CRISPR-powered quantitative keyword search engine in DNA data storage

Jiongyu Zhang; Chengyu Hou; Changchun Liu

doi:10.1038/s41467-024-46767-x

CRISPR-powered quantitative keyword search engine in DNA data storage

Nat Commun. 2024 Mar 15;15(1):2376. doi: 10.1038/s41467-024-46767-x.

Authors

Jiongyu Zhang^{1

2}, Chengyu Hou^{1

2}, Changchun Liu³

Affiliations

¹ Department of Biomedical Engineering, University of Connecticut Health Center, Farmington, CT, 06030, USA.
² Department of Biomedical Engineering, University of Connecticut, Storrs, CT, 06269, USA.
³ Department of Biomedical Engineering, University of Connecticut Health Center, Farmington, CT, 06030, USA. chaliu@uchc.edu.

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.

MeSH terms

Data Compression*
Search Engine*