Centromere/kinetochore is assembled through CENP-C oligomerization.

Kinetochore is an essential protein complex required for accurate chromosome segregation. The constitutive centromere-associated network (CCAN), a subcomplex of the kinetochore, associates with centromeric chromatin and provides a platform for the kinetochore assembly. The CCAN protein CENP-C is thought to be a central hub for the centromere/kinetochore organization. However, the role of CENP-C in CCAN assembly needs to be elucidated. Here, we demonstrate that both the CCAN-binding domain and the C-terminal region that includes the Cupin domain of CENP-C are necessary and sufficient for chicken CENP-C function. Structural and biochemical analyses reveal self-oligomerization of the Cupin domains of chicken and human CENP-C. We find that the CENP-C Cupin domain oligomerization is vital for CENP-C function, centromeric localization of CCAN, and centromeric chromatin organization. These results suggest that CENP-C facilitates the centromere/kinetochore assembly through its oligomerization.

Single-molecule tracking of Nanog and Oct4 in living mouse embryonic stem cells uncovers a feedback mechanism of pluripotency maintenance.

Nanog and Oct4 are core transcription factors that form part of a gene regulatory network to regulate hundreds of target genes for pluripotency maintenance in mouse embryonic stem cells (ESCs). To understand their function in the pluripotency maintenance, we visualised and quantified the dynamics of single molecules of Nanog and Oct4 in a mouse ESCs during pluripotency loss. Interestingly, Nanog interacted longer with its target loci upon reduced expression or at the onset of differentiation, suggesting a feedback mechanism to maintain the pluripotent state. The expression level and interaction time of Nanog and Oct4 correlate with their fluctuation and interaction frequency, respectively, which in turn depend on the ESC differentiation status. The DNA viscoelasticity near the Oct4 target locus remained flexible during differentiation, supporting its role either in chromatin opening or a preferred binding to uncondensed chromatin regions. Based on these results, we propose a new negative feedback mechanism for pluripotency maintenance via the DNA condensation state-dependent interplay of Nanog and Oct4.

Homeostasis imbalance process ontology: a study on COVID-19 infectious processes.

BACKGROUND: One significant challenge in addressing the coronavirus disease 2019 (COVID-19) pandemic is to grasp a comprehensive picture of its infectious mechanisms. We urgently need a consistent framework to capture the intricacies of its complicated viral infectious processes and diverse symptoms. RESULTS: We systematized COVID-19 infectious processes through an ontological approach and provided a unified description framework of causal relationships from the early infectious stage to severe clinical manifestations based on the homeostasis imbalance process ontology (HoIP). HoIP covers a broad range of processes in the body, ranging from normal to abnormal. Moreover, our imbalance model enabled us to distinguish viral functional demands from immune defense processes, thereby supporting the development of new drugs, and our research demonstrates how ontological reasoning contributes to the identification of patients at severe risk. CONCLUSIONS: The HoIP organises knowledge of COVID-19 infectious processes and related entities, such as molecules, drugs, and symptoms, with a consistent descriptive framework. HoIP is expected to harmonise the description of various heterogeneous processes and improve the interoperability of COVID-19 knowledge through the COVID-19 ontology harmonisation working group.

The PAF1 complex cell autonomously promotes oogenesis in Caenorhabditis elegans.

The RNA polymerase II-associated factor 1 complex (PAF1C) is a protein complex that consists of LEO1, RTF1, PAF1, CDC73, and CTR9, and has been shown to be involved in RNA polymerase II-mediated transcriptional and chromatin regulation. Although it has been shown to regulate a variety of biological processes, the precise role of the PAF1C during germ line development has not been clarified. In this study, we found that reduction in the function of the PAF1C components, LEO-1, RTFO-1, PAFO-1, CDC-73, and CTR-9, in Caenorhabditis elegans affects oogenesis. Defects in oogenesis were also confirmed using an oocyte maturation marker, OMA-1::GFP. While four to five OMA-1::GFP-positive oocytes were observed in wild-type animals, their numbers were significantly decreased in pafo-1 mutant and leo-1(RNAi), pafo-1(RNAi), and cdc-73(RNAi) animals. Expression of a functional PAFO-1::mCherry transgene in the germline significantly rescued the oogenesis-defective phenotype of the pafo-1 mutants, suggesting that expression of the PAF1C in germ cells is required for oogenesis. Notably, overexpression of OMA-1::GFP partially rescued the oogenesis defect in the pafo-1 mutants. Based on our findings, we propose that the PAF1C promotes oogenesis in a cell-autonomous manner by positively regulating the expression of genes involved in oocyte maturation.

PHi-C2: interpreting Hi-C data as the dynamic 3D genome state.

SUMMARY: High-throughput chromosome conformation capture (Hi-C) is a widely used assay for studying the three-dimensional (3D) genome organization across the whole genome. Here, we present PHi-C2, a Python package supported by mathematical and biophysical polymer modeling that converts input Hi-C matrix data into the polymer model's dynamics, structural conformations and rheological features. The updated optimization algorithm for regenerating a highly similar Hi-C matrix provides a fast and accurate optimal solution compared to the previous version by eliminating the factors underlying the inefficiency of the optimization algorithm in the iterative optimization process. In addition, we have enabled a Google Colab workflow to run the algorithm, wherein users can easily change the parameters and check the results in the notebook. Overall, PHi-C2 represents a valuable tool for mining the dynamic 3D genome state embedded in Hi-C data. AVAILABILITY AND IMPLEMENTATION: PHi-C2 as the phic Python package is freely available under the GPL license and can be installed from the Python package index. The source code is available from GitHub at https://github.com/soyashinkai/PHi-C2. Moreover, users do not have to prepare a Python environment because PHi-C2 can run on Google Colab (https://bit.ly/3rlptGI). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Statistical image processing quantifies the changes in cytoplasmic texture associated with aging in Caenorhabditis elegans oocytes.

BACKGROUND: Oocyte quality decreases with aging, thereby increasing errors in fertilization, chromosome segregation, and embryonic cleavage. Oocyte appearance also changes with aging, suggesting a functional relationship between oocyte quality and appearance. However, no methods are available to objectively quantify age-associated changes in oocyte appearance. RESULTS: We show that statistical image processing of Nomarski differential interference contrast microscopy images can be used to quantify age-associated changes in oocyte appearance in the nematode Caenorhabditis elegans. Max-min value (mean difference between the maximum and minimum intensities within each moving window) quantitatively characterized the difference in oocyte cytoplasmic texture between 1- and 3-day-old adults (Day 1 and Day 3 oocytes, respectively). With an appropriate parameter set, the gray level co-occurrence matrix (GLCM)-based texture feature Correlation (COR) more sensitively characterized this difference than the Max-min Value. Manipulating the smoothness of and/or adding irregular structures to the cytoplasmic texture of Day 1 oocyte images reproduced the difference in Max-min Value but not in COR between Day 1 and Day 3 oocytes. Increasing the size of granules in synthetic images recapitulated the age-associated changes in COR. Manual measurements validated that the cytoplasmic granules in oocytes become larger with aging. CONCLUSIONS: The Max-min value and COR objectively quantify age-related changes in C. elegans oocyte in Nomarski DIC microscopy images. Our methods provide new opportunities for understanding the mechanism underlying oocyte aging.

Improvement in image quality via the pseudo confocal effect in multidirectional digital scanned laser light-sheet microscopy.

Multidirectional digital scanned laser light-sheet microscopy (mDSLM) cannot be used with the current pseudo confocal system to reduce blurring and background signals. The multiline scanning for light-sheet illumination and the simple image construction proposed in this study are alternative to the pseudo confocal system. We investigate the effectiveness of our pseudo confocal method combined with mDSLM on artificial phantoms and biological samples. The results indicate that image quality from mDSLM can be improved by the confocal effect; their combination is effective and can be applied to biological investigations.

Microrheology for Hi-C Data Reveals the Spectrum of the Dynamic 3D Genome Organization.

The one-dimensional information of genomic DNA is hierarchically packed inside the eukaryotic cell nucleus and organized in a three-dimensional (3D) space. Genome-wide chromosome conformation capture (Hi-C) methods have uncovered the 3D genome organization and revealed multiscale chromatin domains of compartments and topologically associating domains (TADs). Moreover, single-nucleosome live-cell imaging experiments have revealed the dynamic organization of chromatin domains caused by stochastic thermal fluctuations. However, the mechanism underlying the dynamic regulation of such hierarchical and structural chromatin units within the microscale thermal medium remains unclear. Microrheology is a way to measure dynamic viscoelastic properties coupling between thermal microenvironment and mechanical response. Here, we propose a new, to our knowledge, microrheology for Hi-C data to analyze the dynamic compliance property as a measure of rigidness and flexibility of genomic regions along with the time evolution. Our method allows the conversion of an Hi-C matrix into the spectrum of the dynamic rheological property along the genomic coordinate of a single chromosome. To demonstrate the power of the technique, we analyzed Hi-C data during the neural differentiation of mouse embryonic stem cells. We found that TAD boundaries behave as more rigid nodes than the intra-TAD regions. The spectrum clearly shows the dynamic viscoelasticity of chromatin domain formation at different timescales. Furthermore, we characterized the appearance of synchronous and liquid-like intercompartment interactions in differentiated cells. Together, our microrheology data derived from Hi-C data provide physical insights into the dynamics of the 3D genome organization.

Biologically constrained optimization based cell membrane segmentation in C. elegans embryos.

BACKGROUND: Recent 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. RESULTS: Our 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. CONCLUSIONS: BCOMS 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.

SSBD: a database of quantitative data of spatiotemporal dynamics of biological phenomena.

MOTIVATION: Rapid advances in live-cell imaging analysis and mathematical modeling have produced a large amount of quantitative data on spatiotemporal dynamics of biological objects ranging from molecules to organisms. There is now a crucial need to bring these large amounts of quantitative biological dynamics data together centrally in a coherent and systematic manner. This will facilitate the reuse of this data for further analysis. RESULTS: We have developed the Systems Science of Biological Dynamics database (SSBD) to store and share quantitative biological dynamics data. SSBD currently provides 311 sets of quantitative data for single molecules, nuclei and whole organisms in a wide variety of model organisms from Escherichia coli to Mus musculus The data are provided in Biological Dynamics Markup Language format and also through a REST API. In addition, SSBD provides 188 sets of time-lapse microscopy images from which the quantitative data were obtained and software tools for data visualization and analysis. AVAILABILITY AND IMPLEMENTATION: SSBD is accessible at http://ssbd.qbic.riken.jp CONTACT: sonami@riken.jp.

Biological Dynamics Markup Language (BDML): an open format for representing quantitative biological dynamics data.

MOTIVATION: Recent progress in live-cell imaging and modeling techniques has resulted in generation of a large amount of quantitative data (from experimental measurements and computer simulations) on spatiotemporal dynamics of biological objects such as molecules, cells and organisms. Although many research groups have independently dedicated their efforts to developing software tools for visualizing and analyzing these data, these tools are often not compatible with each other because of different data formats. RESULTS: We developed an open unified format, Biological Dynamics Markup Language (BDML; current version: 0.2), which provides a basic framework for representing quantitative biological dynamics data for objects ranging from molecules to cells to organisms. BDML is based on Extensible Markup Language (XML). Its advantages are machine and human readability and extensibility. BDML will improve the efficiency of development and evaluation of software tools for data visualization and analysis. AVAILABILITY AND IMPLEMENTATION: A specification and a schema file for BDML are freely available online at http://ssbd.qbic.riken.jp/bdml/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Improving spinning disk confocal microscopy by preventing pinhole cross-talk for intravital imaging.

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.

WDDD: Worm Developmental Dynamics Database.

During animal development, cells undergo dynamic changes in position and gene expression. A collection of quantitative information about morphological dynamics under a wide variety of gene perturbations would provide a rich resource for understanding the molecular mechanisms of development. Here, we created a database, the Worm Developmental Dynamics Database (http://so.qbic.riken.jp/wddd/), which stores a collection of quantitative information about cell division dynamics in early Caenorhabditis elegans embryos with single genes silenced by RNA-mediated interference. The information contains the three-dimensional coordinate values of the outlines of nuclear regions and the dynamics of the outlines over time. The database provides free access to 50 sets of quantitative data for wild-type embryos and 136 sets of quantitative data for RNA-mediated interference embryos corresponding to 72 of the 97 essential embryonic genes on chromosome III. The database also provides sets of four-dimensional differential interference contrast microscopy images on which the quantitative data were based. The database will provide a novel opportunity for the development of computational methods to obtain fresh insights into the mechanisms of development. The quantitative information and microscopy images can be synchronously viewed through a web browser, which is designed for easy access by experimental biologists.

Prototyping an Ontological Framework for Cellular Senescence Mechanisms: A Homeostasis Imbalance Perspective.

Although cellular senescence is a key factor in organismal aging, with both positive and negative effects on individuals, its mechanisms remain largely unknown. Thus, integrating knowledge is essential to explain how cellular senescence manifests in tissue damage and age-related diseases. Here, we propose an ontological model that organizes knowledge of cellular senescence in a computer-readable form. We manually annotated and defined cellular senescence processes, molecules, anatomical structures, phenotypes, and other entities based on the Homeostasis Imbalance Process ontology (HOIP). We described the mechanisms as causal relationships of processes and modelled a homeostatic imbalance between stress and stress response in cellular senescence for a unified framework. HOIP was assessed formally, and the relationships between cellular senescence and diseases were inferred for higher-order knowledge processing. We visualized cellular senescence processes to support knowledge utilization. Our study provides a knowledge base to help elucidate mechanisms linking cellular and organismal aging.

An atlas and database of neuropeptide gene expression in the adult zebrafish forebrain.

Zebrafish is a useful model organism in neuroscience; however, its gene expression atlas in the adult brain is not well developed. In the present study, we examined the expression of 38 neuropeptides, comparing with GABAergic and glutamatergic neuron marker genes in the adult zebrafish brain by comprehensive in situ hybridization. The results are summarized as an expression atlas in 19 coronal planes of the forebrain. Furthermore, the scanned data of all brain sections were made publicly available in the Adult Zebrafish Brain Gene Expression Database (https://ssbd.riken.jp/azebex/). Based on these data, we performed detailed comparative neuroanatomical analyses of the hypothalamus and found that several regions previously described as one nucleus in the reference zebrafish brain atlas contain two or more subregions with significantly different neuropeptide/neurotransmitter expression profiles. Subsequently, we compared the expression data in zebrafish telencephalon and hypothalamus obtained in this study with those in mice, by performing a cluster analysis. As a result, several nuclei in zebrafish and mice were clustered in close vicinity. The present expression atlas, database, and anatomical findings will contribute to future neuroscience research using zebrafish.

Unifying community-wide whole-brain imaging datasets enables robust automated neuron identification and reveals determinants of neuron positioning in C. elegans.

We develop a data harmonization approach for C. elegans volumetric microscopy data, still or video, consisting of a standardized format, data pre-processing techniques, and a set of human-in-the-loop machine learning based analysis software tools. We unify a diverse collection of 118 whole-brain neural activity imaging datasets from 5 labs, storing these and accompanying tools in an online repository called WormID (wormid.org). We use this repository to generate a statistical atlas that, for the first time, enables accurate automated cellular identification that generalizes across labs, approaching human performance in some cases. We mine this repository to identify factors that influence the developmental positioning of neurons. To facilitate communal use of this repository, we created open-source software, code, web-based tools, and tutorials to explore and curate datasets for contribution to the scientific community. This repository provides a growing resource for experimentalists, theorists, and toolmakers to investigate neuroanatomical organization and neural activity across diverse experimental paradigms, develop and benchmark algorithms for automated neuron detection, segmentation, cell identification, tracking, and activity extraction, and inform models of neurobiological development and function.

Harmonizing the Generation and Pre-publication Stewardship of FAIR Image data.

Together with the molecular knowledge of genes and proteins, biological images promise to significantly enhance the scientific understanding of complex cellular systems and to advance predictive and personalized therapeutic products for human health. For this potential to be realized, quality-assured image data must be shared among labs at a global scale to be compared, pooled, and reanalyzed, thus unleashing untold potential beyond the original purpose for which the data was generated. There are two broad sets of requirements to enable image data sharing in the life sciences. One set of requirements is articulated in the companion White Paper entitled "Enabling Global Image Data Sharing in the Life Sciences," which is published in parallel and addresses the need to build the cyberinfrastructure for sharing the digital array data (arXiv:2401.13023 [q-bio.OT], https://doi.org/10.48550/arXiv.2401.13023). In this White Paper, we detail a broad set of requirements, which involves collecting, managing, presenting, and propagating contextual information essential to assess the quality, understand the content, interpret the scientific implications, and reuse image data in the context of the experimental details. We start by providing an overview of the main lessons learned to date through international community activities, which have recently made considerable progress toward generating community standard practices for imaging Quality Control (QC) and metadata. We then provide a clear set of recommendations for amplifying this work. The driving goal is to address remaining challenges, and democratize access to common practices and tools for a spectrum of biomedical researchers, regardless of their expertise, access to resources, and geographical location.

Evaluation of the effectiveness of simple nuclei-segmentation methods on Caenorhabditis elegans embryogenesis images.

BACKGROUND: For the analysis of spatio-temporal dynamics, various automated processing methods have been developed for nuclei segmentation. These methods tend to be complex for segmentation of images with crowded nuclei, preventing the simple reapplication of the methods to other problems. Thus, it is useful to evaluate the ability of simple methods to segment images with various degrees of crowded nuclei. RESULTS: Here, we selected six simple methods from various watershed based and local maxima detection based methods that are frequently used for nuclei segmentation, and evaluated their segmentation accuracy for each developmental stage of the Caenorhabditis elegans. We included a 4D noise filter, in addition to 2D and 3D noise filters, as a pre-processing step to evaluate the potential of simple methods as widely as possible. By applying the methods to image data between the 50- to 500-cell developmental stages at 50-cell intervals, the error rate for nuclei detection could be reduced to ≤ 2.1% at every stage until the 350-cell stage. The fractions of total errors throughout the stages could be reduced to ≤ 2.4%. The error rates improved at most of the stages and the total errors improved when a 4D noise filter was used. The methods with the least errors were two watershed-based methods with 4D noise filters. For all the other methods, the error rate and the fraction of errors could be reduced to ≤ 4.2% and ≤ 4.1%, respectively. The minimum error rate for each stage between the 400- to 500-cell stages ranged from 6.0% to 8.4%. However, similarities between the computational and manual segmentations measured by volume overlap and Hausdorff distance were not good. The methods were also applied to Drosophila and zebrafish embryos and found to be effective. CONCLUSIONS: The simple segmentation methods were found to be useful for detecting nuclei until the 350-cell stage, but not very useful after the 400-cell stage. The incorporation of a 4D noise filter to the simple methods could improve their performances. Error types and the temporal biases of errors were dependent on the methods used. Combining multiple simple methods could also give good segmentations.