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bioRxiv · 10.64898/2026.01.25.701629

Single-Cell Raman Profiling Enables Rapid Precision Phage Therapy Against Multidrug-Resistant Hypervirulent Klebsiella pneumoniae

Liu, B.·Wang, C.·Zeng, Q.·Wei, M.·Gao, X.·Wan, J.·Feng, J.·Fu, Y. V.
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Abstract

Multidrug-resistant hypervirulent Klebsiella pneumoniae (MDR-hvKP) poses a severe global health threat. Phage therapy is a promising alternative, but requires precise matching of phage to the bacterial strain. Here, we present a proof-of-concept method that integrates single-cell Raman spectroscopy with deep learning to enable rapid and precise selection of lytic phages against MDR-hvKP. By profiling Raman signatures of strains across multiple KL-types (capsule locus types), we trained three deep learning architectures for phage-host matching. Among them, the CNN_MLP-Transformer achieved the best performance (99.7%), slightly outperforming CNN_MLP (99.2%) and CNN_MLP-Attention (99.5%). Validation using 10 hvKP clinical isolates yielded an average phage selection accuracy of 78.3%. These findings demonstrate the feasibility and clinical potential of AI- augmented Raman spectroscopy as a rapid, label-free, precise strategy for guiding phage therapy against MDR-hvKP infections. TeaserAI-guided single-cell Raman profiling enables rapid precision phage selection against multidrug-resistant K. pneumoniae.

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Liu, B., Wang, C., Zeng, Q., Wei, M., Gao, X., Wan, J., Feng, J., Fu, Y. V.. 2026-01-26. Single-Cell Raman Profiling Enables Rapid Precision Phage Therapy Against Multidrug-Resistant Hypervirulent Klebsiella pneumoniae. https://doi.org/10.64898/2026.01.25.701629

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