Lectin microarrays for glycoproteomics: an overview of their use and potential

Ganglioside GM3-based anticancer vaccines: Reviewing the mechanism and current strategies

Ganglioside GM3 is one of the most common membrane-bound glycosphingolipids. The over-expression of GM3 on tumor cells makes it defined as a tumor-associated carbohydrate antigen (TACA). The specific expression property in cancers, especially in melanoma, make it become an important target to develop anticancer vaccines or immunotherapies. However, in the manner akin to most TACAs, GM3 is an autoantigen facing with problems of low immunogenicity and easily inducing immunotolerance, which means itself only cannot elicit a powerful enough immune response to prevent or treat cancer. With a comparative understanding of the mechanisms that how immune system responses to the carbohydrate vaccines, this review summarizes the studies on the recent efforts to development GM3-based anticancer vaccines.

Exploring affinity chromatography in proteomics: A comprehensive review

Over the past decades, the proteomics field has undergone rapid growth. Progress in mass spectrometry and bioinformatics, together with separation methods, has brought many innovative approaches to the study of the molecular biology of the cell. The potential of affinity chromatography was recognized immediately after its first application in proteomics, and since that time, it has become one of the cornerstones of many proteomic protocols. Indeed, this chromatographic technique exploiting the specific binding between two molecules has been employed for numerous purposes, from selective removal of interfering (over)abundant proteins or enrichment of scarce biomarkers in complex biological samples to mapping the post-translational modifications and protein interactions with other proteins, nucleic acids or biologically active small molecules. This review presents a comprehensive survey of this versatile analytical tool in current proteomics. To navigate the reader, the haphazard space of affinity separations is classified according to the experiment's aims and the separated molecule's nature. Different types of available ligands and experimental strategies are discussed in further detail for each of the mentioned procedures.

A Fully Automated Online Enrichment and Separation System for Highly Reproducible and In-Depth Analysis of Intact Glycopeptide

A fully automated online enrichment and separation system for intact glycopeptides, named AutoGP, was developed in this study by integrating three different columns in a nano-LC system. Specifically, the peptide mixture from the enzymatic digestion of a complex biological sample was first loaded on a hydrophilic interaction chromatography (HILIC) column. The nonglycopeptides in the sample were washed off the column, and the glycopeptides retained by the HILIC column were eluted to a C18 trap column to achieve an automated glycopeptide enrichment. The enriched glycopeptides were further eluted to a C18 column for separation, and the separated glycopeptides were eventually analyzed by using an orbitrap mass spectrometer (MS). The optimal operating conditions for AutoGP were systemically studied, and the performance of the fully optimized AutoGP was compared with a conventional manual system used for glycopeptide analysis. The experimental evaluation shows that the total number of glycopeptides identified is at least 1.5-fold higher, and the median coefficient of variation for the analyses is at least 50% lower by using AutoGP, as compared to the results acquired by using the manual system. In addition, AutoGP can perform effective analysis even with a 1-μg sample amount, while a 10-μg sample at least will be needed by the manual system, implying an order of magnitude better sensitivity of AutoGP. All the experimental results have consistently proven that AutoGP can be used for much better characterization of intact glycopeptides.

Machine Learning Reveals Serum Glycopatterns as Potential Biomarkers for the Diagnosis of Nonalcoholic Fatty Liver Disease (NAFLD)

Nonalcoholic fatty liver disease (NAFLD) has emerged as the predominant chronic liver condition globally, and underdiagnosis is common, particularly in mild cases, attributed to the asymptomatic nature and traditional ultrasonography's limited sensitivity to detect early-stage steatosis. Consequently, patients may experience progressive liver pathology. The objective of this research is to ascertain the efficacy of serum glycan glycopatterns as a potential diagnostic biomarker, with a particular focus on the disease's early stages. We collected a total of 170 serum samples from volunteers with mild-NAFLD (Mild), severe-NAFLD (Severe), and non-NAFLD (None). Examination via lectin microarrays has uncovered pronounced disparities in serum glycopatterns identified by 19 distinct lectins. Following this, we employed four distinct machine learning algorithms to categorize the None, Mild, and Severe groups, drawing on the alterations observed in serum glycopatterns. The gradient boosting decision tree (GBDT) algorithm outperformed other models in diagnostic accuracy within the validation set, achieving an accuracy rate of 95% in differentiating the None group from the Mild group. Our research indicates that employing lectin microarrays to identify alterations in serum glycopatterns, when integrated with advanced machine learning algorithms, could constitute a promising approach for the diagnosis of NAFLD, with a special emphasis on its early detection.

Lectins as versatile tools to explore cellular glycosylation

Lectins are naturally occurring carbohydrate-binding proteins that are ubiquitous in nature and highly selective for their, often incompletely characterised, binding partners. From their discovery in the late 1880s to the present day, they have provided a broad palette of versatile tools for exploring the glycosylation of cells and tissues and for uncovering the myriad functions of glycosylation in biological systems. The technique of lectin histochemistry, used to map the glycosylation of tissues, has been instrumental in revealing the changing profile of cellular glycosylation in development, health and disease. It has been especially enlightening in revealing fundamental alterations in cellular glycosylation that accompany cancer development and metastasis, and has facilitated the identification of glycosylated biomarkers that can predict prognosis and may have utility in development of early detection and screening, Moreover, it has led to insights into the functional role of glycosylation in healthy tissues and in the processes underlying disease. Recent advances in biotechnology mean that our understanding of the precise binding partners of lectins is improving and an ever-wider range of lectins are available, including recombinant human lectins and lectins with enhanced, engineered properties. Moreover, use of traditional histochemistry to support a broad range of cutting-edge technologies and the development of high throughout microarray platforms opens the way for ever more sophisticated mapping - and understanding - of the glycome.

Beneficial or detrimental: Recruiting more types of benign cases for cancer diagnosis based on salivary glycopatterns

With the advantages of convenient, painless and non-invasive collection, saliva holds great promise as a valuable biomarker source for cancer detection, pathological assessment and therapeutic monitoring. Salivary glycopatterns have shown significant potential for cancer screening in recent years. However, the understanding of benign lesions at non-cancerous sites in cancer diagnosis has been overlooked. Clarifying the influence of benign lesions on salivary glycopatterns and cancer screening is crucial for advancing the development of salivary glycopattern-based diagnostics. In this study, 2885 samples were analyzed using lectin microarrays to identify variations in salivary glycopatterns according to the number, location, and type of lesions. By utilizing our previously published data of tumor-associated salivary glycopatterns, the performance of machine learning algorithm for cancer screening was investigated to evaluate the effect of adding benign disease cases to the control group. The results demonstrated that both the location and number of lesions had discernible effects on salivary glycopatterns. And it was also revealed that incorporating a broad range of benign diseases into the controls improved the classifier's performance in distinguishing cancer cases from controls. This finding holds guiding significance for enhancing salivary glycopattern-based cancer screening and facilitates their practical implementation in clinical settings.

Structural Analysis and Characterization of an Antiproliferative Lectin from Canavalia villosa Seeds

Cells use glycans to encode information that modulates processes ranging from cell-cell recognition to programmed cell death. This information is encoded within a glycocode, and its decoding is performed by carbohydrate-binding proteins. Among these, lectins stand out due to their specific and reversible interaction with carbohydrates. Changes in glycosylation patterns are observed in several pathologies, including cancer, where abnormal glycans are found on the surfaces of affected tissues. Given the importance of the bioprospection of promising biomolecules, the current work aimed to determine the structural properties and anticancer potential of the mannose-specific lectin from seeds of Canavalia villosa (Cvill). Experimental elucidation of the primary and 3D structures of the lectin, along with glycan array and molecular docking, facilitated the determination of its fine carbohydrate-binding specificity. These structural insights, coupled with the lectin's specificity, have been combined to explain the antiproliferative effect of Cvill against cancer cell lines. This effect is dependent on the carbohydrate-binding activity of Cvill and its uptake in the cells, with concomitant activation of autophagic and apoptotic pathways.

Antidiabetic activity of Tartary buckwheat protein-derived peptide AFYRW and its effects on protein glycosylation of pancreas in mice

Diabetes Mellitus (DM) is one of the most important public health problems, and new antidiabetic drugs with fewer side effects are urgently needed. Here, we measured the antidiabetic effects of an antioxidant peptide (Ala-Phe-Tyr-Arg-Trp, AFYRW) from Tartary Buckwheat Albumin (TBA) in a high-fat diet/streptozotocin (HFD/STZ)-induced diabetic mouse model. The data showed that AFYRW suppressed hepatocyte steatosis and triglycerides while ameliorating insulin resistance in mice. Successively, the influence of AFYRW on aberrant protein glycosylation in diabetic mice was further investigated by lectin microarrays. The results suggested AFYRW could restore the expression of GalNAc, GalNAcα1-3Gal and GalNAcα1-3Galβ1-3/4Glc recognized by PTL-I, Siaα2-3Galβ1-4Glc(NAc)/Glc, Siaα2-3Gal, Siaα2-3 and Siaα2-3GalNAc recognized by MAL-II, terminating in GalNAcα/β1-3/6Gal recognized by WFA and αGalNAc, αGal, anti-A and B recognized by GSI-I to normal levels in the pancreas of HFD-STZ-induced diabetic mice. This work may provide new targets for the future discovery of potential biomarkers to evaluate the efficacy of food-derived antidiabetic drugs based on precise alterations of glycopatterns in DM.

Conventional and advanced detection techniques of foodborne pathogens: A comprehensive review

Foodborne pathogens are a major public health concern and have a significant economic impact globally. From harvesting to consumption stages, food is generally contaminated by viruses, parasites, and bacteria, which causes foodborne diseases such as hemorrhagic colitis, hemolytic uremic syndrome (HUS), typhoid, acute, gastroenteritis, diarrhea, and thrombotic thrombocytopenic purpura (TTP). Hence, early detection of foodborne pathogenic microbes is essential to ensure a safe food supply and to prevent foodborne diseases. The identification of foodborne pathogens is associated with conventional (e.g., culture-based, biochemical test-based, immunological-based, and nucleic acid-based methods) and advances (e.g., hybridization-based, array-based, spectroscopy-based, and biosensor-based process) techniques. For industrial food applications, detection methods could meet parameters such as accuracy level, efficiency, quickness, specificity, sensitivity, and non-labor intensive. This review provides an overview of conventional and advanced techniques used to detect foodborne pathogens over the years. Therefore, the scientific community, policymakers, and food and agriculture industries can choose an appropriate method for better results.

The Blessed Union of Glycobiology and Immunology: A Marriage That Worked

In this article, we discuss the main aspects regarding the recognition of cell surface glycoconjugates and the immunomodulation of responses against the progression of certain pathologies, such as cancer and infectious diseases. In the first part, we talk about different aspects of glycoconjugates and delve deeper into the importance of N-glycans in cancer immunotherapy. Then, we describe two important lectin families that have been very well studied in the last 20 years. Examples include the sialic acid-binding immunoglobulin (Ig)-like lectins (siglecs), and galectins. Finally, we discuss a topic that needs to be better addressed in the field of glycoimmunology: the impact of oncofetal antigens on the cells of the immune system. New findings in this area are of great importance for advancement, especially in the field of oncology, since it is already known that cellular interactions mediated by carbohydrate-carbohydrate and/or carbohydrate proteins are able to modulate the progression of different types of cancer in events that compromise the functionality of the immune responses.

Lectin Histochemistry: Historical Perspectives, State of the Art, and Future Directions

Lectins, discovered more than 100 years ago and defined by their ability to selectively recognize specific carbohydrate structures, are ubiquitous in living organisms. Their precise functions are as yet under-explored and incompletely understood but they are clearly involved, through recognition of their binding partners, in a myriad of biological mechanisms involved in cell identity, adhesion, signaling, and growth regulation in health and disease. Understanding the complex "sugar code" represented by the "glycome" is a major challenge and at the forefront of current biological research. Lectins have been widely employed in histochemical studies to map glycosylation in cells and tissues. Here, a brief history of the discovery of lectins and early developments in their use is presented along with a selection of some of the most interesting and significant discoveries to emerge from the use of lectin histochemistry. Further, an evaluation of the next generation of lectin-based technologies is presented, including the potential for designing recombinant lectins with more precisely defined binding characteristics, linking lectin-based studies with other technologies to answer fundamental questions in glycobiology and approaches to exploring the interactions of lectins with their binding partners in more detail.

Characterization and Function of Glycans on the Spike Proteins of SARS-CoV-2 Variants of Concern

SARS-CoV-2 variants of concern (VOCs) pose a great challenge to viral prevention and treatment owing to spike (S) protein mutations, which enhance their infectivity and capacity for immune evasion. However, whether these S protein mutations affect glycosylation patterns and thereby influence infectivity and immunogenicity remains unclear. In this study, four VOC S proteins-S-Alpha, S-Beta, S-Delta, and S-Omicron-were expressed and purified. Lectin microarrays were performed to characterize their glycosylation patterns. Several glycans were differentially expressed among the four VOC S proteins. Furthermore, the functional examination of glycans differentially expressed on S-Omicron revealed a higher expression of fucose-containing glycans, which modestly increased the binding of S-Omicron to angiotensin converting enzyme 2 (ACE2). A higher abundance of sialic acid and galactose-containing glycan was observed on S-Omicron, which significantly reduced its sensitivity against broad S protein-neutralizing antibodies. These findings contribute to the further understanding of SARS-CoV-2 infection mechanisms and provide novel glycan targets for emerging and future variants of SARS-CoV-2. IMPORTANCE Though glycosylation sites of SARS-CoV-2 S protein remain highly conserved, we confirmed that mutations in the Spike gene affect the S protein glycan expression pattern in different variants. More importantly, we found that glycans were differentially expressed on the S protein of the Omicron variant, enabling different forms of receptor binding and neutralization resistance. This study improves our understanding of SARS-CoV-2 glycomics and glycobiology and provides novel therapeutic and preventive strategies for SARS-CoV-2 VOCs.

Diagnosis of hepatocellular carcinoma based on salivary protein glycopatterns and machine learning algorithms

OBJECTIVES

Hepatocellular carcinoma (HCC) is difficult to diagnose early and progresses rapidly, making it one of the most deadly malignancies worldwide. This study aimed to evaluate whether salivary glycopattern changes combined with machine learning algorithms could help in the accurate diagnosis of HCC.

METHODS

Firstly, we detected the alteration of salivary glycopatterns by lectin microarrays in 118 saliva samples. Subsequently, we constructed diagnostic models for hepatic cirrhosis (HC) and HCC using three machine learning algorithms: Least Absolute Shrinkage and Selector Operation, Support Vector Machine (SVM), and Random Forest (RF). Finally, the performance of the diagnostic models was assessed in an independent validation cohort of 85 saliva samples by a series of evaluation metrics, including area under the receiver operator curve (AUC), accuracy, specificity, and sensitivity.

RESULTS

We identified alterations in the expression levels of salivary glycopatterns in patients with HC and HCC. The results revealed that the glycopatterns recognized by 22 lectins showed significant differences in the saliva of HC and HCC patients and healthy volunteers. In addition, after Boruta feature selection, the best predictive performance was obtained with the RF algorithm for the construction of models for HC and HCC. The AUCs of the RF-HC model and RF-HCC model in the validation cohort were 0.857 (95% confidence interval [CI]: 0.780-0.935) and 0.886 (95% CI: 0.814-0.957), respectively.

CONCLUSIONS

Detecting alterations in salivary protein glycopatterns with lectin microarrays combined with machine learning algorithms could be an effective strategy for diagnosing HCC in the future.

Concanavalin A as a promising lectin-based anti-cancer agent: the molecular mechanisms and therapeutic potential

Concanavalin A (ConA), the most studied plant lectin, has been known as a potent anti-neoplastic agent for a long time. Since initial reports on its capacity to kill cancer cells, much attention has been devoted to unveiling the lectin's exact molecular mechanism. It has been revealed that ConA can bind to several receptors on cancerous and normal cells and modulate the related signaling cascades. The most studied host receptor for ConA is MT1-MMP, responsible for most of the lectin's modulations, ranging from activating immune cells to killing tumor cells. In this study, in addition to studying the effect of ConA on signaling and immune cell function, we will focus on the most up-to-date advancements that unraveled the molecular mechanisms by which ConA can induce autophagy and apoptosis in various cancer cell types, where it has been found that P73 and JAK/STAT3 are the leading players. Moreover, we further discuss the main signaling molecules causing liver injury as the most significant side effect of the lectin injection. Altogether, these findings may shed light on the complex signaling pathways controlling the diverse responses created via ConA treatment, thereby modulating these complex networks to create more potent lectin-based cancer therapy.

High-Throughput Glycomic Methods

Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.

Features, modulation and analysis of glycosylation patterns of therapeutic recombinant immunoglobulin A

Increasing the production of recombinant antibodies while ensuring high and stable protein quality remains a challenge in mammalian cell culture. This review is devoted to advances in the field of obtaining stable and optimal glycosylation of therapeutic antibodies based on IgA, as well as the subsequent issues of glycosylation control of glycoproteins during their production. Current studies also demonstrate a general need for a more fundamental understanding of the use of CHO cell-based producer cell lines, through which the glycoprofile of therapeutic IgA antibodies is produced and the dependence of glycosylation on culture conditions could be controlled. Optimization of glycosylation improves the therapeutic efficacy and can expand the possibilities for the creation of highly effective glycoprotein therapeutic drugs. Current status and trends in glycan analysis of therapeutic IgA, dominantly based on mass spectrometry and lectin microarrays are herein summarised as well.

Machine learning reveals salivary glycopatterns as potential biomarkers for the diagnosis and prognosis of papillary thyroid cancer

The diagnosis of thyroid cancer, especially papillary thyroid cancer (PTC), is increasing rapidly worldwide. In this study, we aimed to study the glycosylation of salivary proteins associated with PTC and assess the likelihood that salivary glycopatterns may be a potential biomarker of PTC diagnosis. Firstly, 22 benign thyroid nodule (BTN) samples, 27 PTC samples, and 30 healthy volunteers (HV) samples were collected to probe the difference of salivary glycopatterns associated with PTC using lectin microarrays. Then, five machine learning models including K-Nearest Neighbor (KNN), Multilayer Perceptron (MLP), Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM) were established to distinguish HV, BTN and PTC based on the changes of salivary glycopatterns. As a result, SVM had the best diagnostic effect with an accuracy rate of 92 % in testing set. Besides, lectin microarrays were used to explore the differences in salivary glycopatterns of 26 paired salivary samples of PTC patients before and after operation in order to probe into salivary glycopatterns as potential biomarkers for prognosis of PTC patients. The results showed that the levels of salivary glycopatterns recognized by 6 different lectins in patients after the operation almost convergenced with HVs. This study could help to screen and assess patients with PTC and their prognosis based on precise changes of salivary glycopatterns.

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.

Glycopattern Alteration of Glycoproteins in Gastrointestinal Cancer Cell Lines and Their Cell-Derived Exosomes

Gastrointestinal (GI) cancers constitute the largest portion of all human cancers, and the most prevalent GI cancers in China are colorectal cancer (CRC), gastric cancer (GC), and hepatocellular carcinoma (HCC). Exosomes are nanosized vesicles containing proteins, lipids, glycans, and nucleic acid, which play important roles in the tumor microenvironment and progression. Aberrant glycosylation is closely associated with GI cancers; however, little is known about the glycopattern of the exosomes from GI cancer cells. In this study, glycopatterns of HCC, CRC, and GC cell lines and their exosomes were detected using lectin microarrays. For all exosomes, (GlcNAcβ1-4)_n and Galβ1-4GlcNAc (DSA) were the most abundant glycans, but αGalNAc and αGal (GSL-II and SBA) were the least. Different cancers had various characteristic glycans in either cells or exosomes. Glycans altered in cell-derived exosomes were not always consistent with the host cells in the same cancer. However, Fucα1-6GlcNAc (core fucose) and Fucα1-3(Galβ1-4)GlcNAc (AAL) were altered consistently in cells and exosomes although they were decreased in HCC and CRC but increased in GC. The study drew the full-scale glycan fingerprint of cells and exosomes related to GI cancer, which may provide useful information for finding specific biomarkers and exploring the underlying mechanism of glycosylation in exosomes.

Abnormal ECA-Binding Membrane Glycans and Galactosylated CAT and P4HB in Lesion Tissues as Potential Biomarkers for Hepatocellular Carcinoma Diagnosis

Hepatocellular carcinoma (HCC) is one of the most common types of cancer. Despite decades of research efforts, the search for novel biomarkers is still urgently needed for the diagnosis of HCC and the improvement of clinical outcomes. Previous studies of HCC clinical biomarkers have usually focused on serum and urine samples (e.g., serum Alpha-fetoprotein (AFP). However, cellular membrane proteins in lesion tissues are less used in HCC diagnosis. The abnormal expression of membrane glycoproteins in tumor lesions are considered as potential targets for tumor diagnosis and tumor therapies. Here, a lectin array has been employed to screen and identify abnormal glycopatterns and cellular membrane glycans in HCC lesion tissues compared with adjacent non-tumor tissues. We found that there was significantly less expression of Erythrina cristagalli (ECA) lectin binding (Galβ1-3/β1-4) glycans on the cellular membrane of HCC lesion tissues compared with those of adjacent non-tumor tissues. Immunohistochemistry analysis further showed that ECA-binding ability on the membrane proteins of HCC tissues progressively decreased in different tumor-node-metastasis (TNM) stages (stage I to stage III) as the malignancy of liver cancer increased. Receiver operating curve (ROC) analysis showed ECA-binding ability yielding a sensitivity of 85% and specificity of 75%, and a combination of ECA and AFP has better clinical diagnostic efficiency, yielding a sensitivity of 90% and specificity of 85%, than ECA or AFP assay alone. ECA pull-down followed by mass spectrometry further showed that there was significantly less expression of ECA binding membrane catalase (CAT) and prolyl 4-hydroxylase beta polypeptide (P4HB) in HCC tissues compared with the adjacent non-tumor tissues. The abnormally increased expression of total CAT and P4HB and decreased expression of galactosylated membrane CAT and P4HB in HCC cell lines were correlated with an HCC metastasis status. Our findings suggest that abnormal declined ECA-binding galatosylated membrane glycans and two galactosylated-CAT and P4HB glycoproteins in lesion tissues are potential biomarkers in the diagnosis and/or metastasis prediction for HCC.

Role of ammonia for brain abnormal protein glycosylation during the development of hepatitis B virus-related liver diseases

Background

Ammonia is the most typical neurotoxin in hepatic encephalopathy (HE), but the underlying pathophysiology between ammonia and aberrant glycosylation in HE remains unknown.

Results

Here, we used HBV transgenic mice and astrocytes to present a systems-based study of glycosylation changes and corresponding enzymes associated with the key factors of ammonia in HE. We surveyed protein glycosylation changes associated with the brain of HBV transgenic mice by lectin microarrays. Upregulation of Galβ1-3GalNAc mediated by core 1 β1,3-galactosyltransferase (C1GALT1) was identified as a result of ammonia stimulation. Using in vitro assays, we validated that upregulation of C1GALT1 is a driver of deregulates calcium (Ca²⁺) homeostasis by overexpression of inositol 1,4,5-trisphosphate receptor type 1 (IP3R1) in astrocytes.

Conclusions

We demonstrated that silencing C1GALT1 could depress the IP3R1 expression, an effective strategy to inhibit the ammonia-induced upregulation of Ca²⁺ activity, thereby C1GALT1 and IP3R1 may serve as therapeutic targets in hyperammonemia of HE.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13578-022-00751-4.

Caveolin-1 knockout mice have altered serum N-glycan profile and sialyltransferase tissue expression

Caveolin-1 (Cav-1) is a constitutive protein within caveolar membranes. Previous studies from our group and others indicated that Cav-1 could mediate N-glycosylation, α2,6-sialylation, and fucosylation in mouse hepatocarcinoma cells in vitro. However, little is known about the effect of Cav-1 expression on glycosylation modifications in vivo. In this study, the N-glycan profiles in serum from Cav-1^-/- mice were investigated by lectin microarray and mass spectrometric analysis approaches. The results showed that levels of multi-antennary branched, α2,6-sialylated, and galactosylated N-glycans increased, while high-mannose typed and fucosylated N-glycans decreased in the serum of Cav-1^-/- mice, compared with that of wild-type mice. Furthermore, the real-time quantitative PCR analysis indicated that α2,6-sialyltransferase gene expression decreased significantly in Cav-1^-/- mouse organ tissues, but α2,3- and α2,8-sialyltransferase did not. Of them, both mRNA and protein expression levels of the β-galactoside α2,6-sialyltransferase 1 (ST6Gal-I) had dramatically reduced in Cav-1^-/- mice organ tissues, which was consistent with the α2,6-sialyl Gal/GalNAc level reduced significantly in tissues instead of serum from Cav-1^-/- mice. These results provide for the first time the N-glycans profile of Cav-1^-/- mice serum, which will facilitate understanding the function of Cav-1 from the perspective of glycosylation.

Comprehensive analysis of glycosphingolipid glycans by lectin microarrays and MALDI-TOF mass spectrometry

Glycosphingolipids (GSLs) are ubiquitous glycoconjugates present on the cell membrane; they play significant roles in many bioprocesses such as cell adhesion, embryonic development, signal transduction and carcinogenesis. Analyzing such amphiphilic molecules is a major challenge in the field of glycosphingolipidomics. We provide a step-by-step protocol that uses a lectin microarray to analyze GSL glycans from cultured cells. The procedure describes (i) extraction of GSLs from cell pellets, (ii) N-monodeacylation using sphingolipid ceramide N-deacylase digestion to form lyso-GSLs, (iii) fluorescence labeling at the newly exposed amine group, (iv) preparation of a lectin microarray, (v) GSL-glycan analysis by a lectin microarray, (vi) complementary mass spectrometry analysis and (vii) data acquisition and analysis. This method is high-throughput, low cost and easy to conduct, and it provides detailed information about glycan linkages. This protocol takes ~10 d.

The Abnormal Glycopatterns of Salivary Glycoproteins in Esophageal Squamous Cell Carcinoma Patients

Glycosylation is one of the most crucial posttranslational modifications of proteins, containing a remarkable amount of biological information. The alteration of glycosylation is closely associated with certain diseases. Exploring glyco-code in the development of diseases is a hot topic in recent years. Esophageal squamous cell carcinoma (ESCC) is the primary pathological histology in developing countries and a severe threat to human health. Although the glycan profiles in the blood samples of ESCC patients were analyzed using glycomic and glycoproteomic methods, the difference of salivary glycopatterns between healthy subjects and ESCC patients is not explicit yet. In the present study, ESCC patients (n = 16) and healthy volunteers (HVs, n = 25) were enrolled. The glycomic strategy combining lectin microarray and lectin blotting was employed to investigate and confirm the altered salivary glycopatterns. Datura stramonium (DSA) was selected to isolate the GlcNAc or Galβ1-4GlcNA-containing glycoproteins due to the distinct difference between ESCC patients and HVs. The N-glycans from DSA-enriched glycoproteins were released by PNGase F and further identified by MALDI-TOF/TOF-MS to obtain the precise structural information of the altered glycans. As a result, the glycopatterns recognized by 13 lectins (e.g., ECA, RCA120, and DSA) showed significant alterations in ESCC patients' saliva. The ESCC patients showed higher levels of GalNAc and Gal, sialic acid, and GlcNAc expression profiles and lower levels of mannose and fucose expression profiles. The MALDI-TOF/TOF-MS results indicated that the proportion of the GlcNAc or Galβ1-4GlcNAc-containing N-glycans was increased in ESCC patients (79.04%) compared with HV (63.20%), which was consistent with the results of lectin microarrays. Our findings provide comprehensive information to understand the complex physiological changes in ESCC patients. And the altered salivary glycopatterns such as GlcNAc or Galβ1-4GlcNAc-containing N-glycans recognized by DSA might serve as potential biomarkers for the diagnosis of ESCC patients.

Analysis of serum glycome by lectin microarrays for prostate cancer patients - a search for aberrant glycoforms

This is the first work focused on glycoprofiling of whole N- and O- glycome using lectins in an array format applied for analysis of serum samples from healthy individuals, benign prostate hyperplasia (BPH) patients, and prostate cancer (PCa) patients. Lectin microarray was prepared using traditional lectins with the incorporation of 2 recombinant bacterial lectins and 3 human lectins (17 lectins in total). Clinical validation of glycans as biomarkers was done in two studies: discrimination of healthy individuals with BPH patients vs. PCa patients (C vs. PCa) and discrimination of healthy individuals vs. BPH and PCa patients (H vs. PCond). Single lectins (17 lectins) and a combination of two lectins (136 binary lectin combinations) were applied in the clinical validation of glycan biomarkers providing 153 AUC values from ROC curves for both studies (C vs. PCa and H vs. PCond). Potential N- and O-glycans as biomarkers were identified and possible carriers of these glycans are shortly discussed.

C-Type Lectins in Veterinary Species: Recent Advancements and Applications

C-type lectins (CTLs), a superfamily of glycan-binding receptors, play a pivotal role in the host defense against pathogens and the maintenance of immune homeostasis of higher animals and humans. CTLs in innate immunity serve as pattern recognition receptors and often bind to glycan structures in damage- and pathogen-associated molecular patterns. While CTLs are found throughout the whole animal kingdom, their ligand specificities and downstream signaling have mainly been studied in humans and in model organisms such as mice. In this review, recent advancements in CTL research in veterinary species as well as potential applications of CTL targeting in veterinary medicine are outlined.

Influence of media composition on recombinant monoclonal IgA1 glycosylation analysed by lectin-based protein microarray and MALDI-MS

Glycosylation of therapeutic glycoproteins significantly affects their physico-chemical properties, bioactivity and immunogenicity. The determination of glycan composition is highly important regarding their development and production. Therefore, there is a demand for analytical techniques enabling rapid and reliable glycoprofiling of therapeutic proteins. For the investigation of changes in glycan structures, we have employed two platforms: lectin-based protein microarray, and MALDI-MS. In lectin-based microarray analysis, the samples of IgA were printed on the microarray slide, incubated with the set of lectins with various specificity and evaluation of changes in glycosylation was based on differences in reactivity of samples with lectins. MALDI-MS was used for N-glycan analysis of IgA1 samples. IgAs are effective as therapeutic agents in defense against viruses that use sialic acid as a receptor. Dimeric IgA1 antibodies were produced by stable cell line IgA1/2G9 on the basal medium at different conditions (different supplementation and feeding) and we also evaluated the effect of different conditions on lactate production, which correlates with IgA productivity. Decrease of lactate levels was observed during supplementation with succinic acid, asparagine, or with mannose feeding. We found by lectin-based microarray analysis that the metabolic shift from glutamine to asparagine or feeding with glucose caused increase of high mannose type glycans what was confirmed also by MALDI-MS. Among other changes in IgA glycosylation determined by lectin-based protein microarray were, for example, reduced galactosylation after supplementation with succinic acid and increase of both sialylation and galactosylation after supplementation with glutamine and feeding with mannose. The elucidation of mechanism of determined changes requires further investigation, but the described analytical approach represent effective platform for determination, screening and evaluation of glycosylation of therapeutic proteins.

Plant lectins and their usage in preparing targeted nanovaccines for cancer immunotherapy

Plant lectins, a natural source of glycans with a therapeutic potential may lead to the discovery of new targeted therapies. Glycans extracted from plant lectins are known to act as ligands for C-type lectin receptors (CLRs) that are primarily present on immune cells. Plant-derived glycosylated lectins offer diversity in their N-linked oligosaccharide structures that can serve as a unique source of homogenous and heterogenous glycans. Among the plant lectins-derived glycan motifs, Man₉GlcNAc₂Asn exhibits high-affinity interactions with CLRs that may resemble glycan motifs of pathogens. Thus, such glycan domains when presented along with antigens complexed with a nanocarrier of choice may bewilder the immune cells and direct antigen cross-presentation - a cytotoxic T lymphocyte immune response mediated by CD8⁺ T cells. Glycan structure analysis has attracted considerable interest as glycans are looked upon as better therapeutic alternatives than monoclonal antibodies due to their cost-effectiveness, reduced toxicity and side effects, and high specificity. Furthermore, this approach will be useful to understand whether the multivalent glycan presentation on the surface of nanocarriers can overcome the low-affinity lectin-ligand interaction and thereby modulation of CLR-dependent immune response. Besides this, understanding how the heterogeneity of glycan structure impacts the antigen cross-presentation is pivotal to develop alternative targeted therapies. In the present review, we discuss the findings on structural analysis of glycans from natural lectins performed using GlycanBuilder2 - a software tool based on a thorough literature review of natural lectins. Additionally, we discuss how multiple parameters like the orientation of glycan ligands, ligand density, simultaneous targeting of multiple CLRs and design of antigen delivery nanocarriers may influence the CLR targeting efficacy. Integrating this information will eventually set the ground for new generation immunotherapeutic vaccine design for the treatment of various human malignancies.