Live-cell imaging under centrifugation characterized the cellular force for nuclear centration in the Caenorhabditis elegans embryo.

Organelles in cells are appropriately positioned, despite crowding in the cytoplasm. However, our understanding of the force required to move large organelles, such as the nucleus, inside the cytoplasm is limited, in part owing to a lack of accurate methods for measurement. We devised a novel method to apply forces to the nucleus of living, wild-type Caenorhabditis elegans embryos to measure the force generated inside the cell. We utilized a centrifuge polarizing microscope (CPM) to apply centrifugal force and orientation-independent differential interference contrast (OI-DIC) microscopy to characterize the mass density of the nucleus and cytoplasm. The cellular forces moving the nucleus toward the cell center increased linearly at ~14 pN/µm depending on the distance from the center. The frictional coefficient was ~1,100 pN s/µm. The measured values were smaller than previously reported estimates for sea urchin embryos. The forces were consistent with the centrosome-organelle mutual pulling model for nuclear centration. Frictional coefficient was reduced when microtubules were shorter or detached from nuclei in mutant embryos, demonstrating the contribution of astral microtubules. Finally, the frictional coefficient was higher than a theoretical estimate, indicating the contribution of uncharacterized properties of the cytoplasm.

An explainable deep learning-based algorithm with an attention mechanism for predicting the live birth potential of mouse embryos.

In assisted reproductive technology (ART), embryos produced by in vitro fertilization (IVF) are graded according to their live birth potential, and high-grade embryos are preferentially transplanted. However, rates of live birth following clinical ART remain low worldwide. Grading is based on the embryo shape at a limited number of stages and does not consider the shape of embryos and intracellular structures, e.g., nuclei, at various stages important for normal embryogenesis. Here, we developed a Normalized Multi-View Attention Network (NVAN) that directly predicts live birth potential from the nuclear structure in live-cell fluorescence images of mouse embryos from zygote to across a wide range of stages. The input is morphological features of cell nuclei, which were extracted as multivariate time-series data by using the segmentation algorithm for mouse embryos. The classification accuracy of our method (83.87%) greatly exceeded that of existing machine-learning methods and that of visual inspection by embryo culture specialists. Our method also has a new attention mechanism that allows us to determine which values of multivariate time-series data, used to describe nuclear morphology, were the basis for the prediction. By visualizing the features that contributed most to the prediction of live birth potential, we found that the size and shape of the nucleus at the morula stage and at the time of cell division were important for live birth prediction. We anticipate that our method will help ART and developmental engineering as a new basic technology for IVF embryo selection.

Asynchronous division at 4-8-cell stage of preimplantation embryos affects live birth through ICM/TE differentiation.

To improve the performance of assisted reproductive technology, it is necessary to find an indicator that can identify and select embryos that will be born or be aborted. We searched for indicators of embryo selection by comparing born/abort mouse embryos. We found that asynchronous embryos during the 4-8-cell stage were predisposed to be aborted. In asynchronous mouse embryos, the nuclear translocation of YAP1 in some blastomeres and compaction were delayed, and the number of ICMs was reduced. Hence, it is possible that asynchronous embryos have abnormal differentiation. When the synchrony of human embryos was observed, it was confirmed that embryos that did not reach clinical pregnancy had asynchrony as in mice. This could make synchrony a universal indicator common to all animal species.

3D convolutional neural networks-based segmentation to acquire quantitative criteria of the nucleus during mouse embryogenesis.

During embryogenesis, cells repeatedly divide and dynamically change their positions in three-dimensional (3D) space. A robust and accurate algorithm to acquire the 3D positions of the cells would help to reveal the mechanisms of embryogenesis. To acquire quantitative criteria of embryogenesis from time-series 3D microscopic images, image processing algorithms such as segmentation have been applied. Because the cells in embryos are considerably crowded, an algorithm to segment individual cells in detail and accurately is needed. To quantify the nuclear region of every cell from a time-series 3D fluorescence microscopic image of living cells, we developed QCANet, a convolutional neural network-based segmentation algorithm for 3D fluorescence bioimages. We demonstrated that QCANet outperformed 3D Mask R-CNN, which is currently considered as the best algorithm of instance segmentation. We showed that QCANet can be applied not only to developing mouse embryos but also to developing embryos of two other model species. Using QCANet, we were able to extract several quantitative criteria of embryogenesis from 11 early mouse embryos. We showed that the extracted criteria could be used to evaluate the differences between individual embryos. This study contributes to the development of fundamental approaches for assessing embryogenesis on the basis of extracted quantitative criteria.

Zygotic Nuclear F-Actin Safeguards Embryonic Development.

After fertilization, sperm and oocyte nuclei are rapidly remodeled to form swollen pronuclei (PN) in mammalian zygotes, and the proper formation and function of PN are key to producing totipotent zygotes. However, how mature PN are formed has been unclear. We find that filamentous actin (F-actin) assembles in the PN of mouse zygotes and is required for fully functional PN. The perturbation of nuclear actin dynamics in zygotes results in the misregulation of genes related to genome integrity and abnormal development of mouse embryos. We show that nuclear F-actin ensures DNA damage repair, thus preventing the activation of a zygotic checkpoint. Furthermore, optogenetic control of cofilin nuclear localization reveals the dynamically regulated F-actin nucleoskeleton in zygotes, and its timely disassembly is needed for developmental progression. Nuclear F-actin is a hallmark of totipotent zygotic PN, and the temporal regulation of its polymerized state is necessary for normal embryonic development.

Chromosome segregation error during early cleavage in mouse pre-implantation embryo does not necessarily cause developmental failure after blastocyst stage.

In the pre-implantation embryo, aneuploidy resulting from chromosome segregation error is considered responsible for pregnancy loss. However, only a few studies have examined the relationship between chromosome segregation errors during early cleavage and development. Here, we evaluated this relationship by live-cell imaging using the histone H2B-mCherry probe and subsequent single blastocyst transfer using mouse embryos obtained by in vitro fertilization. We showed that some embryos exhibiting early chromosomal segregation error and formation of micronuclei retained their developmental potential; however, the error affected the blastocyst/arrest ratio. Further, single-cell sequencing after live-cell imaging revealed that all embryos exhibiting micronuclei formation during 1st mitosis showed aneuploidy at the 2-cell stage. These results suggest that early chromosome segregation error causing micronuclei formation affects ploidy and development to blastocyst but does not necessarily cause developmental failure after the blastocyst stage. Our result suggests the importance of the selection of embryos that have reached blastocysts.