Analysis of Native and Permethylated N-Glycan Isomers Using MGC-LC-MS Techniques.

Glycosylation is an important post-translational modification that affects many critical cellular functions such as adhesion, signaling, protein stability, and function, among others. Abnormal glycosylation has been linked to many diseases. As such, the investigation of glycans and their roles in disease pathway and progression is important. Glycan analysis can be challenging, however, due to such factors as the heterogeneity of glycans and isomers as well as the poor ionization efficiency provided by mass spectrometry analyses. This chapter presents efficient methods that overcome these and other challenges for the analysis of native and permethylated N-glycan isomers in biological samples. Instructions regarding the packing of the MGC column, the N-glycan sample prep, and the LC-MS conditions are also provided.

LC-MS/MS Quantitation of HILIC-Enriched N-glycopeptides Derived from Low-Abundance Serum Glycoproteins in Patients with Narcolepsy Type 1.

Glycoproteomic analysis is always challenging because of low abundance and complex site-specific heterogeneity. Glycoproteins are involved in various biological processes such as cell signaling, adhesion, and cell-cell communication and may serve as potential biomarkers when analyzing different diseases. Here, we investigate glycoproteins in narcolepsy type 1 (NT1) disease, a form of narcolepsy characterized by cataplexy-the sudden onset of muscle paralysis that is typically triggered by intense emotions. In this study, 27 human blood serum samples were analyzed, 16 from NT1 patients and 11 from healthy individuals serving as controls. We quantified hydrophilic interaction liquid chromatography (HILIC)-enriched glycopeptides from low-abundance serum samples of controls and NT1 patients via LC-MS/MS. Twenty-eight unique N-glycopeptides showed significant changes between the two studied groups. The sialylated N-glycopeptide structures LPTQNITFQTESSVAEQEAEFQSPK HexNAc6, Hex3, Neu5Ac2 (derived from the ITIH4 protein) and the structure IVLDPSGSMNIYLVLDGSDSIGASNFTGAK HexNAc5, Hex4, Fuc1 (derived from the CFB protein), with p values of 0.008 and 0.01, respectively, were elevated in NT1 samples compared with controls. In addition, the N-glycopeptide protein sources Ceruloplasmin, Complement factor B, and ITH4 were observed to play an important role in the complement activation and acute-phase response signaling pathways. This may explain the possible association between the biomarkers and pathophysiological effects.

N-Glycome Profile of the Spike Protein S1: Systemic and Comparative Analysis from Eleven Variants of SARS-CoV-2.

The SARS-CoV-2 virus rapidly spread worldwide, threatening public health. Since it emerged, the scientific community has been engaged in the development of effective therapeutics and vaccines. The subunit S1 in the spike protein of SARS-CoV-2 mediates the viral entry into the host and is therefore one of the major research targets. The S1 protein is extensively glycosylated, and there is compelling evidence that glycans protect the virus' active site from the human defense system. Therefore, investigation of the S1 protein glycome alterations in the different virus variants will provide a view of the glycan evolution and its relationship with the virus pathogenesis. In this study, we explored the N-glycosylation expression of the S1 protein for eleven SARS-CoV-2 variants: five variants of concern (VOC), including alpha, beta, gamma, delta, and omicron, and six variants of interest (VOI), including epsilon, eta, iota, lambda, kappa, and mu. The results showed significant differences in the N-glycome abundance of all variants. The N-glycome of the VOC showed a large increase in the abundance of sialofucosylated glycans, with the greatest abundance in the omicron variant. In contrast, the results showed a large abundance of fucosylated glycans for most of the VOI. Two glycan compositions, GlcNAc4,Hex5,Fuc,NeuAc (4-5-1-1) and GlcNAc6,Hex8,Fuc,NeuAc (6-8-1-1), were the most abundant structures across all variants. We believe that our data will contribute to understanding the S1 protein's structural differences between SARS-CoV-2 mutations.