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Updated: Mar 26, 2026

Isolation and Identification of Waterborne Antibiotic-Resistant Bacteria and Molecular Characterization of their Antibiotic Resistance Genes
Published on: March 3, 2023
Probing minority population of antibiotic-resistant bacteria
Tianxun Huang1, Yan Zheng1, Ya Yan1
1The MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, The Key Laboratory for Chemical Biology of Fujian Province, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian 361005, P.R. China.
Abstract:
The evolution and spread of antibiotic-resistant pathogens has become a major threat to public health. Advanced tools are urgently needed to quickly diagnose antibiotic-resistant infections to initiate appropriate treatment. Here we report the development of a highly sensitive flow cytometric method to probe minority population of antibiotic-resistant bacteria via single cell detection. Monoclonal antibody against TEM-1 β-lactamase and Alexa Fluor 488-conjugated secondary antibody were used to selectively label resistant bacteria green, and nucleic acid dye SYTO 62 was used to stain all the bacteria red. A laboratory-built high sensitivity flow cytometer (HSFCM) was applied to simultaneously detect the side scatter and dual-color fluorescence signals of single bacteria. By using E. coli JM109/pUC19 and E. coli JM109 as the model systems for antibiotic-resistant and antibiotic-susceptible bacteria, respectively, as low as 0.1% of antibiotic-resistant bacteria were accurately quantified. By monitoring the dynamic population change of a bacterial culture with the administration of antibiotics, we confirmed that under the antimicrobial pressure, the original low population of antibiotic-resistant bacteria outcompeted susceptible strains and became the dominant population after 5hours of growth. Detection of antibiotic-resistant infection in clinical urine samples was achieved without cultivation, and the bacterial load of susceptible and resistant strains can be faithfully quantified. Overall, the HSFCM-based quantitative method provides a powerful tool for the fundamental studies of antibiotic resistance and holds the potential to provide rapid and precise guidance in clinical therapies.
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