A male pronucleus migrates toward the center of an egg to reach the female pronucleus for zygote formation. This migration depends on microtubules growing from two centrosomes associated with the male pronucleus. Two mechanisms were previously proposed for this migration: a "pushing mechanism," which uses the pushing force resulting from microtubule polymerization, and a "pulling mechanism," which uses the length-dependent pulling force generated by minus-end-directed motors anchored throughout the cytoplasm. We combined two computer-assisted analyses to examine the relative contribution of these mechanisms to male pronuclear migration. Computer simulation revealed an intrinsic difference in migration behavior of the male pronucleus between the pushing and pulling mechanisms. In vivo measurements using image processing showed that the actual migration behavior in Caenorhabditis elegans confirms the pulling mechanism. A male pronucleus having a single centrosome migrated toward the single aster. We propose that the pulling mechanism is the primary mechanism for male pronuclear migration.

Centrosome positioning is actively regulated by forces acting on microtubules radiating from the centrosomes. Two mechanisms, center-directed and polarized cortical pulling, are major contributors to the successive centering and posteriorly displacing migrations of the centrosomes in single-cell–stage Caenorhabditis elegans. In this study, we analyze the spatial distribution of the forces acting on the centrosomes to examine the mechanism that switches centrosomal migration from centering to displacing. We clarify the spatial distribution of the forces using image processing to measure the micrometer-scale movements of the centrosomes. The changes in distribution show that polarized cortical pulling functions during centering migration. The polarized cortical pulling force directed posteriorly is repressed predominantly in the lateral regions during centering migration and is derepressed during posteriorly displacing migration. Computer simulations show that this local repression of cortical pulling force is sufficient for switching between centering and displacing migration. Local regulation of cortical pulling might be a mechanism conserved for the precise temporal regulation of centrosomal dynamic positioning.

A recent key requirement in life sciences is the observation of biological processes in their natural in vivo context. However, imaging techniques that allow fast imaging with higher resolution in 3D thick specimens are still limited. Spinning disk confocal microscopy using a Yokogawa Confocal Scanner Unit, which offers high-speed multipoint confocal live imaging, has been found to have wide utility among cell biologists. A conventional Confocal Scanner Unit configuration, however, is not optimized for thick specimens, for which the background noise attributed to “pinhole cross-talk,” which is unintended pinhole transmission of out-of-focus light, limits overall performance in focal discrimination and reduces confocal capability. Here, we improve spinning disk confocal microscopy by eliminating pinhole cross-talk. First, the amount of pinhole cross-talk is reduced by increasing the interpinhole distance. Second, the generation of out-of-focus light is prevented by two-photon excitation that achieves selective-plane illumination. We evaluate the effect of these modifications and test the applicability to the live imaging of green fluorescent protein-expressing model animals. As demonstrated by visualizing the fine details of the 3D cell shape and submicron-size cytoskeletal structures inside animals, these strategies dramatically improve higher-resolution intravital imaging.

Dynamic chromatin behavior plays a critical role in various genome functions. However, it remains unclear how chromatin behavior changes during interphase, where the nucleus enlarges and genomic DNA doubles. While the previously reported chromatin movements varied during interphase when measured using a minute or longer time scale, we unveil that local chromatin motion captured by single-nucleosome imaging/tracking on a second time scale remained steady throughout G 1 , S, and G 2 phases in live human cells. This motion mode appeared to change beyond this time scale. A defined genomic region also behaved similarly. Combined with Brownian dynamics modeling, our results suggest that this steady-state chromatin motion was mainly driven by thermal fluctuations. Steady-state motion temporarily increased following a DNA damage response. Our findings support the viscoelastic properties of chromatin. We propose that the observed steady-state chromatin motion allows cells to conduct housekeeping functions, such as transcription and DNA replication, under similar environments during interphase.

Bioimaging data have significant potential for reuse, but unlocking this potential requires systematic archiving of data and metadata in public databases. We propose draft metadata guidelines to begin addressing the needs of diverse communities within light and electron microscopy. We hope this publication and the proposed Recommended Metadata for Biological Images (REMBI) will stimulate discussions about their implementation and future extension.

Sperm induce Ca(2+) waves in the fertilized egg by introducing soluble factors or by surface interactions, which activate egg Ca(2+) channels. Involvement of sperm Ca(2+) channels is predicted by the conduit model; however, this model has not been validated. In Caenorhabditis elegans, the sperm-specific TRP family Ca(2+) channel TRP-3 mediates sperm-oocyte fusion. Here, using high-speed in vivo imaging and image analyses, we show that sperm induce an immediate local Ca(2+) rise followed by a Ca(2+) wave in fertilized C. elegans oocytes. Oocytes fertilized by rare trp-3 escaper sperm showed a lack of local rise and a delay in onset of the Ca(2+) wave. Sperm Ca(2+) imaging suggests that the local rise is not due to the bolus introduction of stored Ca(2+). These results suggest that, along with its primary function in sperm-oocyte fusion, TRP-3 induces Ca(2+) waves in fertilized oocytes, consistent with the conduit model.

20of the 3D genome in cell nuclei. Here, we describe a 4D simulation method, PHi-C (Polymer 21 dynamics deciphered from Hi-C data), that depicts dynamic 3D genome features through 22 polymer modelling. This method allows for demonstrations of dynamic characteristics of 23 genomic loci and chromosomes, as observed in live-cell imaging experiments, and provides 24 physical insights into Hi-C data. 25 Genomes consist of one-dimensional DNA sequences and are spatio-temporally organized 26 within the cell nucleus. Contact frequencies in the form of matrix data, measured using genome-27 wide chromosome conformation capture (Hi-C) technologies, have uncovered three-dimensional 28 (3D) features of average genome organization in a cell population 1, 2 . Moreover, live-cell imaging 29 experiments can reveal dynamic chromatin organization in response to biological perturbations 30 within single cells 3, 4 . Bridging the gap between these different sets of data derived from population 31 and single cells is a challenge for modelling dynamic genome organization 5, 6 . 32Several modelling methods have been developed to reconstruct 3D genome structures and 33 predict Hi-C data 7, 8 . In addition, there has been development of bioinformatic normalization 34 techniques in Hi-C matrix data processing to reduce experimental biases 9-11 . However, the mean-35 ing of a contact matrix as quantitative probability data has not been discussed; moreover, a four-36 dimensional (4D) simulation method to explore dynamic 3D genome organization remains lacking. 37Here, we introduce PHi-C, a method that can overcome these challenges by polymer mod-38 elling from a mathematical perspective and at low computational cost. PHi-C is a method that 39 2 deciphers Hi-C data into polymer dynamics simulations ( Fig. 1a, https://github.com/ 40 soyashinkai/PHi-C). PHi-C uses Hi-C contact matrix data generated from a hic file through 41 JUICER 12 as input ( Supplementary Fig. 1a). PHi-C assumes that a genomic region of interest at 42 an appropriate resolution can be modelled using a polymer network model, in which one monomer 43 corresponds to the genomic bin size of the contact matrix data with attractive and repulsive interac-44 tion parameters between all pairs of monomers described as matrix data (Methods, Supplementary 45 Note). Instead of finding optimized 3D conformations, we can utilize the optimization procedure 46 ( Supplementary Fig. 1b,c) to obtain optimal interaction parameters of the polymer network model 47 by using an analytical relationship between the parameters and the contact matrix. We can then 48 reconstruct an optimized contact matrix validated by input Hi-C matrix data using Pearson's cor-49 relation r. Finally, we can perform polymer dynamics simulations of the polymer network model 50 equipped with the optimal interaction parameters. 51First, we evaluated PHi-C's theoretical assumption about chromosome contact. Here, we 52 started with a simple polymer model called the bead-spring model, in which the characteristic 53 length...

BackgroundRecent advances in bioimaging and automated analysis methods have enabled the large-scale systematic analysis of cellular dynamics during the embryonic development of Caenorhabditis elegans. Most of these analyses have focused on cell lineage tracing rather than cell shape dynamics. Cell shape analysis requires cell membrane segmentation, which is challenging because of insufficient resolution and image quality. This problem is currently solved by complicated segmentation methods requiring laborious and time consuming parameter adjustments.ResultsOur new framework BCOMS (Biologically Constrained Optimization based cell Membrane Segmentation) automates the extraction of the cell shape of C. elegans embryos. Both the segmentation and evaluation processes are automated. To automate the evaluation, we solve an optimization problem under biological constraints. The performance of BCOMS was validated against a manually created ground truth of the 24-cell stage embryo. The average deviation of 25 cell shape features was 5.6%. The deviation was mainly caused by membranes parallel to the focal planes, which either contact the surfaces of adjacent cells or make no contact with other cells. Because segmentation of these membranes was difficult even by manual inspection, the automated segmentation was sufficiently accurate for cell shape analysis. As the number of manually created ground truths is necessarily limited, we compared the segmentation results between two adjacent time points. Across all cells and all cell cycles, the average deviation of the 25 cell shape features was 4.3%, smaller than that between the automated segmentation result and ground truth.ConclusionsBCOMS automated the accurate extraction of cell shapes in developing C. elegans embryos. By replacing image processing parameters with easily adjustable biological constraints, BCOMS provides a user-friendly framework. The framework is also applicable to other model organisms. Creating the biological constraints is a critical step requiring collaboration between an experimentalist and a software developer.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1717-6) contains supplementary material, which is available to authorized users.