Tunable and Modular miRNA Classifier through Indirect Associative Toehold Strand Displacement.

Abstract

The programmability of nucleic acids allows detection devices with complex behaviors to be designed de novo. While highly specific, these high-order circuits are usually sequence constrained, making their adaptability toward biological targets challenging. Here, we devise a new strategy called indirect associative strand displacement to decouple sequence constraints between miRNA inputs and de novo strand displacement circuits. By splitting circuit inputs into their toehold and branch migration regions and controlling their association through a docking strand, we demonstrate how any miRNA sequence can be interfaced with synthetic DNA circuits, including catalytic hairpin assembly and a four-input classifier.