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Updated: Sep 10, 2025

Biosensor for Detection of Antibiotic Resistant Staphylococcus Bacteria
Published on: May 8, 2013
A bacteriophage protein-driven platform for rapid and precise diagnosis of bacterial pathogens from blood samples
Jinhuan Liu1, Yijue Wang2, Xin Fan2
1National Key Laboratory of Veterinary Public Health and Safety, College of Veterinary Medicine, China Agricultural University, Beijing, 100193, China; Center for Sustainable Antimicrobials, Department of Pharmacy, Sichuan Agricultural University, Chengdu, 611130, China.
Abstract:
The rapid emergence of antibiotic-resistant pathogens underscores the urgent need for fast, accurate, and accessible diagnostics to guide targeted therapy and mitigate resistance. Conventional methods for identifying bacterial infections are slow, labor-intensive, and costly, necessitating alternative approaches. Here, we developed an integrated diagnostic platform that employs bacteriophage-derived receptor-binding proteins (RBPs) and endolysin cell wall-binding domains (CBDs) for rapid bloodstream pathogen detection. Magnetic nanobeads conjugated with RBPs and CBDs selectively captured Klebsiella pneumoniae, Staphylococcus aureus, and Streptococcus pneumoniae directly from blood samples. Captured bacteria were then labeled with mCherry-fused RBPs/CBDs and analyzed via flow cytometry. The platform demonstrated high specificity and broad strain-level recognition within each species, achieving ∼80 % capture efficiency at bacterial loads ≤106 CFU/mL. Analytical sensitivity ranged from 102 to 106 CFU/mL, covering clinically relevant bloodstream infection levels. Importantly, pathogens were accurately identified from the blood of pneumonia-infected mice within ∼40 min, without the need for culture. By combining magnetic separation, species-specific fluorescent labeling, and flow-cytometric quantification into a single streamlined assay, this approach exploits the robust binding properties and stability of phage-derived proteins. It surpasses conventional antibody-based diagnostics in cost-effectiveness, stability, and strain coverage. Furthermore, its modular design facilitates adaptation to additional pathogens and supports future multiplexed detection. In summary, this rapid, scalable, and highly specific diagnostic platform enables timely bloodstream pathogen identification, offering strong potential for clinical and point-of-care applications to improve infection management and reduce inappropriate antibiotic use.
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