Ultra-Multiplexed Imaging Technology Surpasses Fluorescence Limitations

Expected Applications in Spatial Omics and New Drug Development

A next-generation microscopy technology that enables direct observation of single molecules without fluorescent labeling has been realized by a Korean research team. This breakthrough is expected to present a new turning point in ultra-multiplexed molecular analysis and spatial omics research, overcoming the limitations of conventional bioimaging.


The National Research Foundation of Korea announced on March 23 that a joint research team led by Professors Sanghee Shim, Hanyoung Woo, and Seongnam Park of Korea University has developed a 'Raman-based single-molecule microscopy technology' that allows direct observation of individual molecules without relying on fluorescence detection. This research was published in the international journal Nature Communications on January 29.

Overview of Electron Resonance Raman Microscopy. Different molecules can be distinguished through a non-fluorescent Raman probe that suppresses fluorescence and a dual-laser system. In Raman imaging, particles that were indistinguishable in conventional transmission images are clearly separated, and actual single-molecule detection is confirmed through the photobleaching phenomenon of individual molecules. Figures and descriptions by Professor Sanghee Shim, Korea University.

Overview of Electron Resonance Raman Microscopy. Different molecules can be distinguished through a non-fluorescent Raman probe that suppresses fluorescence and a dual-laser system. In Raman imaging, particles that were indistinguishable in conventional transmission images are clearly separated, and actual single-molecule detection is confirmed through the photobleaching phenomenon of individual molecules. Figures and descriptions by Professor Sanghee Shim, Korea University.

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'Non-Fluorescent Single-Molecule Observation' Surpasses Fluorescence Limitations


Technologies that observe the movement of biomolecules at the single-molecule level are considered key tools for identifying disease mechanisms and developing new drugs. However, conventional fluorescence microscopy has limitations due to its broad signal spectrum, which restricts the number of molecules that can be distinguished simultaneously, and requires repetitive labeling and washing processes.


While Raman spectroscopy offers high resolution by utilizing the unique vibrational signals of molecules, its weak signal has made the detection of single molecules challenging. To address this, the research team combined Electron Resonance-Stimulated Raman Scattering (ER-SRS) technology with a non-fluorescent molecular probe (RANMP).


In particular, they established an 'independently tunable dual-laser system' that allows free adjustment of laser wavelengths, and applied molecular probes that emit minimal fluorescence to suppress background noise. As a result, they succeeded in amplifying the Raman signal by more than 200 times compared to existing methods, enabling single-molecule detection without fluorescence.


The team further succeeded in 'dual imaging,' which allows the simultaneous distinction and observation of two different molecules. They discriminated a subtle Raman frequency difference of just 17 cm⁻¹, demonstrating the potential to identify various molecules simultaneously in complex biological environments.


This technology is expected to be highly useful in the field of spatial omics, where it can be applied to simultaneously analyze the positions of genes and proteins within cells.


Professor Sanghee Shim, who led the research, explained, "By utilizing molecular vibrational signals, we overcame the issue of spectral overlap inherent in conventional fluorescence techniques. This study presents new possibilities for ultra-high-resolution imaging."



Going forward, the research team plans to develop Raman probes with enhanced biocompatibility and functional molecular libraries, expanding the technology into precision tracking of disease-related molecules within living cells.


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