Search

Great advances have been made in mass spectrometric data interpretation for intact glycopeptide analysis. However, accurate identification of intact glycopeptides and modified saccharide units at the site-specific level and with fast speed remains challenging. Here, we present a glycan-first glycopeptide search engine, pGlyco3, to comprehensively analyze intact N- and O-glycopeptides, including glycopeptides with modified saccharide units. A glycan ion-indexing algorithm developed for glycan-first search makes pGlyco3 5–40 times faster than other glycoproteomic search engines without decreasing accuracy or sensitivity. By combining electron-based dissociation spectra, pGlyco3 integrates a dynamic programming-based algorithm termed pGlycoSite for site-specific glycan localization. Our evaluation shows that the site-specific glycan localization probabilities estimated by pGlycoSite are suitable to localize site-specific glycans. With pGlyco3, we confidently identified N-glycopeptides and O-mannose glycopeptides that were extensively modified by ammonia adducts in yeast samples. The freely available pGlyco3 is an accurate and flexible tool that can be used to identify glycopeptides and modified saccharide units.

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N - and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved ‘high-coverage’ and ‘high-accuracy’ glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics., This analysis presents the results of a community-based evaluation of existing software for large-scale glycopeptide data analysis.

Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further utilize a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data-dependent acquisition-based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies., Data independent acquisition (DIA) proteomics provides deep coverage and high quantitative accuracy, but is not yet well established in glycoproteomics. Here, the authors develop a DIA-based glycoproteomics workflow with stringent statistical controls to enable accurate glycopeptide identification.

The heterogeneity and low abundance of protein glycosylation present challenging barriers to the analysis of intact glycopeptides, which is key to comprehensively understanding the role of glycosylation in an organism. Efficient and specific enrichment of intact glycopeptides could help greatly with this problem. Here, we propose a new enrichment strategy using a boronic acid (BA)-functionalized mesoporous graphene-silica composite (denoted as GO@mSiO2-GLYMO-APB) for isolating intact glycopeptides from complex biological samples. The merits of this composite, including high surface area and synergistic effect from size exclusion functionality of mesoporous material, hydrophilic interaction of silica, and the reversible covalent binding with BA, enable the effective and specific enrichment of both intact N- and O-glycopeptides. The results from the enrichment performance of the strategy evaluated by standard glycoproteins and the application to global N- and O-glycosylation analyses in human serum indicate the robustness and potential of the strategy for intact glycopeptide analysis.

Intact glycopeptide identification has long been known as a key and challenging barrier to the comprehensive and accurate understanding the role of glycosylation in an organism. Intact glycopeptide analysis is a blossoming field that has received increasing attention in recent years. MS-based strategies and relative software tools are major drivers that have greatly facilitated the analysis of intact glycopeptides, particularly intact N-glycopeptides. This article provides a systematic review of the intact glycopeptide-identification process using MS data generated in shotgun proteomic experiments, which typically focus on N-glycopeptide analysis. Particular attention is paid to the software tools that have been recently developed in the last decade for the interpretation and quality control of glycopeptide spectra acquired using different MS strategies. The review also provides information about the characteristics and applications of these software tools, discusses their advantages and disadvantages, and concludes with a discussion of outstanding tools., Graphical abstract, Highlights • Summarize the development of software tools for intact glycopeptide analysis. • Survey the MS acquisition strategies for glycopeptide spectrum acquisition. • Conclude the quality control methods for glycopeptide-spectrum matching. • Show the application of intact glycopeptide analysis in glycoproteomic research., In Brief This article provides a systematic review of the most recent MS-based strategies and corresponding software tools for the analysis of intact glycopeptides, particularly intact N-glycopeptides, reported in the last decade, including the process of identifying N-glycopeptides from MS data, the existing methods of MS data acquisition and interpretation, the quality control methods, the display of results, and the software applications.

A powerful and fast glycopeptide/glycan enrichment method is critical for the efficiency and throughput of mass spectrometry (MS)-based glycoproteomic and glycomic analyses, especially for large-scale sample analysis. Here, we report an ultrafast and effective method for both intact N-glycopeptide and N-glycan enrichment and apply it to human serum samples. In this method, a natural hydrophilic material, bacterial cellulose (BC), was adopted and fully optimized for enrichment. This method offers the following advantages: (i) The enrichment material has natural hydrophilicity and is low-cost, biocompatible, biodegradable and easily accessible; (ii) the whole enrichment procedure is remarkably simple and fast. It takes only 10 min for intact glycopeptides/glycans to be easily purified from mixtures; (iii) the specificity of this method is over 94% for both glycan and glycopeptide enrichment; and (iv) the outstanding specificity of this technique enables high isolation efficiency for the enrichment of both intact glycopeptides and glycans. A total of 36 N-glycans and 31 N-glycopeptides were identified from human immunoglobulin G (IgG). The glycan and glycopeptide absorption capacity of BC was as high as 333 μg/mg and 250 μg/mg (IgG/BC) respectively. The selectivity for glycan and glycopeptide enrichment reached 1:100 (IgG/bovine serum albumin (BSA), molar ratio) and 1:200 (maltoheptaose (DP7)/BSA, molar ratio), respectively. Furthermore, a total of 159 N-glycans and 523 N-glycopeptides were identified in human serum by using this method. Overall, the BC-based enrichment method we present here provides an ultrafast and highly efficient method for the enrichment of both N-glycopeptides and N-glycans in complex samples and shows great potential in large-scale glycoproteomic and glycomic analyses.

Precise and automated analysis of site-specific

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.

N-glycosylation is deeply involved in many biological processes, and approximately 50% of mammalian proteins are predicted to be glycosylated. Many large-scale studies have been carried out to reveal the glycosylation status involved in different physiological pathologies across species. However, the lack of a highly specific and high-throughput N-glycosylated enrichment method not only results in extended time requirements but also limits the depth of mapping when handling a large number of samples. In this study, we firstly optimized traditional zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) enrichment and found that using of 70% acetonitrile (ACN), 0.1% trifluoroacetic acid (TFA) as the enrichment buffer, 2800 g as the washing speed and 600 μL as the washing volume achieved the best specificity, which is higher than 75%. On this basis, we developed a multi-parallel enrichment strategy assisted by a filter-coated 96-well plate, which achieved high specificity and high throughput simultaneously. This strategy allowed us to enrich large numbers of fractionated samples from hepatocellular carcinoma (HCC) cell lines in less than 2 h. Its good specificity helped us achieve in-depth mapping of the N-glycoproteome in metastatic HCC cell lines. A total of 5466 N-glycosites from 2383 glycoproteins were identified, among which 1900 N-glycosites were unannotated in UniProt. The in-depth glycoproteome mapping provides insight into the N-glycosylation status in HCC cell lines with differences in metastatic potential and contributes to biomarker discovery.

PNGase F-catalyzed glycosylation site (18)O-labeling is a widely used method for glycoprotein quantitation owing to its efficiency and simplicity. However, PNGase F-catalyzed glycan (18)O-labeling, which offers advantages for glycomics, has not yet been developed. In this study, PNGase F-mediated incorporation of (18)O into glycans during the N-glycan release from glycoproteins by PNGase F was finally realized, named as PCGOL (PNGase F-catalyzed glycan (18)O-labeling), which offers a potential strategy for relative glycan quantitation. This new method showed good linearity and high reproducibility within at least 2 orders of magnitude in the dynamic range. Furthermore, PCGOL combined with our previously developed TOSIL method (tandem (18)O stable isotope labeling for N-glycoproteome quantitation) can be used for comprehensive N-glycosylation quantification, achieving simultaneous quantification of glycans, glycopeptides and glycoproteins in a single workflow, which was also used to analyze glycosylation changes in immunoglobulin G (IgG) associated with hepatocellular carcinoma in the present work.

Efficient glycopeptides enrichment prior to mass spectrometry analysis is essential for glycoproteome study. ZIC-HILIC (zwitterionic hydrophilic interaction liquid chromatography) based glycopeptides enrichment approaches have been attracting more attention for several benefits like easy operating, high enrichment specificity and intact glycopeptide retained. In this study, Poly (amidoamine) dendrimer (PAMAM) was adopted for the synthesis of zwitterionically functionalized (ZICF) materials for glycopeptide enrichment. The multiple branched structure and good solubility of ZICF-PAMAM enables a sufficient interaction with glycopeptides. The ZICF-PAMAM combined with the FASP-mode enrichment strategy exhibits more superior performance compared with the existing methods. It has the minimum detectable concentration of femtomolar level and high recovery rate of over 90.01%, and can efficiently enrich glycopeptides from complex biological samples even for merely 0.1 μL human serum. The remarkable glycopeptides enrichment capacity of ZICF-PAMAM highlights the potential application in in-depth glycoproteome research, which may open up new opportunities for the development of glycoproteomics.

Confident characterization of the microheterogeneity of protein glycosylation through identification of intact glycopeptides remains one of the toughest analytical challenges for glycoproteomics. Recently proposed mass spectrometry (MS)-based methods still have some defects such as lack of the false discovery rate (FDR) analysis for the glycan identification and lack of sufficient fragmentation information for the peptide identification. Here we proposed pGlyco, a novel pipeline for the identification of intact glycopeptides by using complementary MS techniques: 1) HCD-MS/MS followed by product-dependent CID-MS/MS was used to provide complementary fragments to identify the glycans and a novel target-decoy method was developed to estimate the false discovery rate of the glycan identification; 2) data-dependent acquisition of MS3 for some most intense peaks of HCD-MS/MS was used to provide fragments to identify the peptide backbones. By integrating HCD-MS/MS, CID-MS/MS and MS3, intact glycopeptides could be confidently identified. With pGlyco, a standard glycoprotein mixture was analyzed in the Orbitrap Fusion and 309 non-redundant intact glycopeptides were identified with detailed spectral information of both glycans and peptides.