An alternative approach to nucleic acid memory

George D. Dickinson, Golam Md Mortuza, William Clay, Luca Piantanida, Christopher M. Green, Chad Watson, Eric J. Hayden, Tim Andersen, Wan Kuang, Elton Graugnard, Reza Zadegan and William L. Hughes ()
Additional contact information
George D. Dickinson: Boise State University
Golam Md Mortuza: Boise State University
William Clay: Boise State University
Luca Piantanida: Boise State University
Christopher M. Green: Boise State University
Chad Watson: Boise State University
Eric J. Hayden: Boise State University
Tim Andersen: Boise State University
Wan Kuang: Boise State University
Elton Graugnard: Boise State University
Reza Zadegan: Boise State University
William L. Hughes: Boise State University

Nature Communications, 2021, vol. 12, issue 1, 1-10

Abstract: Abstract 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.

Date: 2021
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DOI: 10.1038/s41467-021-22277-y

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