Molecular digital data storage using DNA

A primordial DNA store and compute engine

Any modern information system is expected to feature a set of primordial features and functions: a substrate stably carrying data; the ability to repeatedly write, read, erase, reload and compute on specific data from that substrate; and the overall ability to execute such functions in a seamless and programmable manner. For nascent molecular information technologies, proof-of-principle realization of this set of primordial capabilities would advance the vision for their continued development. Here we present a DNA-based store and compute engine that captures these primordial capabilities. This system comprises multiple image files encoded into DNA and adsorbed onto ~50-μm-diameter, highly porous, hierarchically branched, colloidal substrate particles comprised of naturally abundant cellulose acetate. Their surface areas are over 200 cm2 mg-1 with binding capacities of over 1012 DNA oligos mg-1, 10 TB mg-1 or 104 TB cm-3. This 'dendricolloid' stably holds DNA files better than bare DNA with an extrapolated ability to be repeatedly lyophilized and rehydrated over 170 times compared with 60 times, respectively. Accelerated ageing studies project half-lives of ~6,000 and 2 million years at 4 °C and -18 °C, respectively. The data can also be erased and replaced, and non-destructive file access is achieved through transcribing from distinct synthetic promoters. The resultant RNA molecules can be directly read via nanopore sequencing and can also be enzymatically computed to solve simplified 3 × 3 chess and sudoku problems. Our study establishes a feasible route for utilizing the high information density and parallel computational advantages of nucleic acids.

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

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

DNA-DISK: Automated end-to-end data storage via enzymatic single-nucleotide DNA synthesis and sequencing on digital microfluidics

In the age of information explosion, the exponential growth of digital data far exceeds the capacity of current mainstream storage media. DNA is emerging as a promising alternative due to its higher storage density, longer retention time, and lower power consumption. To date, commercially mature DNA synthesis and sequencing technologies allow for writing and reading of information on DNA with customization and convenience at the research level. However, under the disconnected and nonspecialized mode, DNA data storage encounters practical challenges, including susceptibility to errors, long storage latency, resource-intensive requirements, and elevated information security risks. Herein, we introduce a platform named DNA-DISK that seamlessly streamlined DNA synthesis, storage, and sequencing on digital microfluidics coupled with a tabletop device for automated end-to-end information storage. The single-nucleotide enzymatic DNA synthesis with biocapping strategy is utilized, offering an ecofriendly and cost-effective approach for data writing. A DNA encapsulation using thermo-responsive agarose is developed for on-chip solidification, not only eliminating data clutter but also preventing DNA degradation. Pyrosequencing is employed for in situ and accurate data reading. As a proof of concept, DNA-DISK successfully stored and retrieved a musical sheet file (228 bits) with lower write-to-read latency (4.4 min of latency per bit) as well as superior automation compared to other platforms, demonstrating its potential to evolve into a DNA Hard Disk Drive in the future.

Engineering the Activity of a Template-Independent DNA Polymerase

Enzymatic DNA writing technologies based on the template-independent DNA polymerase terminal deoxynucleotidyl transferase (TdT) have the potential to advance DNA information storage. TdT is unique in its ability to synthesize single-stranded DNA de novo but has limitations, including catalytic inhibition by ribonucleotide presence and slower incorporation rates compared to replicative polymerases. We anticipate that protein engineering can improve, modulate, and tailor the enzyme's properties, but there is limited information on TdT sequence-structure-function relationships to facilitate rational approaches. Therefore, we developed an easily modifiable screening assay that can measure the TdT activity in high-throughput to evaluate large TdT mutant libraries. We demonstrated the assay's capabilities by engineering TdT mutants that exhibit both improved catalytic efficiency and improved activity in the presence of an inhibitor. We screened for and identified TdT variants with greater catalytic efficiency in both selectively incorporating deoxyribonucleotides and in the presence of deoxyribonucleotide/ribonucleotide mixes. Using this information from the screening assay, we rationally engineered other TdT homologues with the same properties. The emulsion-based assay we developed is, to the best of our knowledge, the first high-throughput screening assay that can measure TdT activity quantitatively and without the need for protein purification.

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.

Xeno Nucleic Acids as Functional Materials: From Biophysical Properties to Application

Xeno nucleic acid (XNA) are artificial nucleic acids, in which the chemical composition of the sugar moiety is changed. These modifications impart distinct physical and chemical properties to XNAs, leading to changes in their biological, chemical, and physical stability. Additionally, these alterations influence the binding dynamics of XNAs to their target molecules. Consequently, XNAs find expanded applications as functional materials in diverse fields. This review provides a comprehensive summary of the distinctive biophysical properties exhibited by various modified XNAs and explores their applications as innovative functional materials in expanded fields.

Heterocycles as supramolecular handles for crystal engineering: a case study with 7-(diethylamino)coumarin derivatives

In this study, we present the synthesis and detailed solid-state structural characterization of a Schiff-base-bridged derivative of 7-(diethylamino)coumarin (7-DAC), a molecular block displaying repetitive aggregation modes in the solid state despite being attached to broadly different molecular frameworks. To map the supramolecular habits of this unconventional moiety, we carry out a comparative analysis of the crystal packing in a curated dataset of 50 molecules decorated with the 7-DAC group, retrieved from the literature. We uncover that self-recognition of the 7-DAC moiety has two main components: a set of directional C-H⋯O interactions between neighboring coumarins, and antiparallel dipole-dipole interactions, taking the form of distinct π-stacking modes. The pendant 7-diethylamino group is key to the behavior of 7-DAC, favoring its solubilization through its conformational flexibility in solution, while in the crystalline matrix, it acts as a structural spacer that favors π-stacking interactions. Our findings present a comprehensive analysis of the preferential arrangements of the 7-DAC fragment in various (supra)molecular scenarios, confirming that it is (i) a mobile but mostly planar group, (ii) a group prone to antiparallel aggregation, and (iii) up to 90% likely to pack via π-stacking supported by hydrogen-bonding interactions. These findings enrich the palette of supramolecular motifs available for the bottom-up design of organic materials and their programmed construction.

Efficient DNA Coding Algorithm for Polymerase Chain Reaction Amplification Information Retrieval

Polymerase Chain Reaction (PCR) amplification is widely used for retrieving information from DNA storage. During the PCR amplification process, nonspecific pairing between the 3' end of the primer and the DNA sequence can cause cross-talk in the amplification reaction, leading to the generation of interfering sequences and reduced amplification accuracy. To address this issue, we propose an efficient coding algorithm for PCR amplification information retrieval (ECA-PCRAIR). This algorithm employs variable-length scanning and pruning optimization to construct a codebook that maximizes storage density while satisfying traditional biological constraints. Subsequently, a codeword search tree is constructed based on the primer library to optimize the codebook, and a variable-length interleaver is used for constraint detection and correction, thereby minimizing the likelihood of nonspecific pairing. Experimental results demonstrate that ECA-PCRAIR can reduce the probability of nonspecific pairing between the 3' end of the primer and the DNA sequence to 2-25%, enhancing the robustness of the DNA sequences. Additionally, ECA-PCRAIR achieves a storage density of 2.14-3.67 bits per nucleotide (bits/nt), significantly improving storage capacity.

Cascadable-Controllable Self-Assembly DNA Tiles for Large-Scale DNA Logic Circuits

In the last few decades, DNA-based self-assembly tiles has become a hot field in research due to its special applications and advantages. The regularity and strong design methods comprise other DNA-based digital circuit design methods. In addition to the obvious advantages of this method, there are challenges in performing computations based on self-assembly tiles, which have hindered the development and construction of large computing circuits with this method. The first challenge is the creation of crystals from DNA molecules in the output, which has led to the impossibility of cascading. The second challenge of this method is the uncontrollability of the reactions of the tiles, which increases the percentage of computing errors. In this article, these two challenges have been solved by changing the structure of leading tiles so that without the activator strand, tiles remain inactive and cannot be connected to other tiles. Also, when the tiles are activated, single-strand DNA will be released after connecting to other tiles, which will be used as the output of the circuit. This output gives the possibility of cascading to self-assembly designed circuits. The method introduced in this article can be a beginning for the re-development of DNA-based circuit design with the self-assembly tile method.

Information Density Enhancement Using Lossy Compression in DNA Data Storage

This study develops two deoxyribonucleic acid (DNA) lossy compression models, Models A and B, to encode grayscale images into DNA sequences, enhance information density, and enable high-fidelity image recovery. These models, distinguished by their handling of pixel domains and interpolation methods, offer a novel approach to data storage for DNA. Model A processes pixels in overlapped domains using linear interpolation (LI), whereas Model B uses non-overlapped domains with nearest-neighbor interpolation (NNI). Through a comparative analysis with Joint Photographic Experts Group (JPEG) compression, the DNA lossy compression models demonstrate competitive advantages in terms of information density and image quality restoration. The application of these models to the Modified National Institute of Standards and Technology (MNIST) dataset reveals their efficiency and the recognizability of decompressed images, which is validated by convolutional neural network (CNN) performance. In particular, Model B2, a version of Model B, emerges as an effective method for balancing high information density (surpassing over 20 times the typical densities of two bits per nucleotide) with reasonably good image quality. These findings highlight the potential of DNA-based data storage systems for high-density and efficient compression, indicating a promising future for biological data storage solutions.

Turbo autoencoders for the DNA data storage channel with Autoturbo-DNA

DNA, with its high storage density and long-term stability, is a potential candidate for a next-generation storage device. The DNA data storage channel, composed of synthesis, amplification, storage, and sequencing, exhibits error probabilities and error profiles specific to the components of the channel. Here, we present Autoturbo-DNA, a PyTorch framework for training error-correcting, overcomplete autoencoders specifically tailored for the DNA data storage channel. It allows training different architecture combinations and using a wide variety of channel component models for noise generation during training. It further supports training the encoder to generate DNA sequences that adhere to user-defined constraints. Autoturbo-DNA exhibits error-correction capabilities close to non-neural-network state-of-the-art error correction and constrained codes for DNA data storage. Our results indicate that neural-network-based codes can be a viable alternative to traditionally designed codes for the DNA data storage channel.

Advanced Smart Biomaterials for Regenerative Medicine and Drug Delivery Based on Phosphoramidite Chemistry: From Oligonucleotides to Precision Polymers

Over decades of development, while phosphoramidite chemistry has been known as the leading method in commercial synthesis of oligonucleotides, it has also revolutionized the fabrication of sequence-defined polymers (SDPs), offering novel functional materials in polymer science and clinical medicine. This review has introduced the evolution of phosphoramidite chemistry, emphasizing its development from the synthesis of oligonucleotides to the creation of universal SDPs, which have unlocked the potential for designing programmable smart biomaterials with applications in diverse areas including data storage, regenerative medicine and drug delivery. The key methodologies, functions, biomedical applications, and future challenges in SDPs, have also been summarized in this review, underscoring the significance of breakthroughs in precisely synthesized materials.

Repurposing Waste Chemicals for Sustainable and Durable Molecular Data Storage

Molecular data storage offers the intriguing possibility of higher theoretical density and longer lifetimes than today's electronic memory devices. Some demonstrations have used deoxyribonucleic acid (DNA), but bottlenecks in nucleic acid synthesis continue to make DNA data storage orders of magnitude more expensive than electronic storage media. Additionally, despite its potential for long-term storage, DNA faces durability challenges from environmental degradation. In this work, we demonstrate nongenomic molecular data storage using molecular libraries redirected from chemical waste streams. This approach requires no synthetic effort and can be implemented by using molecules that have a minimal associated cost. While the technique is agnostic about the exact molecular content of its inputs, we confirmed that some sources contained poly fluoroalkyl substances (PFAS), which persist for long periods in the natural environment and could offer extremely durable information storage as well as environmental benefits. These demonstrations provide a perspective on some of the valuable possibilities for nongenomic molecular information systems.

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.

Structures, fundamental properties, and potential applications of low-dimensional C60 polymers and other nanocarbons: a review

Since carbon (C) atom has a variety of chemical bonds via hybridization between s and p atomic orbitals, it is well known that there are robust carbon materials. In particular, discovery of C60 has been an epoch making to cultivate nanocarbon fields. Since then, nanocarbon materials such as nanotube and graphene have been reported. It is interesting to note that C60 is soluble and volatile unlike nanotube and graphene. This indicates that C60 film is easy to be produced on any kinds of substrates, which is advantage for device fabrication. In particular, electron-/photo-induced C60 polymerization finally results in formation of one-dimensional (1D) metallic peanut-shaped and 2D dumbbell-shaped semiconducting C60 polymers, respectively. This enables us to control the physicochemical properties of C60 films using electron-/photo-lithography techniques. In this review, we focused on the structures, fundamental properties, and potential applications of the low-dimensional C60 polymers and other nanocarbons such as C60 peapods, wavy-structured graphene, and penta-nanotubes with topological defects. We hope this review will provide new insights for producing new novel nanocarbon materials and inspire broad readers to cultivate new further research in carbon materials.

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.

"Cell Disk" DNA Storage System Capable of Random Reading and Rewriting

DNA has emerged as an appealing material for information storage due to its great storage density and durability. Random reading and rewriting are essential tasks for practical large-scale data storage. However, they are currently difficult to implement simultaneously in a single DNA-based storage system, strongly limiting their practicability. Here, a "Cell Disk" storage system is presented, achieving high-density in vivo DNA data storage that enables both random reading and rewriting. In this system, each yeast cell is used as a chamber to store information, similar to a "disk block" but with the ability to self-replicate. Specifically, each genome of yeast cell has a customized CRISPR/Cas9-based "lock-and-key" module inserted, which allows selective retrieval, erasure, or rewriting of the targeted cell "block" from a pool of cells ("disk"). Additionally, a codec algorithm with lossless compression ability is developed to improve the information density of each cell "block". As a proof of concept, target-specific reading and rewriting of the compressed data from a mimic cell "disk" comprising up to 105 "blocks" are demonstrated and achieve high specificity and reliability. The "Cell Disk" system described here concurrently supports random reading and rewriting, and it should have great scalability for practical data storage use.

Storage-D: A user-friendly platform that enables practical and personalized DNA data storage

Deoxyribonucleic acid (DNA) has been suggested as a very promising medium for data storage in recent years. Although numerous studies have advocated for DNA data storage, its practical application remains obscure and there is a lack of a user-oriented platform. Here, we developed a DNA data storage platform, named Storage-D, which allows users to convert their data into DNA sequences of any length and vice versa by selecting algorithms, error-correction, random-access, and codec pin strategies in terms of their own choice. It incorporates a newly designed "Wukong" algorithm, which provides over 20 trillion codec pins for data privacy use. This algorithm can also control GC content to the selected standard, as well as adjust the homopolymer run length to a defined level, while maintaining a high coding potential of ~1.98 bis/nt, allowing it to outperform previous algorithms. By connecting to a commercial DNA synthesis and sequencing platform with "Storage-D," we successfully stored "Diagnosis and treatment protocol for COVID-19 patients" into 200 nt oligo pools in vitro, and 500 bp genes in vivo which replicated in both normal and extreme bacteria. Together, this platform allows for practical and personalized DNA data storage, potentially with a wide range of applications.

Exchanging and Releasing Information in Synthetic Digital Polymers Using a Strand-Displacement Strategy

Toehold-mediated strand displacement (TMSD) was tested as a tool to edit information in synthetic digital polymers. Uniform DNA-polymer biohybrid macromolecules were first synthesized by automated phosphoramidite chemistry and characterized by HPLC, mass spectrometry, and polyacrylamide gel electrophoresis (PAGE). These precursors were diblock structures containing a synthetic poly(phosphodiester) (PPDE) segment covalently attached to a single-stranded DNA sequence. Three types of biohybrids were prepared herein: a substrate containing an accessible toehold as well as input and output macromolecules. The substrate and the input macromolecules contained noncoded PPDE homopolymers, whereas the output macromolecule contained a digitally encoded segment. After hybridization of the substrate with the output, incubation in the presence of the input led to efficient TMSD and the release of the digital segment. TMSD can therefore be used to erase or rewrite information in self-assembled biohybrid superstructures. Furthermore, it was found in this work that the conjugation of DNA single strands to synthetic segments of chosen lengths greatly facilitates the characterization and PAGE visualization of the TMSD process.

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.

NeuroPep 2.0: An Updated Database Dedicated to Neuropeptide and Its Receptor Annotations

Neuropeptides not only work through nervous system but some of them also work peripherally to regulate numerous physiological processes. They are important in regulation of numerous physiological processes including growth, reproduction, social behavior, inflammation, fluid homeostasis, cardiovascular function, and energy homeostasis. The various roles of neuropeptides make them promising candidates for prospective therapeutics of different diseases. Currently, NeuroPep has been updated to version 2.0, it now holds 11,417 unique neuropeptide entries, which is nearly double of the first version of NeuroPep. When available, we collected information about the receptor for each neuropeptide entry and predicted the 3D structures of those neuropeptides without known experimental structure using AlphaFold2 or APPTEST according to the peptide sequence length. In addition, DeepNeuropePred and NeuroPred-PLM, two neuropeptide prediction tools developed by us recently, were also integrated into NeuroPep 2.0 to help to facilitate the identification of new neuropeptides. NeuroPep 2.0 is freely accessible at https://isyslab.info/NeuroPepV2/.

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.

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.

How close are we to storing data in DNA?

DNA is an intelligent data storage medium due to its stability and high density. It has been used by nature for over 3.5 billion years. Compared with traditional methods, DNA offers better compression and physical density. DNA can retain information for thousands of years. However, challenges exist in scalability, standardization, metadata gathering, biocybersecurity, and specialized tools. Addressing these challenges is crucial for widespread implementation. Collaboration among experts, as well as keeping the future in mind, is needed to unlock the full potential of DNA data storage, which promises low energy costs, high-density storage, and long-term stability.

Simulation-Assisted DNA Nanodevice Serve as a General Optical Platform for Multiplexed Analysis of Micrornas

Small frame nucleic acids (FNAs) serve as excellent carrier materials for various functional nucleic acid molecules, showcasing extensive potential applications in biomedicine development. The carrier module and function module combination is crucial for probe design, where an improper combination can significantly impede the functionality of sensing platforms. This study explores the effect of various combinations on the sensing performance of nanodevices through simulations and experimental approaches. Variances in response velocities, sensitivities, and cell uptake efficiencies across different structures are observed. Factors such as the number of functional molecules loaded, loading positions, and intermodular distances affect the rigidity and stability of the nanostructure. The findings reveal that the structures with full loads and moderate distances between modules have the lowest potential energy. Based on these insights, a multisignal detection platform that offers optimal sensitivity and response speed is developed. This research offers valuable insights for designing FNAs-based probes and presents a streamlined method for the conceptualization and optimization of DNA nanodevices.

Data Storage Using DNA

The exponential growth of global data has outpaced the storage capacities of current technologies, necessitating innovative storage strategies. DNA, as a natural medium for preserving genetic information, has emerged as a highly promising candidate for next-generation storage medium. Storing data in DNA offers several advantages, including ultrahigh physical density and exceptional durability. Facilitated by significant advancements in various technologies, such as DNA synthesis, DNA sequencing, and DNA nanotechnology, remarkable progress has been made in the field of DNA data storage over the past decade. However, several challenges still need to be addressed to realize practical applications of DNA data storage. In this review, the processes and strategies of in vitro DNA data storage are first introduced, highlighting recent advancements. Next, a brief overview of in vivo DNA data storage is provided, with a focus on the various writing strategies developed to date. At last, the challenges encountered in each step of DNA data storage are summarized and promising techniques are discussed that hold great promise in overcoming these obstacles.

DNA data storage in electrospun and melt-electrowritten composite nucleic acid-polymer fibers

Incorporating biomolecules as integral parts of computational systems represents a frontier challenge in bio- and nanotechnology. Using DNA to store digital data is an attractive alternative to conventional information technologies due to its high information density and long lifetime. However, developing an adequate DNA storage medium remains a significant challenge in permitting the safe archiving and retrieval of oligonucleotides. This work introduces composite nucleic acid-polymer fibers as matrix materials for digital information-bearing oligonucleotides. We devised a complete workflow for the stable storage of DNA in PEO, PVA, and PCL fibers by employing electrohydrodynamic processes to produce electrospun nanofibers with embedded oligonucleotides. The on-demand retrieval of messages is afforded by non-hazardous chemical treatment and subsequent PCR amplification and DNA sequencing. Finally, we develop a platform for melt-electrowriting of polymer-DNA composites to produce microfiber meshes of programmable patterns and geometries.

Long oligodeoxynucleotides: chemical synthesis, isolation via catching-by-polymerization, verification via sequencing, and gene expression demonstration

Long oligodeoxynucleotides (ODNs) are segments of DNAs having over one hundred nucleotides (nt). They are typically assembled using enzymatic methods such as PCR and ligation from shorter 20 to 60 nt ODNs produced by automated de novo chemical synthesis. While these methods have made many projects in areas such as synthetic biology and protein engineering possible, they have various drawbacks. For example, they cannot produce genes and genomes with long repeats and have difficulty to produce sequences containing stable secondary structures. Here, we report a direct de novo chemical synthesis of 400 nt ODNs, and their isolation from the complex reaction mixture using the catching-by-polymerization (CBP) method. To determine the authenticity of the ODNs, 399 and 401 nt ODNs were synthesized and purified with CBP. The two were joined together using Gibson assembly to give the 800 nt green fluorescent protein (GFP) gene construct. The sequence of the construct was verified via Sanger sequencing. To demonstrate the potential use of the long ODN synthesis method, the GFP gene was expressed in E. coli. The long ODN synthesis and isolation method presented here provides a pathway to the production of genes and genomes containing long repeats or stable secondary structures that cannot be produced or are highly challenging to produce using existing technologies.

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.

PEGylated Dmoc phosphoramidites for sensitive oligodeoxynucleotide synthesis

Sensitive oligodeoxynucleotides (ODNs) can be synthesized using Dmoc phosphoramidites, but only short ODNs were demonstrated. Here, we report the synthesis of much longer ODNs, which was made possible by the use of PEGylated Dmoc (pDmoc) phosphoramidites. The longer ODNs synthesized include those containing the sensitive 4acC epigenetic modification recently discovered in nature.

Conception and Evaluation of a Library of Cleavable Mass Tags for Digital Polymers Sequencing

A library of phosphoramidite monomers containing a main-chain cleavable alkoxyamine and a side-chain substituent of variable molar mass (i.e. mass tag) was prepared in this work. These monomers can be used in automated solid-phase phosphoramidite chemistry and therefore incorporated periodically as spacers inside digitally-encoded poly(phosphodiester) chains. Consequently, the formed polymers contain tagged cleavable sites that guide their fragmentation in mass spectrometry sequencing and enhance their digital readability. The spacers were all prepared via a seven steps synthetic procedure. They were afterwards tested for the synthesis and sequencing of model digital polymers. Uniform digitally-encoded polymers were obtained as major species in all cases, even though some minor defects were sometimes detected. Furthermore, the polymers were decoded in pseudo-MS3 conditions, thus confirming the reliability and versatility of the spacers library.

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.

Processing DNA Storage through Programmable Assembly in a Droplet-Based Fluidics System

DNA can be used to store digital data, and synthetic short-sequence DNA pools are developed to store high quantities of digital data. However, synthetic DNA data cannot be actively processed in DNA pools. An active DNA data editing process is developed using splint ligation in a droplet-controlled fluidics (DCF) system. DNA fragments of discrete sizes (100-500 bps) are synthesized for droplet assembly, and programmed sequence information exchange occurred. The encoded DNA sequences are processed in series and parallel to synthesize the determined DNA pools, enabling random access using polymerase chain reaction amplification. The sequencing results of the assembled DNA data pools can be orderly aligned for decoding and have high fidelity through address primer scanning. Furthermore, eight 90 bps DNA pools with pixel information (png: 0.27-0.28 kB), encoded by codons, are synthesized to create eight 270 bps DNA pools with an animation movie chip file (mp4: 12 kB) in the DCF system.

Neural network execution using nicked DNA and microfluidics

DNA has been discussed as a potential medium for data storage. Potentially it could be denser, could consume less energy, and could be more durable than conventional storage media such as hard drives, solid-state storage, and optical media. However, performing computations on the data stored in DNA is a largely unexplored challenge. This paper proposes an integrated circuit (IC) based on microfluidics that can perform complex operations such as artificial neural network (ANN) computation on data stored in DNA. We envision such a system to be suitable for highly dense, throughput-demanding bio-compatible applications such as an intelligent Organ-on-Chip or other biomedical applications that may not be latency-critical. It computes entirely in the molecular domain without converting data to electrical form, making it a form of in-memory computing on DNA. The computation is achieved by topologically modifying DNA strands through the use of enzymes called nickases. A novel scheme is proposed for representing data stochastically through the concentration of the DNA molecules that are nicked at specific sites. The paper provides details of the biochemical design, as well as the design, layout, and operation of the microfluidics device. Benchmarks are reported on the performance of neural network computation.

Potential Use of Nucleic Acids as a Preceramic Polymer to Synthesize Nanodiamond-Embedded Phosphate Glass for Hard Tissue Engineering

In recent years, nucleic acid has emerged as a versatile molecule that has been strategically used in material synthesis and biomedical applications. Keeping in mind the presence of the phosphate group, a glass former in the nucleic acids, we synthesized a transparent glass-like material by the thermal treatment of nucleic acids (DNA and RNA) at 900 °C at atmospheric pressure. Characterization of this material by transmission electron microscopy, X-ray photoelectron spectroscopy, and confocal fluorescence microscopy suggested the presence of in situ-formed nanodiamonds within the phosphate glass matrix. The molecular structure of glass investigated by X-ray photoelectron and infrared spectroscopy indicated a nearly equal proportion of metaphosphates and smaller phosphate units (pyro- and ortho-phosphate) that form the phosphate glass matrix. Thereafter, in vitro biological experiments showed that the nucleic acid-derived glass was non-toxic and cytocompatible, enhanced extracellular matrix secretion, and increased intracellular alkaline phosphatase activity, with potential application in hard tissue engineering. Our work offers insights into nanodiamond synthesis at atmospheric pressure and proves that nucleic acids could be used as a precursor to making an innovative glass-ceramic biomaterial.

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.

Molecular data storage using direct analysis in real time (DART) ionization mass spectrometry for decoding

Molecular data storage is becoming a viable alternative to traditional information storage systems. Here, we propose a method where the presence or absence of a given molecule in a mixture of compounds represents a bit of information. As a novel approach, direct analysis in real time (DART) ionization mass spectrometry is used to recover and decode the information stored at the molecular level. Nicotinic acid derivatives were synthesized and used as the 'bit compounds'. Their volatility and ease of ionization make these molecules especially suitable for DART-MS detection. The application of DART-MS as a method with an ambient ionization technique, enables the re-reading of digital chemical codes embedded in the material of ordinary objects. Our method is designed to store and read back short pieces of digital information, up to several hundred bits. These codes can have the function of barcodes or QR codes, as shown in our proof-of-principle applications. First, modelling a QR code as a link to our university's website, three solutions were prepared, each representing 22 bits. Proceeding further, the bit compounds were incorporated into a polymer matrix that is suitable for 3D printing, and a toy ship was created with a hidden barcode. In addition, decoding software was developed to process the DART-MS spectra. The nicotinic acid components representing the bits dominated the DART-MS spectra and error-free decoding was achieved.

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.

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

DNA is a high-density, long-term stable, and scalable storage medium that can meet the increased demands on storage media resulting from the exponential growth of data. The existing DNA storage encoding schemes tend to achieve high-density storage but do not fully consider the local and global stability of DNA sequences and the read and write accuracy of the stored information. To address these problems, this article presents a graph-based De Bruijn Trim Rotation Graph (DBTRG) encoding scheme. Through XOR between the proposed dynamic binary sequence and the original binary sequence, k-mers can be divided into the De Bruijn Trim graph, and the stored information can be compressed according to the overlapping relationship. The simulated experimental results show that DBTRG ensures base balance and diversity, reduces the likelihood of undesired motifs, and improves the stability of DNA storage and data recovery. Furthermore, the maintenance of an encoding rate of 1.92 while storing 510 KB images and the introduction of novel approaches and concepts for DNA storage encoding methods are achieved.

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

MOTIVATION

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

RESULTS

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

AVAILABILITY AND IMPLEMENTATION

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

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.

RepairNatrix: a Snakemake workflow for processing DNA sequencing data for DNA storage

Motivation

There has been rapid progress in the development of error-correcting and constrained codes for DNA storage systems in recent years. However, improving the steps for processing raw sequencing data for DNA storage has a lot of untapped potential for further progress. In particular, constraints can be used as prior information to improve the processing of DNA sequencing data. Furthermore, a workflow tailored to DNA storage codes enables fair comparisons between different approaches while leading to reproducible results.

Results

We present RepairNatrix, a read-processing workflow for DNA storage. RepairNatrix supports preprocessing of raw sequencing data for DNA storage applications and can be used to flag and heuristically repair constraint-violating sequences to further increase the recoverability of encoded data in the presence of errors. Compared to a preprocessing strategy without repair functionality, RepairNatrix reduced the number of raw reads required for the successful, error-free decoding of the input files by a factor of 25-35 across different datasets.

Availability and implementation

RepairNatrix is available on Github: https://github.com/umr-ds/repairnatrix.

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.

Implementing Logic Gates by DNA Crystal Engineering

DNA self-assembly computation is attractive for its potential to perform massively parallel information processing at the molecular level while at the same time maintaining its natural biocompatibility. It has been extensively studied at the individual molecule level, but not as much as ensembles in 3D. Here, the feasibility of implementing logic gates, the basic computation operations, in large ensembles: macroscopic, engineered 3D DNA crystals is demonstrated. The building blocks are the recently developed DNA double crossover-like (DXL) motifs. They can associate with each other via sticky-end cohesion. Common logic gates are realized by encoding the inputs within the sticky ends of the motifs. The outputs are demonstrated through the formation of macroscopic crystals that can be easily observed. This study points to a new direction of construction of complex 3D crystal architectures and DNA-based biosensors with easy readouts.

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.

Modularized synthetic biology enabled intelligent biosensors

Biosensors that sense the concentration of a specified target and produce a specific signal output have become important technology for biological analysis. Recently, intelligent biosensors have received great interest due to their adaptability to meet sophisticated demands. Advances in developing standard modules and carriers in synthetic biology have shed light on intelligent biosensors that can implement advanced analytical processing to better accommodate practical applications. This review focuses on intelligent synthetic biology-enabled biosensors (SBBs). First, we illustrate recent progress in intelligent SBBs with the capability of computation, memory storage, and self-calibration. Then, we discuss emerging applications of SBBs in point-of-care testing (POCT) and wearable monitoring. Finally, future perspectives on intelligent SBBs are proposed.

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.

Sub-1.4 cm3 capsule for detecting labile inflammatory biomarkers in situ

Transient molecules in the gastrointestinal tract such as nitric oxide and hydrogen sulfide are key signals and mediators of inflammation. Owing to their highly reactive nature and extremely short lifetime in the body, these molecules are difficult to detect. Here we develop a miniaturized device that integrates genetically engineered probiotic biosensors with a custom-designed photodetector and readout chip to track these molecules in the gastrointestinal tract. Leveraging the molecular specificity of living sensors1, we genetically encoded bacteria to respond to inflammation-associated molecules by producing luminescence. Low-power electronic readout circuits2 integrated into the device convert the light emitted by the encapsulated bacteria to a wireless signal. We demonstrate in vivo biosensor monitoring in the gastrointestinal tract of small and large animal models and the integration of all components into a sub-1.4 cm3 form factor that is compatible with ingestion and capable of supporting wireless communication. With this device, diseases such as inflammatory bowel disease could be diagnosed earlier than is currently possible, and disease progression could be more accurately tracked. The wireless detection of short-lived, disease-associated molecules with our device could also support timely communication between patients and caregivers, as well as remote personalized care.

Development of nucleic acid medicines based on chemical technology

Oligonucleotide-based therapeutics have attracted attention as an emerging modality that includes the modulation of genes and their binding proteins related to diseases, allowing us to take action on previously undruggable targets. Since the late 2010s, the number of oligonucleotide medicines approved for clinical uses has dramatically increased. Various chemistry-based technologies have been developed to improve the therapeutic properties of oligonucleotides, such as chemical modification, conjugation, and nanoparticle formation, which can increase nuclease resistance, enhance affinity and selectivity to target sites, suppress off-target effects, and improve pharmacokinetic properties. Similar strategies employing modified nucleobases and lipid nanoparticles have been used for developing coronavirus disease 2019 mRNA vaccines. In this review, we provide an overview of the development of chemistry-based technologies aimed at using nucleic acids for developing therapeutics over the past several decades, with a specific emphasis on the structural design and functionality of chemical modification strategies.