Cited by 82DNA and Biological ComputingAdvanced biosensing and bioanalysis techniquesAlgorithms and Data Compression

An alternative approach to nucleic acid memory

Open access
Dickinson, George D., Mortuza, Golam Md, Clay, William, Piantanida, Luca, Green, Christopher M., Watson, Chad, Hayden, Eric J., Andersen, Tim +4 more·2021·Nature Communications

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.

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  • Information can be stored in the 3D structures of DNA assemblies instead of in the sequence, with readout relying on imaging techniques or single-molecule nanopore measurements.

    “Information can thus be stored in the 3D structures of these assemblies instead of in the sequence, with readout relying on imaging techniques, such as super resolution imaging,22 or using single-molecule nanopore measurements.23,25”
  • A DNA origami breadboard divided into a grid of pixels or an indexed matrix can encode binary information by the presence ("1") or absence ("0") of a docking site for a fluorophore at each location.

    “Another tactic used a DNA origami “breadboard,” which was divided into a grid of pixels or an “indexed matrix of digital information.” Each specific location on the origami represents a bit, with the presence (“1”) or absence (“0”) of a docking site for a fluorophore encoding binary information.22”
  • The DNA origami breadboard tactic requires only femtomoles of material.

    “Unlike DNA sequencing, which requires multiple reads to reach a consensus, this tactic can read 750 origami to reach a 100% probability of full data retrieval, which means that only femtomoles of material are needed.”
  • In the DNA origami breadboard approach, unique data patterns are created by selecting which staple strands within the origami possess data domains.

    “In this example, unique data patterns are created by selecting which staple strands within the origami possess data domains.”
  • The DNA origami breadboard approach uses error-correction algorithms that enable message recovery even when individual docking sites are missing.

    “This approach also uses error-correction algorithms that enable message recovery even when individual docking sites are missing.”

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Research works printed but not linked: 3

  1. [1]Victor, Z. 2018 Semiconductor Synthetic Biology Roadmap. 1–36 10.13140/RG.2.2.34352.40960. (2018). · DOI
  2. [2]ITRS. International Technology Roadmap for Semiconductors, 2015 Results. ITRPV vol. 0 1–37 https://www.semiconductors.org/wp-content/uploads/2018/06/0_2015-ITRS-2.0-Executive-Report-1.pdf. Accessed 1st March 2021. (2016).
  3. [18]Luby, M. LT codes. In Proceedings of the 43rd Annual IEEE Symposium on Foundations of Computer Science (IEEE, 2002) 271–280 (IEEE, 2002).

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Authors
Dickinson, G. D., Mortuza, G. M., Clay, W., Piantanida, L., Green, C. M., Watson, C., Hayden, E. J., Andersen, T., Kuang, W., Graugnard, E., Zadegan, R., & Hughes, W. L.
Affiliations
Boise State University (US)
Corresponding author
Hughes, William L.
Venue
Nature Communications
Published
2021-04-22
Volume
12
Issue
1
Pages
2371-2371
ISSN
2041-1723 (ISSN-L)
OpenAlex
W3157019608
Cited by
82
References
36
Citations by year
2026: 12 · 2025: 19 · 2024: 17 · 2023: 16 · 2022: 13 · 2021: 5
FWCI
4.00
Type
journal article
Language
en
Open access
Locations
  • Nature Communications (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • ScholarWorks (Boise State University) (submittedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Science Foundation (ECCS 1807809)
  • Semiconductor Research Corporation
  • Idaho Global Entrepreneurial Mission and Higher Education Research Council
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › DNA and Biological Computing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced biosensing and bioanalysis techniques
  • Physical Sciences › Computer Science › Artificial Intelligence › Algorithms and Data Compression
Keywords
DNA data storage, DNA origami, DNA-PAINT, fluorescent probe binding, error correction, fountain codes, non-volatile memory, data retention
MeSH terms
Proof of Concept Study, Algorithms, DNA, Single-Stranded, Nucleic Acid Conformation, Information Storage and Retrieval, Nanotechnology, Nanostructures

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