pGlyco 2.0 enables precision N-glycoproteomics with comprehensive quality control and one-step mass spectrometry for intact glycopeptide identification

Abstract

The precise and large-scale identification of intact glycopeptides is a critical step in glycoproteomics. Owing to the complexity of glycosylation, the current overall throughput, data quality and accessibility of intact glycopeptide identification lack behind those in routine proteomic analyses. Here, we propose a workflow for the precise high-throughput identification of intact N-glycopeptides at the proteome scale using stepped-energy fragmentation and a dedicated search engine. pGlyco 2.0 conducts comprehensive quality control including false discovery rate evaluation at all three levels of matches to glycans, peptides and glycopeptides, improving the current level of accuracy of intact glycopeptide identification. The N-glycoproteome of samples metabolically labeled with ¹⁵N/¹³C were analyzed quantitatively and utilized to validate the glycopeptide identification, which could be used as a novel benchmark pipeline to compare different search engines. Finally, we report a large-scale glycoproteome dataset consisting of 10,009 distinct site-specific N-glycans on 1988 glycosylation sites from 955 glycoproteins in five mouse tissues.Protein glycosylation is a heterogeneous post-translational modification that generates greater proteomic diversity that is difficult to analyze. Here the authors describe pGlyco 2.0, a workflow for the precise one step identification of intact N-glycopeptides at the proteome scale.

Fig. 1

Demonstration of the optimized MS/MS collision parameters for an intact glycopeptide. a Intact glycopeptide spectrum obtained using the optimized stepped-energy HCD-MS/MS method. b Spectrum obtained using the default single-energy HCD-MS/MS method for the same glycopeptide shown in a. The design of the upper box above each spectrum consists of the glycosylation site (glysite), modification (mod), spectrum name, precursor mass deviation, glycan composition and peptide sequence with ‘J’ indicating the N-glycosylation site. The glycan symbols are as follows: green circle for Hex, blue square for HexNAc and red triangle for fucose. Peak annotation is shown in the middle box: green and blue peaks represent the fragment ions of the glycan moiety or diagnostic glycan ions, and red peaks represent the Y ions from glycan fragmentation. For clarity, the scale of the relative intensity is automatically adjusted based on the highest peak between 700 and 2000 Th. Mass deviations of the annotated peaks are shown in the lower box

Fig. 2

Design of a dedicated software for intact glycopeptide interpretation

Fig. 3

Analysis of a standard glycoprotein mixture. Protein names and glycosylation sites are listed in the first row, and glycans are listed in the first column. Identified site-specific glycans are ticked in the table. Glycans identified at more than one glycosylation site are shown here

Fig. 4

FDR validation workflow. a Validation workflow. b Two search engine-independent FDRs using information from isotope labeling and an entrapment database, respectively

Fig. 5

FDR validation results. a, b Isotopic peak pairing analysis of different glycopeptide identifications by pGlyco 2.0 and Byonic for the same spectrum. Both ¹⁵N- and ¹³C-labeled precursors agreed with the glycopeptides reported by pGlyco 2.0 a. Analysis of the heavily labeled precursor reported by Byonic in MS1. Neither the ¹⁵N- nor ¹³C-labeled precursors agreed with the glycopeptides reported by Byonic b. c FDRs of pGlyco 2.0 and Byonic for three LC-MS/MS runs. d FDR analysis of the glycopeptide identifications reported by Byonic under different score thresholds

Fig. 6

Results of a large-scale intact N-glycopeptide analysis of mouse tissues. a Precursor mass deviation of 79,930 GPSMs. b Retention times of 61 different glycopeptides with the same peptide backbone ‘NLSYEAAPDHK’. The x-axis represents the window of retention time, the y-axis represents the log10 (intensity), and each color represents a different glycopeptide. c Example of a chimera spectrum from multiple glycopeptides. pGlyco 2.0 identified two different glycopeptides in one spectrum, illustrated in the form of a mirrored spectral annotation. The top and bottom spectra in each figure are the same spectrum with different glycopeptide identifications. The design of the annotation in each spectrum is the same as that in Fig. 1. d The MS1 data corresponds to the chimera spectrum

Fig. 7

Analysis of the glycosylation profiles in different mouse tissues. a Correlation analysis of the glycopeptides in different tissues. b Distribution of glycopeptides containing high levels of mannose, fucose, NeuAc and NeuGc in different tissues. c Venn diagram of the unique glycopeptides, glycosylation sites and glycoproteins in different tissues

Fig. 8

Analysis of the glycosylation profile of protein Q3V3R4 (integrin alpha-1) in five mouse tissues. The glycosylation sites are listed in the first row, and the glycans are listed in the first column. The identified site-specific glycans are shown as a petal-shaped mini figure inside the block to demonstrate the tissue specificity

Fig. 9

Example of an O-glycopeptide SCE-HCD-MS/MS spectrum. A high-quality O-glycopeptide spectrum with abundant glycan and peptide fragment ions derived from stepped-energy HCD-MS/MS is shown. The design of the annotation in each spectrum is the same as that in Fig. 1. This O-glycopeptide has two potential glycosylation sites: T1 and S8. The three diagnostic ions with a HexNAc attached show that S8 is the glycosylation site: y9 + HexNAc (m/z = 1082.59, 1 + ), y11 + HexNAc (m/z = 1267.67, 1 + ), and y12 + HexNAc (m/z = 1366.73, 1+). A zoom-in figure of the latter two fragments is shown in the upper right corner of the spectrum annotation