Comprehensive analysis of lectin-glycan interactions reveals determinants of lectin specificity

Galactia lindenii lectin type-II: Its potential use in thyroid cancer diagnosis

Galactia lindenii lectin type-II (GLL-II) belongs to the group of the legume lectins. The present study investigated the GLL-II staining patterns in histological sections of neoplastic and non-neoplastic thyroid tissues. Besides, hemagglutination assays (HA) using the GLL-II on red blood cells of different glycomic profiles were performed, complementing previous results. The differential staining in Papillary Thyroid Cancer, Invasive Encapsulated Follicular Variant Papillary Thyroid Carcinoma, Hashimoto's thyroiditis, and non-neoplastic thyroid with goiter changes, together with the HA results, allowed us to propose the potential utility of GLL-II as part of lectin platforms used to discriminate between human thyroid pathological samples from normal ones. The present study shed light on potential applications of GLL-II in determining alterations of glycosylation patterns in specific cells, tissues, or body fluids, as well as glycotopes biomarkers of healthy or pathological conditions.

Lectin based differential profiling of sperm membrane glycans for assessment of buffalo (Bubalus bubalis) bull fertility

Spermatozoa membrane glycocalyx plays a crucial role in sperm functions, including maturation, female reproductive tract protection, oviductal epithelium adhesion, and oocyte fusion. This study investigated differences in glycan abundance and mapping in buffalo spermatozoa from high-fertile (HF) and low-fertile (LF) bulls. Semen samples were analyzed for motility, vitality, morphology, and functional characteristics before glycan profiling. Utilizing group of nine different lectins through cytochemistry and flow cytometry analyses we identified differentially abundant glycans (DAGs) on sperm membrane. HF bulls exhibited superior sperm quality and significantly higher glycan abundance than LF bulls. MAL-II (Maackia amurensis lectin II) depicted stronger binding affinity with HF sperm indicating a higher presence of α-2,3-linked sialic acid residues crucial for sperm function. JAC (Artocarpus integrifolia) binding revealed an abundance of N-acetylgalactosamine, while ABL (Agaricus bisporus lectin) indicated greater mannose-containing glycoconjugates in HF sperm. The glycan map of buffalo spermatozoa underscores a higher abundance of α-2,3-linked sialic acids and acetylgalactosamine in HF sperm, highlighting the potential role of glycan profiling as a screening tool for selecting highly fertile bulls. The findings of this study can pave the way to develop a fertility prediction tool as a rapid lab-on-strip device for enhancing the reproductive and breeding performance of buffalo bulls.

Lipopolysaccharide Detection with Glycan-Specific Lectins-a Nonspecific Binding Approach Applied to Surface Plasmon Resonance

The detection and classification of lipopolysaccharides (LPS), pivotal constituents of Gram-negative bacteria, are fundamental to the progression of biosensing technologies in fields such as healthcare, environmental monitoring, and food safety. This study presents an innovative approach utilizing a panel of glycan-selective lectins in conjunction with surface plasmon resonance (SPR) providing a novel perspective on the evolution of biosensors within the context of the ongoing tension between the highly selective, one-probe-one-target methodology and the broader, resource-intensive approach that integrates complex and costly technological tools into the biosensing discipline. Guided by the principles of lean development, we employed a panel of lectins to construct multiprobe detection profiles, thereby facilitating the precise classification of LPS variants while minimizing both variability and resource expenditure. Advanced machine learning techniques were applied to optimize feature selection and enhance classification accuracy, demonstrating that a minimal set of four lectins sustains exceptional predictive performance. This synergy between traditional affinity techniques and data science enhances assay engineering efficiency, scalability, and integration into routine workflows, supporting frontline pathogen monitoring. This innovative approach holds promise for addressing global health challenges, providing more profound insights into biosensing methodologies, and expanding pathogen screening networks closer to the public and health safety management bodies.

Tools for structural lectinomics: From structures to lectomes

Lectins are ubiquitous proteins that interact with glycans in a variety of molecular processes and as such, also play a role in diseases, whether infectious, chronic or cancer-related. The systematic study of lectins is therefore essential, in particular for understanding cell-cell communication. Accumulated protein three-dimensional structural data in the past decades boosted advance in AI-based prediction and opened up new options to characterise lectins that are known to often be multimeric and multivalent. This article reviews the methods to obtain structures of lectins, the current data available for lectin 3D structures and their interactions, how this knowledge is used to classify these proteins and shows that the combination of an array of bioinformatics tools should make the prediction of binding specificity possible in a near future.

Fungal lectins show differential antiproliferative activity against cancer cell lines

Glycosylation patterns represent an important signature of cancer cells that can be decoded by glycan-binding proteins, i.e., lectins. Fungal lectins have unique properties and diverse structural and glycan-recognition features. In this study, the bioactivities of 22 fungal proteins against nine cancer cell lines were analyzed, and cell phenotypes were assessed with live cell imaging providing mechanistic insights. Eight fungal lectins showed antiproliferative activity, which depended on glycan binding and led to different downstream effects. The β-galactoside-binding chimerolectins Marasmius oreades agglutinin (MOA) and Laetiporus sulphureus lectin (LSL) showed indiscriminate antiproliferative activities with different modes of action, whereas the non-chimeric β-galactoside-binding lectin Agrocybe aegerita galectin (AAG) showed differential antiproliferative activity. Other β-galactoside-binding lectins exerted no effects. Fucose-binding lectins showed differential and strong antiproliferative activities, of which Aleuria aurantia lectin (AAL) exerted the strongest effects. Weaker and differential antiproliferative activities were observed with the Galβ1-3GalNAc-binding actinoporin-like lectins Xerocomus chrysenteron lectin (XCL), Sordaria macrospora transcript associated with perithecial development (TAP1), and Agaricus bisporus lectin (ABL). The different downstream effects of lectins, likely influenced by the targeted glycoligands, show that fungal lectins are valuable tools for identifying new therapeutic targets that can induce cancer cell death or growth arrest via different mechanisms.

The crystal structure of Nictaba reveals its carbohydrate-binding properties and a new lectin dimerization mode

Nictaba is a (GlcNAc)n-binding, stress-inducible lectin from Nicotiana tabacum that serves as a representative for the Nictaba-related lectins, a group of proteins that play pivotal roles in plant defense mechanisms and stress response pathways. Despite extensive research into biological activities and physiological role(s) of the lectin, the three-dimensional structure of Nictaba remained largely unknown. Here, we report crystal structures for Nictaba in the apo form and bound to chitotriose. The structures reveal that the Nictaba protomer has a jelly-roll fold, similar to the cucumber lectin Cus17, but exhibit a unique and previously unseen mode of dimerization. The chitotriose binding mode, similar to Cus17, centers around the central GlcNAc residue, providing insights into the determinants of specificity of Nictaba towards carbohydrate structures. By integrating these structural insights with inputs from glycan arrays, molecular docking, and molecular dynamics simulations, we propose that Nictaba employs a single carbohydrate-recognition domain within each of the two subunits in the dimer to display pronounced specificity towards GlcNAc-containing carbohydrates. Furthermore, we identified amino acid residues involved in the extended binding site capable of accommodating structurally diverse high-mannose and complex N-glycans. Glycan array and in silico analyses revealed interactions centered around the conserved Man3GlcNAc2 core, explaining the broad recognition of N-glycan structures. Collectively, the structural and biochemical insights presented here fill a void into the atlas of lectin structure-function relationships and pave the way for future developments in plant stress biology and lectin-based applications.

Unlocking the future of colorectal cancer detection: Advances in screening glycosylation-based biomarkers on biological mass spectrometry technology

The incidence of colorectal cancer (CRC) is increasingly affecting younger populations, with its mortality rate rising annually. However, current clinical diagnostic techniques, such as colonoscopy and CEA antigen testing, remain invasive and prone to false-positive results, complicating early diagnosis and intervention. Glycosylation, a key post-translational modification, plays an essential role in cellular function, physiological regulation, and disease processes. In recent years, mass spectrometry technology has emerged as a powerful tool for screening glycan biomarkers, owing to its exceptional separation capabilities and sensitivity. This review encompasses the advancements in CRC glycan biomarkers from 2016 to 2024, with particular emphasis placed on N/O-glycan biomarkers identified through mass spectrometry. Nonetheless, the intrinsic low abundance and polyhydroxy nature of glycans hinder the specificity and sensitivity of current glycan biomarkers. To overcome these limitations, this article outlines pretreatment strategies for N/O-glycans, including glycan release, enrichment, purification, and derivatization, in conjunction with relative quantification techniques and high-throughput bioinformatics tools for biomarker screening. These strategies are anticipated to enhance the efficiency and precision of glycan biomarker identification through mass spectrometry. These advancements hold significant promise for enhancing CRC prevention, diagnosis, and treatment, thereby potentially improving patient outcomes and quality of life.

Diagnostic value and application prospect of tumor abnormal protein test in head and neck tumors

Tumor abnormal protein (TAP) test also called abnormal glycoprotein chain test assesses the level of abnormal glycosylation in the body by measuring the agglutination of 10 different agglutinins, including wheat germ agglutinin, cuttle bean agglutinin, and so on. The lectins are proteins containing one or more binding sites with a strong affinity for particular carbohydrate chains that can specifically identify and bind to abnormal glycan molecules on malignant cells. It has been widely used clinically in recent years for the early diagnosis of tumourigenesis. Numerous studies have been conducted to investigate the mechanisms by which lectins bind to a set of glycans. As the incidence of head and neck cancer is high, with squamous cell carcinoma being the most common type. The lack of highly specific and sensitive tests makes early screening difficult, and treatment is often delayed, resulting in organ loss or even death, and often has a negative psychological impact. This narrative review will analyze the principle and current status of clinical application of TAP detection to prove TAP test will offer more sensitive methods for the precancerous risk assessment of head and neck squamous cell carcinoma, as well as for tracking metastases and recurrence.

RNA-seq transcriptome and pathway analysis of the medicinal mushroom Lignosus tigris (Polyporaceae) offer insights into its bioactive compounds with anticancer and antioxidant potential

ETHNOPHARMACOLOGICAL RELEVANCE

Medicinal mushrooms belonging to the Lignosus spp., colloquially known as Tiger Milk mushrooms (TMMs), are used as traditional medicine by communities across various regions of China and Southeast Asia to enhance immunity and to treat various diseases. At present, three Lignosus species have been identified in Malaysia: L. rhinocerus, L. tigris, and L. cameronensis. Similarities in their macroscopic morphologies and the nearly indistinguishable appearance of their sclerotia often lead to interchangeability between them. Hence, substantiation of their traditional applications via identification of their individual bioactive properties is imperative in ensuring that they are safe for consumption. L. tigris was first identified in 2013. Thus far, studies on L. tigris cultivar sclerotia (Ligno TG-K) have shown that it possesses significant antioxidant activities and has greater antiproliferative action against selected cancer cells in vitro compared to its sister species, L. rhinocerus TM02®. Our previous genomics study also revealed significant genetic dissimilarities between them. Further omics investigations on Ligno TG-K hold immense potential in facilitating the identification of its bioactive compounds and their associated bioactivities.

AIM OF STUDY

The overall aim of this study was to investigate the gene expression profile of Ligno TG-K via de novo RNA-seq and pathway analysis. We also aimed to identify highly expressed genes encoding compounds that contribute to its cytotoxic and antioxidant properties, as well as perform a comparative transcriptomics analysis between Ligno TG-K and its sister species, L. rhinocerus TM02®.

MATERIALS AND METHODS

Total RNA from fresh 3-month-old cultivated L. tigris sclerotia (Ligno TG-K) was extracted and analyzed via de novo RNA sequencing. Expressed genes were analyzed using InterPro and NCBI-Nr databases for domain identification and homology search. Functional categorization based on gene functions and pathways was performed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Clusters of Orthologous Genes (COG) databases. Selected genes were subsequently subjected to phylogenetic analysis.

RESULTS

Our transcriptomics analysis of Ligno TG-K revealed that 68.06% of its genes are expressed in the sclerotium; 80.38% of these were coding transcripts. Our analysis identified highly expressed transcripts encoding proteins with prospective medicinal properties. These included serine proteases (FPKM = 7356.68), deoxyribonucleases (FPKM = 3777.98), lectins (FPKM = 3690.87), and fungal immunomodulatory proteins (FPKM = 2337.84), all of which have known associations with anticancer activities. Transcripts linked to proteins with antioxidant activities, such as superoxide dismutase (FPKM = 1161.69) and catalase (FPKM = 1905.83), were also highly expressed. Results of our sequence alignments revealed that these genes and their orthologs can be found in other mushrooms. They exhibit significant sequence similarities, suggesting possible parallels in their anticancer and antioxidant bioactivities.

CONCLUSION

This study is the first to provide a reference transcriptome profile of genes expressed in the sclerotia of L. tigris. The current study also presents distinct COG profiles of highly expressed genes in Ligno TG-K and L. rhinocerus TM02®, highlighting that any distinctions uncovered may be attributed to their interspecies variations and inherent characteristics that are unique to each species. Our findings suggest that Ligno TG-K contains bioactive compounds with prospective medicinal properties that warrant further investigations.

CLASSIFICATION

Systems biology and omics.

Alterations of mannosylated glycopatterns recognized by Hippeastrum hybrid lectin in saliva of patients with lung cancer

OBJECTIVES

Lung cancer (LC) is the malignant tumor with the highest mortality rate worldwide, and precise early diagnosis can improve patient prognosis. The purpose of this study was to investigate whether alterations in the glycopatterns recognized by the Hippeastrum hybrid lectin (HHL) in salivary proteins are associated with the development of LC.

MATERIALS AND METHODS

First, we collected saliva samples from LC (15 lung adenocarcinoma (ADC); 15 squamous cell carcinoma (SCC); 15 small cell lung cancer (SCLC)) and 15 benign pulmonary disease (BPD) for high-throughput detection of abundance levels of HHL-recognized glycopatterns using protein microarrays, and then validated the pooled samples from each group with lectin blotting analysis. Finally, the N-glycan profiles of salivary glycoproteins isolated from the pooled samples using HHL-magnetic particle conjugates were characterized separately using MALDI-TOF/TOF-MS.

RESULTS

The results showed that the abundance level of glycopatterns recognized by HHL in salivary proteins was elevated in LC compared to BPD. The proportion of mannosylated N-glycans was notably higher in ADC (31.7%), SCC (39.0%), and SCLC (46.6%) compared to BPD (23.3%).

CONCLUSIONS

The altered salivary glycopatterns such as oligomannose, Manα1-3Man, or Manα1-6Man N-glycans recognized by HHL might serve as potential biomarkers for the diagnosis of LC patients.

CLINICAL RELEVANCE

This study provides crucial information for studying changes in salivary to differentiate between BPD and LC and facilitate the discovery of biomarkers for LC diagnosis based on precise alterations of mannosylated N-glycans in saliva.

Dielectrophoretic Capture of Cancer-Derived Small-Extracellular-Vesicle-Bound Janus Nanoparticles via Lectin-Glycan Interaction

Glycosylation is closely related to cellular metabolism and disease progression. In particular, glycan levels in cancer cells and tissues increase during cancer progression. This upregulation of glycosylation in cancer cells may provide a basis for the development of new biomarkers for the targeting and diagnosis of specific cancers. Here, they developed a detection technology for pancreatic cancer cell-derived small extracellular vesicles (PC-sEVs) based on lectin-glycan interactions. Lectins specific for sialic acids are conjugated to Janus nanoparticles to induce interactions with PC-sEVs in a dielectrophoretic (DEP) system. PC-sEVs are selectively bound to the lectin-conjugated Janus nanoparticles (lectin-JNPs) with an affinity comparable to that of conventionally used carbohydrate antigen 19-9 (CA19-9) antibodies. Furthermore, sEVs-bound Lectin-JNPs (sEVs-Lec-JNPs) are manipulated between two electrodes to which an AC signal is applied for DEP capture. In addition, the proposed DEP system can be used to trap the sEVs-Lec-JNP on the electrodes. Their results, which are confirmed by lectin-JNPs using the proposed DEP system followed by target gene analysis, provide a basis for the development of a new early diagnostic marker based on the glycan characteristics of PC-sEVs. In turn, these novel detection methods could overcome the shortcomings of commercially available pancreatic cancer detection techniques.

HumanLectome, an update of UniLectin for the annotation and prediction of human lectins

The UniLectin portal (https://unilectin.unige.ch/) was designed in 2019 with the goal of centralising curated and predicted data on carbohydrate-binding proteins known as lectins. UniLectin is also intended as a support for the study of lectomes (full lectin set) of organisms or tissues. The present update describes the inclusion of several new modules and details the latest (https://unilectin.unige.ch/humanLectome/), covering our knowledge of the human lectome and comprising 215 unevenly characterised lectins, particularly in terms of structural information. Each HumanLectome entry is protein-centric and compiles evidence of carbohydrate recognition domain(s), specificity, 3D-structure, tissue-based expression and related genomic data. Other recent improvements regarding interoperability and accessibility are outlined.

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.

Coral-algal endosymbiosis characterized using RNAi and single-cell RNA-seq

Corals form an endosymbiotic relationship with the dinoflagellate algae Symbiodiniaceae, but ocean warming can trigger algal loss, coral bleaching and death, and the degradation of ecosystems. Mitigation of coral death requires a mechanistic understanding of coral-algal endosymbiosis. Here we report an RNA interference (RNAi) method and its application to study genes involved in early steps of endosymbiosis in the soft coral Xenia sp. We show that a host endosymbiotic cell marker called LePin (lectin and kazal protease inhibitor domains) is a secreted Xenia lectin that binds to algae to initiate phagocytosis of the algae and coral immune response modulation. The evolutionary conservation of domains in LePin among marine anthozoans performing endosymbiosis suggests a general role in coral-algal recognition. Our work sheds light on the phagocytic machinery and posits a mechanism for symbiosome formation, helping in efforts to understand and preserve coral-algal relationships in the face of climate change.

Assembly and recognition mechanisms of glycosylated PEGylated polyallylamine phosphate nanoparticles: A fluorescence correlation spectroscopy and small angle X-ray scattering study

HYPOTHESIS

Modification of polyallylamine hydrochloride (PAH) with heterobifunctional low molecular weight polyethylene glycol (PEG) (600 and 1395 Da), and subsequent attachment of mannose, glucose, or lactose sugars to PEG, can lead to formation of polyamine phosphate nanoparticles (PANs) with lectin binding affinity and narrow size distribution.

EXPERIMENTS

Size, polydispersity, and internal structure of glycosylated PEGylated PANs were characterized by transmission electron microscopy (TEM), dynamic light scattering (DLS) and small angle X-ray scattering (SAXS). Fluorescence correlation spectroscopy (FCS) was used to study the association of labelled glycol-PEGylated PANs. The number of polymer chains forming the nanoparticles was determined from the changes in amplitude of the cross-correlation function of the polymers after formation of the nanoparticles. SAXS and fluorescence cross-correlation spectroscopy were used to investigate the interaction of PANs with lectins: concanavalin A with mannose modified PANs, and jacalin with lactose modified ones.

FINDINGS

Glyco-PEGylated PANs are highly monodispersed, with diameters of a few tens of nanometers and low charge, and a structure corresponding to spheres with Gaussian chains. FCS shows that the PANs are single chain nanoparticles or formed by two polymer chains. Concanavalin A and jacalin show specific interactions for the glyco-PEGylated PANs with higher affinity than bovine serum albumin.

Glycoinformatics in the Artificial Intelligence Era

Artificial intelligence (AI) methods have been and are now being increasingly integrated in prediction software implemented in bioinformatics and its glycoscience branch known as glycoinformatics. AI techniques have evolved in the past decades, and their applications in glycoscience are not yet widespread. This limited use is partly explained by the peculiarities of glyco-data that are notoriously hard to produce and analyze. Nonetheless, as time goes, the accumulation of glycomics, glycoproteomics, and glycan-binding data has reached a point where even the most recent deep learning methods can provide predictors with good performance. We discuss the historical development of the application of various AI methods in the broader field of glycoinformatics. A particular focus is placed on shining a light on challenges in glyco-data handling, contextualized by lessons learnt from related disciplines. Ending on the discussion of state-of-the-art deep learning approaches in glycoinformatics, we also envision the future of glycoinformatics, including development that need to occur in order to truly unleash the capabilities of glycoscience in the systems biology era.

Upregulated influenza A viral entry factors and enhanced interferon-alpha response in the nasal epithelium of pregnant rats

Despite the increased severity of influenza A infection in pregnancy, knowledge about the expression of cell entry factors for influenza A virus (IAV) and the innate immune response in the nasal epithelium, the primary portal of viral entry, is limited. Here, we compared the expression of IAV cell entry factors and the status of the innate immune response in the nasal epithelium of pregnant vs. non-pregnant female rats. IAV cell entry factors — sialic acid [SA] α-2,3- and α-2,6-linked glycans for avian and human IAV, respectively — were detected and quantified with lectin-based immunoblotting and flow cytometry. Baseline frequencies of innate immune cell phenotypes in single cell suspensions of the nasal epithelium were studied with flow cytometry. Subsequently, the magnitude of interferon and cytokine responses was studied with ELISA and cytokine arrays after intranasal resiquimod, a Toll-like receptor 7/8 agonist that mimics IAV infection. We noted substantially increased expression of cell entry factors for both avian and human IAV in the nasal epithelium during pregnancy. Assessment of the innate immune state of the nasal epithelium during pregnancy revealed two previously unreported features: (i) increased presence of tissue-resident plasmacytoid dendritic cells, and (ii) markedly enhanced release of interferon-α but not of the other interferons or cytokines 2 h after intranasal resiquimod. Collectively, our findings challenge the conventional notion of pregnancy-induced immunosuppression as a cause for severe influenza A disease and suggest the need for focused studies on viral tropism during pregnancy to better understand the proximate cause for the observed immunopathology.

Structural insights into host-microbe glycointeractions

Despite their ubiquitous presence in biological systems, glycans have historically received less attention than they deserved. Investigations in recent years have featured important findings about the role of glycans in regulating the human gut microbiota. Here, we present a brief overview of current trends that shape future directions of computational and experimental research approaches and add to our understanding of host-microbe glycointeractions.

UniLectin, A One-Stop-Shop to Explore and Study Carbohydrate-Binding Proteins

All eukaryotic cells are covered with a dense layer of glycoconjugates, and the cell walls of bacteria are made of various polysaccharides, putting glycans in key locations for mediating protein-protein interactions at cell interfaces. Glycan function is therefore mainly defined as binding to other molecules, and lectins are proteins that specifically recognize and interact non-covalently with glycans. UniLectin was designed based on insight into the knowledge of lectins, their classification, and their biological role. This modular platform provides a curated and periodically updated classification of lectins along with a set of comparative and visualization tools, as well as structured results of screening comprehensive sequence datasets. UniLectin can be used to explore lectins, find precise information on glycan-protein interactions, and mine the results of predictive tools based on HMM profiles. This usage is illustrated here with two protocols. The first one highlights the fine-tuned role of the O blood group antigen in distinctive pathogen recognition, while the second compares the various bacterial lectin arsenals that clearly depend on living conditions of species even in the same genus. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Searching for the structural details of lectins binding the O blood group antigen Basic Protocol 2: Comparing the lectomes of related organisms in different environments.