Nucleic Acid Databases and Molecular-Scale Computing

Song, Xin; Reif, John

doi:10.1021/acsnano.9b02562

Cited by 73DNA and Biological ComputingAdvanced biosensing and bioanalysis techniquesAlgorithms and Data Compression

Nucleic Acid Databases and Molecular-Scale Computing

Song, Xin, Reif, John·2019·ACS Nano

DOI 10.1021/acsnano.9b02562

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Abstract

DNA outperforms most conventional storage media in terms of information retention time, physical density, and volumetric coding capacity. Advances in synthesis and sequencing technologies have enabled implementations of large synthetic DNA databases with impressive storage capacity and reliable data recovery. Several robust DNA storage architectures featuring random access, error correction, and content rewritability have been constructed with the potential for scalability and cost reduction. We survey these recent achievements and discuss alternative routes for overcoming the hurdles of engineering practical DNA storage systems. We also review recent exciting work on in vivo DNA memory including intracellular recorders constructed by programmable genome editing tools. Besides information storage, DNA could serve as a versatile molecular computing substrate. We highlight several state-of-the-art DNA computing techniques such as strand displacement, localized hybridization chain reactions, and enzymatic reaction networks. We summarize how these simple primitives have facilitated rational designs and implementations of in vitro DNA reaction networks that emulate digital/analog circuits, artificial neural networks, or nonlinear dynamic systems. We envision these modular primitives could be strategically adapted for sophisticated database operations and massively parallel computations on DNA databases. We also highlight in vivo DNA computing modules such as CRISPR logic gates for building scalable genetic circuits in living cells. To conclude, we discuss various implications and challenges of DNA-based storage and computing, and we particularly encourage innovative work on bridging these two areas of research to further explore molecular parallelism and near-data processing. Such integrated molecular systems could lead to far-reaching applications in biocomputing, security, and medicine.

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The dynamic nature of DNA nanostructure assemblies can be exploited to perform data operations, allowing DNA data storage to integrate directly into DNA computation.
“Moreover, the dynamic nature of these assemblies can be exploited to perform data operations,13,27 which allows DNA data storage to integrate directly into the field of DNA computation.”
From Emerging Approaches to DNA Data Storage: Challenges and Prospects (2022) · cites this paper as [13]

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Authors: Song, X., & Reif, J.
Affiliations: Duke University (US)
Corresponding author: Song, Xin
ORCID: Song, Xin
Reif, John
Venue: ACS Nano
Publisher: American Chemical Society (ACS)
Published: 2019-05-22
Volume: 13
Issue: 6
Pages: 6256-6268
ISSN: 1936-0851 (ISSN-L)
1936-086X
DOI: 10.1021/acsnano.9b02562
OpenAlex: W2946512629
Cited by: 73
References: 105
Citations by year: 2026: 2 · 2025: 7 · 2024: 13 · 2023: 8 · 2022: 10 · 2021: 21 · 2020: 10 · 2019: 2
FWCI: 0.95
Type: journal article
Language: en
Open access: closed
Licence: doi.org/10.15223/policy-029 (stm-asf)
doi.org/10.15223/policy-037 (stm-asf)
doi.org/10.15223/policy-045 (stm-asf)
Locations: ACS Nano (publishedVersion)
PubMed (publishedVersion)
Funders: Division of Computing and Communication Foundations (CCF-1617791)
Division of Graduate Education (DGE-1545220)
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, molecular computing, strand displacement, enzymatic reaction networks, synthetic gene circuits, genome editing, error correction, artificial neural networks, nonlinear dynamical systems, near-data processing, biocomputing
MeSH terms: Animals, DNA, Humans, Sequence Analysis, DNA, Databases, Nucleic Acid, Computers, Molecular, Synthetic Biology

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