Dataset Information

Site-specific glycoform analysis of mouse tissue N-glycoproteomes by the Glyco-RIDGE method

ABSTRACT: To understand biological and pathological functions of protein glycosylations, it is crucial to uncover glycan heterogeneities, which depend on the type and status of cells, for each glycosite of single glycoprotein. For evaluating the glycan heterogeneities at macro-, micro-, and meta-levels, a reliable strategy is needed to compare site-specific glycoforms of glycoproteins in two and more samples, such as different tissues, in a comprehensive manner. To analyze this "inter-heterogeneity" of samples, we have developed a MS1-based glycopeptide detection method named "Glycan heterogeneity-based Relational Identification of Glycopeptide signals on Elution profile (Glyco-RIDGE)." In the present study, to elucidate inter-tissue glycan heterogeneities, the Glyco-RIDGE method was applied to site-specific N-glycoform analysis of six mouse tissues. To improve the sensitivity of analysis, glycopeptides prepared from the tissues were desialylated and fractioned, and then analyzed using the Glyco-RIDGE method. The validity of the MS1-based method was confirmed for the liver using MS2 spectra. This method estimated 11,325 site-specific N-glycoforms with 239 glycan compositions on 1,260 sites of 800 glycoproteins, revealing inter-tissue differences in macro-, micro-, and meta-glycan heterogeneities.

ORGANISM(S): Mus Musculus (mouse)

SUBMITTER: Chiaki Nagai-Okatani

PROVIDER: PXD054368 | JPOST Repository | Mon Dec 16 00:00:00 GMT 2024

REPOSITORIES: jPOST

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Dataset's files

Source:

			Action	DRS
	mKidney-TL+Am+AT+ODS%231-sp+monoC-dd2HCD-5-15-35-105g-02.mgf	Mgf
	mKidney-TL+Am+AT+ODS%231-sp+monoC-dd2HCD-5-15-35-105g-02_xtract.raw	Raw
	mKidney-TL+Am+AT+ODS%232-sp+monoC-dd2HCD-5-15-35-105g-02_xtract.raw	Raw
	mKidney-TL+Am+AT+ODS%233-sp+monoC-dd2HCD-5-15-35-105g-02_xtract.raw	Raw
	mKidney-TL+Am+AT+ODS%234-sp+monoC-dd2HCD-5-15-35-105g-05_xtract.raw	Raw

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Publications

Expanding the recognition of monosaccharides and glycans: A comprehensive analytical approach using chemical-nose/tongue technology and a comparison to lectin microarrays.

Tomita Shunsuke S Nagai-Okatani Chiaki C

BBA advances 20241208

Chemical-nose/tongue technologies are emerging as promising analytical tools for glycan analysis. After briefly introducing the importance of glycans and their analytical methods, including the lectin microarray (LMA) as one of the gold standards, the fundamental principles underlying chemical noses/tongues are explained and various applications for monosaccharides and glycans are introduced. Then, the similarities and differences of these two approaches are discussed. While both technologies ai ...[more]

PMID: 39790466

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Project description: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 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 of the algorithms 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 us 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 be freely run online using a web browser via the GlyCosmos Portal (https://glycosmos.org/grable).

Project description:Glycobiology plays a central role in prostate cancer (PCa), as evidenced by the aberrant glycosylation in PCa-derived glycoproteins. Understanding the protein glycosylation changes underling PCa onset and progression may open opportunities for the discovery of novel biomarkers for PCa detection and stratification as well as targets for PCa metastasis. Advances in mass spectrometry-based glycomics and glycoproteomics have opened up exciting avenues for deep characterisation of the immensely, yet poorly understood complex glycoproteome. In this study, we have used integrated glycomics and glycoproteomics to explore the protein, cell and tumour-grade specific N- and O- glycosylation signatures in surgically-removed fresh PCa tissues grouped into five PCa disease grades and tissues from benign prostatic hyperplasia patients (BPH). Porous graphitised carbon–liquid chromatography (PGC–LC)-MS/MS analysis was used to profile the N-and O-glycome, revealing PCa grade specific N and O glycosylation changes, including oligomannosidic and paucimannosidic, bisecting-GlcNAc and highly branched tri- and tetra-antennary fucosylated and sialylated N-glycans as well as sialylated core 1 and 2 type O-glycans. High resolution LC-MS/MS was then employed to capture the micro and macroheterogeneity of 1,085 N-glycosites (>7,400 unique N-glycopeptides) from 540 N-glycoproteins and 360 O-glycosites (>500 unique O-glycopeptides) from 178 O-glycoproteins and reveal protein and cell specific N- and O- glycosylation changes associated with PCa progression. We also showed PCa grade-specific increase in the expression of oligosaccharyltransferase (OST) subunits that correlate with changes in the site occupancy of N-glycoproteins. In conclusion, this study shows that integrated glycomics and glycoproteomics can provide unprecedented insight into key molecular features and site-specific glycan heterogeneity contributing to the highly diverse tumour-microenvironment and allow us to deconstruct the regulation of the protein, cell and tumour-grade-specific glycosylation associated with PCa onset and development.