Clinical application of quantitative glycomics

Machine Learning-Enhanced Cerebrospinal Fluid N-Glycome for the Diagnosis and Prognosis of Primary Central Nervous System Lymphoma

The diagnosis and prognosis of Primary Central Nervous System Lymphoma (PCNSL) present significant challenges. In this study, the potential use of machine learning algorithms in diagnosing and predicting the prognosis for PCNSL based on cerebrospinal fluid (CSF) N-glycomics was investigated. First, CSF samples obtained from a cohort of 60 PCNSL patients and 30 controls were analyzed by hydrophilic interaction-based ultra performance liquid chromatography (HILIC-UPLC)-fluorescence mass spectrometry. Subsequently, nine machine learning models were established to diagnose PCNSL based on the changes of CSF N-glycome, with the Random Forest algorithm proving to be the most effective, achieving an accuracy of 100% in the training set and 89.3% in the test set. Moreover, a COX proportional-hazard model and a nomogram incorporating CSF N-glycome (GP6 and GP27) along with clinical data (age) were crafted. This nomogram's discrimination capacity was considered satisfactory, as evidenced by a C-index of 0.804 (95% CI: 0.68, 0.927). The study reveals that machine learning models based on CSF N-glycome offer a valuable approach for diagnosing and prognosticating PCNSL, demonstrating high accuracy and sensitivity in both classification and survival analysis. These findings may offer new insights into the molecular mechanisms underlying PCNSL and contribute to the advancement of personalized medicine for patients with this disease.

Recent Advances in Labeling-Based Quantitative Glycomics: From High-Throughput Quantification to Structural Elucidation

Glycosylation, a crucial posttranslational modification (PTM), plays important roles in numerous biological processes and is linked to various diseases. Despite its significance, the structural complexity and diversity of glycans present significant challenges for mass spectrometry (MS)-based quantitative analysis. This review aims to provide an in-depth overview of recent advancements in labeling strategies for N-glycomics and O-glycomics, with a specific focus on enhancing the sensitivity, specificity, and throughput of MS analyses. We categorize these advancements into three major areas: (1) the development of isotopic/isobaric labeling techniques that significantly improve multiplexing capacity and throughput for glycan quantification; (2) novel methods that aid in the structural elucidation of complex glycans, particularly sialylated and fucosylated glycans; and (3) labeling techniques that enhance detection ionization efficiency, separation, and sensitivity for matrix-assisted laser desorption/ionization (MALDI)-MS and capillary electrophoresis (CE)-based glycan analysis. In addition, we highlight emerging trends in single-cell glycomics and bioinformatics tools that have the potential to revolutionize glycan quantification. These developments not only expand our understanding of glycan structures and functions but also open new avenues for biomarker discovery and therapeutic applications. Through detailed discussions of methodological advancements, this review underscores the critical role of derivatization methods in advancing glycan identification and quantification.

N-glycan as new potential biomarker for predicting treatment response in patients with type 2 diabetes mellitus

AIMS

To investigate the N-glycans related to the metformin efficacy in patients with type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

We enrolled 141 healthy controls and 195 newly diagnosed T2DM patients treated with metformin for 3 months. Serum N-glycan profile was determined by DNA sequencer - assisted fluorophore-assisted carbohydrate electrophoresis (DSA-FACE). The N-glycan model was established by logistic regression analysis. Receiver operating characteristic curve (ROC) analysis was used to analyze the predictive power of the N-glycan model for metformin efficacy.

RESULTS

The abundances of several N-glycans in serum of T2DM patients at baseline were significantly different from those of healthy controls and tended to recover the N-glycan of controls after 3 months treatment. Serum N-glycans changes were more significant in the good response group (FPG <7 mmol/L) after metformin treatment. In addition, the abundance of peak9 at baseline had an opposite tendency between HbA1c increased and decreased groups post-treatment, which could be a biomarker for predicting metformin efficacy. Peak9 combined with other 11 N-glycans at baseline was used to establish the predictive model to distinguish non-response from response patients (AUROC = 0.780, sensitivity = 70.6% and specificity = 77.5%).

CONCLUSIONS

Serum N-glycans may have potential value as biomarkers for indicating the efficacy of metformin.

Serum N-Glycan Changes in Rats Chronically Exposed to Glyphosate-Based Herbicides

Glyphosate, the active ingredient in many herbicides, has been widely used in agriculture since the 1970s. Despite initial beliefs in its safety for humans and animals due to the absence of the shikimate pathway, recent studies have raised concerns about its potential health effects. This study aimed to identify glycomic changes indicative of glyphosate-induced toxicity. Specifically, the study focused on profiling N-glycosylation, a protein post-translational modification increasingly recognized for its involvement in various disorders, including neurological conditions. A comprehensive analysis of rat serum N-glycomics following chronic exposure to glyphosate-based herbicides (GBH) was conducted using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The results revealed significant changes in the N-glycan profile, particularly in sialylated and sialofucosylated N-glycans. The analysis of N-glycans across gender subgroups provided insights into gender-specific responses to GBH exposure, with the male rats exhibiting a higher susceptibility to these N-glycan changes compared to females. The validation of significantly altered N-glycans using parallel reaction monitoring (PRM) confirmed their expression patterns. This study provides novel insights into the impact of chronic GBH exposure on serum N-glycan composition, with implications for assessing glyphosate toxicity and its potential neurological implications.

Standards-Free Absolute Quantitation of Oxidizable Glycopeptides by Coulometric Mass Spectrometry

Currently, glycopeptide quantitation is mainly based on relative quantitation due to absolute quantitation requiring isotope-labeled or standard glycopeptides which may not be commercially available or are very costly and time consuming to synthesize. To address this grand challenge, coulometric mass spectrometry (CMS), based on the combination of electrochemistry (EC) and mass spectrometry (MS), was utilized to quantify electrochemically active glycopeptides without the need of using standard materials. In this study, we studied tyrosine-containing glycopeptides, NYIVGQPSS(β-GlcNAc)TGNL-OH and NYSVPSS(β-GlcNAc)TGNL-OH, and successfully quantified them directly with CMS with a discrepancy of less than 5% between the CMS measured amount and the theoretical amount. Taking one step further, we applied this approach to quantify glycopeptides generated from the digestion of NIST mAb, a monoclonal antibody reference material. Through HILIC column separation, five N297 glycopeptides resulting from NIST mAb tryptic digestion were successfully separated and quantified by CMS for an absolute amount without the use of any standard materials. This study indicates the potential utility of CMS for quantitative proteomics research.

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.

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.

In Silico Study on a Binding Mechanism of ssDNA Aptamers Targeting Glycosidic Bond-Containing Small Molecules

Aptamer-based detection targeting glycoconjugates has attracted significant attention for its remarkable potential in identifying structural changes in saccharides in different stages of various diseases. However, the challenges in screening aptamers for small carbohydrates or glycoconjugates, which contain highly flexible and diverse glycosidic bonds, have hindered their application and commercialization. In this study, we investigated the binding conformations between three glycosidic bond-containing small molecules (GlySMs; glucose, N-acetylneuraminic acid, and neomycin) and their corresponding aptamers in silico, and analyzed factors contributing to their binding affinities. Based on the findings, a novel binding mechanism was proposed, highlighting the central role of the stem structure of the aptamer in binding and recognizing GlySMs and the auxiliary role of the mismatched bases in the adjacent loop. Guided by this binding mechanism, an aptamer with a higher 6'-sialyllactose binding affinity was designed, achieving a KD value of 4.54 ± 0.64 μM in vitro through a single shear and one mutation. The binding mechanism offers crucial guidance for designing high-affinity aptamers, enhancing the virtual screening efficiency for GlySMs. This streamlined workflow filters out ineffective binding sites, accelerating aptamer development and providing novel insights into glycan-nucleic acid interactions.

A glycosylation-related signature predicts survival in pancreatic cancer

BACKGROUND

Tumor initiation and progression are closely associated with glycosylation. However, glycosylated molecules have not been the subject of extensive studies as prognostic markers for pancreatic cancer. The objectives of this study were to identify glycosylation-related genes in pancreatic cancer and use them to construct reliable prognostic models.

MATERIALS AND METHODS

The Cancer Genome Atlas and Gene Expression Omnibus databases were used to assess the differential expression of glycosylation-related genes; four clusters were identified based on consistent clustering analysis. Kaplan-Meier analyses identified three glycosylation-related genes associated with overall survival. LASSO analysis was then performed on The Cancer Genome Atlas and International Cancer Genome Consortium databases to identify glycosylation-related signatures. We identified 12 GRGs differently expressed in pancreatic cancer and selected three genes (SEL1L, TUBA1C, and SDC1) to build a prognostic model. Thereafter, patients were divided into high and low-risk groups. Eventually, we performed Quantitative real-time PCR (qRT-PCR) to validate the signature.

RESULTS

Clinical outcomes were significantly poorer in the high-risk group than in the low-risk group. There were also significant correlations between the high-risk group and several risk factors, including no-smoking history, drinking history, radiotherapy history, and lower tumor grade. Furthermore, the high-risk group had a higher proportion of immune cells. Eventually, three glycosylation-related genes were validated in human PC cell lines.

CONCLUSION

This study identified the glycosylation-related signature for pancreatic cancer. It is an effective predictor of survival and can guide treatment decisions.

Glycan/Protein-Stable Isotope Labeling in Cell Culture for Enabling Concurrent Quantitative Glycomics/Proteomics/Glycoproteomics

The complexity and heterogeneity of protein glycosylation present an analytical challenge to the studies of characterization and quantitation. Various LC-MS-based quantitation strategies have emerged in recent decades. Metabolic stable isotope labeling has been developed to enhance the accurate LC/MS-based quantitation between different cell lines. Stable isotope labeling by amino acids in a cell culture (SILAC) is the most widely used metabolic labeling method in proteomic analysis. However, it can only label the peptide backbone and is thus limited in glycomic studies. Here, we present a metabolic isotope labeling strategy, named GlyProSILC (Glycan Protein Stable Isotope Labeling in Cell Culture), that can label both the glycan motif and peptide backbone from the same batch of cells. It was performed by feeding cells with a heavy medium containing amide-15N-glutamine, 13C6-arginine (Arg6), and 13C6-15N2-lysine (Lys8). No significant change of cell line metabolism after GlyProSILC labeling was observed based on transcriptomic, glycomic, and proteomic data. The labeling conditions, labeling efficiency, and quantitation accuracy were investigated. After quantitation correction, we simultaneously quantified 62 N-glycans, 574 proteins, and 344 glycopeptides using the same batch of mixed 231BR/231 cell lines. So far, GlyProSILC provides an accurate and effective quantitation approach for glycomics, proteomics, and glycoproteomics in a cell culture system.

Assessing the hydrophobicity of glycopeptides using reversed-phase liquid chromatography and tandem mass spectrometry

Retention time is one of the most important parameters that has been widely used to demonstrate the separation results obtained from liquid chromatography (LC) platforms. However, retention time can shift when samples are tested with different instruments and laboratories, which hinders the identification process of analytes when comparing data collected from different LC systems. To address this problem, hydrophobicity index was introduced for retention time normalization of the glycopeptides separated by reversed-phase LC (RPLC). Tandem MS was used for the detection and identification of glycopeptides. In addition, the influence of different types of glycans on the hydrophobicity of peptide backbones was studied by comparing the retention time of glycopeptides with their non-glycosylated counterparts. The hydrophobicity of tryptic digested glycopeptides derived from model glycoproteins, including bovine fetuin, α1-acid glycoprotein, and haptoglobin from human plasma, were evaluated based on the hydrophobicity index of the standard peptides from a peptide retention time calibration mixture. The reduction of hydrophobicity of multiple peptide backbones was observed due to the hydrophilic glycan structures. By comparing the hydrophobicity index of glycopeptides collected from different time and instruments, the day-to-day and lab-to-lab comparisons suggested high reliability and reproducibility of this approach. The RSD% of hydrophobicity index from inter-lab experiments was 1.2%, while the RSD% of retention time was 5.1%. Then, the applications of this method were demonstrated on complex glycopeptide samples extracted from human blood serum. The hydrophobicity index can be applied to address the retention time shift when using different instruments, thereby boosting confidence of the characterization of glycopeptides.

Stable isotope labeling differential glycans discovery in the serum of acute myocardial infarction by ultrahigh-performance liquid chromatography-quadrupole-Orbitrap high resolution mass spectrometry

Acute myocardial infarction (AMI) poses a grave threat to human life. However, most clinical biomarkers have limitations of low sensitivity and specificity. Therefore, screening novel glycan biomarkers with high sensitivity and specificity is crucial for the prevention and treatment of AMI. The novel method of ultrahigh-performance liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS) with d0/d5-BOTC probe labeling for relative quantification of glycans based on Pronase E digestion was established to screen novel glycan biomarkers in the serum of 34 AMI patients relative to healthy volunteers. The monosaccharide model D-glucosamine was used to investigate the effectiveness of the derivatization; the limit of detection (S/N = 3) was 10 amol. The accuracy was verified based on the consistency of different theoretical molar ratios (d0/d5 = 1:2, 2:1) and intensity ratios following digestion of glycoprotein ribonuclease B. Expressions of H4N4F3SA, H4N6F2, H4N6SA, H4N6F3 and H5N4FSA in the serum were significantly different (p < 0.0005) between AMI patients and healthy volunteers. The area under the receiver operating characteristic curve (AUC) for H4N6SA, H5N4FSA, and H4N6F2 was greater than 0.9039. Based on the proposed method, H4N6SA, H5N4FSA, and H4N6F2 in human serum showed high accuracy and specificity and may serve as potential glycan biomarkers, crucial for the diagnosis and treatment monitoring of AMI.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2017-2018

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization mass spectrometry (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2018. Also included are papers that describe methods appropriate to glycan and glycoprotein analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. Topics covered in the first part of the review include general aspects such as theory of the MALDI process, new methods, matrices, derivatization, MALDI imaging, fragmentation and the use of arrays. The second part of the review is devoted to applications to various structural types such as oligo- and poly-saccharides, glycoproteins, glycolipids, glycosides, and biopharmaceuticals. Most of the applications are presented in tabular form. The third part of the review covers medical and industrial applications of the technique, studies of enzyme reactions, and applications to chemical synthesis. The reported work shows increasing use of combined new techniques such as ion mobility and highlights the impact that MALDI imaging is having across a range of diciplines. MALDI is still an ideal technique for carbohydrate analysis and advancements in the technique and the range of applications continue steady progress.

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.

Targeting osteoarthritis-associated galectins and an induced effector class by a ditopic bifunctional reagent: Impact of its glycan part on binding measured in the tissue context

Pairing glycans with tissue lectins controls multiple effector pathways in (patho)physiology. A clinically relevant example is the prodegradative activity of galectins-1 and -3 (Gal-1 and -3) in the progression of osteoarthritis (OA) via matrix metalloproteinases (MMPs), especially MMP-13. The design of heterobifunctional inhibitors that can block galectin binding and MMPs both directly and by preventing their galectin-dependent induction selectively offers a perspective to dissect the roles of lectins and proteolytic enzymes. We describe the synthesis of such a reagent with a bivalent galectin ligand connected to an MMP inhibitor and of two tetravalent glycoclusters with a subtle change in headgroup presentation for further elucidation of influence on ligand binding. Testing was performed on clinical material with mixtures of galectins as occurring in vivo, using sections of fixed tissue. Two-colour fluorescence microscopy monitored binding to the cellular glycome after optimization of experimental parameters. In the presence of the inhibitor, galectin binding to OA specimens was significantly reduced. These results open the perspective to examine the inhibitory capacity of custom-made ditopic compounds on binding of lectins in mixtures using sections of clinical material with known impact of galectins and MMPs on disease progression.

Quantitative clinical glycomics strategies: A guide for selecting the best analysis approach

Glycans introduce complexity to the proteins to which they are attached. These modifications vary during the progression of many diseases; thus, they serve as potential biomarkers for disease diagnosis and prognosis. The immense structural diversity of glycans makes glycosylation analysis and quantitation difficult. Fortunately, recent advances in analytical techniques provide the opportunity to quantify even low-abundant glycopeptides and glycans derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Understanding the strengths and weaknesses of different quantitative glycomics analysis methods is important for selecting the best strategy to analyze glycosylation changes in any given set of clinical samples. To provide guidance towards selecting the proper approach, we discuss four widely used quantitative glycomics analysis platforms, including fluorescence-based analysis of released N-linked glycans and three different varieties of MS-based analysis: liquid chromatography (LC)-mass spectrometry (MS) analysis of glycopeptides, matrix-assisted laser desorption ionization-time of flight MS, and LC-ESI-MS analysis of released N-linked glycans. These methods' strengths and weaknesses are compared, particularly associated with the figures of merit that are important for clinical biomarker studies, including: the initial sample requirements, the methods' throughput, sample preparation time, the number of species identified, the methods' utility for isomer separation and structural characterization, method-related challenges associated with quantitation, repeatability, the expertise required, and the cost for each analysis. This review, therefore, provides unique guidance to researchers who endeavor to undertake a clinical glycomics analysis by offering insights on the available analysis technologies.

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.

Mass spectrometry-based N-glycosylation analysis in kidney disease

Kidney disease is a global health concern with an enormous expense. It is estimated that more than 10% of the population worldwide is affected by kidney disease and millions of patients would progress to death prematurely and unnecessarily. Although creatinine detection and renal biopsy are well-established tools for kidney disease diagnosis, they are limited by several inevitable defects. Therefore, diagnostic tools need to be upgraded, especially for the early stage of the disease and possible progression. As one of the most common post-translational modifications of proteins, N-glycosylation plays a vital role in renal structure and function. Deepening research on N-glycosylation in kidney disease provides new insights into the pathophysiology and paves the way for clinical application. In this study, we reviewed recent N-glycosylation studies on several kidney diseases. We also summarized the development of mass spectrometric methods in the field of N-glycoproteomics and N-glycomics.

Isomeric separation of permethylated glycans by extra-long reversed-phase liquid chromatography (RPLC)-MS/MS

Glycosylation is known as a critical biological process that can largely affect the properties and the functions of proteins. Glycan isomers have been shown to be involved in a variety of disease progressions. However, the separation and identification of glycan isomers has been a challenge for years due to the microheterogeneity of glycan isomeric structures. Therefore, effective and stable techniques have been investigated over the last few decades to improve isomeric separations of glycans. RPLC has been widely used in biomolecule analysis because of its extraordinary reproducibility and reliability in retention time and separation resolution. However, so far, no studies have achieved high resolution of glycan isomers using this technique. In this study, we focused on further boosting the isomeric separation of permethylated glycans using a 500 mm reversed-phase LC column. To achieve better resolutions on permethylated glycans, different LC conditions were optimized using glycan standards, including core- and branch-fucosylated N-glycan isomers and sialic acid linked isomers, which were both successfully separated. Then, the optimal separation strategy was applied to achieve separations of N- and O-glycan isomers derived from model glycoproteins, including bovine fetuin, ribonuclease B and κ-casein. Baseline separations were observed on multiple sialylated linkage isomers. However, the separation performance of high-mannose isomers needs further improvement. The reproducibility and stability of this long C18 column was also tested by doing run-to-run, day-to-day and month-to-month comparisons of retention times on multiple glycans and the %RSD was found less than 0.92%. Finally, we applied this approach to separate glycan isomers derived from complex biological samples, including blood serum and cell lines, where baseline separations were attained on several isomeric structures. Compared to the separation efficiency of PGC and MGC columns, the RPLC C18 column provides lower resolution but more robust reproducibility, which makes it a good complementary alternative for isomeric separations of glycans.

Genetic regulation of post-translational modification of two distinct proteins

Post-translational modifications diversify protein functions and dynamically coordinate their signalling networks, influencing most aspects of cell physiology. Nevertheless, their genetic regulation or influence on complex traits is not fully understood. Here, we compare the genetic regulation of the same PTM of two proteins - glycosylation of transferrin and immunoglobulin G (IgG). By performing genome-wide association analysis of transferrin glycosylation, we identify 10 significantly associated loci, 9 of which were not reported previously. Comparing these with IgG glycosylation-associated genes, we note protein-specific associations with genes encoding glycosylation enzymes (transferrin - MGAT5, ST3GAL4, B3GAT1; IgG - MGAT3, ST6GAL1), as well as shared associations (FUT6, FUT8). Colocalisation analyses of the latter suggest that different causal variants in the FUT genes regulate fucosylation of the two proteins. Glycosylation of these proteins is thus genetically regulated by both shared and protein-specific mechanisms.

Glycomic and Glycoproteomic Techniques in Neurodegenerative Disorders and Neurotrauma: Towards Personalized Markers

The proteome represents all the proteins expressed by a genome, a cell, a tissue, or an organism at any given time under defined physiological or pathological circumstances. Proteomic analysis has provided unparalleled opportunities for the discovery of expression patterns of proteins in a biological system, yielding precise and inclusive data about the system. Advances in the proteomics field opened the door to wider knowledge of the mechanisms underlying various post-translational modifications (PTMs) of proteins, including glycosylation. As of yet, the role of most of these PTMs remains unidentified. In this state-of-the-art review, we present a synopsis of glycosylation processes and the pathophysiological conditions that might ensue secondary to glycosylation shortcomings. The dynamics of protein glycosylation, a crucial mechanism that allows gene and pathway regulation, is described. We also explain how-at a biomolecular level-mutations in glycosylation-related genes may lead to neuropsychiatric manifestations and neurodegenerative disorders. We then analyze the shortcomings of glycoproteomic studies, putting into perspective their downfalls and the different advanced enrichment techniques that emanated to overcome some of these challenges. Furthermore, we summarize studies tackling the association between glycosylation and neuropsychiatric disorders and explore glycoproteomic changes in neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington disease, multiple sclerosis, and amyotrophic lateral sclerosis. We finally conclude with the role of glycomics in the area of traumatic brain injury (TBI) and provide perspectives on the clinical application of glycoproteomics as potential diagnostic tools and their application in personalized medicine.

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.

N-Glycosylation Profiling of Human Blood in Type 2 Diabetes by Capillary Electrophoresis: A Preliminary Study

Currently, diagnosing type 2 diabetes (T2D) is a great challenge. Thus, there is a need to find rapid, simple, and reliable analytical methods that can detect the disease at an early stage. The aim of this work was to shed light on the importance of sample collection options, sample preparation conditions, and the applied capillary electrophoresis bioanalytical technique, for a high-resolution determination of the N-glycan profile in human blood samples of patients with type 2 diabetes (T2D). To achieve the profile information of these complex oligosaccharides, linked by asparagine to hIgG in the blood, the glycoproteins of the samples needed to be cleaved, labelled, and purified with sufficient yield and selectivity. The resulting samples were analyzed by capillary electrophoresis, with laser-induced fluorescence detection. After separation parameter optimization, the capillary electrophoresis technique was implemented for efficient N-glycan profiling of whole blood samples from the diabetic patients. Our results revealed that there were subtle differences between the N-glycan profiles of the diabetic and control samples; in particular, two N-glycan structures were identified as potential glycobiomarkers that could reveal significant changes between the untreated/treated type 2 diabetic and control samples. By analyzing the resulting oligosaccharide profiles, clinically relevant information was obtained, revealing the differences between the untreated and HMG-CoA reductase-inhibitor-treated diabetic patients on changes in the N-glycan profile in the blood. In addition, the information from specific IgG N-glycosylation profiles in T2D could shed light on underlying inflammatory pathophysiological processes and lead to drug targets.

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.

Chondroitin Sulfate Disaccharides, a Serum Marker for Primary Serous Epithelial Ovarian Cancer

Glycosaminoglycans are long polysaccharidic chains, which are mostly present in connective tissues. Modified GAG expression in tissues surrounding malignant cells has been shown to contribute to tumor progression, aggressive status and metastasis in many types of cancer. Ovarian cancer is one of the most lethal gynecological malignancies due to its late diagnosis because of the absence of clear symptoms and unavailability of early disease markers. We investigated for the first time GAG changes at the molecular level as a novel biomarker for primary epithelial ovarian cancer. To this end, serum of a cohort of 68 samples was digested with chondroitinase ABC, which releases chondroitin sulfate into disaccharides. After labeling and purification, they were measured by HPLC, yielding a profile of eight disaccharides. We proposed a novel GAG-based score named "CS- bio" from the measured abundance of disaccharides present that were of statistical relevance. CS-bio's performance was compared with CA125, the clinically used serum tumor marker in routine diagnostics. CS-bio had a better sensitivity and specificity than CA125. It was more apt in differentiating early-stage patients from healthy controls, which is of high interest for oncologists.

Revealing the changes of IgG subclass-specific N-glycosylation in colorectal cancer progression by high-throughput assay

PURPOSE

The changes of glycosylation of different IgG subclass in colorectal cancer (CRC) were rarely investigated. The authors aimed to use a simple and high-throughput analytical method to explore the changes of subclass-specific IgG glycosylation in CRC, and to find the specific glyco-biomarkers for early detection of this disease.

EXPERIMENTAL DESIGN

Serum samples from 71 cancer patients and 22 benign patients with 50 age- and sex-matched healthy controls were collected from two independent cohorts. Subclass-specific IgG glycosylation was profiled by MALDI-MS followed by the structural identification through MALDI-MS/MS. The exported MS data was automatically and rapidly processed by the self-developed MATLAB code.

RESULTS

Statistical analysis suggested the significantly decreased galactosylation and remarkably increased agalactosylation of IgG1 or IgG2 in the malignant transformation of CRC, which enables the differentiation between cancer patients and healthy controls. The changes of glycan features were elucidated by the exploration of individual glycopeptides, showing the biantennary fucosylated glycan without galactose (H3N4F1) or with two galactose (H5N4F1) of IgG1 and IgG2 could distinguish cancer group from both benign and control groups.

CONCLUSIONS AND CLINICAL RELEVANCE

Through the simple and high-throughput procedures, this study revealed the important role of IgG glycopeptides in the premature pathology of CRC.

Serum N-glycan profiles differ for various breast cancer subtypes

Breast cancer is the most prevalent cancer in women. Early detection of this disease improves survival and therefore population screenings, based on mammography, are performed. However, the sensitivity of this screening modality is not optimal and new screening methods, such as blood tests, are being explored. Most of the analyses that aim for early detection focus on proteins in the bloodstream. In this study, the biomarker potential of total serum N-glycosylation analysis was explored with regard to detection of breast cancer. In an age-matched case-control setup serum protein N-glycan profiles from 145 breast cancer patients were compared to those from 171 healthy individuals. N-glycans were enzymatically released, chemically derivatized to preserve linkage-specificity of sialic acids and characterized by high resolution mass spectrometry. Logistic regression analysis was used to evaluate associations of specific N-glycan structures as well as N-glycosylation traits with breast cancer. In a case-control comparison three associations were found, namely a lower level of a two triantennary glycans and a higher level of one tetraantennary glycan in cancer patients. Of note, various other N-glycomic signatures that had previously been reported were not replicated in the current cohort. It was further evaluated whether the lack of replication of breast cancer N-glycomic signatures could be partly explained by the heterogenous character of the disease since the studies performed so far were based on cohorts that included diverging subtypes in different numbers. It was found that serum N-glycan profiles differed for the various cancer subtypes that were analyzed in this study.

Serum N-glycan profiling as a diagnostic biomarker for the identification and assessment of psoriasis

Background

Glycosylation is an important post‐translational modification of protein. The change in glycosylation is involved in the occurrence and development of various diseases, and this study verified that N‐glycan markers might be a diagnostic marker in psoriasis.

Methods

A total of 76 psoriasis patients were recruited. We used Psoriasis Area Severity Index (PASI) scores to evaluate the state of psoriasis, 41 of whom were divided into three subgroups: mild, moderate, and severe. At the same time, 76 healthy subjects were enrolled as a control group. We used DNA sequencer–assisted fluorophore‐assisted carbohydrate electrophoresis (DSA‐FACE) to analyze serum N‐glycan profiling.

Results

Compared with the healthy controls, the relative abundance of structures in peaks 5(NA2), 9(NA3Fb), 11(NA4), and 12(NA4Fb) was elevated (p < .05), while that in peaks 3(NG1A2F), 4(NG1A2F), 6(NA2F), and 7(NA2FB) was decreased (p < .05) in the psoriasis group. The abundance of peak 5 (NA2) increased gradually with the aggravation of disease severity though there was no statistically significant, was probably correlated with the disease severity. The best area under the receiver operating characteristic (ROC) curve (AUC) of the logistic regression model (PglycoA) to diagnose psoriasis was 0.867, with a sensitivity of 72.37%, a specificity of 85.53%, a positive predictive value(PPV) of 83.33%, a negative predictive value(NPV) of 75.58%, and an accuracy of 78.95%.

Conclusions

Our study indicated that the N‐glycan–based diagnostic model would be a new, valuable, and noninvasive alternative for diagnosing psoriasis. Furthermore, the characteristic distinctive N‐glycan marker might be correlated with the severity gradation of the psoriasis disease.

Automation of Immunoglobulin Glycosylation Analysis

The development of reliable, affordable, high-resolution glycomics technologies that can be used for many samples in a high-throughput manner are essential for both the optimization of glycosylation in the biopharmaceutical industry as well as for the advancement of clinical diagnostics based on glycosylation biomarkers. We will use this chapter to review the sample preparation processes that have been used on liquid-handling robots to obtain high-quality glycomics data for both biopharmaceutical and clinical antibody samples. This will focus on glycoprotein purification, followed by glycan or glycopeptide generation, derivatization and enrichment. The use of liquid-handling robots for glycomics studies on other sample types beyond antibodies will not be discussed here. We will summarize our thoughts on the current status of the field and explore the benefits and challenges associated with developing and using automated platforms for sample preparation. Finally, the future outlook for the automation of glycomics will be discussed along with a projected impact on the field in general.

Chitosan oligosaccharide induces resistance to Pst DC3000 in Arabidopsis via a non-canonical N-glycosylation regulation pattern

Roles of protein N-glycosylation in chitosan oligosaccharide (COS) induced resistance were investigated in the present study. Results demonstrated that N-glycosylation deficient Arabidopsis mutants (stt3a and ManI) were more susceptible against Pseudomonas syringae pv. tomato DC3000 (Pst DC3000) than wild type (WT) plants. Surprisingly, in stt3a and ManI, COS-induced resistance to Pst DC3000 was mostly intact, and the up-regulation effect on SA- and JA-mediated signalling pathways also similar like WT. Nucleotide sugars accumulation and N-glycosylation related genes expression were differently regulated after COS treatment. Global glycomics analysis quantified 157 N-glycan isomers, and 56.7, 50.3 and 47.1 % of them were significantly changed in COS, mock + Pst, and COS + Pst treated plants, respectively. Moreover, COS pretreatment could reverse the effect of Pst DC3000 on many N-glycans, suggesting that COS regulates protein N-glycosylation via a non-canonical pattern compared with plant defense, which may contribute to its obvious disease control effect when N-glycosylation impairment occurs.

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.

Sample Preparation Scale-Up for Deep N-glycomic Analysis of Human Serum by Capillary Electrophoresis and CE-ESI-MS

We introduce an efficient sample preparation workflow to facilitate deep N-glycomics analysis of the human serum by capillary electrophoresis with laser induced fluorescence (CE-LIF) detection and to accommodate the higher sample concentration requirement of electrospray ionization mass spectrometry connected to capillary electrophoresis (CE-ESI-MS). A novel, temperature gradient denaturing protocol was applied on amine functionalized magnetic bead partitioned glycoproteins to circumvent the otherwise prevalent precipitation issue. During this process, the free sugar content of the serum was significantly decreased as well, accommodating enhanced PNGase F mediated release of the N-linked carbohydrates. The liberated oligosaccharides were tagged with aminopyrene-trisulfonate, utilizing a modified evaporative labeling protocol. Processing the samples with this new workflow enabled deep CE-LIF analysis of the human serum N-glycome and provided the appropriate amount of material for CE-ESI-MS analysis in negative ionization mode.

Integrated Transcriptomics, Proteomics, and Glycomics Reveals the Association between Up-regulation of Sialylated N-glycans/Integrin and Breast Cancer Brain Metastasis

Breast cancer brain metastasis has been recognized as one of the central issues in breast cancer research. The elucidation of the processes and pathways that mediate this step will provide important clues for a better understanding of breast cancer metastasis. Increasing evidence suggests that aberrant glycosylation patterns greatly contribute to cell invasion and cancer metastasis. Herein, we combined next-generation RNA sequencing with liquid chromatography-tandem mass spectrometry-based proteomic and N-glycomic analysis from five breast cancer cell lines and one brain cancer cell line to investigate the possible mechanisms of breast cancer brain metastasis. The genes/proteins associated with cell movement were highlighted in breast cancer brain metastasis. The integrin signaling pathway and the up-regulation of α-integrin (ITGA2, ITGA3) were associated with the brain metastatic process. 12 glycogenes showed unique expression in 231BR, which could result in an increase of sialylation during brain metastasis. In agreement with the changes of glycogenes, 60 out of 63 N-glycans that were identified exhibited differential expression among cell lines. The correlation between glycogenes and glycans revealed the importance of sialylation and sialylated glycans in breast cancer brain metastasis. Highly sialylated N-glycans, which were up-regulated in brain-seeking cell line 231BR, likely play a role in 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.

Accelerating research on biological aging and mental health: Current challenges and future directions

Aging is associated with complex biological changes that can be accelerated, slowed, or even temporarily reversed by biological and non-biological factors. This article focuses on the link between biological aging, psychological stressors, and mental illness. Rather than comprehensively reviewing this rapidly expanding field, we highlight challenges in this area of research and propose potential strategies to accelerate progress in this field. This effort requires the interaction of scientists across disciplines - including biology, psychiatry, psychology, and epidemiology; and across levels of analysis that emphasize different outcome measures - functional capacity, physiological, cellular, and molecular. Dialogues across disciplines and levels of analysis naturally lead to new opportunities for discovery but also to stimulating challenges. Some important challenges consist of 1) establishing the best objective and predictive biological age indicators or combinations of indicators, 2) identifying the basis for inter-individual differences in the rate of biological aging, and 3) examining to what extent interventions can delay, halt or temporarily reverse aging trajectories. Discovering how psychological states influence biological aging, and vice versa, has the potential to create novel and exciting opportunities for healthcare and possibly yield insights into the fundamental mechanisms that drive human aging.

Characterization of glycan isomers using magnetic carbon nanoparticles as a MALDI co-matrix

Matrix-assisted laser desorption ionization-in source decay (MALDI-ISD) analysis is a useful technique in the structural analysis of glycans. Our recent publication demonstrated that magnetic carbon nanoparticles (MCNPs), used as a MALDI co-matrix, significantly enhanced ISD efficiency for glycomic analysis by MALDI-TOF. In this study, MCNPs were used for the structural study of isomeric glycans. Results from the standard glycans confirmed easy distinction of positional and linkage isomers without the need for further derivatization of glycan molecules. Extensive glycosidic and cross-ring fragmented ions provided different fragment patterns for various glycan isomers. Core- and branch-fucosylated isomers were distinguished by several unique ions, and pseudo-MS³ data were used to recognize the fucosylated branch. Although no diagnostic fragment ion was observed for 2,3- and 2,6-linked sialic acid isomers, their MALDI-ISD patterns were found to be significantly different (P < 0.05). Furthermore, the method introduced in this study could not only be used for the identification of glycan isomers but has also proved effective for the isomeric structural confirmation of gangliosides. GD1a and GD1b gangliosides were easily distinguished by the diagnostic ion originated from GD1a, produced by Z_4αZ_2β cleavages. Moreover, liquid chromatography coupled with MALDI-TOF was applied to analyze N-glycan isomers derived from a pooled human blood serum sample, providing an alternative method of isomeric glycomic analysis of biological specimens.

Magnetic carbon nanoparticles as a MALDI co-matrix enable isomeric characterization of glycans in biological samples.

Defining the genetic control of human blood plasma N-glycome using genome-wide association study

Glycosylation is a common post-translational modification of proteins. Glycosylation is associated with a number of human diseases. Defining genetic factors altering glycosylation may provide a basis for novel approaches to diagnostic and pharmaceutical applications. Here we report a genome-wide association study of the human blood plasma N-glycome composition in up to 3811 people measured by Ultra Performance Liquid Chromatography (UPLC) technology. Starting with the 36 original traits measured by UPLC, we computed an additional 77 derived traits leading to a total of 113 glycan traits. We studied associations between these traits and genetic polymorphisms located on human autosomes. We discovered and replicated 12 loci. This allowed us to demonstrate an overlap in genetic control between total plasma protein and IgG glycosylation. The majority of revealed loci contained genes that encode enzymes directly involved in glycosylation (FUT3/FUT6, FUT8, B3GAT1, ST6GAL1, B4GALT1, ST3GAL4, MGAT3 and MGAT5) and a known regulator of plasma protein fucosylation (HNF1A). However, we also found loci that could possibly reflect other more complex aspects of glycosylation process. Functional genomic annotation suggested the role of several genes including DERL3, CHCHD10, TMEM121, IGH and IKZF1. The hypotheses we generated may serve as a starting point for further functional studies in this research area.