ACS Sens. 2025 Jul 28. doi: 10.1021/acssensors.5c00508. Online ahead of print.
ABSTRACT
Klebsiella pneumoniae (Kpn) is a common opportunistic pathogen, with hypervirulent strains (hvKpn) posing significant risks even to healthy individuals. Traditional clinical diagnostics often use real-time quantitative polymerase chain reaction (PCR) with TaqMan probes, which are costly and unstable due to their reliance on fluorophore and quencher molecules. This study introduces a novel probe using silicon-doped carbon quantum dots (Si-QDs) and single-layer graphene oxides (GOs), forming the Si-QD-probe-GO. This new probe offers excellent selectivity, sensitivity, stability, low photobleaching, and cost-effectiveness. A sensor array targeting khe, peg-344, and iucA genes is developed to detect Kpn and differentiate between classical Kpn (cKpn) and hvKpn. Using a partial least-squares discriminant analysis (PLS-DA) model, the system achieves 100% accuracy in distinguishing hvKpn from cKpn. The study also employs droplet digital PCR (ddPCR) with microfluidic technology to enhance sensitivity and quantification, achieving a detection limit of 5 CFU/mL. In a mouse pneumonia model, the PLS-DA model accurately identifies hvKpn in lung samples. The ddPCR quantification using Si-QD-probe-GO shows strong correlation with traditional culture methods. This research presents a promising ddPCR system for precise detection and virulence identification of Kpn, offering a new direction for clinical diagnostics.
PMID:40720899 | DOI:10.1021/acssensors.5c00508
