High-Performance Electrochemiluminescence Imaging Immunosensor for Adeno-Associated Virus Serotype 8 Detection Based on Nanobody-Functionalized Covalent Organic Frameworks and Au@Rh Catalytic Amplification

Adeno-associated virus serotype 8 (AAV8) is a widely used gene therapy vector with the characteristics of high transduction efficiency and tissue specificity. Reliable detection of AAV8 is crucial for assessing therapeutic efficacy and tracking its in vivo distribution. Herein, we develop a nanobody-based electrochemiluminescence (ECL) imaging immunosensor based on integrating advanced functional materials with spatially resolved signal output for sensitive and visual detection of AAV8. This immunosensor employs a tetraphenylethylene-derived covalent organic framework (TC-COF) as the ECL emitter with the advantages of excellent chemical stability, structural rigidity, and aggregation-induced luminescence. Moreover, the gold-rhodium core-shell bimetallic nanoparticles (Au@Rh) are introduced as the efficient coreaction accelerators to promote the formation of triethylamine (TEA) radicals. Nanobodies serve as the high-affinity and low-steric-hindrance recognition elements with the advantages of enhanced epitope accessibility and stable surface immobilization. Both the Au@Rh and nanobodies contribute to good specificity and high sensitivity. Notably, this ECL immunosensor enables direct visualization of AAV8 binding events, and the pixel-based signal quantification ensures robust calibration and high reproducibility. This ECL immunosensor can achieve a wide linear detection range from 1 × 10⁸ to 5 × 10¹¹ vg/mL, with the limit of detection (LOD) reaching as low as 1 × 10^7.15 vg/mL. To the best of our knowledge, this work reports the first application of AAV8-specific nanobodies in an ECL biosensing platform. This study demonstrates a significant analytical advancement by integrating nanobody technology, COF-based luminescent materials, and catalytic nanoparticles into a robust and broadly applicable sensing platform for virus detection.