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Stacking effects on mutation detection by T4 DNA ligation within dimeric DNA origami triangle barcodes for single-molecule nanopore analysis

Aboagye-Mensah, D.; Confederat, S.; Alammar, F.; Kailas, L.; Adedeji-Olulana, A. F.; Stopar, A.; Nicholson, A. W.; Thomson, N. H.; Actis, P.; Castronovo, M.

2024-01-09 synthetic biology
10.1101/2024.01.09.574918 bioRxiv
Show abstract

Solid-state nanopores represent an emerging technology for the highly sensitive detection of biomolecular markers, but the detection of DNA point mutations is challenged by the high noise levels associated with solid-state nanopore reading. In contrast, barcoded DNA origami nanostructures can provide unique single-molecule nanopore fingerprints. In this work, we have integrated nanopore-barcoded DNA nanostructures with enzymatic DNA ligation, the latter of which is routinely involved in clinical protocols for DNA mutation detection. We designed two triangular DNA origami variants containing three elongated staples that provide strands extensions on one side that are complementary to a target sequence. Addition of the latter in solution promotes the formation of a DNA triangle dimer. Since T4 DNA ligase repairs a nick in a dsDNA segment only if there is Watson-Crick base-pairing at the nick, the two DNA triangles can be covalently linked only if the DNA sequence bridging the two triangles carries the targeted mutation. We have found striking differences between ligation detection by gel electrophoresis, AFM, and quartz capillary-based nanopores. The stacking interaction between DNA triangles is enhanced by the formation of dimers, and promote the formation of higher order nanostructure, which serve as molecular weight amplification for DNA ligation in gels. The triangle-triangle stacking dynamics presumably involves a clam-like folding mechanism, which is detectable by quartz nanopore analysis, and which hinders ligation by T4 DNA ligase. The results provide the basis for development of rapid, highly sensitive, and affordable high-throughput approaches for profiling genetic variations in point-of-care settings.

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