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Organelle dynamics and sequential cell divisions for 200 time points at 44 sec intervals in the early zebrafish brain, 14 hours post fertilization. As seen by adaptive optical lattice light sheet microscopy:

Eric Betzig

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11,952 次观看 • 1 年前 •via X (Twitter)

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#FluorescenceFriday #neuroscience #neurodevelopment Axonal wiring of newly differentiated neurons stochastically labeled by Autobow in the spinal cord of a zebrafish embryo, 48-60 hours post fertilization, as seen by adaptive optical lattice light sheet microscopy

#FluorescenceFriday #neuroscience #neurodevelopment Axonal wiring of newly differentiated neurons stochastically labeled by Autobow in the spinal cord of a zebrafish embryo, 48-60 hours post fertilization, as seen by adaptive optical lattice light sheet microscopy

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Dictyostelia are FAST. Microtubules in clustering Dicty cells, color coded by height above the substrate, at 2 sec intervals for 1430 time points (~48 min). As seen by lattice light sheet microscopy:

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#FluorescenceFriday #cellbiology #bioart A neutrophilic cell migrating through a 3D collagen mesh at 1.3 sec intervals for 5.5 min, as seen by lattice light sheet microscopy.

#FluorescenceFriday #cellbiology #bioart A neutrophilic cell migrating through a 3D collagen mesh at 1.3 sec intervals for 5.5 min, as seen by lattice light sheet microscopy.

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10/ With adaptive optical lattice light sheet microscopy (AO-LLSM), we’ve opened a stunningly beautiful and humblingly complex world of 4D subcellular processes viewed with high definition in living transparent multicellular organisms such as zebrafish.

10/ With adaptive optical lattice light sheet microscopy (AO-LLSM), we’ve opened a stunningly beautiful and humblingly complex world of 4D subcellular processes viewed with high definition in living transparent multicellular organisms such as zebrafish.

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Aurora B kinase (green) distribution during initial cell divisions of a C elegans embryo relative to plasma membranes and nuclei (red), highlighting apical midbody remnants after cytokinesis. As seen by lattice light sheet microscopy. With Bembenek Lab

Aurora B kinase (green) distribution during initial cell divisions of a C elegans embryo relative to plasma membranes and nuclei (red), highlighting apical midbody remnants after cytokinesis. As seen by lattice light sheet microscopy. With Bembenek Lab

Eric Betzig

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#FluorescenceFriday #Science #neuroscience Dendritic branches (green) in the mouse brain, studded with spines ("lollipops"), and myelin sheaths (pink tubes) that surround axons. Contacts between axons and dendrites called synapses facilitate communication between neurons. There are ~100 trillion synapses in the human brain, so collectively humanity has the same order of synapses as the 10^24 stars estimated in the observable universe. As seen by lattice light sheet expansion microscopy.

#FluorescenceFriday #Science #neuroscience Dendritic branches (green) in the mouse brain, studded with spines ("lollipops"), and myelin sheaths (pink tubes) that surround axons. Contacts between axons and dendrites called synapses facilitate communication between neurons. There are ~100 trillion synapses in the human brain, so collectively humanity has the same order of synapses as the 10^24 stars estimated in the observable universe. As seen by lattice light sheet expansion microscopy.

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How does an embryo reliably "compute" its form - "cell by cell" - using only local interactions and mechanics, yet produce a precise global body plan? I’m excited to share our Nature Methods paper "MultiCell: geometric learning in multicellular development", presenting #AIxBiology research led by Haiqian Yang and the result of a great collaboration with Ming Guo, George Roy, Tomer Stern, Anh Nguyen and Dapeng Bi. A long-standing challenge in developmental biology is to predict how thousands of cells collectively self-organize as tissues fold, divide, and rearrange. In MultiCell, we represent a developing embryo as a dual graph that unifies two complementary views of tissue mechanics with single-cell resolution: cells as moving points (granular) and cells as a connected foam (junction network). This lets the model learn dynamics from both geometry and cell–cell connectivity. On whole-embryo 4D light-sheet movies of Drosophila gastrulation (~5,000 cells), our model predicts key cell behaviors and the timing of events, including junction loss, rearrangements, and divisions with high accuracy, at single-cell resolution. Beyond prediction, the same representation supports robust time alignment across embryos and offers interpretable activation maps that highlight the morphogenetic "drivers" of development. The broader goal is a foundation for cell-by-cell forecasting in more complex tissues, and eventually for detecting subtle dynamical signatures of disease. Kudos to the team for this inspiring collaboration with brilliant researchers to push the boundary of AI for biology! Citation: Yang, H., Roy, G., Nguyen, A.Q., Buehler, M.J., et al. MultiCell: geometric learning in multicellular development. Nature Methods (2025), DOI: 10.1038/s41592-025-02983-x Code/data links are in the manuscript.

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