Lectin microarray

Lectin-Based Approaches to Analyze the Role of Glycans and Their Clinical Application in Disease

Lectin-based approaches remain a valuable tool for analyzing glycosylation, especially when detecting cancer-related changes. Certain glycans function as platforms for cell communication, signal transduction, and adhesion. Therefore, the functions of glycans are important considerations for clinical aspects, such as cancer, infection, and immunity. Considering that the three-dimensional structure and multivalency of glycans are important factors for their function, their binding characteristics toward lectins provide vital information. Glycans and lectins are inextricably linked, and studies on lectins have also led to research on the roles of glycans. The applications of lectins are not limited to analysis but can also be used as drug delivery tools. Moreover, mammalian lectins are potential therapeutic targets because certain lectins change their expression in cancer, and lectin regulation subsequently regulates several molecules with glycans. Herein, we review lectin-based approaches for analyzing the role of glycans and their clinical applications in diseases, as well as our recent results.

LeGenD: determining N-glycoprofiles using an explainable AI-leveraged model with lectin profiling

Glycosylation affects many vital functions of organisms. Therefore, its surveillance is critical from basic science to biotechnology, including biopharmaceutical development and clinical diagnostics. However, conventional glycan structure analysis faces challenges with throughput and cost. Lectins offer an alternative approach for analyzing glycans, but they only provide glycan epitopes and not full glycan structure information. To overcome these limitations, we developed LeGenD, a lectin and AI-based approach to predict N-glycan structures and determine their relative abundance in purified proteins based on lectin-binding patterns. We trained the LeGenD model using 309 glycoprofiles from 10 recombinant proteins, produced in 30 glycoengineered CHO cell lines. Our approach accurately reconstructed experimentally-measured N-glycoprofiles of bovine Fetuin B and IgG from human sera. Explanatory AI analysis with SHapley Additive exPlanations (SHAP) helped identify the critical lectins for glycoprofile predictions. Our LeGenD approach thus presents an alternative approach for N-glycan analysis.

Influence of microbiota-driven natural antibodies on dengue transmission

Dengue has had a significant global health impact, with a dramatic increase in incidence over the past 50 years, affecting more than 100 countries. The absence of a specific treatment or widely applicable vaccine emphasizes the urgent need for innovative strategies. This perspective reevaluates current evidence supporting the concept of dual protection against the dengue virus (DENV) through natural antibodies (NAbs), particularly anti-α-Gal antibodies induced by the host's gut microbiome (GM). These anti-α-Gal antibodies serve a dual purpose. Firstly, they can directly identify DENV, as mosquito-derived viral particles have been observed to carry α-Gal, thereby providing a safeguard against human infections. Secondly, they possess the potential to impede virus development in the vector by interacting with the vector's microbiome and triggering infection-refractory states. The intricate interplay between human GM and NAbs on one side and DENV and vector microbiome on the other suggests a novel approach, using NAbs to directly target DENV and simultaneously disrupt vector microbiome to decrease pathogen transmission and vector competence, thereby blocking DENV transmission cycles.

Lectins as potential tools for cancer biomarker discovery from extracellular vesicles

Extracellular vesicles (EVs) have considerable potential as diagnostic, prognostic, and therapeutic agents, in large part because molecular patterns on the EV surface betray the cell of origin and may also be used to "target" EVs to specific cells. Cancer is associated with alterations to cellular and EV glycosylation patterns, and the surface of EVs is enriched with glycan moieties. Glycoconjugates of EVs play versatile roles in cancer including modulating immune response, affecting tumor cell behavior and site of metastasis and as such, paving the way for the development of innovative diagnostic tools and novel therapies. Entities that recognize specific glycans, such as lectins, may thus be powerful tools to discover and detect novel cancer biomarkers. Indeed, the past decade has seen a constant increase in the number of published articles on lectin-based strategies for the detection of EV glycans. This review explores the roles of EV glycosylation in cancer and cancer-related applications. Furthermore, this review summarizes the potential of lectins and lectin-based methods for screening, targeting, separation, and possible identification of improved biomarkers from the surface of EVs.

One, two, many: Strategies to alter the number of carbohydrate binding sites of lectins

Carbohydrates are more than an energy-storage. They are ubiquitously found on cells and most proteins, where they encode biological information. Lectins bind these carbohydrates and are essential for translating the encoded information into biological functions and processes. Hundreds of lectins are known, and they are found in all domains of life. For half a century, researchers have been preparing variants of lectins in which the binding sites are varied. In this way, the traits of the lectins such as the affinity, avidity and specificity towards their ligands as well as their biological efficacy were changed. These efforts helped to unravel the biological importance of lectins and resulted in improved variants for biotechnological exploitation and potential medical applications. This review gives an overview on the methods for the preparation of artificial lectins and complexes thereof and how reducing or increasing the number of binding sites affects their function.

Advances in glycopeptide enrichment methods for the analysis of protein glycosylation over the past decade

Advances in bioanalytical technology have accelerated the analysis of complex protein glycosylation, which is beneficial to understanding glycosylation in drug discovery and disease diagnosis. Due to its biological uniqueness in the course of disease occurrence and development, disease-specific glycosylation requires quantitative characterization of protein glycosylation. We provide a comprehensive review of recent advances in glycosylation analysis, including workflows for glycoprotein digestion, glycopeptide separation and enrichment, and mass-spectrometry sequencing. We specifically focus on different strategies for glycopeptide enrichment through physical interaction, chemical oxidation, or metabolic labeling of intact glycopeptides. The recent advances and challenges of O-glycosylation analysis are presented, and the development of improved enrichment methods combining different proteases to analyze O-glycosylation is also proposed. This article is protected by copyright. All rights reserved.

A Nanopore-Based Saccharide Sensor

Saccharides play critical roles in many forms of cellular activities. Saccharide structures are however complicated and similar, setting a technical hurdle for direct identification. Nanopores, which are emerging single molecule tools sensitive to minor structural differences between analytes, can be engineered to identity saccharides. A hetero-octameric Mycobacterium smegmatis porin A nanopore containing a phenylboronic acid was prepared, and was able to clearly identify nine monosaccharide types, including D-fructose, D-galactose, D-mannose, D-glucose, L-sorbose, D-ribose, D-xylose, L-rhamnose and N-acetyl-D-galactosamine. Minor structural differences between saccharide epimers can also be distinguished. To assist automatic event classification, a machine learning algorithm was developed, with which a general accuracy score of 0.96 was achieved. This sensing strategy is generally suitable for other saccharide types and may bring new insights to nanopore saccharide sequencing.

Lectins applied to diagnosis and treatment of prostate cancer and benign hyperplasia: A review

Environmental factors, as well as genetic factors, contribute to the increase in prostate cancer cases (PCa), the second leading cause of cancer death in men. This fact calls for the development of more reliable, quick and low-cost early detection tests to distinguish between malignant and benign cases. Abnormal cell glycosylation pattern is a promising PCa marker for this purpose. Proteins, such as lectins can decode the information contained in the glycosylation patterns. Several studies have reported on applications of plant lectins as diagnostic tools for PCa considering the ability to differentiate it from benign cases. In addition, they can be used to detect, separate and differentiate the glycosylation patterns of cells or proteins present in serum, urine and semen. Herein, we present an overview of these studies, showing the lectins that map glycans differentially expressed in PCa, as well as benign hyperplasia (BPH). We further review their applications in biosensors, histochemical tests, immunoassays, chromatography, arrays and, finally, their therapeutic potential. This is the first study to review vegetable lectins applied specifically to PCa.

Systematic review on lectin-based electrochemical biosensors for clinically relevant carbohydrates and glycoconjugates

Carbohydrates and glycoconjugates are involved in numerous natural and pathological metabolic processes, and the precise elucidation of their biochemical functions has been supported by smart technologies assembled with lectins, i.e., ubiquitous proteins of nonimmune origin with carbohydrate-specific domains. When lectins are anchored on suitable electrochemical transducers, sensitive and innovative bioanalytical tools (lectin-based biosensors) are produced, with the ability to screen target sugars at molecular levels. In addition to the remarkable electroanalytical sensitivity, these devices associate specificity, precision, stability, besides the possibility of miniaturization and portability, which are special features required for real-time and point-of-care measurements. The mentioned attributes can be improved by combining lectins with biocompatible 0-3D semiconductors derived from carbon, metal nanoparticles, polymers and their nanocomposites, or employing labeled biomolecules. This systematic review aims to substantiate and update information on the progress made with lectin-based biosensors designed for electroanalysis of clinically relevant carbohydrates and glycoconjugates (glycoproteins, pathogens and cancer biomarkers), highlighting their main detection principles and performance in highly complex biological milieus. Moreover, particular emphasis is given to the main advantages and limitations of the reported devices, as well as the new trends for the current demands. We believe that this review will support and encourage more cutting-edge research involving lectin-based electrochemical biosensors.

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.

Protein glycosylation in extracellular vesicles: Structural characterization and biological functions

Extracellular vesicles (EVs) are lipid bilayer-enclosed particles involved in intercellular communication, delivery of biomolecules from donor to recipient cells, cellular disposal and homeostasis, potential biomarkers and drug carriers. The content of EVs includes DNA, lipids, metabolites, proteins, and microRNA, which have been studied in various diseases, such as cancer, diabetes, pregnancy, neurodegenerative, and cardiovascular disorders. EVs are enriched in glycoconjugates and exhibit specific glycosignatures. Protein glycosylation is a co- and post-translational modification (PTM) that plays an important role in the expression and function of exosomal proteins. N- and O-linked protein glycosylation has been mapped in exosomal proteins. The purpose of this review is to highlight the importance of glycosylation in EVs proteins. Initially, we describe the main PTMs in EVs with a focus on glycosylation. Then, we explore glycan-binding proteins describing the main findings of studies that investigated the glycosylation of EVs in cancer, pregnancy, infectious diseases, diabetes, mental disorders, and animal fluids. We have highlighted studies that have developed innovative methods for studying the content of EVs. In addition, we present works related to lipid glycosylation. We explored the content of studies deposited in public databases, such as Exocarta and Vesiclepedia. Finally, we discuss analytical methods for structural characterization of glycoconjugates and present an overview of the critical points of the study of glycosylation EVs, as well as perspectives in this field.

Searching for the sweet spot of amoebic gill disease of farmed Atlantic salmon: the potential role of glycan-lectin interactions in the adhesion of Neoparamoeba perurans

One of the first critical steps in the pathogenesis of amoebic gill disease (AGD) of farmed salmon is the adhesion of the causative amoeba to the host. The current study aimed to investigate the potential involvement of glycan-binding proteins expressed on the extracellular surface of Neoparamoeba perurans in gill tissue recognition and binding. The glycan-binding properties of the surface membrane of N. perurans and the carbohydrate binding profile of Atlantic salmon gill-derived epithelial cells were identified through the use of glycan and lectin microarrays, respectively. The occurrence of specific carbohydrate-mediated binding was then further assessed by in vitro attachment assays using microtitre plates pre-coated with the main glycan candidates. Adhesion assays were also performed in the presence of exogenous saccharides with the aim of blocking glycan-specific binding activity. Comparative analysis of the results from both lectin and glycan arrays showed significant overlap, as some glycans to which binding by the amoeba was seen were reflected as being present on the gill epithelial cells. The two main candidates proposed to be involved in amoeba attachment to the gills are mannobiose and N-acetylgalactosamine (GalNAc). Adhesion of amoebae significantly increased by 33.5 and 23% when cells were added to α1,3-Mannobiose-BSA and GalNAc-BSA coated plates. The observed increased in attachment was significantly reduced when the amoebae were incubated with exogenous glycans, further demonstrating the presence of mannobiose- and GalNAc-binding sites on the surfaces of the cells. We believe this study provides the first evidence for the presence of a highly specific carbohydrate recognition and binding system in N. perurans. These preliminary findings could be of extreme importance given that AGD is an external parasitic infestation and much of the current research on the development of alternative treatment strategies relies on either instant amoeba detachment or blocking parasite attachment.

Identification of Cancerlectins By Using Cascade Linear Discriminant Analysis and Optimal g-gap Tripeptide Composition

Background:

Lectins are a diverse group of glycoproteins or glycoconjugate proteins that can be extracted from plants, invertebrates and higher animals. Cancerlectins, a kind of lectins, which play a key role in the process of tumor cells interacting with each other and are being employed as therapeutic agents. A full understanding of cancerlectins is significant because it provides a tool for the future direction of cancer therapy.

Objective:

To develop an accurate and practically useful timesaving tool to identify cancerlectins. A novel sequence-based method is proposed along with a correlative webserver to access the proposed tool.

Methods:

Firstly, protein features were extracted in a newly feature building way termed, g-gap tripeptide composition. After which a proposed cascade linear discriminant analysis (Cascade LDA) is used to alleviate the high dimensional difficulties with the Analysis Of Variance (ANOVA) as a feature importance criterion. Finally, Support Vector Machine (SVM) is used as the classifier to identify cancerlectins.

Results:

The proposed method achieved an accuracy of 91.34% with sensitivity of 89.89%, specificity of 92.48% and an 0.8318 Mathew’s correlation coefficient based on only 13 fusion features in jackknife cross validation, the result of which is superior to other published methods in this domain.

Conclusion:

In this study, a new method based only on primary structure of protein is proposed and experimental results show that it could be a promising tool to identify cancerlectins. An openaccess webserver is made available in this work to facilitate other related works.

Seizure protein 6 controls glycosylation and trafficking of kainate receptor subunits GluK2 and GluK3

Seizure protein 6 (SEZ6) is required for the development and maintenance of the nervous system, is a major substrate of the protease BACE1 and is linked to Alzheimer's disease (AD) and psychiatric disorders, but its molecular functions are not well understood. Here, we demonstrate that SEZ6 controls glycosylation and cell surface localization of kainate receptors composed of GluK2/3 subunits. Loss of SEZ6 reduced surface levels of GluK2/3 in primary neurons and reduced kainate-evoked currents in CA1 pyramidal neurons in acute hippocampal slices. Mechanistically, loss of SEZ6 in vitro and in vivo prevented modification of GluK2/3 with the human natural killer-1 (HNK-1) glycan, a modulator of GluK2/3 function. SEZ6 interacted with GluK2 through its ectodomain and promoted post-endoplasmic reticulum transport of GluK2 in the secretory pathway in heterologous cells and primary neurons. Taken together, SEZ6 acts as a new trafficking factor for GluK2/3. This novel function may help to better understand the role of SEZ6 in neurologic and psychiatric diseases.

Establishment of a 1, 4, 7, 10-tetraazacyclododecane-1,4,7,10-tetraacetic acid mono-N-hydroxysuccinimide ester (DOTA-NHS-ester) based lectin microarray for efficiently detecting serum glycans in gastric cancers

Development of cancers is involved in changes of a variety of glycans. Lectin microarray is one of the most powerful methodologies for investigation of glycan alterations in biological samples with its advantages of high through-put, selectivity and specificity of the technique. However, utilization of lectin microarrays available commercially keeps of great challenges. In this study, we took use of the molecular self-assembled monolayer technique to modify a gold surface with the reagent 1,4,7,10-tetraazacyclododecane- 1,4,7,10-tetraacetic acid mono-N-hydroxysuccinimide ester (DOTA-NHS-ester) in combination with 16-amino-1-hexadecanethiol hydrochloride. Cross-linking effect of DOTA-NHS-ester is brought about via activating three -OH ends to three terminals of succinylimidines, making selective binding of the terminal amino groups in proteins possible. We immobilized ten commercial lectins on the platform and measured changes of serum lectin-matched glycans in patients with gastric cancer. The results demonstrated that this biochip modification platform conferred impressive chemical surface stabilization, sensitivity and geometric images. We observed that all the serum glycans tested in the patients were significantly higher than those in the controls (P < 0.05). The biochip would provide a versatile platform for investigation of potential glycan biomarkers in making tumor diagnosis decision and analyzing escape of tumors from immunity.

Application of Lectin Microarrays for Biomarker Discovery

Many proteins in living organisms are glycosylated. As their glycan patterns exhibit protein-, cell-, and tissue-specific heterogeneity, changes in the glycosylation levels could serve as useful indicators of various pathological and physiological states. Thus, the identification of glycoprotein biomarkers from specific changes in the glycan profiles of glycoproteins is a trending field. Lectin microarrays provide a new glycan analysis platform, which enables rapid and sensitive analysis of complex glycans without requiring the release of glycans from the protein. Recent developments in lectin microarray technology enable high-throughput analysis of glycans in complex biological samples. In this review, we will discuss the basic concepts and recent progress in lectin microarray technology, the application of lectin microarrays in biomarker discovery, and the challenges and future development of this technology. Given the tremendous technical advancements that have been made, lectin microarrays will become an indispensable tool for the discovery of glycoprotein biomarkers.

Characterization of a Novel Mannose-Binding Lectin with Antiviral Activities from Red Alga, Grateloupia chiangii

Lectins have the ability to bind specific carbohydrates and they have potential applications as medical and pharmacological agents. The unique structure and usefulness of red algal lectin have been reported, but these lectins are limited to a few marine algal groups. In this study, a novel mannose-binding lectin from Grateloupia chiangii (G. chiangii lectin, GCL) was purified using antiviral screens and affinity chromatography. We characterized the molecular weight, agglutination activity, hemagglutination activity, and heat stability of GCL. To determine the carbohydrate specificity, a glycan microarray was performed. GCL showed strong binding affinity for Maltohexaose-β-Sp1 and Maltoheptaose-β-Sp1 with weak affinity for other monosaccharides and preferred binding to high-mannan structures. The N-terminal sequence and peptide sequence of GCL were determined using an Edman degradation method and LC-MS/MS, and the cDNA and peptide sequences were deduced. GCL was shown to consist of 231 amino acids (24.9 kDa) and the N-terminus methionine was eliminated after translation. GCL possessed a tandem repeat structure of six domains, similar to the other red algal lectins. The mannose binding properties and tandem repeat structure of GCL may confer it the potential to act as an antiviral agent for protection against viral infection.

Advancing Solutions to the Carbohydrate Sequencing Challenge

Carbohydrates possess a variety of distinct features with stereochemistry playing a particularly important role in distinguishing their structure and function. Monosaccharide building blocks are defined by a high density of chiral centers. Additionally, the anomericity and regiochemistry of the glycosidic linkages carry important biological information. Any carbohydrate-sequencing method needs to be precise in determining all aspects of this stereodiversity. Recently, several advances have been made in developing fast and precise analytical techniques that have the potential to address the stereochemical complexity of carbohydrates. This perspective seeks to provide an overview of some of these emerging techniques, focusing on those that are based on NMR and MS-hybridized technologies including ion mobility spectrometry and IR spectroscopy.

Lectin biosensors in cancer glycan biomarker detection

Cancer has high incidence and it will continue to increase over the next decades. Detection and quantification of cancer-associated biomarkers is frequently carried out for diagnosis, prognosis and treatment monitoring at various disease stages. It is well-known that glycosylation profiles change significantly during oncogenesis. Aberrant glycans produced during tumorigenesis are, therefore, valuable molecules for detection and characterization of cancer, and for therapeutic design and monitoring. Although glycoproteomics has benefited from the development of analytical tools such as high performance liquid chromatography, two-dimensional gel and capillary electrophoresis and mass spectrometry, these approaches are not well suited for rapid point-of-care (POC) testing easily performed by medical staff. Lectins are biomolecules found in nature with specific affinities toward particular glycan structures and bind them thus forming a relatively strong complex. Because of this characteristic, lectins have been used in analytical techniques for the selective capture or separation of certain glycans in complex samples, namely, in lectin affinity chromatography, or to characterize glycosylation profiles in diverse clinical situations, using lectin microarrays. Lectin-based biosensors have been developed for the detection of specific aberrant and cancer-associated glycostructures to aid diagnosis, prognosis and treatment assessment of these patients. The attractive features of biosensors, such as portability and simple use make them highly suitable for POC testing. Recent developments in lectin biosensors, as well as their potential and pitfalls in cancer glycan biomarker detection, are presented in this chapter.

Identification of Critical Surface Parameters Driving Lectin-Mediated Capture of Bacteria from Solution

Lectin-functional interfaces are useful for isolation of bacteria from solution because they are low-cost and allow nondestructive, reversible capture. This study provides a systematic investigation of physical and chemical surface parameters that influence bacteria capture over lectin-functionalized polymer interfaces and then applies these findings to construct surfaces with significantly enhanced bacteria capture. The designer block copolymer poly(glycidyl methacrylate)- block-poly(vinyldimethyl azlactone) was used as a lectin attachment layer, and lectin coupling into the polymer film through azlactone-lectin coupling reactions was first characterized. Here, experimental parameters including polymer areal chain density, lectin molecular weight, and lectin coupling buffer were systematically varied to identify parameters driving highest azlactone conversions and corresponding lectin surface densities. To introduce physical nanostructures into the attachment layer, nanopillar arrays (NPAs) of varied heights (300 and 2100 nm) were then used to provide an underlying surface template for the functional polymer layer. Capture of Escherichia coli on lectin-polymer surfaces coated over both flat and NPA surfaces was then investigated. For flat polymer interfaces, bacteria were detected on the surface after incubation at a solution concentration of 10³ cfu/mL, and a corresponding detection limit of 1.7 × 10³ cfu/mL was quantified. This detection limit was 1 order of magnitude lower than control lectin surfaces functionalized with standard, carbodiimide coupling chemistry. NPA surfaces containing 300 nm tall pillars further improved the detection limit to 2.1 × 10² cfu/mL, but also reduced the viability of captured cells. Finally, to investigate the impact of cell surface parameters on capture, we used Agrobacterium tumefaciens cells genetically modified to allow manipulation of exopolysaccharide adhesin production levels. Statistical analysis of surface capture levels revealed that lectin surface density was the primary factor driving capture, as opposed to exopolysaccharide adhesin expression. These findings emphasize the critical importance of the synthetic interface and the development of surfaces that combine high lectin densities with tailored physical features to drive high levels of capture. These insights will aid in design of biofunctional interfaces with physicochemical surface properties favorable for capture and isolation of bacteria cells from solutions.

A Golgi-associated redox switch regulates catalytic activation and cooperative functioning of ST6Gal-I with B4GalT-I

Glycosylation, a common modification of cellular proteins and lipids, is often altered in diseases and pathophysiological states such as hypoxia, yet the underlying molecular causes remain poorly understood. By utilizing lectin microarray glycan profiling, Golgi pH and redox screens, we show here that hypoxia inhibits terminal sialylation of N- and O-linked glycans in a HIF- independent manner by lowering Golgi oxidative potential. This redox state change was accompanied by loss of two surface-exposed disulfide bonds in the catalytic domain of the α-2,6-sialyltransferase (ST6Gal-I) and its ability to functionally interact with B4GalT-I, an enzyme adding the preceding galactose to complex N-glycans. Mutagenesis of selected cysteine residues in ST6Gal-I mimicked these effects, and also rendered the enzyme inactive. Cells expressing the inactive mutant, but not those expressing the wild type ST6Gal-I, were able to proliferate and migrate normally, supporting the view that inactivation of the ST6Gal-I help cells to adapt to hypoxic environment. Structure comparisons revealed similar disulfide bonds also in ST3Gal-I, suggesting that this O-glycan and glycolipid modifying sialyltransferase is also sensitive to hypoxia and thereby contribute to attenuated sialylation of O-linked glycans in hypoxic cells. Collectively, these findings unveil a previously unknown redox switch in the Golgi apparatus that is responsible for the catalytic activation and cooperative functioning of ST6Gal-I with B4GalT-I.

Lectin microarray and mass spectrometric analysis of hepatitis C proteins reveals N-linked glycosylation

We used lectin microarray and mass spectrometric analysis to identify the N-linked glycosylation patterns of hepatitis C virus (HCV) particles. HCV J6/JFH-1 chimeric cell culture (HCVcc) in the culture supernatant was concentrated and purified by ultrafiltration and sucrose gradient ultracentrifugation. Twelve fractions were collected from the top and analyzed for viral infectivity and HCV RNA content after sucrose gradient separation. HCV RNA and proteins were separated by ultracentrifugation in a continuous 10% to 60% sucrose gradient to purify viral particles based on their sedimentation velocities. HCVcc particles were found mainly in fractions 6 to 8, as determined by quantitative polymerase chain reaction (qPCR) analysis for HCV RNA and ELISA of the HCV core protein. The N-glycans on HCV proteins were analyzed by lectin microarray and mass spectrometry. We identified that 32 of 37 lectins displayed the positive binding signals and 16 types of N-glycoforms of which the major HCV glycoforms were high mannose-type N-linked oligosaccharides, hybrid N-glycans, and fucosylated N-glycans. Our study provided new detailed information regarding the majority of the glycan-protein profile, complementing to previous findings of glycan-HCV protein interactions.

A Two-Step Feature Selection Method to Predict Cancerlectins by Multiview Features and Synthetic Minority Oversampling Technique

Cancerlectins have an inhibitory effect on the growth of cancer cells and are currently being employed as therapeutic agents. The accurate identification of the cancerlectins should provide insight into the molecular mechanisms of cancers. In this study, a new computational method based on the RF (Random Forest) algorithm is proposed for further improving the performance of identifying cancerlectins. Hybrid feature space before feature selection is developed by combining different individual feature spaces, CTD (Composition, Transition, and Distribution), PseAAC (Pseudo Amino Acid Composition), PSSM (Position-Specific Scoring Matrix), and disorder. The SMOTE (Synthetic Minority Oversampling Technique) is applied to solve the imbalanced data problem. To reduce feature redundancy and computation complexity, we propose a two-step feature selection process to select informative features. A 5-fold cross-validation technique is used for the evaluation of various prediction strategies. The proposed method achieves a sensitivity of 0.779, a specificity of 0.717, an accuracy of 0.748, and an MCC (Matthew's Correlation Coefficient) of 0.497. The prediction results are also compared with other existing methods on the same dataset using 5-fold cross-validation. The comparison results demonstrate the high effectiveness of our method for predicting cancerlectins.

Vitronectin (Vn) glycosylation patterned by lectin affinity assays-A potent glycoproteomic tool to discriminate plasma Vn from cancer ascites Vn

Changes in glycosylation have been associated with human cancer, but their complexity poses an analytical challenge. Ovarian cancer is a major cause of death in women because of an often late diagnosis. At least one-third of patients presents ascites fluid at diagnosis, and almost all have ascites at recurrence. Vitronectin (Vn) is a multifunctional glycoprotein that is suggested to be implicated in ovarian cancer metastasis and is found within ascites. The present study evaluated the potential of using lectin affinity for characterizing the glycosylation pattern of Vn. Human Vn was purified from 1 sample of ovarian cancer ascites or a pool of plasma samples. Consistent findings were observed with both dot blot and lectin array assays. Based on a panel of 40 lectins, the lectin array revealed discriminant patterns of lectin binding to Vn glycans. Interestingly, almost all the highlighted interactions were found to be higher with Vn from ascites relative to the plasma counterpart. Also, the lectin array was able to discriminate profiles of lectin interactions (ConA, SNA-I, PHA-E, PHA-L) between Vn samples that were not evident using dot blot, indicating its high sensitivity. The model of ConA binding during thermal unfolding of Vn confirmed the higher accessibility of mannosylated glycans in Vn from ascites as monitored by turbidimetry. Thus, this study demonstrated the usefulness of lectins and the lectin array as a glycoproteomic tool for high throughput and sensitive analysis of glycosylation patterns. Our data provide novel insights concerning Vn glycosylation patterns in clinical specimens, paving the way for further investigations regarding their functional impact and clinical interest.

Lectins: an effective tool for screening of potential cancer biomarkers

In recent years, the use of lectins for screening of potential biomarkers has gained increased importance in cancer research, given the development in glycobiology that highlights altered structural changes of glycans in cancer associated processes. Lectins, having the properties of recognizing specific carbohydrate moieties of glycoconjugates, have become an effective tool for detection of new cancer biomarkers in complex bodily fluids and tissues. The specificity of lectins provides an added advantage of selecting peptides that are differently glycosylated and aberrantly expressed in cancer patients, many of which are not possibly detected using conventional methods because of their low abundance in bodily fluids. When coupled with mass spectrometry, research utilizing lectins, which are mainly from plants and fungi, has led to identification of numerous potential cancer biomarkers that may be used in the future. This article reviews lectin-based methods that are commonly adopted in cancer biomarker discovery research.

Glycopatterns of Urinary Protein as New Potential Diagnosis Indicators for Diabetic Nephropathy

Diabetic nephropathy is a major cause of chronic kidney disease and end-stage kidney disease. However, so little is known about alterations of the glycopatterns in urine with the development of diabetic nephropathy. Presently, we interrogated glycopatterns in urine specimens using a lectin microarray. The results showed that expression levels of Siaα2-6Gal/GalNAc recognized by SNA exhibited significantly increased tendency with the development of diabetic nephropathy; moreover, SNA blotting indicated glycoproteins (90 kDa, 70 kDa, and 40 kDa) in urine may contribute to this alteration. Furthermore, the glycopatterns of (GlcNAc)_2-4 recognized by STL exhibited difference between diabetic and nondiabetic nephropathy. The results of urinary protein microarray fabricated by another 48 urine specimens also indicated (GlcNAc)_2-4 is a potential indictor to differentiate the patients with diabetic nephropathy from nondiabetic nephropathy. Furtherly, STL blotting showed that the 50 kDa glycoproteins were correlated with this alteration. In conclusion, our data provide pivotal information to monitor the development of diabetic nephropathy and distinguish between diabetic nephropathy and nondiabetic renal disease based on precise alterations of glycopatterns in urinary proteins, but further studies are needed in this regard.

Identification of sperm equatorial segment protein 1 in the acrosome as the primary binding target of peanut agglutinin (PNA) in the mouse testis

Peanut agglutinin (PNA), a plant lectin protein that recognizes the galactose β (1 -> 3) N-acetylgalactosamine carbohydrate sequence, has been widely used as a sperm acrosome-specific marker; however, the acrosomal glycoproteins that specifically bind to PNA have yet to be identified. We herein purified and identified PNA-binding glycoproteins in the mouse testis using biotinylated PNA and streptavidin-coupled magnetic beads, and liquid chromatography-tandem mass spectrometry (LC-MS/MS), respectively. In six repeated experiments, sperm equatorial segment protein 1 (SPESP1) was detected most frequently as a PNA-binding glycoprotein, followed by dipeptidase 3, proacrosin-binding protein, and acrosin prepropeptide. The identification of SPEPS1 in the testis lysate and its PNA-bound fraction was verified with lectin and Western blot analyses, and the co-localization of PNA and SPEPS1 in acrosomes was confirmed with lectin- and immunohistochemistry. Since the PNA reactivity of sperm acrosomes was observed not only in normal mice, but also in SPESP1-deficient mice, although at lower levels, PNA was also considered to bind to other candidate glycoproteins. The present study identified SPESP1 in the acrosome as the primary binding target of PNA in the mouse testis. Further defining the specific lectin-glycoprotein relationships in individual cells will enhance the value of lectin histochemistry.

Current landscape of protein glycosylation analysis and recent progress toward a novel paradigm of glycoscience research

This review covers the basics and some applications of methodologies for the analysis of glycoprotein glycans. Analytical techniques used for glycoprotein glycans, including liquid chromatography (LC), capillary electrophoresis (CE), mass spectrometry (MS), and high-throughput analytical methods based on microfluidics, were described to supply the essentials about biopharmaceutical and biomarker glycoproteins. We will also describe the MS analysis of glycoproteins and glycopeptides as well as the chemical and enzymatic releasing methods of glycans from glycoproteins and the chemical reactions used for the derivatization of glycans. We hope the techniques have accommodated most of the requests from glycoproteomics researchers.

Binding Cooperativity Matters: A GM1-Like Ganglioside-Cholera Toxin B Subunit Binding Study Using a Nanocube-Based Lipid Bilayer Array

Protein-glycan recognition is often mediated by multivalent binding. These multivalent bindings can be further complicated by cooperative interactions between glycans and individual glycan binding subunits. Here we have demonstrated a nanocube-based lipid bilayer array capable of quantitatively elucidating binding dissociation constants, maximum binding capacity, and binding cooperativity in a high-throughput format. Taking cholera toxin B subunit (CTB) as a model cooperativity system, we studied both GM₁ and GM₁-like gangliosides binding to CTB. We confirmed the previously observed CTB-GM₁ positive cooperativity. Surprisingly, we demonstrated fucosyl-GM₁ has approximately 7 times higher CTB binding capacity than GM₁. In order to explain this phenomenon, we hypothesized that the reduced binding cooperativity of fucosyl-GM₁ caused the increased binding capacity. This was unintuitive, as GM₁ exhibited higher binding avidity (16 times lower dissociation constant). We confirmed the hypothesis using a theoretical stepwise binding model of CTB. Moreover, by taking a mixture of fucosyl-GM₁ and GM₂, we observed the mild binding avidity fucosyl-GM₁ activated GM₂ receptors enhancing the binding capacity of the lipid bilayer surface. This was unexpected as GM₂ receptors have negligible binding avidity in pure GM₂ bilayers. These unexpected discoveries demonstrate the importance of binding cooperativity in multivalent binding mechanisms. Thus, quantitative analysis of multivalent protein-glycan interactions in heterogeneous glycan systems is of critical importance. Our user-friendly, robust, and high-throughput nanocube-based lipid bilayer array offers an attractive method for dissecting these complex mechanisms.

Role of lectin microarrays in cancer diagnosis

The majority of cell differentiation associated tumor markers reported to date are either glycoproteins or glycolipids. Despite there being a large number of glycoproteins reported as candidate markers for various cancers, only a handful are approved by the US Food and Drug Administration. Lectins, which bind to the glycan part of the glycoproteins, can be exploited to identify aberrant glycosylation patterns, which in turn would help in enhancing the specificity of cancer diagnosis. Although conventional techniques such as HPLC and MS have been instrumental in performing the glycomic analyses, these techniques lack multiplexity. Lectin microarrays have proved to be useful in studying multiple lectin-glycan interactions in a single experiment and, with the advances made in the field, hold a promise of enabling glycomic profiling of cancers in a fast and efficient manner.

Glycoarray Technologies: Deciphering Interactions from Proteins to Live Cell Responses

Microarray technologies inspired the development of carbohydrate arrays. Initially, carbohydrate array technology was hindered by the complex structures of glycans and their structural variability. The first designs of glycoarrays focused on the HTP (high throughput) study of protein-glycan binding events, and subsequently more in-depth kinetic analysis of carbohydrate-protein interactions. However, the applications have rapidly expanded and now achieve successful discrimination of selective interactions between carbohydrates and, not only proteins, but also viruses, bacteria and eukaryotic cells, and most recently even live cell responses to immobilized glycans. Combining array technology with other HTP technologies such as mass spectrometry is expected to allow even more accurate and sensitive analysis. This review provides a broad overview of established glycoarray technologies (with a special focus on glycosaminoglycan applications) and their emerging applications to the study of complex interactions between glycans and whole living cells.

Predicting cancerlectins by the optimal g-gap dipeptides

The cancerlectin plays a key role in the process of tumor cell differentiation. Thus, to fully understand the function of cancerlectin is significant because it sheds light on the future direction for the cancer therapy. However, the traditional wet-experimental methods were money- and time-consuming. It is highly desirable to develop an effective and efficient computational tool to identify cancerlectins. In this study, we developed a sequence-based method to discriminate between cancerlectins and non-cancerlectins. The analysis of variance (ANOVA) was used to choose the optimal feature set derived from the g-gap dipeptide composition. The jackknife cross-validated results showed that the proposed method achieved the accuracy of 75.19%, which is superior to other published methods. For the convenience of other researchers, an online web-server CaLecPred was established and can be freely accessed from the website http://lin.uestc.edu.cn/server/CalecPred. We believe that the CaLecPred is a powerful tool to study cancerlectins and to guide the related experimental validations.

Development and Applications of Lectins as Biological Tools in Biomedical Research

As a new and burgeoning area following genomics and proteomics, glycomics has become a hot issue due to its pivotal roles in many physiological and pathological processes. Glycans are much more complicated than genes or proteins since glycans are highly branched and dynamic. Antibodies and lectins are the two major molecular tools applied for glycan profiling. Though the study of antibodies and lectins started at almost the same time in 1880s, lectins gained much less attention than the antibodies until recent decades when the importance and difficulties of glycomics were realized. The present review summarizes the discovery history of lectins and their biological functions with a special emphasis on their various applications as biological tools. Both older techniques that had been developed in the last century and new technologies developed in recent years, especially lectin microarrays and lectin-based biosensors, are included in this account.

Characterization of N-Glycan Structures on the Surface of Mature Dengue 2 Virus Derived from Insect Cells

DENV envelope glycoprotein (E) is responsible for interacting with host cell receptors and is the main target for the development of a dengue vaccine based on an induction of neutralizing antibodies. It is well known that DENV E glycoprotein has two potential N-linked glycosylation sites at Asn67 and Asn153. The N-glycans of E glycoprotein have been shown to influence the proper folding of the protein, its cellular localization, its interactions with receptors and its immunogenicity. However, the precise structures of the N-glycans that are attached to E glycoprotein remain elusive, although the crystal structure of DENV E has been determined. This study characterized the structures of envelope protein N-linked glycans on mature DENV-2 particles derived from insect cells via an integrated method that used both lectin microarray and MALDI-TOF-MS. By combining these methods, a high heterogeneity of DENV N-glycans was found. Five types of N-glycan were identified on DENV-2, including mannose, GalNAc, GlcNAc, fucose and sialic acid; high mannose-type N-linked oligosaccharides and the galactosylation of N-glycans were the major structures that were found. Furthermore, a complex between a glycan on DENV and the carbohydrate recognition domain (CRD) of DC-SIGN was mimicked with computational docking experiments. For the first time, this study provides a comprehensive understanding of the N-linked glycan profile of whole DENV-2 particles derived from insect cells.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: an update for 2009-2010

This review is the sixth update of the original article published in 1999 on the application of MALDI mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2010. General aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, arrays and fragmentation are covered in the first part of the review and applications to various structural typed constitutes the remainder. The main groups of compound that are discussed in this section are oligo and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals. Many of these applications are presented in tabular form. Also discussed are medical and industrial applications of the technique, studies of enzyme reactions and applications to chemical synthesis.

Solid-phase biological assays for drug discovery

In the past 30 years, there has been a significant growth in the use of solid-phase assays in the area of drug discovery, with a range of new assays being used for both soluble and membrane-bound targets. In this review, we provide some basic background to typical drug targets and immobilization protocols used in solid-phase biological assays (SPBAs) for drug discovery, with emphasis on particularly labile biomolecular targets such as kinases and membrane-bound receptors, and highlight some of the more recent approaches for producing protein microarrays, bioaffinity columns, and other devices that are central to small molecule screening by SPBA. We then discuss key applications of such assays to identify drug leads, with an emphasis on the screening of mixtures. We conclude by highlighting specific advantages and potential disadvantages of SPBAs, particularly as they relate to particular assay formats.

On-plate glycoproteins/glycopeptides selective enrichment and purification based on surface pattern for direct MALDI MS analysis

In this paper, a novel method has been proposed to achieve selective enrichment and purification of glycoproteins/glycopeptides on a surface patterned sample support, which consists of a hydrophobic outer layer (F-SAM) and an internal boronic acid-modified gold microspot (900 μm). Upon deposition, the sample solution is firstly concentrated in a small area by repulsion of the hydrophobic outer layer, and then the glycoproteins/glycopeptides are selectively captured through boronic acid covalently binding in the inner layer. However, the non-glycosylated proteins/peptides or high concentration salts are removed after rinsing with alkaline solution. As a result, the detection sensitivity is improved by an order of magnitude greater than when using a stainless steel MALDI plate. With surface patterned sample support, the glycoproteins/glycopeptides can be detected even under interference from the excessive existing non-glycosylated proteins/peptides (10 times more than glycoproteins/glycopeptides). Simultaneously, high-quality mass spectra can be obtained even in the presence of urea (1 M), NaCl (1 M), or NH4HCO3 (200 mM). Therefore, this novel technique may be applied to high-throughput analysis of low-abundance glycoproteins/glycopeptides in complicated proteome research.

Glycoproteomic analysis of tissues from patients with colon cancer using lectin microarrays and nanoLC-MS/MS

The current study evaluated the glycoproteomic profile of tissues from colon cancer patients. The lectin microarray was first performed to compare the glycoprotein profiles between colon cancer and matched normal tissues. Level of N-acetylglucosamine (GlcNAc) that Solanum tuberosum lectin (STL) bound was found to be elevated in colon cancer, which was verified through lectin histochemistry. The subsequent glycoproteomic analysis based on STL enrichment of glycoproteins followed by label-free quantitative nano liquid chromatography-mass spectrometry/mass spectrometry (nanoLC-MS/MS) analysis identified 72 proteins in high confidence. Among these proteins, 17 were exclusively detected in cancer tissues, and 14 were significantly upregulated in tumor tissues. Annexin A1 and HSP90β were chosen for further investigation by immunoprecipitation coupled with lectin blots, western blots and tissue microarrays. Both Annexin A1 and HSP90β were GlcNAcylated, and their protein expressions were elevated in colon cancer, compared to normal tissues. Moreover, specific changes of GlcNAc abundances in Annexin A1 and HSP90β suggested that tumor-specific glycan patterns could serve as candidate biomarkers of colon cancer for distinguishing cancer patients from healthy individuals.

Directed, strong, and reversible immobilization of proteins tagged with a β-trefoil lectin domain: a simple method to immobilize biomolecules on plain agarose matrixes

A highly stable lipase from Geobacillus thermocatenolatus (BTL2) and the enhanced green fluorescent protein from Aquorea victoria (EGFP) were recombinantly produced N-terminally tagged to the lectin domain of the hemolytic pore-forming toxin LSLa from the mushroom Laetiporus sulphureus . Such a domain (LSL(150)), recently described as a novel fusion tag, is based on a β-trefoil scaffold with two operative binding sites for galactose or galactose-containing derivatives. The fusion proteins herein analyzed have enabled us to characterize the binding mode of LSL(150) to polymeric and solid substrates such as agarose beads. The lectin-fusion proteins are able to be quantitatively bound to both cross-linked and non-cross-linked agarose matrixes in a very rapid manner, resulting in a surprisingly dynamic protein distribution inside the porous beads that evolves from heterogeneous to homogeneous along the postimmobilization time. Such dynamic distribution can be related to the reversible nature of the LSL(150)-agarose interaction. Furthermore, this latter interaction is temperature dependent since it is 4-fold stronger when the immobilization takes place at 25 °C than when it does at 4 °C. The strongest lectin-agarose interaction is also quite stable under a survey of different conditions such as high temperatures (up to 60 °C) or high organic solvent concentrations (up to 60% of acetonitrile). Notably, the use of cross-linked agarose would endow the system with more robustness due to its better mechanical properties compared to the noncross-linked one. The stability of the LSL(150)-agarose interaction would prevent protein leaching during the operation process unless high pH media are used. In summary, we believe that the LSL(150) lectin domain exhibits interesting structural features as an immobilization domain that makes it suitable to reversibly immobilize industrially relevant enzymes in very simple carriers as agarose.

Characterization of the human submandibular/sublingual saliva glycoproteome using lectin affinity chromatography coupled to multidimensional protein identification technology

In-depth analysis of the salivary proteome is fundamental to understanding the functions of salivary proteins in the oral cavity and to reveal disease biomarkers involved in different pathophysiological conditions, with the ultimate goal of improving patient diagnosis and prognosis. Submandibular and sublingual glands contribute saliva rich in glycoproteins to the total saliva output, making them valuable sources for glycoproteomic analysis. Lectin-affinity chromatography coupled to mass spectrometry-based shotgun proteomics was used to explore the submandibular/sublingual (SM/SL) saliva glycoproteome. A total of 262 N- and O-linked glycoproteins were identified by multidimensional protein identification technology (MudPIT). Only 38 were previously described in SM and SL salivas from the human salivary N-linked glycoproteome, while 224 were unique. Further comparison analysis with SM/SL saliva of the human saliva proteome, revealed 125 glycoproteins not formerly reported in this secretion. KEGG pathway analyses demonstrated that many of these glycoproteins are involved in processes such as complement and coagulation cascades, cell communication, glycosphingolipid biosynthesis neo-lactoseries, O-glycan biosynthesis, glycan structures-biosynthesis 2, starch and sucrose metabolism, peptidoglycan biosynthesis or others pathways. In summary, lectin-affinity chromatography coupled to MudPIT mass spectrometry identified many novel glycoproteins in SM/SL saliva. These new additions to the salivary proteome may prove to be a critical step for providing reliable biomarkers in the diagnosis of a myriad of oral and systemic diseases.

Analysis and prediction of cancerlectins using evolutionary and domain information

BACKGROUND

Predicting the function of a protein is one of the major challenges in the post-genomic era where a large number of protein sequences of unknown function are accumulating rapidly. Lectins are the proteins that specifically recognize and bind to carbohydrate moieties present on either proteins or lipids. Cancerlectins are those lectins that play various important roles in tumor cell differentiation and metastasis. Although the two types of proteins are linked, still there is no computational method available that can distinguish cancerlectins from the large pool of non-cancerlectins. Hence, it is imperative to develop a method that can distinguish between cancer and non-cancerlectins.

RESULTS

All the models developed in this study are based on a non-redundant dataset containing 178 cancerlectins and 226 non-cancerlectins in which no two sequences have more than 50% sequence similarity. We have applied the similarity search based technique, i.e. BLAST, and achieved a maximum accuracy of 43.25%. The amino acids compositional analysis have shown that certain residues (e.g. Leucine, Proline) were preferred in cancerlectins whereas some other (e.g. Asparatic acid, Asparagine) were preferred in non-cancerlectins. It has been found that the PROSITE domain "Crystalline beta gamma" was abundant in cancerlectins whereas domains like "SUEL-type lectin domain" were found mainly in non-cancerlectins. An SVM-based model has been developed to differentiate between the cancer and non-cancerlectins which achieved a maximum Matthew's correlation coefficient (MCC) value of 0.32 with an accuracy of 64.84%, using amino acid compositions. We have developed a model based on dipeptide compositions which achieved an MCC value of 0.30 with an accuracy of 64.84%. Thereafter, we have developed models based on split compositions (2 and 4 parts) and achieved an MCC value of 0.31, 0.32 with accuracies of 65.10% and 66.09%, respectively. An SVM model based on Position Specific Scoring Matrix (PSSM), generated by PSI-BLAST, was developed and achieved an MCC value of 0.36 with an accuracy of 68.34%. Finally, we have integrated the PROSITE domain information with PSSM and developed an SVM model that has achieved an MCC value of 0.38 with 69.09% accuracy.

CONCLUSION

BLAST has been found inefficient to distinguish between cancer and non-cancerlectins. We analyzed the protein sequences of cancer and non-cancerlectins and identified interesting patterns. We have been able to identify PROSITE domains that are preferred in cancer and non-cancerlectins and thus provided interesting insights into the two types of proteins. The method developed in this study will be useful for researchers studying cancerlectins, lectins and cancer biology. The web-server based on the above study, is available at http://www.imtech.res.in/raghava/cancer_pred/

Human cancer classification: a systems biology- based model integrating morphology, cancer stem cells, proteomics, and genomics

Human cancer classification is currently based on the idea of cell of origin, light and electron microscopic attributes of the cancer. What is not yet integrated into cancer classification are the functional attributes of these cancer cells. Recent innovative techniques in biology have provided a wealth of information on the genomic, transcriptomic and proteomic changes in cancer cells. The emergence of the concept of cancer stem cells needs to be included in a classification model to capture the known attributes of cancer stem cells and their potential contribution to treatment response, and metastases. The integrated model of cancer classification presented here incorporates all morphology, cancer stem cell contributions, genetic, and functional attributes of cancer. Integrated cancer classification models could eliminate the unclassifiable cancers as used in current classifications. Future cancer treatment may be advanced by using an integrated model of cancer classification.

Glycan and lectin microarrays for glycomics and medicinal applications

Three different array formats to study a challenging field of glycomics are presented here, based on the use of a panel of immobilized glycan or lectins, and on in silico computational approach. Glycan and lectin arrays are routinely used in combination with other analytical tools to decipher a complex nature of glycan-mediated recognition responsible for signal transduction of a broad range of biological processes. Fundamental aspects of the glycan and lectin array technology are discussed, with the focus on the choice and availability of the biorecognition elements, fabrication protocols, and detection platforms involved. Moreover, practical applications of both technologies especially in the field of clinical diagnostics are provided. The future potential of a complementary in silico array technology to reveal details of the protein-glycan-binding profiles is discussed here.