A label-free colorimetric isothermal cascade amplification for the detection of disease-related nucleic acids based on double-hairpin molecular beacon

Highlight
- A new colorimetric assay for K-Ras gene detection was developed based on double-hairpin molecular beacon (DHMB).
- Utilizing this colorimetric scheme, target DNA detection and screening of point mutations were accomplished by the naked eye.
- The colorimetric cascade amplification platform also holds the potential for common non-oligonucleotide target detection.
- The DHMB-based colorimetric strategy is a promising candidate platform for diagnostic applications.

K-Ras mutations at codon 12 play an important role in an early step of carcinogenesis. Here, a label-free colorimetric isothermal cascade amplification for ultrasensitive and specific detection of K-Ras point mutation is developed based on a double-hairpin molecular beacon (DHMB). The biosensor consists of DHMB probe and a primer-incorporated polymerization template (PPT) designed partly complementary to DHMB. In the presence of polymerase, target DNA is designed to trigger strand displacement amplification (SDA) via promote the hybridization of PPT with DHMB and subsequently initiates cascade amplification process with the help of the nicking endonuclease. During the hybridization and enzymatic reaction, G-quadruplex/hemin DNAzymes are generated, catalyzing the oxidation of ABTS2− by H2O2 in the presence of hemin. Utilizing the proposed facile colorimetric scheme, the target DNA can be quantified down to 4 pM with the dynamic response range of 5 orders of magnitude, indicating the substantially improved detection capability. Even more strikingly, point mutation in K-ras gene can be readily observed by the naked eye without the need for the labeling or expensive equipment. Given the high-performance for K-Ras analysis, the enhanced signal transduction capability associated with double-hairpin structure of DHMB provides a novel rout to screen biomarkers, and the descripted colorimetric biosensor seems to hold great promise for diagnostic applications of genetic diseases.

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