bioRxivBioengineering
Data-driven multiplexed microtomography of endogenous subcellular dynamics
Y. Jo, H. Cho, W. S. Park, G. Kim, D. Ryu, Y. S. Kim, M. Lee, H. Joo, H. Jo, S. Lee, H.-s. Min, W. D. Heo, Y. Park
Abstract
Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal scales would be an invaluable tool in biomedicine. However, conventional imaging modalities have stark tradeoffs precluding the fulfilment of all functional requirements. Here we propose the refractive index (RI), an intrinsic quantity governing light-matter interaction, as a means for such measurement. We show that major endogenous subcellular structures, which are conventionally accessed via exogenous fluorescence labeling, are encoded in 3D RI tomograms. We decode this information in a data-driven manner, thereby achieving multiplexed microtomography. This approach inherits the advantages of both high-specificity fluorescence imaging and label-free RI imaging. The performance, reliability, and scalability of this technology have been extensively characterized, and its application within single-cell profiling at unprecedented scales has been demonstrated.
- assay: imaging
- research focus: cell type annotation
- research focus: clustering
- approach: deep learning
- approach: statistical model
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