Microarray analyses of closely related glycoforms reveal different accessibilities of glycan determinants on N-glycan branches

Enzymatic modular synthesis of asymmetrically branched human milk oligosaccharides

Human milk oligosaccharides (HMOs) are intricate glycans that promote healthy growth of infants and have been incorporated into infant formula as food additives. Despite their importance, the limited availability of asymmetrically branched HMOs hinders the exploration of their structure and function relationships. Herein, we report an enzymatic modular strategy for the efficient synthesis of these HMOs. The key branching enzyme for the assembly of branched HMOs, human β1,6-N-acetylglucosaminyltransferase 2 (GCNT2), was successfully expressed in Pichia pastoris for the first time. Then, it was integrated with six other bacterial glycosyltransferases to establish seven glycosylation modules. Each module comprises a one-pot multi-enzyme (OPME) system for in-situ generation of costly sugar nucleotide donors, combined with a glycosyltransferase for specific glycosylation. This approach enabled the synthesis of 31 branched HMOs and 13 linear HMOs in a stepwise manner with well-programmed synthetic routes. The binding details of these HMOs with related glycan-binding proteins were subsequently elucidated using glycan microarray assays to provide insights into their biological functions. This comprehensive collection of synthetic HMOs not only serves as standards for HMOs structure identification in complex biological samples but also significantly enhances the fields of HMOs glycomics, opening new avenues for biomedical applications.

Syntactic sugars: crafting a regular expression framework for glycan structures

Motivation

Structural analysis of glycans poses significant challenges in glycobiology due to their complex sequences. Research questions such as analyzing the sequence content of the α1-6 branch in N-glycans, are biologically meaningful yet can be hard to automate.

Results

Here, we introduce a regular expression system, designed for glycans, feature-complete, and closely aligned with regular expression formatting. We use this to annotate glycan motifs of arbitrary complexity, perform differential expression analysis on designated sequence stretches, or elucidate branch-specific binding specificities of lectins in an automated manner. We are confident that glycan regular expressions will empower computational analyses of these sequences.

Availability and implementation

Our regular expression framework for glycans is implemented in Python and is incorporated into the open-source glycowork package (version 1.1+). Code and documentation are available at https://github.com/BojarLab/glycowork/blob/master/glycowork/motif/regex.py.

Computational insights into the circular permutation roles on ConA binding and structural stability

The mechanisms behind Concanavalin A (ConA) circular permutation have been under investigation since 1985. Although a vast amount of information is available about this lectin and its applications, the exact purpose of its processing remains unclear. To shed light on this, this study employed computer simulations to compare the unprocessed ProConA with the mature ConA. This approach aimed to reveal the importance of the post-translational modifications, especially how they affect the lectin stability and carbohydrate-binding properties. To achieve these goals, we conducted 200 ns molecular dynamics simulations and trajectory analyses on the monomeric forms of ProConA and ConA (both unbound and in complex with D-mannose and the GlcNAc2Man9 N-glycan), as well as on their oligomeric forms. Our findings reveal significant stability differences between ProConA and ConA at both the monomeric and tetrameric levels, with ProConA exhibiting consistently lower stability parameters compared to ConA. In terms of carbohydrate binding properties, however, both lectins showed remarkable similarities in their interaction profiles, contact numbers, and binding free energies with D-mannose and the high-mannose N-glycan. Overall, our results suggest that the processing of ProConA significantly enhances the stability of the mature lectin, especially in maintaining the tetrameric oligomer, without substantially affecting its carbohydrate-binding properties.

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

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

A Versatile Urea Type Linker for Functionalizing Natural Glycans and Its Validation in Glycan Arrays

The isolation from organisms and readily available glycoproteins has become an increasingly convenient source of N-glycans for multiple applications including glycan microarrays, as reference standards in glycan analysis or as reagents that improve bioavailability of protein and peptide therapeutics through conjugation. A problematic step in the isolation process on a preparative scale can be the attachment of a linker for the improved purification, separation, immobilization and quantification of the glycan structures. Addressing this issue, we firstly aimed for the development of an UV active linker for a fast and reliable attachment to anomeric glycosylamines via urea bond formation. Secondly, we validated the new linker on glycan arrays in a comparative study with a collection of N-glycans which were screened against various lectins. In total, we coupled four structurally varied N-glycans to four different linkers, immobilized all constructs on a microarray and compared their binding affinities to four plant and fungal lectins of widely described specificity. Our study shows that the urea type linker showed an overall superior performance for lectin binding and once more, highlights the often neglected influence of the choice of linker on lectin recognition.

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 (K_d) 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 K_d 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.

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.

Immobilization of Biantennary N-Glycans Leads to Branch Specific Epitope Recognition by LSECtin

The molecular recognition features of LSECtin toward asymmetric N-glycans have been scrutinized by NMR and compared to those occurring in glycan microarrays. A pair of positional glycan isomers (LDN3 and LDN6), a nonelongated GlcNAc4Man3 N-glycan (G0), and the minimum binding epitope (the GlcNAcβ1-2Man disaccharide) have been used to shed light on the preferred binding modes under both experimental conditions. Strikingly, both asymmetric LDN3 and LDN6 N-glycans are recognized by LSECtin with similar affinities in solution, in sharp contrast to the results obtained when those glycans are presented on microarrays, where only LDN6 was efficiently recognized by the lectin. Thus, different results can be obtained using different experimental approaches, pointing out the tremendous difficulty of translating in vitro results to the in vivo environment.

Systematic synthesis of bisected N-glycans and unique recognitions by glycan-binding proteins

Bisected N-glycans represent a unique class of protein N-glycans that play critical roles in many biological processes. Herein, we describe the systematic synthesis of these structures. A bisected N-glycan hexasaccharide was chemically assembled with two orthogonal protecting groups attached at the C2 of the branching mannose residues, followed by sequential installation of GlcNAc and LacNAc building blocks to afford two asymmetric bisecting "cores". Subsequent enzymatic modular extension of the "cores" yielded a comprehensive library of biantennary N-glycans containing the bisecting GlcNAc and presenting 6 common glycan determinants in a combinatorial fashion. These bisected N-glycans and their non-bisected counterparts were used to construct a distinctive glycan microarray to study their recognition by a wide variety of glycan-binding proteins (GBPs), including plant lectins, animal lectins, and influenza A virus hemagglutinins. Significantly, the bisecting GlcNAc could bestow (PHA-L, rDCIR2), enhance (PHA-E), or abolish (ConA, GNL, anti-CD15s antibody, etc.) N-glycan recognition of specific GBPs, and is tolerated by many others. In summary, synthesized compounds and the unique glycan microarray provide ideal standards and tools for glycoanalysis and functional glycomic studies. The microarray data provide new information regarding the fine details of N-glycan recognition by GBPs, and in turn improve their applications.

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.

OUP accepted manuscript

Glycan arrays continue to be the primary resource for determining the glycan-binding specificity of proteins. The volume and diversity of glycan-array data are increasing, but no common method and resource exist to analyze, integrate, and use the available data. To meet this need, we developed a resource of analyzed glycan-array data called CarboGrove. Using the ability to process and interpret data from any type of glycan array, we populated the database with the results from 35 types of glycan arrays, 13 glycan families, 5 experimental methods, and 19 laboratories or companies. In meta-analyses of glycan-binding proteins, we observed glycan-binding specificities that were not uncovered from single sources. In addition, we confirmed the ability to efficiently optimize selections of glycan-binding proteins to be used in experiments for discriminating between closely related motifs. Through descriptive reports and a programmatically accessible Application Programming Interface, CarboGrove yields unprecedented access to the wealth of glycan-array data being produced and powerful capabilities for both experimentalists and bioinformaticians.

Chemical Synthesis of Sialyl N-Glycans and Analysis of Their Recognition by Neuraminidase

The chemical synthesis of a fully sialylated tetraantennary N-glycan has been achieved for the first time by using the diacetyl strategy, in which NHAc is protected as NAc₂ to improve reactivity by preventing intermolecular hydrogen bonds. Another key was the glycosylation to the branched mannose in an ether solvent, which promoted the desired glycosylation by stabilizing the oxocarbenium ion intermediate. Furthermore, high α-selectivity of these glycosylation reactions was realized by utilizing remote participation. Two asymmetrically deuterium labeled sialyl N-glycans were also synthesized by the same strategy. The synthesized N-glycans were used to probe the molecular basis of H1N1 neuraminidase recognition. The asymmetrically deuterated N-glycans revealed a difference in the recognition of sialic acid on each branch. Meanwhile, the tetraantennary N-glycan was used to evaluate the effects of multivalency and steric hinderance by forming branching structures.

Combined Analysis of Multiple Glycan-Array Datasets: New Explorations of Protein-Glycan Interactions

Glycan arrays are indispensable for learning about the specificities of glycan-binding proteins. Despite the abundance of available data, the current analysis methods do not have the ability to interpret and use the variety of data types and to integrate information across datasets. Here, we evaluated whether a novel, automated algorithm for glycan-array analysis could meet that need. We developed a regression-tree algorithm with simultaneous motif optimization and packaged it in software called MotifFinder. We applied the software to analyze data from eight different glycan-array platforms with widely divergent characteristics and observed an accurate analysis of each dataset. We then evaluated the feasibility and value of the combined analyses of multiple datasets. In an integrated analysis of datasets covering multiple lectin concentrations, the software determined approximate binding constants for distinct motifs and identified major differences between the motifs that were not apparent from single-concentration analyses. Furthermore, an integrated analysis of data sources with complementary sets of glycans produced broader views of lectin specificity than produced by the analysis of just one data source. MotifFinder, therefore, enables the optimal use of the expanding resource of the glycan-array data and promises to advance the studies of protein-glycan interactions.

Terminal Epitope-Dependent Branch Preference of Siglecs Toward N-Glycans

Siglecs are sialic acid–binding immunoglobulin-like lectins that play vital roles in immune cell signaling. Siglecs help the immune system distinguish between self and nonself through the recognition of glycan ligands. While the primary binding specificities of Siglecs are known to be divergent, their specificities for complex glycans remain unclear. Herein, we determined N-glycan binding profiles of a set of Siglecs by using a complex asymmetric N-glycan microarray. Our results showed that Siglecs had unique terminal epitope-dependent branch preference when recognizing asymmetric N-glycans. Specifically, human Siglec-3, -9, and -10 prefer the α1-3 branch when Siaα2-6Galβ1-4GlcNAc terminal epitope serves as the binding ligand but prefer the opposite α1-6 branch when Siaα2-3Galβ1-4GlcNAc epitope serves as the ligand. Interestingly, Siglec-10 exhibited dramatic binding divergence toward a pair of Neu5Ac-containing asymmetric N-glycan isomers, as well as their Neu5Gc-containing counterparts. This new information on complex glycan recognition by Siglecs provides insights into their biological roles and applications.

Recent Advances in the Chemical Biology of N-Glycans

Asparagine-linked N-glycans on proteins have diverse structures, and their functions vary according to their structures. In recent years, it has become possible to obtain high quantities of N-glycans via isolation and chemical/enzymatic/chemoenzymatic synthesis. This has allowed for progress in the elucidation of N-glycan functions at the molecular level. Interaction analyses with lectins by glycan arrays or nuclear magnetic resonance (NMR) using various N-glycans have revealed the molecular basis for the recognition of complex structures of N-glycans. Preparation of proteins modified with homogeneous N-glycans revealed the influence of N-glycan modifications on protein functions. Furthermore, N-glycans have potential applications in drug development. This review discusses recent advances in the chemical biology of N-glycans.

Mass Spectrometry-Based Shotgun Glycomics for Discovery of Natural Ligands of Glycan-Binding Proteins

Glycans attached to lipids and membrane-bound and secreted proteins and peptides mediate many important physiological and pathophysiological processes through interactions with glycan-binding proteins (GBPs). However, uncovering functional glycan ligands is challenging due to the large number of naturally occurring glycan structures, the limited availability of glycans in their purified form, the low affinities of GBP-glycan interactions, and limitations in existing binding assays. This work explores the application of catch-and-release electrospray ionization mass spectrometry (CaR-ESI-MS) for screening libraries of N-glycans derived from natural sources. The assay was tested by screening a small-defined library of complex N-glycans at equimolar concentrations against plant and human GBPs with known specificities for either α2-3- or α2-6-linked sialosides, with affinities in the millimolar to micromolar range. Validation experiments, performed in negative ion mode, revealed that bound N-glycan ligands are readily released, as intact deprotonated ions, from GBPs in the gas phase using collision-induced dissociation. Moreover, the relative abundances of the released ligands closely match their solution affinities. The results obtained for a natural N-glycan library produced from cultured immune cells serve to highlight the ease with which CaR-ESI-MS can screen complex mixtures of N-glycans for interactions. Additionally, scaling the relative abundances of released glycan ligands according to their relative abundances in solution, as determined by hydrophilic interaction-ultrahigh-performance liquid chromatography of the fluorescently labeled library, allows the relative affinities of glycan ligands to be ranked.

Synthesis of Asymmetric N-Glycans as Common Core Substrates for Structural Diversification through Selective Enzymatic Glycosylation

N-glycans on the cell surface provide distinct signatures that are recognized by different glycan-binding proteins (GBPs) and pathogens. Most glycans in humans are asymmetric and isomeric, yet their biological functions are not well understood due to their lack of availability for studies. In this work, we have developed an improved strategy for asymmetric N-glycan assembly and diversification using designed common core substrates prepared chemically for selective enzymatic fucosylation and sialylation. The resulting 26 well-defined glycans that carry the sialic acid residue on different antennae were used in a microarray as a representative application to profile the binding specificity of hemagglutinin (HA) from the avian influenza virus (H5N2). We found distinct binding affinity for the Neu5Ac-Gal epitope linked to the N-acetylglucosamine (GlcNAc) of different branches and only a minor effect in binding for the terminal galactose on different branches. Overall, the microarray analysis showed branch-biased and context-based recognition patterns.