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Updated: May 5, 2026

Biosensor for Detection of Antibiotic Resistant Staphylococcus Bacteria
Published on: May 8, 2013
Dark-field intelligent detection of V. parahaemolyticus using T4 bacteriophage displaying tail spike proteins and
Huquan Zhu1, Shafiq Ur Rahman1, Ting Pan1
1College of Veterinary Medicine, Institute of Comparative Medicine, Yangzhou University, Yangzhou, 225009, China.
Abstract:
Vibrio parahaemolyticus, a significant seafood-borne pathogen, necessitates rapid and precise detection to guarantee food safety. Herein, we developed a visualization assay method by engineering T4 bacteriophage (T4) to display approximately 870 tail spike proteins (TSPs) derived from a lytic bacteriophage specific to target bacteria, along with about 30 gold nanoparticles (GNPs) of 5 nm at distinct capsid domains. Specifically, we fused the small outer capsid protein (Soc) of T4 with a TSP to obtain a fusion protein Soc-VP-TSP. In parallel, we fused the highly antigenic outer capsid protein (Hoc) with a biotin acceptor peptide (Avi-tag), generating the fusion protein Avi-Hoc. These two fusion proteins were co-assembled onto a T4ΔHS bacteriophage (T4ΔHS) capsid deficient in both native Hoc and Soc proteins, yielding a dual-functionalized phage (T4@TSPs@Avi) that simultaneously displays TSPs and Avi-tags. After covalent biotinylation via BirA biotin-protein ligase, the phages were conjugated to streptavidin-coated GNPs, forming a final detection probe termed T4@TSPs@GNPs. This dual-display T4 allows targeting bacteria to appear as visual golden rod-shaped structures under dark-field microscopy. To enable intelligent and efficient detection, we employed a DenseNet169 model combining saliency-guided region-of-interest extraction, multi-scale feature fusion, and Grad-CAM to accurately distinguish target bacteria from background noise. The entire detection process can be completed within 30 min, achieving a detection limit of 4 CFU/μL and an accuracy that is completely consistent with the gold standard. This integrated strategy provides a powerful and adaptable tool for intelligent pathogen detection in food safety, clinical diagnostics, and environmental monitoring.

