An Adaptive Trimodal Bioanalysis System via Heterogeneous Interface Engineering and Enzyme-Powered Molecular Machines

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Authors: Lin Sun, Wan-Zhen Xie, Yu Ya, Lihui Mao, Yanni Luo, Defen Feng, Jiawen Wu, Ke-Jing Huang, XueCai TAN
Cited by: 6
References: 43

Abstract

This study reports a trimodal biosensing platform centered on an adaptive signal-fusion strategy for the ultrasensitive detection of pathogens, developed through the strategic integration of heterogeneous interface engineering and enzyme-powered molecular machines. The platform is built on a Ni-MOF-on-Co-MOF heterostructure, where precise interface modulation and pore channel engineering significantly enhance the specific surface area and electron-transport efficiency (1.55-fold higher enzyme-loading capacity), complemented by a novel Au@Ni/Co ZIF@PDA with a remarkable 38.1% photothermal conversion efficiency. For the detection mechanism, the system synergistically combines exonuclease III-mediated target cycling with a dual-output toehold-mediated strand displacement-DNA Walker cascade amplification strategy, which achieves exponential signal amplification by releasing double the signal probes per reaction cycle. This integrated design enables electrochemical, colorimetric, and photothermal trimodal output, with exceptional detection limits (LOD, S / N = 3) of 31.4 aM, 1.32 fM, and 1.14 fM respectively, alongside built-in self-verification and correction for enhanced reliability. Practical validation with real samples shows strong agreement with qPCR results, high spiked recovery rates (96.1–103.4%), excellent repeatability, and outstanding stability. Consequently, this trimodal system presents a novel, robust approach for pathogen detection and, via its adaptive intelligent multisignal cross-checking, offers a highly promising technological platform for complex sample analysis in early agricultural disease diagnosis, food safety monitoring, and clinical diagnostics.

Fields of Study & Subjects

Advanced biosensing and bioanalysis techniques Advanced Nanomaterials in Catalysis Biosensors and Analytical Detection

Publication details

Journal / source
Analytical Chemistry
Publisher
American Chemical Society (ACS)
Volume
98
Issue
5
Pages
3983–3997
Publication date
31 January 2026
Language
EN