DNA Logic Operation with Nanopore Decoding To Recognize MicroRNA Patterns in Small Cell Lung Cancer

Although DNA computation has traditionally been developed for parallel calculations in molecular analyses, this approach has recently been considered for use in diagnostic or medical applications in living systems. In this study, we propose that the DNA logic operation may be a powerful tool for the recognition of microRNA patterns, which may have applications for the early diagnosis of cancers. We developed a rapid, label-free decoding method for output diagnostic molecules using nanopore measurements. We designed diagnostic DNAs that autonomously recognized two microRNAs, miR-20a and miR-17-5p, and formed a four-way junction structure that was captured in the nanopore, showing long blocking currents. We analyzed the blocking duration based on the central limit theorem and found that four different operations, i.e., (0, 0), (0, 1), (1, 0), and (1, 1), could be discriminated. This pattern recognition method has been differentiated from simple detection methods based on DNA computing and nanopore technologies.