Bench-Top Fabrication of Single-Molecule Nanoarrays by DNA Origami Placement

Large-scale nanoarrays of single biomolecules enable high-throughput assays while unmasking the underlying heterogeneity within ensemble populations. Until recently, creating such grids which combine the advantages of micro-arrays and single-molecule experiments (SMEs) has been particularly challenging due to the mismatch between the size of these molecules and the resolution of top-down fabrication techniques. DNA origami placement (DOP) combines two powerful techniques to address this issue: (i) DNA origami, which provides a similar to 100 nm self-assembled template for single-molecule organization with 5 nm resolution and (ii) top-down lithography, which patterns these DNA nanostructures, transforming them into functional nanodevices via large-scale integration with arbitrary substrates. Presently, this technique relies on state-of-the-art infrastructure and highly trained personnel, making it prohibitively expensive for researchers. Here, we introduce a cleanroom-free, $1 benchtop technique to create meso-to-macro-scale DNA origami nanoarrays using self-assembled colloidal nanoparticles, thereby circumventing the need for top-down fabrication. We report a maximum yield of 74%, 2-fold higher than the statistical limit of 37% imposed on non-specific molecular loading alternatives. Furthermore, we provide a proof-of-principle for the ability of this nanoarray platform to transform traditionally low-throughput, stochastic, single-molecule assays into high-throughput, deterministic ones, without compromising data quality. Our approach has the potential to democratize single-molecule nanoarrays and demonstrates their utility as a tool for biophysical assays and diagnostics.

Automated summary

A new benchtop technique has been introduced to create DNA origami nanoarrays using self-assembled colloidal nanoparticles, bypassing the need for traditional top-down fabrication. This approach offers a higher yield and the ability to convert traditional low-throughput, stochastic single-molecule assays into high-throughput, deterministic ones without compromising data quality.