Search for: All records

Living cells regulate the dynamics of developmental events through interconnected signaling systems that activate and deactivate inert precursors. This suggests that similarly, synthetic biomaterials could be designed to develop over time by using chemical reaction networks to regulate the availability of assembling components. Here we demonstrate how the sequential activation or deactivation of distinct DNA building blocks can be modularly coordinated to form distinct populations of self-assembling polymers using a transcriptional signaling cascade of synthetic genes. Our building blocks are DNA tiles that polymerize into nanotubes, and whose assembly can be controlled by RNA molecules produced by synthetic genes that target the tile interaction domains. To achieve different RNA production rates, we use a strategy based on promoter “nicking” and strand displacement. By changing the way the genes are cascaded and the RNA levels, we demonstrate that we can obtain spatially and temporally different outcomes in nanotube assembly, including random DNA polymers, block polymers, and as well as distinct autonomous formation and dissolution of distinct polymer populations. Our work demonstrates a way to construct autonomous supramolecular materials whose properties depend on the timing of molecular instructions for self-assembly, and can be immediately extended to a variety of other nucleic acid circuits and assemblies. 

Abstract We present a strategy to control dynamically the loading and release of molecular ligands from synthetic nucleic acid receptors using in vitro transcription. We demonstrate this by engineering three model synthetic DNA‐based receptors: a triplex‐forming DNA complex, an ATP‐binding aptamer, and a hairpin strand, whose ability to bind their specific ligands can be cotranscriptionally regulated (activated or inhibited) through specific RNA molecules produced by rationally designed synthetic genes. The kinetics of our DNA sensors and their genetically generated inputs can be captured using differential equation models, corroborating the predictability of the approach used. This approach shows that highly programmable nucleic acid receptors can be controlled with molecular instructions provided by dynamic transcriptional systems, illustrating their promise in the context of coupling DNA nanotechnology with biological signaling.