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An automated intact glycopeptide enrichment method for serum site-specific N-glycoproteomic analysis

ABSTRACT: We developed an automated glycopeptide enrichment method for the analysis of serum site-specific N-glycoproteome. This automated method allowed for processing one sample within 20 min. It showed higher enrichment specificity, more intact glycopeptide identifications, and better quantitative reproducibility than the traditional manual method using micro-tip enrichment devices. We further applied this method to investigate the serum site-specific N-glycosylation changes between four patients with pancreatic cancer and seven healthy controls. The principal component analysis of intact N-glycopeptides showed a good clustering across cancer and normal groups. And we found that the site-specific glycoforms, mono-fucosylated and non-sialylated oligosaccharides, on IgG1 site 180 expressed a significant decrease in pancreatic cancer patients compared to healthy controls. Together, the automated method is a powerful tool for site-specific N-glycoproteomics analysis of complex biological samples, and it has great potential for clinical utilities.

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Mingliang Ye

PROVIDER: PXD025151 | JPOST Repository | Tue Apr 06 00:00:00 BST 2021

REPOSITORIES: jPOST

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Publications

Automated Intact Glycopeptide Enrichment Method Facilitating Highly Reproducible Analysis of Serum Site-Specific N-Glycoproteome.

Liu Luyao L Zhu Bin B Fang Zheng Z Zhang Na N Qin Hongqiang H Guo Zhimou Z Liang Xinmiao X Yao Zhenzhen Z Ye Mingliang M

Analytical chemistry 20210511 20

Bottom-up proteomics has been increasingly applied in clinical research to study the disease pathophysiology and to discover disease biomarkers. However, glycoproteomic analysis always requires tedious experimental steps for intact glycopeptide enrichment, which has been the technique bottleneck for large-scale analysis of clinical samples. Herein, we developed an automated glycopeptide enrichment method for the analysis of serum site-specific N-glycoproteome. This automated method allowed for p ...[more]

PMID: 33973768

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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).

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