DNA Nanostructures Characterized via Dual Nanopore Resensing.

Abstract

DNA nanotechnology uses predictable interactions of nucleic acids to precisely engineer complex nanostructures. Characterizing these self-assembled structures at the single-structure level is crucial for validating their design and functionality. Nanopore sensing is a promising technique for this purpose as it is label-free, solution-based, and high-throughput. Here, we present a device that incorporates dynamic feedback to control the translocation of DNA origami structures through and between two nanopores. We observe multiple translocations of the same structure through the two distinct nanopores as well as measure its time-of-flight between the pores. We use machine learning classification methods in tandem with classical analysis of dwell-time/blockade distributions to analyze the complex multitranslocation events generated by different nanostructures. With this approach, we demonstrate the ability to distinguish DNA nanostructures of different lengths and/or small structural differences, all of which are difficult to detect using conventional, single-nanopore sensing. In addition, we develop a finite element diffusion model of the time-of-flight process and estimate nanostructure size. This work establishes the dual nanopore device as a powerful tool for DNA nanostructure characterization.