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

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.

Hierarchical Mechanical Transduction of Precision-Engineered DNA Hydrogels with Sacrificial Bonds

Engineering the response to external signals in mechanically switchable hydrogels is important to promote smart materials applications. However, comparably little attention has focused on embedded precision mechanisms for autonomous nonlinear response in mechanical profiles in hydrogels, and we lack understanding of how the behavior from the molecular scale transduces to the macroscale. Here, we design a nonlinear stress-strain response into hydrogels by engineering sacrificial DNA hairpin loops into model network hydrogels formed from star-shaped building blocks. We characterize the force-extension response of single DNA hairpins and are able to describe how the specific topology influences the nonlinear mechanical behavior at different length scales. For this purpose, we utilize force spectroscopy as well as microscopic and macroscopic deformation tests. This study contributes to a better understanding of designing nonlinear strain-adaptive features into hydrogel materials.

Enzymatic synthesis and nanopore sequencing of 12-letter supernumerary DNA

The 4-letter DNA alphabet (A, T, G, C) as found in Nature is an elegant, yet non-exhaustive solution to the problem of storage, transfer, and evolution of biological information. Here, we report on strategies for both writing and reading DNA with expanded alphabets composed of up to 12 letters (A, T, G, C, B, S, P, Z, X, K, J, V). For writing, we devise an enzymatic strategy for inserting a singular, orthogonal xenonucleic acid (XNA) base pair into standard DNA sequences using 2'-deoxy-xenonucleoside triphosphates as substrates. Integrating this strategy with combinatorial oligos generated on a chip, we construct libraries containing single XNA bases for parameterizing kmer basecalling models for commercially available nanopore sequencing. These elementary steps are combined to synthesize and sequence DNA containing 12 letters - the upper limit of what is accessible within the electroneutral, canonical base pairing framework. By introducing low-barrier synthesis and sequencing strategies, this work overcomes previous obstacles paving the way for making expanded alphabets widely accessible.

Towards long double-stranded chains and robust DNA-based data storage using the random code system

DNA has become a popular choice for next-generation storage media due to its high storage density and stability. As the storage medium of life's information, DNA has significant storage capacity and low-cost, low-power replication and transcription capabilities. However, utilizing long double-stranded DNA for storage can introduce unstable factors that make it difficult to meet the constraints of biological systems. To address this challenge, we have designed a highly robust coding scheme called the "random code system," inspired by the idea of fountain codes. The random code system includes the establishment of a random matrix, Gaussian preprocessing, and random equilibrium. Compared to Luby transform codes (LT codes), random code (RC) has better robustness and recovery ability of lost information. In biological experiments, we successfully stored 29,390 bits of data in 25,700 bp chains, achieving a storage density of 1.78 bits per nucleotide. These results demonstrate the potential for using long double-stranded DNA and the random code system for robust DNA-based data storage.

DNA Data Storage

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

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

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

GCNSA: DNA storage encoding with a graph convolutional network and self-attention

DNA Encoding, as a key step in DNA storage, plays an important role in reading and writing accuracy and the storage error rate. However, currently, the encoding efficiency is not high enough and the encoding speed is not fast enough, which limits the performance of DNA storage systems. In this work, a DNA storage encoding system with a graph convolutional network and self-attention (GCNSA) is proposed. The experimental results show that DNA storage code constructed by GCNSA increases by 14.4% on average under the basic constraints, and by 5%-40% under other constraints. The increase of DNA storage codes effectively improves the storage density of 0.7-2.2% in the DNA storage system. The GCNSA predicted more DNA storage codes in less time while ensuring the quality of codes, which lays a foundation for higher read and write efficiency in DNA storage.

An Engineered OmpG Nanopore with Displayed Peptide Motifs for Single-Molecule Multiplex Protein Detection

Molecular detection via nanopore, achieved by monitoring changes in ionic current arising from analyte interaction with the sensor pore, is a promising technology for multiplex sensing development. Outer Membrane Protein G (OmpG), a monomeric porin possessing seven functionalizable loops, has been reported as an effective sensing platform for selective protein detection. Using flow cytometry to screen unfavorable constructs, we identified two OmpG nanopores with unique peptide motifs displayed in either loop 3 or 6, which also exhibited distinct analyte signals in single-channel current recordings. We exploited these motif-displaying loops concurrently to facilitate single-molecule multiplex protein detection in a mixture. We additionally report a strategy to increase sensor sensitivity via avidity motif display. These sensing schemes may be expanded to more sophisticated designs utilizing additional loops to increase multiplicity and sensitivity.

Emerging Approaches to DNA Data Storage: Challenges and Prospects

With the total amount of worldwide data skyrocketing, the global data storage demand is predicted to grow to 1.75 × 10¹⁴ GB by 2025. Traditional storage methods have difficulties keeping pace given that current storage media have a maximum density of 10³ GB/mm³. As such, data production will far exceed the capacity of currently available storage methods. The costs of maintaining and transferring data, as well as the limited lifespans and significant data losses associated with current technologies also demand advanced solutions for information storage. Nature offers a powerful alternative through the storage of information that defines living organisms in unique orders of four bases (A, T, C, G) located in molecules called deoxyribonucleic acid (DNA). DNA molecules as information carriers have many advantages over traditional storage media. Their high storage density, potentially low maintenance cost, ease of synthesis, and chemical modification make them an ideal alternative for information storage. To this end, rapid progress has been made over the past decade by exploiting user-defined DNA materials to encode information. In this review, we discuss the most recent advances of DNA-based data storage with a major focus on the challenges that remain in this promising field, including the current intrinsic low speed in data writing and reading and the high cost per byte stored. Alternatively, data storage relying on DNA nanostructures (as opposed to DNA sequence) as well as on other combinations of nanomaterials and biomolecules are proposed with promising technological and economic advantages. In summarizing the advances that have been made and underlining the challenges that remain, we provide a roadmap for the ongoing research in this rapidly growing field, which will enable the development of technological solutions to the global demand for superior storage methodologies.

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

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

A nanopore interface for higher bandwidth DNA computing

DNA has emerged as a powerful substrate for programming information processing machines at the nanoscale. Among the DNA computing primitives used today, DNA strand displacement (DSD) is arguably the most popular, with DSD-based circuit applications ranging from disease diagnostics to molecular artificial neural networks. The outputs of DSD circuits are generally read using fluorescence spectroscopy. However, due to the spectral overlap of typical small-molecule fluorescent reporters, the number of unique outputs that can be detected in parallel is limited, requiring complex optical setups or spatial isolation of reactions to make output bandwidths scalable. Here, we present a multiplexable sequencing-free readout method that enables real-time, kinetic measurement of DSD circuit activity through highly parallel, direct detection of barcoded output strands using nanopore sensor array technology (Oxford Nanopore Technologies’ MinION device). These results increase DSD output bandwidth by an order of magnitude over what is currently feasible with fluorescence spectroscopy.