Biology subjects

Hiroi, N.

Publications and source records attributed to Hiroi, N..

13 recordsLinked to original sources

bioRxiv2026

TabularQual: A spreadsheet-based format for annotating and curating logical models in SBML-qual

Logical models are widely used to study regulatory and signaling systems, yet their reuse, annotation, and exchange across tools remain challenging. Although SBML Level 3 Qualitative Models (SBML-qual) provides a standard representation, its XML-based syntax is difficult to inspect and edit directly. Here we introduce TabularQual, a spreadsheet-based, community-driven representation for Boolean and multi-valued logical models, together with a bidirectional converter between spreadsheets and SBML-qual. The converter is accessible programmatically and via a web interface to support diverse user workflows. We further describe two integration strategies that enable existing modeling tools to operate with TabularQual, either through SBML-qual exchange or via direct support. Case studies using the Stress Knowledge Map and CaSQ demonstrate how this integration supports model construction, curation, and reuse. TabularQual provides a practical bridge between human-readable model representations and standardized executable formats, supporting reproducibility, interoperability, and community-driven model development.

systems biology↗

bioRxiv2026

User-driven development and evaluation of an agentic framework for analysis of large pathway diagrams

As biomedical knowledge keeps growing, resources storing available information multiply and grow in size and complexity. Such resources can be in the format of molecular interaction maps, which represent cellular and molecular processes under normal or pathological conditions. However, these maps can be complex and hard to navigate, especially to novice users. Large Language Models (LLMs), particularly in the form of agentic frameworks, have emerged as a promising technology to support this exploration. In this article, we describe a user-driven process of prototyping, development, and user testing of Llemy, an LLM-based system for exploring these molecular interaction maps. By involving domain experts from the very first prototyping in the form of a hackathon and collecting both fine-grained and general feedback on more refined versions, we were able to evaluate the perceived utility and quality of the developed system, in particular for summarising maps and pathways, as well as prioritise the development of future features. We recommend continued user-driven development and benchmarking to keep the community engaged. This will also facilitate the transition towards open-weight LLMs to support the needs of the open research environment in an ever-changing technology landscape.

bioinformatics↗

bioRxiv2026

Neonatal social communication and single genes predict the variability of post-pubertal social behavior in a mouse model of paternal 15q11-13 duplication

Mental illnesses associated with high-risk copy number variations (CNVs) are characterized by incomplete penetrance and variable severity, with their underlying mechanisms remaining inadequately understood. We hypothesized that such phenotypic variability is evident from the neonatal stage and is, at least in part, attributable to individual differences in the expression levels of CNV-encoded genes in the brain. We conducted an analysis of the quantitative and functional structure of neonatal social communication, assessed post-pubertal social interaction, and evaluated the brain expression levels of genes within the same cohort of a mouse model of paternal human 15q11-13 duplication, a high-risk factor variably associated with neurodevelopmental disorders. Subsequently, computational methods were utilized to identify predictive variables for the variability of post-pubertal social interaction. Mice harboring the 15q11-13 duplication exhibited distinctive call sequences characterized by diverse connections, which lacked the incentive value necessary for effective social communication with mother mice. The neonatal call sequences and the expression levels of Magel2, along with, to a lesser extent, Herc2 and Ndn, in the prefrontal cortex of the 15q11-13 duplication model were predictive of post-pubertal social interaction. Our findings demonstrate that variability in post-pubertal social interaction--a dimensional characteristic of neurodevelopmental disorders--can be predicted by the variability of neonatal social communication and is influenced by the expression levels of specific CNV-encoded genes in the prefrontal cortex. This computational approach has the potential to predict the developmental trajectories of various dimensions of mental illness among CNV carriers in humans and to identify CNV-encoded driver genes in preclinical models, thereby providing potential mechanistic bases for the development of gene-based therapeutic strategies.

neuroscience↗

bioRxiv2025

Tbx1 heterozygosity in the oligodendrocyte lineage has distinct effects on myelinated axons in the fimbria and on behaviors related to neurodevelopmental disorders in mice.

Constitutive heterozygosity of Tbx1, a T-box transcription factor gene located within the 22q11.2 deletion region, results in behavioral deficits and altered composition of myelinated axons in the fimbria, together with reduced levels of an oligodendrocyte precursor cell (OPC) marker, in mice. However, the cellular origins of these effects and the extent to which axonal changes causally contribute to behavioral impairments remain unclear. We hypothesized that Tbx1 deficiency specifically within the oligodendrocyte lineage contributes to myelin and behavioral phenotypes. To test this hypothesis, we first demonstrated through in vitro siRNA knockdown that Tbx1 regulates both OPCs and mature oligodendrocytes. Subsequently, we assessed the impact of Tbx1 heterozygosity initiated in OPCs on behavioral and myelin phenotypes in male conditional PdgfrCre;Tbx1+/flox mice. These mice exhibited Cre-mediated recombination in Pdgfr-expressing brain regions and in the OPC progeny within the fimbria. At one month of age, the mutants displayed a higher rate of spontaneous alternation at the longest inter-trial interval in the T-maze compared to their wild-type littermates--an effect that was dissipated at two months. No significant phenotypic abnormalities were observed in conditional PdgfrCre;Tbx1+/flox mice regarding neonatal ultrasonic vocalizations, social interaction, novel object approach, anxiety-like behavior (elevated plus maze), or open-field locomotion and thigmotaxis. Electron microscopic analysis revealed a compositional shift in myelinated axons within the fimbria of adult male mutants, characterized by an increased number of myelinated axons in the 300-800 nm diameter range and a decreased number in the [~]1,200 nm and [~]1,400 nm ranges, with myelin thickness remaining unchanged across diameters. These findings indicate that Tbx1 heterozygosity in the oligodendrocyte lineage leads to a selective shift towards smaller myelinated axons in the fimbria and a transiently higher level of capacity for working memory and cognitive flexibility. However, it does not replicate the full spectrum of myelination abnormalities or the broader cognitive and social deficits observed in constitutive Tbx1 heterozygotes, suggesting that Tbx1 deficiency in non-oligodendrocyte lineage cells may lead to altered myelination and neurodevelopmental behavioral impairments.

neuroscience↗

bioRxiv2025

An interplay between cytoplasmic flow and cell morphology during cytokinesis simulated by the moving-particle semi-implicit method

Cells are composite mechanical systems: a viscoelastic cytoplasm enclosed by a deformable cell cortex. These two components exchange forces continuously--fluid motion deforms the cortex, and cortical deformation in turn redirects intracellular flow. Yet most cellular mechanics simulations treat either the fluid or the cortex in isolation, leaving their mechanical interplay largely unexplored. To address this gap, we developed a fluid-structure interaction framework based on the moving-particle semi-implicit (MPS) method that solves the coupled dynamics of cytoplasmic flow, internal pressure, and cortical elasticity. We applied this framework to cytokinesis, focusing on how the cleavage plane is positioned. While the mitotic spindle is known to specify the furrow site, prior work has emphasized biochemical cues emanating from the spindle, whereas a direct mechanical cue has been difficult to interrogate. Our simulations show that spindle elongation generates cytoplasmic flows that create a pressure minimum near the spindle midzone; when the cortex is modeled as an elastic shell, this pressure landscape drives a localized cortical invagination at that site. We therefore propose that spindle-driven cytoplasmic flow provides a mechanical positional cue for cleavage-furrow initiation. Author SummaryDividing cells exhibit two contrasting properties: dynamic state changes and the maintenance of homeostasis. During cell division, a dividing cell breaks its identity while successful daughter cells inherit a certain set of its components for survival. Heterogeneous physical properties such as cell shape, cytoplasmic flow, and internal pressure interact to maintain an appropriate range of cellular conditions. The interaction of such physical components is highly dynamic; therefore, simulation studies play an important role in understanding the mechanisms. We constructed a model based on the moving-particle semi-implicit method that recapitulates the behavior of highly dynamic physical objects such as cytoplasmic fluid with practical computational time. The simulation showed that the change in cell shape is caused by internal cell pressure, which is evoked by cytoplasmic flow during elongation of spindle microtubules. The developed simulation platform provided a tool to integrate physical measurements to understand the mechanisms that balance physical dynamics during cell division. Such quantitative simulation combined with the data from molecular or genetic experiments may predict how internal dynamics maintain homeostasis during drastic changes in the cell state.

systems biology↗

bioRxiv2023

Structural alterations in the amygdala and impaired social incentive learning in a mouse model of a genetic variant associated with neurodevelopmental disorders

Copy number variants (CNVs) are robustly associated with psychiatric disorders and their dimensions and changes in brain structures and behavior. However, as CNVs contain many genes, the precise gene-phenotype relationship remains unclear. Although various volumetric alterations in the brains of 22q11.2 CNV carriers have been identified in humans and mouse models, it is unknown how the genes in the 22q11.2 region individually contribute to structural alterations and associated mental illnesses and their dimensions. Our previous studies have identified Tbx1, a T-box family transcription factor encoded in 22q11.2 CNV, as a driver gene for social interaction and communication, spatial and working memory, and cognitive flexibility. However, it remains unclear how TBX1 impacts the volumes of various brain regions and their functionally linked behavioral dimensions. In this study, we used volumetric magnetic resonance imaging analysis to comprehensively evaluate brain region volumes in congenic Tbx1 heterozygous mice. Our data show that the volumes of anterior and posterior portions of the amygdaloid complex and its surrounding cortical regions were reduced in Tbx1 heterozygous mice. Moreover, we examined the behavioral consequences of an altered volume of the amygdala. Tbx1 heterozygous mice were impaired for their ability to detect the incentive value of a social partner in a task that depends on the amygdala. Our findings identify the structural basis for a specific social dimension associated with loss-of-function variants of TBX1 and 22q11.2 CNV.

neuroscience↗

bioRxiv2021

Transcriptional regulation of neonatal neural stem cells is a determinant of social behavior

Rare gene variants confer a high level of penetrance to neurodevelopmental disorders, but their developmental origin and cellular substrates remain poorly understood. To address this limitation, we explored the role of TBX1, a gene encoded in a rare copy number variant, in cell and mouse models. Here, we report that neonatal Tbx1 deficiency contributes to defective peripubertal social behavior and impairs the proliferation of neonatal neural stem/progenitor cells. Moreover, TBX1 transcriptionally regulates genes linked to post-embryonic neurogenesis and neurodevelopmental disorders associated with other rare gene variants. Our data indicate a precise time window and cell type through which the social dimension is altered by a gene encoded in a rare CNV and provide a potential common mechanistic basis for a group of neurodevelopmental disorders. One-Sentence SummaryTbx1, a gene affecting neonatal stem cell proliferation, influences peripubertal social behavior.

neuroscience↗

bioRxiv2021

Tbx1, a 22q11.2-encoded gene, is a link between alterations in fimbria myelination and cognitive speed in mice

Copy number variants (CNVs) have provided a reliable entry point to identify structural correlates of atypical cognitive development. Hemizygous deletion of human chromosome 22q11.2 is associated with impaired cognitive function; however, the mechanisms by which numerous genes encoded in this CNV contribute to cognitive deficits via diverse structural alterations in the brain remain unclear. This study aimed to determine the cellular basis of the link between alterations in brain structure and cognitive functions in a mouse model. The heterozygosity of Tbx1, a 22q11.2 gene, altered the composition of myelinated axons in the fimbria, reduced oligodendrocyte production capacity, and slowed the acquisition of spatial memory and cognitive flexibility. Our findings provide a cellular basis for specific cognitive dysfunctions that occur in patients with loss-of-function TBX1 variants and 22q11.2 hemizygous deletion. TeaserA risk gene for autism alters myelin composition in the hippocampal connection and slows cognitive speed.

neuroscience↗

bioRxiv2020

COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms

We describe a large-scale community effort to build an open-access, interoperable, and computable repository of COVID-19 molecular mechanisms - the COVID-19 Disease Map. We discuss the tools, platforms, and guidelines necessary for the distributed development of its contents by a multi-faceted community of biocurators, domain experts, bioinformaticians, and computational biologists. We highlight the role of relevant databases and text mining approaches in enrichment and validation of the curated mechanisms. We describe the contents of the Map and their relevance to the molecular pathophysiology of COVID-19 and the analytical and computational modelling approaches that can be applied for mechanistic data interpretation and predictions. We conclude by demonstrating concrete applications of our work through several use cases and highlight new testable hypotheses.

systems biology↗

bioRxiv2020

Maternal approach behaviors toward neonatal calls are impaired by mother's experiences of raising pups with a risk gene variant for autism

How the intrinsic sequence structure of neonatal mouse pup ultrasonic vocalization (USV) and maternal experiences determine maternal behaviors in mice is poorly understood. Our previous work showed that pups with a Tbx1 heterozygous (HT) mutation, a genetic risk for autism spectrum disorder (ASD), emit altered call sequences that do not induce maternal approach behaviors in C57BL6/J mothers. Here, we tested how maternal approach behaviors induced by wild-type and HT USVs are influenced by the mothers experience in raising pups of these two genotypes. The results showed that wild-type USVs were effective in inducing maternal approach behaviors when mothers raised wild-type but not HT pups. The USVs of HT pups were ineffective regardless of whether mothers raised HT or wild-type pups. However, the sequence structure of pup USVs had no effect on the general, non-directional incentive motivation of maternal behaviors. Our data show how the mothers experience with a pup with a genetic risk for ASD alters the intrinsic incentive values of USV sequences in maternal approach behaviors.

developmental biology↗

bioRxiv2018

Predicting the future direction of cell movement with convolutional neural networks

Image-based deep learning systems, such as convolutional neural networks (CNNs), have recently been applied to cell classification, producing impressive results; however, application of CNNs has been confined to classification of the current cell state from the image. Here, we focused on cell movement where current and/or past cell shape can influence the future cell fate. We demonstrate that CNNs prospectively predicted the future direction of cell movement with high accuracy from a single image patch of a cell at a certain time. Furthermore, by visualizing the image features that were learned by the CNNs, we could identify morphological features, e.g., the protrusions and trailing edge that have been experimentally reported to determine the direction of cell movement. Our results indicate that CNNs have the potential to predict the future cell fate from current cell shape, and can be used to automatically identify those morphological features that influence future cell fate.

systems biology↗

bioRxiv2018

Transcriptome analysis of Pv11 cells infers the mechanism of desiccation tolerance and recovery

The larvae of the African midge, Polypedilum vanderplanki, can enter an ametabolic state called anhydrobiosis to conquer fatal desiccation stress. The Pv11 cell line, derived from embryos of the midge, shows desiccation tolerance by pretreatment with trehalose before desiccation; they can resume proliferation after rehydration. To address the underlying molecular mechanisms, we desiccated Pv11 cells after pretreatment with the medium containing trehalose and induced proliferation by rehydration. We collected the cells at each before and after desiccation and rehydration step and performed CAGE-seq of mRNA of those cells. By analysing differentially expressed genes (DEGs) among the results of CAGE-seq, we detected 384 DEGs after trehalose treatment and 14 DEGs after rehydration. Hierarchical clustering of the identified DEGs indicated that rehydration returns their expression pattern to that in the control culture state. DEGs involved in various stress responses, detoxification of harmful chemicals, and regulation of oxidoreduction were upregulated by trehalose treatment. DEGs for rehydration supported that DNA repair is one of the potential mechanisms involves recovery. This study provided initial insight into the molecular mechanisms underlying the extreme desiccation tolerance of Pv11 cells with a potential for proliferation following rehydration.

genomics↗

bioRxiv2018

Development of Convolutional Neural Network Based Instance Segmentation Algorithm to Acquire Quantitative Criteria of Mouse Development

In embryology, analytical approaches such as segmentation are applied to acquiring quantitative criteria from time-series three-dimensional microscopic images. When used to segment cells or intracellular organelles, several current machine learning techniques outperform traditional image processing algorithms. However segmentation algorithms still have unsolved problems, especially in bioimage processing. The most critical issue is that the existing algorithms can perform only semantic segmentation, which distin-guishes whether a pixel is within an object (for example, nucleus) or not. In this study, we implemented a novel segmentation algorithm, based on deep learning, which segments each nucleus and adds different labels to the detected objects. This segmentation algorithm is called instance segmentation. Our instance segmentation algorithm, implemented as a neural network, which we named QCA Net, substantially out-performed 3D U-Net, which is the best semantic segmentation algorithm that uses deep learning. Using QCA Net, we quantified the nuclear number, volume, surface area, and center of gravity coordinates during the development of mouse embryos. In particular, QCA Net distinguished nuclei of embryonic cells from those of polar bodies formed in meiosis. We consider that QCA Net can greatly contribute to bioimage segmentation in embryology by generating quantitative criteria from segmented images.

systems biology↗