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Advancing synthesis-free and enzyme-free rewritable DNA memory through frameshift encoding and nanopore duplex interruption decoding
Journal article   Peer reviewed

Advancing synthesis-free and enzyme-free rewritable DNA memory through frameshift encoding and nanopore duplex interruption decoding

Kai Tian, Sicheng Zhang, Sally Chen, Rugare G Chingarande, Chengrui Hou, Emily Ma, Jarett Ren, Shinghua Ding, Mia Stertzer, Binquan Luan, …
PNAS nexus, Vol.4(9), p.pgaf233
01/09/2025
PMID: 40917905

Abstract

Biological, Health, and Medical Sciences
DNA data storage is a promising alternative to conventional storage due to high density, low energy consumption, durability, and ease of replication. While information can be encoded into DNA via synthesis, high costs and the lack of rewriting capability limit its applications beyond archival storage. Emerging “hard drive” strategies seek to encode data onto universal DNA templates without de novo synthesis, using methods such as DNA nanostructures and base modifications. However, these approaches face challenges including complexity, low data density, enzymatic constraints, and reliance on costly instrumentation. Here, we introduce a DNA memory system based on frameshift encoding, inspired by viral ribosomal frameshifting, to enable rapid, cost-effective, and parallel data writing on a universal DNA template, without synthesis, enzymatic processing, or labeling. Information is encoded as checkpoint frameshifts by annealing microstaples of varying lengths at predefined sites along a long template strand. Data are decoded using MspA nanopore duplex interruption sequencing, which leverages a novel unzipping marker we discovered and frameshift-induced current signatures to resolve individual bits while sequentially unzipping tandem template–microstaple duplexes. Importantly, the duplex structure enables efficient, bit-specific rewriting through toehold-mediated strand displacement. This approach presents a scalable and versatile framework for DNA-based hard drives, with potential applications extending into in-memory computing, encryption, and dynamic biomolecular sensing.
url
https://doi.org/10.1093/pnasnexus/pgaf233View
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