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Updated: Mar 12, 2026

Multiplex Detection of Bacteria in Complex Clinical and Environmental Samples using Oligonucleotide-coupled Fluorescent Microspheres
Published on: October 23, 2011
Fingerprinting Fluorescent In Situ Hybridization Enables Multiplexed Identification of Pathogenic Bacteria
Wenxing Li1, Liang Wu1, Chenbin Liu1
1Department of Clinical Laboratory Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, P. R. China.
Abstract:
Fluorescence in situ hybridization (FISH) is a highly specific technique for pathogenic bacteria detection that requires no culturing and provides simultaneous information on pathogenic bacteria abundance, morphology, and spatial localization. However, the limited sensitivity and poor multiplexing capacity of conventional FISH have hindered its broader application. Herein, we proposed a fingerprinting FISH (FinFISH) strategy driven by DNA self-assembly for multiplexed pathogenic bacteria detection. Using respiratory pathogens as representative models, FinFISH employs three distinct fluorophores in combinatorial labeling to generate identifiable fluorescent fingerprints for each species. In this work, FAM, Cy3, and Cy5 were selected as the fluorescent reporters because they represent well-established fluorophore combinations for multicolor imaging and combinatorial encoding, with minimal spectral overlap under standard fluorescence microscopy conditions. This strategy enables pathogen detection far beyond the limitations imposed by fluorescence channel numbers, effectively overcoming the throughput bottleneck of conventional imaging systems while offering high scalability for further expansion. Additionally, a custom-designed enclosed chip featuring multichannel reaction chambers improves parallel sample processing and simplifies experimental operation. Experimental results demonstrated that FinFISH not only performed well in identifying pathogenic bacteria within simulated sputum and urine samples but also proved applicable to clinical samples. Moreover, FinFISH provides additional semiquantitative insights into mixed infections. With future integration of expanded probe design and artificial intelligence (AI)-assisted analysis, FinFISH has the potential to advance clinical pathogenic bacteria diagnostics, microbial colocalization studies, and spatial analysis of intratumoral bacteria.
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