An allosteric DNAzyme-Based modular system for dynamic computation and sensitive MicroRNA detection

Abstract

Introduction Circulating microRNAs (miRNAs) are widely studied as biomarkers for early diagnosis and disease follow-up, but their analysis is still limited by low abundance, short length, and high sequence similarity among miRNA family members. DNAzymes and entropy-driven catalysis (EDC) provide useful tools for nucleic acid sensing without exogenous protein enzymes. However, in many existing designs, signal amplification and molecular computation are treated as separate processes, and the amplified target signal is not readily converted into inputs for downstream logic circuits. To address this issue, we designed an allosterically regulated DNAzyme platform in which miRNA sensing and molecular computation are constructed from compatible nucleic acid modules. Methods In the computing unit, controlled activation of DNAzymes was used to implement co-activated AND logic, thresholding, and subtraction. These gates were then connected through orthogonal sequence domains to form an integrated logic circuit capable of cascaded signal processing. In the sensing unit, an EDC reaction was coupled with DNAzyme-mediated cleavage to establish a self-feedback amplification pathway. First, the target miRNA initiates a strand displacement reaction to release an active DNAzyme. Subsequently, this DNAzyme cleaves its substrate to generate an initial fluorescence output and simultaneously release a secondary trigger for downstream signal amplification. Results Using miRNA-10b as a model target, the biosensor operated under isothermal conditions without exogenous protein enzymes and showed a linear response from 50 pM to 5 nM, with a detection limit of 30 pM. The assay also distinguished miRNA-10b from single-base mismatched sequences and non-target miRNAs. Discussion This work links EDC-based amplification with allosteric DNAzyme computation, offering a programmable strategy for nucleic acid systems that combine biomarker recognition with molecular information processing.