CONSPECTUS

While the field of DNA computing and molecular programming was engendered in large measure as a curiosity-driven exercise, it has taken on increasing importance for analytical applications. This is in large measure because of the modularity of DNA circuitry, which can serve as a programmable intermediate between inputs and outputs. These qualities may make nucleic acid circuits useful for making decisions relevant to diagnostic applications. This is especially true given that nucleic acid circuits can potentially directly interact with and be triggered by diagnostic nucleic acids and other analytes. Chemists are, by and large, unaware of many of these advances, and this Account provides a means of touching on what might seem to be an arcane field. We begin by explaining nucleic acid amplification reactions that can lead to signal amplification, such as catalytic hairpin assembly (CHA) and the hybridization chain reaction (HCR). In these circuits, a single-stranded input acts on kinetically trapped substrates via exposed toeholds and strand exchange reactions, refolding the substrates and allowing them to interact with one another. As multiple duplexes (CHA) or concatemers of increasing length (HCR) are generated, there are opportunities to couple these outputs to different analytical modalities, including transduction to fluorescent, electrochemical, and colorimetric signals. Because both amplification and transduction are at their root dependent on the programmability of Waston-Crick base pairing, nucleic acid circuits can be much more readily tuned and adapted to new applications than can many other biomolecular amplifiers. As an example, robust methods for real-time monitoring of isothermal amplification reactions have been developed recently. Beyond amplification, nucleic acid circuits can include logic gates and thresholding components that allow them to be used for analysis and decision making. Scalable and complex DNA circuits (seesaw gates) capable of carrying out operations such as taking square roots or implementing neural networks capable of learning have now been constructed. Into the future, we can expect that molecular circuitry will be designed to make decisions on the fly that reconfigure diagnostic devices or lead to new treatment options.