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

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.