A controllable SERS biosensor for ultrasensitive detection of miRNAs based on porous MOFs and subject-object recognition ability - He, Yi; Liao, Xiangjian; Wu, Haonan; Huang, Jialiang; Zhang, Yi; Peng, Yanyu; Wang, Zhen; Cao, Xin; Wu, Caijun; Luo, Xiaojun (Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy, 2023)
In this work, a simple and sensitive SERS biosensor was constructed for detection of miRNA 21. Here, the porosity of Zr-MOF can pack lots of Raman probe NR which would produce a strong Raman signal. Second, the subject-object recognition ability of CB[7] and NR can provide more accurate Raman signal and stronger Raman intensity. At last, AuNS possess lots of tips which can obviously enhance the Raman intensity for provide sensitivity of SERS biosensor. [Display omitted] •Porosity of Zr-MOF can as a container to pack lots of Raman probe NR to produce a strong Raman signal.•The subject-object recognition ability of CB[7] and NR can provide more accurate Raman signal and stronger Raman intensity.•AuNS possess lots of tips to obviously enhance the Raman intensity for improving sensitivity of SERS biosensor. In this work, a simple and sensitive SERS-based miRNA biosensor was constructed based on porous MOFs nanoparticles and efficient subject-object recognition ability. MOFs as a container can package lots of signal probe neutral red (NR) for the advantages of three dimensional structure and porosity. The partially complementary duplex DNA can as a “lock” to lock up the hole for obtaining a weak Raman signal. In the present of miRNA, miRNA just like a “key” to open the duplex structure with the results of releasing NR. At this time, the released NR can be captured by SERS substrate AuNS@CB[7] for the subject-object recognition ability to produce a strong Raman signal which was positive correlation to target miRNA. By this way, the proposed SERS biosensor can achieve sensitively and selectively detect miRNA with a detection limit of 0.562 fM. This MOF-based SERS biosensor also be hopeful application for clinical diagnostics.