A review of intact glycopeptide enrichment and glycan separation through hydrophilic interaction liquid chromatography stationary phase materials.

Protein glycosylation, one of the most important biologically relevant post-translational modifications for biomarker discovery, faces analytical challenges due to heterogeneous glycosite, diverse glycans, and mass spectrometry limitations. Glycopeptide enrichment by removing abundant hydrophobic peptides helps overcome some of these obstacles. Hydrophilic interaction liquid chromatography (HILIC), known for its selectivity, glycan separations, intact glycopeptide enrichment, and compatibility with mass spectrometry, has seen recent advancements in stationary phases like Amide-80, glycoHILIC, amino acids or peptides for improved HILIC-based glycopeptide analysis. Utilization of these materials can improve glycopeptide enrichment through solid-phase extraction and separation via high-performance liquid chromatography. Additionally, using glycopeptides themselves to modify HILIC stationary phases holds promise for improving selectivity and sensitivity in glycosylation analysis. Additionally, HILIC has capability to assess the information about glycosites and structural information of glycans. This review summarizes recent breakthroughs in HILIC stationary materials, highlighting their impact on glycopeptide analysis. Ongoing research on advanced materials continues to refine HILIC's performance, solidifying its value as a tool for exploring protein glycosylation.

Integrated Proteomic and Glycoproteomic Analysis Reveals Heterogeneity and Molecular Signatures of Brain Metastases from Lung Adenocarcinomas.

Brain metastasis is a major cause of poor prognosis and death in lung adenocarcinoma (LUAD); however, the understanding of therapeutic strategies and mechanisms for brain metastases from LUAD (BM-LUAD) remains notably limited, especially at the proteomics levels. To address this issue, we conducted integrated proteomic and glycoproteomic analyses on 49 BM-LUAD tumors, revealing two distinct subtypes of the disease: BM-S1 and BM-S2. Whole exome sequencing analysis revealed that somatic mutations in STK11 and KEAP1, as well as copy number deletions on chr19p13.3, such as STK11, UQCR11, and SLC25A23, were more frequently detected in BM-S2. In BM-S1 tumors, we observed significant infiltration of GFAP+ astrocytes, as evidenced by elevated levels of GFAP, GABRA2, GABRG1 and GAP43 proteins and an enrichment of astrocytic signatures in both our proteomic data and external spatial transcriptomic data. Conversely, BM-S2 tumors demonstrated higher levels of PD-1 immune cell infiltration, supported by the upregulation of PD-1 and LAG-3 genes. These findings suggest distinct microenvironmental adaptations required by the different BM-LUAD subtypes. Additionally, we observed unique glycosylation patterns between the subtypes, with increased fucosylation in BM-S1 and enhanced sialylation in BM-S2, primarily affected by glycosylation enzymes such as FUT9, B4GALT1, and ST6GAL1. Specifically, in BM-S2, these sialylation modifications are predominantly localized to the lysosomes, underscoring the critical role of N-glycosylation in the tumor progression of BM-LUAD. Overall, our study not only provides a comprehensive multi-omic data resource but also offers valuable biological insights into BM-LUAD, highlighting potential mechanisms and therapeutic targets for further investigation.

GRable Version 1.0: A Software Tool for Site-Specific Glycoform Analysis With Improved MS1-Based Glycopeptide Detection With Parallel Clustering and Confidence Evaluation With 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 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).

Quantitative N-glycoproteomics characterization of differential N-glycosylation in Sorghum bicolor under salinity stress.

Salt stress is one of the significant environmental stresses that severely affect plant growth and development. Here, we report quantitative N-glycoproteomics characterization of differential N-glycosylation in Sorghum bicolor under low, median and high salinity stress. 21,621 intact N-glycopeptides coming from the combination of 127 N-glycan structures on 6574 N-glycosites from 5321 proteins were identified; differential N-glycosylation was observed for 682 N-glycoproteins which are mainly involved in the pathways of biosynthesis of secondary metabolites, biosynthesis of amino acids and several metabolic pathways. 41 N-glycan structures modifying on 338 N-glycopeptides from 122 glycoproteins were co-quantified and deregulated under at least one salt stress, including enzymes of energy production and carbohydrate metabolisms, cell wall organization related proteins, glycosyltransferases and so on. Intriguingly, with increasing salt concentration, there was an increase in the percentage of complex N-glycans on the altered N-glycopeptides. Furthermore, the observation of glycoproteins with distinct salt sensitivity is noteworthy, particularly the upregulated hyposensitive glycoproteins that predominantly undergo complex N-glycan modification. This is the first N-glycoproteome description of salt stress response at the intact N-glycopeptide level in sorghum and a further validation of data reported here would likely provide deeper insights into the stress physiology of this important crop plant.

Clinical glycoprotein mass spectrometry: The future of disease detection and monitoring.

Protein glycosylation is the co- and/or post-translational modification of proteins with oligosaccharides (glycans). This process is not template based and can introduce a heterogeneous set of glycan modifications onto substrate proteins. Glycan structures preserve biomolecular information from the cell, with glycoproteins from different cell types and tissues displaying distinct patterns of glycosylation. Several decades of research have revealed that glycan structures also differ between normal physiology and disease. This suggests that the information stored in glycoproteins and glycans can be utilized for disease diagnosis and monitoring. Methods that enable sensitive and site-specific measurement of protein glycosylation in clinical settings, such as nano-flow liquid chromatography tandem mass spectrometry, are therefore essential. The purpose of this perspective is to discuss recent advances in mass spectrometry and the potential of these advances to facilitate the detection and monitoring of disease-specific glycoprotein glycoforms. Glycoproteomics, the system-wide characterization of glycoprotein identity inclusive of site-specific characterization of carbohydrate modifications on proteins, and glycomics, the characterization of glycan structures, will be discussed in this context. Quantitative measurement of glycopeptide markers via parallel reaction monitoring is highlighted. The development of promising glycopeptide markers for autoimmune disease, liver disease, and liver cancer is discussed. Synthetic glycopeptide standards, ambient ionization mass spectrometry, and consideration of glyco-biomarkers in two- and three-dimensional space within tissue will be critical to the advancement of this field. The authors envision a future in which glycoprotein mass spectrometry workflows will be integrated into clinical settings, to aid in the rapid diagnosis and monitoring of disease.

Deep structure-level N-glycan identification using feature-induced structure diagnosis integrated with a deep learning model.

Being a widely occurring protein post-translational modification, N-glycosylation features unique multi-dimensional structures including sequence and linkage isomers. There have been successful bioinformatics efforts in N-glycan structure identification using N-glycoproteomics data; however, symmetric "mirror" branch isomers and linkage isomers are largely unresolved. Here, we report deep structure-level N-glycan identification using feature-induced structure diagnosis (FISD) integrated with a deep learning model. A neural network model is integrated to conduct the identification of featured N-glycan motifs and boosts the process of structure diagnosis and distinction for linkage isomers. By adopting publicly available N-glycoproteomics datasets of five mouse tissues (17,136 intact N-glycopeptide spectrum matches) and a consideration of 23 motif features, a deep learning model integrated with a convolutional autoencoder and a multilayer perceptron was trained to be capable of predicting N-glycan featured motifs in the MS/MS spectra with previously identified compositions. In the test of the trained model, a prediction accuracy of 0.8 and AUC value of 0.95 were achieved; 5701 previously unresolved N-glycan structures were assigned by matched structure-diagnostic ions; and by using an explainable learning algorithm, two new fragmentation features of m/z = 674.25 and m/z = 835.28 were found to be significant to three N-glycan structure motifs with fucose, NeuAc, and NeuGc, proving the capability of FISD to discover new features in the MS/MS spectra.

Mass spectrometry-based structure-specific N-glycoproteomics and biomedical applications.

N-linked glycosylation is a common posttranslational modification of proteins that results in macroheterogeneity of the modification site. However, unlike simpler modifications, N-glycosylation introduces an additional layer of complexity with tens of thousands of possible structures arising from various dimensions, including different monosaccharide compositions, sequence structures, linking structures, isomerism, and three-dimensional conformations. This results in additional microheterogeneity of the modification site of N-glycosylation, i.e., the same N-glycosylation site can be modified with different glycans with a certain stoichiometric ratio. N-glycosylation regulates the structure and function of N-glycoproteins in a site- and structure-specific manner, and differential expression of N-glycosylation under disease conditions needs to be characterized through site- and structure-specific quantitative analysis. Numerous advanced methods ranging from sample preparation to mass spectrum analysis have been developed to distinguish N-glycan structures. Chemical derivatization of monosaccharides, online liquid chromatography separation and ion mobility spectrometry enable the physical differentiation of samples. Tandem mass spectrometry further analyzes the macro/microheterogeneity of intact N-glycopeptides through the analysis of fragment ions. Moreover, the development of search engines and AI-based software has enhanced our understanding of the dissociation patterns of intact N-glycopeptides and the clinical significance of differentially expressed intact N-glycopeptides. With the help of these modern methods, structure-specific N-glycoproteomics has become an important tool with extensive applications in the biomedical field.

LacdiNAc to LacNAc: remodelling of bovine α-lactalbumin N-glycosylation during the transition from colostrum to mature milk.

α -Lactalbumin, an abundant protein present in the milk of most mammals, is associated with biological, nutritional and technological functionality. Its sequence presents N-glycosylation motifs, the occupancy of which is species-specific, ranging from no to full occupancy. Here, we investigated the N-glycosylation of bovine α-lactalbumin in colostrum and milk sampled from four individual cows, each at 9 time points starting from the day of calving up to 28.0 d post-partum. Using a glycopeptide-centric mass spectrometry-based glycoproteomics approach, we identified N-glycosylation at both Asn residues found in the canonical Asn-Xxx-Ser/Thr motif, i.e. Asn45 and Asn74 of the secreted protein. We found similar glycan profiles in all four cows, with partial site occupancies, averaging at 35% and 4% for Asn45 and Asn74, respectively. No substantial changes in occupancy occurred over lactation at either site. Fucosylation, sialylation, primarily with N-acetylneuraminic acid (Neu5Ac), and a high ratio of N,N'-diacetyllactosamine (LacdiNAc)/N-acetyllactosamine (LacNAc) motifs were characteristic features of the identified N-glycans. While no substantial changes occurred in site occupancy at either site during lactation, the glycoproteoform (i.e. glycosylated form of the protein) profile revealed dynamic changes; the maturation of the α-lactalbumin glycoproteoform repertoire from colostrum to mature milk was marked by substantial increases in neutral glycans and the number of LacNAc motifs per glycan, at the expense of LacdiNAc motifs. While the implications of α-lactalbumin N-glycosylation on functionality are still unclear, we speculate that N-glycosylation at Asn74 results in a structurally and functionally different protein, due to competition with the formation of its two intra-molecular disulphide bridges.

Quantification and site-specific analysis of co-occupied N- and O-glycopeptides.

Protein glycosylation is a complex post-translational modification that is generally classified as N- or O-linked. Site-specific analysis of glycopeptides is accomplished with a variety of fragmentation methods, depending on the type of glycosylation being investigated and the instrumentation available. For instance, collisional dissociation methods are frequently used for N-glycoproteomic analysis with the assumption that one N-sequon exists per tryptic peptide. Alternatively, electron-based methods are indispensable for O-glycosite localization. However, the presence of simultaneously N- and O-glycosylated peptides could suggest the necessity of electron-based fragmentation methods for N-glycoproteomics, which is not commonly performed. Thus, we quantified the prevalence of N- and O-glycopeptides in mucins and other glycoproteins. A much higher frequency of co-occupancy within mucins was detected whereas only a negligible occurrence occurred within non-mucin glycoproteins. This was demonstrated from analyses of recombinant and/or purified proteins, as well as more complex samples. Where co-occupancy occurred, O-glycosites were frequently localized to the Ser/Thr within the N-sequon. Additionally, we found that O-glycans in close proximity to the occupied Asn were predominantly unelaborated core 1 structures, while those further away were more extended. Overall, we demonstrate electron-based methods are required for robust site-specific analysis of mucins, wherein co-occupancy is more prevalent. Conversely, collisional methods are generally sufficient for analyses of other types of glycoproteins.

Evidence of Gas Phase Glucosyl Transfer and Glycation in the CID/HCD-Spectra of S-Glucosylated Peptides.

Protein cysteine S-glycosylation is a relatively rare and less well characterized post-translational modification (PTM). Creating reliable model proteins that carry this modification is challenging. The lack of available models or natural S-glycosylated proteins significantly hampers the development of mass-spectrometry-based (MS-based) methodologies for detecting protein cysteine S-glycosylation in real-world proteomic studies. There is also limited MS-sequencing data describing it as easier to create synthetic S-glycopeptides. Here, we present the results of an in-depth manual analysis of automatically annotated CID/HCD spectra for model S-glucopeptides. The CID spectra show a long series of y/b-fragment ions with retained S-glucosylation, regardless of the dominant m/z signals corresponding to neutral loss of 1,2-anhydroglucose from the precursor ions. In addition, the spectra show signals manifesting glucosyl transfer from the cysteine position onto lysine, arginine (Lys, Arg) side chains, and a peptide N-terminus. Other spectral evidence indicates that the N-glucosylated initial products of transfer are converted into N-fructosylated (i.e., glycated) structures due to Amadori rearrangement. We discuss the peculiar transfer of the glucose oxocarbenium ion (Glc+) to positively charged guanidinium residue (ArgH+) and propose a mechanism for the gas-phase Amadori rearrangement involving a 1,2-hydride ion shift.

Analysis of Mucin-Domain Glycoproteins Using Mass Spectrometry.

Mucin-domain glycoproteins are characterized by their high density of glycosylated serine and threonine residues, which complicates their analysis by mass spectrometry. The dense glycosylation renders the protein backbone inaccessible to workhorse proteases like trypsin, the vast heterogeneity of glycosylation often results in ion suppression from unmodified peptides, and search algorithms struggle to confidently analyze and site-localize O-glycosites. We have made a number of advances to address these challenges, rendering mucinomics possible for the first time. Here, we summarize these contributions and provide a detailed protocol for mass spectrometric analysis of mucin-domain glycoproteins. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Enrichment of mucin-domain glycoproteins Basic Protocol 2: Enzymatic digestion of mucin-domain glycoprotein(s) Basic Protocol 3: Mass spectrometry data collection for O-glycopeptides Basic Protocol 4: Mass spectrometry data analysis of O-glycopeptides.

Multi-scale signaling and tumor evolution in high-grade gliomas.

Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas.

Integrating HexNAcQuest with Glycoproteomics Data Analysis Software to Distinguish HexNAc Isomers on Peptides.

Recently, HexNAcQuest was developed to help distinguish peptides modified by HexNAc isomers, more specifically O-linked ß-N-acetylglucosamine (O-GlcNAc) and O-linked α-N-acetylgalactosamine (O-GalNAc, Tn antigen). To facilitate its usage (particularly for datasets from glycoproteomics studies), herein we present a detailed protocol. It describes example cases and procedures for which users might need to use HexNAcQuest to distinguish these two modifications.

The glycosylation landscape of prostate cancer tissues and biofluids.

An overview of the role of glycosylation in prostate cancer (PCa) development and progression is presented, focusing on recent advancements in defining the N-glycome through glycomic profiling and glycoproteomic methodologies. Glycosylation is a common post-translational modification typified by oligosaccharides attached N-linked to asparagine or O-linked to serine or threonine on carrier proteins. These attached sugars have crucial roles in protein folding and cellular recognition processes, such that altered glycosylation is a hallmark of cancer pathogenesis and progression. In the past decade, advancements in N-glycan profiling workflows using Matrix Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) technology have been applied to define the spatial distribution of glycans in PCa tissues. Multiple studies applying N-glycan MALDI-MSI to pathology-defined PCa tissues have identified significant alterations in N-glycan profiles associated with PCa progression. N-glycan compositions progressively increase in number, and structural complexity due to increased fucosylation and sialylation. Additionally, significant progress has been made in defining the glycan and glycopeptide compositions of prostatic-derived glycoproteins like prostate-specific antigen in tissues and biofluids. The glycosyltransferases involved in these changes are potential drug targets for PCa, and new approaches in this area are summarized. These advancements will be discussed in the context of the further development of clinical diagnostics and therapeutics targeting glycans and glycoproteins associated with PCa progression. Integration of large scale spatial glycomic data for PCa with other spatial-omic methodologies is now feasible at the tissue and single-cell levels.

The Human Glycome Atlas Project for cataloging all glycan-related omics data in human.

The Human Glycome Atlas (HGA) Project was launched in April 2023, spearheaded by three Japanese institutes: the Tokai National Higher Education and Research System, the National Institutes of Natural Sciences, and Soka University. This was the first time that a field in the life sciences was adopted by the Ministry of Education, Culture, Sports, Science and Technology (MEXT) for a Large-scale Academic Frontiers Promotion Project. This project aims to construct a knowledgebase of human glycans and glycoproteins as a standard for the human glycome. A high-throughput pipeline for comprehensively analyzing 20,000 blood samples in its first five years is planned, at which time an access-controlled version of a human glycomics knowledgebase, called TOHSA, will be released. By the end of the final tenth year, TOHSA will provide a central resource linking human glycan data with other omics data including disease-related information.

O-GlcNAcase regulates pluripotency states of human embryonic stem cells.

Understanding the regulation of human embryonic stem cells (hESCs) pluripotency is critical to advance the field of developmental biology and regenerative medicine. Despite the recent progress, molecular events regulating hESC pluripotency, especially the transition between naive and primed states, still remain unclear. Here we show that naive hESCs display lower levels of O-linked N-acetylglucosamine (O-GlcNAcylation) than primed hESCs. O-GlcNAcase (OGA), the key enzyme catalyzing the removal of O-GlcNAc from proteins, is highly expressed in naive hESCs and is important for naive pluripotency. Depletion of OGA accelerates naive-to-primed pluripotency transition. OGA is transcriptionally regulated by EP300 and acts as a transcription regulator of genes important for maintaining naive pluripotency. Moreover, we profile protein O-GlcNAcylation of the two pluripotency states by quantitative proteomics. Together, this study identifies OGA as an important factor of naive pluripotency in hESCs and suggests that O-GlcNAcylation has a broad effect on hESCs homeostasis.

Quantitative proteome-wide O-glycoproteomics analysis with FragPipe.

Identification of O-glycopeptides from tandem mass spectrometry data is complicated by the near complete dissociation of O-glycans from the peptide during collisional activation and by the combinatorial explosion of possible glycoforms when glycans are retained intact in electron-based activation. The recent O-Pair search method provides an elegant solution to these problems, using a collisional activation scan to identify the peptide sequence and total glycan mass, and a follow-up electron-based activation scan to localize the glycosite(s) using a graph-based algorithm in a reduced search space. Our previous O-glycoproteomics methods with MSFragger-Glyco allowed for extremely fast and sensitive identification of O-glycopeptides from collisional activation data but had limited support for site localization of glycans and quantification of glycopeptides. Here, we report an improved pipeline for O-glycoproteomics analysis that provides proteome-wide, site-specific, quantitative results by incorporating the O-Pair method as a module within FragPipe. In addition to improved search speed and sensitivity, we add flexible options for oxonium ion-based filtering of glycans and support for a variety of MS acquisition methods and provide a comparison between all software tools currently capable of O-glycosite localization in proteome-wide searches.

Multi Omics Applications in Biological Systems.

Traditional methodologies often fall short in addressing the complexity of biological systems. In this regard, system biology omics have brought invaluable tools for conducting comprehensive analysis. Current sequencing capabilities have revolutionized genetics and genomics studies, as well as the characterization of transcriptional profiling and dynamics of several species and sample types. Biological systems experience complex biochemical processes involving thousands of molecules. These processes occur at different levels that can be studied using mass spectrometry-based (MS-based) analysis, enabling high-throughput proteomics, glycoproteomics, glycomics, metabolomics, and lipidomics analysis. Here, we present the most up-to-date techniques utilized in the completion of omics analysis. Additionally, we include some interesting examples of the applicability of multi omics to a variety of biological systems.

Glycan-Tailored Glycoproteomic Analysis Reveals Serine is the Sole Residue Subjected to O-Linked Glycosylation in Acinetobacter baumannii.

Protein glycosylation is a ubiquitous process observed across all domains of life. Within the human pathogen Acinetobacter baumannii, O-linked glycosylation is required for virulence; however, the targets and conservation of glycosylation events remain poorly defined. In this work, we expand our understanding of the breadth and site specificity of glycosylation within A. baumannii by demonstrating the value of strain specific glycan electron-transfer/higher-energy collision dissociation (EThcD) triggering for bacterial glycoproteomics. By coupling tailored EThcD-triggering regimes to complementary glycopeptide enrichment approaches, we assessed the observable glycoproteome of three A. baumannii strains (ATCC19606, BAL062, and D1279779). Combining glycopeptide enrichment techniques including ion mobility (FAIMS), metal oxide affinity chromatography (titanium dioxide), and hydrophilic interaction liquid chromatography (ZIC-HILIC), as well as the use of multiple proteases (trypsin, GluC, pepsin, and thermolysis), we expand the known A. baumannii glycoproteome to 33 unique glycoproteins containing 42 glycosylation sites. We demonstrate that serine is the sole residue subjected to glycosylation with the substitution of serine for threonine abolishing glycosylation in model glycoproteins. An A. baumannii pan-genome built from 576 reference genomes identified that serine glycosylation sites are highly conserved. Combined this work expands our knowledge of the conservation and site specificity of A. baumannii O-linked glycosylation.

Experimentally Determined Diagnostic Ions for Identification of Peptide Glycotopes.

The analysis of the structures of glycans present on glycoproteins is an essential component for determining glycoprotein function; however, detailed glycan structural assignment on glycopeptides from proteomics mass spectrometric data remains challenging. Glycoproteomic analysis by mass spectrometry currently can provide significant, yet incomplete, information about the glycans present, including the glycan monosaccharide composition and in some circumstances the site(s) of glycosylation. Advancements in mass spectrometric resolution, using high-mass accuracy instrumentation and tailored MS/MS fragmentation parameters, coupled with a dedicated definition of diagnostic fragmentation ions have enabled the determination of some glycan structural features, or glycotopes, expressed on glycopeptides. Here we present a collation of diagnostic glycan fragments produced by traditional positive-ion-mode reversed-phase LC-ESI MS/MS proteomic workflows and describe the specific fragmentation energy settings required to identify specific glycotopes presented on N- or O-linked glycopeptides in a typical proteomics MS/MS experiment.