Biology subjects

Onami, S.

Publications and source records attributed to Onami, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Automahout: an autonomous image analysis system for cell tracking

Cell tracking in time-lapse images is complex image analysis that involves detection, linking and proofreading, often requiring the algorithm to be tuned for every new dataset. We present Automahout, an autonomous agent for the Mastodon/ELEPHANT platform that carries out these operations. It looks at the data and tries existing models; where none fits, it annotates reference cells, trains a detector from those sparse annotations, reviews its output against them and feeds the corrections back until its own stopping criteria are met. It then links, checks the lineage and moves on. On three public datasets, a 2D fluorescence culture, a 2D phase-contrast culture and a 3D embryo, it produced lineages without human input and reached TRA scores of 0.95-0.96.

bioinformatics↗

bioRxiv2026

Immobilization-free chemotaxis analysis reveals the novel behavioral mode of leaving in Caenorhabditis elegans

Animals balance staying in a favorable environment with exploring new ones. In C. elegans chemotaxis, the process by which worms migrate toward an attractant has been extensively studied. However, what happens after they reach it remains largely unexplored, partly because conventional assays immobilize worms at the point of arrival. Here, we quantitatively analyzed chemotactic behavior upon reaching an attractive odor source using an immobilization-free chemotaxis assay. We observed that 62% animals left the isoamyl alcohol region after initially approaching it, a behavior we termed "leaving behavior." Quantitative analysis revealed that leaving behavior represents a distinct locomotor state compared with free-moving, high-concentration odor avoidance, and approach behavior. To test whether leaving behavior is related to olfactory adaptation, we analyzed mutants in adaptation-related genes. The proportion of leaving behavior was significantly increased in egl-4 loss-of-function mutants compared with wild-type animals, whereas arr-1 mutants showed no significant difference. These results suggest that egl-4 negatively regulates leaving behavior, suggesting a role for this kinase in stabilizing post-arrival behavioral states beyond its known function in olfactory adaptation. Our findings indicate that chemotaxis involves dynamic behavioral transitions even after reaching an attractant, consistent with an exploration-exploitation trade-off framework. Significance StatementBy eliminating immobilization from a conventional chemotaxis assay, this study reveals behaviors that are typically obscured after animals reach an attractant. In C. elegans, we identify a post-arrival behavioral mode, "leaving," in which animals move away from an attractive odorant (isoamyl alcohol) after initially approaching it. Leaving behavior is quantitatively distinct from free-moving behavior, high-concentration odor avoidance, and approaching behavior. We further show that the frequency of leaving behavior is increased in animals lacking the egl-4 gene. These findings extend chemotaxis analysis beyond the point of odor source arrival and suggest that the nervous system actively drives behavioral switching even after a goal is reached, broadening our understanding of how sensory circuits govern exploration-exploitation decisions.

animal behavior and cognition↗

bioRxiv2026

Self-Supervised Behavioral Representations Across the Life Course: A Killifish Case Study

Self-supervised foundation models of aging are increasingly built from longitudinal data (biobanks, electronic health records, wearables) that is inherently incomplete: no individual is followed across a whole lifetime, and how much of each life is captured varies widely. This raises two linked questions: is it worth modeling an individuals whole life course rather than its current state, and can such a model be built from brief, fragmentary records? No human cohort can settle them, because none offers a complete life to compare against. We turn to the African turquoise killifish (Nothobranchius furzeri), tracked from youth to natural death in publicly released recordings, as a controlled testbed: its complete lifespans provide the full-life reference that human data lacks. On these data we build LifeMAE, a two-stage self-supervised model: a day encoder that summarizes each day of behavior, then a life-course encoder over the trajectory of those daily summaries. We find that the day encoder alone is already strong: from a single day of behavior it predicts chronological age, separates long-from short-lived individuals (coarsely), and flags nearness to death. Adding the life-course encoder improves on none of the three; each is matched by trivially aggregating the day-level predictions (a smoother for age, an early-life average for lifespan). Near-term mortality seems the exception, where the whole-life model looks far better (AUROC 0.81 to 0.91), but the gain is not behavioral: it reflects where each day falls within the observation window (a cue supplied by the models encoding of time), and a single-day model given that cue closes the gap at any observation length. For these traits, an individuals place in its life course is legible from a single day: the trajectory stage is unnecessary, and the record it needs is as short as one day, the finest grain our day-level setup resolves. For characterizing a cohort, this favors observing many individuals briefly over tracking a few for long. The result joins a growing body of work in which deep and foundation models, fairly benchmarked, fail to beat deliberately simple baselines. We add a concrete mechanism for the over-optimism: a models encoding of time can leak the very quantity it predicts, which backward-looking evaluation mistakes for learned biology, so only evaluation fixed to the moment of prediction is trustworthy.

animal behavior and cognition↗

bioRxiv2026

A Computational Framework for Extracting Mechanistic Hypotheses from Quantitative Data of Morphological Dynamics

Advances in live-cell imaging and image analysis have made it possible to quantitatively measure the spatiotemporal morphological dynamics of biological phenomena at scale. However, a general framework is still lacking for systematically extracting, from the resulting multivariate data, which relationships between phenotypic characters are mechanistically interpretable and which gene perturbations disrupt those relationships. Here, we propose a computational framework for extracting mechanistic hypotheses and candidate genes from quantitative data of morphological dynamics. First, we detect reproducible correlations between phenotypic characters in wild-type data and interpret them as mechanistic hypotheses in light of existing knowledge. Next, we perform outlier analysis on data obtained under gene perturbation and extract, as candidates, genes that selectively disrupt relationships between phenotypic characters maintained in the wild type. We further integrate the extracted relationships into a spatiotemporal network to provide an overview of how phenotypic characters are linked across the developmental process. As a proof of concept, we applied the framework to quantitative data on nuclear division dynamics during early embryogenesis in Caenorhabditis elegans and recovered relationships between phenotypic characters consistent with known mechanisms while prioritizing candidate genes. This framework provides a useful basis for efficiently generating testable mechanistic hypotheses from quantitative data of morphological dynamics. Author SummaryHow does a single cell give rise to a complex organism? Answering this question requires understanding not only which genes are active, but how the physical behavior of cells--their shapes, positions, and movements--is coordinated across time and space. Live-cell imaging now allows researchers to measure these morphological dynamics in quantitative detail, yet extracting biological meaning from the resulting large, high-dimensional datasets remains a challenge. Here we present a computational framework that addresses this challenge by treating correlations between quantitative morphological measurements as windows into the underlying biological machinery. Applied to the nematode Caenorhabditis elegans, a powerful model organism whose early development is exquisitely reproducible, our approach automatically identifies pairs of cellular measurements that reliably co-vary in normal embryos and interprets these relationships as reflecting shared biological mechanisms. When genes are inactivated one at a time and the resulting embryos deviate from the expected co-variation, those genes are flagged as candidates for the disrupted mechanism. In a systematic test using embryos in which 263 genes had been individually inactivated, the framework correctly prioritized genes with known roles in spindle positioning and cell polarity. By converting large-scale morphodynamic datasets into a network of testable mechanistic hypotheses, this framework offers a broadly applicable strategy for moving from quantitative phenotyping to mechanistic understanding across diverse biological systems.

Systems Biology↗

bioRxiv2026

Divergence of Cortical Force-Generating Mechanisms Underlies Differences in Spindle Behavior between C. elegans and C. inopinata

Microtubule-dependent pronuclear migration and mitotic spindle positioning are fundamental processes during the first embryonic division in many animals. In the one-cell embryo of Caenorhabditis elegans, these events are regulated by well-characterized pulling forces acting on astral microtubules, including cortical forces mediated by the G-GPR-LIN-5 dynein complex. Although the overall framework of these dynamics is conserved, recent studies have revealed substantial interspecies variation in their regulation. Here, we investigated nuclei and mitotic spindle behaviors in one-cell embryos of Caenorhabditis inopinata, the closest known relative of C. elegans, using live-cell imaging and functional perturbation. We found that C. inopinata embryos exhibit altered pronuclear migration, reduced anaphase spindle oscillations, and slower centrosome diffusion during telophase compared with C. elegans. These differences suggest weaker cortical pulling forces. Functional analyses using RNA interference showed that GPR retains its essential role in force generation, whereas the contribution of the microtubule depolymerizing kinesin KLP-7 is reduced in C. inopinata. Our results point to evolutionary changes in microtubule-regulated spindle dynamics, and provide insight into how conserved cellular processes can diversify through subtle changes in their underlying mechanisms.

cell biology↗

bioRxiv2026

Image-scanning light-sheet microscopy for high-speed volumetric imaging of complex biological dynamics

Volumetric fluorescence microscopy is a powerful method for studying complex biological systems because it enables comprehensive observation of structural and physiological dynamics. In particular, light-sheet microscopy (LSM) is a leading option for real-time volumetric fluorescence imaging as it combines high imaging speed, low phototoxicity, minimal photobleaching, high spatiotemporal resolution, and low computational burden. To capture fast biological events, various efforts have been made to improve the imaging speed of volumetric fluorescence microscopy, including LSM. However, existing approaches entail significant trade-offs that make routine volumetric imaging at and beyond video rates challenging under practical conditions. Here, we introduce image-scanning LSM, a method that substantially increases the volumetric imaging speed achievable with LSM while preserving key performance metrics, such as spatial resolution and photon efficiency, as well as accessibility. Our implementation, termed image-scanning oblique plane (ISOP) microscopy, enables volumetric fluorescence imaging at up to 1,000 volumes per second with submicrometer lateral spatial resolution. We demonstrate the broad utility of ISOP microscopy by recording and analyzing the dynamics of behaving and rapidly moving organisms.

bioengineering↗

bioRxiv2025

The transsulfuration pathway suppresses the embryonic lethalphenotype of glutathione reductase mutants in Caenorhabditis elegans

The gsr-1 gene encodes the only glutathione reductase in Caenorhabditis elegans and gsr-1 loss of function alleles have a fully penetrant embryonic lethal phenotype. Therefore, maintenance of glutathione redox homeostasis is essential for nematode survival. We report here that impairment of the nonsense-mediated mRNA decay (NMD) pathway suppresses the embryonic lethality of gsr-1 mutants, allowing their normal development and growth. This NMD pathway dependent suppression requires cth-1 and cth-2 that encode, respectively, two isoforms of cystathionine-{gamma}-lyase that catalyze the conversion of cystathionine to cysteine through the transsulfuration pathway. Interestingly, the thioredoxin system that can also provide cysteine through the cystine reduction pathway is not required for the suppression of the lethal phenotype of gsr-1 embryos when the NMD pathway is inactivated. Together, our data indicate that increasing the activity of the reverse transsulfuration pathway can compensate the detrimental effect of the gsr-1 mutation, raising the interesting question of why C. elegans has not preserved such compensatory mechanism to avoid the embryonic lethality of these mutants. HighlightsO_LIA novel cryptic deletion in the smg-3 gene suppresses the embryonic lethality of C. elegans gsr-1 mutants. C_LIO_LIInactivation of the nonsense-mediated mRNA decay (NMD) pathway allows survival of gsr-1 mutant worms. C_LIO_LIGenetic impairment of the transsulfuration pathway restores the embryonic lethal phenotype in gsr-1; smg-3 mutants. C_LI

genetics↗

bioRxiv2024

Spatial organization of supercoil dynamics during DNA replication

Progression of DNA replication inevitably generates helical tension and resulting super-helical structures, or supercoils, that originate from the double helix of DNA. As DNA polymerases progress, negative supercoils accumulate in the wake of the replication fork, thereby impeding fork progression unless the supercoils are resolved topologically. Using super-resolution microscopy combined with spatial distribution analysis, here we describe that SMC5/6-mediated confinement of negative supercoils lies at the basis of releasing them by topoisomerase Top2A. Along with DNA replication, SMC5/6 progressively associates with chromatin and locally increases the density of supercoil clusters behind the fork, allowing Top2A to efficiently target and release the accumulated supercoils. These processes are essential to complete DNA replication prior to mitosis and therefore to ensure genome stability. Remarkably, we found that HeLa cells over-accumulate poorly confined negative supercoils beyond the processing capacity of cellular SMC5/6, which may exemplify the condition associated with genome instability of cancer cells.

cell biology↗

bioRxiv2024

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 train three existing automated cell identification algorithms to, for the first time, enable accuracy in neural 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 (a) study neuroanatomical organization and neural activity across diverse experimental paradigms, (b) develop and benchmark algorithms for automated neuron detection, segmentation, cell identification, tracking, and activity extraction, and (c) inform models of neurobiological development and function.

neuroscience↗

bioRxiv2023

Transcription-coupled changes in higher-order genomic structure and transcription hub viscosity prolong enhancer-promoter connectivity

The orchestration of our genes heavily relies on a coordinated communication between enhancers and promoters, yet how this dynamic interplay remains elusive while transcription is active. Here, we investigated enhancer-promoter (E-P) interactions and relative to transcriptional bursting in mouse embryonic stem cells using sequential DNA/RNA/immunofluorescence (IF)-FISH analyses and computational simulations. Our data reveal that the active state of specific genes is characterized by higher-order genomic structures and local condensates of transcriptional regulatory factors, leading to an elevation in local viscosity that highly stabilizes the duration of E-P interactions. Our study underscores the pivotal role of viscosity in transcriptional dynamics and paves the way for a more nuanced understanding of gene-specific regulatory mechanisms.

molecular biology↗

bioRxiv2023

Volumetric trans-scale imaging of massive quantity of heterogeneous cell populations in centimeter-wide tissue and embryo

We established a volumetric trans-scale imaging system with an ultra-large field-of-view (FOV) that enables simultaneous observation of millions of cellular dynamics in centimeter-wide three-dimensional (3D) tissues and embryos. Using a custom-made giant lens system with a magnification of 2x and a numerical aperture (NA) of 0.25, and a CMOS camera with more than 100 megapixels, we built a trans-scale scope AMATERAS-2, and realized fluorescence imaging with a transverse spatial resolution of approximately 1.1 {micro}m across an FOV of approximately 1.5 x 1.0 cm2. The 3D resolving capability was realized through a combination of optical and computational sectioning techniques tailored for our low-power imaging system. We applied the imaging technique to 1.2 cm-wide section of mouse brain, and successfully observed various regions of the brain with sub-cellular resolution in a single FOV. We also performed time-lapse imaging of a 1-cm-wide vascular network during quail embryo development for over 24 hours, visualizing the movement of over 4.0 x 105 vascular endothelial cells and quantitatively analyzing their dynamics. Our results demonstrate the potential of this technique in accelerating production of comprehensive reference maps of all cells in organisms and tissues, which contributes to understanding developmental processes, brain functions, and pathogenesis of disease, as well as high-throughput quality check of tissues used for transplantation medicine.

developmental biology↗

bioRxiv2023

Trans-scale live imaging of an E5.5 mouse embryo using incubator-type dual-axes light-sheet microscopy

We report our success in simultaneously tracking tissue formation and single-cell migration in a mouse embryo on embryonic day 5.5 for 12 h. The microscope, incubator, and observation protocols were comprehensively specialized and optimized to achieve this. The present system revealed new phenomena that had not previously been observed and promises to elucidate the mechanism of mouse embryonic development in the future.

developmental biology↗

bioRxiv2023

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, and glutamatergic neuron marker gene mix (slc17a6a, slc17a6b, slc17a7a, and slc17a7b) in the adult zebrafish brain using in situ hybridization. The results are summarized as an expression atlas in 19 coronal planes of the forebrain. Furthermore, the scan data of all sections were made publicly available as a database. Based on these data, we performed detailed neuroanatomical analyses of the hypothalamus. By scrutinizing and comparing the expression patterns of neuropeptides, we found that several regions described as one nucleus in the reference zebrafish brain atlas contain two or more subregions with significantly different neuropeptide/neurotransmitter expression profiles, and we proposed them as novel subnuclei. Subsequently, the expression data obtained in this study were compared with those in mice, and a cluster analysis was performed to examine the similarities. As a result, several nuclei in zebrafish and mice were clustered in close vicinity: zebrafish ventral part of the anterior part of the parvocellular preoptic nucleus (PPav)/magnocellular preoptic nucleus (PM) and mouse paraventricular hypothalamic nucleus (Pa), zebrafish posterior part of the parvocellular preoptic nucleus (PPp) and mouse medial preoptic area (MPA), zebrafish dorsal part of the ventral zone of periventricular hypothalamus (Hvd)/anterior tuberal nucleus (ATN) and mouse ventromedial hypothalamic nucleus (VMN). The present expression atlas, database, and anatomical findings will contribute to future neuroscientific research using zebrafish. Key pointsO_LIThe expression of 38 neuropeptides and GABAergic/glutamatergic neuronal marker genes in adult zebrafish forebrain was examined and compiled as an atlas. C_LIO_LIAll scanned brain section data were published as a database. C_LIO_LIBased on the expression data obtained, multiple subnuclei in the zebrafish hypothalamus were proposed, and comparisons with the mouse hypothalamus were conducted. C_LI

neuroscience↗

bioRxiv2023

Ontology for Cellular Senescence Mechanisms

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. We described the mechanisms as causal relationships of processes and modeled 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 disease 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.

cell biology↗

bioRxiv2022

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 the 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 high spatiotemporal resolution, 0.5 m thickness of optical sections, and 30-second intervals of recordings. By comparing the morphodynamics between the embryos, we found high reproducibility of the dynamics. The median correlation coefficient of morphological features, such as volume and surface area, was 0.09, suggesting high reproducibility. Furthermore, the morphodynamics was significantly different from the other cell types in all cells before the onset of gastrulation, indicating high uniqueness of the dynamics. Furthermore, physical cell-cell contacts were quantified to analyze inter-cell relationships, and their reproducibility was calculated between the embryos. The number of contacts formed in every embryo was less than half of all detected contacts because variability in division timings and cell arrangements produced various combinations of brief contacts. In contrast, the area of contacts formed in every embryo occupied 96% of the total area, suggesting the high reproducibility of spatial occupancies and adjacency relationships of the cells. Our data further allowed detailed analyses of specific cellular features. By normalizing the sphericity dynamics, we found a significant increase in sphericity 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. Therefore, we demonstrate that our data provides a precise understanding of the cellular processes and could potentially be used to gain further insight into developmental mechanisms.

developmental biology↗

bioRxiv2022

The centromere/kinetochore is assembled through CENP-C oligomerization

The kinetochore is an essential protein complex for accurate chromosome segregation. The constitutive centromere-associated network (CCAN), a subcomplex of the kinetochore, associates with centromeric chromatin providing a platform for the kinetochore assembly. A CCAN protein, CENP-C, is thought to be a central hub for the centromere/kinetochore organization. However, the crucial role of CENP-C in centromeres remains to be elucidated. Here, we demonstrated that both the CCAN-binding domain and C-terminal Cupin domain of CENP-C are necessary and sufficient for chicken CENP-C function. Our structural and biochemical analyses revealed that the Cupin domain of chicken and human CENP-C is self-oligomerization domain, which is crucial for centromeric chromatin organization. CENP-C mutants lacking the oligomerization interface cause mislocalization of CCAN and cell death. Based on these results, we conclude that the CENP-C oligomerization plays a crucial role in centromere function via providing the robust centromeric chromatin in vertebrate cells.

cell biology↗

bioRxiv2022

Single-molecule tracking of Nanog and Oct4 in mouse embryonic stem cells

Nanog and Oct4 are core transcription factors in a gene regulatory network that regulate hundreds of target genes for pluripotency maintenance in mouse embryonic stem cells. To understand their function as a gatekeeper or a pioneer factor at the molecular scale, we quantified the residence time on target loci, fluctuation at the loci, and interaction clustering by visualizing single molecules of Nanog and Oct4 in a living nucleus during the pluripotency loss. Interestingly, Nanog interacted longer with its target loci in the lower Nanog expression state or at the onset of differentiation, indicating the possibility of a new feedback mechanism to maintain Nanog expression. The interaction time of Nanog and Oct4 corresponded to their fluctuation and interaction clustering, which depended on their expression or differentiation state, respectively. The DNA viscoelasticity near the Oct4 target locus remained flexible during the differentiation, reflecting its role as a pioneer factor. Based on these results, we propose a new feedback mechanism for pluripotency maintenance in which Nanog function is prolonged, corresponding to chromatin condensation, and Oct4 reopens the condensation.

biophysics↗

bioRxiv2022

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

Hi-C is a widely used assay for studying 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 an input Hi-C matrix data into the polymer models dynamics, structural conformations, and rheological features. The updated optimization algorithm to regenerate a highly similar Hi-C matrix provides a fast and accurate optimal solution compared to the previous version by eliminating a computational bottleneck in the iterative optimization process. Besides, we newly set up the availability on Google Colab workflow to run, easily change parameters and check the results in the notebook. Overall, PHi-C2 can be a valuable tool to mine the dynamic 3D genome state embedded in Hi-C data. Availability and ImplementationPHi-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. Without preparing a Python environment, PHi-C2 can run on Google Colab (https://bit.ly/3rlptGI). Contactsoya.shinkai@riken.jp or sonami@riken.jp

bioinformatics↗