No abstract

Engineered molecular circuits that process information in biological systems could address emerging human health and biomanufacturing needs. However, such circuits can be difficult to rationally design and scale. DNA-based strand displacement reactions have demonstrated the largest and most computationally powerful molecular circuits to date but are limited in biological systems due to the difficulty in genetically encoding components. Here, we develop scalable cotranscriptionally encoded RNA strand displacement (ctRSD) circuits that are rationally programmed via base pairing interactions. ctRSD circuits address the limitations of DNA-based strand displacement circuits by isothermally producing circuit components via transcription. We demonstrate circuit programmability in vitro by implementing logic and amplification elements, as well as multilayer cascades. Furthermore, we show that circuit kinetics are accurately predicted by a simple model of coupled transcription and strand displacement, enabling model-driven design. We envision ctRSD circuits will enable the rational design of powerful molecular circuits that operate in biological systems, including living cells.

The use of proteins that bind and catalyze reactions with DNA alongside DNA nanostructures has broadened the functionality of DNA devices. DNA binding proteins have been used to specifically pattern and tune structural properties of DNA nanostructures and polymerases have been employed to directly and indirectly drive structural changes in DNA structures and devices. Despite these advances, undesired and poorly understood interactions between DNA nanostructures and proteins that bind DNA continue to negatively affect the performance and stability of DNA devices used in conjunction with enzymes. A better understanding of these undesired interactions will enable the construction of robust DNA nanostructure-enzyme hybrid systems. Here, we investigate the undesired disassembly of DNA nanotubes in the presence of viral RNA polymerases (RNAPs) under conditions used for in vitro transcription. We show that nanotubes and individual nanotube monomers (tiles) are non-specifically transcribed by T7 RNAP, and that RNA transcripts produced during non-specific transcription disassemble the nanotubes. Disassembly requires a single-stranded overhang on the nanotube tiles where transcripts can bind and initiate disassembly through strand displacement, suggesting that single-stranded domains on other DNA nanostructures could cause unexpected interactions in the presence of viral RNA polymerases.

Crystallization is a ubiquitous means of self-assembly that can organize matter over length scales orders of magnitude larger than those of the monomer units. Yet crystallization is notoriously difficult to control because it is exquisitely sensitive to monomer concentration, which changes as monomers are depleted during growth. Living cells control crystallization using chemical reaction networks that offset depletion by synthesizing or activating monomers to regulate monomer concentration, stabilizing growth conditions even as depletion rates change, and thus reliably yielding desired products. Using DNA nanotubes as a model system, here we show that coupling a generic reversible bimolecular monomer buffering reaction to a crystallization process leads to reliable growth of large, uniformly sized crystals even when crystal growth rates change over time. Buffering could be applied broadly as a simple means to regulate and sustain batch crystallization and could facilitate the self-assembly of complex, hierarchical synthetic structures.

Engineered far-from-equilibrium synthetic chemical networks that pulse or switch states in response to environmental signals could precisely regulate the kinetics of chemical synthesis or self-assembly pathways. Currently, such networks must be extensively tune to compensate for the different activities of and unintended reactions between a network's different chemical elements. Elements with standardized performance would allow rapid construction of networks with designed functions. Here we develop standardized excitable chemical elements, termed genelets, and use them to construct complex in vitro transcriptional networks. We develop a protocol for identifying >15 interchangeable genelet regulatory elements with uniform performance and minimal crosstalk. These elements can be combined to engineer feedforward and feedback modules whose dynamics are predicted by a simple kinetic model. We show modules can be rationally integrated and reorganized into networks that produce tunable temporal pulses and act as multi-state switchable memories. Standardized genelet elements, and the workflow to identify more, should make engineering complex far-from-equilibrium chemical dynamics routine.