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CRISPR-powered quantitative keyword search engine in DNA data storage

Author

Listed:
  • Jiongyu Zhang

    (University of Connecticut Health Center
    University of Connecticut)

  • Chengyu Hou

    (University of Connecticut Health Center
    University of Connecticut)

  • Changchun Liu

    (University of Connecticut Health Center)

Abstract

Despite the growing interest of archiving information in synthetic DNA to confront data explosion, quantitatively querying the data stored in DNA is still a challenge. Herein, we present Search Enabled by Enzymatic Keyword Recognition (SEEKER), which utilizes CRISPR-Cas12a to rapidly generate visible fluorescence when a DNA target corresponding to the keyword of interest is present. SEEKER achieves quantitative text searching since the growth rate of fluorescence intensity is proportional to keyword frequency. Compatible with SEEKER, we develop non-collision grouping coding, which reduces the size of dictionary and enables lossless compression without disrupting the original order of texts. Using four queries, we correctly identify keywords in 40 files with a background of ~8000 irrelevant terms. Parallel searching with SEEKER can be performed on a 3D-printed microfluidic chip. Overall, SEEKER provides a quantitative approach to conducting parallel searching over the complete content stored in DNA with simple implementation and rapid result generation.

Suggested Citation

  • Jiongyu Zhang & Chengyu Hou & Changchun Liu, 2024. "CRISPR-powered quantitative keyword search engine in DNA data storage," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-46767-x
    DOI: 10.1038/s41467-024-46767-x
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    References listed on IDEAS

    as
    1. Lee Organick & Yuan-Jyue Chen & Siena Dumas Ang & Randolph Lopez & Xiaomeng Liu & Karin Strauss & Luis Ceze, 2020. "Probing the physical limits of reliable DNA data retrieval," Nature Communications, Nature, vol. 11(1), pages 1-7, December.
    2. Callista Bee & Yuan-Jyue Chen & Melissa Queen & David Ward & Xiaomeng Liu & Lee Organick & Georg Seelig & Karin Strauss & Luis Ceze, 2021. "Molecular-level similarity search brings computing to DNA data storage," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    3. Mazhar Adli, 2018. "The CRISPR tool kit for genome editing and beyond," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    4. Xiong Ding & Kun Yin & Ziyue Li & Rajesh V. Lalla & Enrique Ballesteros & Maroun M. Sfeir & Changchun Liu, 2020. "Ultrasensitive and visual detection of SARS-CoV-2 using all-in-one dual CRISPR-Cas12a assay," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    5. Tom van der Valk & Patrícia Pečnerová & David Díez-del-Molino & Anders Bergström & Jonas Oppenheimer & Stefanie Hartmann & Georgios Xenikoudakis & Jessica A. Thomas & Marianne Dehasque & Ekin Sağlıcan, 2021. "Million-year-old DNA sheds light on the genomic history of mammoths," Nature, Nature, vol. 591(7849), pages 265-269, March.
    6. Lee Organick & Yuan-Jyue Chen & Siena Dumas Ang & Randolph Lopez & Xiaomeng Liu & Karin Strauss & Luis Ceze, 2020. "Author Correction: Probing the physical limits of reliable DNA data retrieval," Nature Communications, Nature, vol. 11(1), pages 1-1, December.
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