Experimental analysis of the basic idea on the transcription-based diagnostic automata controlled by programmed molecules

Abstract

Biomolecular computing using the artificial nucleic acid technology is expected to bring new solutions to various health problems. We focus on the noninvasive transcriptome diagnosis by salivary mRNAs and present the novel concept of transcription-based diagnostic automata that are constructed by programmed DNA modules. The main computational element has a stem shaped promoter region and a pseudo-loop shaped read-only memory region for transcription regulation through the conformation change caused by targets. Our system quantifies targets by transcription of malachite green aptamer sequence triggered by the target recognition. This algorithm makes it possible to realize the cost-effective and sequence-specific real-time target detection. Moreover, in the in-vivo therapeutic use, this transcription-based system can release RNA-aptamer drugs multiply at the transcription stage, different from the digestion-based systems by the restriction enzyme which was proposed previously. We verified the sensitivity, the selectivity and the quantitative stability of the diagnostic automata in basic conditions. Our approach will provide promising applications of autonomous intelligent systems using programmed molecules.