Signal Compensation Dual-Mode Biosensors Based on Multifunctional Hybrid Nanoflowers for Portable Detection of Listeria monocytogenes

Nanoprobe-based biosensors have emerged as a promising alternative to conventional analytical methods, offering advantages in rapid detection, cost-effectiveness, and no need for professional participation. However, challenges in nanoprobe complexity and instability impede biosensor standardization, frequently resulting in unreliable results. To address these limitations, we present a novel signal-compensated dual-mode biosensor platform utilizing multifunctional hybrid nanoflowers, namely aptamer-sucrase @horseradish peroxidase @nanoflower (Apt-Sucrase@HRP@NFs, NFs), for the detection of Listeria monocytogenes (L.m). Specifically, NFs with capture and reporting capabilities require only a simple and gentle one-pot synthesis, avoiding the complex preparation processes of multifunctional nanoprobes. In addition to HRP and sucrase activity, NFs also exhibit enhanced stability, which contributes to the standardization of biosensing probes. The NFs-based dual-mode biosensing platform integrates smartphone-assisted colorimetric analysis with portable glucose meter (PGM) detection, enabling on-site quantification of L.m in less than 70 min with a detection limit of 4 CFU mL^-1, which ensures both rapidity and reliability for field-deployable pathogen monitoring. Besides, a partitioned trust model is constructed based on complementarity between colorimetric and PGM signals for the evaluation and selection of detection results. Colorimetric signals are prioritized at low concentrations (below 10^2.54 CFU mL^-1) while PGM signals are more reliable at high concentrations (above 10^7.5 CFU mL^-1). The reliability and practicality of this platform were validated through spiked recovery assays of several actual samples. Therefore, this methodology not only demonstrates promising applicability for rapid pathogen screening in food safety monitoring but also provides a new perspective for solving the standardization challenges of biosensors.