Programmable Control of Nucleation for Algorithmic Self-assembly. In: Ferretti C, Mauri G, Zandron C, editors. DNA Computing. Berlin: Springer Berlin Heidelberg; 2005. pp. 319-28. [DOI: 10.1007/11493785_28]

Regulating DNA Self-Assembly Dynamics with Controlled Nucleation

Controlling the nucleation step of a self-assembly system is essential for engineering structural complexity and dynamic behaviors. Here, we design a "frame-filling" model system that comprises one type of self-complementary DNA tile and a hosting DNA origami frame to investigate the inherent dynamics of three general nucleation modes in nucleated self-assembly: unseeded, facet, and seeded nucleation. Guided by kinetic simulation, which suggested an optimal temperature range to differentiate the individual nucleation modes, and complemented by single-molecule observations, the transition of tiles from a metastable, monomeric state to a stable, polymerized state through the three nucleation pathways was monitored by Mg²⁺-triggered kinetic measurements. The temperature-dependent kinetics for all three nucleation modes were correlated by a "nucleation-growth" model, which quantified the tendency of nucleation using an empirical nucleation number. Moreover, taking advantage of the temperature dependence of nucleation, tile assembly can be regulated externally by the hosting frame. An ultraviolet (UV)-responsive trigger was integrated into the frame to simultaneously control "when" and "where" nucleation started. Our results reveal the dynamic mechanisms of the distinct nucleation modes in DNA tile-based self-assembly and provide a general strategy for controlling the self-assembly process.

An information-bearing seed for nucleating algorithmic self-assembly

Self-assembly creates natural mineral, chemical, and biological structures of great complexity. Often, the same starting materials have the potential to form an infinite variety of distinct structures; information in a seed molecule can determine which form is grown as well as where and when. These phenomena can be exploited to program the growth of complex supramolecular structures, as demonstrated by the algorithmic self-assembly of DNA tiles. However, the lack of effective seeds has limited the reliability and yield of algorithmic crystals. Here, we present a programmable DNA origami seed that can display up to 32 distinct binding sites and demonstrate the use of seeds to nucleate three types of algorithmic crystals. In the simplest case, the starting materials are a set of tiles that can form crystalline ribbons of any width; the seed directs assembly of a chosen width with >90% yield. Increased structural diversity is obtained by using tiles that copy a binary string from layer to layer; the seed specifies the initial string and triggers growth under near-optimal conditions where the bit copying error rate is <0.2%. Increased structural complexity is achieved by using tiles that generate a binary counting pattern; the seed specifies the initial value for the counter. Self-assembly proceeds in a one-pot annealing reaction involving up to 300 DNA strands containing >17 kb of sequence information. In sum, this work demonstrates how DNA origami seeds enable the easy, high-yield, low-error-rate growth of algorithmic crystals as a route toward programmable bottom-up fabrication.

Analysis of punctures in DNA self-assembly under forward growth

This paper deals with the characterization and analysis of intentionally induced punctures on a DNA self-assembly. Based on forward growth, punctures are utilized to remove errors in DNA tiles from the self-assembly. Initially, a Markov model is proposed by considering different types of punctures under various bonding conditions in the tiles. For different values of on and off rates (as corresponding to the parameters G(se) and G(mc)), it is shown that the proposed models can assess the types of puncture for removing mismatched tiles as errors. Subsequently, a novel model of puncturing is introduced to establish the condition by which a generic aggregate can utilize punctures for error resilience. It is proven that by using the correct puncture(s), errors as frozen mismatched tiles are moved toward the boundaries, thus ensuring the generation of the target assembly and ease in removal of the errors. As an example, the Sierpinski tile set is analyzed based on the proposed models to fully assess the appropriate type of puncture for this pattern. Simulation results are provided as evidence that the proposed models are effective.