Biology subjects

Tomioka, A.

Publications and source records attributed to Tomioka, A..

7 recordsLinked to original sources

bioRxiv2026

Spatial proteomics identifies altered thick ascending limb cells as drivers of kidney disease through uromodulin retention

Chronic kidney disease (CKD) is increasingly prevalent and is a leading cause of mortality. Recent transcriptomic studies have identified the persistence of injury-induced renal tubular epithelial cell states, yet the cell populations that drive CKD remain unresolved. Uromodulin (UMOD) is the most abundant urinary secreted protein expressed exclusively in thick ascending limb (TAL) epithelial cells in the kidney. UMOD is strongly associated with CKD risk in genome-wide association studies, suggesting a broader, yet unexplored role of UMOD and TAL cells in CKD pathogenesis. Here, using spatial proteomics, we identified an injury-induced TAL cell state marked by intracellular UMOD accumulation. Spatially resolved multimodal integration revealed that UMOD accumulation occurred without transcriptional upregulation. Impaired urinary UMOD secretion further supported pathological intracellular retention. These altered TAL cells with UMOD retention exhibited inflammatory signaling, formed profibrotic niches enriched with M2-like macrophages across renal compartments, and were associated with CKD progression in multiple experimental models. Reducing the burden of UMOD retention diminished altered TAL cells and their profibrotic microenvironments, and attenuated CKD development. A similar altered TAL state was identified in human kidney disease and was associated with worse kidney function. Together, we identify pathological UMOD retention and altered TAL cells as key drivers of CKD development and potential therapeutic targets. This study also highlights that protein-level alterations can redefine disease-associated cell states beyond transcript profiling.

cell biology↗

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

Bottom-up proteomics under acidic conditions using protease type XIII from Aspergillus saitoi

Bottom-up proteomics is a powerful technique for comprehensive analysis of proteins by proteolytic cleavage followed by liquid chromatography/tandem mass spectrometry to identify the resulting peptides. Trypsin is the gold-standard protease for bottom-up proteomics, though its cleavage specificity limits peptide identification, depending on the protein sequence. In addition, its optimal pH is weakly alkaline, which can cause modification artifacts such as deamidation. We hypothesized that these limitations might be overcome by using protease type XIII (P13ase) from Aspergillus saitoi, which is active at low pH. P13ase has been used for protein structural analysis by hydrogen-deuterium exchange mass spectrometry, but its cleavage preferences have not been clarified. Here, we show that P13ase primarily cleaves the C-terminal side of Lys, Arg, and Leu, and the optimal P13ase digestion conditions for bottom-up proteomics are pH 3.5, 37{degrees}C for 60 min. Under these conditions, sequence coverage of more than 90% was achieved for several proteins in HeLa cell extracts, which is unachievable with trypsin. In addition, P13ase digestion reduced artifacts such as deamidation products generated by cyclization reactions and subsequent hydrolysis. These results indicate that P13ase is a promising new tool for precision proteomics.

biochemistry↗

bioRxiv2024

High-Recovery Desalting Tip Columns for a Wide Variety of Peptides in Mass Spectrometry-based Proteomics

In mass spectrometry-based proteomics, loss-minimized peptide purification techniques play a key role in improving sensitivity and coverage. We have developed a desalting tip column packed with thermoplastic polymer-coated chromatographic particles, named ChocoTip, to achieve high recoveries in peptide purification by pipette-tip-based LC with centrifugation (tipLC). ChocoTip identified more than twice as many peptides from 20 ng of tryptic peptides from Hela cell lysate compared to a typical StageTip packed with chromatographic particles entangled in a Teflon mesh in tipLC. The high recovery of ChocoTip in tipLC was maintained for peptides with a wide variety of physical properties over the entire retention time range of the LC/MS/MS analysis, and was especially noteworthy for peptides with long retention times. These excellent properties are attributable to the unique morphology of ChocoTip, in which the thermoplastic polymer covers the pores, thereby inhibiting irreversible adsorption of peptides into mesopores of the chromatographic particles. ChocoTip is expected to find applications, especially in clinical proteomics and single-cell proteomics, where sample amounts are limited.

biochemistry↗

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↗

bioRxiv2023

One thousand samples per day capillary-flow LC/MS/MS for high-speed, high-sensitivity and in-depth proteomics

We developed a capillary-flow LC/MS/MS system with ultrahigh speed, enabling a throughput of 1,000 samples per day while maintaining high sensitivity and depth of analysis. In targeted LC/MS mode, 36 endogenous phosphopeptides in HeLa cells, including EphA2- derived phosphopeptide isomers, were successfully quantified with high selectivity and linearity by combining ion mobility separation. When 500 ng of HeLa cell digest was measured 100 times repeatedly in data-dependent acquisition mode, the coefficient of variation of retention time, peak intensity and number of identified peptides were on average 3.4%, 19.8%, and 6.0%, respectively. In data-independent acquisition mode, this system achieved the identification and quantification of 3,139 protein groups from a 100 ng HeLa cell digest and 2,145 protein groups from a sample of only 10 ng. The coefficient of variation of protein commonly quantified in the triplicate analysis ranged from 12 to 24% for HeLa digest samples ranging from 10 to 1000 ng. Finally, we applied this high-speed system to the spatial proteomics of the mouse brain, and succeeded in capturing the proteome distribution along a 96-sectioned brain structure in 135 minutes. This is the first LC/MS/MS system to achieve both more than 500 samples per day and more than 3000 identified protein groups ID with less than 100 ng human cultured cells simultaneously.

systems 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↗