Automated annotation and quantification of glycans using liquid chromatography-mass spectrometry

Suppressing the background of LC-ESI-MS analysis of permethylated glycans using the active background ion reduction device

Mass spectrometry (MS) has revolutionized analytical chemistry, enabling precise identification and quantification of chemical species, which is pivotal for biomarker discovery and understanding complex biological systems. Despite its versatility, the presence of background ions in MS analysis hinders the sensitive detection of low-abundance analytes. Therefore, studies aimed at lowering background ion levels have become increasingly important. Here, we utilized the commercially available Active Background Ion Reduction Device (ABIRD) to suppress background ions and assess its effect on the liquid chromatography-electrospray ionization (LC-ESI)-MS analyses of N-glycans on the Q Exactive HF mass spectrometer. We also investigated the effect of different solvent vapors in the ESI source on N-glycan analysis by MS. ABIRD generally had no effect on high-mannose and neutral structures but reduced the intensity of some structures that contained sialic acid, fucose, or both when methanol vapor filled the ESI source. Based on our findings on the highest number of identified N-glycans from human serum, methanol vapor in the ion source compartment may enhance N-glycan LC-ESI-MS analyses by improving the desolvation of droplets formed during the ESI process due to its high volatility. This protocol may be further validated and extended to advanced bottom-up proteomic/glycoproteomic studies for the analysis of peptide/glycopeptide ions by MS.

O-Glycome Profiling of Breast Cancer Cell Lines to Understand Breast Cancer Brain Metastasis

Breast cancer is the second leading cause of cancer-related death among women and a major source of brain metastases. Despite the increasing incidence of brain metastasis from breast cancer, the underlying mechanisms remain poorly understood. Altered glycosylation is known to play a role in various diseases including cancer metastasis. However, profiling studies of O-glycans and their isomers in breast cancer brain metastasis (BCBM) are scarce. This study analyzed the expression of O-glycans and their isomers in human breast cancer cell lines (MDA-MB-231, MDA-MB-361, HTB131, and HTB22), a brain cancer cell line (CRL-1620), and a brain metastatic breast cancer cell line (MDA-MB-231BR) using nanoLC-MS/MS, identifying 27 O-glycan compositions. We observed significant upregulation in the expression of HexNAc1Hex1NeuAc2 and HexNAc2Hex3, whereas the expression of HexNAc1Hex1NeuAc1 was downregulated in MDA-MB-231BR compared to other cell lines. In our isomeric analysis, we observed notable alterations in the isomeric forms of the O-glycan structure HexNAc1Hex1NeuAc1 in a comparison of different cell lines. Our analysis of O-glycans and their isomers in cancer cells demonstrated that changes in their distribution can be related to the metastatic process. We believe that our investigation will contribute to an enhanced comprehension of the significance of O-glycans and their isomers in BCBM.

An Efficient and Economical N-Glycome Sample Preparation Using Acetone Precipitation

Due to the critical role of the glycome in organisms and its close connections with various diseases, much time and effort have been dedicated to glycomics-related studies in the past decade. To achieve accurate and reliable identification and quantification of glycans extracted from biological samples, several analysis methods have been well-developed. One commonly used methodology for the sample preparation of N-glycomics usually involves enzymatic cleavage by PNGase F, followed by sample purification using C18 cartridges to remove proteins. PNGase F and C18 cartridges are very efficient both for cleaving N-glycans and for protein removal. However, this method is most suitable for a limited quantity of samples. In this study, we developed a sample preparation method focusing on N-glycome extraction and purification from large-scale biological samples using acetone precipitation. The N-glycan yield was first tested on standard glycoprotein samples, bovine fetuin and complex biological samples, and human serum. Compared to C18 cartridges, most of the sialylated N-glycans from human serum were detected with higher abundance after acetone precipitation. However, C18 showed a slightly higher efficiency for protein removal. Using the unfiltered human serum as the baseline, around 97.7% of the proteins were removed by acetone precipitation, while more than 99.9% of the proteins were removed by C18 cartridges. Lastly, the acetone precipitation was applied to N-glycome extraction from egg yolks to demonstrate large-scale glycomics sample preparation.

Glycosylation of a key cubilin Asn residue results in reduced binding to albumin

Kidney disease often manifests with an increase in proteinuria, which can result from both glomerular and/or proximal tubule injury. The proximal tubules are the major site of protein and peptide endocytosis of the glomerular filtrate, and cubilin is the proximal tubule brush border membrane glycoprotein receptor that binds filtered albumin and initiates its processing in proximal tubules. Albumin also undergoes multiple modifications depending upon the physiologic state. We previously documented that carbamylated albumin had reduced cubilin binding, but the effects of cubilin modifications on binding albumin remain unclear. Here, we investigate the cubilin-albumin binding interaction to define the impact of cubilin glycosylation and map the key glycosylation sites while also targeting specific changes in a rat model of proteinuria. We identified a key Asn residue, N1285, that when glycosylated reduced albumin binding. In addition, we found a pH-induced conformation change may contribute to ligand release. To further define the albumin-cubilin binding site, we determined the solution structure of cubilin's albumin-binding domain, CUB7,8, using small-angle X-ray scattering and molecular modeling. We combined this information with mass spectrometry crosslinking experiments of CUB7,8 and albumin that provides a model of the key amino acids required for cubilin-albumin binding. Together, our data supports an important role for glycosylation in regulating the cubilin interaction with albumin, which is altered in proteinuria and provides new insight into the binding interface necessary for the cubilin-albumin interaction.

Glycome Profiling of Cancer Cell Lines Cultivated in Physiological and Commercial Media

A complex physiological culture medium (Plasmax) was introduced recently, composed of nutrients and metabolites at concentrations normally found in human plasma to mimic the in vivo environment for cell line cultivation. As glycosylation has been proved to be involved in cancer development, it is necessary to investigate the glycan expression changes in media with different nutrients. In this study, a breast cancer cell line, MDA-MB-231BR, and a brain cancer cell line, CRL-1620, were cultivated in Plasmax and commercial media to reveal cell line glycosylation discrepancies prompted by nutritional environments. Glycomics analyses of cell lines were performed using LC-MS/MS. The expressions of multiple fucosylated N-glycans, such as HexNAc₄Hex₃DeoxyHex₁ and HexNAc₅Hex₃DeoxyHex₁, derived from both cell lines exhibited a significant increase in Plasmax. Among the O-glycans, significant differences were also observed. Both cell lines cultivated in EMEM had the lowest amounts of O-glycans expressed. The original work described the development of Plasmax, which improves colony formation, and resulted in transcriptomic and metabolomic alterations of cancer cell lines, while our results indicate that Plasmax can significantly impact protein glycosylation. This study also provides information to guide the selection of media for in vitro cancer cell glycomics studies.

Salmonella enterica serovar Typhimurium chitinases modulate the intestinal glycome and promote small intestinal invasion

Salmonella enterica serovar Typhimurium (S. Typhimurium) is one of the leading causes of food-borne illnesses worldwide. To colonize the gastrointestinal tract, S. Typhimurium produces multiple virulence factors that facilitate cellular invasion. Chitinases have been recently emerging as virulence factors for various pathogenic bacterial species, and the S. Typhimurium genome contains two annotated chitinases: STM0018 (chiA) and STM0233. However, the role of these chitinases during S. Typhimurium pathogenesis is unknown. The putative chitinase STM0233 has not been studied previously, and only limited data exists on ChiA. Chitinases typically hydrolyze chitin polymers, which are absent in vertebrates. However, chiA expression was detected in infection models and purified ChiA cleaved carbohydrate subunits present on mammalian surface glycoproteins, indicating a role during pathogenesis. Here, we demonstrate that expression of chiA and STM0233 is upregulated in the mouse gut and that both chitinases facilitate epithelial cell adhesion and invasion. S. Typhimurium lacking both chitinases showed a 70% reduction in invasion of small intestinal epithelial cells in vitro. In a gastroenteritis mouse model, chitinase-deficient S. Typhimurium strains were also significantly attenuated in the invasion of small intestinal tissue. This reduced invasion resulted in significantly delayed S. Typhimurium dissemination to the spleen and the liver, but chitinases were not required for systemic survival. The invasion defect of the chitinase-deficient strain was rescued by the presence of wild-type S. Typhimurium, suggesting that chitinases are secreted. By analyzing N-linked glycans of small intestinal cells, we identified specific N-acetylglucosamine-containing glycans as potential extracellular targets of S. Typhimurium chitinases. This analysis also revealed a differential abundance of Lewis X/A-containing glycans that is likely a result of host cell modulation due to the detection of S. Typhimurium chitinases. Similar glycomic changes elicited by chitinase deficient strains indicate functional redundancy of the chitinases. Overall, our results demonstrate that S. Typhimurium chitinases contribute to intestinal adhesion and invasion through modulation of the host glycome.

Changes in the Expression of Renal Brush Border Membrane N-Glycome in Model Rats with Chronic Kidney Diseases

Chronic kidney disease (CKD) is defined by a reduced renal function i.e., glomerular filtration rate (GFR), and the presence of kidney damage is determined by measurement of proteinuria or albuminuria. Albuminuria increases with age and can result from glomerular and/or proximal tubule (PT) alterations. Brush-border membranes (BBMs) on PT cells play an important role in maintaining the stability of PT functions. The PT BBM, a highly dynamic, organized, specialized membrane, contains a variety of glycoproteins required for the functions of PT. Since protein glycosylation regulates many protein functions, the alteration of glycosylation due to the glycan changes has attracted more interests for a variety of disease studies recently. In this work, liquid chromatography-tandem mass spectrometry was utilized to analyze the abundances of permethylated glycans from rats under control to mild CKD, severe CKD, and diabetic conditions. The most significant differences were observed in sialylation level with the highest present in the severe CKD and diabetic groups. Moreover, high mannose N-glycans was enriched in the CKD BBMs. Characterization of all the BBM N-glycan changes supports that these changes are likely to impact the functional properties of the dynamic PT BBM. Further, these changes may lead to the potential discovery of glycan biomarkers for improved CKD diagnosis and new avenues for therapeutic treatments.

Altered O-glycomes of Renal Brush-Border Membrane in Model Rats with Chronic Kidney Diseases

Chronic kidney disease (CKD) is defined as a decrease in renal function or glomerular filtration rate (GFR), and proteinuria is often present. Proteinuria increases with age and can be caused by glomerular and/or proximal tubule (PT) alterations. PT cells have an apical brush border membrane (BBM), which is a highly dynamic, organized, and specialized membrane region containing multiple glycoproteins required for its functions including regulating uptake, secretion, and signaling dependent upon the physiologic state. PT disorders contribute to the dysfunction observed in CKD. Many glycoprotein functions have been attributed to their N- and O-glycans, which are highly regulated and complex. In this study, the O-glycans present in rat BBMs from animals with different levels of kidney disease and proteinuria were characterized and analyzed using liquid chromatography tandem mass spectrometry (LC-MS/MS). A principal component analysis (PCA) documented that each group has distinct O-glycan distributions. Higher fucosylation levels were observed in the CKD and diabetic groups, which may contribute to PT dysfunction by altering physiologic glycoprotein interactions. Fucosylated O-glycans such as 1-1-1-0 exhibited higher abundance in the severe proteinuric groups. These glycomic results revealed that differential O-glycan expressions in CKD progressions has the potential to define the mechanism of proteinuria in kidney disease and to identify potential therapeutic interventions.

gQuant, an Automated Tool for Quantitative Glycomic Data Analysis

MALDI-MS-based glycan isotope labeling methods have been effectively and widely used for quantitative glycomics. However, interpretation of the data produced by MALDI-MS is inaccurate and tedious because the bioinformatic tools are inadequate. In this work, we present gQuant, an automated tool for MALDI-MS-based glycan isotope labeling data processing. gQuant was designed with a set of dedicated algorithms to improve the efficiency, accuracy and convenience of quantitation data processing. When tested on the reference data set, gQuant showed a fast processing speed, as it was able to search the glycan data of model glycoproteins in a few minutes and reported more results than the manual analysis did. The reported quantitation ratios matched well with the experimental glycan mixture ratios ranging from 1:10 to 10:1. In addition, gQuant is fully open-source and is coded in Python, which is supported by most operating systems, and it has a user-friendly interface. gQuant can be easily adapted by users for specific experimental designs, such as specific glycan databases, different derivatization types and relative quantitation designs and can thus facilitate fast glycomic quantitation for clinical sample analysis using MALDI-MS-based stable isotope labeling.

GlycanGUI: Automated Glycan Annotation and Quantification Using Glucose Unit Index

The retention time provides critical information for glycan annotation and quantification from the Liquid Chromatography Mass Spectrometry (LC-MS) data. However, the variation of the precise retention time of glycans is highly dependent on the experimental conditions such as the specific separating columns, MS instruments and/or the buffer used. This variation hampers the exploitation of retention time for the glycan annotation from LC-MS data, especially when inter-laboratory data are compared. To incorporate the retention time of glycan across experiments, Glucose Unit Index (GUI) can be computed using the dextrin ladder as internal standard. The retention time of glycans are then calibrated with respect to glucose units derived from dextrin ladders. Despite the successful application of the GUI approach, the manual calibration process is quite tedious and often error prone. In this work, we present a standalone software tool GlycanGUI, with a graphic user interface to automatically carry out the GUI-based glycan annotation/quantification and subsequent data analysis. When tested on experimental data, GlycanGUI reported accurate GUI values compared with manual calibration, and thus is ready to be used for automated glycan annotation and quantification using GUI.

Determination of Isomeric Glycan Structures by Permethylation and Liquid Chromatography-Mass Spectrometry (LC-MS)

The existence of glycans in isomeric forms is responsible for the multifariousness of their properties and biological functions. Their altered expression has been associated with various diseases and cancers. Analysis of native glycans is not very sensitive due to the low ionization efficiency of glycans. These facts necessitate their comprehensive structural studies and establishes a high demand for sensitive and reliable techniques. In this chapter, we discuss the strategies for effective separation and identification of permethylated isomeric glycans. The sample preparation for permethylated glycans derived from model glycoproteins and complex biological samples, analyzed using LC-MS/MS, is delineated. We introduce protein extraction and release of glycans, followed by strategies to purify the released glycans, which are reduced and permethylated to improve ionization efficiency and stabilize sialic acid residues. High-temperature LC-based separation on PGC (porous graphitized carbon) column is conducive to isomeric separation of glycans and allows their sensitive identification and quantification using MS/MS.

Characterization of Glycosphingolipids and Their Diverse Lipid Forms through Two-Stage Matching of LC-MS/MS Spectra

Glycosphingolipids (GSLs) play a key role in various biological and pathological events. Thus, determination of the complete GSL compositions in human tissues is essential for comparative and functional studies of GSLs. In this work, a new strategy was developed for GSL characterization and glycolipidomics analysis based on two-stage matching of experimental and reference MS/MS spectra. In the first stage, carbohydrate fragments, which contain only glycans and thus are conserved within a GSL species, are directly matched to yield a species identification. In the second stage, glycolipid fragments from the matched GSL species, which contain both the lipid and glycans and thus shift due to lipid structural changes, are treated according to lipid rule-based matching to characterize the lipid compositions. This new strategy uses the whole spectrum for GSL characterization. Furthermore, simple databases containing only a single lipid form per GSL species can be utilized to identify multiple GSL lipid forms. It is expected that this method will help accelerate glycolipidomics analysis and disclose new and diverse lipid forms of GSLs.

N-Linked Surface Glycan Biosynthesis, Composition, Inhibition, and Function in Cnidarian-Dinoflagellate Symbiosis

The success of symbioses between cnidarian hosts (e.g., corals and sea anemones) and micro-algal symbionts hinges on the molecular interactions that govern the establishment and maintenance of intracellular mutualisms. As a fundamental component of innate immunity, glycan-lectin interactions impact the onset of marine endosymbioses, but our understanding of the effects of cell surface glycome composition on symbiosis establishment remains limited. In this study, we examined the canonical N-glycan biosynthesis pathway in the genome of the dinoflagellate symbiont Breviolum minutum (family Symbiodiniaceae) and found it to be conserved with the exception of the transferase GlcNAc-TII (MGAT2). Using coupled liquid chromatography-mass spectrometry (LC-MS/MS), we characterized the cell surface N-glycan content of B. minutum, providing the first insight into the molecular composition of surface glycans in dinoflagellates. We then used the biosynthesis inhibitors kifunensine and swainsonine to alter the glycan composition of B. minutum. Successful high-mannose enrichment via kifunensine treatment resulted in a significant decrease in colonization of the model sea anemone Aiptasia (Exaiptasia pallida) by B. minutum. Hybrid glycan enrichment via swainsonine treatment, however, could not be confirmed and did not impact colonization. We conclude that functional Golgi processing of N-glycans is critical for maintaining appropriate cell surface glycan composition and for ensuring colonization success by B. minutum.

Best-first search guided multistage mass spectrometry-based glycan identification

MOTIVATION

Glycan identification has long been hampered by complicated branching patterns and various isomeric structures of glycans. Multistage mass spectrometry (MSn) is a promising glycan identification technique as it generates multiple-level fragments of a glycan, which can be explored to deduce branching pattern of the glycan and further distinguish it from other candidates with identical mass. However, the automatic glycan identification still remains a challenge since it mainly relies on expertise to guide a MSn instrument to generate spectra.

RESULTS

Here, we proposed a novel method, named bestFSA, based on a best-first search algorithm to guide the process of spectrum producing in glycan identification using MSn. BestFSA is able to select the most appropriate peaks for next round of experiments and complete the identification using as few experimental rounds. Our analysis of seven representative glycans shows that bestFSA correctly distinguishes actual glycans efficiently and suggested bestFSA could be used in practical glycan identification. The combination of the MSn technology coupled with bestFSA should greatly facilitate the automatic identification of glycan branching patterns, with significantly improved identification sensitivity, and reduce time and cost of MSn experiments.

AVAILABILITY AND IMPLEMENTATION

http://glycan.ict.ac.cn.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Comparative Membrane N-Glycomics of Different Breast Cancer Cell Lines To Understand Breast Cancer Brain Metastasis

The mechanism of brain metastatic breast cancer has gained attention because of its increased incidence rate and its low survival rate. Aberrant protein glycosylation is thought to be a contributing factor in this metastatic mechanism, in which metastatic cancer cells can pass through the blood-brain barrier (BBB). The cell membrane is the outermost layer of a cell and in direct contact with the environment and with other cells, making membrane glycans especially important in many biological processes that include mediating cell-cell adhesion, cell signaling, and interactions. Thus, membrane glycomics has attracted more interest for a variety of disease studies in recent years. To reveal the role that membrane N-glycans play in breast cancer brain metastasis, in this study, membrane enrichment was achieved by ultracentrifugation. Liquid chromatography-tandem mass spectrometry was employed to analyze enriched membrane N-glycomes from five breast cancer cell lines and one brain cancer cell line. Relative quantitative glycomic data from each cell line were compared to MDA-MB-231BR, which is the brain-seeking cell line. The higher sialylation level observed in MDA-MB-231BR suggested the importance of sialylation as it might assist with cell invasion and the penetration of the BBB. Some highly sialylated N-glycans, such as HexNAc₅Hex₆DeoxyHex₁NeuAc₃ and HexNAc₆Hex₇DeoxyHex₁NeuAc₃, exhibited higher abundances in 231BR, indicating their possible contributions to breast cancer brain metastasis as well as their potential to be indicators for the breast cancer brain metastasis.

Application of network smoothing to glycan LC-MS profiling

Motivation

Glycosylation is one of the most heterogeneous and complex protein post-translational modifications. Liquid chromatography coupled mass spectrometry (LC-MS) is a common high throughput method for analyzing complex biological samples. Accurate study of glycans require high resolution mass spectrometry. Mass spectrometry data contains intricate sub-structures that encode mass and abundance, requiring several transformations before it can be used to identify biological molecules, requiring automated tools to analyze samples in a high throughput setting. Existing tools for interpreting the resulting data do not take into account related glycans when evaluating individual observations, limiting their sensitivity.

Results

We developed an algorithm for assigning glycan compositions from LC-MS data by exploring biosynthetic network relationships among glycans. Our algorithm optimizes a set of likelihood scoring functions based on glycan chemical properties but uses network Laplacian regularization and optionally prior information about expected glycan families to smooth the likelihood and thus achieve a consistent and more representative solution. Our method was able to identify as many, or more glycan compositions compared to previous approaches, and demonstrated greater sensitivity with regularization. Our network definition was tailored to N-glycans but the method may be applied to glycomics data from other glycan families like O-glycans or heparan sulfate where the relationships between compositions can be expressed as a graph.

Availability and implementation Built Executable

http://www.bumc.bu.edu/msr/glycresoft/ and Source Code: https://github.com/BostonUniversityCBMS/glycresoft.

Supplementary information

Supplementary data are available at Bioinformatics online.

8-plex LC-MS/MS Analysis of Permethylated N-Glycans Achieved by Using Stable Isotopic Iodomethane

Glycosylation is an important post-translational modification of proteins. Many diseases, such as cancer, have proved to be related to aberrant glycosylation. High throughput quantitative methods have gained attention recently in the study of glycomics. With the development of high-resolution mass spectrometry, the sensitivity of detection in glycomics has largely improved; however, most of the commonly used MS-based techniques are focused on relative quantitative analysis, which can hardly provide direct comparative glycomic quantitation results. In this study, we developed a novel multiplex glycomic analysis method on an LC-ESI-MS platform. Reduced glycans were stable isotopic labeled during the permethylation procedure, with the use of iodomethane reagents CH2DI, CHD2I, CD3I, 13CH3I, 13CH2DI, 13CHD2I, 13CD3I, and CH3I. Up to 8-plex glycomic profiling was possible in a single analysis by LC-MS, and a 100 k mass resolution was sufficient to allow a baseline resolution of the mass differences among the 8-plex labeled glycans. The major advantages of this method are that it overcomes quantitative fluctuations caused by nanoESI, it facilitates a level of comparative quantitative glycomic analysis that accurately reflects the quantitative information in samples, and it dramatically shortens analysis time. Quantitation validation was tested on glycans released from bovine fetuin and model glycoprotein mixtures (RNase B, bovine fetuin, and IgG) with good linearity (R2 = 0.9884) and a dynamic range from 0.1 to 10. The 8-plex strategy was successfully applied to a comparative glycomic study of cancer cell lines. The results demonstrate that different distributions of sialylated glycans are related to the metastatic properties of cell lines and provide important clues for a better understanding of breast cancer brain metastasis.

Revealing the Biological Attributes of N-Glycan Isomers in Breast Cancer Brain Metastasis Using Porous Graphitic Carbon (PGC) Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS)

Breast cancer is a leading cancer in women and is considered to be the second-most common metastatic cancer following lung cancer. An estimated 10-16% of breast cancer patients are suffering from brain metastasis, and the diagnostic cases of breast cancer brain metastasis are increasing. Nevertheless, the mechanisms behind this process are still unclear. Aberrant glycosylation has been proved to be related to many diseases and cancer metastasis. However, studies of N-glycan isomer function in breast cancer brain metastasis are limited. In this study, the expressions of N-glycan isomers derived from five breast cancer cell lines and one brain cancer cell line were investigated and compared to a brain-seeking cell line, 231BR, to acquire a better understanding of the role glycan isomers play in breast cancer brain metastasis. The high temperature nanoPGC-LC-MS/MS achieved an efficient isomeric separation and permitted the identification and quantitation of 144 isomers from 50 N-glycan compositions. There were significant expression alterations of these glycan isomers among the different breast cancer cell lines. The increase of total glycan abundance and sialylation level were observed to be associated with breast cancer invasion. With regard to individual isomers, the greatest number of sialylated isomers was observed along with significant expression alterations in 231BR, suggesting a relationship between glycan sialylation and breast cancer brain metastasis. Furthermore, the increase of the α2,6-sialylation level in 231BR likely contributes to the passage of breast cancer cells through the blood-brain barrier, thus facilitating breast cancer brain metastasis. Meanwhile, the upregulation of highly sialylated glycan isomers with α2,6-linked sialic acids were found to be associated with breast cancer metastasis. This investigation of glycan isomer expressions, especially the unique isomeric expression in brain-seeking cell line 231BR, provides new information toward understanding the potential roles glycan isomers play during breast cancer metastasis and more clues for a deeper insight of this bioprocess.

LC-MS/MS glycomics of idiopathic rapid eye movement sleep behavior disorder

Idiopathic REM sleep behavior disorder (iRBD) is now considered a prodromal stage of an α-synucleinopathy-related to neurodegenerative disease such as Parkinson's diseases. Emerging evidence has shown that post-translational modification or glycosylation are implicated in dynamic disease mechanisms and the onset of many pathological conditions. We hypothesized that the characterization of the glycosylation pattern of patients with RBD would be of great value to understand the pathophysiology and underlying mechanisms and represent potentially useful biomarkers for disease-associated molecular changes. To test this hypothesis, we assessed the serum glycome of patients with RBD and compared to that of healthy controls. NanoRPLC-MS was used to generate quantitative N-glycan profiles while high-temperature PGC-LC-MS platform was employed to generate quantitative isomeric N-glycan profiles. By analyzing permethylated glycans derived from human blood sera on C18-LC-MS/MS, we identified 59 N-glycan structures in healthy (control) cohort, 56 N-glycans in RBD cohort. Sixteen N-glycans structures were found to be significantly altered in the RBD cohort (p < 0.05). N-glycans with the composition of HexNAc4 Hex5 Fuc1 , HexNAc5 Hex5 , and HexNAc4 Hex5 Fuc1 NeuAc1 presented the most substantial difference between controls and RBD patients (p < 0.01). HexNAc4 Hex5 Fuc1 NeuAc1 showed a relatively high abundance (3.1 ± 0.7% in the control cohort versus 4 ± 3% in the idiopathic RBD cohort). These N-glycans can be potential diagnostic biomarker candidates and provide a window into underlying neurodegenerative processes in patients with idiopathic RBD. In addition, 7 N-glycan isomers were significantly different between controls and RBD patients (p < 0.05). HexNAc4 Hex5 Fuc1 NeuAc1 (4511-2) and HexNAc4 Hex5 Fuc1 NeuAc2 (4512-2) showed the most substantial difference between the control and idiopathic RBD cohorts (p < 0.001). Levels of both these two isomeric structures were higher in the idiopathic RBD cohort. Further larger studies are required to assess the reproducibility of these findings and to elucidate the role played by the changes in glycan structures in the pathogenetic mechanisms of RBD. This information will be instrumental in developing molecular therapeutic targets to promote neuroprotection and prevention of neurodegeneration.

Quantitative glycomics using liquid phase separations coupled to mass spectrometry

Post-translational modification of proteins by the attachment of glycans is governed by a variety of highly specific enzymes and is associated with fundamental impacts on the parent protein's physical, chemical and biological properties. The inherent connection between cellular physiology and specific glycosylation patterns has been shown to offer potential for diagnostic and prognostic monitoring of altered glycosylation in the disease state. Conversely, glycoprotein based biopharmaceuticals have emerged as dominant therapeutic strategies in the treatment of intricate diseases. Glycosylation present on these biopharmaceuticals represents a major critical quality attribute with impacts on both pharmacokinetics and pharmacodynamics. The structural variety of glycans, based upon their non-template driven assembly, poses a significant analytical challenge for both qualitative and quantitative analysis. Labile monosaccharide constituents, isomeric species and often low sample availability from biological sources necessitates meticulous sample handling, ultra-high-resolution analytical separation and sensitive detection techniques, respectively. In this article a critical review of analytical quantitation approaches using liquid phase separations coupled to mass spectrometry for released glycans of biopharmaceutical and biomedical significance is presented. Considerations associated with sample derivatisation strategies, ionisation, relative quantitation through isotopic as well as isobaric labelling, metabolic/enzymatic incorporation and targeted analysis are all thoroughly discussed.

Enhanced Quantitative LC-MS/MS Analysis of N-linked Glycans Derived from Glycoproteins Using Sodium Deoxycholate Detergent

Protein glycosylation is a common protein post-translational modification (PTM) in living organisms and has been shown to associate with multiple diseases, and thus may potentially be a biomarker of such diseases. Efficient protein/glycoprotein extraction is a crucial step in the preparation of N-glycans derived from glycoproteins prior to LC-MS analysis. Convenient, efficient and unbiased sample preparation protocols are needed. Herein, we evaluated the use of sodium deoxycholate (SDC) acidic labile detergent to release N-glycans of glycoproteins derived from biological samples such as cancer cell lines. Compared to the filter-aided sample preparation approach, the sodium deoxycholate (SDC) assisted approach was determined to be more efficient and unbiased. SDC removal was determined to be more efficient when using acidic precipitation rather than ethyl acetate phase transfer. Efficient extraction of proteins/glycoproteins from biological samples was achieved by combining SDC lysis buffer and beads beating cell disruption. This was suggested by a significant overall increase in the intensities of N-glycans released from cancer cell lines. Additionally, the use of SDC approach was also shown to be more reproducible than those methods that do not use SDC.

Discrimination of Isomers of Released N- and O-Glycans Using Diagnostic Product Ions in Negative Ion PGC-LC-ESI-MS/MS

Profiling cellular protein glycosylation is challenging due to the presence of highly similar glycan structures that play diverse roles in cellular physiology. As the anomericity and the exact linkage type of a single glycosidic bond can influence glycan function, there is a demand for improved and automated methods to confirm detailed structural features and to discriminate between structurally similar isomers, overcoming a significant bottleneck in the analysis of data generated by glycomics experiments. We used porous graphitized carbon-LC-ESI-MS/MS to separate and detect released N- and O-glycan isomers from mammalian model glycoproteins using negative mode resonance activation CID-MS/MS. By interrogating similar fragment spectra from closely related glycan isomers that differ only in arm position and sialyl linkage, product fragment ions for discrimination between these features were discovered. Using the Skyline software, at least two diagnostic fragment ions of high specificity were validated for automated discrimination of sialylation and arm position in N-glycan structures, and sialylation in O-glycan structures, complementing existing structural diagnostic ions. These diagnostic ions were shown to be useful for isomer discrimination using both linear and 3D ion trap mass spectrometers when analyzing complex glycan mixtures from cell lysates. Skyline was found to serve as a useful tool for automated assessment of glycan isomer discrimination. This platform-independent workflow can potentially be extended to automate the characterization and quantitation of other challenging glycan isomers. Graphical Abstract ᅟ.

Human disease glycomics: technology advances enabling protein glycosylation analysis - part 1

INTRODUCTION

Protein glycosylation is recognized as an important post-translational modification, with specific substructures having significant effects on protein folding, conformation, distribution, stability and activity. However, due to the structural complexity of glycans, elucidating glycan structure-function relationships is demanding. The fine detail of glycan structures attached to proteins (including sequence, branching, linkage and anomericity) is still best analysed after the glycans are released from the purified or mixture of glycoproteins (glycomics). The technologies currently available for glycomics are becoming streamlined and standardized and many features of protein glycosylation can now be determined using instruments available in most protein analytical laboratories. Areas covered: This review focuses on the current glycomics technologies being commonly used for the analysis of the microheterogeneity of monosaccharide composition, sequence, branching and linkage of released N- and O-linked glycans that enable the determination of precise glycan structural determinants presented on secreted proteins and on the surface of all cells. Expert commentary: Several emerging advances in these technologies enabling glycomics analysis are discussed. The technological and bioinformatics requirements to be able to accurately assign these precise glycan features at biological levels in a disease context are assessed.

Algorithms and design strategies towards automated glycoproteomics analysis

Glycoproteomics involves the study of glycosylation events on protein sequences ranging from purified proteins to whole proteome scales. Understanding these complex post-translational modification (PTM) events requires elucidation of the glycan moieties (monosaccharide sequences and glycosidic linkages between residues), protein sequences, as well as site-specific attachment of glycan moieties onto protein sequences, in a spatial and temporal manner in a variety of biological contexts. Compared with proteomics, bioinformatics for glycoproteomics is immature and many researchers still rely on tedious manual interpretation of glycoproteomics data. As sample preparation protocols and analysis techniques have matured, the number of publications on glycoproteomics and bioinformatics has increased substantially; however, the lack of consensus on tool development and code reuse limits the dissemination of bioinformatics tools because it requires significant effort to migrate a computational tool tailored for one method design to alternative methods. This review discusses algorithms and methods in glycoproteomics, and refers to the general proteomics field for potential solutions. It also introduces general strategies for tool integration and pipeline construction in order to better serve the glycoproteomics community. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:475-498, 2017.

A Brief Review of Bioinformatics Tools for Glycosylation Analysis by Mass Spectrometry

The purpose of this review is to provide updated information regarding bioinformatic software for the use in the characterization of glycosylated structures since 2013. A comprehensive review by Woodin et al.Analyst 138: 2793-2803, 2013 (ref. 1) described two main approaches that are introduced for starting researchers in this area; analysis of released glycans and the identification of glycopeptide in enzymatic digests, respectively. Complementary to that report, this review focuses on mass spectrometry related bioinformatics tools for the characterization of N-linked and O-linked glycopeptides. Specifically, it also provides information regarding automated tools that can be used for glycan profiling using mass spectrometry.

Analysis of Permethylated Glycan by Liquid Chromatography (LC) and Mass Spectrometry (MS)

The development of a reliable and high-throughput glycomic profiling strategy is in high demand due to the biological roles of glycans and their association with different diseases. Native analysis can be quite difficult because of the low ionization efficiency and microheterogeneity of glycans. In this chapter, the sample preparation protocols and LC-MS analysis of permethylated glycan strategies are introduced. Solid-phase permethylation is a fast, convenient, and high-yield method to stabilize sialic acid and improve glycan ionization efficiency and analysis in positive mode; this results in a more sensitive and reliable glycomic profiling strategy. Several modifications in the LC method are also mentioned in this chapter. Online purification simplifies sample preparation and reduces sample loss. Elevating the column temperature significantly improves the peak shape of permethylated glycans and results in isomeric separation. The identification and quantification of permethylated glycans can be achieved through high resolution MS and MS/MS experiments using a MRM method; both approaches are reliable, sensitive, and conducive to high-throughput glycomic studies.

Quantitative profiling of glycans and glycopeptides: an informatics' perspective

Experimental techniques to identify and quantify glycan structures in a given sample are continuously improving. However, as they advance data analysis and annotation seems to become more complex. To address this issue, much progress has been made in developing software for interpretation of quantitative glycan profiles. Here, we focus on these informatics tools for high/ultra performance liquid chromatography (H/UPLC), mass spectrometry (MS), tandem mass spectrometry (MSⁿ) and combinations thereof. Software for biomarker discovery, pathway, genomic and disease analysis and a final note on some future prospects for glycoinformatics are also mentioned.

LaCyTools: A Targeted Liquid Chromatography-Mass Spectrometry Data Processing Package for Relative Quantitation of Glycopeptides

Bottom-up glycoproteomics by liquid chromatography-mass spectrometry (LC-MS) is an established approach for assessing glycosylation in a protein- and site-specific manner. Consequently, tools are needed to automatically align, calibrate, and integrate LC-MS glycoproteomics data. We developed a modular software package designed to tackle the individual aspects of an LC-MS experiment, called LaCyTools. Targeted alignment is performed using user defined m/z and retention time (tr) combinations. Subsequently, sum spectra are created for each user defined analyte group. Quantitation is performed on the sum spectra, where each user defined analyte can have its own tr, minimum, and maximum charge states. Consequently, LaCyTools deals with multiple charge states, which gives an output per charge state if desired, and offers various analyte and spectra quality criteria. We compared throughput and performance of LaCyTools to combinations of available tools that deal with individual processing steps. LaCyTools yielded relative quantitation of equal precision (relative standard deviation <0.5%) and higher trueness due to the use of MS peak area instead of MS peak intensity. In conclusion, LaCyTools is an accurate automated data processing tool for high-throughput analysis of LC-MS glycoproteomics data. Released under the Apache 2.0 license, it is freely available on GitHub ( https://github.com/Tarskin/LaCyTools ).

Deciphering glycomics and neuroproteomic alterations in experimental traumatic brain injury: Comparative analysis of aspirin and clopidogrel treatment

As populations age, the number of patients sustaining traumatic brain injury (TBI) and concomitantly receiving preinjury antiplatelet therapy such as aspirin (ASA) and clopidogrel (CLOP) is rising. These drugs have been linked with unfavorable clinical outcomes following TBI, where the exact mechanism(s) involved are still unknown. In this novel work, we aimed to identify and compare the altered proteome profile imposed by ASA and CLOP when administered alone or in combination, prior to experimental TBI. Furthermore, we assessed differential glycosylation PTM patterns following experimental controlled cortical impact model of TBI, ASA, CLOP, and ASA + CLOP. Ipsilateral cortical brain tissues were harvested 48 h postinjury and were analyzed using an advanced neuroproteomics LC-MS/MS platform to assess proteomic and glycoproteins alterations. Of interest, differential proteins pertaining to each group (22 in TBI, 41 in TBI + ASA, 44 in TBI + CLOP, and 34 in TBI + ASA + CLOP) were revealed. Advanced bioinformatics/systems biology and clustering analyses were performed to evaluate biological networks and protein interaction maps illustrating molecular pathways involved in the experimental conditions. Results have indicated that proteins involved in neuroprotective cellular pathways were upregulated in the ASA and CLOP groups when given separately. However, ASA + CLOP administration revealed enrichment in biological pathways relevant to inflammation and proinjury mechanisms. Moreover, results showed differential upregulation of glycoproteins levels in the sialylated N-glycans PTMs that can be implicated in pathological changes. Omics data obtained have provided molecular insights of the underlying mechanisms that can be translated into clinical bedside settings.

Reliable LC-MS quantitative glycomics using iGlycoMab stable isotope labeled glycans as internal standards

Glycans have numerous functions in various biological processes and participate in the progress of diseases. Reliable quantitative glycomic profiling techniques could contribute to the understanding of the biological functions of glycans, and lead to the discovery of potential glycan biomarkers for diseases. Although LC-MS is a powerful analytical tool for quantitative glycomics, the variation of ionization efficiency and MS intensity bias are influencing quantitation reliability. Internal standards can be utilized for glycomic quantitation by MS-based methods to reduce variability. In this study, we used stable isotope labeled IgG2b monoclonal antibody, iGlycoMab, as an internal standard to reduce potential for errors and to reduce variabililty due to sample digestion, derivatization, and fluctuation of nanoESI efficiency in the LC-MS analysis of permethylated N-glycans released from model glycoproteins, human blood serum, and breast cancer cell line. We observed an unanticipated degradation of isotope labeled glycans, tracked a source of such degradation, and optimized a sample preparation protocol to minimize degradation of the internal standard glycans. All results indicated the effectiveness of using iGlycoMab to minimize errors originating from sample handling and instruments.

Integrated Transcriptomic and Glycomic Profiling of Glioma Stem Cell Xenografts

Bone marrow-derived human mesenchymal stem cells (BM-hMSCs) have the innate ability to migrate or home toward and engraft in tumors such as glioblastoma (GBM). Because of this unique property of BM-hMSCs, we have explored their use for cell-mediated therapeutic delivery for the advancement of GBM treatment. Extravasation, the process by which blood-borne cells—such as BM-hMSCs—enter the tissue, is a highly complex process but is heavily dependent upon glycosylation for glycan-glycan and glycan-protein adhesion between the cell and endothelium. However, in a translationally significant preclinical glioma stem cell xenograft (GSCX) model of GBM, BM-hMSCs demonstrate unequal tropism toward these tumors. We hypothesized that there may be differences in the glycan compositions between the GSCXs that elicit homing ("attractors") and those that do not ("non-attractors") that facilitate or impede the engraftment of BM-hMSCs in the tumor. In this study, glycotranscriptomic analysis revealed significant heterogeneity within the attractor phenotype and the enrichment of high mannose type N-glycan biosynthesis in the non-attractor phenotype. Orthogonal validation with topical PNGase F deglycosylation on the tumor regions of xenograft tissue, followed by nLC-ESI-MS, confirmed the presence of increased high mannose type N-glycans in the non-attractors. Additional evidence provided by our glycomic study revealed the prevalence of terminal sialic acid-containing N-glycans in non-attractors and terminal galactose and N-acetyl-glucosamine N-glycans in attractors. Our results provide the first evidence for differential glycomic profiles in attractor and non-attractor GSCXs and extend the scope of molecular determinates in BM-hMSC homing to glioma.

Automated annotation and quantitation of glycans by liquid chromatography/electrospray ionization mass spectrometric analysis using the MultiGlycan-ESI computational tool

RATIONALE

Liquid chromatography/mass spectrometry (LC/MS) is currently considered to be a conventional glycomics analysis strategy due to the high sensitivity and ability to handle complex biological samples. Interpretation of LC/MS data is a major bottleneck in high-throughput glycomics LC/MS-based analysis. The complexity of LC/MS data associated with biological samples prompts the needs to develop computational tools capable of facilitating automated data annotation and quantitation.

METHODS

An LC/MS-based automated data annotation and quantitation software, MultiGlycan-ESI, was developed and utilized for glycan quantitation. Data generated by the software from LC/MS analysis of permethylated N-glycans derived from fetuin were initially validated by manual integration to assess the performance of the software. The performance of MultiGlycan-ESI was then assessed for the quantitation of permethylated fetuin N-glycans analyzed at different concentrations or spiked with permethylated N-glycans derived from human blood serum.

RESULTS

The relative abundance differences between data generated by the software and those generated by manual integration were less than 5%, indicating the reliability of MultiGlycan-ESI in quantitation of permethylated glycans analyzed by LC/MS. Automated quantitation resulted in a linear relationship for all six N-glycans derived from 50 ng to 400 ng fetuin with correlation coefficients (R(2) ) greater than 0.93. Spiking of permethylated fetuin N-glycans at different concentrations in permethylated N-glycan samples derived from a 0.02 μL of HBS also exhibited linear agreement with R(2) values greater than 0.9.

CONCLUSIONS

With a variety of options, including mass accuracy, merged adducts, and filtering criteria, MultiGlycan-ESI allows automated annotation and quantitation of LC/ESI-MS N-glycan data. The software allows the reliable quantitation of glycan LC/MS data. The software is reliable for automated glycan quantitation, thus facilitating rapid and reliable high-throughput glycomics studies.

GlyQ-IQ: glycomics quintavariate-informed quantification with high-performance computing and GlycoGrid 4D visualization

Glycomics quintavariate-informed quantification (GlyQ-IQ) is a biologically guided glycomics analysis tool for identifying N-glycans in liquid chromatography-mass spectrometry (LC-MS) data. Glycomics LC-MS data sets have convoluted extracted ion chromatograms that are challenging to deconvolve with existing software tools. LC deconvolution into constituent pieces is critical in glycomics data sets because chromatographic peaks correspond to different intact glycan structural isomers. The biological targeted analysis approach offers several key advantages to traditional LC-MS data processing. A priori glycan information about the individual target's elemental composition allows for improved sensitivity by utilizing the exact isotope profile information to focus chromatogram generation and LC peak fitting on the isotopic species having the highest intensity. Glycan target annotation utilizes glycan family relationships and in source fragmentation in addition to high specificity feature LC-MS detection to improve the specificity of the analysis. The GlyQ-IQ software was developed in this work and evaluated in the context of profiling the N-glycan compositions from human serum LC-MS data sets. A case study is presented to demonstrate how GlyQ-IQ identifies and removes confounding chromatographic peaks from high mannose glycan isomers from human blood serum. In addition, GlyQ-IQ was used to generate a broad human serum N-glycan profile from a high resolution nanoelectrospray-liquid chromatography-tandem mass spectrometry (nESI-LC-MS/MS) data set. A total of 156 glycan compositions and 640 glycan isomers were detected from a single sample. Over 99% of the GlyQ-IQ glycan-feature assignments passed manual validation and are backed with high-resolution mass spectra.

Specific glycosylation of membrane proteins in epithelial ovarian cancer cell lines: glycan structures reflect gene expression and DNA methylation status

Epithelial ovarian cancer is the fifth most common cause of cancer in women worldwide bearing the highest mortality rate among all gynecological cancers. Cell membrane glycans mediate various cellular processes such as cell signaling and become altered during carcinogenesis. The extent to which glycosylation changes are influenced by aberrant regulation of gene expression is nearly unknown for ovarian cancer and remains crucial in understanding the development and progression of this disease. To address this effect, we analyzed the membrane glycosylation of non-cancerous ovarian surface epithelial (HOSE 6.3 and HOSE 17.1) and serous ovarian cancer cell lines (SKOV 3, IGROV1, A2780, and OVCAR 3), the most common histotype among epithelial ovarian cancers. N-glycans were released from membrane glycoproteins by PNGase F and analyzed using nano-liquid chromatography on porous graphitized carbon and negative-ion electrospray ionization mass spectrometry (ESI-MS). Glycan structures were characterized based on their molecular masses and tandem MS fragmentation patterns. We identified characteristic glycan features that were unique to the ovarian cancer membrane proteins, namely the "bisecting N-acetyl-glucosamine" type N-glycans, increased levels of α 2-6 sialylated N-glycans and "N,N'-diacetyl-lactosamine" type N-glycans. These N-glycan changes were verified by examining gene transcript levels of the enzymes specific for their synthesis (MGAT3, ST6GAL1, and B4GALNT3) using qRT-PCR. We further evaluated the potential epigenetic influence on MGAT3 expression by treating the cell lines with 5-azacytidine, a DNA methylation inhibitor. For the first time, we provide evidence that MGAT3 expression may be epigenetically regulated by DNA hypomethylation, leading to the synthesis of the unique "bisecting GlcNAc" type N-glycans on the membrane proteins of ovarian cancer cells. Linking the observation of specific N-glycan substructures and their complex association with epigenetic programming of their associated synthetic enzymes in ovarian cancer could potentially be used for the development of novel anti-glycan drug targets and clinical diagnostic tools.