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Fast segmentation and multiplexing imaging of organelles in live cells

Author

Listed:
  • Karl Zhanghao

    (Peking University
    Eastern Institute of Technology)

  • Meiqi Li

    (Peking University
    Peking University)

  • Xingye Chen

    (Tsinghua University)

  • Wenhui Liu

    (Tsinghua University)

  • Tianling Li

    (China Agricultural University)

  • Yiming Wang

    (Peking University)

  • Fei Su

    (University of Technology Sydney)

  • Zihan Wu

    (Southern University of Science and Technology)

  • Chunyan Shan

    (Peking University)

  • Jiamin Wu

    (Tsinghua University)

  • Yan Zhang

    (Peking University)

  • Jingyan Fu

    (China Agricultural University)

  • Peng Xi

    (Peking University
    Southern University of Science and Technology
    Peking University)

  • Dayong Jin

    (Eastern Institute of Technology
    University of Technology Sydney
    Southern University of Science and Technology)

Abstract

Studying organelles’ interactome at system level requires simultaneous observation of subcellular compartments and tracking their dynamics. Conventional multicolor approaches rely on specific fluorescence labeling, where the number of resolvable colors is far less than the types of organelles. Here, we use a lipid-specific dye to stain all the membrane-associated organelles and spinning-disk microscopes with an extended resolution of ~143 nm for high spatiotemporal acquisition. Due to the chromatic polarity sensitivity, high-resolution ratiometric images well reflect the heterogeneity of organelles. With deep convolutional neuronal networks, we successfully segmented up to 15 subcellular structures using one laser excitation. We further show that transfer learning can predict both 3D and 2D datasets from different microscopes, different cell types, and even complex systems of living tissues. We succeeded in resolving the 3D anatomic structure of live cells at different mitotic phases and tracking the fast dynamic interactions among six intracellular compartments with high robustness.

Suggested Citation

  • Karl Zhanghao & Meiqi Li & Xingye Chen & Wenhui Liu & Tianling Li & Yiming Wang & Fei Su & Zihan Wu & Chunyan Shan & Jiamin Wu & Yan Zhang & Jingyan Fu & Peng Xi & Dayong Jin, 2025. "Fast segmentation and multiplexing imaging of organelles in live cells," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-57877-5
    DOI: 10.1038/s41467-025-57877-5
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    References listed on IDEAS

    as
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