N-Glycosylation can selectively block or foster different receptor-ligand binding modes

Surface plasmon resonance microscopy identifies glycan heterogeneity in pancreatic cancer cells that influences mucin-4 binding interactions

Membrane proteins are the main targets of therapeutic drugs and most of them are glycosylated. Glycans play pivotal roles in several biological processes, and glycosylation changes are a well-established hallmark of several types of cancer, including pancreatic cancer, that contribute to tumor growth. Mucin-4 (MUC-4) is a membrane glycoprotein which is associated with pancreatic cancer and metastasis, and it has been targeted as a promising vaccine candidate. In this study, Surface Plasmon Resonance Microscopy (SPRM) was implemented to study complex influences of the native N-glycan cellular environment on binding interactions to the MUC-4 receptor as this is currently the only commercially available label-free technique with high enough sensitivity and resolution to measure binding kinetics and heterogeneity on single cells. Such unique capability enables for a more accurate understanding of the "true" binding interactions on human cancer cells without disrupting the native environment of the target MUC-4 receptor. Removal of N-linked glycans in pancreatic cancer cells using PNGase F exposed heterogeneity in Concanavalin (Con A) binding by revealing three new binding populations with higher affinities than the glycosylated control cells. Anti-MUC-4 binding interactions of enzymatically N-linked deglycosylated pancreatic cancer cells produced a 25x faster association and 37x higher affinity relative to the glycosylated control cells. Lastly, four interaction modes were observed for Helix Pomatia Agglutinin (HPA) binding to the glycosylated control cells, but shifted and increased in activity upon removal of N-linked glycans. These results identified predominant interaction modes of glycan and MUC-4 in pancreatic cancer cells, the kinetics of their binding interactions were quantified, and the influence of N-linked glycans in MUC-4 binding interactions was revealed.

CD44: a cancer stem cell marker and therapeutic target in leukemia treatment

CD44 is a ubiquitous leukocyte adhesion molecule involved in cell-cell interaction, cell adhesion, migration, homing and differentiation. CD44 can mediate the interaction between leukemic stem cells and the surrounding extracellular matrix, thereby inducing a cascade of signaling pathways to regulate their various behaviors. In this review, we focus on the impact of CD44s/CD44v as biomarkers in leukemia development and discuss the current research and prospects for CD44-related interventions in clinical application.

Metabolism-driven glycosylation represents therapeutic opportunities in interstitial lung diseases

Metabolic changes are coupled with alteration in protein glycosylation. In this review, we will focus on macrophages that are pivotal in the pathogenesis of pulmonary fibrosis and sarcoidosis and thanks to their adaptable metabolism are an attractive therapeutic target. Examples presented in this review demonstrate that protein glycosylation regulates metabolism-driven immune responses in macrophages, with implications for fibrotic processes and granuloma formation. Targeting proteins that regulate glycosylation, such as fucosyltransferases, neuraminidase 1 and chitinase 1 could effectively block immunometabolic changes driving inflammation and fibrosis, providing novel avenues for therapeutic interventions.

Hyaluronan-arginine enhanced and dynamic interaction emerges from distinctive molecular signature due to electrostatics and side-chain specificity

Hyaluronan is a natural carbohydrate polymer with a negative charge that fosters gel-like conditions crucial for its cellular functions and industrial applications. As a recognized ligand for proteins, understanding their mutual interactions provides solid ground to tune hyaluronan's gel properties using biocompatible peptides. This work employs NMR and molecular dynamics simulations to identify molecular motifs relevant to hyaluronan-peptide interactions using arginine, lysine, and glycine oligopeptides. Arginine-rich peptides exhibit the strongest binding to hyaluronan according to chemical shift perturbation measurements, followed distantly by the similarly charged lysine. This difference highlights the significance of electrostatics and the peculiarities of the guanidinium side chain in arginine, capable of non-polar interactions that further stabilize the binding. Additional nuclear Overhauser effect measurements do not show stable interaction partners, precluding strong and well-defined complexes. Finally, molecular simulations support our findings and show an extended but significant interaction region, especially for arginine, responsible for the observed enhanced binding, which can also promote cross-linking of hyaluronan polymers. Our findings pave the way for optimizing biocompatible peptides to alter hyaluronan gels' properties efficiently and also explain why hyaluronan-protein interaction typically involves positively charged arginine-rich regions also capable of forming hydrogen bonds and non-polar interactions.

Multiple circulating forms of neprilysin detected with novel epitope-directed monoclonal antibodies

Neprilysin (NEP) is an emerging biomarker for various diseases including heart failure (HF). However, major inter-assay inconsistency in the reported concentrations of circulating NEP and uncertainty with respect to its correlations with type and severity of disease are in part attributed to poorly characterized antibodies supplied in commercial ELISA kits. Validated antibodies with well-defined binding footprints are critical for understanding the biological and clinical context of NEP immunoassay data. To achieve this, we applied in silico epitope prediction and rational peptide selection to generate monoclonal antibodies (mAbs) against spatially distant sites on NEP. One of the selected epitopes contained published N-linked glycosylation sites at N285 and N294. The best antibody pair, mAb 17E11 and 31E1 (glycosylation-sensitive), were characterized by surface plasmon resonance, isotyping, epitope mapping, and western blotting. A validated two-site sandwich NEP ELISA with a limit of detection of 2.15 pg/ml and working range of 13.1-8000 pg/ml was developed with these mAbs. Western analysis using a validated commercial polyclonal antibody (PE pAb) and our mAbs revealed that non-HF and HF plasma NEP circulates as a heterogenous mix of moieties that possibly reflect proteolytic processing, post-translational modifications and homo-dimerization. Both our mAbs detected a ~ 33 kDa NEP fragment which was not apparent with PE pAb, as well as a common ~ 57-60 kDa moiety. These antibodies exhibit different affinities for the various NEP targets. Immunoassay results are dependent on NEP epitopes variably detected by the antibody pairs used, explaining the current discordant NEP measurements derived from different ELISA kits.

Cancer-specific glycosylation of CD13 impacts its detection and activity in preclinical cancer tissues

Harnessing the differences between cancer and non-cancer tissues presents new opportunities for selective targeting by anti-cancer drugs. CD13, a heavily glycosylated protein, is one example with significant unmet clinical potential in cancer drug discovery. Despite its high expression and activity in cancers, CD13 is also expressed in many normal tissues. Here, we report differential tissue glycosylation of CD13 across tissues and demonstrate for the first time that the nature and pattern of glycosylation of CD13 in preclinical cancer tissues are distinct compared to normal tissues. We identify cancer-specific O-glycosylation of CD13, which selectively blocks its detection in cancer models but not in normal tissues. In addition, the metabolism activity of cancer-expressed CD13 was observed to be critically dependent on its unique glycosylation. Thus, our data demonstrate the existence of discrete cancer-specific CD13 glycoforms and propose cancer-specific CD13 glycoforms as a clinically useful target for effective cancer-targeted therapy.

The role of N-glycosylation modification in the pathogenesis of liver cancer

N-glycosylation is one of the most common types of protein modifications and it plays a vital role in normal physiological processes. However, aberrant N-glycan modifications are closely associated with the pathogenesis of diverse diseases, including processes such as malignant transformation and tumor progression. It is known that the N-glycan conformation of the associated glycoproteins is altered during different stages of hepatocarcinogenesis. Characterizing the heterogeneity and biological functions of glycans in liver cancer patients will facilitate a deeper understanding of the molecular mechanisms of liver injury and hepatocarcinogenesis. In this article, we review the role of N-glycosylation in hepatocarcinogenesis, focusing on epithelial-mesenchymal transition, extracellular matrix changes, and tumor microenvironment formation. We highlight the role of N-glycosylation in the pathogenesis of liver cancer and its potential applications in the treatment or diagnosis of liver cancer.

CD44 Glycosylation as a Therapeutic Target in Oncology

The interaction of non-kinase transmembrane glycoprotein CD44 with ligands including hyaluronic acid (HA) is closely related to the occurrence and development of tumors. Changes in CD44 glycosylation can regulate its binding to HA, Siglec-15, fibronectin, TM4SF5, PRG4, FGF2, collagen and podoplanin and activate or inhibit c-Src/STAT3/Twist1/Bmi1, PI3K/AKT/mTOR, ERK/NF-κB/NANOG and other signaling pathways, thereby having a profound impact on the tumor microenvironment and tumor cell fate. However, the glycosylation of CD44 is complex and largely unknown, and the current understanding of how CD44 glycosylation affects tumors is limited. These issues must be addressed before targeted CD44 glycosylation can be applied to treat human cancers.

Efficiently Computing NMR 1H and 13C Chemical Shifts of Saccharides in Aqueous Environment

Determining the structure of saccharides in their native environment is crucial to understanding their function and more accurately targeting their utilization. Nuclear magnetic resonance observables such as the nuclear Overhauser effect or spin-spin coupling constants are routinely utilized to study saccharides in their native water environment. However, while highly sensitive to the local environment, chemical shifts are mostly overlooked, despite being commonly measured for compounds identification. Although chemical shifts carry considerable structural information, their direct association with structure is notoriously difficult. This is mostly due to the similarity in the chemical nature of most saccharides causing similar physicochemical environments close to sugar C and H atoms, resulting in comparable chemical shifts. The rise of computational power allows one to compute reliable chemical shifts and use them to determine atomistic details of these sugars in solution. However, any prediction is severely limited by the computational protocol used and its accuracy. In this work, we studied a set of 31 saccharides on which we evaluated various computational protocols to calculate the total number of 375 ¹H and 327 ¹³C chemical shifts of sugars in an aqueous environment. Our study proposes two cost-effective protocols for simulating ¹H and ¹³C chemical shifts that we recommend for further use. These protocols can help with the interpretation of experimental spectra, but we also show that they are also capable of structure prediction independently. This is possible because of the low mean absolute deviations of calculated shifts from the experiment (0.06 ppm for ¹H and 1.09 ppm for ¹³C). We explore different solvation methods, basis sets, and optimization schemes to reach such accuracy. A correct sampling of the conformation phase space of flexible sugar molecules is also key to obtaining accurately converged theoretical chemical shifts. The linear regression method was applied to convert the calculated isotropic nuclear magnetic shielding constants to simulated chemical shifts comparable with the experiment. The achieved level of accuracy can help in utilizing chemical shifts for elucidating the 3D atomistic structure of saccharides in aqueous solutions. All linear regression parameters obtained on our extensive set of sugars for all the tested protocols can be reutilized in future works.

Role of CD44 isoforms in epithelial-mesenchymal plasticity and metastasis

Cellular plasticity lies at the core of cancer progression, metastasis, and resistance to treatment. Stemness and epithelial-mesenchymal plasticity in cancer are concepts that represent a cancer cell's ability to coopt and adapt normal developmental programs to promote survival and expansion. The cancer stem cell model states that a small subset of cancer cells with stem cell-like properties are responsible for driving tumorigenesis and metastasis while remaining especially resistant to common chemotherapeutic drugs. Epithelial-mesenchymal plasticity describes a cancer cell's ability to transition between epithelial and mesenchymal phenotypes which drives invasion and metastasis. Recent research supports the existence of stable epithelial/mesenchymal hybrid phenotypes which represent highly plastic states with cancer stem cell characteristics. The cell adhesion molecule CD44 is a widely accepted marker for cancer stem cells, and it lies at a functional intersection between signaling networks regulating both stemness and epithelial-mesenchymal plasticity. CD44 expression is complex, with alternative splicing producing many isoforms. Interestingly, not only does the pattern of isoform expression change during transitions between epithelial and mesenchymal phenotypes in cancer, but these isoforms have distinct effects on cell behavior including the promotion of metastasis and stemness. The role of CD44 both downstream and upstream of signaling pathways regulating epithelial-mesenchymal plasticity and stemness make this protein a valuable target for further research and therapeutic intervention.

Comparison of self-sampling blood collection for N-glycosylation analysis

Objective

Self-sampling of capillary blood provides easier sample collection, handling, and shipping compared to more invasive blood sampling via venepuncture. Recently, other means of capillary blood collection were introduced to the market, such as Neoteryx sticks and Noviplex cards. We tested the comparability of these two self-sampling methods, alongside dried blood spots (DBS), with plasma acquired from venepunctured blood in N-glycoprofiling of total proteins. We have also tested the intra-day repeatability of the three mentioned self-sampling methods. Capillary blood collection with Neoteryx, Noviplex and DBS was done following the manufacturers’ instructions and N-glycoprofiling of released, fluorescently labelled N-glycans was performed with ultra-performance liquid chromatography.

Results

Comparability with plasma was assessed by calculating the relative deviance, which was 0.674 for DBS, 0.092 for Neoteryx sticks, and 0.069 for Noviplex cards. In repeatability testing, similar results were obtained, with Noviplex cards and Neoteryx sticks performing substantially better than DBS (CVs = 4.831% and 7.098%, compared to 14.305%, respectively). Our preliminary study on the use of Neoteryx and Noviplex self-sampling devices in glycoanalysis demonstrates their satisfactory performance in both the comparability and repeatability testing, however, they should be further tested in larger collaborations and cohorts.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-022-05958-9.

Use of Raman and Raman optical activity to extract atomistic details of saccharides in aqueous solution

Sugars are crucial components in biosystems and industrial applications. In aqueous environments, the natural state of short saccharides or charged glycosaminoglycans is floating and wiggling in solution. Therefore, tools to characterize their structure in a native aqueous environment are crucial but not always available. Here, we show that a combination of Raman/ROA and, on occasions, NMR experiments with Molecular Dynamics (MD) and Quantum Mechanics (QM) is a viable method to gain insights into structural features of sugars in solutions. Combining these methods provides information about accessible ring puckering conformers and their proportions. It also provides information about the conformation of the linkage between the sugar monomers, i.e., glycosidic bonds, allowing for identifying significantly accessible conformers and their relative abundance. For mixtures of sugar moieties, this method enables the deconvolution of the Raman/ROA spectra to find the actual amounts of its molecular constituents, serving as an effective analytical technique. For example, it allows calculating anomeric ratios for reducing sugars and analyzing more complex sugar mixtures to elucidate their real content. Altogether, we show that combining Raman/ROA spectroscopies with simulations is a versatile method applicable to saccharides. It allows for accessing many features with precision comparable to other methods routinely used for this task, making it a viable alternative. Furthermore, we prove that the proposed technique can scale up by studying the complicated raffinose trisaccharide, and therefore, we expect its wide adoption to characterize sugar structural features in solution.

SARS-CoV-2 spike binding to ACE2 is stronger and longer ranged due to glycan interaction

Highly detailed steered molecular dynamics simulations are performed on differently glycosylated receptor binding domains of the severe acute respiratory syndrome coronavirus-2 spike protein. The binding strength and the binding range increase with glycosylation. The interaction energy rises very quickly when pulling the proteins apart and only slowly drops at larger distances. We see a catch-slip-type behavior whereby interactions during pulling break and are taken over by new interactions forming. The dominant interaction mode is hydrogen bonds, but Lennard-Jones and electrostatic interactions are relevant as well.