Cube-track encoded dual-mode ECL/SERS biosensor for ultrasensitive NF-κB p50 detection via transcription-DSN cascade
Pengwei Guo1, Haozhen Ren2, Jiran Pan1
1Guangxi Key Laboratory for Preclinical and Translational Research on Bone and Joint Degenerative Diseases, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi, 533000, China.
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Accurate quantification of trace transcription factors remains challenging because protein-nucleic acid recognition must be translated into a robust signal while resisting matrix interference and instrumental drift. Here, we report a dual-mode ratiometric biosensor for ultrasensitive detection of NF-κB p50 by integrating a CsPbBr3@PDA@AuNPs/MXene (PAM) hybrid transducer with a programmable nucleic-acid cascade and a wireframe DNA cube-track interface. In this design, NF-κB p50 initiates a DNA regulatory circuit that generates amplified nucleic-acid outputs through T7 transcription, which subsequently drive DSN-assisted cleavage of ferrocene (Fc) tags positioned on cube tracks at the electrode surface. This target-programmed interfacial Fc depletion simultaneously restores the PAM electrochemiluminescence (ECL-on) and attenuates the Fc Raman signal (SERS-off), enabling a self-calibrated ratiometric readout. The biosensor exhibits a wide working range from 0.1 to 1000 pM and an estimated limit of detection of 2.3 × 10-3 pM based on the 3σ criterion, further supported by additional low-concentration experimental verification. Selectivity studies against closely related NF-κB family proteins and high-concentration non-specific proteins confirm strong target/non-target discrimination, while repeatability, electrode-to-electrode reproducibility, stability assays, and spike-recovery experiments in diluted MCF-7 cell lysate demonstrate reliable operation in complex samples. This work establishes a general protein-to-nucleic-acid information conversion strategy coupled with cube-track encoded dual-mode transduction, providing a practical route for sensitive and robust transcription-factor analysis and offering potential for further miniaturization and point-of-care applications.


