IgE glycosylation and impact on structure and function: A systematic review.

The impact of human IgE glycosylation on structure, function and disease mechanisms is not fully elucidated, and heterogeneity in different studies renders drawing conclusions challenging. Previous reviews discussed IgE glycosylation focusing on specific topics such as health versus disease, FcεR binding or impact on function. We present the first systematic review of human IgE glycosylation conducted utilizing the PRISMA guidelines. We sought to define the current consensus concerning the roles of glycosylation on structure, biology and disease. Despite diverse analytical methodologies, source, expression systems and the sparsity of data on IgE antibodies from non-allergic individuals, collectively evidence suggests differential glycosylation profiles, particularly in allergic diseases compared with healthy states, and indicates functional impact, and contributions to IgE-mediated hypersensitivities and atopic diseases. Beyond allergic diseases, dysregulated terminal glycan structures, including sialic acid, may regulate IgE metabolism. Glycan sites such as N394 may contribute to stabilizing IgE structure, with alterations in these glycans likely influencing both structure and IgE-FcεR interactions. This systematic review therefore highlights critical IgE glycosylation attributes in health and disease that may be exploitable for therapeutic intervention, and the need for novel analytics to explore pertinent research avenues.

Erythropoietin N-glycosylation of Therapeutic Formulations Quantified and Characterized: An Interlab Comparability Study of High-Throughput Methods.

Recombinant human erythropoietin (EPO) is a biopharmaceutical frequently used in the treatment of anemia. It is a heavily glycosylated protein with a diverse and complex glycome. EPO N-glycosylation influences important pharmacological parameters, prominently serum half-life. Therefore, EPO N-glycosylation analysis is of the utmost importance in terms of controlling critical quality attributes. In this work, we performed an interlaboratory study of glycoanalytical techniques for profiling and in-depth characterization, namely (1) hydrophilic interaction liquid chromatography with fluorescence detection after 2-aminobenzamide labeling (HILIC-FLD(2AB)) and optional weak anion exchange chromatography (WAX) fractionation and exoglycosidase digestion, (2) HILIC-FLD after procainamide labeling (PROC) optionally coupled to electrospray ionization-MS and (3) matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-MS). All techniques showed good precision and were able to differentiate the unique N-glycosylation profiles of the various EPO preparations. HILIC-FLD showed higher precision, while MALDI-TOF-MS covered the most analytes. However, HILIC-FLD differentiated isomeric N-glycans, i.e., N-acetyllactosamine repeats and O-acetylation regioisomers. For routine profiling, HILIC-FLD methods are more accessible and cover isomerism in major structures, while MALDI-MS covers more minor analytes with an attractively high throughput. For in-depth characterization, MALDI-MS and HILIC-FLD(2AB)/WAX give a similar amount of orthogonal information. HILIC-FLD(PROC)-MS is attractive for covering isomerism of major structures with a significantly less extensive workflow compared to HILIC-FLD(2AB)/WAX.

Protocols for isolation and characterization of nanoparticle biomolecular corona complexes.

Engineered nanoparticles (NPs) pose a broad spectrum of interesting properties that make them useful for many applications. However, continuous exposure to NPs requires the need to deeply understand the outcomes when these NPs interact with different biological environments. After exposure within (to) these environments, the pristine surfaces of NPs strongly interact with the molecules from the surrounding medium, including metabolites, lipids, glycan, and proteins, forming the so-called protein corona (PC). It is well established that the NP-PC strongly influences the biological fate of various NPs types, including cellular uptake, toxicity, and biodistribution. Thus, for a proper assessment of potential hazards associated with engineered NPs, it is mandatory to study and evaluate the PC that forms around NPs. Herein, we describe protocols in detail for the isolation and characterization of NP-PC complexes and cover the following aspects: 1) isolation protocols for different nanomaterials in a range of exposing media, including magnetic isolation methods for superparamagnetic NPs, 2) NP physico-chemical characterization using advanced and standard techniques available in regular laboratories, and 3) NP- PC characterization of the protein and glycan components.

Exploring the sequence-function space of microbial fucosidases.

Microbial α-L-fucosidases catalyse the hydrolysis of terminal α-L-fucosidic linkages and can perform transglycosylation reactions. Based on sequence identity, α-L-fucosidases are classified in glycoside hydrolases (GHs) families of the carbohydrate-active enzyme database. Here we explored the sequence-function space of GH29 fucosidases. Based on sequence similarity network (SSN) analyses, 15 GH29 α-L-fucosidases were selected for functional characterisation. HPAEC-PAD and LC-FD-MS/MS analyses revealed substrate and linkage specificities for α1,2, α1,3, α1,4 and α1,6 linked fucosylated oligosaccharides and glycoconjugates, consistent with their SSN clustering. The structural basis for the substrate specificity of GH29 fucosidase from Bifidobacterium asteroides towards α1,6 linkages and FA2G2 N-glycan was determined by X-ray crystallography and STD NMR. The capacity of GH29 fucosidases to carry out transfucosylation reactions with GlcNAc and 3FN as acceptors was evaluated by TLC combined with ESI-MS and NMR. These experimental data supported the use of SSN to further explore the GH29 sequence-function space through machine-learning models. Our lightweight protein language models could accurately allocate test sequences in their respective SSN clusters and assign 34,258 non-redundant GH29 sequences into SSN clusters. It is expected that the combination of these computational approaches will be used in the future for the identification of novel GHs with desired specificities.