Biology subjects

Yamamoto, E.

Publications and source records attributed to Yamamoto, E..

12 recordsLinked to original sources

bioRxiv2026

IL-17A Mediates Cardiac Hypertrophy in Chronic Kidney Disease through the IL-23/Th17 Axis.

Background: Chronic kidney disease (CKD) is a major risk factor for cardiovascular morbidity, promoting left ventricular hypertrophy (LVH) prior to overt heart failure. The mechanisms underlying early cardiac remodeling in CKD remain incompletely understood. The IL-23/Th17/IL-17A inflammatory axis has emerged as a key mediator of cardiovascular pathology; however, its role in CKD-associated cardiac remodeling remains unclear. This study aimed to elucidate the contribution of this pathway to the early cardiac changes in CKD. Methods: Using a 5/6 nephrectomy (5/6Nx) mouse model of CKD, we evaluated cardiac structure, mitochondrial function, and inflammatory signaling. Cardiomyocyte transcriptomes were analyzed by RamDA-seq to identify molecular alterations. Circulating cytokines were profiled longitudinally, and IL-17A neutralization experiments were performed to assess causality. In addition, serum IL-12p40 concentrations were measured in patients with CKD and correlated with their renal function and cardiac remodeling indices. Results: At 16 weeks post-5/6Nx, mice developed LVH with preserved systolic function, accompanied by increased oxidative stress and mitochondrial structural abnormalities, but without significant myocardial fibrosis. Transcriptomic analysis identified oxidative phosphorylation as the most significantly downregulated pathway in cardiomyocytes. Despite increased mitochondrial DNA copy number and elevated PGC-1 expression, ATP production and mitochondrial respiratory chain proteins were reduced, indicating mitochondrial dysfunction. Circulating IL-12p40 and IL-23 levels increased progressively, concurrent with expansion of splenic Th17 cells and elevated cardiac IL-17A expression. Recombinant IL-17A directly impaired mitochondrial respiration in cultured cardiomyocytes. In vivo, IL-17A neutralization attenuated LVH, reduced oxidative stress, and partially restored mitochondrial protein expression without improving renal function. In patients with CKD, serum IL-12p40 levels correlated inversely with estimated glomerular filtration rate and positively with left ventricular mass index, supporting clinical relevance. Conclusions: Activation of the systemic IL-23/Th17/IL-17A axis contributes to early CKD-associated cardiac remodeling by promoting oxidative stress and mitochondrial dysfunction. Circulating IL-12p40 may serve as a biomarker of cardiorenal remodeling, and the IL-23/IL-17A pathway represents a potential therapeutic target.

physiology↗

bioRxiv2026

Coarse-grained models for simulations of double-stranded nucleic acids for mixed protein-nucleic acid condensates

Biomolecular condensates function as membraneless compartments, and some protein condensates can selectively concentrate single-stranded nucleic acids while excluding double-stranded nucleic acids. Understanding how nucleic acid structure affects partitioning into condensates has important implications for nucleic acid activity and function within condensates. Here, we present a set of coarse-grained two-bead-per-nucleotide models for simulations of double-stranded RNA and DNA in the CALVADOS framework. Our models separately represent the backbone and base, and maintain the helical structures using an elastic network potential tuned to capture chain stiffness. For dsRNA, the base stickiness was tuned using experimental data on differential partitioning of single- and double-stranded RNA into Ddx4N1 condensates in order to account for reduced base accessibility upon duplex formation. This RNA structural selectivity varied with the balance of electrostatic and non-electrostatic interactions, as revealed by simulations of condensates of the CAPRIN1 disordered region at varying ionic concentrations and with an R-to-K sequence variant. Finally, we developed parameters for double-stranded DNA using a similar approach. We envision that the CALVADOS models for double-stranded RNA and DNA will be useful for studying co-condensates of proteins and structured nucleic acids.

biophysics↗

bioRxiv2026

Hepatic Ketogenesis Attenuates Cardiac Hypertrophy via Metabolic Reprogramming

BackgroundHeart failure with preserved ejection fraction (HfpEF) is increasingly recognized as a multisystem disorder linked to the cardiovascular-kidney-metabolic (CKM) syndrome. While the falling heart undergoes metabolic reprogramming, the interorgan crosstalk regulating myocardial substrate preference in HFpEF remains elusive. We aimed to clarify the role of systemic and local ketogenesis in the pathogenesis of cardiac hypertrophy and HFpEF. MethodsA mouse model of HFpEF was employed using a high-fat diet combined with NG-Nitro-L-arginine methyl ester hydrochloride (L-NAME). Cardiac hypertrophy and systemic metabolic profiling including ketogenesis were evaluated. To dissect the role of site-specific ketogenesis, we generated inducible cardiomyocyte-specific (Hmgcs2{Delta}iCM) and hepatocyte-specific (Hmgcs2{Delta}Hep) knockout mice of HMG-CoA synthase 2 (Hmgcs2), deficient in the rate-limiting enzyme for ketogenesis. Cardiomyocyte -specific nuclei were isolated for transcriptomic (RNA-seq) and in vitro assays in H9C2 cells were used to elucidate molecular mechanisms. ResultsThe HFpEF model successfully exhibited diastolic dysfunction, impaired exercise capacity and cardiac hypertrophy with elevated circulating ketone body concentration. Myocardial metabolomics and snRNA-seq identified a profound metabolic shift characterized by the accumulation of long-chain fatty acids and Krebs cycle intermediates, coupled with the transcriptional downregulation of insulin signaling and fatty acid degradation pathways. Although circulating ketone body level was upregulated, Hmgcs2{Delta}iCM mice showed no exacerbation of the HFpEF phenotype. In contrast, Hmgcs2{Delta}Hep mice exhibited significantly aggravated cardiac hypertrophy (HW/TL; Hmgcs2flox: 7.41 {+/-} 0.87: Hmgcs2{Delta}Hep: 8.29 {+/-} 0.73; p = 0.0154). Mechanistically, hepatic ketogenesis was required to maintain circulating beta-hydroxybutyrate (BHB) levels, which directly modulated cardiomyocyte metabolism. BHB acted as a metabolic signal to dampen fatty acid overload and facilitate glucose utilization. ConclusionsOur study identifies a critical "liver-heart axis" where hepatic ketogenesis serves as an essential regulator of myocardial metabolic resilience. Impaired hepatic ketogenesis creates a metabolic mismatch that drives pathological cardiac remodeling. These findings highlight the liver as a therapeutic target within the CKM syndrome framework, suggesting that restoring the hepato-cardiac metabolic bridge may ameliorate HFpEF progression. What is New?O_LIThis study identifies a novel liver-adipose-heart axis that governs myocardial metabolic resilience during the development of heart failure with preserved ejection fraction (HFpEF). C_LIO_LIWe demonstrate that while both the liver and heart upregulate ketogenesis under metabolic stress, only hepatic ketogenesis--and not cardiac-intrinsic ketogenesis--is essential for mitigating pathological cardiac remodeling. C_LIO_LIMechanistically, liver-derived {beta} -hydroxybutyrate acts as a critical C_LIO_LIendocrine signal that dampens fatty acid oxidation and facilitates myocardial glucose utilization. C_LI What Are the Clinical Implications?O_LIOur findings highlight the liver as a central therapeutic target within the cardiovascular-kidney-metabolic (CKM) syndrome framework, where hepatic metabolic failure directly drives cardiac dysfunction. C_LIO_LIRestoring the hepato-cardiac metabolic bridge, through either hepatic-targeted therapies or ketone body supplementation, represents a promising strategy to enhance myocardial metabolic flexibility and ameliorate HfpEF in patients with multi-organ metabolic disorders. C_LI

biochemistry↗

bioRxiv2025

Molecular interactions underlying selective partitioning of clients into MED1 and FUS condensates

AbstractBiomolecular condensates selectively recruit and exclude proteins, and this partitioning is sometimes dictated by their intrinsically disordered regions. Factors that determine partitioning include client-scaffold interactions and stabilisation of the scaffold network within the condensate, yet a molecular and predictive understanding has not been fully achieved. Here, we used coarse-grained molecular dynamics simulations to elucidate molecular interactions between two types of nuclear proteins as scaffolds: the charge-rich disordered region of Mediator 1 (MED1) and the aromaticrich disordered region of Fused in sarcoma (FUS), in mixtures with client intrinsically disordered regions from six different proteins. We show distinct partitioning into the MED1 and FUS condensates, while enrichment of RNA in the dilute phase modulated partitioning in FUS condensates. Favourable client-scaffold interaction energies within condensates were associated with client partitioning, while client-scaffold interactions competed with scaffold self-interactions. Analysis of interaction energies of individual residues revealed that the interactions were localised to specific sequence regions: charged blocks for interactions with MED1, and dispersed aromatic residues for interactions with FUS. Based on these molecular insights, we developed a sequence-based predictor of partitioning trends and applied it to a set of 243 sequences. Our prediction approach for partitioning can be extended to other biomolecules, offering a framework to analyse their partitioning in cellular environments.

biophysics↗

bioRxiv2025

Multi-omics profiling with indoor-unmanned phenotyping reveals drought adaptation through constitutive ABF1 expression in wild rice

Improving drought resistance is crucial for stable crop production under climate change. Identifying the mechanisms of drought resistance using diverse genetic resources, including crop wild relatives, would be beneficial for molecular breeding. Here, we developed an indoor, unmanned phenotyping platform that can noninvasively and automatically collect temporal data on plant responses to drought stress. Using this system, we analyzed the phenotypic, transcriptomic, and environmental data of four cultivated rice varieties and five wild relatives. Multi-omics analysis revealed that one wild rice species exhibited drought adaptation through the constitutive expression of ABSCISIC ACID RESPONSIVE ELEMENT-BINDING FACTOR 1 (ABF1), which encodes a transcription factor that regulates drought resistance, before drought stress. Drought testing of introgression lines of cultivated rice with constitutive ABF1 expression revealed higher drought tolerance than in cultivars without a growth penalty. Our findings suggest that constitutive ABF1 expression contributes to drought adaptation in both cultivated and wild rice.

plant biology↗

bioRxiv2025

Rational engineering of lipid-binding probes via high-throughput protein-lipid interaction screening

Lipid-binding domains, originally isolated from natural proteins, are useful tools essential for analyzing membrane lipids in cells, and their applications are varied. Yet, there is no general strategy for engineering lipid-binding domains. Here, we present a robust method for monitoring protein-lipid interactions, named the Cell surface Liposome Binding (CLiB) assay. Using this technique, we isolated high-affinity lipid-binding domains and nanobodies that preferentially bind to phosphatidylinositol phosphates. Furthermore, by combining the CLiB assay with next-generation sequencing, allowing the analysis of more than 10,000 clones in parallel, we identified novel variants with enhanced binding to phosphatidylinositol phosphates and uncovered a common structural feature: a positively charged pocket necessary for binding, formed by the three loop regions. This study opens a new avenue for the rational design and generation of lipid-binding probes on demand.

cell biology↗

bioRxiv2024

A coarse-grained model of disordered RNA for simulations of biomolecular condensates

Protein-RNA condensates are involved in a range of cellular activities. Coarse-grained molecular models of intrinsically disordered proteins have been developed to shed light on and predict single-chain properties and phase separation. An RNA model compatible with such models for disordered proteins would enable the study of complex biomolecular mixtures involving RNA. Here, we present a sequence-independent coarse-grained, two-bead-per-nucleotide model of disordered, flexible RNA based on a hydropathy scale. We parameterize the model, which we term CALVADOS-RNA, using a combination of bottom-up and top-down approaches to reproduce local RNA geometry and intramolecular interactions based on atomistic simulations and in vitro experiments. The model semi-quantitatively captures several aspects of RNA-RNA and RNA-protein interactions. We examined RNA-RNA interactions by comparing calculated and experimental virial coefficients, and non-specific RNA-protein interaction by studying reentrant phase behavior of protein-RNA mixtures. We demonstrate the utility of the model by simulating the formation of mixed condensates consisting of the disordered region of MED1 and RNA chains, and the selective partitioning of disordered regions from transcription factors into these, and compare the results to experiments. Despite the simplicity of our model we show that it captures several key aspects of protein-RNA interactions and may therefore be used as a baseline model to study several aspects of the biophysics and biology of protein-RNA condensates.

biophysics↗

bioRxiv2021

Balanced release of neuropeptide FF and gonadotropin-releasing hormone 3 modulates male sexual behavior

Animals properly perform sexual behaviors by using multiple sensory cues. However, neural mechanisms integrating multiple sensory cues and regulating motivation for sexual behaviors remain unclear. Here, we focused on peptidergic neurons, terminal nerve gonadotropin-releasing hormone (TN-GnRH) neurons, which receive inputs from various sensory systems and co-express neuropeptide FF (NPFF) in addition to GnRH. Our behavioral analyses using knockout medaka of GnRH (gnrh3) and/or NPFF (npff) demonstrated that some sexual behavioral repertories were delayed, not disrupted, in gnrh3-/- and npff-/- males, while the double knockout showed normal behaviors. We also found anatomical evidence to show that both neuropeptides modulate the sexual behavior-controlling brain areas. Furthermore, we demonstrated that NPFF activates neurons in the preoptic area via indirect pathway, which is considered to induce the increase in the motivation for male sexual behaviors. Considering these results, we propose a novel mechanism by which balanced release of co-existing peptides is important for the neuromodulatory function of TN-GnRH neurons in the control of behavioral motivation. Our results may go a long way toward understanding the functional significance of peptidergic neuromodulation in response to external environments.

neuroscience↗

bioRxiv2020

Exploring Efficient Linear Mixed Models to Detect Quantitative Trait Locus-by-environment Interactions

Genotype-by-environment interactions (GxE) are important for understanding genotype-phenotype relationships. To date, various statistical models have been proposed to account for GxE effects, especially in genomic selection (GS) studies. Generally, GS does not focus on the detection of each quantitative trait locus (QTL), while the genome-wide association study (GWAS) was designed for QTL detection. GxE modeling methods in GS can be included as covariates in GWAS using unified linear mixed models (LMMs). However, the efficacy of GxE modeling methods in GS studies has not been evaluated for GWAS. In this study, we performed a comprehensive comparison of LMMs that integrate the GxE modeling methods to detect both QTL and QTL-by-environment interaction (QxE) effects. Model efficacy was evaluated using simulation experiments. For the fixed effect terms representing QxE effects, simultaneous scoring of specific and non-specific environmental effects was recommended because of the higher recall and improved genomic inflation factor value. For random effects, it was necessary to account for both GxE and genotype-by-trial (GxT) effects to control genomic inflation factor value. Thus, the recommended LMM includes fixed QTL effect terms that simultaneously score specific and non-specific environmental effects and random effects accounting for both GxE and GxT. The LMM was applied to real tomato phenotype data obtained from two different cropping seasons. We detected not only QTLs with persistent effects across the cropping seasons but also QTLs with QxE effects. The optimal LMM identified in this study successfully detected more QTLs with QxE effects.

genetics↗

bioRxiv2020

Loss of Photosynthetic Rhythm Thermal Plasticity Under Domestication and RepurposingDrivers of Circadian Clock (DOC) Loci for Adaptive Breeding in Barley

Circadian clock rhythms are critical to control physiological and development traits, allowing, plants to adapt to changing environments. Here we show that the circadian rhythms of cultivated barley (Hordeum vulgare) have slowed and amplitude increased under domestication by comparing with its wild ancestor (H. spontaneum). Moreover, we show a significant loss of thermal plasticity during barley evolution for the period and more extensively for amplitude. Our genetic analysis indicates that wild allele at epistatic loci, which mutually condition clock variation and its thermal plasticity in interspecific crosses, are absent in a contemporary barley breeding panel. These epistatic interactions include conditioned effects of Drivers of Circadian (DOC) clock loci on chromosome 3 and 5, which mediate amplitude decrease and period lengthening, respectively, under domestication. Notably, two significant loci, DOC3.1 and DOC5.1, which are not associated with clock diversity in cultivated breeding material, do show pleiotropic effects on flowering time and grain yield at multiple experimental sites across the U.S. in a temperature-dependent manner. We suggest that transition from winter growth of wild barley (H. spontaneum) to spring growth of modern cultivars included the loss and repurposing of circadian clock regulators to yield adaptation by mechanisms yet to be clarified. Significance statementCircadian clock rhythms are crucial factors affecting crop adaptation to changing environments. If faced with increased temperature plants could respond with temperature compensation adaptation and maintain clock rhythms, or they can change period and/or amplitude to adapt. We used a combination of approaches: high-throughput clock analysis under optimal and elevated heat conditions, genome-wide association study (GWAS) with cultivated and wild diversity panels to identify changes under domestication and quantitative trait loci (QTL) that control the clock and its responses, and QTL-environment association for testing environmentally-conditioned effects of these QTLongrain yield and flowering timingacross US. Our findings provide insights into changes of circadian rhythms under domestication and genetic tools for plant breeders to develop better-adapted cultivars to changing environments.

genetics↗

bioRxiv2019

Neighbor GWAS: incorporating neighbor genotypic identity into genome-wide association studies of field herbivory on Arabidopsis thaliana

An increasing number of field studies have shown that the phenotype of an individual plant depends not only on its genotype but also on those of neighboring plants; however, this fact is not taken into consideration in genome-wide association studies (GWAS). Based on the Ising model of ferromagnetism, we incorporated neighbor genotypic identity into a regression model, named "Neighbor GWAS". Our simulations showed that the effective range of neighbor effects could be estimated using an observed phenotype from when the proportion of phenotypic variation explained (PVE) by neighbor effects peaked. The spatial scale of the first nearest neighbors gave the maximum power to detect the causal variants responsible for neighbor effects, unless their effective range was too broad. However, if the effective range of the neighbor effects was broad and minor allele frequencies were low, there was collinearity between the self and neighbor effects. To suppress the false positive detection of neighbor effects, the fixed effect and variance components involved in the neighbor effects should be tested in comparison with a standard GWAS model. We applied neighbor GWAS to field herbivory data from 199 accessions of Arabidopsis thaliana and found that neighbor effects explained 8% more of the PVE of the observed damage than standard GWAS. The neighbor GWAS method provides a novel tool that could facilitate the analysis of complex traits in spatially structured environments and is available as an R package at CRAN (https://cran.rproject.org/package=rNeighborGWAS).

genetics↗

bioRxiv2019

Genetic Mapping in Autohexaploid Sweet Potato with Low-coverage NGS-based Genotyping Data

Next-generation sequencing (NGS)-based genotyping methods can generate numerous genetic markers in a single experiment and have contributed to plant genetic mapping. However, the benefits of NGS-based methods are limited in autopolyploids as their genetic segregation mode is complex. Moreover, autopolyploids have large genomes and require abundant sequencing data to obtain sufficient genetic markers. There are several methods for genetic mapping in autopolyploids. These approaches may be impractical for plant genetic studies as they require large amounts of data and are not cost-effective. In the present study, we propose a simple strategy for genetic mapping of polyploids in a cost-effective manner. The allele dosage probabilities calculated from NGS read counts were used in association analyses to detect loci associated with specific phenotypes. This approach is superior to conventional methods of determining allele dosage, which usually result in the filtering of many genetic markers with low read depth. The validity of the strategy was demonstrated using real phenotype data from autohexaploid sweet potato populations to detect genetic loci for both qualitative and quantitative traits, the latter of which required the use of allele dosage probabilities for the detection of loci. We demonstrate that this proposed method is useful with reasonable NGS read counts.

genetics↗