Integrated in vivo functional screens and multi-omics analyses identify α-2,3-sialylation as essential for melanoma maintenance.

Glycosylation is a hallmark of cancer biology, and altered glycosylation influences multiple facets of melanoma growth and progression. To identify glycosyltransferases, glycans, and glycoproteins essential for melanoma maintenance, we conducted an in vivo growth screen with a pooled shRNA library of glycosyltransferases, lectin microarray profiling of benign nevi and melanoma patient samples, and mass spectrometry-based glycoproteomics. We found that α-2,3 sialyltransferases ST3GAL1 and ST3GAL2 and corresponding α-2,3-linked sialosides are upregulated in melanoma compared to nevi and are essential for melanoma growth in vivo and in vitro. Glycoproteomics revealed that glycoprotein targets of ST3GAL1 and ST3GAL2 are enriched in transmembrane proteins involved in growth signaling, including the amino acid transporter Solute Carrier Family 3 Member 2 (SLC3A2/CD98hc). CD98hc suppression mimicked the effect of ST3GAL1 and ST3GAL2 silencing, inhibiting melanoma cell proliferation. We found that both CD98hc protein stability and its pro-survival effect in melanoma are dependent upon α-2,3 sialylation mediated by ST3GAL1 and ST3GAL2. In summary, our studies reveal that α-2,3-sialosides functionally contribute to melanoma maintenance, supporting ST3GAL1 and ST3GAL2 as novel therapeutic targets in these tumors.

Patient Subtyping Analysis of Baseline Multi-omic Data Reveals Distinct Pre-immune States Predictive of Vaccination Responses.

Understanding the molecular mechanisms that underpin diverse vaccination responses is a critical step toward developing efficient vaccines. Molecular subtyping approaches can offer valuable insights into the heterogeneous nature of responses and aid in the design of more effective vaccines. In order to explore the molecular signatures associated with the vaccine response, we analyzed baseline transcriptomics data from paired samples of whole blood, proteomics and glycomics data from serum, and metabolomics data from urine, obtained from influenza vaccine recipients (2019-2020 season) prior to vaccination. After integrating the data using a network-based model, we performed a subtyping analysis. The integration of multiple data modalities from 62 samples resulted in five baseline molecular subtypes with distinct molecular signatures. These baseline subtypes differed in the expression of pre-existing adaptive or innate immunity signatures, which were linked to significant variation across subtypes in baseline immunoglobulin A (IgA) and hemagglutination inhibition (HAI) titer levels. It is worth noting that these significant differences persisted through day 28 post-vaccination, indicating the effect of initial immune state on vaccination response. These findings highlight the significance of interpersonal variation in baseline immune status as a crucial factor in determining vaccine response and efficacy. Ultimately, incorporating molecular profiling could enable personalized vaccine optimization.

HIV-1 interaction with an O-glycan-specific bacterial lectin enhances virus infectivity and resistance to neutralization by antibodies.

Bacteria dysbiosis has been associated with an increased risk of HIV-1 transmission and acquisition. The prevalent idea is that bacteria dysbiosis compromises mucosal integrity and promotes inflammatory conditions to cause recruitment and activation of immune cells that harbor or are targeted by HIV-1. However, it is also possible that HIV-1 directly binds bacteria or bacterial products to impact virus infectivity and transmissibility. This study evaluated HIV-1 interactions with bacteria through glycan-binding lectins. The Streptococcal Siglec-like lectin SLBR-N, which is part of the fimbriae shrouding the bacteria surface and recognizes α2,3 sialyated O-linked glycans, was noted for its ability to enhance HIV-1 infectivity in the context of cell-free infection and cell-to-cell transfer. Enhancing effects were recapitulated with O-glycan-binding plant lectins, signifying the importance of O-glycans. Conversely, N-glycan-binding bacterial lectins FimH and Msl had no effect. SLBR-N was demonstrated to capture and transfer infectious HIV-1 virions, bind to O-glycans on HIV-1 Env, and increase HIV-1 resistance to broadly neutralizing antibodies targeting different regions of Env. Hence, this study highlights the potential contribution of O-glycans in promoting HIV-1 infection through the exploitation of O-glycan-binding lectins from commensal bacteria at the mucosa.

CRISPR screens and lectin microarrays identify novel high mannose N-glycan regulators.

Glycans play critical roles in cellular signaling and function. Unlike proteins, glycan structures are not templated from genes but the concerted activity of many genes, making them historically challenging to study. Here, we present a strategy that utilizes pooled CRISPR screens and lectin microarrays to uncover and characterize regulators of cell surface glycosylation. We applied this approach to study the regulation of high mannose glycans - the starting structure of all asparagine(N)-linked-glycans. We used CRISPR screens to uncover the expanded network of genes controlling high mannose surface levels, followed by lectin microarrays to fully measure the complex effect of select regulators on glycosylation globally. Through this, we elucidated how two novel high mannose regulators - TM9SF3 and the CCC complex - control complex N-glycosylation via regulating Golgi morphology and function. Notably, this method allowed us to interrogate Golgi function in-depth and reveal that similar disruption to Golgi morphology can lead to drastically different glycosylation outcomes. Collectively, this work demonstrates a generalizable approach for systematically dissecting the regulatory network underlying glycosylation.

The microenvironment dictates glycocalyx construction and immune surveillance.

Efforts to identify anti-cancer therapeutics and understand tumor-immune interactions are built with in vitro models that do not match the microenvironmental characteristics of human tissues. Using in vitro models which mimic the physical properties of healthy or cancerous tissues and a physiologically relevant culture medium, we demonstrate that the chemical and physical properties of the microenvironment regulate the composition and topology of the glycocalyx. Remarkably, we find that cancer and age-related changes in the physical properties of the microenvironment are sufficient to adjust immune surveillance via the topology of the glycocalyx, a previously unknown phenomenon observable only with a physiologically relevant culture medium.

Absolute Affinities from Quantitative Shotgun Glycomics Using Concentration-Independent (COIN) Native Mass Spectrometry.

Native mass spectrometry (nMS) screening of natural glycan libraries against glycan-binding proteins (GBPs) is a powerful tool for ligand discovery. However, as the glycan concentrations are unknown, affinities cannot be measured directly from natural libraries. Here, we introduce Concentration-Independent (COIN)-nMS, which enables quantitative screening of natural glycan libraries by exploiting slow mixing of solutions inside a nanoflow electrospray ionization emitter. The affinities (Kd) of detected GBP-glycan interactions are determined, simultaneously, from nMS analysis of their time-dependent relative abundance changes. We establish the reliability of COIN-nMS using interactions between purified glycans and GBPs with known Kd values. We also demonstrate the implementation of COIN-nMS using the catch-and-release (CaR)-nMS assay for glycosylated GBPs. The COIN-CaR-nMS results obtained for plant, fungal, viral, and human lectins with natural libraries containing hundreds of N-glycans and glycopeptides highlight the assay's versatility for discovering new ligands, precisely measuring their affinities, and uncovering "fine" specificities. Notably, the COIN-CaR-nMS results clarify the sialoglycan binding properties of the SARS-CoV-2 receptor binding domain and establish the recognition of monosialylated hybrid and biantennary N-glycans. Moreover, pharmacological depletion of host complex N-glycans reduces both pseudotyped virions and SARS-CoV-2 cell entry, suggesting that complex N-glycans may serve as attachment factors.

Native Mass Spectrometry Quantitation of α2-3-Linked N-Acetylneuraminic Acid Content of Prostate-Specific Antigen: An Accurate Liquid Biopsy for Clinically Significant Prostate Cancer.

Application of the prostate-specific antigen (PSA) test, which measures PSA levels in blood, is standard in prostate cancer (PCa) screening. However, because PSA levels may be elevated for reasons other than PCa, it leads to high rates of misdiagnosis and overtreatment. Recently, alteration in the N-glycan sialylation of PSA, specifically increased levels of α2-3-linked N-acetylneuraminic acid (α2-3-Neu5Ac or α2-3-sialic acid), was identified as a potential biomarker for clinically significant PCa. Here, we introduce a robust top-down native mass spectrometry (MS) approach, performed using a combination of α2-3-Neu5Ac-specific and nonspecific neuraminidases and employing center-of-mass monitoring (CoMMon), for quantifying the levels of α2-3-Neu5Ac as a fraction of total N-linked Neu5Ac present on PSA extracted from blood serum. To illustrate the potential of the assay for clinical diagnosis and disease staging of PCa, the percentages of α2-3-Neu5Ac on PSA (%α23PSA) in the serum of low-grade (International Society of Urological Pathology Grade Group/GG1), intermediate-grade (GG2), and high-grade (GG3,4,5) PCa individuals were measured. We observed a high sensitivity (85.5%) and specificity (84.6%) for discrimination of GG1 from clinically significant GG2-5 patients when using a %α23PSA test cut-off of 28.0%. Our results establish that the %α23PSA in blood serum PSA, which can be precisely measured in a non-invasive manner with our dual neuraminidase native MS/CoMMon assay, can discriminate between clinically significant PCa (GG2-5) and low-grade PCa (GG1). Such discrimination has not been previously achieved and represents an important clinical need. This assay could greatly improve the standard PSA test and serve as a valuable PCa diagnostic tool.

Influenza Defective Interfering Virus Promotes Multiciliated Cell Differentiation and Reduces the Inflammatory Response in Mice.

Influenza defective interfering (DI) viruses have long been considered promising antiviral candidates because of their ability to interfere with replication-competent viruses and induce antiviral immunity. However, the mechanisms underlying DI-mediated antiviral immunity have not been extensively explored. Here, we demonstrated the interferon (IFN)-independent protection conferred by the influenza DI virus against homologous virus infection in mice deficient in type I and III IFN signaling. We identified unique host signatures responding to DI coinfection by integrating transcriptional and posttranscriptional regulatory data. DI-treated mice exhibited reduced viral transcription, less intense inflammatory and innate immune responses, and primed multiciliated cell differentiation in their lungs at an early stage of infection, even in the absence of type I or III IFNs. This increased multiciliogenesis could also be detected at the protein level via the immunofluorescence staining of lung tissue from DI-treated mice. Overall, our study provides mechanistic insight into the protection mediated by DIs, implying a unifying theme involving inflammation and multiciliogenesis in maintaining respiratory homeostasis and revealing their IFN-independent antiviral activity. IMPORTANCE During replication, the influenza virus generates genetically defective viruses. These are found in natural infections as part of the virus population within the infected host. Some versions of these defective viruses are thought to have protective effects through their interference with replication-competent viruses and induction of antiviral immunity. To better determine the mechanisms underlying the protective effects of these defective interfering (DI) viruses, we tested a DI that we previously identified in vitro with mice. Mice that were infected with a mix of wild-type influenza and DI viruses had less intense inflammatory and innate immune responses than did mice that were infected with the wild-type virus only, even when type I or III interferons, which are cytokines that play a prominent role in defending the respiratory epithelial barrier, were absent. More interestingly, the DI-infected mice had primed multiciliated cell differentiation in their lungs, indicating the potential promotion of epithelial repair by DIs.

Siglec-6 mediates the uptake of extracellular vesicles through a noncanonical glycolipid binding pocket.

Immunomodulatory Siglecs are controlled by their glycoprotein and glycolipid ligands. Siglec-glycolipid interactions are often studied outside the context of a lipid bilayer, missing the complex behaviors of glycolipids in a membrane. Through optimizing a liposomal formulation to dissect Siglec-glycolipid interactions, it is shown that Siglec-6 can recognize glycolipids independent of its canonical binding pocket, suggesting that Siglec-6 possesses a secondary binding pocket tailored for recognizing glycolipids in a bilayer. A panel of synthetic neoglycolipids is used to probe the specificity of this glycolipid binding pocket on Siglec-6, leading to the development of a neoglycolipid with higher avidity for Siglec-6 compared to natural glycolipids. This neoglycolipid facilitates the delivery of liposomes to Siglec-6 on human mast cells, memory B-cells and placental syncytiotrophoblasts. A physiological relevance for glycolipid recognition by Siglec-6 is revealed for the binding and internalization of extracellular vesicles. These results demonstrate a unique and physiologically relevant ability of Siglec-6 to recognize glycolipids in a membrane.

High-Throughput Analysis Reveals miRNA Upregulating α-2,6-Sialic Acid through Direct miRNA-mRNA Interactions.

Chemical biology has revealed the importance of sialic acids as a major signal in physiology and disease. The terminal modification α-2,6-sialic acid is controlled by the enzymes ST6GAL1 and ST6GAL2. Dysregulation of this glycan impacts immunological recognition and cancer development. microRNAs (miRNA, miR), noncoding RNAs that downregulate protein expression, are important regulators of glycosylation. Using our recently developed high-throughput fluorescence assay (miRFluR), we comprehensively mapped the miRNA regulatory landscape of α-2,6-sialyltransferases ST6GAL1 and ST6GAL2. We found, contrary to expectations, the majority of miRNAs upregulate ST6GAL1 and α-2,6-sialylation in a variety of cancer cells. In contrast, miRNAs that regulate ST6GAL2 were predominantly downregulatory. Mutational analysis identified direct binding sites in the 3'-untranslated region (UTR) responsible for upregulation, confirming it is a direct effect. The miRNA binding proteins AGO2 and FXR1 were required for upregulation. Our results upend common assumptions surrounding miRNA, arguing that upregulation by these noncoding RNA is common. Indeed, for some proteins, upregulation may be the dominant function of miRNA. Our work also suggests that upregulatory miRNAs enhance overexpression of ST6GAL1 and α-2,6-sialylation, providing another potential pathway to explain the dysregulation observed in cancer and other disease states.

Deep learning explains the biology of branched glycans from single-cell sequencing data.

Glycosylation is ubiquitous and often dysregulated in disease. However, the regulation and functional significance of various types of glycosylation at cellular levels is hard to unravel experimentally. Multi-omics, single-cell measurements such as SUGAR-seq, which quantifies transcriptomes and cell surface glycans, facilitate addressing this issue. Using SUGAR-seq data, we pioneered a deep learning model to predict the glycan phenotypes of cells (mouse T lymphocytes) from transcripts, with the example of predicting ß1,6GlcNAc-branching across T cell subtypes (test set F1 score: 0.9351). Model interpretation via SHAP (SHapley Additive exPlanations) identified highly predictive genes, in part known to impact (i) branched glycan levels and (ii) the biology of branched glycans. These genes included physiologically relevant low-abundance genes that were not captured by conventional differential expression analysis. Our work shows that interpretable deep learning models are promising for uncovering novel functions and regulatory mechanisms of glycans from integrated transcriptomic and glycomic datasets.

α2,6-Sialylation Is Upregulated in Severe COVID-19, Implicating the Complement Cascade.

Better understanding of the molecular mechanisms underlying COVID-19 severity is desperately needed in current times. Although hyper-inflammation drives severe COVID-19, precise mechanisms triggering this cascade and what role glycosylation might play therein are unknown. Here we report the first high-throughput glycomic analysis of COVID-19 plasma samples and autopsy tissues. We find that α2,6-sialylation is upregulated in the plasma of patients with severe COVID-19 and in autopsied lung tissue. This glycan motif is enriched on members of the complement cascade (e.g., C5, C9), which show higher levels of sialylation in severe COVID-19. In the lung tissue, we observe increased complement deposition, associated with elevated α2,6-sialylation levels, corresponding to elevated markers of poor prognosis (IL-6) and fibrotic response. We also observe upregulation of the α2,6-sialylation enzyme ST6GAL1 in patients who succumbed to COVID-19. Our work identifies a heretofore undescribed relationship between sialylation and complement in severe COVID-19, potentially informing future therapeutic development.

Mass spectrometry-based shotgun glycomics for discovery of natural ligands of glycan-binding proteins.

The non-covalent associations of complex carbohydrates (glycans) with glycan-binding proteins mediate many important physiological and pathophysiological processes. Identifying these interactions is essential to understanding their diverse biological functions and enables the development of new disease treatments and diagnostics. Knowledge of the repertoire of glycans recognized by most glycan-binding proteins and their affinities is incomplete. Mass spectrometry-based screening of natural glycan libraries has emerged as a promising approach to defining the glycan interactome of glycan-binding proteins. Here, we review recent advances in mass spectrometry-based natural library screening that have led to the discovery of glycan ligands of endogenous and exogenous proteins and illuminated their binding specificities.

Quantifying Biomolecular Interactions Using Slow Mixing Mode (SLOMO) Nanoflow ESI-MS.

Electrospray ionization mass spectrometry (ESI-MS) is a powerful label-free assay for detecting noncovalent biomolecular complexes in vitro and is increasingly used to quantify binding thermochemistry. A common assumption made in ESI-MS affinity measurements is that the relative ion signals of free and bound species quantitatively reflect their relative concentrations in solution. However, this is valid only when the interacting species and their complexes have similar ESI-MS response factors (RFs). For many biomolecular complexes, such as protein-protein interactions, this condition is not satisfied. Existing strategies to correct for nonuniform RFs are generally incompatible with static nanoflow ESI (nanoESI) sources, which are typically used for biomolecular interaction studies, thereby significantly limiting the utility of ESI-MS. Here, we introduce slow mixing mode (SLOMO) nanoESI-MS, a direct technique that allows both the RF and affinity (K d) for a biomolecular interaction to be determined from a single measurement using static nanoESI. The approach relies on the continuous monitoring of interacting species and their complexes under nonhomogeneous solution conditions. Changes in ion signals of free and bound species as the system approaches or moves away from a steady-state condition allow the relative RFs of the free and bound species to be determined. Combining the relative RF and the relative abundances measured under equilibrium conditions enables the K d to be calculated. The reliability of SLOMO and its ease of use is demonstrated through affinity measurements performed on peptide-antibiotic, protease-protein inhibitor, and protein oligomerization systems. Finally, affinities measured for the binding of human and bacterial lectins to a nanobody, a viral glycoprotein, and glycolipids displayed within a model membrane highlight the tremendous power and versatility of SLOMO for accurately quantifying a wide range of biomolecular interactions important to human health and disease.

SARS-CoV-2 impairs interferon production via NSP2-induced repression of mRNA translation.

Viruses evade the innate immune response by suppressing the production or activity of cytokines such as type I interferons (IFNs). Here we report the discovery of a mechanism by which the SARS-CoV-2 virus coopts an intrinsic cellular machinery to suppress the production of the key immunostimulatory cytokine IFN-ß. We reveal that the SARS-CoV-2 encoded nonstructural protein 2 (NSP2) directly interacts with the cellular GIGYF2 protein. This interaction enhances the binding of GIGYF2 to the mRNA cap-binding protein 4EHP, thereby repressing the translation of the Ifnb1 mRNA. Depletion of GIGYF2 or 4EHP significantly enhances IFN-ß production, which inhibits SARS-CoV-2 replication. Our findings reveal a target for rescuing the antiviral innate immune response to SARS-CoV-2 and other RNA viruses.

Prevaccination Glycan Markers of Response to an Influenza Vaccine Implicate the Complement Pathway.

A key to improving vaccine design and vaccination strategy is to understand the mechanism behind the variation of vaccine response with host factors. Glycosylation, a critical modulator of immunity, has no clear role in determining vaccine responses. To gain insight into the association between glycosylation and vaccine-induced antibody levels, we profiled the pre- and postvaccination serum protein glycomes of 160 Caucasian adults receiving the FLUZONE influenza vaccine during the 2019-2020 influenza season using lectin microarray technology. We found that prevaccination levels of Lewis A antigen (Lea) are significantly higher in nonresponders than responders. Glycoproteomic analysis showed that Lea-bearing proteins are enriched in complement activation pathways, suggesting a potential role of glycosylation in tuning the activities of complement proteins, which may be implicated in mounting vaccine responses. In addition, we observed a postvaccination increase in sialyl Lewis X antigen (sLex) and a decrease in high mannose glycans among high responders, which were not observed in nonresponders. These data suggest that the immune system may actively modulate glycosylation as part of its effort to establish effective protection postvaccination.

α2,6-Sialylation is Upregulated in Severe COVID-19 Implicating the Complement Cascade.

Better understanding of the mechanisms of COVID-19 severity is desperately needed in current times. Although hyper-inflammation drives severe COVID-19, precise mechanisms triggering this cascade and what role glycosylation might play therein is unknown. Here we report the first high-throughput glycomic analysis of COVID-19 plasma samples and autopsy tissues. We find α2,6-sialylation is upregulated in plasma of patients with severe COVID-19 and in the lung. This glycan motif is enriched on members of the complement cascade, which show higher levels of sialylation in severe COVID-19. In the lung tissue, we observe increased complement deposition, associated with elevated α2,6-sialylation levels, corresponding to elevated markers of poor prognosis (IL-6) and fibrotic response. We also observe upregulation of the α2,6-sialylation enzyme ST6GAL1 in patients who succumbed to COVID-19. Our work identifies a heretofore undescribed relationship between sialylation and complement in severe COVID-19, potentially informing future therapeutic development.

Glycomic Analysis Reveals a Conserved Response to Bacterial Sepsis Induced by Different Bacterial Pathogens.

Sepsis is an extreme inflammatory response to infection that occurs in the bloodstream and causes damage throughout the body. Glycosylation is known to play a role in immunity and inflammation, but the role of glycans in sepsis is not well-defined. Herein, we profiled the serum glycomes of experimental mouse sepsis models to identify changes induced by 4 different clinical bacterial pathogens (Gram-positive: Streptococcus pneumoniae and Staphylococcus aureus, Gram-negative: Escherichia coli and Salmonella Typhimurium) using our lectin microarray technology. We observed global shifts in the blood sera glycome that were conserved across all four species, regardless of whether they were Gram positive or negative. Bisecting GlcNAc was decreased upon sepsis and a strong increase in core 1/3 O-glycans was observed. Lectin blot analysis revealed a high molecular weight protein induced in sepsis by all four bacteria as the major cause of the core 1/3 O-glycan shift. Analysis of this band by mass spectrometry identified interalpha-trypsin inhibitor heavy chains (ITIHs) and fibronectin, both of which are associated with human sepsis. Shifts in the glycosylation of these proteins were observed. Overall, our work points toward a common mechanism for bacterially induced sepsis, marked by conserved changes in the glycome.

Mass Spectrometry-Based Shotgun Glycomics Using Labeled Glycan Libraries.

Mass spectrometry-based shotgun glycomics (MS-SG) is a rapid, sensitive, label-, and immobilization-free approach for the discovery of natural ligands of glycan-binding proteins (GBPs). To perform MS-SG, natural libraries of glycans derived from glycoconjugates in cells or tissues are screened against a target GBP using catch-and-release electrospray ionization mass spectrometry (CaR-ESI-MS). Because glycan concentrations are challenging to determine, ligand affinities cannot be directly measured. In principle, relative affinities can be ranked by combining CaR-ESI-MS data with relative concentrations established by hydrophilic interaction liquid chromatography (HILIC) performed on the fluorophore-labeled glycan library. To validate this approach, as well as the feasibility of performing CaR-ESI-MS directly on labeled glycans, libraries of labeled N-glycans extracted from the human monocytic U937 cells or intestinal tissues were labeled with 2-aminobenzamide (2-AB), 2-aminobenzoic acid (2-AA), or procainamide (proA). The libraries were screened against plant and human GBPs with known specificities for α2-3- and α2-6-linked sialosides and quantified by HILIC. Dramatic differences, in some cases, were found for affinity rankings obtained with libraries labeled with different fluorophores, as well as those produced using the combined unlabeled/labeled library approach. The origin of these differences could be explained by differential glycan labeling efficiencies, the impact of specific labels on glycan affinities for the GBPs, and the relative efficiency of release of ligands from GBPs in CaR-ESI-MS. Overall, the results of this study suggest that the 2-AB(CaR-ESI-MS)/2-AB(HILIC) combination provides the most reliable description of the binding specificities of GBPs for N-glycans and is recommended for MS-SG applications.

A Useful Guide to Lectin Binding: Machine-Learning Directed Annotation of 57 Unique Lectin Specificities.

Glycans are critical to every facet of biology and medicine, from viral infections to embryogenesis. Tools to study glycans are rapidly evolving; however, the majority of our knowledge is deeply dependent on binding by glycan binding proteins (e.g., lectins). The specificities of lectins, which are often naturally isolated proteins, have not been well-defined, making it difficult to leverage their full potential for glycan analysis. Herein, we use a combination of machine learning algorithms and expert annotation to define lectin specificity for this important probe set. Our analysis uses comprehensive glycan microarray analysis of commercially available lectins we obtained using version 5.0 of the Consortium for Functional Glycomics glycan microarray (CFGv5). This data set was made public in 2011. We report the creation of this data set and its use in large-scale evaluation of lectin-glycan binding behaviors. Our motif analysis was performed by integrating 68 manually defined glycan features with systematic probing of computational rules for significant binding motifs using mono- and disaccharides and linkages. Combining machine learning with manual annotation, we create a detailed interpretation of glycan-binding specificity for 57 unique lectins, categorized by their major binding motifs: mannose, complex-type N-glycan, O-glycan, fucose, sialic acid and sulfate, GlcNAc and chitin, Gal and LacNAc, and GalNAc. Our work provides fresh insights into the complex binding features of commercially available lectins in current use, providing a critical guide to these important reagents.