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We report quantitative label-free imaging with phase and polarization (QLIPP) for simultaneous measurement of density, anisotropy, and orientation of structures in unlabeled live cells and tissue slices. We combine QLIPP with deep neural networks to predict fluorescence images of diverse cell and tissue structures. QLIPP images reveal anatomical regions and axon tract orientation in prenatal human brain tissue sections that are not visible using brightfield imaging. We report a variant of U-Net architecture, multi-channel 2.5D U-Net, for computationally efficient prediction of fluorescence images in three dimensions and over large fields of view. Further, we develop data normalization methods for accurate prediction of myelin distribution over large brain regions. We show that experimental defects in labeling the human tissue can be rescued with quantitative label-free imaging and neural network model. We anticipate that the proposed method will enable new studies of architectural order at spatial scales ranging from organelles to tissue. Microscopy is central to biological research and has enabled scientist to study the structure and dynamics of cells and their components within. Often, fluorescent dyes or trackers are used that can be detected under the microscope. However, this procedure can sometimes interfere with the biological processes being studied. Now, Guo, Yeh, Folkesson et al. have developed a new approach to examine structures within tissues and cells without the need for a fluorescent label. The technique, called QLIPP, uses the phase and polarization of the light passing through the sample to get information about its makeup. A computational model was used to decode the characteristics of the light and to provide information about the density and orientation of molecules in live cells and brain tissue samples of mice and human. This way, Guo et al. were able to reveal details that conventional microscopy would have missed. Then, a type of machine learning, known as ‘deep learning’, was used to translate the density and orientation images into fluorescence images, which enabled the researchers to predict specific structures in human brain tissue sections. QLIPP can be added as a module to a microscope and its software is available open source. Guo et al. hope that this approach can be used across many fields of biology, for example, to map the connectivity of nerve cells in the human brain or to identify how cells respond to infection. However, further work in automating other aspects, such as sample preparation and analysis, will be needed to realize the full benefits.

At each cell division, nanometer-scale components self-organize to build a micron-scale spindle. In mammalian spindles, microtubule bundles called kinetochore-fibers attach to chromosomes and focus into spindle poles. Despite evidence suggesting that poles can set spindle length, their role remains poorly understood. In fact, many species do not have spindle poles. Here, we probe the pole’s contribution to mammalian spindle length, dynamics, and function by inhibiting dynein to generate spindles whose kinetochore-fibers do not focus into poles, yet maintain a metaphase steady-state length. We find that unfocused kinetochore-fibers have a mean length indistinguishable from control, but a broader length distribution, and reduced length coordination between sisters and neighbors. Further, we show that unfocused kinetochore-fibers, like control, can grow back to their steady-state length if acutely shortened by drug treatment or laser ablation: they recover their length by tuning their end dynamics, albeit slower due to their reduced baseline dynamics. Thus, kinetochore-fiber dynamics are regulated by their length, not just pole-focusing forces. Finally, we show that spindles with unfocused kinetochore-fibers can segregate chromosomes but fail to correctly do so. We propose that mammalian spindle length emerges locally from individual k-fibers while spindle poles globally coordinate k-fibers across space and time.

The cell cycle, over which cells grow and divide, is a fundamental process of life. Its dysregulation has devastating consequences, including cancer 1 – 3 . The cell cycle is driven by precise regulation of proteins in time and space, which creates variability between individual proliferating cells. To our knowledge, no systematic investigations of such cell-to-cell proteomic variability exist. Here we present a comprehensive, spatiotemporal map of human proteomic heterogeneity by integrating proteomics at subcellular resolution with single-cell transcriptomics and precise temporal measurements of individual cells in the cell cycle. We show that around one-fifth of the human proteome displays cell-to-cell variability, identify hundreds of proteins with previously unknown associations with mitosis and the cell cycle, and provide evidence that several of these proteins have oncogenic functions. Our results show that cell cycle progression explains less than half of all cell-to-cell variability, and that most cycling proteins are regulated post-translationally, rather than by transcriptomic cycling. These proteins are disproportionately phosphorylated by kinases that regulate cell fate, whereas non-cycling proteins that vary between cells are more likely to be modified by kinases that regulate metabolism. This spatially resolved proteomic map of the cell cycle is integrated into the Human Protein Atlas and will serve as a resource for accelerating molecular studies of the human cell cycle and cell proliferation. Spatial and temporal variations among individual human cell proteomes are comprehensively mapped across the cell cycle using proteomic imaging and transcriptomics.

We designed an epi-illumination SPIM system that uses a single objective and has a sample interface identical to that of an inverted fluorescence microscope with no additional reflection elements. It achieves subcellular resolution and single-molecule sensitivity, and is compatible with common biological sample holders, including multi-well plates. We demonstrated multicolor fast volumetric imaging, single-molecule localization microscopy, parallel imaging of 16 cell lines and parallel recording of cellular responses to perturbations.Epi-illumination SPIM enables fast, volumetric, high-resolution, subcellular imaging of any sample compatible with a standard inverted fluorescence microscope.

Both motor and non-motor proteins organize microtubules to build the spindle and maintain it against opposing forces. NuMA, a long microtubule binding protein, is essential to spindle structure and function. NuMA recruits the motor dynein to spindle microtubule minus-ends to actively cluster them, but whether NuMA performs other spindle roles remains unknown. Here, we show that NuMA acts independently of dynein to passively reinforce the mammalian spindle. NuMA that cannot bind dynein is sufficient to protect spindle poles against fracture under external force. In contrast, NuMA with a shorter coiled-coil or disrupted self-interactions cannot protect spindle poles, and NuMA turnover differences cannot explain mechanical differences. , NuMA's C-terminus self-interacts and bundles microtubules without dynein, dependent on residues essential to pole protection . Together, this suggests that NuMA reinforces spindle poles by crosslinking microtubules, using its long coiled-coiled and self-interactions to reach multiple, far-reaching pole microtubules. We propose that NuMA acts as a mechanical \"multitasker\" targeting contractile motor activity and separately crosslinking microtubules, both functions synergizing to drive spindle mechanical robustness.

To segregate chromosomes at cell division, the spindle must maintain its structure under force. How it does so remains poorly understood. To address this question, we use microneedle manipulation to apply local force to spindle microtubule bundles, kinetochore-fibers (k-fibers), inside mammalian cells. We show that local load directly fractures k-fibers, and that newly created plus-ends often have arrested dynamics, resisting depolymerization. Force alone, without fracture, is sufficient for spindle microtubule stabilization, as revealed by laser ablating k-fibers under local needle force. Doublecortin, which binds a compacted microtubule lattice, is lost around the force application site, suggesting local force-induced structural remodeling. In turn, EB1, which recognizes GTP-tubulin, is locally enriched at stabilization sites, both before and after force-induced fracture. Together, our findings support a model where force-induced damage leads to local spindle microtubule lattice remodeling and stabilization, which we propose reinforces the spindle where it experiences critical loads.

During cell division, NuMA orchestrates the focusing of microtubule minus-ends in spindle poles and cortical force generation on astral microtubules by interacting with dynein motors, microtubules, and other cellular factors. Here we used in vitro reconstitution, cryo-electron microscopy, and live cell imaging to understand the mechanism and regulation of NuMA. We determined the structure of the processive dynein/dynactin/NuMA complex (DDN) and showed that the NuMA N-terminus drives dynein motility in vitro and facilitates dynein-mediated transport in live cells. The C-terminus of NuMA directly binds to and suppresses the dynamics of the microtubule minus-end. Full-length NuMA is autoinhibited, but mitotically phosphorylated NuMA activates dynein in vitro and interphase cells. Together with dynein, activated full-length NuMA focuses microtubule minus-ends into aster-like structures. The binding of the cortical protein LGN to the NuMA C-terminus results in preferential binding of NuMA to the microtubule plus-end. These results provide critical insights into the activation of NuMA and dynein for their functions in the spindle body and the cell cortex.

At each cell division, nanometer-scale motors and microtubules give rise to the micron-scale spindle. Many mitotic motors step helically around microtubules in vitro, and most are predicted to twist the spindle in a left-handed direction. However, the human spindle exhibits only slight global twist, raising the question of how these molecular torques are balanced. Here, using lattice light sheet microscopy, we find that anaphase spindles in the epithelial cell line MCF10A have a high baseline twist, and we identify factors that both increase and decrease this twist. The midzone motors KIF4A and MKLP1 are redundantly required for left-handed twist at anaphase, and we show that KIF4A generates left-handed torque in vitro. The actin cytoskeleton also contributes to left-handed twist, but dynein and its cortical recruitment factor LGN counteract it. Together, our work demonstrates that force generators regulate twist in opposite directions from both within and outside the spindle, preventing strong spindle twist during chromosome segregation.

CRISPR/Cas technologies have transformed our ability to add functionality to the genome by knock-in of payload via homology-directed repair (HDR). However, a systematic and quantitative profiling of the knock-in integration landscape is still lacking. Here, we present a framework based on long-read sequencing and an integrated computational pipeline (knock-knock) to analyze knock-in repair outcomes across a wide range of experimental parameters. Our data uncover complex repair profiles, with perfect HDR often accounting for a minority of payload integration events, and reveal markedly distinct mis-integration patterns between cell-types or forms of HDR templates used. Our analysis demonstrates that the two sides of a given double-strand break can be repaired by separate pathways and identifies a major role for sequence micro-homology in driving donor mis-integration. Altogether, our comprehensive framework paves the way for investigating repair mechanisms, monitoring accuracy, and optimizing the precision of genome engineering. Footnotes * https://github.com/jeffhussmann/knock-knock