Biology subjects

Nakaya, H.

Publications and source records attributed to Nakaya, H..

10 recordsLinked to original sources

bioRxiv2026

Decoding the RNA Splicing Network in HNRNPH2-R114W Brain Organoids

Autism spectrum disorder and related neurodevelopmental diseases are increasingly linked to disrupted RNA processing during corticogenesis, yet resolving variant-specific mechanisms during early human development remains challenging. We generated isogenic cerebral organoids from a patient iPSC line carrying the HNRNPH2-R114W mutation and its CRISPR-corrected counterpart. Developmental validation by time-course imaging, followed by bulk RNA-Seq at day 20, showed comparable early differentiation and corticogenesis. Genotype was the primary determinant of global expression state, with organized remodeling of neuronal and metabolic programs. Splicing analyses demonstrated junction-dominant dysregulation, where 6,310 junctions exhibited significant differential usage. Junction-level resolution revealed a dominant genotype-related signal than exon-centric analysis. A structural docking model shows HNRNPH2 RNA recognition motifs 1-3 within a spliceosomal context and position residue R114 at an RNA-contact cleft, consistent with direct disruption of RNA engagement by R114W. Integrating differential expression with event- and isoform-level evidence prioritized convergent regulatory hubs enriched for axon guidance, synaptic signaling, and extracellular matrix programs. Single-cell RNA-Seq deconvolution revealed modest compositional shifts that do not account for the magnitude of transcriptional and splicing alterations. Collectively, these data support that HNRNPH2-R114W drives pervasive, junction-centered RNA rewiring in human cortical organoids and defines isoform-level endpoints for mechanistic studies and therapeutic testing in an isogenic developmental model.

neuroscience↗

bioRxiv2025

Innate antiviral readiness drives the expansion of protective T stem cell memory against influenza

The development of T-cell-based influenza vaccines relies on eliciting broad CD8+ T-cell immunity, wherein T stem cell-like memory (TSCM) cells serve as the ultimate long-lived reservoir for immune memory, thereby unlocking the potential for durable protection against viral drift and shift. However, the specific immunological cues that drive the robust expansion and functional preservation of this self-renewing, multipotent subset remain unknown. Here, utilizing multi-omic systems immunology in a pediatric cohort immunized with live attenuated influenza vaccine, we identified the determinants governing the expansion of influenza virus-reactive TSCM cells. We show that a pre-existing state of innate antiviral readiness, defined by a plasmacytoid dendritic cell-associated type I interferon signature, is the requisite condition for a robust TSCM expansion. Mechanistically, this baseline innate state enhances antigen priming and enforces a qualitative divergence in T-cell fate, driving responders toward a functionally poised, Th1-dominant phenotype while non-responders default to a dysfunctional, hyper-proliferative state. To determine the clinical relevance of this cellular subset, we analyzed an independent controlled human influenza challenge study. This validation revealed a critical functional division of labor in host defense: whereas pre-existing antibodies primarily mitigated symptom severity, the baseline frequency of influenza virus-reactive TSCM cells was the strongest predictor of rapid viral load clearance. These findings establish that the expansion of durable cellular memory is not stochastic but is predetermined by the innate cytokine environment, providing a predictive biomarker for patient stratification and a validated target for adjuvants designed to expand the TSCM reservoir deliberately.

immunology↗

bioRxiv2025

Long Non-Coding RNAs in Response to Ebola Virus Vaccine-Induced Immunity

Long noncoding RNAs (lncRNAs) have emerged as critical regulators of gene expression, yet their role in shaping human responses to vaccination remains largely uncharacterized. Here, we analyzed RNA-sequencing data from three independent human cohorts vaccinated with the rVSV{Delta}G-ZEBOV-GP Ebola vaccine to profile lncRNA expression dynamics. Using differential expression analysis and correlation meta-analysis across cohorts, we identified an expression signature with several lncRNAs, including LEF1-AS1 and DOCK8-AS1, that exhibit conserved transcriptional activation following vaccination. Correlation of lncRNA expression with gene targets and IgG titers revealed putative roles for lncRNAs in regulating and/or participate in both innate immune responses and adaptive antibody production. Functional enrichment of lncRNA co-expressed protein-coding genes highlighted involvement in T-cell differentiation, interferon signaling, and leukocyte activation. Integrating global run-on sequencing data and comparative transcriptomic analysis across other vaccine studies suggests that LEF1-AS1 modulation is distinctively associated with Ebola vaccination. Our findings demonstrate that lncRNAs are potential integral components of the human vaccine response and provide a foundation for future mechanistic studies targeting noncoding RNA regulation of immunity SignificanceEbola virus remains a significant global health threat due to its high mortality rate and potential for widespread outbreaks, underscoring the urgent need for effective and durable vaccines to control future epidemics. Understanding the transcriptional mechanisms underlying immune responses to vaccination is important to improving vaccine design and efficacy. While protein-coding genes have been extensively studied, the role of long noncoding RNAs (lncRNAs) in vaccine-induced immunity remains poorly understood. Here, we characterize the dynamics of lncRNA expression following administration of the rVSV{Delta}G-ZEBOV-GP Ebola vaccine across multiple human cohorts and identify conserved lncRNA signatures associated with both innate and adaptive immunity. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=154 SRC="FIGDIR/small/671152v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@25581aorg.highwire.dtl.DTLVardef@1bb31cforg.highwire.dtl.DTLVardef@c3299eorg.highwire.dtl.DTLVardef@e176b9_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2025

Integrative Mapping of Pre-existing Immune Landscapes for Vaccine Response Prediction

Predicting individual vaccine responses remains a significant challenge due to the complexity and variability of immune processes. To address this gap, we developed immunaut, an open-source, data-driven framework implemented as an R package specifically designed for all systems vaccinologists seeking to analyze and predict immunological outcomes across diverse vaccination settings. Leveraging one of the most comprehensive live attenuated influenza vaccine (LAIV) datasets to date - 244 Gambian children enrolled in a phase 4 immunogenicity study - immunaut integrates humoral, mucosal, cellular, transcriptomic, and microbiological parameters collected before and after vaccination, providing an unprecedentedly holistic view of LAIV-induced immunity. Through advanced dimensionality reduction, clustering, and predictive modeling, immunaut identifies distinct immunophenotypic responder profiles and their underlying baseline determinants. In this study, immunaut delineated three immunophenotypes: (1) CD8 T-cell responders, marked by strong baseline mucosal immunity and extensive prior influenza virus exposure that boosts memory CD8 T-cell responses, without generating influenza virus-specific antibody responses; (2) Mucosal responders, characterized by pre-existing systemic influenza A virus immunity (specifically to H3N2) and stable epithelial integrity, leading to potent mucosal IgA expansions and subsequent seroconversion to influenza B virus; and (3) Systemic, broad influenza A virus responders, who start with relatively naive immunity and leverage greater initial viral replication to drive broad systemic antibody responses against multiple influenza A virus variants beyond those included in the LAIV vaccine. By integrating pathway-level analysis, model-derived contribution scores, and hierarchical decision rules, immunaut elucidates how distinct immunological landscapes shape each response trajectory and how key baseline features, including pre-existing immunity, mucosal preparedness, and cellular support, dictate vaccine outcomes. Collectively, these findings emphasize the power of integrative, predictive frameworks to advance precision vaccinology, and highlight immunaut as a versatile, community-available resource for optimizing immunization strategies across diverse populations and vaccine platforms. One-Sentence SummaryUsing one of the most comprehensive LAIV datasets compiled to date, immunaut, an integrative machine learning framework, identifies distinct immunophenotypic responder groups shaped by baseline immune landscapes, advancing precision vaccinology and guiding more effective, personalized immunization strategies. Graphical abstractImmunaut, an automated framework for mapping and predicting vaccine response immunotypes. Step 1 outlines the identification of vaccine response outcomes using pre- and post-vaccination data integration across immune features, including antibodies, flu-specific T-cells, and immunophenotyping at mucosal and systemic sites. Clustering methods define the vaccine response landscape, stability, and validation through t-SNE-based visualization. Step 2 leverages an automated machine learning modeling approach, to enhance the accuracy and interpretability of vaccine response predictions, enabling stratification and targeted intervention strategies for personalized vaccine immunogenicity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC="FIGDIR/small/634302v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@62276corg.highwire.dtl.DTLVardef@a5f25org.highwire.dtl.DTLVardef@eca34borg.highwire.dtl.DTLVardef@1d4999b_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

Generation of a T cell receptor, cytokine and cell repertoire synovial fluid atlas to define commonalities and dissimilarities between arthritic diseases through systems immunology approaches

Although different chronic arthritic diseases are defined by clinical factors like gender, psoriasis and auto-antibodies, the biology of inflamed joints while comparing the different diseases remains neglected. Here, after curating an inflamed joint derived T-cell receptor (TCR) database, our new TRIASSIC tool identified 66303 significantly convergent TCR clonotypes. Clustering TCR clonotypes showed that synovial fluid convergence clusters (SFCCs) characterized HLA-B27+ mediated diseases (spondyloarthritis, SpA, and enthesitis-related juvenile idiopathic arthritis, JIA-ERA), Lyme arthritis and oligoarticular JIA. Single-cell transcriptomics and bulk proteomics showed upregulated interferon type I and II and TNF- pathways in oJIA. Adult and juvenile psoriatic arthritis, (JIA-)PsA, was characterized by upregulated HSP expression in monocytes and TXNIP in T-cells. We discovered an abundance of CCL5 expressing CD8+ T-cells in SF from HLA-B27+ JIA-ERA and SpA patients. JIA-ERA patients showed upregulation of CD74 and LGALS1 in Th1 and Th17 cells and IGHV7-4.1 in B-cells. oJIA patients shared a TRBV28 RG-motif on CXCL13 producing helper T-cells. Rheumatoid arthritis and (JIA-)PsA patients carried EBV-reactive cytotoxic CD8+ T-cells. Annexin signalling was shown to be important in the intercellular communication for all arthritis groups. Collectively, our work showed that chronic arthritis is characterized by both disease-specific and broadly shared mechanisms.

immunology↗

bioRxiv2024

Dysregulation of synaptic-related genes within neuroimmune networks of peripheral blood mononuclear cells in major depressive disorder

Major depressive disorder (MDD) involves complex neuroimmune interactions linked to gene modulation. Our study investigates synaptic-related gene dysregulation in peripheral blood mononuclear cells (PBMCs) from MDD patients, showing how these immune cells mirror neural processes. Using RNA-seq data, we identified 1,383 differentially expressed genes (DEGs) related to neuroimmune crosstalk, with 49 DEGs effectively distinguishing MDD patients from controls based on synaptic functions. Synaptic genes, enriched for roles like vesicle transport, suggest mechanistic links between immune cells and neural signaling. Eleven synaptic-related DEGs were shared between PBMCs and brain regions involved in mood regulation, highlighting a common molecular signature. Among them, ADORA3 and RPS28 emerged as potential biomarkers. These findings highlight the potential of PBMCs in the diagnosis and treatment of MDD, reinforcing the development of future neuroimmune-targeted therapies for depression.

bioinformatics↗

bioRxiv2023

SARS-CoV-2 selectively induces the expression of unproductive splicing isoforms of interferon, class I MHC and splicing machinery genes

Splicing is a highly conserved, intricate mechanism intimately linked to transcription elongation, serving as a pivotal regulator of gene expression. Alternative splicing may generate specific transcripts incapable of undergoing translation into proteins, designated as unproductive. A plethora of respiratory viruses, including Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), strategically manipulate the hosts splicing machinery to circumvent antiviral responses. During the infection, SARS-CoV-2 effectively suppresses interferon (IFN) expression, leading to B cell and CD8+ T cell leukopenia, while simultaneously increasing the presence of macrophages and neutrophils in patients with severe COVID-19. In this study, we integrated publicly available omics datasets to systematically analyze transcripts at the isoform level and delineate the nascent-peptide translatome landscapes of SARS-CoV-2-infected human cells. Our findings reveal a hitherto uncharacterized mechanism whereby SARS-CoV-2 infection induces the predominant expression of unproductive splicing isoforms in key IFN signaling genes, interferon-stimulated genes (ISGs), class I MHC genes, and splicing machinery genes, including IRF7, OAS3, HLA-B, and HNRNPH1. In stark contrast, cytokine and chemokine genes, such as IL6, CXCL8, and TNF, predominantly express productive (protein-coding) splicing isoforms in response to SARS-CoV-2 infection. We postulate that SARS-CoV-2 employs a previously unreported tactic of exploiting the host splicing machinery to bolster viral replication and subvert the immune response by selectively upregulating unproductive splicing isoforms from antigen presentation and antiviral response genes. Our study sheds new light on the molecular interplay between SARS-CoV-2 and the host immune system, offering a foundation for the development of novel therapeutic strategies to combat COVID-19.

bioinformatics↗

bioRxiv2022

Polycomb Repressive Complex 1 subunit Cbx4 positively regulates effector responses in CD8 T cells

CD8 T cell differentiation is controlled by the crosstalk of various transcription factors and epigenetic modulators. Uncovering the different players in regulating this process is fundamental to improving immunotherapy and designing novel therapeutic approaches. Here, we show that Polycomb Repressive Complex (PRC)1 subunit Chromobox (Cbx)4 favors differentiation to effector CD8 T cells. Cbx4 deficiency in CD8 T cells induced transcriptional signature and phenotype of memory cells, increasing the formation of memory population during acute viral infection. It has been previously shown that besides chromodomain-mediated binding to H3K27me3, Cbx4 function as a SUMO E3 ligase in a SUMO interacting motifs (SIM)-dependent way. The overexpression of Cbx4 mutants in distinct domains showed that this protein regulates CTL differentiation primarily in a SIM-dependent way and partially through its chromodomain. Our data revealed a novel role of a Polycomb group protein Cbx4 controlling CD8 T lymphocyte differentiation and indicates the SUMOylation process as a key molecular mechanism connected to chromatin modification in this process. SummaryUnderstanding the epigenetic control of CTL differentiation is critical for the manipulation of these cells in immunotherapy protocols. This article demonstrates a novel role for Cbx4, a Polycomb-group protein, in supporting CD8 T cell commitment to an effector cell phenotype.

immunology↗

bioRxiv2021

Using coexpression to explore cell-type diversity with the fcoex package

Here, we present the fcoex package, which infers coexpression from scRNA-seq data and yields multiple, overlapping classes of cells based on coexpression modules. The tool extends the current scRNA-seq toolbox, providing a multi-hierarchy view on cell functionality and enabling the development of more complete cell atlases. Single-cell RNA sequencing (scRNA-seq) captures details of the cellular landscape, basing a fine-grained view on biological processes. Current pipelines, however, are restricted to single-label perspectives, missing details of the classification landscape. In the pbmc3k blood cell dataset, fcoex detects known classes, like antigen-presenting cells and a new theoretical group of cells, marked by the expression of FCGR3A (CD16). Fcoex extends the current scRNA-seq toolbox, providing a multi-hierarchy view on cell functions as a tool to develop complete cell type atlases. Availability and ImplementationFcoex is written in R and openly available in Bioconductor (https://bioconductor.org/packages/fcoex/). Supplementary informationSupplementary data is available at the end of the manuscript. Source code for analysis is available at https://github.com/csbl-inovausp/fcoex_analysis;

systems biology↗

bioRxiv2019

Platelet disturbances correlate with endothelial cell activation in uncomplicated Plasmodium vivax malaria

IntroductionPlatelets drive endothelial cell activation in many diseases. However, if this occurs in Plasmodium vivax malaria is unclear. As platelets have been reported to be activated and to play a role in inflammatory response during malaria, we hypothesized that this would correlate with endothelial alterations during acute illness.\n\nMethodsWe performed platelet flow cytometry of PAC-1 and P-selectin. We measured Platelet markers (CXCL4, CD40L, P-selectin, Thrombopoietin, IL-11) and endothelial markers (ICAM-1, von Willebrand Factor and E-selectin) in plasma with a multiplex-based assay. The values of each mediator were used to generate heatmaps, K-means clustering and Principal Component analysis. In addition, we determined pair-wise Pearsons correlation coefficients to generate correlation networks.\n\nResultsPlatelet counts were reduced, and mean platelet volume increased in malaria patients. The activation of circulating platelets in flow cytometry did not differ between patients and controls. CD40L levels (Median [IQ]: 517 [406-651] vs. 1029 [732- 1267] pg/mL, P=0.0001) were significantly higher in patients, while P-selectin (Median [IQ]: 17.0 [15.4-20.6] vs. 22.2 [17.6-25.7] ng/mL, P=0.0621) and CXCL4 showed a nonsignificant trend towards higher levels in patients. The network correlation approach demonstrated the correlation between markers of platelet and endothelial activation, and the heatmaps revealed a distinct pattern of activation in two subsets of P. vivax patients when compared to controls.\n\nConclusionplatelet activation occurs in uncomplicated vivax malaria and this correlates with higher endothelial cell activation, especially in a subset of patients.\n\nAUTHOR SUMMARYEndothelial cell activation is a key process in the pathogenesis of Plasmodium vivax malaria. Platelets are classically involved endothelial cell activation in several diseases, but their role in context of vivax malaria remains unclear. Thrombocytopenia is the most common hematological disturbance in P. vivax-infected patients, and platelets have been implicated in parasitemia control. In this study, we studied the activation of platelets in association with endothelial cell activation in vivax malaria. Platelets retrieved from infected peripheral blood were non-activated when analyzed by flow cytometry; however, they displayed higher mean volume and significantly reduced counts. We also found higher levels of circulating factors associated with platelet activation (especially CD40L), thrombopoiesis and endothelial cell activation in infected patients. Further, through pair-wise correlation and clustering analysis, we found a subgroup of patients showing significant associations between markers of platelet and endothelial activation in a pattern different from that of endemic controls. Collectively, our findings point to a peculiar role of platelets in endothelial cell activation in vivax malaria and indicate a heterogeneous host response in the setting of uncomplicated disease, a finding to be further explored in future studies.

immunology↗