To date, various methods-based miRNA detection approaches have been developed. However, although methods-based approaches provide highly sensitive detection in matrices that lack non-target background species, they typically require sample preparation steps to concentrate the target species and mitigate potential inhibitory species for detection applications in complex matrices. Alternatively, sensor-based miRNA detection approaches are emerging as a technique for sample preparation-free real-time sensitive detection of miRNA in complex matrices, such as circulating body fluids. Here, we highlight a sensitive, selective, sample preparation-free sensor-based approach for real-time detection of microRNA in human serum using gold (Au)-coated dynamic piezoelectric cantilever sensors. The sensor-based approach is capable of detecting target <i>let-7a</i> with a dynamic range spanning six orders of magnitude (10 fM – 1 nM) and a limit of detection at less than 10 attomole (~ 4 fM). Serum background had negligible effect on sensitivity relative to results obtained in buffer due to reduction in nonspecific binding caused by continuous sensor vibration. Both hybridization and nonspecific binding reduction were confirmed using fluorescence-based assays to support sensor-based results. The sensor-based method demonstrated excellent selectivity for the microRNA target in comparison with similar microRNA differing by only a single nucleotide (<i>hsa-let-7c</i>) and random microRNA sequences. Au nanoparticle-based amplification of sensor response was investigated and led to one order of magnitude improvement in the detection limit and amplification of sensor response over the entire dynamic range. The cantilever sensor-based microRNA assay provides competitive sensitivity with current microRNA detection methods, as well as has the advantage of requiring no sample preparation even when working with biological samples that contain complex background.

Sample preparation-free real-time sensitive detection of MicroRNA in human serum using cantilever biosensors

254th National Meeting (2017)

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