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.

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.

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.

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.

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.

Condensed but liquid-like domain organization of active chromatin regions in living human cells.

In eukaryotes, higher-order chromatin organization is spatiotemporally regulated as domains, for various cellular functions. However, their physical nature in living cells remains unclear (e.g., condensed domains or extended fiber loops; liquid-like or solid-like). Using novel approaches combining genomics, single-nucleosome imaging, and computational modeling, we investigated the physical organization and behavior of early DNA replicated regions in human cells, which correspond to Hi-C contact domains with active chromatin marks. Motion correlation analysis of two neighbor nucleosomes shows that nucleosomes form physically condensed domains with ~150-nm diameters, even in active chromatin regions. The mean-square displacement analysis between two neighbor nucleosomes demonstrates that nucleosomes behave like a liquid in the condensed domain on the ~150 nm/~0.5 s spatiotemporal scale, which facilitates chromatin accessibility. Beyond the micrometers/minutes scale, chromatin seems solid-like, which may contribute to maintaining genome integrity. Our study reveals the viscoelastic principle of the chromatin polymer; chromatin is locally dynamic and reactive but globally stable.

Systematic analysis of cell morphodynamics in C. elegans early embryogenesis.

The invariant cell lineage of Caenorhabditis elegans allows unambiguous assignment of the identity for each cell, which offers a unique opportunity to study developmental dynamics such as the timing of cell division, dynamics of gene expression, and cell fate decisions at single-cell resolution. However, little is known about cell morphodynamics, including the extent to which they are variable between individuals, mainly due to the lack of sufficient amount and quality of quantified data. In this study, we systematically quantified the cell morphodynamics in 52 C. elegans embryos from the two-cell stage to mid-gastrulation at the high spatiotemporal resolution, 0.5 µm thickness of optical sections, and 30-second intervals of recordings. Our data allowed systematic analyses of the morphological features. We analyzed sphericity dynamics and found a significant increase at the end of metaphase in every cell, indicating the universality of the mitotic cell rounding. Concomitant with the rounding, the volume also increased in most but not all cells, suggesting less universality of the mitotic swelling. Combining all features showed that cell morphodynamics was unique for each cell type. The cells before the onset of gastrulation could be distinguished from all the other cell types. Quantification of reproducibility in cell-cell contact revealed that variability in division timings and cell arrangements produced variability in contacts between the embryos. However, the area of such contacts occupied less than 5% of the total area, suggesting the high reproducibility of spatial occupancies and adjacency relationships of the cells. By comparing the morphodynamics of identical cells between the embryos, we observed diversity in the variability between cells and found it was determined by multiple factors, including cell lineage, cell generation, and cell-cell contact. We compared the variabilities of cell morphodynamics and cell-cell contacts with those in ascidian Phallusia mammillata embryos. The variabilities were larger in C. elegans, despite smaller differences in embryo size and number of cells at each developmental stage.

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.

Single-nucleosome imaging reveals steady-state motion of interphase chromatin in living human cells.

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 G1, S, and G2 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.

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.

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.

C. elegans spermatozoa lacking spe-45 are incapable of fusing with the oocyte plasma membrane.

C. elegans spe-9 class genes encode sperm proteins with indispensable roles during fertilization. We have previously reported that spe-45 belongs to the spe-9 class, based on the finding that self-sperm of spe-45(tm3715) hermaphrodites were not consumed by fertilization. In this study, we directly observed live fertilization in the spermatheca of fem-1(hc17) females after mating with spe-45(tm3715) males. As expected, it was clearly shown that spe-45 mutant spermatozoa failed to fuse with the oocyte plasma membrane. Thus, our live imaging system for C. elegans fertilization seems to be useful for evaluation of the functions of male and female gametes.

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.

NeuroGT: A brain atlas of neurogenic tagging CreER drivers for birthdate-based classification and manipulation of mouse neurons.

Neuronal birthdate is one of the major determinants of neuronal phenotypes. However, most birthdating methods are retrospective in nature, allowing very little experimental access to the classified neuronal subsets. Here, we introduce four neurogenic tagging mouse lines, which can assign CreER-loxP recombination to neuron subsets that share the same differentiation timing in living animals and enable various experimental manipulations of the classified subsets. We constructed a brain atlas of the neurogenic tagging mouse lines (NeuroGT), which includes holistic image data of the loxP-recombined neurons and their processes across the entire brain that were tagged on each single day during the neurodevelopmental period. This image database, which is open to the public, offers investigators the opportunity to find specific neurogenic tagging driver lines and the stages of tagging appropriate for their own research purposes.

Toward understanding the dynamic state of 3D genome.

The three-dimensional (3D) genome organization and its role in biological activities have been investigated for over a decade in the field of cell biology. Recent studies using live-imaging and polymer simulation have suggested that the higher-order chromatin structures are dynamic; the stochastic fluctuations of nucleosomes and genomic loci cannot be captured by bulk-based chromosome conformation capture techniques (Hi-C). In this review, we focus on the physical nature of the 3D genome architecture. We first describe how to decode bulk Hi-C data with polymer modeling. We then introduce our recently developed PHi-C method, a computational tool for modeling the fluctuations of the 3D genome organization in the presence of stochastic thermal noise. We also present another new method that analyzes the dynamic rheology property (represented as microrheology spectra) as a measure of the flexibility and rigidity of genomic regions over time. By applying these methods to real Hi-C data, we highlighted a temporal hierarchy embedded in the 3D genome organization; chromatin interaction boundaries are more rigid than the boundary interior, while functional domains emerge as dynamic fluctuations within a particular time interval. Our methods may bridge the gap between live-cell imaging and Hi-C data and elucidate the nature of the dynamic 3D genome organization.

BD5: An open HDF5-based data format to represent quantitative biological dynamics data.

BD5 is a new binary data format based on HDF5 (hierarchical data format version 5). It can be used for representing quantitative biological dynamics data obtained from bioimage informatics techniques and mechanobiological simulations. Biological Dynamics Markup Language (BDML) is an XML (Extensible Markup Language)-based open format that is also used to represent such data; however, it becomes difficult to access quantitative data in BDML files when the file size is large because parsing XML-based files requires large computational resources to first read the whole file sequentially into computer memory. BD5 enables fast random (i.e., direct) access to quantitative data on disk without parsing the entire file. Therefore, it allows practical reuse of data for understanding biological mechanisms underlying the dynamics.

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.