A label-free and enzyme-free ultra-sensitive transcription factors biosensor using DNA-templated copper nanoparticles as fluorescent indicator and hairpin DNA cascade reaction as signal amplifier

Detection and quantification of specific protein with ultralow concentration play a crucial role in biotechnological applications and biomedical diagnostics. In this paper, a label-free and enzyme-free amplified fluorescent biosensor has been developed for transcription factors detection based on AT-rich double-stranded DNA-templated copper nanoparticles (ds DNA/Cu NPs) and hairpin DNA cascade reaction. This strategy was demonstrated by using nuclear factor-kappa B p50 (NF-kappa B p50) and specific recognition sequences as a model case. In this assay, a triplex consists of double-stranded DNA containing NF-kappa B p50 specifically binding sequences and a special design single-stranded DNA (Trigger) which is able to activate the hairpin DNA cascade amplifier (HDCA). In the presence of NF-kappa B p50, the triplex became unstable since the target bound to the recognition sequences with strong affinity. The selective binding event confirmed that the Trigger was successfully released from the triplex and initiated HDCA to yield the product which could effectively template the formation of fluorescent Cu NPs. The experimental results revealed that the advanced strategy was ultra-sensitive for detecting NF-kappa B p50 in the concentration range from 0.1 to 1000 pM with a detection limit of 0.096 pM. In addition, the relative standard deviation was 4.08% in 3 repetitive assays of 500 pM NF-kappa B p50, which indicated that the reproducibility of this strategy was acceptable. Besides desirable sensitivity, the developed biosensor also showed high selectivity, cost-effective, and simplified operations. In addition, the proposed biosensing platform is versatile. By conjugating with various specific recognition units, it could hold considerable potential to sensitive and selective detect various DNA-binding proteins and might find wide applications in biomedical fields. (C) 2016 Published by Elsevier B.V.