Biology subjects

Kaji, H.

Publications and source records attributed to Kaji, H..

8 recordsLinked to original sources

bioRxiv2026

Reverse genetics system for emerging tick-borne orthonairovirus highlights dispensable N-terminal region of Gn associated with replication in tick vectors

A growing number of emerging and re-emerging tick-borne orthonairoviruses belonging to the Sulina and Tamdy genogroups have recently been identified in association with febrile diseases in East Asia. Yezo virus (YEZV) is one such viruses and is genetically distinct from well-characterized Crimean-Congo hemorrhagic fever virus. Orthonairovirus glycoproteins (Gn and Gc) expressed from a single glycoprotein precursor (GPC) gene mediate interaction with host cells, yet the organization and functions of the YEZV glycoproteins remain largely undefined. To characterize YEZV glycoproteins in the context of infection, we developed a reverse genetics system that enables recovery of recombinant YEZV entirely from cloned cDNAs. The recombinant wild-type virus exhibited growth properties comparable to those of the parental isolate in vitro and maintained pathogenicity in vivo. Proteomic analysis of purified virus particles produced in mammalian cells showed that peptide coverage of GPC-derived products began at residue 69. We therefore used the reverse genetics system to examine the functional importance of the GPC subregion upstream of residue 69. A mutant with a deletion of GPC residues 28 to 68 (rYEZV GPC{Delta}28-68), which retained the predicted signal peptide, was successfully recovered, suggesting that this subregion is dispensable for producing infectious virus. rYEZV GPC{Delta}28-68 propagated at levels comparable to those of the wild-type virus in mammalian cells and exhibited similar pathogenicity in a mouse model. Interestingly, the mutant reached lower viral titers in tick-derived ISE6 cells and in ticks in vivo, suggesting that this N-terminal subregion may contribute to virus replication in ticks. Together, these findings demonstrate the utility of the newly established reverse genetics system for dissecting the functions of the YEZV glycoproteins in mammalian and tick systems.

microbiology↗

bioRxiv2026

Three-dimensional vascular microenvironments uncover endothelial plasticity during TGF-β2-driven vascular remodeling

The tumor microenvironment plays a pivotal role in tumor development, harboring elements such as endothelial cells, immune cells, fibroblasts, and soluble factors such as transforming growth factor-{beta} (TGF-{beta}) family. TGF-{beta} family regulates cell development and promotes tumor invasion, metastasis, angiogenesis, and endothelial-to-mesenchymal transition (EndoMT). Here, we investigate the effects of TGF-{beta} signaling on vascular remodeling using a three-dimensional (3D) vascular network in a microfluidic device. Using both a co-culture (3D-Co) and simplified endothelial monoculture (3D-CM), we demonstrate that TGF-{beta} signaling reduces the quality and functionality of the vasculature by regressing them. In addition, we observed the upregulation of EndoMT-related markers in mRNA and protein expressions, suggesting the induction of EndoMT in 3D vascular networks. The increased vascular permeability stimulated by TGF-{beta}2 also supports the loss of endothelial identity in the 3D-Co. Transcriptomic analysis revealed the coordinated activation of pathways associated with cell migration and EndoMT, along with the suppression of cell cycle progression. A comparative analysis of two-dimensional (2D) and 3D cultures revealed a fundamentally distinct endothelial response to TGF-{beta}2 in the 3D context, including metabolic reprogramming. These findings demonstrate that the 3D microenvironment critically modulates endothelial responses to TGF-{beta} and enables the emergence of vascular phenotypes not captured in 2D systems. This study provides a more physiologically relevant platform to investigate endothelial dysfunction and vascular remodeling.

bioengineering↗

bioRxiv2026

Real-time mass defect-driven prediction of glycopeptide precursors enables enrichment-free serum glycoproteomics

Glycopeptide enrichment remains a cornerstone in glycoproteomics, but bias and reproducibility issues continue to hinder biological insight and clinical translation. Employing curated glycoproteomics datasets and machine learning, we trained a glycopeptide classifier to recognize N-glycopeptide precursors through mass defect signatures. Integration of the classifier into a data-dependent acquisition framework facilitated real-time prediction of N-glycopeptides from human serum and revealed sex differences in murine plasma fucosylation opening avenues for enrichment-free glycoproteomics.

bioinformatics↗

bioRxiv2025

Comparative Evaluation of Glycoproteomics Software for Rare Glycopeptide Identification

Advancements in glycoproteomics software have improved glycopeptide identification; however, algorithm differences cause discrepancies in identified glycopeptide, even when identical datasets. We compared five state-of-the-art glycoproteomics software programs (Byonic, MSFragger-Glyco, pGlyco3, Glyco-Decipher, and GRable), investigating their unique capabilities, and examined their ability to identify rare sialic acid-containing glycopeptides (NeuGc and KDN) derived from BJAB-K20 cells, which lack UDP-N-acetylglucosamine 2-epimerase, the rate-limiting enzyme for sialic acid synthesis. Approximately half of the identified glycopeptides were unique to individual tools. Byonic identified the highest number of glycopeptides, whereas Glyco-Decipher and GRable identified complex highly branched glycan structures. NeuGc- and KDN-containing glycopeptides were identified by specific programs, highlighting their capability to handle rare glycan structures. To assess the reliability of these identifications, we reanalyzed the MS/MS spectra for the presence of diagnostic ions corresponding to each identified glycopeptide. Some software programs identified glycopeptides without detecting the corresponding diagnostic ions, raising concerns regarding result reliability. However, leveraging the distinct capabilities of each software enabled us to achieve a comprehensive and reliable analysis of glycopeptides, including those with rare glycan structures. Combining multiple glycoproteomics software programs with complementary strengths and incorporating post- verification steps, such as diagnostic ion analysis, enhances the accuracy and depth of glycopeptide identification.

biochemistry↗

bioRxiv2025

Sinusoidal regulation denoises circadian machinery

The rhythms transmitted from the circadian clock inevitably fluctuate because of molecular noise. The level of period fluctuations, observed not in the circadian clock, but in the output system that receives the transmitted rhythm, varies according to the organism and cell type, ranging from 0.5% to 10%. However, it remains unclear how the signal transduction involved in this transmission affects the fluctuations in the oscillation period of the output system. To address this, we investigated a coupled system consisting of a circadian clock and its output. We numerically and analytically demonstrated that the rhythmic regulation through which the clock controls downstream gene expression affects the level of fluctuations in the output system. Moreover, Gibbs sampling based on the analytically obtained fluctuation formula confirmed that the sine-wave-like regulatory functions effectively minimized the fluctuation of the output system. These theoretical insights provide new perspectives on signal transduction as a denoising mechanism embodied in the circadian system. Author summaryRecent single-cell observations have revealed that individual cells exhibit circadian rhythms with intrinsic variability. In particular, the period fluctuation, evaluated using the coefficient of variation (CV), was studied. In this study, we investigated how signal transduction from the central clock affects period fluctuations in the output system. We identified a key factor influencing these fluctuations: the waveform of the regulatory function by which the circadian clock governs the downstream output. We numerically demonstrated that the fluctuations vary widely depending on the regulatory function and that the sinusoidal function significantly reduced fluctuations in the output system. Furthermore, Gibbs sampling revealed that sine-like regulatory functions effectively minimized fluctuations. These findings suggest a preference for near-sinusoidal waveforms in the regulation of circadian rhythms.

systems biology↗

bioRxiv2023

GRable version 1.0: A software tool for site-specific glycoform analysis using the improved Glyco-RIDGE method with parallel clustering and MS2 information

High-throughput intact glycopeptide analysis is crucial for elucidating the physiological and pathological status of the glycans attached to each glycoprotein. Mass spectrometry-based glycoproteomic methods are challenging because of the diversity and heterogeneity of glycan structures. Therefore, we have developed an MS1-based site-specific glycoform analysis method named "Glycan heterogeneity-based Relational IDentification of Glycopeptide signals on Elution profile (Glyco-RIDGE)" for a more comprehensive analysis. This method detects glycopeptide signals as a cluster based on the mass and chromatographic properties of glycopeptides and then searches for each combination of core peptides and glycan compositions by matching their mass and retention time differences. Here we developed a novel browser-based software named GRable for semi-automated Glyco-RIDGE analysis with significant improvements in glycopeptide detection algorithms, including "parallel clustering." This unique function improved the comprehensiveness of glycopeptide detection and allowed the analysis to focus on specific glycan structures, such as pauci-mannose. The other notable improvement is evaluating the "confidence level" of the GRable results, especially using MS2 information. This function facilitated reduced misassignment of the core peptide and glycan composition and improved the interpretation of the results. Additional improved points are: "correction function" for accurate monoisotopic peak picking; one-to-one correspondence of clusters and core peptides even for multiply sialylated glycopeptides; and "inter-cluster analysis" function for understanding the reason for detected but unmatched clusters. The significance of these improvements was demonstrated using purified and crude glycoprotein samples, showing that GRable allowed site-specific glycoform analysis of intact sialylated glycoproteins on a large scale and in depth. Therefore, this software will help to analyze the status and changes in glycans to obtain biological and clinical insights into protein glycosylation by complementing the comprehensiveness of MS2-based glycoproteomics. GRable can run freely online using a web browser via the GlyCosmos Portal (https://glycosmos.org/grable). Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/564073v2_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@12ae798org.highwire.dtl.DTLVardef@1cac352org.highwire.dtl.DTLVardef@dd6b92org.highwire.dtl.DTLVardef@c16ddf_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2021

Combinatorial approach with mass spectrometry and lectin microarray dissected glycoproteomic features of virion-derived spike protein of SARS-CoV-2

The COVID-19 pandemic caused by the novel coronavirus, SARS-CoV-2, has a global impact on public health. Since glycosylation of the viral envelope glycoproteins is known to be deeply associated with their immunogenicity, intensive studies on the glycans of its major glycoprotein, S protein, have been conducted. Nevertheless, the detailed site-specific glycan compositions of virion-associated S protein have not yet been clarified. Here, we conducted intensive glycoproteomic analyses of SARS-CoV-2 S protein using a combinatorial approach with two different technologies: mass spectrometry (MS) and lectin microarray. Using our unique MS1-based glycoproteomic technique, Glyco-RIDGE, in addition to MS2-based Byonic search, we identified 1,759 site-specific glycan compositions. The most frequent was HexNAc:Hex:Fuc:NeuAc:NeuGc = 6:6:1:0:0, suggesting a tri-antennary N-glycan terminating with LacNAc and having bisecting GlcNAc and a core fucose, which was found in 20 of 22 glycosylated sites. The subsequent lectin microarray analysis emphasized intensive outer arm fucosylation of glycans, which efficiently complemented the glycoproteomic features. The present results illustrate the high-resolution glycoproteomic features of SARS-CoV-2 S protein and significantly contribute to vaccine design, as well as the understanding of viral protein synthesis.

molecular biology↗

bioRxiv2021

Altered O-glycosylation Level of SARS-CoV-2 Spike Protein by Host O-glycosyltransferase Strengthens Its Trimeric Structure

The trimeric spike protein (S) mediates host-cell entry and membrane fusion of SARS-CoV-2. S protein is highly glycosylated, whereas its O-glycosylation is still poorly understood. Herein, we site-specifically examine the O-glycosylation of S protein through a mass spectrometric approach with HCD-triggered-ETD model. We identify 15 high-confidence O-glycosites and at least 10 distinct O-glycan structures on S protein. Peptide microarray assays prove that human ppGalNAc-T6 actively participates in O-glycosylation of S protein. Importantly, the upregulation of ppGalNAc-T6 expression can profoundly enhance the O-glycosylation level by generating new O-glycosites and increasing both O-glycan heterogeneity and intensities. Further molecular dynamics simulations reveal that the O-glycosylation on the protomer-interface regions, which are mainly modified by ppGalNAc-T6, can potentially stabilize the trimeric S protein structure. Our work provides deep molecular insights of how viral infection harnesses the host O-glycosyltransferases to dynamically regulate the O-glycosylation level of the viral envelope protein responsible for membrane fusion.

biochemistry↗