Construction and configuration analysis of Zelkova serrata lenticel-like patterns generated through DNA algorithmic self-assembly

Abstract

Multiple models and simulations have been proposed and performed to understand the mechanism of the various pattern formations existing in nature. However, the logical implementation of those patterns through efficient building blocks such as nanomaterials and biological molecules is rarely discussed. This study adopts a cellular automata model to generate simulation patterns (SPs) and experimental patterns (EPs) obtained from DNA lattices similar to the discrete horizontal brown-color line-like patterns on the bark of the Zelkova serrata tree, known as lenticels [observation patterns (OPs)]. SPs and EPs are generated through the implementation of six representative rules (i.e., R004, R105, R108, R110, R126, and R218) in three-input/one-output algorithmic logic gates. The EPs obtained through DNA algorithmic self-assembly are visualized by atomic force microscopy. Three different modules (A, B, and C) are introduced to analyze the similarities between the SPs, EPs, and OPs of Zelkova serrata lenticels. Each module has unique configurations with specific orientations allowing the calculation of the deviation of the SPs and the EPs with respect to the OPs within each module. The findings show that both the SP and the EP generated under R105 and R126 and analyzed with module B provide a higher similarity of Zelkova serrata lenticel-like patterns than the other four rules. This study provides a perspective regarding the use of DNA algorithmic self-assembly for the construction of various complex natural patterns.