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Many cellular processes and functions involve phenotypic changes or biomolecular interactions at the intracellular level. Researchers can exploit knowledge of these phenotypic changes to better elucidate basic cellular biology, profile disease pathology, or identify new drug targets. Classically, cellular phenotypes have been assessed using high-resolution, imagebased microscopy approaches. However, microscopy-based approaches are slow, manual, and time consuming. Recently, phenotypic assessment using flow cytometry has been developed, offering substantially higher throughput. However, conventional flow cytometers only collect data on the average intensity of light signals and can not deeply analyze intracellular
phenotypes with a high degree of spatial resolution. In addition, imaging flow cytometers are unable to sort cells based on intracellular phenotypes at high speed. We have developed a fluorescence-based ghost cytometry (FL-GC) technique that enables both rapid analysis and sorting of cells based on intracellular phenotypes with high spatial resolution. As proof-ofconcept, we demonstrated FL-GC’s ability to detect nuclear translocation, organelle localization, and protein-protein interaction within single cells.