Configuration Analysis of a Lizard Skin-like Pattern Formed by DNA Self-Assembly

Nature manifests diverse and complicated patterns through efficient physical, chemical, and biological processes. One of the approaches to generate complex patterns, as well as simple patterns, is the use of the cellular automata algorithm. However, there are certain limitations to produce such patterns experimentally due to the difficulty of finding candidate programmable building blocks. Here, we demonstrated the feasibility of generating an ocellated lizard skin-like pattern by simulation considering the probabilistic occurrence of cells and constructed the simulation results on DNA lattices via bottom-up self-assembly. To understand the similarity between the simulated pattern (SP) and the observed pattern (OP) of lizard skin, a unique configuration scheme (unit configuration was composed of 7 cells) was conceived. SPs were generated through a computer with a controlling population of gray and black cells in a given pattern. Experimental patterns (EPs) on DNA lattices, consisting of double-crossover (DX) tiles without and with protruding hairpins, were fabricated and verified through atomic force microscopy (AFM). For analyzing the similarity of the patterns, we introduced deviation of the average configuration occurrence for SP and EP with respect to OP, i.e., σα(SO) and σα(EO). The configuration and deviation provide characteristic information of patterns. We recognized that the minimum values of <σα(SO)> and <σα(EO)> occurred when 50% (55%) of black cells in given SPs (DX tiles with hairpins in given EPs) appeared to be most similar to the OP. Our study provides a novel platform for the applicability of DNA molecules to systematically demonstrate other naturally existing complex patterns or processes with ease.