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Nagai-Okatani, C.

Publications and source records attributed to Nagai-Okatani, C..

5 recordsLinked to original sources

Lectin-Assisted Imaging Mass Cytometry (Lectin-IMC) Enables Spatial Validation of Disease-Associated Glyco-Niches within a Multimodal Glycoprotein Analysis Framework

Understanding the pathological significance of protein glycosylation and translating disease-associated glycan alterations into diagnostic and therapeutic opportunities require integrated analysis of glycans, their carrier glycoproteins, and spatial context. Here, we present an expanded multimodal glycoprotein analysis framework incorporating lectin-assisted imaging mass cytometry (Lectin-IMC) for stepwise discovery and spatial validation of disease-associated glyco-niches. Disease-associated glycans identified by laser microdissection-assisted lectin microarray (LMD-LMA) tissue glycome mapping are spatially evaluated by Lectin-IMC in relation to cell types and tissue microenvironments, and candidate carrier glycoproteins identified by MS-based glycoproteomics are subsequently incorporated for higher-order evaluation of glycan-protein-cell type relationships. Multiplex panel design is guided by LMA-based assessment of lectin-lectin interactions and biologically informed probe selection. Using a dilated cardiomyopathy model, we constructed a five-lectin panel centered on Wisteria floribunda agglutinin (WFA), which recognizes fibrosis-associated asialo N-glycans identified previously. Glycan-dependent WFA detection was validated by competitive inhibition and PNGase F treatment, and WFA-reactive glycans were spatially associated with fibrotic regions containing ACTA2VIM myofibroblast-like cells. Among six extracellular matrix glycoprotein candidates identified in WFA-binding fractions, periostin showed the strongest spatial correspondence with WFA-positive regions by pixel-based quantitative analysis and was further associated with ACTA2VIMWFA fibrotic microenvironments. The optimized Lectin-IMC panel was also transferable to a human FFPE cardiomyopathy specimen. Collectively, Lectin-IMC provides intuitive spatial visualization and interpretability of glycan-protein-cell type relationships and serves as an on-tissue spatial validation and prioritization layer within an iterative multimodal framework in which spatially defined glyco-niches can guide subsequent proteomic or glycoproteomic discovery.

biochemistry↗

Multi-omics definition of the sex-specific glycoproteome of murine tissues

Sex-specific differences in the glycoproteome remain poorly defined despite growing evidence that protein glycosylation is a key determinant of sex biology. Here we present a tissue-resolved glycoproteome atlas of adult male and female C57BL/6J mice, integrating transcriptomics, proteomics and glycoproteomics with sialic acid speciation and lectin microarray profiling across 19 tissues. Quantitative analysis of >26,800 protein- and site-specific N-glycoforms from 1,512 glycoproteins revealed highly distinct tissue glycoproteomes shaped by coordinated regulation of protein abundance and glyco-enzyme expression. Multi-omics integration identified strong glycophenotype-enzyme relationships, including control of tissue sialylation by Cmas and Cmah, suggesting rate-limiting roles in glycosylation. Pronounced sex-linked glycophenotypes were observed in salivary gland, liver and kidney, driven by differences in fucosylation, sialylation and protein abundance, whereas the brain glycome was largely conserved between sexes. An interactive online database (https://igcore.cloud/mta/atlas-viewer/) provides a resource for exploring sex-biased glycosylation across mouse tissues.

cell biology↗

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↗

LM-GlycoRepo Version 1.0: A novel repository system for mouse tissue glycome mapping data

Lectin microarray (LMA) is a high-sensitive profiling method of protein glycosylation. The increasing use of this method in many studies has led to a growing demand for a repository system that meets the FAIR data principles (Findable, Accessible, Interoperable, and Reusable). Herein, we present a novel repository system, "LM-GlycoRepo," for lectin-based multimodal (LM) data, including LMA data, in accordance with the international guideline MIRAGE (Minimum Information Required for a Glycomics Experiment). As a first step in our efforts to provide a general repository for storing various types of LM data, LM-GlycoRepo Version 1.0 is specialized for mouse tissue glycome mapping data obtained using standardized laser microdissection (LMD)-assisted LMA procedures. This system allows users to deposit datasets containing LMD images, LMA data, and high-resolution lectin staining images as LM data. In addition, this repository adopted an "embargo" system that allows users to specify the release date of datasets, allowing compatibility with an article peer review system. Notably, after the release date, the deposited data were visualized using an existing web tool called LM-GlycomeAtlas. LM-GlycoRepo will evolve into a comprehensive tool for lectin-based multimodal data for various biospecimens, including human samples. LM-GlycoRepo is freely available at the GlyCosmos portal (https://lm-glycorepo.glycosmos.org/lm_glycorepo/).

bioinformatics↗

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↗