Nucleic acid memory

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

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

Semiautomated synthesis of sequence-defined polymers for information storage

Accelerated and parallel synthesis of sequence-defined polymers is an utmost challenge for realizing ultrahigh-density storage of digital information in molecular media. Here, we report step-economical synthesis of sequence-defined poly(l-lactic-co-glycolic acid)s (PLGAs) using continuous flow chemistry. A reactor performed the programmed coupling of the 2-bit storing building blocks to generate a library of their permutations in a single continuous flow, followed by their sequential convergences to a sequence-defined PLGA storing 64 bits in four successive flows. We demonstrate that a bitmap image (896 bits) can be encoded and decoded in 14 PLGAs using only a fraction of the time required for an equivalent synthesis by conventional batch processes. Accelerated synthesis of sequence-defined polymers could also contribute to macromolecular engineering with precision comparable to natural precedents.

Expanding the Molecular Alphabet of DNA-Based Data Storage Systems with Neural Network Nanopore Readout Processing

DNA is a promising next-generation data storage medium, but challenges remain with synthesis costs and recording latency. Here, we describe a prototype of a DNA data storage system that uses an extended molecular alphabet combining natural and chemically modified nucleotides. Our results show that MspA nanopores can discriminate different combinations and ordered sequences of natural and chemically modified nucleotides in custom-designed oligomers. We further demonstrate single-molecule sequencing of the extended alphabet using a neural network architecture that classifies raw current signals generated by Oxford Nanopore sequencers with an average accuracy exceeding 60% (39× larger than random guessing). Molecular dynamics simulations show that the majority of modified nucleotides lead to only minor perturbations of the DNA double helix. Overall, the extended molecular alphabet may potentially offer a nearly 2-fold increase in storage density and potentially the same order of reduction in the recording latency, thereby enabling new implementations of molecular recorders.

Recent Advances in Polymer Additive Engineering for Diagnostic and Therapeutic Hydrogels

Hydrogels are hydrophilic polymer materials that provide a wide range of physicochemical properties as well as are highly biocompatible. Biomedical researchers are adapting these materials for the ever-increasing range of design options and potential applications in diagnostics and therapeutics. Along with innovative hydrogel polymer backbone developments, designing polymer additives for these backbones has been a major contributor to the field, especially for expanding the functionality spectrum of hydrogels. For the past decade, researchers invented numerous hydrogel functionalities that emerge from the rational incorporation of additives such as nucleic acids, proteins, cells, and inorganic nanomaterials. Cases of successful commercialization of such functional hydrogels are being reported, thus driving more translational research with hydrogels. Among the many hydrogels, here we reviewed recently reported functional hydrogels incorporated with polymer additives. We focused on those that have potential in translational medicine applications which range from diagnostic sensors as well as assay and drug screening to therapeutic actuators as well as drug delivery and implant. We discussed the growing trend of facile point-of-care diagnostics and integrated smart platforms. Additionally, special emphasis was given to emerging bioinformatics functionalities stemming from the information technology field, such as DNA data storage and anti-counterfeiting strategies. We anticipate that these translational purpose-driven polymer additive research studies will continue to advance the field of functional hydrogel engineering.

Multi-resolution simulation of DNA transport through large synthetic nanostructures

Modeling and simulation has become an invaluable partner in development of nanopore sensing systems. The key advantage of the nanopore sensing method - the ability to rapidly detect individual biomolecules as a transient reduction of the ionic current flowing through the nanopore - is also its key deficiency, as the current signal itself rarely provides direct information about the chemical structure of the biomolecule. Complementing experimental calibration of the nanopore sensor readout, coarse-grained and all-atom molecular dynamics simulations have been used extensively to characterize the nanopore translocation process and to connect the microscopic events taking place inside the nanopore to the experimentally measured ionic current blockades. Traditional coarse-grained simulations, however, lack the precision needed to predict ionic current blockades with atomic resolution whereas traditional all-atom simulations are limited by the length and time scales amenable to the method. Here, we describe a multi-resolution framework for modeling electric field-driven passage of DNA molecules and nanostructures through to-scale models of synthetic nanopore systems. We illustrate the method by simulating translocation of double-stranded DNA through a solid-state nanopore and a micron-scale slit, capture and translocation of single-stranded DNA in a double nanopore system, and modeling ionic current readout from a DNA origami nanostructure passage through a nanocapillary. We expect our multi-resolution simulation framework to aid development of the nanopore field by providing accurate, to-scale modeling capability to research laboratories that do not have access to leadership supercomputer facilities.

Synthetic DNA applications in information technology

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

Fractal construction of constrained code words for DNA storage systems

The use of complex biological molecules to solve computational problems is an emerging field at the interface between biology and computer science. There are two main categories in which biological molecules, especially DNA, are investigated as alternatives to silicon-based computer technologies. One is to use DNA as a storage medium, and the other is to use DNA for computing. Both strategies come with certain constraints. In the current study, we present a novel approach derived from chaos game representation for DNA to generate DNA code words that fulfill user-defined constraints, namely GC content, homopolymers, and undesired motifs, and thus, can be used to build codes for reliable DNA storage systems.

Biotechnologies to Bridge the Schism in the Bioeconomy

Schism is the new normal for the bioeconomy concept. Since its proliferation in governments, the concept has been adapted to fit national or regional exigencies. Earlier this century the knowledge-based bioeconomy (KBBE) in Europe was seen as a technical and knowledge fix in the evolving sustainability landscape. At the OECD, the concept was further honed by imagining a future where biotechnologies contribute significantly to economic growth and development. Countries started to make national bioeconomy strategies. Some countries have diverged and made the bioeconomy both much larger and more general, involving a wide variety of sectors, such as industry, energy, healthcare, agriculture, aquaculture, forestry and fishing. Whatever the approach, what seems to be consistent is the need to reconcile environmental, social and economic sustainability. This paper attempts to establish one schism that could have ramifications for the future development of the bioeconomy. Some countries, including some of the largest economies but not exclusively so, are clearly following a biotechnology model, whereas others are clearly not. In the wake of the COVID-19 pandemic, biotechnologies offer outstanding potential in healthcare, although this sector is by no means included in all bioeconomy strategies. The paper also attempts to clarify how biotechnologies can address the grand challenges and the United Nations Sustainable Development Goals. The communities of scientists seem to have no difficulty with this, but citizens and governments find it more difficult. In fact, some biotechnologies are already well established, whereas others are emerging and more controversial.

Concepts and Application of DNA Origami and DNA Self-Assembly: A Systematic Review

With the arrival of the post-Moore Era, the development of traditional silicon-based computers has reached the limit, and it is urgent to develop new computing technology to meet the needs of science and life. DNA computing has become an essential branch and research hotspot of new computer technology because of its powerful parallel computing capability and excellent data storage capability. Due to good biocompatibility and programmability properties, DNA molecules have been widely used to construct novel self-assembled structures. In this review, DNA origami is briefly introduced firstly. Then, the applications of DNA self-assembly in material physics, biogenetics, medicine, and other fields are described in detail, which will aid the development of DNA computational model in the future.

Storing and Reading Information in Mixtures of Fluorescent Molecules

The rapidly increasing use of digital technologies requires the rethinking of methods to store data. This work shows that digital data can be stored in mixtures of fluorescent dye molecules, which are deposited on a surface by inkjet printing, where an amide bond tethers the dye molecules to the surface. A microscope equipped with a multichannel fluorescence detector distinguishes individual dyes in the mixture. The presence or absence of these molecules in the mixture encodes binary information (i.e., "0" or "1"). The use of mixtures of molecules, instead of sequence-defined macromolecules, minimizes the time and difficulty of synthesis and eliminates the requirement of sequencing. We have written, stored, and read a total of approximately 400 kilobits (both text and images) with greater than 99% recovery of information, written at an average rate of 128 bits/s (16 bytes/s) and read at a rate of 469 bits/s (58.6 bytes/s).

Building blocks for autonomous computing materials: Dimers, trimers, and tetramers

Autonomous computing materials for data storage and computing offer an opportunity for next generation of computing devices. Patchy nanoparticle networks, for example, have been suggested as potential candidates for emulating neuronal networks and performing brain-like computing. Here, we use molecular dynamics (MD) simulations to show that stable dimers, trimers, and tetramers can be built from citrate capped gold nanoparticles (cit-AuNPs) linked by poly(allylamine hydrochloride) (PAH) chains. We use different lengths of PAHs to build polymer-networked nanoparticle assemblies that can emulate a complex neuronal network linked by axons of varying lengths. We find that the tetramer structure can accommodate up to 11 different states when the AuNP pairs are connected by either of two polymer linkers, PAH₂₀₀ and PAH₃₀₀. We find that the heavy AuNPs contribute to the assembly's structure stability. To further illustrate the stability, the AuNP-AuNP distances in dimer, trimer, and tetramer structures are reduced by steering the cit-AuNPs closer to each other. At different distances, these steered structures are all locally stable in a 10 ns MD simulation time scale because of their connection to the AuNPs. We also find that the global potential energy minimum is at short AuNP-AuNP distances where AuNPs collapse because the -NH₃ ⁺ and -COO^- attraction reduces the potential energy. The stability and application of these fundamental structures remain to be further improved through the use of alternative polymer linkers and nanoparticles.

Nanopores in Atomically Thin 2D Nanosheets Limit Aqueous Single-Stranded DNA Transport

Nanopores in 2D materials are highly desirable for DNA sequencing, yet achieving single-stranded DNA (ssDNA) transport through them is challenging. Using density functional theory calculations and molecular dynamics simulations we show that ssDNA transport through a pore in monolayer hexagonal boron nitride (h-BN) is marked by a basic nanomechanical conflict. It arises from the notably inhomogeneous flexural rigidity of ssDNA and causes high friction via transient DNA desorption costs exacerbated by solvation effects. For a similarly sized pore in bilayer h-BN, its self-passivated atomically smooth edge enables continuous ssDNA transport. Our findings shed light on the fundamental physics of biopolymer transport through pores in 2D materials.

A self-contained and self-explanatory DNA storage system

Current research on DNA storage usually focuses on the improvement of storage density by developing effective encoding and decoding schemes while lacking the consideration on the uncertainty in ultra-long-term data storage and retention. Consequently, the current DNA storage systems are often not self-contained, implying that they have to resort to external tools for the restoration of the stored DNA data. This may result in high risks in data loss since the required tools might not be available due to the high uncertainty in far future. To address this issue, we propose in this paper a self-contained DNA storage system that can bring self-explanatory to its stored data without relying on any external tool. To this end, we design a specific DNA file format whereby a separate storage scheme is developed to reduce the data redundancy while an effective indexing is designed for random read operations to the stored data file. We verified through experimental data that the proposed self-contained and self-explanatory method can not only get rid of the reliance on external tools for data restoration but also minimise the data redundancy brought about when the amount of data to be stored reaches a certain scale.

Random access DNA memory using Boolean search in an archival file storage system

DNA is an ultrahigh-density storage medium that could meet exponentially growing worldwide demand for archival data storage if DNA synthesis costs declined sufficiently and if random access of files within exabyte-to-yottabyte-scale DNA data pools were feasible. Here, we demonstrate a path to overcome the second barrier by encapsulating data-encoding DNA file sequences within impervious silica capsules that are surface labelled with single-stranded DNA barcodes. Barcodes are chosen to represent file metadata, enabling selection of sets of files with Boolean logic directly, without use of amplification. We demonstrate random access of image files from a prototypical 2-kilobyte image database using fluorescence sorting with selection sensitivity of one in 10⁶ files, which thereby enables one in 10^6N selection capability using N optical channels. Our strategy thereby offers a scalable concept for random access of archival files in large-scale molecular datasets.

A mirror-image protein-based information barcoding and storage technology

A mirror-image protein-based information barcoding and storage technology wherein D-amino acids are used to encode information into mirror-image proteins that are chemically synthesized is described. These mirror-image proteins were then fused into various materials from which information-encoded objects were produced. Subsequently, the mirror-image proteins were extracted from the objects using biotin-streptavidin resin-mediated specific enrichment and cleaved using an Ni(II)-mediated selective peptide cleavage. Protein sequencing was accomplished using liquid chromatography/tandem mass spectrometry (LC-MS/MS) and then transcoded into the recorded information. We demonstrated the use of this technology to encode Chinese words into mirror-image proteins, which were then fused onto a poly(ethylene terephthalate) (PET) film and retrieved and decoded by LC-MS/MS sequencing. Compared to information barcoding and storage technologies using natural biopolymers, the mirror-image biopolymers used in our technology may be more stable and durable.

Image Encoding Using Multi-Level DNA Barcodes with Nanopore Readout

Deoxyribonucleic acid (DNA) nanostructure-based data encoding is an emerging information storage mode, offering rewritable, editable, and secure data storage. Herein, a DNA nanostructure-based storage method established on a solid-state nanopore sensing platform to save and encrypt a 2D grayscale image is proposed. DNA multi-way junctions of different sizes are attached to a double strand of DNA carriers, resulting in distinct levels of current blockades when passing through a glass nanopore with diameters around 14 nm. The resulting quaternary encoding doubles the capacity relative to a classical binary system. Through toehold-mediated strand displacement reactions, the DNA nanostructures can be precisely added to and removed from the DNA carrier. By encoding the image into 16 DNA carriers using the quaternary barcodes and reading them in one simultaneous measurement, the image is successfully saved, encrypted, and recovered. Avoiding any proteins or enzymatic reactions, the authors thus realize a pure DNA storage system on a nanopore platform with increased capacity and programmability.

Large-Scale de novo Oligonucleotide Synthesis for Whole-Genome Synthesis and Data Storage: Challenges and Opportunities

Over the past decades, remarkable progress on phosphoramidite chemistry-based large-scale de novo oligonucleotide synthesis has been achieved, enabling numerous novel and exciting applications. Among them, de novo genome synthesis and DNA data storage are striking. However, to make these two applications more practical, the synthesis length, speed, cost, and throughput require vast improvements, which is a challenge to be met by the phosphoramidite chemistry. Harnessing the power of enzymes, the recently emerged enzymatic methods provide a competitive route to overcome this challenge. In this review, we first summarize the status of large-scale oligonucleotide synthesis technologies including the basic methodology and large-scale synthesis approaches, with special focus on the emerging enzymatic methods. Afterward, we discuss the opportunities and challenges of large-scale oligonucleotide synthesis on de novo genome synthesis and DNA data storage respectively.

Progress towards a cellularly resolved mouse mesoconnectome is empowered by data fusion and new neuroanatomy techniques

Over the past decade there has been a rapid improvement in techniques for obtaining large-scale cellular level data related to the mouse brain connectome. However, a detailed mapping of cell-type-specific projection patterns is lacking, which would, for instance, allow us to study the role of circuit motifs in cognitive processes. In this work, we review advanced neuroanatomical and data fusion techniques within the context of a proposed Multimodal Connectomic Integration Framework for augmenting the cellularly resolved mouse mesoconnectome. First, we emphasize the importance of registering data modalities to a common reference atlas. We then review a number of novel experimental techniques that can provide data for characterizing cell-types in the mouse brain. Furthermore, we examine a number of data integration strategies, which involve fine-grained cell-type classification, spatial inference of cell densities, latent variable models for the mesoconnectome and multi-modal factorisation. Finally, we discuss a number of use cases which depend on connectome augmentation techniques, such as model simulations of functional connectivity and generating mechanistic hypotheses for animal disease models.

Promiscuous molecules for smarter file operations in DNA-based data storage

DNA holds significant promise as a data storage medium due to its density, longevity, and resource and energy conservation. These advantages arise from the inherent biomolecular structure of DNA which differentiates it from conventional storage media. The unique molecular architecture of DNA storage also prompts important discussions on how data should be organized, accessed, and manipulated and what practical functionalities may be possible. Here we leverage thermodynamic tuning of biomolecular interactions to implement useful data access and organizational features. Specific sets of environmental conditions including distinct DNA concentrations and temperatures were screened for their ability to switchably access either all DNA strands encoding full image files from a GB-sized background database or subsets of those strands encoding low resolution, File Preview, versions. We demonstrate File Preview with four JPEG images and provide an argument for the substantial and practical economic benefit of this generalizable strategy to organize data.

The art of molecular computing: Whence and whither

An astonishingly diverse biomolecular circuitry orchestrates the functioning machinery underlying every living cell. These biomolecules and their circuits have been engineered not only for various industrial applications but also to perform other atypical functions that they were not evolved for-including computation. Various kinds of computational challenges, such as solving NP-complete problems with many variables, logical computation, neural network operations, and cryptography, have all been attempted through this unconventional computing paradigm. In this review, we highlight key experiments across three different ''eras'' of molecular computation, beginning with molecular solutions, transitioning to logic circuits and ultimately, more complex molecular networks. We also discuss a variety of applications of molecular computation, from solving NP-hard problems to self-assembled nanostructures for delivering molecules, and provide a glimpse into the exciting potential that molecular computing holds for the future. Also see the video abstract here: https://youtu.be/9Mw0K0vCSQw.

Uncertainties in synthetic DNA-based data storage

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

Sequence-Encoded Macromolecules with Increased Data Storage Capacity through a Thiol-Epoxy Reaction

Sequence-encoded oligo(thioether urethane)s with two different coding monomers per backbone unit were prepared via a solid phase, two-step iterative protocol based on thiolactone chemistry. The first step of the synthetic cycle consists of the thiolactone ring opening with a primary amine, whereby the in situ released thiol is immediately reacted with an epoxide. In the second step, the thiolactone group is reinstalled to initiate the next cycle. This strategy allows to introduce two different coding monomers per synthetic cycle, rendering the resulting macromolecules especially attractive in the area of (macro)molecular data storage because of their increased data storage capacity. Subsequently, the efficiency of the herein reported synthesis route and the applicability of the dual-encoded sequence-defined macromolecules as a potential data storage platform have been demonstrated by unraveling the exact monomer order using tandem mass spectrometry techniques.

CLGBO: An Algorithm for Constructing Highly Robust Coding Sets for DNA Storage

In the era of big data, new storage media are urgently needed because the storage capacity for global data cannot meet the exponential growth of information. Deoxyribonucleic acid (DNA) storage, where primer and address sequences play a crucial role, is one of the most promising storage media because of its high density, large capacity and durability. In this study, we describe an enhanced gradient-based optimizer that includes the Cauchy and Levy mutation strategy (CLGBO) to construct DNA coding sets, which are used as primer and address libraries. Our experimental results show that the lower bounds of DNA storage coding sets obtained using the CLGBO algorithm are increased by 4.3–13.5% compared with previous work. The non-adjacent subsequence constraint was introduced to reduce the error rate in the storage process. This helps to resolve the problem that arises when consecutive repetitive subsequences in the sequence cause errors in DNA storage. We made use of the CLGBO algorithm and the non-adjacent subsequence constraint to construct larger and more highly robust coding sets.

An artificial chromosome for data storage

DNA digital storage provides an alternative for information storage with high density and long-term stability. Here, we report the de novo design and synthesis of an artificial chromosome that encodes two pictures and a video clip. The encoding paradigm utilizing the superposition of sparsified error correction codewords and pseudo-random sequences tolerates base insertions/deletions and is well suited to error-prone nanopore sequencing for data retrieval. The entire 254 kb sequence was 95.27% occupied by encoded data. The Transformation-Associated Recombination method was used in the construction of this chromosome from DNA fragments and necessary autonomous replication sequences. The stability was demonstrated by transmitting the data-carrying chromosome to the 100th generation. This study demonstrates a data storage method using encoded artificial chromosomes via in vivo assembly for write-once and stable replication for multiple retrievals, similar to a compact disc, with potential in economically massive data distribution.

An alternative approach to nucleic acid memory

DNA is a compelling alternative to non-volatile information storage technologies due to its information density, stability, and energy efficiency. Previous studies have used artificially synthesized DNA to store data and automated next-generation sequencing to read it back. Here, we report digital Nucleic Acid Memory (dNAM) for applications that require a limited amount of data to have high information density, redundancy, and copy number. In dNAM, data is encoded by selecting combinations of single-stranded DNA with (1) or without (0) docking-site domains. When self-assembled with scaffold DNA, staple strands form DNA origami breadboards. Information encoded into the breadboards is read by monitoring the binding of fluorescent imager probes using DNA-PAINT super-resolution microscopy. To enhance data retention, a multi-layer error correction scheme that combines fountain and bi-level parity codes is used. As a prototype, fifteen origami encoded with 'Data is in our DNA!\n' are analyzed. Each origami encodes unique data-droplet, index, orientation, and error-correction information. The error-correction algorithms fully recover the message when individual docking sites, or entire origami, are missing. Unlike other approaches to DNA-based data storage, reading dNAM does not require sequencing. As such, it offers an additional path to explore the advantages and disadvantages of DNA as an emerging memory material.

Autonomous Computing Materials

Conventional materials are reaching their limits in computation, sensing, and data storage capabilities, ushered in by the end of Moore's law, myriad sensing applications, and the continuing exponential rise in worldwide data storage demand. Conventional materials are also limited by the controlled environments in which they must operate, their high energy consumption, and their limited capacity to perform simultaneous, integrated sensing, computation, and data storage and retrieval. In contrast, the human brain is capable of multimodal sensing, complex computation, and both short- and long-term data storage simultaneously, with near instantaneous rate of recall, seamless integration, and minimal energy consumption. Motivated by the brain and the need for revolutionary new computing materials, we recently proposed the data-driven materials discovery framework, autonomous computing materials. This framework aims to mimic the brain's capabilities for integrated sensing, computation, and data storage by programming excitonic, phononic, photonic, and dynamic structural nanoscale materials, without attempting to mimic the unknown implementational details of the brain. If realized, such materials would offer transformative opportunities for distributed, multimodal sensing, computation, and data storage in an integrated manner in biological and other nonconventional environments, including interfacing with biological sensors and computers such as the brain itself.

DNA stability: a central design consideration for DNA data storage systems

Data storage in DNA is a rapidly evolving technology that could be a transformative solution for the rising energy, materials, and space needs of modern information storage. Given that the information medium is DNA itself, its stability under different storage and processing conditions will fundamentally impact and constrain design considerations and data system capabilities. Here we analyze the storage conditions, molecular mechanisms, and stabilization strategies influencing DNA stability and pose specific design configurations and scenarios for future systems that best leverage the considerable advantages of DNA storage.

Applications of Discrete Synthetic Macromolecules in Life and Materials Science: Recent and Future Trends

In the last decade, the field of sequence-defined polymers and related ultraprecise, monodisperse synthetic macromolecules has grown exponentially. In the early stage, mainly articles or reviews dedicated to the development of synthetic routes toward their preparation have been published. Nowadays, those synthetic methodologies, combined with the elucidation of the structure-property relationships, allow envisioning many promising applications. Consequently, in the past 3 years, application-oriented papers based on discrete synthetic macromolecules emerged. Hence, material science applications such as macromolecular data storage and encryption, self-assembly of discrete structures and foldamers have been the object of many fascinating studies. Moreover, in the area of life sciences, such structures have also been the focus of numerous research studies. Here, it is aimed to highlight these recent applications and to give the reader a critical overview of the future trends in this area of research.

Novel Modalities in DNA Data Storage

The field of storing information in DNA has expanded exponentially. Most common modalities involve encoding information from bits into synthesized nucleotides, storage in liquid or dry media, and decoding via sequencing. However, limitations to this paradigm include the cost of DNA synthesis and sequencing, along with low throughput. Further unresolved questions include the appropriate media of storage and the scalability of such approaches for commercial viability. In this review, we examine various storage modalities involving the use of DNA from a systems-level perspective. We compare novel methods that draw inspiration from molecular biology techniques that have been devised to overcome the difficulties posed by standard workflows and conceptualize potential applications that can arise from these advances.

Damage and Repair in Informational Poly(N-substituted urethane)s

The degradation and repair of uniform sequence-defined poly(N-substituted urethane)s was studied. Polymers containing an ω-OH end-group and only ethyl carbamate main-chain repeat units rapidly degrade in NaOH solution through an ω→α depolymerization mechanism with no apparent sign of random chain cleavage. The degradation mechanism is not notably affected by the nature of the side-chain N-substituents and took place for all studied sequences. On the other hand, depolymerization is significantly influenced by the molecular structure of the main-chain repeat units. For instance, hexyl carbamate main-chain motifs block unzipping and can therefore be used to control the degradation of specific sequence sections. Interestingly, the partially degraded polymers can also be repaired; for example by using a combination of N,N'-disuccinimidyl carbonate with a secondary amine building-block. Overall, these findings open up interesting new avenues for chain-healing and sequence editing.

Decoding DNA data storage for investment

While DNA's perpetual role in biology and life science is well documented, its burgeoning digital applications are beginning to garner significant interest. As the development of novel technologies requires continuous research, product development, startup creation, and financing, this work provides an overview of each respective area and highlights current trends, challenges, and opportunities. These are supported by numerous interviews with key opinion leaders from across academia, government agencies and the commercial sector, as well as investment data analysis. Our findings illustrate the societal and economic need for technological innovation and disruption in data storage, paving the way for nature's own time-tested, advantageous, and unrivaled solution. We anticipate a significant increase in available investment capital and continuous scientific progress, creating a ripe environment on which DNA data storage-enabling startups can capitalize to bring DNA data storage into daily life.

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Overview on current DNA data storage technologies and commercialization hurdles

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Insights from leading DNA data storage experts and investment financing data

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DNA synthesis remains the biggest challenge in the industry

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Archiving cold data is the low-hanging fruit in DNA data storage

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Upwards trend in investment landscape suggests optimal startup fundraising period

Producing highly complicated materials. Nature does it better

Through the years, mineralogical studies have produced a tremendous amount of data on the atomic arrangement and mineral properties. Quite often, structural analysis has led to elucidate the role played by minor components, giving interesting insights into the physico-chemical conditions of mineral crystallization and allowing the description of unpredictable structures that represented a body of knowledge critical for assessing their technological potentialities. Using such a rich database, containing many basic acquisitions, further steps became appropriate and possible, into the directions of more advanced knowledge frontiers. Some of these frontiers assume the name of modularity, complexity, aperiodicity, and matter organization at not conventional levels, and will be discussed in this review.

DNA Micro-Disks for the Management of DNA-Based Data Storage with Index and Write-Once-Read-Many (WORM) Memory Features

DNA-based data storage has attracted attention because of its higher physical density of the data and longer retention time than those of conventional digital data storage. However, previous DNA-based data storage lacked index features and the data quality of storage after a single access was not preserved, obstructing its industrial use. Here, DNA micro-disks, QR-coded micro-sized disks that harbor data-encoded DNA molecules for the efficient management of DNA-based data storage, are proposed. The two major features that previous DNA-based data-storage studies could not achieve are demonstrated. One feature is accessing data items efficiently by indexing the data-encoded DNA library. Another is achieving write-once-read-many (WORM) memory through the immobilization of DNA molecules on the disk and their enrichment through in situ DNA production. Through these features, the reliability of DNA-based data storage is increased by allowing selective and multiple accession of data-encoded DNA with lower data loss than previous DNA-based data storage methods.

Recent Advances in Biomolecule-Nanomaterial Heterolayer-Based Charge Storage Devices for Bioelectronic Applications

With the acceleration of the Fourth Industrial Revolution, the development of information and communications technology requires innovative information storage devices and processing devices with low power and ultrahigh stability. Accordingly, bioelectronic devices have gained considerable attention as a promising alternative to silicon-based devices because of their various applications, including human-body-attached devices, biomaterial-based computation systems, and biomaterial-nanomaterial hybrid-based charge storage devices. Nanomaterial-based charge storage devices have witnessed considerable development owing to their similarity to conventional charge storage devices and their ease of applicability. The introduction of a biomaterial-to-nanomaterial-based system using a combination of biomolecules and nanostructures provides outstanding electrochemical, electrical, and optical properties that can be applied to the fabrication of charge storage devices. Here, we describe the recent advances in charge storage devices containing a biomolecule and nanoparticle heterolayer including (1) electrical resistive charge storage devices, (2) electrochemical biomemory devices, (3) field-effect transistors, and (4) biomemristors. Progress in biomolecule-nanomaterial heterolayer-based charge storage devices will lead to unprecedented opportunities for the integration of information and communications technology, biotechnology, and nanotechnology for the Fourth Industrial Revolution.

Quantifying molecular bias in DNA data storage

DNA has recently emerged as an attractive medium for archival data storage. Recent work has demonstrated proof-of-principle prototype systems; however, very uneven (biased) sequencing coverage has been reported, which indicates inefficiencies in the storage process. Deviations from the average coverage in the sequence copy distribution can either cause wasteful provisioning in sequencing or excessive number of missing sequences. Here, we use millions of unique sequences from a DNA-based digital data archival system to study the oligonucleotide copy unevenness problem and show that the two paramount sources of bias are the synthesis and amplification (PCR) processes. Based on these findings, we develop a statistical model for each molecular process as well as the overall process. We further use our model to explore the trade-offs between synthesis bias, storage physical density, logical redundancy, and sequencing redundancy, providing insights for engineering efficient, robust DNA data storage systems.

What Is Physical Information?

This paper presents the concept of physical information, and it discusses what physical information is, and how it can be defined. The existence of physical information has been discussed in several studies which recognize that properties of information are characteristic of physical phenomena. That is, information has an objective existence, a lack of meaning, and can be quantified. In addition, these studies recognize how a phenomenon that is denoted as physical information can be expressed as an organization of natural or artificial entities. This paper argues that concepts of (abstract) information that are associated with meaning also depend (to a substantial degree) on physical information.

Functionalized Silicon Electrodes in Electrochemistry

Avoiding the growth of SiO_x has been an enduring task for the use of silicon as an electrode material in dynamic electrochemistry. This is because electrochemical assays become unstable when the SiO_x levels change during measurements. Moreover, the silicon electrode can be completely passivated for electron transfer if a thick layer of insulating SiO_x grows on the surface. As such, the field of silicon electrochemistry was mainly developed by electron-transfer studies in nonaqueous electrolytes and by applications employing SiO_x-passivated silicon-electrodes where no DC currents are required to cross the electrode/electrolyte interface. A solution to this challenge began by functionalizing Si-H electrodes with monolayers based on Si-O-Si linkages. These monolayers have proven very efficient to avoid SiO_x formation but are not stable for a long-term operation in aqueous electrolytes due to hydrolysis. It was only with the development of self-assembled monolayers based on Si-C linkages that a reliable protection against SiO_x formation was achieved, particularly with monolayers based on α,ω-dialkynes. This review discusses in detail how this surface chemistry achieves such protection, the electron-transfer behavior of these monolayer-modified silicon surfaces, and the new opportunities for electrochemical applications in aqueous solution.

Dynamic and scalable DNA-based information storage

The physical architectures of information storage systems often dictate how information is encoded, databases are organized, and files are accessed. Here we show that a simple architecture comprised of a T7 promoter and a single-stranded overhang domain (ss-dsDNA), can unlock dynamic DNA-based information storage with powerful capabilities and advantages. The overhang provides a physical address for accessing specific DNA strands as well as implementing a range of in-storage file operations. It increases theoretical storage densities and capacities by expanding the encodable sequence space and simplifies the computational burden in designing sets of orthogonal file addresses. Meanwhile, the T7 promoter enables repeatable information access by transcribing information from DNA without destroying it. Furthermore, saturation mutagenesis around the T7 promoter and systematic analyses of environmental conditions reveal design criteria that can be used to optimize information access. This simple but powerful ss-dsDNA architecture lays the foundation for information storage with versatile capabilities.

The physical architectures of information storage dictate how data is encoded, organised and accessed. Here the authors use DNA with a single-strand overhang as a physical address to access specific data and do in-storage file operations in a scalable and reusuable manner.

Rapidly sequence-controlled electrosynthesis of organometallic polymers

Single rich-stimuli-responsive organometallic polymers are considered to be the candidate for ultrahigh information storage and anti-counterfeiting security. However, their controllable synthesis has been an unsolved challenge. Here, we report the rapidly sequence-controlled electrosynthesis of organometallic polymers with exquisite insertion of multiple and distinct monomers. Electrosynthesis relies on the use of oxidative and reductive C–C couplings with the respective reaction time of 1 min. Single-monomer-precision propagation does not need protecting and deprotecting steps used in solid-phase synthesis, while enabling the uniform synthesis and sequence-defined possibilities monitored by both UV–vis spectra and cyclic voltammetry. Highly efficient electrosynthesis possessing potentially automated production can incorporate an amount of available metal and ligand species into a single organometallic polymer with complex architectures and functional versatility, which is proposed to have ultrahigh information storage and anti-counterfeiting security with low-cost coding and decoding processes at the single organometallic polymer level.

The controllable synthesis of organometallic polymers that can be used in ultrahigh information storage and anti-counterfeiting security has been an unsolved challenge. Here, the authors show sequence-controlled electrosynthesis of organometallic polymers with exquisite insertion of multiple and distinct monomers.

DNA punch cards for storing data on native DNA sequences via enzymatic nicking

Synthetic DNA-based data storage systems have received significant attention due to the promise of ultrahigh storage density and long-term stability. However, all known platforms suffer from high cost, read-write latency and error-rates that render them noncompetitive with modern storage devices. One means to avoid the above problems is using readily available native DNA. As the sequence content of native DNA is fixed, one can modify the topology instead to encode information. Here, we introduce DNA punch cards, a macromolecular storage mechanism in which data is written in the form of nicks at predetermined positions on the backbone of native double-stranded DNA. The platform accommodates parallel nicking on orthogonal DNA fragments and enzymatic toehold creation that enables single-bit random-access and in-memory computations. We use Pyrococcus furiosus Argonaute to punch files into the PCR products of Escherichia coli genomic DNA and accurately reconstruct the encoded data through high-throughput sequencing and read alignment.

Current synthetic DNA-based data storage systems have high recording costs, read-write latency and error-rates that make them uncompetitive compared to traditional digital storage. The authors use nicks in native DNA to encode data in parallel and create access sites for in-memory computations.