Recent advances in mass spectrometry-based glycoproteomics

An Introduction to Analytical Challenges, Approaches, and Applications in Mass Spectrometry-Based Secretomics

The active release of proteins into the extracellular space and the proteolytic cleavage of cell surface proteins are key processes that coordinate and fine-tune a multitude of physiological functions. The entirety of proteins that fulfill these extracellular tasks are referred to as the secretome and are of special interest for the investigation of biomarkers of disease states and physiological processes related to cell-cell communication. LC-MS-based proteomics approaches are a valuable tool for the comprehensive and unbiased characterization of this important subproteome. This review discusses procedures, opportunities, and limitations of mass spectrometry-based secretomics to better understand and navigate the complex analytical landscape for studying protein secretion in biomedical science.

A characteristic N-glycopeptide signature associated with diabetic cognitive impairment identified in a longitudinal cohort study

BACKGROUND

Identifying a biomarker for the decline in cognitive function in patients with diabetes is important. Therefore, we aimed to identify the N-glycopeptides on plasma proteins associated with diabetic cognitive impairment in participants in a longitudinal study using N-glycoproteomics.

METHODS

We used samples from the 3-year SONIC (Septuagenarians, Octogenarians, Nonagenarians Investigation with Centenarians) longitudinal cohort study of older Japanese people in the general population. First, we placed the participants with diabetes into two groups: those that did or did not have cognitive decline over a 6-year period. Next, their plasma protein profiles were compared between baseline and the 6-year time point using two-dimensional fluorescence difference gel electrophoresis. Finally, an N-glycoproteomic study of the focused proteins was performed using an enrichment technique and liquid chromatography-tandem mass spectrometry.

RESULTS

Approximately 500 N-glycopeptides, derived from 18 proteins, were identified in each sample, from among which we identified the N-glycopeptides that were associated with diabetic cognitive impairment using multivariate analysis. We found that N-glycopeptides with sialylated tri- or tetra-antennary glycans on alpha-2-macroglobulin, clusterin, serum paraoxonase/arylesterase 1, and haptoglobin were less abundant, whereas 3-sialylated tri-antennary N-glycopeptides on serotransferrin were more abundant.

CONCLUSION

N-glycopeptides with sialylated multi-antennary glycans comprise a characteristic signature associated with diabetic cognitive impairment.

GENERAL SIGNIFICANCE

The characterized N-glycopeptides represent potential biomarker candidates for diabetic cognitive impairment.

GlycoSLASH: Concurrent Glycopeptide Identification from Multiple Related LC-MS/MS Data Sets by Using Spectral Clustering and Library Searching

Liquid chromatography coupled with tandem mass spectrometry is commonly adopted in large-scale glycoproteomic studies involving hundreds of disease and control samples. The software for glycopeptide identification in such data (e.g., the commercial software Byonic) analyzes the individual data set and does not exploit the redundant spectra of glycopeptides presented in the related data sets. Herein, we present a novel concurrent approach for glycopeptide identification in multiple related glycoproteomic data sets by using spectral clustering and spectral library searching. The evaluation on two large-scale glycoproteomic data sets showed that the concurrent approach can identify 105%-224% more spectra as glycopeptides compared to the glycopeptide identification on individual data sets using Byonic alone. The improvement of glycopeptide identification also enabled the discovery of several potential biomarkers of protein glycosylations in hepatocellular carcinoma patients.

Serum Glycoproteomics and Identification of Potential Mechanisms Underlying Alzheimer’s Disease

Objectives. This study compares glycoproteomes in Thai Alzheimer’s disease (AD) patients with those of cognitively normal individuals. Methods. Study participants included outpatients with clinically diagnosed AD ( $N=136$ ) and healthy controls without cognitive impairment ( $N=183$ ). Blood samples were collected from all participants for biochemical analysis and for $\text{Apolipoprotein}\text{E}$ (APOE) genotyping by real-time TaqMan PCR assays. Comparative serum glycoproteomic profiling by liquid chromatography-tandem mass spectrometry was then performed to identify differentially abundant proteins with functional relevance. Results. Statistical differences in age, educational level, and APOE ɛ3/ɛ4 and ɛ4/ɛ4 haplotype frequencies were found between the AD and control groups. The frequency of the APOE ɛ4 allele was significantly higher in the AD group than in the control group. In total, 871 glycoproteins were identified, including 266 and 259 unique proteins in control and AD groups, respectively. There were 49 and 297 upregulated and downregulated glycoproteins, respectively, in AD samples compared with the controls. Unique AD glycoproteins were associated with numerous pathways, including Alzheimer’s disease-presenilin pathway (16.6%), inflammation pathway mediated by chemokine and cytokine signaling (9.2%), Wnt signaling pathway (8.2%), and apoptosis signaling pathway (6.7%). Conclusion. Functions and pathways associated with protein-protein interactions were identified in AD. Significant changes in these proteins can indicate the molecular mechanisms involved in the pathogenesis of AD, and they have the potential to serve as AD biomarkers. Such findings could allow us to better understand AD pathology.

Distinct glycosylation in membrane proteins within neonatal versus adult myocardial tissue

Mammalian hearts have regenerative potential restricted to early neonatal stage and lost within seven days after birth. Carbohydrates exclusive to cardiac neonatal tissue may be key regulators of regenerative potential. Although cell surface and extracellular matrix glycosylation are known modulators of tissue and cellular function and development, variation in cardiac glycosylation from neonatal tissue to maturation has not been fully examined. In this study, glycosylation of the adult rat cardiac ventricle showed no variability between the two strains analysed, nor were there any differences between the glycosylation of the right or left ventricle using lectin histochemistry and microarray profiling. However, in the Sprague-Dawley strain, neonatal cardiac glycosylation in the left ventricle differed from adult tissues using mass spectrometric analysis, showing a higher expression of high mannose structures and lower expression of complex N-linked glycans in the three-day-old neonatal tissue. Man₆GlcNAc₂ was identified as the main high mannose N-linked structure that was decreased in adult while higher expression of sialylated N-linked glycans and lower core fucosylation for complex structures were associated with ageing. The occurrence of mucin core type 2 O-linked glycans was reduced in adult and one sulfated core type 2 O-linked structure was identified in neonatal tissue. Interestingly, O-linked glycans from mature tissue contained both N-acetylneuraminic acid (Neu5Ac) and N-glycolylneuraminic acid (Neu5Gc), while all sialylated N-linked glycans detected contained only Neu5Ac. As glycans are associated with intracellular communication, the specific neonatal structures found may indicate a role for glycosylation in the neonatal associated regenerative capacity of the mammalian heart. New strategies targeting tissue glycosylation could be a key contributor to achieve an effective regeneration of the mammalian heart in pathological scenarios such as myocardial infarction.

Differential Quantitative Determination of Site-Specific Intact N-Glycopeptides in Serum Haptoglobin between Hepatocellular Carcinoma and Cirrhosis Using LC-EThcD-MS/MS

Intact N-glycopeptide analysis remains challenging due to the complexity of glycopeptide structures, low abundance of glycopeptides in protein digests, and difficulties in data interpretation/quantitation. Herein, we developed a workflow that involved advanced methodologies, the EThcD-MS/MS fragmentation method and data interpretation software, for differential analysis of the microheterogeneity of site-specific intact N-glycopeptides of serum haptoglobin between early hepatocellular carcinoma (HCC) and liver cirrhosis. Haptoglobin was immunopurified from 20 μL of serum in patients with early HCC, liver cirrhosis, and healthy controls, respectively, followed by trypsin/GluC digestion, glycopeptide enrichment, and LC-EThcD-MS/MS analysis. Identification and differential quantitation of site-specific N-glycopeptides were performed using a combination of Byonic and Byologic software. In total, 93, 87, and 68 site-specific N-glycopeptides were identified in early HCC, liver cirrhosis, and healthy controls, respectively, with high confidence. The increased variety of N-glycopeptides in liver diseases compared to healthy controls was due to increased branching with hyper-fucosylation and sialylation. Differential quantitation analysis showed that 5 site-specific N-glycopeptides on sites N184 and N241 were significantly elevated in early HCC compared to cirrhosis ( p < 0.05) and normal controls ( p ≤ 0.001). The result demonstrates that the workflow provides a strategy for detailed profiles of N-glycopeptides of patient samples as well as for relative quantitation to determine the level changes in site-specific N-glycopeptides between disease states.

Identification of Poly-N-Acetyllactosamine-Carrying Glycoproteins from HL-60 Human Promyelocytic Leukemia Cells Using a Site-Specific Glycome Analysis Method, Glyco-RIDGE

To elucidate the relationship between the protein function and the diversity and heterogeneity of glycans conjugated to the protein, glycosylation sites, glycan variation, and glycan proportions at each site of the glycoprotein must be analyzed. Glycopeptide-based structural analysis technology using mass spectrometry has been developed; however, complicated analyses of complex spectra obtained by multistage fragmentation are necessary, and sensitivity and throughput of the analyses are low. Therefore, we developed a liquid chromatography/mass spectrometry (MS)-based glycopeptide analysis method to reveal the site-specific glycome (Glycan heterogeneity-based Relational IDentification of Glycopeptide signals on Elution profile, Glyco-RIDGE). This method used accurate masses and retention times of glycopeptides, without requiring MS2, and could be applied to complex mixtures. To increase the number of identified peptide, fractionation of sample glycopeptides for reduction of sample complexity is required. Therefore, in this study, glycopeptides were fractionated into four fractions by hydrophilic interaction chromatography, and each fraction was analyzed using the Glyco-RIDGE method. As a result, many glycopeptides having long glycans were enriched in the highest hydrophilic fraction. Based on the monosaccharide composition, these glycans were thought to be poly-N-acetyllactosamine (polylactosamine [pLN]), and 31 pLN-carrier proteins were identified in HL-60 cells. Gene ontology enrichment analysis revealed that pLN carriers included many molecules related to signal transduction, receptors, and cell adhesion. Thus, these findings provided important insights into the analysis of the glycoproteome using our novel Glyco-RIDGE method. Graphical Abstract ᅟ.

Stage Dependence, Cell-Origin Independence, and Prognostic Capacity of Serum Glycan Fucosylation, β1-4 Branching, β1-6 Branching, and α2-6 Sialylation in Cancer

Glycans represent a promising but only marginally accessed source of cancer markers. We previously reported the development of a molecularly bottom-up approach to plasma and serum (P/S) glycomics based on glycan linkage analysis that captures features such as α2-6 sialylation, β1-6 branching, and core fucosylation as single analytical signals. Based on the behavior of P/S glycans established to date, we hypothesized that the alteration of P/S glycans observed in cancer would be independent of the tissue in which the tumor originated yet exhibit stage dependence that varied little between cancers classified on the basis of tumor origin. Herein, the diagnostic utility of this bottom-up approach as applied to lung cancer patients (n = 127 stage I; n = 20 stage II; n = 81 stage III; and n = 90 stage IV) as well as prostate (n = 40 stage II), serous ovarian (n = 59 stage III), and pancreatic cancer patients (n = 15 rapid autopsy) compared to certifiably healthy individuals (n = 30), nominally healthy individuals (n = 166), and risk-matched controls (n = 300) is reported. Diagnostic performance in lung cancer was stage-dependent, with markers for terminal (total) fucosylation, α2-6 sialylation, β1-4 branching, β1-6 branching, and outer-arm fucosylation most able to differentiate cases from controls. These markers behaved in a similar stage-dependent manner in other types of cancer as well. Notable differences between certifiably healthy individuals and case-matched controls were observed. These markers were not significantly elevated in liver fibrosis. Using a Cox proportional hazards regression model, the marker for α2-6 sialylation was found to predict both progression and survival in lung cancer patients after adjusting for age, gender, smoking status, and stage. The potential mechanistic role of aberrant P/S glycans in cancer progression is discussed.

Combining Click Chemistry-Based Proteomics With Dox-Inducible Gene Expression

Inactivating mutations in single genes can trigger, prevent, promote, or alleviate diseases. Identifying such disease-related genes is a main pillar of medical research. Since proteins play a crucial role in mediating these effects, their impact on the diseased cells' proteome including posttranslational modifications has to be elucidated for a detailed understanding of the role of these genes in the disease process. In complex disorders, like cancer, several genes contribute to the disease process, thereby hampering the assignment of a proteomic change to the corresponding causative gene. To enable comprehensive screening for the impact of inactivation of a gene, e.g., loss of a tumor suppressor in cancer, on the cellular proteome, we present a strategy based on combination of three technologies that is recombinase-mediated cassette exchange, click chemistry, and mass spectrometry. The methodology is exemplified by the analysis of the proteomic changes induced by the loss of a tumor suppressor gene in colorectal cancer cells. To demonstrate the applicability to screen for posttranslational modification changes, we also describe the analysis of protein glycosylation changes caused by the tumor suppressor inactivation. In principle, this strategy can be applied to analyze the effects of any gene of interest on protein expression as well as posttranslational modification by glycosylation. Moreover adaptation of the strategy to an appropriate cell culture model has the potential for application on a broad range of diseases where the disease-promoting mutations have been identified.

Three-Dimensionally Functionalized Reverse Phase Glycoprotein Array for Cancer Biomarker Discovery and Validation

Glycoproteins have vast structural diversity that plays an important role in many biological processes and have great potential as disease biomarkers. Here, we report a novel functionalized reverse phase protein array (RPPA), termed polymer-based reverse phase glycoprotein array (polyGPA), to capture and profile glycoproteomes specifically, and validate glycoproteins. Nitrocellulose membrane functionalized with globular hydroxyaminodendrimers was used to covalently capture preoxidized glycans on glycoproteins from complex protein samples such as biofluids. The captured glycoproteins were subsequently detected using the same validated antibodies as in RPPA. We demonstrated the outstanding specificity, sensitivity, and quantitative capabilities of polyGPA by capturing and detecting purified as well as endogenous α-1-acid glycoprotein (AGP) in human plasma. We further applied quantitative N-glycoproteomics and the strategy to validate a panel of glycoproteins identified as potential biomarkers for bladder cancer by analyzing urine glycoproteins from bladder cancer patients or matched healthy individuals.

A case for protein-level and site-level specificity in glycoproteomic studies of disease

Abnormal glycosylation of proteins is known to be either resultant or causative of a variety of diseases. This makes glycoproteins appealing targets as potential biomarkers and focal points of molecular studies on the development and progression of human ailment. To date, a majority of efforts in disease glycoproteomics have tended to center on either determining the concentration of a given glycoprotein, or on profiling the total population of glycans released from a mixture of glycoproteins. While these approaches have demonstrated some diagnostic potential, they are inherently insensitive to the fine molecular detail which distinguishes unique and possibly disease relevant glycoforms of specific proteins. As a consequence, such analyses can be of limited sensitivity, specificity, and accuracy because they do not comprehensively consider the glycosylation status of any particular glycoprotein, or of any particular glycosylation site. Therefore, significant opportunities exist to improve glycoproteomic inquiry into disease by engaging in these studies at the level of individual glycoproteins and their exact loci of glycosylation. In this concise review, the rationale for glycoprotein and glycosylation site specificity is developed in the context of human disease glycoproteomics with an emphasis on N-glycosylation. Recent examples highlighting disease-related perturbations in glycosylation will be presented, including those involving alterations in the overall glycosylation of a specific protein, alterations in the occupancy of a given glycosylation site, and alterations in the compositional heterogeneity of glycans occurring at a given glycosylation site. Each will be discussed with particular emphasis on how protein-specific and site-specific approaches can contribute to improved discrimination between glycoproteomes and glycoproteins associated with healthy and unhealthy states.

Mass Spectrometry-Based N-Glycomics of Colorectal Cancer

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide. An increased molecular understanding of the CRC pathology is warranted to gain insights into the underlying molecular and cellular mechanisms of the disease. Altered protein glycosylation patterns are associated with most diseases including malignant transformation. Recent advances in mass spectrometry and bioinformatics have accelerated glycomics research and present a new paradigm for cancer biomarker discovery. Mass spectrometry (MS)-based glycoproteomics and glycomics, therefore, hold considerable promise to improve the discovery of novel biomarkers with utility in disease diagnosis and therapy. This review focuses on the emerging field of glycomics to present a comprehensive review of advances in technologies and their application in studies aimed at discovering novel glycan-based biomarkers. We will also discuss some of the challenges associated with using glycans as biomarkers.

In-depth N-glycome profiling of paired colorectal cancer and non-tumorigenic tissues reveals cancer-, stage- and EGFR-specific protein N-glycosylation

Glycomics may assist in uncovering the structure-function relationships of protein glycosylation and identify glycoprotein markers in colorectal cancer (CRC) research. Herein, we performed label-free quantitative glycomics on a carbon-liquid chromatography-tandem mass spectrometry-based analytical platform to accurately profile the N-glycosylation changes associated with CRC malignancy. N-Glycome profiling was performed on isolated membrane proteomes of paired tumorigenic and adjacent non-tumorigenic colon tissues from a cohort of five males (62.6 ± 13.1 y.o.) suffering from colorectal adenocarcinoma. The CRC tissues were typed according to their epidermal growth factor receptor (EGFR) status by western blotting and immunohistochemistry. Detailed N-glycan characterization and relative quantitation identified an extensive structural heterogeneity with a total of 91 N-glycans. CRC-specific N-glycosylation phenotypes were observed including an overrepresentation of high mannose, hybrid and paucimannosidic type N-glycans and an under-representation of complex N-glycans (P < 0.05). Sialylation, in particular α2,6-sialylation, was significantly higher in CRC tumors relative to non-tumorigenic tissues, whereas α2,3-sialylation was down-regulated (P < 0.05). CRC stage-specific N-glycosylation was detected by high α2,3-sialylation and low bisecting β1,4-GlcNAcylation and Lewis-type fucosylation in mid-late relative to early stage CRC. Interestingly, a novel link between the EGFR status and the N-glycosylation was identified using hierarchical clustering of the N-glycome profiles. EGFR-specific N-glycan signatures included high bisecting β1,4-GlcNAcylation and low α2,3-sialylation (both P < 0.05) relative to EGFR-negative CRC tissues. This is the first study to correlate CRC stage and EGFR status with specific N-glycan features, thus advancing our understanding of the mechanisms causing the biomolecular deregulation associated with CRC.

Targeted methods for quantitative analysis of protein glycosylation

Quantification of proteins by LC-MS/MS-MRM has become a standard method with broad projected clinical applicability. MRM quantification of protein modifications is, however, far less utilized, especially in the case of glycoproteins. This review summarizes current methods for quantitative analysis of protein glycosylation with a focus on MRM methods. We describe advantages of this quantitative approach, analytical parameters that need to be optimized to achieve reliable measurements, and point out the limitations. Differences between major classes of N- and O-glycopeptides are described and class-specific glycopeptide assays are demonstrated.

Multiple enzyme approach for the characterization of glycan modifications on the C-terminus of the intestinal MUC2mucin

The polymeric mucin MUC2 constitutes the main structural component of the mucus that covers the colon epithelium. The protein’s central mucin domain is highly O-glycosylated and binds water to provide lubrication and prevent dehydration, binds bacteria, and separates the bacteria from the epithelial cells. Glycosylation outside the mucin domain is suggested to be important for proper protein folding and protection against intestinal proteases. However, glycosylation of these regions of the MUC2 has not been extensively studied. A purified 250 kDa recombinant protein containing the last 981 amino acids of human MUC2 was produced in CHO-K1 cells. The protein was analyzed before and after PNGase F treatment, followed by in-gel digestion with trypsin, chymotrypsin, subtilisin, or Asp-N. Peptides were analyzed by nLC/MS/MS using a combination of CID, ETD, and HCD fragmentation. The multiple enzyme approach increased peptide coverage from 36% when only using trypsin, to 86%. Seventeen of the 18 N-glycan consensus sites were identified as glycosylated. Fifty-six N-glycopeptides covering 10 N-glycan sites, and 14 O-glycopeptides were sequenced and characterized. The presented method of protein digestion can be used to gain better insights into the density and complexity of glycosylation of complex glycoproteins such as mucins.