DNA-Based Computing and Data Storage

On-demand access to information encoded in nucleotides lies at the heart of DNA/RNA applications. Here the authors develop a real-time method using nanopore sequencing, SUSTag-ORCtrL, to directly read DNA tags and access stored data without PCR.

Multi-template PCR enables parallel DNA amplification but suffers from sequence-specific biases. Here, the authors develop a 1D-CNN model predicting amplification efficiency directly from the DNA sequence and discover adapter-mediated self-priming as a key cause of uneven amplification during PCR.

High-throughput electrochemical synthesis is ideal for DNA storage, but suffers from low fidelity. Here, authors propose a coding scheme named DNA StairLoop. Experiments demonstrate that it can recover data with high error rates and low sequencing depths, improving the practicality of this technique.

Nanopore sequencing offers rapid DNA readout but suffers from severe insertion/deletion errors. Here, authors devise medium-length DNA fragments using a PNC-LDPC coding scheme, with an efficient cleavage library preparation to quickly recover original data at very low coverages without assembly.

CRISPR-Cas9 has potential as an efficient tool for information retrieval in DNA data storage. Here the authors present a Cas9-based random access and similarity search approach and test on DNA databases, progressing toward simpler, isothermal protocols.

Chip-scale DNA synthesis enables large-scale DNA data storage, but unbiased retrieval remains challenging. Here, authors introduce MPHAC-DIS, an energy-based amplification strategy enabling unbiased, high-accuracy DNA data retrieval, significantly reducing costs and enhancing data accessibility.

Systems combining nucleic acid hybridization with enzymatic catalysis could offer both excellent precision and efficient signal amplification. Here authors develop a system based on “thiol switching”, where specific DNA sequences control enzyme activity – an approach that could have a wide range of applications in biotechnology.

DNA computing systems face challenges in switching functions due to complex molecular redesigns. Here, the authors introduce a base Stacking-Mediated Allostery (SMALL) strategy enabling efficient function switching with minimal architecture changes (1-2 nucleotides), implemented across diverse logic operations and cellular gene regulation patterns.

The predictive design of gene circuits in plants has been challenging and lagging behind other organisms. Here, the authors report a predictive framework for designing synthetic genetic circuits in Arabidopsis and Nicotiana benthamiana in reprograming gene expression and hypersensitive response.

Inducible gene expression systems can be used to control the expression of a gene of interest by means of small molecules. Here the authors present CASwitch, a synthetic gene circuit platform enhancing inducible gene expression systems by reducing leakiness and boosting fold induction, for real world applications like gene therapy vector production and biosensors.

Achieving truly continuous and precise analog calculations using DNA neural networks is challenging. Here, the authors develop a fully analog DNA neural network system called CALCUL, that performs highly accurate weighted-sum operations and can be recycled.

Physical sources of randomness are indispensable for information technology and modern cryptography. In this Perspective, the authors explore entropy as a key concept and the interdisciplinary work that utilizes randomness.

Tracking raw materials is critical for securing global supply chains, but traditional tags lack in traceability and anticounterfeiting. The authors present a DNATag-based system for secure traceability, featuring error tolerance, mobile phone readability, and robust forgery protection.

Adding nanobodies into DNA computing has proven difficult due to there always on state. Here, the authors propose a spatial segregation-based molecular computing strategy to program nanobodies into DNA molecular computation and elucidate the kinetic mechanism of microenvironment-confined DNA molecular computation.

Artificial simulated communication networks use biological and chemical molecules as information carriers to realize information transmission, but their design is challenging. Here, the authors report a DNA nanostructure recognition-based artificial molecular communication network, in which rectangular DNA origami nanostructures serve as nodes and their recognition as edges, and use it to construct various communication network topologies.