Correction: Recent progress in DNA data storage based on high-throughput DNA synthesis.

Surface Functionalized Titanium Nitride Electrode for CMOS Compatible Bioelectronic Devices.

One of the challenges in de novo DNA synthesis is the occurrence of errors. The number of errors associated with synthesis protocols limits the efficiency of obtaining synthetic DNA fragments, both on small and large scales. In this study, we propose a new rapid protocol for the synthesis of DNA fragments using the thermostable endonuclease V from (Tma endonuclease) as an error-correction enzyme. The aim of the research is to develop a one-step error-correction method for de novo gene synthesis. The recombinant Tma endonuclease enzyme was obtained. To evaluate the efficiency of error correction using Tma endonuclease, the synthesis of the mTomato gene was performed using various protocols. The enzyme's efficiency was assessed visually based on the number of fluorescent colonies. To confirm the results, random samples of colonies were selected, and the assembled sequences were sequenced using the Sanger method. It was demonstrated that Tma endonuclease can be used in both the classical three-step and the rapid one-step error-correction protocols without loss of activity. It was also established that, with comparable accuracy of DNA fragment synthesis, the efficiency of Tma endonuclease is similar to that of the commercial enzyme Correctase (ThermoFisher). It was concluded that one-step error correction using endonuclease V accelerates the process of DNA fragment synthesis and error correction. By reducing the number of steps, this protocol is better suited for high-throughput DNA synthesis platforms compared to the classical protocol using non-thermostable enzymes.

This study introduces a robust selective on-chip DNA synthesis platform utilizing an electric field-assisted polymerase chain reaction (E-PCR) system based on a microelectrode array. We demonstrate the use of electric field manipulation for the selective immobilization of DNA and enzyme-mediated single-stranded DNA synthesis, achieving precise spatial control at the microscale. By optimizing electric field patterns, we achieved high-efficiency synthesis and addressed critical challenges in electrochemical stability and DNA integrity. The E-PCR system enables selective DNA synthesis, length-controlled synthesis, and sensitive nucleic acid detection. Our findings provide a scalable foundation for high-throughput enzymatic synthesis, offering significant potential for DNA data storage, synthetic biology, and molecular diagnostics.

A wide range of codecs with vastly different error-correction approaches have been proposed and implemented for DNA data storage to date. However, while many codecs claim to provide superior performance, no studies have systematically benchmarked codec implementations to establish the current state-of-the-art in DNA data storage. In this study, we use standardized error scenarios – both in silico and in vitro – to compare the performance of six representative codecs from the literature. We find synthetic benchmarks commonly used in literature to be unsuitable indicators of codec performance, as our data shows that common experimental benchmarks fail to differentiate codecs under standardized conditions. Instead, we implement a comprehensive benchmark covering the major experimental parameters to assess codec performance under realistic DNA data storage conditions, while establishing important baselines for future codec development. Verifying our results with fair and standardized experiments, we demonstrate data storage at 43 EB g-1 using synthesis by material deposition and 13 EB g-1 using the more error prone electrochemical synthesis, employing only existing codecs from the literature. Besides closing in on the physical limits of DNA data storage, this study thus showcases the maturity of error-correction coding and defines its current state-of-the-art.

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

Handling and storing the immense amounts of data native to the information age is a major challenge in terms of technological sustainability and energy demand. To date, tape storage remains the most widespread method for data archiving, while DNA data storage appears to offer the best data density and long-term stability in the future. However, DNA data storage is still in its infancy primarily due to economic and accessibility challenges. This emphasizes the need for more practical and readily available alternatives. We present a method for data storage utilizing inkjet printable quantum dots on paper with photoluminescence (PL) readout. Our proof of principle study showcases the ability to print and stack multiple bits of data on a single spot by exploiting the unique PL properties of quantum dots. This approach utilizes easily accessible resources, including a consumer-grade printer and paper as the substrate. Additionally, we perform initial stability tests, investigate scalability by controlling emission intensity, and evaluate the potential data density achievable by our approach.

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.

The emerging field of synthetic biology is generating insatiable demands for synthetic genes, which far exceed existing gene synthesis capabilities. This review discusses the current methods of chemical DNA synthesis and gene assembly, as well as the latest engineering tools, technologies and trends which could potentially lead to breakthroughs in the development of accurate, low-cost and high-throughput gene synthesis technology. The capability of generating unlimited supplies of DNA molecules of any sequence or size will transform biomedical research in the near future.

DNA data storage has emerged as a promising information storage technology by encoding information down to base molecules. However, it remains a challenge to structure the DNA data with ease of recording, retrieving, and reading. Here, a primer‐disk‐enabled hierarchical DNA data storage system is introduced, which allows for the multiple immobilizations of DNA molecules and the generation of corresponding QR codes for retrieving. The primer disk is pre‐engineered to present multiple primers, on which encoded DNA molecules with complementary primers can be covalently immobilized on demand via solid‐phase PCR. Each DNA file can be retrieved by inkjet printing a fluorescent QR code. A primer disk with up to 10 primers is used. The results show that different DNA files can be subsequently stored on the disk. One can have readily access to the index via fluorescent QR codes and decode information after sequent imaging, convention, and recognition. To this end, the recorded DNA files can be randomly read via solid‐phase PCR with sufficient copies of collected DNA for up to 20 reads. Together, this work provides a new DNA data storage system with index and record‐many‐read‐many features, paving the way for the practical use of DNA data storage.

In this paper, a new efficient error correcting scheme for DNA archival digital data storage is proposed. We devise a double protection scheme for DNA oligos, aiming to ensure the protection of both information and indexing header data from both symbol flipping and erasure-burst errors, using two different cyclic ternary difference-set codes, which are known to be completely orthogonalisable and very easy to decode using a simple majority-logic decoding algorithm. We show that the proposed scheme is efficient and easily scalable, and provides a coding potential of 1.97 bit per nucleotide, and a reasonable net information density of 0.75 bit/nt under the considered experimental conditions, with relatively a lower decoding complexity and costs compared to other DNA data storage approaches.

DNA promises to be a high density data storage medium, but physical storage poses a challenge. To store large amounts of data, pools must be physically isolated so they can share the same addressing scheme. We propose the storage of dehydrated DNA spots on glass as an approach for scalable DNA data storage. The dried spots can then be retrieved by a water droplet using a digital microfluidic device. Here we show that this storage schema works with varying spot organization, spotted masses of DNA, and droplet retrieval dwell times. In all cases, the majority of the DNA was retrieved and successfully sequenced. We demonstrate that the spots can be densely arranged on a microfluidic device without significant contamination of the retrieval. We also demonstrate that 1 TB of data could be stored in a single spot of DNA and successfully retrieved using this method.

MotivationAs nanopore technology reaches ever higher throughput and accuracy, it becomes an increasingly viable candidate for reading out DNA data storage. Nanopore sequencing offers considerable flexibility by allowing long reads, real-time signal analysis, and the ability to read both DNA and RNA. We need flexible and efficient designs that match nanopore’s capabilities, but relatively few designs have been explored and many have significant inefficiency in read density, error rate, or compute time. To address these problems, we designed a new single-read per-strand decoder that achieves low byte error rates, offers high throughput, scales to long reads, and works well for both DNA and RNA molecules. We achieve these results through a novel soft decoding algorithm that can be effectively parallelized on a GPU. Our faster decoder allows us to study a wider range of system designs.ResultsWe demonstrate our approach on HEDGES, a state-of-the-art DNA-constrained convolutional code. We implement one hard decoder that runs serially and two soft decoders that run on GPUs. Our evaluation for each decoder is applied to the same population of nanopore reads collected from a synthesized library of strands. These same strands are synthesized with a T7 promoter to enable RNA transcription and decoding. Our results show that the hard decoder has a byte error rate over 25%, while the prior state of the art soft decoder can achieve error rates of 2.25%. However, that design also suffers a low throughput of 183 s/read. Our new Alignment Matrix Trellis soft decoder improves throughput by 257× with the trade-off of a higher byte error rate of 3.52% compared to the state of the art. Furthermore, we use the faster speed of our algorithm to explore more design options. We show that read densities of 0.33 bits/base can be achieved, which is 4× larger than prior MSA-based decoders. We also compare RNA to DNA, and find that RNA has 85% as many error-free reads when compared to DNA.Availability and implementationSource code for our soft decoder and data used to generate figures is available publicly in the Github repository https://github.com/dna-storage/hedges-soft-decoder (10.5281/zenodo.11454877). All raw FAST5/FASTQ data are available at 10.5281/zenodo.11985454 and 10.5281/zenodo.12014515.

Synchronization errors, arising from both synthesis and sequencing noise, present a fundamental challenge in DNA-based data storage systems. These errors are often modeled as insertion-deletion-substitution (IDS) channels, for which maximum-likelihood decoding is quite computationally expensive. In this work, we propose a data-driven approach based on neural polar decoders (NPDs) to design decoders with reduced complexity for channels with synchronization errors. The proposed architecture enables decoding over IDS channels with reduced complexity <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</i>(<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">AN</i> log<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i>), where <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</i> is a tunable parameter independent of the channel. NPDs require only sample access to the channel and can be trained without an explicit channel model. Additionally, NPDs provide mutual information (MI) estimates that can be used to optimize input distributions and code design. We demonstrate the effectiveness of NPDs on both synthetic deletion and IDS channels. For deletion channels, we show that NPDs achieve near-optimal decoding performance and accurate MI estimation, with significantly lower complexity than trellis-based decoders. We also provide numerical estimates of the channel capacity for the deletion channel. We extend our evaluation to realistic DNA storage settings, including channels with multiple noisy reads and real-world Nanopore sequencing data. Our results show that NPDs match or surpass the performance of existing methods while using significantly fewer parameters than the state-of-the-art. These findings highlight the promise of NPDs for robust and efficient decoding in DNA data storage systems.

基于 DNA 电化学传导的可重置键盘锁 蔺超 翟伟 范楼珍 李晓宏 * (北京师范大学化学学院 北京 100875) 摘要 选择巯基化并含有 PW17 碱基序列的 DNA 在金电极上自组装, 在 10 μmol/L Pb 2＋ 存在下, Pb 2＋ 诱导自组装的 DNA 形成 Pb 2＋ 稳定的 G-四联体.通过微分脉冲伏安法发现 Pb 2＋ 稳定的 G

SummaryBiology is an analytical and informational science that is becoming increasingly dependent on chemical synthesis. One example is the high‐throughput and low‐cost synthesis of DNA, which is a foundation for the research field of synthetic biology (SB). The aim of SB is to provide biotechnological solutions to health, energy and environmental issues as well as unsustainable manufacturing processes in the frame of naturally existing chemical building blocks. Xenobiology (XB) goes a step further by implementing non‐natural building blocks in living cells. In this context, genetic code engineering respectively enables the re‐design of genes/genomes and proteins/proteomes with non‐canonical nucleic (XNAs) and amino (ncAAs) acids. Besides studying information flow and evolutionary innovation in living systems, XB allows the development of new‐to‐nature therapeutic proteins/peptides, new biocatalysts for potential applications in synthetic organic chemistry and biocontainment strategies for enhanced biosafety. In this perspective, we provide a brief history and evolution of the genetic code in the context of XB. We then discuss the latest efforts and challenges ahead for engineering the genetic code with focus on substitutions and additions of ncAAs as well as standard amino acid reductions. Finally, we present a roadmap for the directed evolution of artificial microbes for emancipating rare sense codons that could be used to introduce novel building blocks. The development of such xenomicroorganisms endowed with a ‘genetic firewall’ will also allow to study and understand the relation between code evolution and horizontal gene transfer.