Biology subjects

Mochizuki, A.

Publications and source records attributed to Mochizuki, A..

16 recordsLinked to original sources

bioRxiv2025

Identifying Phenotype-Indicative Molecules from the Structure of Biochemical Reaction Networks

Multistability in chemical reaction networks (CRNs) is a key mechanism underlying the diversity in cellular phenotypes. Identifying the steady state a cell occupies requires measuring molecular concentrations. This in turn raises a fundamental question: which chemical species should be selected to reliably distinguish among multiple steady states? We introduce a network-structural approach for identifying indicator species--a subset of species whose concentrations alone suffice to identify which steady state the system occupies. By decomposing a CRN into subnetworks based on structural criteria and applying topological degree theory, we show that the concentrations within certain subnetworks uniquely determine those of all remaining species. These subnetworks thus provide indicator species that distinguish all possible steady states. Crucially, our method relies only on stoichiometric and regulatory information, without requiring kinetic parameters. Implemented via a computational algorithm, the framework is validated through numerical simulations and applied to biochemical networks. This work provides a principled strategy for steady-state identification in high-dimensional biochemical networks from partial observations, with potential applications in single-cell data analysis and biomarker discovery.

biophysics↗

bioRxiv2025

Network topology creates independent control of G2-M from G1-S checkpoints in the fission yeast cell cycle system

Physiological functions of cells arise from the dynamics of chemical reaction networks. The cell cycle of fission yeast is controlled by dynamical changes in two cyclin-dependent kinase (CDK)-cyclin complexes based on a complicated reaction network consisting of protein synthesis, complex formation, and degradation1,2. Each of the two checkpoints, G1-S and G2-M, is driven by an increase in the concentration of CDK-Cig2 and CDK-Cdc13, respectively. However, it is not understood how these complexes in the single connected network are controlled independently in a stage-specific manner. Here we theoretically predict that independent control of CDK-Cdc13 from CDK-Cig2 is achieved by the topology of the cell cycle network, and experimentally validate this prediction, while updating the network information by comparing predictions and experiments. We analyzed a known cell cycle network using a topology-based theory3-6 and revealed that the two CDK-cyclin complexes are included in different "regulatory modules", suggesting that the concentration of each CDK-cyclin complex is controlled independently from the other. Experimental validation confirmed that the concentration of CDK-Cdc13 is controlled by the Cdc13 synthesis rate, independently from CDK-Cig2, as predicted. Conversely, the Cig2 synthesis rate affected not only CDK-Cig2 but also CDK-Cdc13. The fact, however, indicates the necessity of updating the network. We theoretically predicted the existence of an unknown necessary reaction, a Cdc13 degradation pathway, and experimentally confirmed it. The prediction and validation approach using the topology-based theory proposes a new systems biology, which progresses by comparing network structures with manipulation experiments and updating network information.

systems biology↗

bioRxiv2024

Uncovering Bifurcation Behaviors of Biochemical Reaction Systems from Network Topology

The regulation of biological functions is achieved through the modulation of biochemical reaction network dynamics. The diversity of cell states and the transitions between them have been interpreted as bifurcations in these dynamics. However, due to the complexity of networks and limited knowledge of reaction kinetics, bifurcation behaviors in biological systems remain largely underexplored. To address this, we developed a mathematical method, Structural Bifurcation Analysis (SBA), which decomposes the system into substructures and determines important aspects of bifurcation behaviors--such as substructures responsible for bifurcation conditions, bifurcation-inducing parameters, and bifurcating variables--solely from network topology. We establish a direct relationship between SBA and classical bifurcation analysis, enabling the study of systems even in the presence of conserved quantities. Additionally, we provide a step-by-step bifurcation analysis for general use. We applied our method to the macrophage M1/M2 polarization system. Our analysis reveals that the network structure strongly constrains possible patterns of polarization. We also clarify the dependency of the M1/M2 balance on gene expression levels and predict the emergence of intermediate polarization patterns under gene deletions, including SOCS3, which are experimentally testable.

biophysics↗

bioRxiv2024

Quantification of Cyclin-CDK dissociation constants in living cells using fluorescence cross-correlation spectroscopy with green and near-infrared fluorescent proteins.

The cell cycle is a highly coordinated process governed by cyclin-bound cyclin-dependent kinases (CDKs). While the interaction between cyclin and CDK are well-documented, the dissociation constants (Kd) between specific cyclin-CDK pairs within living cells remain poorly understood. Fluorescence cross-correlation spectroscopy (FCCS) enables the quantification of the Kd, but challenges remain in selecting an optimal pair of fluorescent molecules for FCCS in a living cell. In this study, we demonstrate that mNeonGreen and phycocyanobilin-bound miRFP670 represent a suitable pair for FCCS in living cells from the viewpoint of high photostability and low bleed-through. This fluorescent protein pair enables us to measure the Kd values of the cyclin-dependent kinase Cdc2 and B-type cyclin Cdc13 in fission yeast cells. Moreover, we conducted a comprehensive analysis of the Kd values for 36 cyclin-CDK complexes, formed by 9 distinct cyclins and 4 CDKs, in mammalian cells, including unconventional cyclin-CDK pairs. These findings provide insights into the redundancy of cyclin-CDK binding in cell cycle progression, with potential implications for understanding cell cycle regulation in both fission yeast and higher eukaryotes.

cell biology↗

bioRxiv2024

Biregional division angles generate sharp apex and concave joints in leaves

Leaf apex, the distal end of the leaf blade, exhibits enormous shape variations across plant species. Among these variations, the sharp apex, characterized by its pointed tip, is important in species identification and environmental adaptation. Despite its taxonomic and ecological importance, the developmental mechanisms underlying the formation of a sharp apex remain unknown. The present study aims to investigate the curvature patterns and morphogenesis of the sharp apex to uncover these mechanisms using Triadica sebifera leaves. Our research revealed that the sharp apex marks the maximum positive curvature, and is flanked by concave joints with negative curvatures, suggestive of differential tissue growth and spatially regulated cellular behavior. Through a combination of wet experiments and numerical simulations, we demonstrated that biregional cell division angles, rather than locally differing cell expansion or division frequency, play a determining role in shaping distinct leaf morphology. Our study highlights the importance of spatiotemporal regulation of cell division angles during leaf development, suggesting that a biregional growth pattern and cellular behavior contribute to diversity in leaf apex morphology.

plant biology↗

bioRxiv2024

Characterization of sediment and granite hosted deep underground research laboratories reveals diverse microbiome functions, limited temporal variation and substantial genomic conservation

Underground research laboratories (URLs) provide a window on the deep biosphere and enable investigation of potential microbial impacts on nuclear waste, CO2 and H2 stored in the subsurface. We carried out the first multi-year study of groundwater microbiomes sampled from defined intervals between 140 and 400 m below the surface of the Horonobe and Mizunami URLs, Japan. We reconstructed draft genomes for >90% of all organisms detected over a four year period. The Horonobe and Mizunami microbiomes are dissimilar, likely because the Mizunami URL is hosted in granitic rock and the Horonobe URL in sedimentary rock. Despite this, hydrogen metabolism, rubisco-based CO2 fixation, reduction of nitrogen compounds and sulfate reduction are well represented functions in microbiomes from both URLs, although methane metabolism is more prevalent at the organic- and CO2-rich Horonobe URL. High fluid flow zones and proximity to subsurface tunnels select for candidate phyla radiation bacteria in the Mizunami URL. We detected near-identical genotypes for approximately one third of all genomically defined organisms at multiple depths within the Horonobe URL. This cannot be explained by inactivity, as in situ growth was detected for some bacteria, albeit at slow rates. Given the current low hydraulic conductivity and groundwater compositional heterogeneity, ongoing inter-site strain dispersal seems unlikely. Alternatively, the Horonobe URL microbiome homogeneity may be explained by higher groundwater mobility during the last glacial period. Genotypically-defined species closely related to those detected in the URLs were identified in three other subsurface environments in the USA. Thus, dispersal rates between widely separated underground sites may be fast enough relative to mutation rates to have precluded substantial divergence in species composition. Species overlaps between subsurface locations on different continents constrain expectations regarding the scale of global subsurface biodiversity. Overall, microbiome and geochemical stability over the study period has important implications for underground storage applications.

microbiology↗

bioRxiv2024

BayesianSSA: a Bayesian statistical model based on structural sensitivity analysis for predicting responses to enzyme perturbations in metabolic networks

BackgroundChemical bioproduction has attracted attention as a key technology in a decarbonized society. In computational design for chemical bioproduction, it is necessary to predict changes in metabolic fluxes when up-/down-regulating enzymatic reactions, that is, responses of the system to enzyme perturbations. Structural sensitivity analysis (SSA) was previously developed as a method to predict qualitative responses to enzyme perturbations on the basis of the structural information of the reaction network. However, the network structural information can sometimes be insufficient to predict qualitative responses unambiguously, which is a practical issue in bioproduction applications. To address this, in this study, we propose BayesianSSA, a Bayesian statistical model based on SSA. BayesianSSA extracts environmental information from perturbation datasets collected in environments of interest and integrates it into SSA predictions. ResultsWe applied BayesianSSA to synthetic and real datasets of the central metabolic pathway of Escherichia coli. Our result demonstrates that BayesianSSA can successfully integrate environmental information extracted from perturbation data into SSA predictions. In addition, the posterior distribution estimated by BayesianSSA can be associated with the known pathway reported to enhance succinate export flux in previous studies. ConclusionsWe believe that BayesianSSA will accelerate the chemical bioproduction process and contribute to advancements in the field.

bioinformatics↗

bioRxiv2023

Patterns of change in regulatory modules of chemical reaction systems induced by network modification

Cellular functions are realized through the dynamics of chemical reaction networks formed by thousands of chemical reactions. Numerical studies have empirically demonstrated that small differences in network structures among species or tissues can cause substantial changes in dynamics. However, the existence of a general principle for behavior changes in response to network structure modifications is not known. The chemical reaction system possesses substructures called buffering structures, which are characterized by a certain topological index being zero. It was proven that the steady-state response to modulation of reaction parameters inside a buffering structure is localized in the buffering structure [1, 2, 3]. In this study, we developed a method to systematically identify the loss or creation of buffering structures induced by the addition of a single degradation reaction from network structure alone. This makes it possible to predict the qualitative and macroscopic changes in regulation that will be caused by the network modification. This method was applied to two reaction systems: the central metabolic system and the mitogen-activated protein kinases (MAPK) signal transduction system. Our method enables identification of reactions that are important for biological functions in living systems. Significance StatementDynamics of complex biological systems have been understood using mathematical models[4, 5, 6, 7]; however, various assumptions are necessary to construct models for large networks such as those found in the life sciences, and discussing the relation between the network structure and its behavior is difficult. Our study using structural sensitivity analysis [1, 2, 3] shows that directly discussing changes in the structure and behavior of a reaction network without making assumptions about kinetics is possible. This enabled the prediction of changes in behavior depending on whether a reaction is present or not and identify reactions that are essentially important for biological behavior.

biophysics↗

bioRxiv2023

Finding regulatory modules of chemical reaction systems

Within a cell, numerous chemical reactions form chemical reaction networks (CRNs), which are the origins of cellular functions. We previously developed a theoretical method called structural sensitivity analysis (SSA) [1], which enables us to determine, solely from the network structure, the qualitative changes in the steady-state concentrations of chemicals resulting from the perturbations to a parameter. Notably, if a subnetwork satisfies specific topological conditions, it is referred to as a buffering structure, and the effects of perturbations to the parameter within the subnetwork are localized to the subnetwork (the law of localization) [2, 3]. A buffering structure can be the origin of modularity in the regulation of cellular functions generated from CRNs. However, an efficient method to search for buffering structures in a large CRN has not yet been established. In this study, we proved the "inverse theorem" of the law of localization, which states that a certain subnetwork exhibiting a confined response range is always a buffering structure. In other words, we are able to identify buffering structures in terms of sensitivities rather than the topological conditions. By leveraging this property, we developed an algorithm to enumerate all buffering structures for a given network by calculating the sensitivity. In addition, using the inverse theorem, we demonstrated that the hierarchy among nonzero responses is equivalent to the hierarchy of buffering structures. Our method will be a powerful tool for understanding the regulation of cellular functions generated from CRNs.

systems biology↗

bioRxiv2023

Inference of gene regulatory networks using time-series single-cell RNA-seq data with CRISPR perturbations

Single-cell RNA-seq analysis coupled with CRISPR-based perturbation (scCRISPR) has enabled the inference of gene regulatory networks (GRNs) with causal relationships. However, a snapshot of scCRISPR data may not lead to an accurate inference, since a gene knockout can influence multi-layered downstream over time. Here, we developed RENGE, a new computational method that infers GRNs using a time-series scCRISPR dataset. RENGE models the propagation process of the effects elicited by a gene knockout on its GRN. It can distinguish between direct and indirect regulations, which allows for the inference of regulations by genes that are not knocked out. RENGE therefore outperforms current methods in the accuracy of inferring GRNs. When used on a dataset we derived from human-induced pluripotent stem cells, RENGE yielded a GRN consistent with multiple databases and literature. Accurate inference of GRNs by RENGE would enable the identification of key factors for various biological systems.

bioinformatics↗

bioRxiv2023

Shared GABA transmission pathology in dopamine agonist- and antagonist-induced dyskinesia

Dyskinesia is involuntary movement caused by long-term medication with dopamine-related agents: the dopamine agonist, L-DOPA, to treat Parkinsons disease (L-DOPA-induced dyskinesia [LID]) or dopamine antagonists to treat schizophrenia (tardive dyskinesia [TD]). However, it remains unknown why distinct types of medications for distinct neuropsychiatric disorders induce similar involuntary movements. Here, we searched for a shared structural footprint using magnetic resonance imaging-based macroscopic screening and super-resolution microscopy-based microscopic identification. We identified the enlarged axon terminals of striatal medium spiny neurons in both LID and TD model mice. The striatal overexpression of vesicular gamma-aminobutyric acid transporter (VGAT) was necessary and sufficient for modeling these structural changes; VGAT levels gated the functional and behavioral alterations in dyskinesia models. Our findings indicate that lowered type 2 dopamine receptor signaling with repetitive dopamine fluctuations is a common cause of VGAT overexpression and late-onset dyskinesia formation, and that reducing dopamine fluctuation rescues dyskinesia pathology via VGAT downregulation. HighlightsO_LIEnhancement of GABAergic transmission is a shared mechanism between LID and TD. C_LIO_LIVGAT levels in MSNs govern the structure and function of MSN presynaptic terminals. C_LIO_LIGain and loss of VGAT function in MSNs exacerbates and ameliorates dyskinesia. C_LIO_LILowered D2 signaling with repetitive DA fluctuations causes VGAT overexpression. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=188 HEIGHT=200 SRC="FIGDIR/small/550763v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@15041b4org.highwire.dtl.DTLVardef@9bf41org.highwire.dtl.DTLVardef@1eb7ee4org.highwire.dtl.DTLVardef@1d7dae8_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

GABAergic neuron-to-glioma synapses in diffuse midline gliomas

Pediatric high-grade gliomas are the leading cause of brain cancer-related death in children. High-grade gliomas include clinically and molecularly distinct subtypes that stratify by anatomical location into diffuse midline gliomas (DMG) such as diffuse intrinsic pontine glioma (DIPG) and hemispheric high-grade gliomas. Neuronal activity drives high-grade glioma progression both through paracrine signaling1,2 and direct neuron-to-glioma synapses3-5. Glutamatergic, AMPA receptor-dependent synapses between neurons and malignant glioma cells have been demonstrated in both pediatric3 and adult high-grade gliomas4, but neuron-to-glioma synapses mediated by other neurotransmitters remain largely unexplored. Using whole-cell patch clamp electrophysiology, in vivo optogenetics and patient-derived glioma xenograft models, we have now identified functional, tumor-promoting GABAergic neuron-to-glioma synapses mediated by GABAA receptors in DMGs. GABAergic input has a depolarizing effect on DMG cells due to NKCC1 expression and consequently elevated intracellular chloride concentration in DMG tumor cells. As membrane depolarization increases glioma proliferation3, we find that the activity of GABAergic interneurons promotes DMG proliferation in vivo. Increasing GABA signaling with the benzodiazepine lorazepam - a positive allosteric modulator of GABAA receptors commonly administered to children with DMG for nausea or anxiety - increases GABAA receptor conductance and increases glioma proliferation in orthotopic xenograft models of DMG. Conversely, levetiracetam, an anti-epileptic drug that attenuates GABAergic neuron-to-glioma synaptic currents, reduces glioma proliferation in patient-derived DMG xenografts and extends survival of mice bearing DMG xenografts. Concordant with gene expression patterns of GABAA receptor subunit genes across subtypes of glioma, depolarizing GABAergic currents were not found in hemispheric high-grade gliomas. Accordingly, neither lorazepam nor levetiracetam influenced the growth rate of hemispheric high-grade glioma patient-derived xenograft models. Retrospective real-world clinical data are consistent with these conclusions and should be replicated in future prospective clinical studies. Taken together, these findings uncover GABAergic synaptic communication between GABAergic interneurons and diffuse midline glioma cells, underscoring a tumor subtype-specific mechanism of brain cancer neurophysiology with important potential implications for commonly used drugs in this disease context.

neuroscience↗

bioRxiv2021

IRAK1-dependent Regnase-1-14-3-3 complex formation controls Regnase-1-mediated mRNA decay

Regnase-1 is an endoribonuclease crucial for controlling inflammation by degrading mRNAs encoding cytokines and inflammatory mediators in mammals. However, it is unclear how Regnase-1-mediated mRNA decay is controlled in interleukin (IL)-1{beta} or Toll-like receptor (TLR) ligand-stimulated cells. Here, by analyzing the Regnase-1 interactome, we found that IL-1{beta} or TLR stimulus dynamically induced the formation of Regnase-1-{beta}-transducin repeat-containing protein ({beta}TRCP) complex. Importantly, we also uncovered a novel interaction between Regnase-1 and 14-3-3 in both mouse and human cells. Strikingly, both interactions occur in a mutually exclusive manner, underscoring the importance of modulating Regnase-1s activity. Additionally, we show that in IL-1R/TLR-stimulated cells, the Regnase-1-14-3-3 interaction is mediated by IRAK1 through a previously uncharacterized C-terminal structural domain. Phosphorylation of Regnase-1 at S494 and S513 is critical for Regnase-1-14-3-3 interaction, while a different set of phosphorylation sites of Regnase-1 are known to be required for the recognition by {beta}TRCP and proteasome-mediated degradation. 14-3-3 stabilizes Regnase-1 but abolishes its activity by inhibiting Regnase-1-mRNA association. Furthermore, nuclear-cytoplasmic shuttling of Regnase-1 is abrogated by 14-3-3 interaction. Taken together, the results suggest that a novel inflammation-induced interaction of 14-3-3 with Regnase-1 stabilizes inflammatory mRNAs by sequestering Regnase-1 in the cytoplasm to prevent mRNA recognition.

immunology↗

bioRxiv2020

Origin of diverse phosphorylation patterns in the ERBB system

Intercellular signals induce various cellular responses, including growth, proliferation, and differentiation, via the dynamic processes of signal transduction pathways. For cell-fate decisions, ligand-binding induces the phosphorylation of ERBB receptors, which in turn activate downstream molecules. The ERBB family includes four subtypes, which diverged through two gene duplications from a common ancestor, of different kinetic properties. Differences in the expression patterns of the subtypes have been reported between different organs in the human body. However, how these different kinetic and expression properties influence the diverse phosphorylation dynamics of ERBB proteins is not well understood. Here we study the phosphorylation dynamics by experimental and mathematical analyses. The experimental measurements clarified that the phosphorylation dynamics heavily depend on the ERBB expression profiles. We developed a mathematical model consisting of the four subtypes as monomers, homodimers and heterodimers and estimated the rate constants governing the phosphorylation dynamics from the experimental data. To understand the origin of the diversity of the phosphorylation responses of the ERBB system, we analyzed the expression profiles and reaction rates of the ERBB subtypes. The difference in phosphorylation rates between ERBB subtypes showed a much larger contribution to the diversity of the phosphorylation responses than did the dimerization rates. This result implies that divergent evolution in phosphorylation reactions rather than in dimerization reactions after whole genome duplications was essential for increasing the diversity of the phosphorylation responses. Statement of SignificanceIt is known that the expression patterns of a protein family are different between different organs in the human body. This difference is considered essential for the functional diversity between organs. However, the dynamical processes that translate expression patterns into function are not well understood. Here we study the origin of the diversity in ERBB phosphorylation patterns by combining experimental and mathematical methods. We confirmed experimentally that phosphorylation patterns depend on the ERBB expression profiles. Our mathematical model found that differences in phosphorylation rates made the largest contribution to the diversity of phosphorylation patterns between ERBB subtypes.

systems biology↗

bioRxiv2020

Expression of a gene for an MLX56 defense protein derived from mulberry latex confers strong resistance against a broad range of insect pests on transgenic tomato lines

Insect pests cause serious damage in crop production, and various attempts have been made to produce insect-resistance crops, including the expression of genes for proteins with anti-herbivory activity, such as BT toxins. However, the number of available genes with sufficient anti-herbivory activity is limited. MLX56 is an anti-herbivory protein isolated from the latex of mulberry plants, and has been shown to have a strong growth-suppressing activity against the larvae of a variety of lepidopteran species. As a model of herbivore-resistant plants, we produced transgenic tomato lines expressing the gene for MLX56. The transgenic tomato lines showed strong anti-herbivory activities against the larvae of the common cutworm, Spodoptera litura. Surprisingly, the transgenic tomato lines also exhibited strong activity against the attack of the western flower thrips, Frankliniera occidentalis. Further, growth of the hadda beetle, Henosepilachna vigintioctopunctata fed on leaves of transgenic tomato was significantly retarded. The levels of damage caused by both western flower thrips and hadda beetles were negligible in the high-MLX56-expressing tomato line. These results indicate that introduction of the gene for MLX56 into crops can enhance crop resistance against a wide range of pest insects, and that MLX56 can be utilized in developing pest-resistance GM crops.

bioengineering↗

bioRxiv2020

Quantitative analyses reveal extracellular dynamics of Wnt ligands in Xenopus embryos

The mechanism of intercellular transport of Wnt ligands is still a matter of debate. Here, to better understand this issue, we examined distribution and dynamics of Wnt8 in Xenopus embryos. While Venus-tagged Wnt8 was found on the surfaces of cells close to Wnt-producing cells, we also detected its dispersal over distances of 15 cell diameters. A combination of fluorescence correlation spectroscopy and quantitative imaging revealed that only a small proportion of Wnt8 ligands diffuses freely, whereas most Wnt8 molecules are bound to cell surfaces. Fluorescence decay after photoconversion showed that Wnt8 ligands bound on cell surfaces decreased exponentially, suggesting a dynamic exchange of bound forms of Wnt ligands. Mathematical modelling based on this exchange recapitulates a graded distribution of bound, but not free, Wnt ligands. Based on these results, we propose that Wnt distribution in tissues is controlled by a dynamic exchange of its abundant bound and rare free populations.

developmental biology↗