Target-Triggered, Dual Amplification Strategy for Sensitive Electrochemical Detection of a Lymphoma-associated MicroRNA

DNA technology, through rational design of sequence, has led to a series of DNA-based nanomachines and logic circuits that have emerged as nano-implements to achieve autonomous and programmable systems. In particular, DNA circuits have proven to be versatile functional units for integration. In this study, we developed a DNA amplification, circuitry-integrated, electrochemical biosensor for the detection of diffuse, large B-cell lymphoma (DLBCL)-associated microRNA, miR-155. The nucleic acid amplification circuitry in the upstream included the incorporation of a nuclease-assisted amplification reaction as a switch to initiate a one-to-many recognition event for the recycling of target miR-155. The subsequent release of a single strand (discharge A, dA) launched a strand displacement reaction as a secondary amplification process for the multiplied production of inducer (I) (a DNA fragment) in the downstream. This was encountered subsequently with a signal processor, a methylene blue-tagged hairpin, sensitized-electrode, which resulted in signal translation from a DNA recognition event to an electrochemical signal readout for the quantification of miR-155 that was present in the sample. This electrochemical biosensor offers an ultrasensitive detection, with a LOD calculated at 3.57 fM. The precision of this biosensor has an acceptable CV (coefficient of variation) value of 14.92%. The recovery of 89.43 +/- 8.83% obtained from the analysis of a spiked sample was satisfactory, which demonstrated that this biosensor meets the analytical requirements for clinical samples. The distinctive DNA circuitry, in conjunction with the universal, electrochemical sensing platform, provides a promising application for the detection of miR-155 or other disease-related oligonucleotide; this circuitry can be extended further to clinical diagnosis of liquid biopsy samples for patients with mammalian lymphoma. (C) 2017 Elsevier Ltd. All rights reserved.