Biology subjects

Morita, K.

Publications and source records attributed to Morita, K..

At least 19 recordsLinked to original sources

bioRxiv2025

Dynamic adjustment of feeding behavior depending on dominant-subordinate relationship in large-billed crows.

Animals that forage socially adjust their behavior according to social status. Dominance and subordination are defined by priority of access to resources in competitive contexts. While dominant individuals can control access to resources, subordinates must obtain food through alternative strategies. In direct encounters with dominants, subordinates are expected to adjust their behavior to the partner on a moment to moment basis. However, the decision dynamics in such situations remain unclear. We tested large-billed crows in a dyadic feeding experiment to examine whether social status shapes feeding behavior. Using tracking analysis, we quantified the time series of approach velocity toward food and assessed whether its dynamics were modulated by the partners movements. Subordinates adjusted the velocity of their reaching movements. Specifically, a dominants approach increased a subordinates reaching speed, suggesting that subordinates accelerated to avoid aggression under dominance pressure. In contrast, this effect was weak or absent in dominants, indicating asymmetric social influences on foraging. Taken together, these findings suggest that subordinates fine tune the kinematics of feeding behavior in response to dominant movements, whereas dominants do not.

animal behavior and cognition↗

bioRxiv2025

Is hybridization evil? --Competition generates alternative stable states of coexistence of hybridizing species

Predicting ecological outcomes of hybridizing species remains challenging because of complex interactions between genetic and ecological processes. Previous studies have mainly focused on exclusion scenarios driven by genetic mechanisms, whereas few have explored the impact of competitive interactions among parent species and their hybrids on generating multiple coexistence regimes. Here, we develop a population dynamics model that explicitly couples hybridization genetics with population dynamics driven by competitive interactions among two parent species and their hybrids. Our analysis reveals that backcrossing can fundamentally reshape coexistence regimes, generating five alternative outcomes: (i) alternative stable states of coexistence of both parent species and hybrids, (ii) frequency-independent coexistence, (iii) frequency-dependent coexistence, (iv) competitive exclusion of a rarer species, and (v) extinction of all populations. These outcomes arise from the balance between two key processes: regeneration of parental genotypes through hybrid x hybrid mating and competitive exclusion mediated by hybrids. Thus, hybridization can generate multiple stable coexistence regimes even when species would otherwise be excluded. This eco-genetic mechanism provides a unifying theoretical basis for predicting the ecological consequences of hybridization, highlighting the crucial role of competitive interactions in determining coexistence outcomes.

ecology↗

bioRxiv2025

Metabolic Trans-Omic Analysis Reveals Key Regulatory Disruption of Energy Metabolism in Alzheimer's Disease

Alzheimers disease (AD), a leading cause of dementia, has been recognized as a disease with profound metabolic dysregulation. However, a systems-level view of metabolic regulation across multiple omic modalities in AD remains elusive. Here, we integrated public multi-omic datasets (transcriptome, proteome, and metabolome) from the dorsolateral prefrontal cortex of AD patients and controls. By leveraging existing molecular biological knowledge, we reconstructed a multi-layered metabolic regulatory network to systematically map the potential interplay among mRNAs, proteins, and metabolites in AD. Our analysis revealed a putative coordinated downregulation of energy producing pathways, including the TCA cycle, oxidative phosphorylation, and ketone body metabolism, driven by reduced enzyme abundance and inhibitory allosteric effects. In contrast, the glycolysis pathway appeared to be influenced by opposing enzymatic and allosteric regulations. These findings highlight key metabolic dysregulations that may contribute to the bioenergetic deficits in AD.

systems biology↗

bioRxiv2025

Mesocorticolimbic reinforcement learning of reward representation and value provides an integrated mechanistic account for schizophrenia

Mesocorticolimbic dopamine projections are crucial for value learning, motivational control, and cognitive functions, but their precise neurocomputational roles remain elusive. Based on recent experimental and theoretical findings, we constructed a neural circuit model where dopamine neuronal populations receive differential inputs from individual rewards and encode heterogeneous reward prediction errors, which train cortical and striatal neurons to learn reward-associated state representation and value. Learning is achieved via simultaneous alignments of the cortical and striatal downstream connections to the mesocorticolimbic dopamine projections, and inhibition-dominance in the cortical recurrent network is a key for successful learning. Excessive excitation, whether pre-existing or induced by manipulations, leads to aberrant activity, which disrupts the alignments and even causes anti-alignment. This impairs both reward-specific motivational control and credit assignment, potentially explaining the negative and positive symptoms of schizophrenia, respectively. Our model thus provides a mechanistic account for schizophrenia, integrating the different causes and symptoms, with testable predictions.

neuroscience↗

bioRxiv2025

Global loss of responsiveness in key regulator metabolites and elevated enzyme proteins as metabolic dysregulation in skeletal muscle and liver of obese mice during starvation

Starvation induces complex metabolic adaptations in skeletal muscle, a key tissue for maintaining energy homeostasis; however, these adaptations are largely impaired in obesity. How obesity alters global metabolic adaptations to starvation in skeletal muscle remains unclear. Here, we analyzed the metabolic adaptations on a trans-omics scale during starvation in skeletal muscle from wild-type (WT) and leptin-deficient obese (ob/ob) mice. We measured multi-omics data during starvation and constructed global trans-omics networks in WT and ob/ob mice. We found that starvation induces "responsiveness" in WT mice, characterized by increases or decreases in key regulator metabolites, including ATP and AMP, as well as enzyme proteins, leading to global regulation of metabolic pathways, which was lost in ob/ob mice. In contrast, during starvation, ob/ob mice exhibit "difference" in comparison to WT mice, manifested by the persistently elevated expression of metabolic enzymes. These features were similarly found in liver, another key metabolic organ. Thus, global loss of responsiveness and elevated enzyme proteins are systemic features of metabolic dysregulation in ob/ob mice.

systems biology↗

bioRxiv2025

Striatal Gradient in Value-Decay Explains Regional Differences in Dopamine Patterns and Reinforcement Learning Computations

Dopamine has been suggested to encode reward-prediction-error (RPE) in reinforcement learning (RL) theory, but also shown to exhibit heterogeneous patterns depending on regions and conditions: some exhibiting ramping response to predictable reward while others only responding to reward-predicting cue. It remains elusive how these heterogeneities relate to various RL algorithms proposed to be employed by animals/humans, such as RL under predictive state representation, hierarchical RL, and distributional RL. Here we demonstrate that these relationships can be coherently explained by incorporating the decay of learned values (value-decay), implementable by the decay of dopamine-dependent plastic changes in the synaptic strengths. First, we show that value-decay causes ramping RPE under certain state representations but not under others. This accounted for the observed gradual fading of dopamine ramping across repeated reward navigation, attributed to the gradual formation of predictive state representations. It also explained the cue-type and inter-trial-interval-dependent temporal patterns of dopamine. Next, we constructed a hierarchical RL model composed of two coupled systems--one with value-decay and one without. The model accounted for distinct patterns of neuronal activity in parallel striatal-dopamine circuits and their proposed roles in flexible learning and stable habit formation. Lastly, we examined two distinct algorithms of distributional RL with and without value-decay. These algorithms explained how distinct dopamine patterns across striatal regions relate to the reported differences in the strength of distributional coding. These results suggest that within-striatum differences--specifically, a medial-to-lateral gradient in value or synaptic decay--tune regional RL computations by generating distinct patterns of dopamine/RPE signals.

neuroscience↗

bioRxiv2024

How can interspecific pollen transfer affect the coevolution and coexistence of two closely related plant species?

Interspecific pollen transfer (IPT), the movement of pollen grains between different plant species by sharing pollinators, incurs costs (fitness reduction) for seed production. IPT thereby reduces the reproductive success of co-flowering plants sharing pollinators, thus preventing their coexistence. However, the impact of IPT on the evolutionary dynamics and evolution-mediated ecological dynamics of sex allocation resource investment to pollen versus ovules) is poorly understood. Here, we investigate the consequences of the female costs incurred by IPT for the co-evolution and coexistence of two plants, by using a mathematical model where two plant species interact with each other via resource competition, pollen movements within and between species, and reduced fertilization due to IPT. The ecological situation we consider here is that an invasive species with female-biased sex allocation immigrates into a habitat of a resident species whose sex allocation is evolutionarily maintained at Fisherian sex allocation (FSA). By using adaptive dynamics theory, we found that regardless of the strength of IPT, natural selection favours the equal allocation to pollen grains and ovules (FSA) for both species. If the mutual impact of IPT on two species is similar in magnitude, we find that the eco-evolutionary dynamics can lead to their stable coexistence. In contrast, when only the invasive species negatively impacts the resident species through IPT, the evolution in invasive species from female-biased sex allocation to FSA causes the extinction of the resident species. Given that local mate competition in small populations is expected to result in female-based sex allocation, our finding suggests that if invasive species are relaxed from local mate competition, they may drive the resident species to extinction. Our study highlights the importance and complexity of the evolution of biased sex allocation driven by IPT to understand the coexistence of closely related plant species.

ecology↗

bioRxiv2024

Reinforcement learning of state representation and value: the power of random feedback and biological constraints

Representation of external and internal states in the brain plays a critical role in enabling suitable behavior. Recent studies suggest that state representation and state value can be simultaneously learnt through Temporal-Difference-Reinforcement-Learning (TDRL) and Backpropagation-Through-Time (BPTT) in recurrent neural networks (RNNs) and their readout. However, neural implementation of such learning remains unclear as BPTT requires offline update using transported downstream weights, which is suggested to be biologically implausible. We demonstrate that simple online training of RNNs using TD reward prediction error and random feedback, without additional memory or eligibility trace, can still learn the structure of tasks with cue-reward delay and timing variability. This is because TD learning itself is a solution for temporal credit assignment, and feedback alignment, a mechanism originally proposed for supervised learning, enables gradient approximation without weight transport. Furthermore, we show that biologically constraining downstream weights and random feedback to be non-negative not only preserves learning but may even enhance it because the non-negative constraint ensures loose alignment - allowing the downstream and feedback weights to roughly align from the beginning. These results provide insights into the neural mechanisms underlying the learning of state representation and value, highlighting the potential of random feedback and biological constraints.

neuroscience↗

bioRxiv2024

Structural robustness and temporal vulnerability of the starvation-responsive metabolic network in liver of healthy and obese mice

Adaptation to starvation is a multi-molecular and temporally ordered process, that could be impaired in obesity. To elucidate how the healthy liver regulates various molecules in a temporally ordered manner during starvation and how obesity disrupts this process, we measured time course multiomic data in the liver of wild-type (WT) and leptin-deficient obese (ob/ob) mice during starvation. Using the measured data, we constructed a starvation-responsive metabolic network, that is a transomic network including responsive molecules and their regulatory relationships during starvation, and analyzed the structure of the network. In WT mice, ATP and AMP, the energy indicators, regulated various metabolic reactions in the network as the hub molecules, both of which were not responsive in ob/ob mice. However, the structural properties of the network were maintained in ob/ob mice. In WT mice, the molecules in the network were temporally ordered through metabolic process coordinated by the hub molecules including ATP and AMP and were positively or negatively co-regulated. By contrast, both temporal order and co-regulation were disrupted in ob/ob mice. Taken together, the starvation-responsive metabolic network is structurally robust, but temporally vulnerable by the loss of responsiveness of the hub molecules in obesity. In addition, we proposed a potential therapeutic target to treat the negative effects of obesity on intermittent fasting to extend lifespan. One Sentence SummaryHub molecules activate or inhibit various molecules in a temporally ordered manner in healthy liver, and the regulatory network is structurally robust but temporally vulnerable to obesity.

systems biology↗

bioRxiv2024

Clinical factors associated with SFTS diagnosis and severity in cats

Severe fever with thrombocytopenia syndrome (SFTS) is a potentially fatal tick-borne zoonosis caused by SFTS virus (SFTSV). In addition to tick bites, animal-to-human transmission of SFTSV has been reported, but little is known about feline SFTSV infection. In this study, we analyzed data on 187 cats with suspected SFTS to identify biomarkers for SFTS diagnosis and clinical outcome., Body weight, red and white blood cell and platelet counts, serum aspartate aminotransferase and total bilirubin levels, were useful for SFTS diagnosis, and alanine aminotransferase, aspartate aminotransferase and serum SFTSV RNA levels were associated with the clinical outcome. We developed a scoring model to predict SFTSV infection. In addition, we performed a phylogenetic analysis to reveal the relationship between disease severity and viral strain. This study provides comprehensive information on feline SFTS and could contribute to the protection of cat owners, community members, and veterinarians from the risk of cat-transmitted SFTSV infection.

zoology↗

bioRxiv2024

Establishment of an easy-to-construct liver injury mouse model for longitudinal analysis by drinking-water administration of 4,4'-methylenedianiline

Background & AimsLongitudinal animal models are essential for understanding the temporal dynamics of liver injury and recovery. While drinking water-based administration is ideal for sustained exposure in high feasibility, available compounds are limited, with thioacetamide (TAA) being the primary option. Here, we aimed to establish a novel drinking water-induced mouse model of cholestatic liver injury using 4,4-methylenedianiline (MDA), and to characterize its pathological trajectory in comparison to the TAA model. MethodsMice were administered MDA via drinking water for 28 Days. To elucidate the early events that give rise to chronic pathological divergence, we conducted a multi-layered analysis comprising plasma biochemical assays, immune cell profiling by flow cytometry, and hepatic transcriptomics at five time points during the early phase. The MDA model was evaluated against the established TAA model. ResultsMDA administration induced sustained ALT elevation, peribiliary fibrosis, and spatially irregular focal hepatocellular necrosis, distinguishing it from the centrilobular injury observed with TAA. Additionally, the MDA model showed significant elevations in ALP, TBIL, and TCHO, indicating cholestatic liver dysfunction. Early-phase analyses revealed model-specific differences in immunological and molecular responses, including increased CD8 T cell populations and enrichment of fibrinolysis-related gene expression in MDA-DW mice. ConclusionsWe present the MDA-DW model as a novel, longitudinally tractable liver injury model that complements existing systems by capturing alternative spatial, immunological, and transcriptional patterns of injury. This model offers a valuable platform for dissecting the temporal dynamics of liver disease progression in experimental settings. Significance StatementWe developed a cost-effective, non-invasive mouse model of cholestatic liver injury using drinking-water administration of 4,4-methylenedianiline (MDA). This model exhibits periportal-predominant damage, peribiliary fibrosis, and spatially irregular focal hepatocellular necrosis, distinct from conventional centrilobular models. Early-phase multi-omics analysis revealed immunological and transcriptomic differences, including increased CD8 T cells and activation of fibrinolysis-related pathways. The low mortality rate and ease of implementation enable long-term studies and cross-sectional comparisons across time points or interventions. This study provides not only a practical model for investigating chronic liver injury, but also a rich time-series, multi-view dataset, offering a valuable resource for advancing research on liver pathophysiology and toxicological mechanisms.

pharmacology and toxicology↗

bioRxiv2023

iTraNet: A Web-Based Platform for integrated Trans-Omics Network Visualization and Analysis

ABSTRACTA major goal in biology is to comprehensively understand molecular interactions within living systems. Visualization and analysis of biological networks play crucial roles in understanding these biochemical processes. Biological networks include diverse types, from gene regulatory networks and protein-protein interactions (PPIs) to metabolic networks. Metabolic networks include substrates, products, and enzymes, which are regulated by allosteric mechanisms and gene expression. Given this complexity, there is a pressing need to investigate trans-omics networks that include these various regulations to understand living systems. However, analyzing various omics layers is laborious due to the diversity of databases and the intricate nature of network analysis. We developed iTraNet, a user-friendly interactive web application that visualizes and analyzes trans-omics networks involving four major types of networks: gene regulatory networks (including transcription factor, microRNA, and mRNA); PPIs; metabolic networks (including enzyme, mRNA, and metabolite); and metabolite exchange networks (including transporter, mRNA, and metabolite). Using iTraNet, we found that in wild-type mice, hub molecules within the network tended to respond to glucose administration, whereas in ob/ob mice, this tendency disappeared. With its ability to facilitate network visualization and analysis, we anticipate that iTraNet will help researchers gain insights into biological systems. iTraNet is available at (https://transomics.streamlit.app/). GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/569499v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@12bb1c1org.highwire.dtl.DTLVardef@1a326b7org.highwire.dtl.DTLVardef@42cfc9org.highwire.dtl.DTLVardef@57aee6_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2023

Trans-omic analysis reveals opposite metabolic dysregulation between feeding and fasting in liver associated with obesity

Dysregulation of liver metabolism associated with obesity during feeding and fasting leads to the breakdown of metabolic homeostasis. However, the underlying mechanism remains unknown. Here, we measured multi-omics data in the liver of wild-type and leptin-deficient obese (ob/ob) mice at ad libitum feeding, and constructed a differential regulatory trans-omic network of metabolic reactions. We compared the trans-omic network at feeding with that at 16 h-fasting constructed in our previous study. Intermediate metabolites in glycolytic and nucleotide metabolism decreased in ob/ob mice at feeding but increased at fasting. Allosteric regulation reversely shifted between feeding and fasting, generally showing activation at feeding while inhibition at fasting in ob/ob mice. Transcriptional regulation was similar between feeding and fasting, generally showing inhibiting transcription factor regulations, activating enzyme protein regulations in ob/ob mice. The opposite metabolic dysregulation between feeding and fasting characterizes breakdown of metabolic homeostasis associated with obesity.

systems biology↗

bioRxiv2023

Network-based clustering unveils interconnected landscapes of genomic and clinical features across myeloid malignancies

Myeloid malignancies exhibit considerable heterogeneity with overlapping clinical and genetic features among different subtypes. Current classification schemes, predominantly based on clinical features, fall short of capturing the complex genomic landscapes of these malignancies. Here, we present a data-driven approach that integrates mutational features and clinical covariates within networks of their probabilistic relationships, enabling the discovery of de novo cancer subgroups. In a cohort of 1323 patients across acute myeloid leukemia, myelodysplastic syndromes, chronic myelomonocytic leukemia and myeloproliferative neoplasms, we identified novel subgroups that outperform established risk classifications in prognostic accuracy. Our findings suggest that mutational patterns are often shared across different types of myeloid malignancies, with distinct subtypes potentially representing evolutionary stages en route to leukemia. Within the novel subgroups, our integrative method discerns unique patterns combining genomic and clinical features to provide a comprehensive view of the multifaceted genomic and clinical landscape of myeloid malignancies. This in turn may guide the development of targeted therapeutic strategies and offers a pathway to enhanced patient stratification.

cancer biology↗

bioRxiv2023

A Tetravalent Dengue Virus-like Particle Vaccine Induces High levels of Neutralizing Antibodies and Inhibits Dengue Replication in Non-Human Primates

Dengue virus (DENV) represents a significant global health burden, with 50% of the worlds population at risk of infection, and there is an urgent need for next-generation vaccines. Virus-like particle (VLP)-based vaccines, which mimic the antigenic structure of the authentic virus but lack the viral genome, are an attractive approach. Here we describe a dengue VLP (DENVLP) vaccine which generates a robust and long-lasting neutralizing antibody response against all four DENV serotypes in non-human primates. Importantly, DENVLP vaccination produced no ADE response against any of four DENV serotypes. Finally, we demonstrate in a non-human primate challenge model that DENVLP vaccination substantially reduces viral replication. We also transfer the purified IgG from the immunized monkeys into immunodeficient mice, where they protect against subsequent lethal dengue virus challenge, indicating a humoral mechanism of protection. These results indicate that a DENVLP vaccine is a safe and effective vaccine candidate. One Sentence Summary: Immunization of non-human primates with a tetravalent dengue VLP vaccine induces high levels of neutralizing antibodies and reduces the severity of infection for all four dengue serotypes.

microbiology↗

bioRxiv2023

Evolution of wheat blast resistance gene Rmg8 accompanied by differentiation of variants recognizing the powdery mildew fungus

Wheat blast, a devastating disease having spread recently from South America to Asia and Africa, is caused by Pyricularia oryzae pathotype Triticum which emerged in 1985. Rmg8 and Rmg7, genes for resistance to wheat blast found in common wheat and tetraploid wheat, respectively, recognize the same avirulence gene, AVR-Rmg8. Here, we show an evolutionary process in which resistance gene(s), which had obtained an ability to recognize AVR-Rmg8 before the differentiation of Triticum and Aegilops, has expanded its target pathogens. Molecular cloning revealed that Rmg7 was one of alleles of Pm4 (Pm4a), a gene for resistance to wheat powdery mildew on 2AL, whereas Rmg8 was its homoeolog on 2BL ineffective against wheat powdery mildew. Rmg8 variants with the ability to recognize AVR-Rmg8 were distributed not only in Triticum spp. but also in Aegilops speltoides, Ae. umbellulata, and Ae. comosa. This result suggests that the origin of resistance gene(s) recognizing AVR-Rmg8 dates back to the time before differentiation of A, B, S, U, and M genomes, that is, [~]5 million years before the emergence of its current target, the wheat blast fungus. Phylogenetic analyses suggested that, in the evolutionary process thereafter, some of their variants gained the ability to recognize the wheat powdery mildew fungus and evolved into genes for resistance to wheat powdery mildew.

plant biology↗

bioRxiv2023

Breeding of a near-isogenic wheat line resistant to wheat blast at both seedling and heading stages through incorporation of Rmg8

Wheat blast caused by Pyricularia oryzae Triticum pathotype (MoT) has been transmitted from South America to Bangladesh and Zambia and is now spreading in these countries. To prepare against its further spread to Asian countries, we introduced Rmg8, a gene for resistance to wheat blast, into a Japanese elite cultivar, Chikugoizumi (ChI), through recurrent backcrosses, and established ChI near-isogenic lines, #2-1-10 with the Rmg8/Rmg8 genotype and #4-2-10 with the rmg8/rmg8 genotype. A molecular analysis suggested that at least 96.6% of the #2-1-10 genome was derived from the recurrent parent ChI. The #2-1-10 line was resistant to MoT not only in primary leaves at the seedling stage but also in spikes and flag leaves at the heading stage. The strength of the resistance in spikes of this Rmg8 carrier was comparable to that of a carrier of the 2NS segment which has been the only one genetic resource released to farmers field for wheat blast resistance. On the other hand, the 2NS resistance was not expressed on leaves at the seedling stage nor flag leaves at the heading stage. Considering that leaf blast has been increasingly reported and regarded as an important inoculum source for spike blast, Rmg8 expressed at both the seedling and heading stages, or more strictly in both leaves and spikes, is suggested to be useful to prevent the spread of MoT in Asia and Africa.

plant biology↗

bioRxiv2023

Rat Deconvolution as Knowledge Miner for Immune Cell Trafficking from Toxicogenomics Databases

Toxicogenomics databases are useful for understanding biological responses in individuals because they include a diverse spectrum of biological responses. Although these databases contain no information regarding immune cells in the liver, which are important in the progression of liver injury, deconvolution that estimates cell-type proportions from bulk transcriptome could extend immune information. However, deconvolution has been mainly applied to humans and mice and less often to rats, which are the main target of toxicogenomics databases. Here, we developed a deconvolution method for rats to retrieve information regarding immune cells from toxicogenomics databases. The rat-specific deconvolution showed high correlations for several types of immune cells between spleen and blood, and between liver treated with toxicants compared with those based on human and mouse data. Additionally, we found 4 clusters of compounds in Open TG-GATEs database based on estimated immune cell trafficking, which are different from those based on transcriptome data itself. The contributions of this work are three-fold. First, we obtained the gene expression profiles of 6 rat immune cells necessary for deconvolution. Second, we clarified the importance of species differences on deconvolution. Third, we retrieved immune cell trafficking from toxicogenomics databases. Accumulated and comparable immune cell profiles of massive data of immune cell trafficking in rats could deepen our understanding of enable us to clarify the relationship between the order and the contribution rate of immune cells, chemokines and cytokines, and pathologies. Ultimately, these findings will lead to the evaluation of organ responses in Adverse Outcome Pathway.

bioinformatics↗