Biology subjects

Okumura, H.

Publications and source records attributed to Okumura, H..

8 recordsLinked to original sources

bioRxiv2025

Integrated structural dynamics uncover new modes of B12 photoreceptor activation

Photoreceptor proteins initiate, regulate and control fundamental biological processes such as vision, photosynthesis and circadian rhythms1. A large photoreceptor subfamily uses vitamin B12 derivatives for light sensing2, contrasting with the well-established mode of action of these organometallic derivatives in thermally activated enzymatic reactions3. The molecular mechanism of B12 photoreception and how this differs to the thermal pathways remain unknown. Here we provide a detailed spatio-temporal description of photoactivation in the prototypical tetrameric B12 photoreceptor CarH4,5 from nanoseconds to seconds by using an integrative approach, combining time- and temperature-resolved structural and spectroscopic methods with quantum chemical calculations. High resolution structural snapshots of key intermediates illustrate how photocleavage of a Co-C bond triggers a pathway of structural changes that propagate throughout CarH from the B12 chromophore, via a previously unknown adduct, to finally cause tetramer dissociation. These unique intermediates, which differentiate CarH from thermally-activated B12 enzymes, steer the photoactivation pathway and act as the molecular bridge between photochemical and photobiological timescales. Our results offer a spatio-temporal understanding of CarH photoactivation and pave the way for designing and optimising B12-dependent photoreceptors for future optogenetic applications.

biophysics↗

bioRxiv2025

Twinfilin-1 phosphorylation in reelin signaling regulates actin dynamics and spine development

Reelin is an extracellular glycoprotein essential for neuronal migration, spine development, and synaptic plasticity. Impaired reelin signaling is linked to neurological disorders, including schizophrenia and autism. While reelin mutant (reeler) mice exhibit behavioral deficits associated with impaired spine formation, the underlying molecular mechanisms remain unclear. We identified Twinfilin-1 (Twf1) as a downstream effector of reelin signaling via phosphoproteomic analysis, based on its reduced tyrosine phosphorylation in reeler mice. We found that Src regulated Twf1 phosphorylation at tyrosine 309, and reelin stimulation increased Twf1 phosphorylation in neurons, an effect blocked by the Src inhibitor PP2. A phospho-resistant Twf1 mutant (Twf1 Y309F) showed reduced capping protein binding and a lower F/G-actin ratio. Twf1Y309F mice exhibited cognitive deficits, reduced spine density, smaller spine head size, and a decreased F/G-actin ratio in synaptosomes. These findings highlight Twf1 phosphorylation as a key component of reelin signaling involved in actin remodeling and spine development.

neuroscience↗

bioRxiv2025

Uromodulin velcro sheets and their interaction with uropathogenic E. coli

Homopolymeric uromodulin (UMOD), the most abundant protein in human urine, protects against urinary tract infections (UTI) by acting as a decoy for uropathogenic E. coli (UPEC). Using cryo-electron tomography (ET), we show that urinary UMOD filaments naturally form sheets that interact with UPEC type I pili. Sheet formation is salt-dependent, and we resolve their high-resolution structure using single-particle cryo-electron microscopy (EM). This reveals a lateral interface between polymers, whose mutation disrupts UMOD filament bundle formation in mammalian cells. Branchless egg coat protein ZPD also forms sheets, and cryo-ET of elastase-treated UMOD indicates that absence of N-terminal branches promotes the stacking of UMOD-like protein sheets into thick 3D matrices. These results rationalize early observations of salt-dependent aggregation of UMOD, explain how UMOD can assemble into extended velcro-like structures that efficiently inactivate a multitude of adhesive UPEC pili, and suggest how UMOD-like molecules can generally organize into supramolecular structures of variable thickness.

biophysics↗

bioRxiv2024

Cell position-based evaluation of mechanical features of cells in multicellular systems

Measurement of mechanical forces of cell-cell interactions is important for studying the emergence of diverse three-dimensional morphologies of multicellular organisms. We previously reported an image-based statistical method for inferring effective pairwise forces of cell-cell interactions (i.e., attractive/repulsive forces), where a cell particle model was fitted to cell tracking data acquired by live imaging. However, because the particle model is a coarse-grained model, it remains unclear how the pairwise forces relates to sub-cellular mechanical components including cell-cell adhesive forces. Here we applied our inference method to cell tracking data generated by vertex models that assumed sub-cellular components. Through this approach, we investigated the relationship between the effective pairwise forces and various sub-cellular components: cell-cell adhesion forces, cell surface tensions, cell-extracellular matrix (ECM) adhesion, traction forces between cells and ECM, cell growth, etc. We found that the cell-cell adhesion forces were attractive, and both the cell surface tensions and cell-ECM adhesive forces were repulsive, etc. These results indicate that sub-cellular mechanical components can contribute to the effective attractive/repulsive forces of cell-cell interactions. This comprehensive analysis provides theoretical bases for linking the pairwise forces to the sub-cellular mechanical components: this showcase is useful for speculating the sub-cellular mechanical components from the information of cell positions, and for interpreting simulation results based on particle models.

biophysics↗

bioRxiv2024

Inferring extrinsic factor-dependent single-cell transcriptome dynamics using a deep generative model

1RNA velocity estimation helps elucidate temporal changes in the single-cell transcriptome. However, current methodologies for inferring single-cell transcriptome dynamics ignore extrinsic factors, such as experimental conditions and neighboring cell. Here, we propose ExDyn--a deep generative model integrated with splicing kinetics for estimating cell state dynamics dependent on extrinsic factors. ExDyn enables the counterfactual inference of cell state dynamics under different conditions. Among the extrinsic factors, ExDyn can extract key features which have large effects on cell state dynamics. ExDyn correctly estimated the difference in dynamics between two conditions and showed better accuracy over existing RNA velocity methods. ExDyn were utilized for unveiling the effect of PERK-knockout on neurosphere differentiation, hematopoietic stem cell differentiation driven by chromatin activity and the dynamics of squamous cell carcinoma cells dependent on colocalized neighboring cells. These results demonstrated that ExDyn is useful for analyzing key features in the dynamic generation of heterogeneous cell populations.

bioinformatics↗

bioRxiv2023

Effective mechanical potential of cell-cell interaction in tissues harboring cavity and in cell sheet toward morphogenesis

Measuring mechanical forces of cell-cell interactions is important for studying morphogenesis in multicellular organisms. We previously reported an image-based statistical method for inferring effective mechanical potentials of pairwise cell-cell interactions by fitting cell tracking data with a theoretical model. However, whether this method is applicable to tissues with non-cellular components such as cavities remains elusive. Here we evaluated the applicability of the method to cavity-harboring tissues. Using synthetic data generated by simulations, we found that the effect of expanding cavities was added to the pregiven potentials used in the simulations, resulting in the inferred effective potentials having an additional repulsive component derived from the expanding cavities. Interestingly, simulations by using the effective potentials reproduced the cavity-harboring structures. Then, we applied our method to the mouse blastocysts, and found that the inferred effective potentials can reproduce the cavity-harboring structures. Pairwise potentials with additional repulsive components were also detected in two-dimensional cell sheets, by which curved sheets including tubes and cups were simulated. We conclude that our inference method is applicable to tissues harboring cavities and cell sheets, and the resultant effective potentials are useful to simulate the morphologies.

biophysics↗

bioRxiv2022

The double-layered structure of amyloid-β assemblage on GM1-containing membranes catalytically promotes fibrillization

Alzheimers disease (AD) is associated with progressive accumulation of amyloid-{beta} (A{beta}) cross-{beta} fibrils in the brain. A{beta} species tightly associated with GM1 ganglioside, a glycosphingolipid abundant in neuronal membranes, promote amyloid fibril formation; therefore, they could be attractive clinical targets. However, the active conformational state of A{beta} in GM1-containing lipid membranes is still unknown. The present solid-state nuclear magnetic resonance study revealed a nonfibrillar A{beta} assemblage characterized by a double-layered antiparallel {beta}-structure specifically formed on GM1 ganglioside clusters. Our data show that this unique assemblage was not transformed into fibrils on GM1-containing membranes, but could promote conversion of monomeric A{beta} into fibrils, suggesting that a solvent-exposed hydrophobic layer provides a catalytic surface evoking A{beta} fibril formation. Our findings will offer structural clues for designing drugs targeting catalytically active A{beta} conformational species for the development of anti-AD therapeutics.

biophysics↗

bioRxiv2019

Effective physical properties of cell-cell interaction explain basic structural units of three-dimensional morphogenesis

Mechanical forces are critical for the emergence of diverse three-dimensional morphologies of multicellular systems. However, it remains unclear what kind of mechanical parameters at cellular level substantially contribute to tissue morphologies. This is largely due to technical limitations of live measurements of cellular forces. Here we developed a framework for inferring and modeling mechanical forces of cell-cell interactions. First, by analogy to coarse-grained models in molecular and colloidal sciences, we approximated cells as particles, where mean forces (i.e. effective forces) of pairwise cell-cell interactions are considered. Then, the forces were statistically inferred by fitting the mathematical model to cell tracking data. This method was validated by using synthetic cell tracking data resembling various in vivo situations. Application of our method to the cells in the early embryos of mice and the nematode Caenorhabditis elegans revealed that cell-cell interaction forces can be written as a pairwise potential energy in a manner dependent on cell-cell distances. Importantly, the profiles of the pairwise potentials were quantitatively different among species and embryonic stages, and the quantitative differences correctly described the differences of their morphological features such as spherical vs. distorted cell aggregates, and tightly vs. non-tightly assembled aggregates. We conclude that the effective pairwise potential of cell-cell interactions is a live measurable parameter whose quantitative differences can be a parameter describing three-dimensional tissue morphologies. Author summaryEmergence of diverse three-dimensional morphologies of multicellular organisms is one of the most intriguing phenomena in nature. Due to the complex situations in living systems (e.g. a lot of genes are involved in morphogenesis.), a model for describing the emergent properties of multicellular systems has not been established. To approach this issue, approximation of the complex situations to limited numbers of parameters is required. Here, we searched for mechanical parameters for describing morphologies. We developed a statistical method for inferring mechanical potential energy of cell-cell interactions in three-dimensional tissues; the mechanical potential is an approximation of various mechanical components such as cell-cell adhesive forces, cell surface tensions, etc. Then, we showed that the quantitative differences in the potential is sufficient to reproduce basic three-dimensional morphologies observed during the mouse and C. elegans early embryogenesis, revealing a direct link between cellular level mechanical parameters and three-dimensional morphologies. Our framework provides a noninvasive tool for measuring spatiotemporal cellular forces, which would be useful for studying morphogenesis of larger tissues including organs and their regenerative therapy.

biophysics↗