Pomegranate-Bionic Encapsulating Horseradish Peroxidase Using Dopamine Flexible Scaffold-Coated Multishell Porous ZIF-8 To Enhance Immunochromatographic Diagnosis

Nanoparticle-natural enzyme complexes are receiving increasing attention as the promising signal reporters for colorimetric lateral flow immunoassay (LFIA). Nonetheless, it remains a challenge to develop the nanocomplexes with high loading efficiency, catalytic efficiency, and colorimetric signal brightness. Herein, inspired by pomegranate structure, we reported the synthesis of a colorimetric catalytic nanocomplex ((HRP@ZIF-8)3@PDA@HRP), using dopamine flexible scaffold-coated multishell porous zeolitic imidazolate framework-8 (ZIF-8) as a hierarchical scaffold to encapsulate horseradish peroxidase (HRP), and described its potential to promote an ultrasensitive colorimetric LFIA of cardiac troponin I (cTnI). (HRP@ZIF-8)3@PDA@HRP exhibited ultrahigh HRP loading efficiency and catalytic activity due to the epitaxial shell-by-shell overgrowth of porous ZIF-8 scaffold, which provided more cavities for enzyme immobilization and a diffusion path for the catalytic substrate. Furthermore, the polydopamine (PDA) layer on the (HRP@ZIF-8)3 surface both enhanced the colorimetric signal brightness and acted as a flexible scaffold to immobilize HRP, further increasing the amount of enzyme. Following integration with LFIA, the developed platform achieved an ultrasensitive colorimetric test strip assay for cTnI with pre- and postcatalytic naked-eye detection sensitivities of 0.5 ng mL–1 and 0.01 ng mL–1, respectively, which were 4/2- and 200/100-fold higher than gold nanoparticles (AuNPs)/PDA-based LFIA and comparable to chemiluminescence immunoassay. Further, the quantitative testing results of the developed colorimetric LFIA on 57 clinical serum samples agreed well with the clinical data. This work provides ideas for the design of natural enzymes-based colorimetric catalytic nanocomplex to encourage applications for the development of ultrasensitive LFIA for early diseases diagnosis.