Biology subjects

Hashimoto, R.

Publications and source records attributed to Hashimoto, R..

16 recordsLinked to original sources

bioRxiv2025

A cattle-derived human H5N1 isolate suppresses innate immunity despite efficient replication in human respiratory organoids

The H5N1 high pathogenicity avian influenza virus (HPAIV) of clade 2.3.4.4b, which spreads globally via wild birds, has become a major public health concern because it can infect a variety of mammals, including humans. In 2024, infection of dairy cattle with H5N1 HPAIV clade 2.3.4.4b was confirmed in the United States, and subsequent human cases were reported. Although these viruses are highly pathogenic in animal models, human infections have generally been mild, revealing a striking discrepancy. Here, we characterized the cattle-derived human H5N1 isolate A/Texas/37/2024 (TX37-H5N1) using three-dimensional human respiratory organoids derived from induced pluripotent stem (iPS) cells. Despite efficient replication, TX37-H5N1 induced minimal interferon and inflammatory cytokine responses. Bulk and single-cell RNA sequencing revealed reduced STAT1-mediated transcriptional activity in TX37-H5N1-infected organoids compared to the historic H5N1 human isolate A/Vietnam/1203/2004. These findings suggest that TX37-H5N1 fails to trigger the strong innate responses, including robust cytokine production, that are typically associated with severe H5N1 disease and are thought to contribute to cytokine storm-medicated pathogenesis. This attenuated response may help explain the discrepancy between the high pathogenicity of TX37-H5N1 in animal models and its mild clinical presentation in humans. While zoonotic influenza risk is often assessed using cell lines or animal models, our study highlights the value of using human respiratory organoids to evaluate human-specific virus-host interactions. This platform provides a complementary tool for assessing the risk of emerging avian influenza viruses. HighlightsO_LIHuman respiratory organoids were used to model zoonotic B3.13 H5N1 infections. C_LIO_LIA cattle-derived human isolate, TX37-H5N1, replicated more efficiently than historical VN1203-H5N1. C_LIO_LITX37-H5N1 suppressed STAT-IRF-mediated innate immune responses. C_LIO_LITX37-H5N1 was sensitive to baloxavir and oseltamivir but less sensitive to favipiravir. C_LIO_LIHuman respiratory organoids offer a complementary platform for zoonotic influenza risk assessment. C_LI In briefOur study used human iPSC-derived respiratory organoids to investigate the mild clinical presentation of zoonotic B3.13 H5N1 viruses. We found that TX37-H5N1 replicates efficiently but suppresses innate immune responses, providing mechanistic insight into species-specific pathogenesis and highlighting the utility of human organoids for zoonotic risk assessment.

microbiology↗

bioRxiv2025

Unsupervised feature computation-based feature selection robustly extracted resting-state functional connectivity patterns related to mental disorders

Research on biomarkers for predicting psychiatric disorders from resting-state functional connectivity (FC) is advancing. While the focus has primarily been on the discriminative performance of biomarkers by machine learning, identification of abnormal FCs in psychiatric disorders has often been treated as a secondary goal. However, it is crucial to investigate the effect size and robustness of the selected FCs because they can be used as potential targets of neurofeedback training or transcranial magnetic stimulation therapy. Here, we incorporated approximately 5,000 runs of resting-state functional magnetic resonance imaging from six datasets, including individuals with three different psychiatric disorders (major depressive disorder [MDD], schizophrenia [SCZ], and autism spectrum disorder [ASD]). We demonstrated that an unsupervised feature-computation-based feature selection method can robustly extract FCs related to psychiatric disorders compared to other conventional supervised feature selection methods. We found that our proposed method robustly extracted FCs with larger effect sizes from the validation dataset compared to different types of feature selection methods based on supervised learning for MDD (Cohens d = 0.40 vs. 0.25), SCZ (0.37 vs. 0.28), and ASD (0.17 vs. 0.16). We found 78, 69, and 81 essential FCs for MDD, SCZ, and ASD, respectively, and these FCs were mainly thalamic and motor network FCs. The current study showed that the unsupervised feature-computation-based feature selection method robustly identified abnormal FCs in psychiatric disorders consistently across datasets. The discovery of such robust FCs will contribute to understanding neural mechanisms as abnormal brain signatures in psychiatric disorders. Furthermore, this finding can aid in developing precise therapeutic interventions, such as neurofeedback training or transcranial magnetic stimulation therapy.

neuroscience↗

bioRxiv2025

Evolution of BA.2.86 to JN.1 reveals functional changes in non-structural viral proteins are required for fitness of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the coronavirus disease 2019 (COVID-19), is still circulating among humans, leading to the continuous evolution. SARS-CoV-2 Omicron JN.1 evolved from a distinct SARS-CoV-2 lineage, BA.2.86, spread rapidly worldwide. It is unclear why BA.2.86 did not become dominant and was quickly replaced by JN.1, which possesses one amino acid substitution in the spike protein (S:L455S) and two in the non-spike proteins NSP6 and ORF7b (NSP6:R252K and ORF7b:F19L) compared to BA.2.86. Here, we utilized recombinant viruses to elucidate the impact of these mutations on the virological characteristics of JN.1. We found that the mutation in the spike attenuated viral replication, but the non-spike mutations enhanced replication, suggesting the mutations in the non-spike proteins compensate for the one in the spike to improve viral fitness, as the mutations in the spike contribute to further immune evasion. Our findings suggest that functional changes in both the spike and non-spike proteins are necessary in the evolution of SARS-CoV-2 to enable evasion of adaptive immunity within the human population while sustaining replication. IMPORTANCEBecause the spike protein is strongly associated with certain virological properties of SARS-CoV-2, such as immune evasion and infectivity, most previous studies on SARS-CoV-2 variants have focused on spike protein mutations. However, the non-spike proteins also contribute to infectivity, as observed throughout the evolution of Omicron subvariants. In this study, we demonstrate a "trade-off" strategy in SARS-CoV-2 Omicron JN.1 in which the reduced infectivity caused by spike mutation is compensated by non-spike mutations. Our results provide insight into the evolutionary scenario of the emerging virus in the human population.

microbiology↗

bioRxiv2024

Generalizability of Normative Models of Brain Morphometry Across Distinct Ethnoracial Groups

Normative modeling of brain morphometric data can inform about the clinical significance of deviations from typical patterns in brain structure. Their usefulness, however, is dependent on their applicability to diverse ethnoracial groups. With this in mind, we developed age- and sex-specific normative models for cortical thickness, surface area, and subcortical volumes using brain scans from 37,407 healthy individuals from a diverse international sample. Here we demonstrate the validity of these models in diverse and distinct populations. Specifically, we tested these pre-trained models on independent samples of healthy individuals that either self-identified as Black, South Asian, East Asian Chinese, East Asian Japanese, or we categorized as African, Admixed American, East Asian, and European based on their genetic ancestry. Regardless of ethnoracial definition, the performance of the pretrained models in these samples was exceptionally high; the relative mean absolute error for each regional brain morphometry measure was less than 10% across all the distinct ethnoracial groups. These findings affirm the broad applicability of our models, ensuring that brain morphometry assessments using these models are accurate and reliable for individuals regardless of background. This broad applicability has significant implications for advancing personalized medicine and improving health outcomes in diverse populations.

bioinformatics↗

bioRxiv2024

Trifunctional fatty acid derivatives demonstrate the impact of diazirine placement

Functionalized lipid probes are a critical new tool to interrogate the function of individual lipid species, but the structural parameters that constrain their utility have not been thoroughly described. Here, we synthesize three palmitic acid derivatives with a diazirine at different positions on the acyl chain and examine their metabolism, subcellular localization, and protein interactions. We demonstrate that while they produce very similar metabolites and subcellular distributions, probes with the diazirine at either end pulldown distinct subsets of proteins after photo-crosslinking. This highlights the importance of thoughtful diazirine placement when developing probes based on biological molecules.

biochemistry↗

bioRxiv2023

Nitrogen signaling factor triggers a respiration-like gene expression program

Microbes have evolved intricate communication systems that enable individual cells of a population to send and receive signals in response to changes in their immediate environment. In the fission yeast Schizosaccharomyces pombe, the oxylipin Nitrogen Signaling Factor (NSF) is part of such communication system, which functions to regulate the usage of different nitrogen sources. Yet, the pathways and mechanisms by which NSF acts are poorly understood. Here, we show that NSF physically interacts with the mitochondrial sulfide:quinone oxidoreductase Hmt2 and that it prompts a change from a fermentation- to a respiration-like gene expression program independently of the carbon source. Our results suggest that NSF activity is not restricted to nitrogen metabolism alone and that it could function as a rheostat to prepare a population of S. pombe cells for an imminent shortage of their preferred nutrients.

microbiology↗

bioRxiv2023

Estimating multimodal brain variability in schizophreniaspectrum disorders: A worldwide ENIGMA study

ObjectiveSchizophrenia is a multifaceted disorder associated with structural brain heterogeneity. Despite its relevance for identifying illness subtypes and informative biomarkers, structural brain heterogeneity in schizophrenia remains incompletely understood. Therefore, the objective of this study was to provide a comprehensive insight into the structural brain heterogeneity associated with schizophrenia. MethodsThis meta- and mega-analysis investigated the variability of multimodal structural brain measures of white and gray matter in individuals with schizophrenia versus healthy controls. Using the ENIGMA dataset of MRI-based brain measures from 22 international sites with up to 6139 individuals for a given brain measure, we examined variability in cortical thickness, surface area, folding index, subcortical volume and fractional anisotropy. ResultsWe found that individuals with schizophrenia are distinguished by higher heterogeneity in the frontotemporal network with regard to multimodal structural measures. Moreover, individuals with schizophrenia showed higher homogeneity of the folding index, especially in the left parahippocampal region. ConclusionsHigher multimodal heterogeneity in frontotemporal regions potentially implies different subtypes of schizophrenia that converge on impaired frontotemporal interaction as a core feature of the disorder. Conversely, more homogeneous folding patterns in the left parahippocampal region might signify a consistent characteristic of schizophrenia shared across subtypes. These findings underscore the importance of structural brain variability in advancing our neurobiological understanding of schizophrenia, and aid in identifying illness subtypes as well as informative biomarkers.

neuroscience↗

bioRxiv2023

Virological characteristics of the SARS-CoV-2 XBB.1.5 variant

Circulation of SARS-CoV-2 Omicron XBB has resulted in the emergence of XBB.1.5, a new Variant of Interest. Our phylogenetic analysis suggests that XBB.1.5 evolved from XBB.1 by acquiring the F486P spike (S) mutation, subsequent to the acquisition of a nonsense mutation in ORF8. Neutralization assays showed similar abilities of immune escape between XBB.1.5 and XBB.1. We determined the structural basis for the interaction between human ACE2 and the S protein of XBB.1.5, showing similar overall structures between the S proteins of XBB.1 and XBB.1.5. The intrinsic pathogenicity of XBB.1.5 in hamsters is lower than that of XBB.1. Importantly, we found that the ORF8 nonsense mutation of XBB.1.5 resulted in impairment of MHC expression. In vivo experiments using recombinant viruses revealed that the XBB.1.5 mutations are involved with reduced virulence of XBB.1.5. Together, these data suggest that the mutations in ORF8 and S could enhance spreading of XBB.1.5 in humans.

microbiology↗

bioRxiv2022

Comparative pathogenicity of SARS-CoV-2 Omicron subvariants including BA.1, BA.2, and BA.5

Unremitting emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants imposes us to continuous control measurement. Given the rapid spread, new Omicron subvariant named BA.5 is urgently required for characterization. Here we analyzed BA.5 with the other Omicron variants BA.1, BA.2, and ancestral B.1.1 comprehensively. Although in vitro growth kinetics of BA.5 is comparable among the Omicron subvariants, BA.5 become much more fusogenic than BA.1 and BA.2. The airway-on-a-chip analysis showed that the ability of BA.5 to disrupt the respiratory epithelial and endothelial barriers is enhanced among Omicron subvariants. Furthermore, in our hamster model, in vivo replication of BA.5 is comparable with that of the other Omicrons and less than that of the ancestral B.1.1. Importantly, inflammatory response against BA.5 is strong compared with BA.1 and BA.2. Our data suggest that BA.5 is still low pathogenic compared to ancestral strain but evolved to induce enhanced inflammation when compared to prior Omicron subvariants.

microbiology↗

bioRxiv2022

Development of a new 3D tracking system for multiple marmosets under free-moving conditions

Assessment of social interactions and behavioral changes in nonhuman primates is useful for understanding brain function changes during life events and pathogenesis of neurological diseases. The common marmoset (Callithrix jacchus), that lives in a nuclear family like humans, is a useful model, but long-term automated behavioral observation of multiple animals has not been achieved. Here, we developed a Full Monitoring and Animal Identification (FulMAI) system for long-term detection of three-dimensional (3D) trajectories of each individual in multiple marmosets under free-moving conditions by combining video tracking, Light Detection And Ranging, and deep learning. Using this system, identification of each animal was more than 97% accurate. Location preferences and inter-individual distance could be calculated, and deep learning could detect grooming behavior. The FulMAI system allows us to analyze the natural behavior of individuals in a family over their lifetime and understand how behavior changes due to life events together with other data.

animal behavior and cognition↗

bioRxiv2020

Promoter activity-based case-control association study on SLC6A4 highlighting hypermethylation and altered amygdala volume in male patients with schizophrenia

Associations between altered DNA methylation of the serotonin transporter (5-HTT)-encoding gene SLC6A4 and early life adversity, mood and anxiety disorders, and amygdala reactivity have been reported. However, few studies have examined epigenetic alterations of SLC6A4 in schizophrenia (SZ). We examined CpG sites of SLC6A4, whose DNA methylation levels have been reported to be altered in bipolar disorder, using three independent cohorts of patients with SZ and age-matched controls. We found significant hypermethylation of a CpG site in SLC6A4 in male patients with SZ in all three cohorts. We showed that chronic administration of risperidone did not affect the DNA methylation status at this CpG site using common marmosets, and that in vitro DNA methylation at this CpG site diminished the promoter activity of SLC6A4. We then genotyped the 5-HTT-linked polymorphic region (5-HTTLPR) and investigated the relationship among 5-HTTLPR, DNA methylation, and amygdala volume using brain imaging data. We found that patients harboring low-activity 5-HTTLPR alleles showed hypermethylation and they showed a negative correlation between DNA methylation levels and left amygdala volumes. These results suggest that hypermethylation of the CpG site in SLC6A4 is involved in the pathophysiology of SZ, especially in male patients harboring low-activity 5-HTTLPR alleles.

genetics↗

bioRxiv2019

Polygenic architecture of human neuroanatomical diversity

We analysed the genomic architecture of neuroanatomical diversity using magnetic resonance imaging and single nucleotide polymorphism (SNP) data from >26,000 individuals from the UK Biobank project and 5 other projects that had previously participated in the ENIGMA consortium. Our results confirm the polygenic architecture of neuroanatomical diversity, with SNPs capturing from 40% to 54% of regional brain volume variance. Chromosomal length correlated with the amount of phenotypic variance captured, r[~]0.64 on average, suggesting that at a global scale causal variants are homogeneously distributed across the genome. At a local scale, SNPs within genes ([~]51%) captured [~]1.5 times more genetic variance than the rest; and SNPs with low minor allele frequency (MAF) captured less variance than the rest: the 40% of SNPs with MAF<5% captured <1/4th of the genetic variance. We also observed extensive pleiotropy across regions, with an average genetic correlation of rG[~]0.45. Genetic correlations were similar to phenotypic and environmental correlations, however, genetic correlations were often larger than phenotypic correlations for the left/right volumes of the same region. The heritability of differences in left/right volumes was generally not statistically significant, suggesting an important influence of environmental causes in the variability of brain asymmetry. Our code is available at https://github.com/neuroanatomy/genomic-architecture.

neuroscience↗

bioRxiv2018

Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias

When collecting large neuroimaging data associated with psychiatric disorders, images must be acquired from multiple sites because of the limited capacity of a single site. However, site differences represent the greatest barrier when acquiring multi-site neuroimaging data. We utilized a traveling-subject dataset in conjunction with a multi-site, multi-disorder dataset to demonstrate that site differences are composed of biological sampling bias and engineering measurement bias. Effects on resting-state functional MRI connectivity because of both bias types were greater than or equal to those because of psychiatric disorders. Furthermore, our findings indicated that each site can sample only from among a subpopulation of participants. This result suggests that it is essential to collect large neuroimaging data from as many sites as possible to appropriately estimate the distribution of the grand population. Finally, we developed a novel harmonization method that removed only the measurement bias by using traveling-subject dataset and achieved the reduction of the measurement bias by 29% and the improvement of the signal to noise ratios by 40%.

neuroscience↗

bioRxiv2018

Overlapping but asymmetrical relationships between schizophrenia and autism revealed by brain connectivity

(Abstract included 248 words)Although the relationship between schizophrenia spectrum disorder (SSD) and autism spectrum disorder (ASD) has long been debated, it has not yet been fully elucidated. To address this issue, we took advantage of dual (ASD and SSD) classifiers that discriminate patients from their controls based on resting state brain functional connectivity. An SSD classifier using sophisticated machine-learning algorithms that automatically selected SSD- specific functional connections was applied to Japanese datasets including adult patients with SSD in a chronic stage. We demonstrated good performance of the SSD classification for independent validation cohorts. The generalizability was tested by USA and European cohorts in a chronic stage, and one USA cohort including first episode schizophrenia. The specificity was tested by two adult Japanese cohorts of ASD and major depressive disorder, and one European cohort of attention-deficit hyperactivity disorder. The weighted linear summation of the classifiers functional connections constituted the biological dimensions representing neural liability to the disorders. Our previously developed robust ASD classifier constituted the ASD dimension. Distributions of individuals with SSD, ASD and healthy controls were examined on the SSD and ASD biological dimensions. The SSD and ASD populations exhibited overlapping but asymmetrical patterns on the two biological dimensions. That is, the SSD population showed increased liability on the ASD dimension, but not vice versa. Furthermore, the two dimensions were correlated within the ASD population but not the SSD population. Using the two biological dimensions based on resting-state functional connectivity enabled us to quantify and visualize the relationships between SSD and ASD.

neuroscience↗

bioRxiv2017

A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity

Individual differences in cognitive function have been shown to correlate with brain-wide functional connectivity, suggesting a common foundation relating connectivity to cognitive function across healthy populations. However, it remains unknown whether this relationship is preserved in cognitive deficits seen in a range of psychiatric disorders. Using machine learning methods, we built a prediction model of working memory function from whole-brain functional connectivity among a healthy population (N = 17, age 19-24 years). We applied this normative model to a series of independently collected resting state functional connectivity datasets (N = 968), involving multiple psychiatric diagnoses, sites, ages (18-65 years), and ethnicities. We found that predicted working memory ability was correlated with actually measured working memory performance in both schizophrenia patients (partial correlation,{rho} = 0.25, P = 0.033, N = 58) and a healthy population (partial correlation,{rho} = 0.11, P = 0.0072, N = 474). Moreover, the model predicted diagnosis-specific severity of working memory impairments in schizophrenia (N = 58, with 60 controls), major depressive disorder (N = 77, with 63 controls), obsessive-compulsive disorder (N = 46, with 50 controls), and autism spectrum disorder (N = 69, with 71 controls) with effect sizes g = -0.68, -0.29, -0.19, and 0.09, respectively. According to the model, each diagnosiss working memory impairment resulted from the accumulation of distinct functional connectivity differences that characterizes each diagnosis, including both diagnosis-specific and diagnosis-invariant functional connectivity differences. Severe working memory impairment in schizophrenia was related not only with fronto-parietal, but also widespread network changes. Autism spectrum disorder showed greater negative connectivity that related to improved working memory function, suggesting that some non-normative functional connections can be behaviorally advantageous. Our results suggest that the relationship between brain connectivity and working memory function in healthy populations can be generalized across multiple psychiatric diagnoses. This approach may shed new light on behavioral variances in psychiatric disease and suggests that whole-brain functional connectivity can provide an individual quantitative behavioral profile in a range of psychiatric disorders.

neuroscience↗

bioRxiv2017

Placental gene expression mediates the interaction between obstetrical history and genetic risk for schizophrenia

Defining the environmental context in which genes enhance susceptibility can provide insight into the pathogenesis of complex disorders, like schizophrenia. Here we show that the intrauterine and perinatal environment modulates the association of schizophrenia with genomic risk, as measured with polygenic risk scores (PRS) based primarily on GWAS significant variants. Genomic risk interacts with intrauterine and perinatal complications (Early Life Complications, ELCs) in each of three independent samples from USA, Italy and Germany (overall n= 1693, p= 6e-05). In each sample, the liability of schizophrenia explained by PRS is nominally more than five times greater in the presence of a history of ELCs compared with its absence. In each sample, patients with positive ELC histories have higher PRS than patients without ELCs, which is further confirmed in two additional patient samples from Germany and Japan (overall n=2038, p= 1e-04). The gene set based on the schizophrenia loci interacting with ELCs is highly expressed in multiple placental compartments and dynamically regulated in placenta from complicated in comparison with normal pregnancies. The same genes are differentially up-regulated in placentae from male compared with female offspring. The interaction between genomic risk and ELCs is mainly driven by GWAS significant loci enriched for genes highly expressed in the various placenta samples. Molecular pathway analyses based on the genes not driving this interaction reflect previous analyses about schizophrenia risk-genes, while genes highly and differentially expressed in placentae implicate an orthogonal biology involving cellular stress. These results suggest that the most significant genetic variants detected by current schizophrenia GWAS contribute to risk in part by converging on a developmental trajectory sensitive to events affecting placentation, which may underlie the male preponderance of schizophrenia and offer new insights into primary prevention.

genetics↗