Universal-labeled recombinase polymerase amplification coupled with lateral flow assay for simultaneous detection of Acinetobacter baumannii and its resistance gene
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Updated: Oct 30, 2026

Rapid and Specific Detection of Acinetobacter baumannii Infections Using a Recombinase Polymerase Amplification/Cas12a-based System
Published on: April 25, 2025
Hao Liu1, Zhongzhong Wang1, Yu Zhou2
1Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, China; Beijing Key Laboratory of Environment and Aging, Beijing, China.
Abstract:
Acinetobacter baumannii is a WHO critical-priority pathogen whose clinical threat is dramatically exacerbated by carbapenem-resistant strains (CRAB) harboring bla OXA-23. Simultaneous identification of this pathogen and its resistance determinant under field conditions remains an unmet clinical need. Here we report a universal-labeled recombinase polymerase amplification coupled with lateral flow assay (UL-RALA) for simultaneous, sensitive detection of A. baumannii (recA) and its resistance gene bla OXA-23 from clinical sputum. Chimeric tailed primers enable a single universal labeled primer-probe set to amplify both targets, eliminating target-specific probes and suppressing cross-reactivity. Streptavidin-conjugated quantum dot nano-labels deliver independent FAM/recA and DIG/bla OXA-23 fluorescent readouts without signal crosstalk. Under optimized conditions, the platform achieves a limit of detection of 1 copy/μL for both target nucleic acids within 15 min. The outcomes of the clinical validation serve as a strong proof-of-concept for our proposed platform. This modular, platform provides a promising platform for rapid dual-profiling of CRAB infections at the point of care. The modular architecture and encoding-free probe strategy of this UL-RALA methodology It could also provide a highly adaptable, and scalable blueprint for the rapid, on-site diagnostic screening of other emerging infectious pathogens and their associated antimicrobial resistance profiles.
