be problematic for some applications. Here, it is found that limiting unnecessary stretches of Watson-Crick base pairing, referred to as unnecessary duplexes, can yield exceptionally low kinetic dispersions. Hybridization kinetics can be affected by unnecessary intra-oligomer duplexes containing only 2 base-pairs, and such duplexes explain up to 94% of previously reported kinetic dispersion. As a general design rule, it is recommended that unnecessary intra-oligomer duplexes larger than 2 base-pairs and unnecessary inter-oligomer duplexes larger than 7 base-pairs be avoided. Unnecessary duplexes typically scale exponentially with network size, and nearly all networks contain unnecessary duplexes substantial enough to affect hybridization kinetics. A new method for generating networks which utilizes in-silico optimization to mitigate unnecessary duplexes is proposed and demonstrated to reduce in-vitro kinetic dispersions as much as 96%. The limitations of the new design rule and generation method are evaluated in-silico by creating new oligomers for several designs, including three previously programmed reactions and one previously engineered structure.

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.

RBS: A Rotational Coding Based on Blocking Strategy for DNA Storage

The data volume of global information has grown exponentially in recent years, but the development of silicon-based memory has entered a bottleneck period. Deoxyribonucleic acid (DNA) storage is drawing attention owing to its advantages of high storage density, long storage time, and easy maintenance. However, the base utilization and information density of existing DNA storage methods are insufficient. Therefore, this study proposes a rotational coding based on blocking strategy (RBS) for encoding digital information such as text and images in DNA data storage. This strategy satisfies multiple constraints and produces low error rates in synthesis and sequencing. To illustrate the superiority of the proposed strategy, it was compared and analyzed with existing strategies in terms of entropy value change, free energy size, and Hamming distance. The experimental results show that the proposed strategy has higher information storage density and better coding quality in DNA storage, so it will improve the efficiency, practicality, and stability of DNA storage.

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.

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.

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.

DNA Data Storage

The demand for data storage is growing at an unprecedented rate, and current methods are not sufficient to accommodate such rapid growth due to their cost, space requirements, and energy consumption. Therefore, there is a need for a new, long-lasting data storage medium with high capacity, high data density, and high durability against extreme conditions. DNA is one of the most promising next-generation data carriers, with a storage density of 10¹⁹ bits of data per cubic centimeter, and its three-dimensional structure makes it about eight orders of magnitude denser than other storage media. DNA amplification during PCR or replication during cell proliferation enables the quick and inexpensive copying of vast amounts of data. In addition, DNA can possibly endure millions of years if stored in optimal conditions and dehydrated, making it useful for data storage. Numerous space experiments on microorganisms have also proven their extraordinary durability in extreme conditions, which suggests that DNA could be a durable storage medium for data. Despite some remaining challenges, such as the need to refine methods for the fast and error-free synthesis of oligonucleotides, DNA is a promising candidate for future data storage.

Toward highly effective loading of DNA in hydrogels for high-density and long-term information storage

Digital information, when converted into a DNA sequence, provides dense, stable, energy-efficient, and sustainable data storage. The most stable method for encapsulating DNA has been in an inorganic matrix of silica, iron oxide, or both, but are limited by low DNA uptake and complex recovery techniques. This study investigated a rationally designed thermally responsive functionally graded (TRFG) hydrogel as a simple and cost-effective method for storing DNA. The TRFG hydrogel shows high DNA uptake, long-term protection, and reusability due to nondestructive DNA extraction. The high loading capacity was achieved by directly absorbing DNA from the solution, which is then retained because of its interaction with a hyperbranched cationic polymer loaded into a negatively charged hydrogel matrix used as a support and because of its thermoresponsive nature, which allows DNA concentration within the hydrogel through multiple swelling/deswelling cycles. We were able to achieve a high DNA data density of 7.0 × 10⁹ gigabytes per gram using a hydrogel-based system.

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.

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.

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.

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.

Digital synthetic polymers for information storage

Digital synthetic polymers with uniform chain lengths and defined monomer sequences have recently become intriguing alternatives to traditional silicon-based information devices or natural biomacromolecules for data storage. The structural diversity of information-containing macromolecules endows the digital synthetic polymers with higher stability and storage density but less occupied space. Through subtly designing each unit of coded structure, the information can be readily encoded into digital synthetic polymers in a more economical scheme and more decodable, opening up new avenues for molecular digital data storage with high-level security. This tutorial review summarizes recent advances in salient features of digital synthetic polymers for data storage, including encoding, decoding, editing, erasing, encrypting, and repairing. The current challenges and outlook are finally discussed to offer potential solution guidance and new perspectives for the creation of next-generation digital synthetic polymers and broaden the scope of their applicability.

DNAsmart: Multiple attribute ranking tool for DNA data storage systems

In an ever-growing need for data storage capacity, the Deoxyribonucleic Acid (DNA) molecule gains traction as a new storage medium with a larger capacity, higher density, and a longer lifespan over conventional storage media. To effectively use DNA for data storage, it is important to understand the different methods of encoding information in DNA and compare their effectiveness. This requires evaluating which decoded DNA sequences carry the most encoded information based on various attributes. However, navigating the field of coding theory requires years of experience and domain expertise. For instance, domain experts rely on various mathematical functions and attributes to score and evaluate their encodings. To enable such analytical tasks, we provide an interactive and visual analytical framework for multi-attribute ranking in DNA storage systems. Our framework follows a three-step view with user-settable parameters. It enables users to find the optimal en-/de-coding approaches by setting different weights and combining multiple attributes. We assess the validity of our work through a task-specific user study on domain experts by relying on three tasks. Results indicate that all participants completed their tasks successfully under two minutes, then rated the framework for design choices, perceived usefulness, and intuitiveness. In addition, two real-world use cases are shared and analyzed as direct applications of the proposed tool. DNAsmart enables the ranking of decoded sequences based on multiple attributes. In sum, this work unveils the evaluation of en-/de-coding approaches accessible and tractable through visualization and interactivity to solve comparison and ranking tasks.

Giving Gold Wings: Ultrabright and Fragmentation Free Mass Spectrometry Reporters for Barcoding, Bioconjugation Monitoring, and Data Storage

The widespread application of laser desorption/ionization mass spectrometry (LDI-MS) highlights the need for a bright and multiplexable labeling platform. While ligand-capped Au nanoparticles (AuNPs) have emerged as a promising LDI-MS contrast agent, the predominant thiol ligands suffer from low ion yields and extensive fragmentation. In this work, we develop a N-heterocyclic carbene (NHC) ligand platform that enhances AuNP LDI-MS performance. NHC scaffolds are tuned to generate barcoded AuNPs which, when benchmarked against thiol-AuNPs, are bright mass tags and form unfragmented ions in high yield. To illustrate the transformative potential of NHC ligands, the mass tags were employed in three orthogonal applications: monitoring a bioconjugation reaction, performing multiplexed imaging, and storing and reading encoded information. These results demonstrate that NHC-nanoparticle systems are an ideal platform for LDI-MS and greatly broaden the scope of nanoparticle contrast agents.

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.

Unraveling the impact of nano-scaling on silicon field-effect transistors for the detection of single-molecules

Electrolyte-gated silicon field-effect transistors (FETs) capable of detecting single molecules could enable high-throughput molecular sensing chips to advance, for example, genomics or proteomics. For solid-gated silicon FETs it is well-known that nano-scaled devices become sensitive to single elementary charges near the silicon-oxide interface. However, in electrolyte-gated FETs, electrolyte screening strongly reduces sensitivity to charges near the gate oxide. The question arises whether nano-scaling electrolyte-gated FETs can entail a sufficiently large signal-to-noise ratio (SNR) for the detection of single molecules. We enhanced a technology computer-aided design tool with electrolyte screening models to calculate the impact of the FET geometry on the single-molecule signal and FET noise. Our continuum FET model shows that a sufficiently large single-molecule SNR is only obtained when nano-scaling all FET channel dimensions. Moreover, we show that the expected scaling trend of the single-molecule SNR breaks down and no longer results in improvements for geometries approaching the decananometer size. This is the characteristic size of the FET channel region modulated by a typical molecule. For gate lengths below 50 nm, the overlap of the modulated region with the highly conductive junctions leads to saturation of the SNR. For cross-sections below 10-30 nm, SNR degrades due to the overlap of the modulated region with the convex FET corners where a larger local gate capacitance reduces charge sensitivity. In our study, assuming a commercial solid-state FET noise amplitude, we find that a suspended nanowire FET architecture with 35 nm length and 5 × 10 nm² cross-section results in the highest SNR of about 10 for a 15-base DNA oligo in a 15 mM electrolyte. In contrast with typical silicon nanowire FET sensors which possess micron-scale gate lengths, we find it to be key that all channel dimensions are scaled down to the decananometer range.

Reading Information Stored in Synthetic Macromolecules

The storage of information in synthetic (macro)molecules provides an attractive alternative for current archival storage media, and the advancements made within this area have prompted the investigation of such molecules for numerous other applications (e.g., anti-counterfeiting tags, steganography). While different strategies have been described for storing information at the molecular level, this Perspective aims to provide a critical overview of the most prominent approaches that can be utilized for retrieving the encoded information. The major part will focus on the sequence determination of synthetic macromolecules, wherein information is stored by the precise arrangement of constituting monomers, with an emphasis on chemically aided strategies, (tandem) mass spectrometry, and nanopore sensing. In addition, recent progress in utilizing (mixtures of) small molecules for information storage will be discussed. Finally, the closing remarks aim to highlight which strategy we believe is the most suitable for a series of specific applications, and will also touch upon the future research avenues that can be pursued for reading (macro)molecular information.

Engineered Spore-Forming Bacillus as a Microbial Vessel for Long-Term DNA Data Storage

DNA data storage technology may supersede conventional chip or magnetic data storage medium, providing long-term stability, high density, and sustainable storage. Due to its error-correcting capability, DNA data stored in living organisms exhibits high fidelity in information replication. Here we report the development of a Bacillus chassis integrated with an inducible artificially assembled bacterial chromosome to facilitate random data access. We generated three sets of data in the form of DNA sequences using a rudimentary coding system accessible by the regulatory promoter. Sporulated Bacillus harboring the genes were used for long-term storage, where viability assays of spores were subjected to harsh environmental stresses to evaluate the data storage stability. The data accuracy remained above 99% after high temperature and oxidative stress treatment, whereas UV irradiation treatment provided above 96% accuracy. The developed Bacillus chassis and artificial chromosome facilitate the long-term storage of larger datum volume by using other DNA digital encoding and decoding programs.

Czy plastik może rozpocząć nową erę w archiwizacji danych?

With the rapid development of information technology, many aspects of our lives are undergoing a digital transformation. An increasing number of users are going online every year, and constantly improving artificial intelligence is gaining popularity, which leads to the growing production of information. Nowadays, information is usually stored in data centres, which will be forced to increase their space with the constant flow of new bits of information. Together with the increase in their space, energy consumption and associated maintenance costs are escalating. In 2021, global data centre power consumption was 220–320 TWh, which is about 0.9–1.3% of global power consumption. Continuous power supply for database operations is responsible for about 1% of total carbon dioxide emissions. Furthermore, it has already been reported that with the exponentially growing amount of data, in about 20 years, the amount of silicon for microprocessors will no longer be sufficient to store all the information. Therefore, scientists are looking for alternatives to the currently used data storage solutions and are developing new technologies using chemical molecules. Recently, even plastic has been explored as a data carrier. In this work, we present examples of new technologies for data storage in polymers. We have discussed polymers as data carriers in comparison with currently used solutions and deliberated whether plastic can become a future material for information archiving.

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.

An enzymatic repair system is described which repairs nicked DNA in DNA libraries, and simulations of damage and repair suggests this enzymatic repair step is beneficial for DNA data storage.

Nondestructive Sequencing of Enantiopure Oligoesters by Nuclear Magnetic Resonance Spectroscopy

Sequence-defined synthetic oligomers and polymers are promising molecular media for permanently storing digital information. However, the information decoding process relies on degradative sequencing methods such as mass spectrometry, which consumes the information-storing polymers upon decoding. Here, we demonstrate the nondestructive decoding of sequence-defined oligomers of enantiopure α-hydroxy acids, oligo(l-mandelic-co-d-phenyl lactic acid)s (oMPs), and oligo(l-lactic-co-glycolic acid)s (oLGs) by ¹³C nuclear magnetic resonance spectroscopy. We were able to nondestructively decode a bitmap image (192 bits) encoded using a library of 12 equimolar mixtures of an 8-bit-storing oMP and oLG, synthesized through semiautomated flow chemistry in less than 1% of the reaction time required for the repetition of conventional batch reactions. Our results highlight the potential of bundles of sequence-defined oligomers as efficient media for encoding and decoding large-scale information based on the automation of their synthesis and nondestructive sequencing processes.

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.

DNA data storage is a rapidly developing technology with great potential due to its high density, long-term durability, and low maintenance cost. Here the authors present a strand assembly algorithm (DBGPS) using de Bruijn graph and greedy path search.

Nanopore Detection Assisted DNA Information Processing

The deoxyribonucleotide (DNA) molecule is a stable carrier for large amounts of genetic information and provides an ideal storage medium for next-generation information processing technologies. Technologies that process DNA information, representing a cross-disciplinary integration of biology and computer techniques, have become attractive substitutes for technologies that process electronic information alone. The detailed applications of DNA technologies can be divided into three components: storage, computing, and self-assembly. The quality of DNA information processing relies on the accuracy of DNA reading. Nanopore detection allows researchers to accurately sequence nucleotides and is thus widely used to read DNA. In this paper, we introduce the principles and development history of nanopore detection and conduct a systematic review of recent developments and specific applications in DNA information processing involving nanopore detection and nanopore-based storage. We also discuss the potential of artificial intelligence in nanopore detection and DNA information processing. This work not only provides new avenues for future nanopore detection development, but also offers a foundation for the construction of more advanced DNA information processing technologies.

Molecular Encryption and Steganography Using Mixtures of Simultaneously Sequenced, Sequence-Defined Oligourethanes

Molecular encoding in abiotic sequence-defined polymers (SDPs) has recently emerged as a versatile platform for information and data storage. However, the storage capacity of these sequence-defined polymers remains underwhelming compared to that of the information storing biopolymer DNA. In an effort to increase their information storage capacity, herein we describe the synthesis and simultaneous sequencing of eight sequence-defined 10-mer oligourethanes. Importantly, we demonstrate the use of different isotope labels, such as halogen tags, as a tool to deconvolute the complex sequence information found within a heterogeneous mixture of at least 96 unique molecules, with as little as four micromoles of total material. In doing so, relatively high-capacity data storage was achieved: 256 bits in this example, the most information stored in a single sample of abiotic SDPs without the use of long strands. Within the sequence information, a 256-bit cipher key was stored and retrieved. The key was used to encrypt and decrypt a plain text document containing The Wonderful Wizard of Oz. To validate this platform as a medium of molecular steganography and cryptography, the cipher key was hidden in the ink of a personal letter, mailed to a third party, extracted, sequenced, and deciphered successfully in the first try, thereby revealing the encrypted document.

Molecular data storage with zero synthetic effort and simple read-out

Compound mixtures represent an alternative, additional approach to DNA and synthetic sequence-defined macromolecules in the field of non-conventional molecular data storage, which may be useful depending on the target application. Here, we report a fast and efficient method for information storage in molecular mixtures by the direct use of commercially available chemicals and thus, zero synthetic steps need to be performed. As a proof of principle, a binary coding language is used for encoding words in ASCII or black and white pixels of a bitmap. This way, we stored a 25 × 25-pixel QR code (625 bits) and a picture of the same size. Decoding of the written information is achieved via spectroscopic (¹H NMR) or chromatographic (gas chromatography) analysis. In addition, for a faster and automated read-out of the data, we developed a decoding software, which also orders the data sets according to an internal “ordering” standard. Molecular keys or anticounterfeiting are possible areas of application for information-containing compound mixtures.

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.

Rewritable two-dimensional DNA-based data storage with machine learning reconstruction

DNA-based data storage platforms traditionally encode information only in the nucleotide sequence of the molecule. Here we report on a two-dimensional molecular data storage system that records information in both the sequence and the backbone structure of DNA and performs nontrivial joint data encoding, decoding and processing. Our 2DDNA method efficiently stores images in synthetic DNA and embeds pertinent metadata as nicks in the DNA backbone. To avoid costly worst-case redundancy for correcting sequencing/rewriting errors and to mitigate issues associated with mismatched decoding parameters, we develop machine learning techniques for automatic discoloration detection and image inpainting. The 2DDNA platform is experimentally tested by reconstructing a library of images with undetectable or small visual degradation after readout processing, and by erasing and rewriting copyright metadata encoded in nicks. Our results demonstrate that DNA can serve both as a write-once and rewritable memory for heterogenous data and that data can be erased in a permanent, privacy-preserving manner. Moreover, the storage system can be made robust to degrading channel qualities while avoiding global error-correction redundancy.

Current DNA-based data storage platforms encode information only in the nucleotide sequence. Here, the authors report a 2DDNA platform that can store data in both sequence context and backbone structure, and has improved image inpainting and enhancement via automatic discoloration detection and deep learning.

DeSP: a systematic DNA storage error simulation pipeline

Background

Using DNA as a storage medium is appealing due to the information density and longevity of DNA, especially in the era of data explosion. A significant challenge in the DNA data storage area is to deal with the noises introduced in the channel and control the trade-off between the redundancy of error correction codes and the information storage density. As running DNA data storage experiments in vitro is still expensive and time-consuming, a simulation model is needed to systematically optimize the redundancy to combat the channel's particular noise structure.

Results

Here, we present DeSP, a systematic DNA storage error Simulation Pipeline, which simulates the errors generated from all DNA storage stages and systematically guides the optimization of encoding redundancy. It covers both the sequence lost and the within-sequence errors in the particular context of the data storage channel. With this model, we explained how errors are generated and passed through different stages to form final sequencing results, analyzed the influence of error rate and sampling depth to final error rates, and demonstrated how to systemically optimize redundancy design in silico with the simulation model. These error simulation results are consistent with the in vitro experiments.

Conclusions

DeSP implemented in Python is freely available on Github (https://github.com/WangLabTHU/DeSP). It is a flexible framework for systematic error simulation in DNA storage and can be adapted to a wide range of experiment pipelines.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04723-w.

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.

Rewritable Macromolecular Data Storage with Automated Read-out

Rewriting data stored on synthetic macromolecules is an interesting feature, even though it is considered as being quite challenging within the area of digital macromolecules. In this context, we initially studied a strategy for modifying the position tag of sequence-encoded macromolecules in a reversible manner. The efficiency of this method, which relies on the orthogonal cleavage of a thioester moiety via aminolysis, was demonstrated by modifying parts of an exemplary sentence. Simultaneously, a novel algorithm was developed to ease the read-out of macromolecular information by means of MS/MS techniques. This program, Oligoreader, can identify potential information-containing macromolecules from a series of MS¹ spectra, analyze the corresponding MS² spectra, and finally decode the data. Consequently, the algorithm simplifies the entire read-out process by avoiding any interference from the operator, which increases the potential for blind sequencing of uniform macromolecules.