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bioRxiv · 10.1101/2025.05.13.653868

Cell shapes decode molecular phenotypes in image-basedspatial proteomics

Le, T.·Leineweber, W. D.·Viana, M. P.·Cesnik, A.·Hansen, J. N.·Ouyang, W.·Rafelski, S. M.·Lundberg, E.
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Abstract

The diversity of cellular and tissue structures can arise from a few basic cell shapes, which undergo various transformations based on biophysical constraints on cytoskeletal organization. While cellular geometry has been linked with selected biological processes such as polarity, signaling or morphogenesis, the orchestration of the whole proteome in association to cell shape is still poorly understood. In this study, using more than 1 million images of single cells stained for 11,998 proteins across 10 cell lines in the Human Protein Atlas database, we performed an integrated analysis of organelle, pathway and single protein levels in association to a 2D cellular shapespace. We found that cell and nuclear shapes across cell lines exist in a shared continuum. We also found that the subcellular organelle topology varies across cell lines, but remains robust within each cell lines shapespace. At the single protein level, we found that cells of different shapes in the same cell cycle phase might be preparing for different fates, and that many non-cell cycle proteins expressed shape-based abundance variation. Using the same coordinate framework defined by shape, we could analyze the distribution shift of protein spatial localization under drug perturbation.

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Le, T., Leineweber, W. D., Viana, M. P., Cesnik, A., Hansen, J. N., Ouyang, W., Rafelski, S. M., Lundberg, E.. 2025-05-16. Cell shapes decode molecular phenotypes in image-basedspatial proteomics. https://doi.org/10.1101/2025.05.13.653868

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